Journal articles: 'Variant calling, whole exome sequencing, database'

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Bryant, Dean, Will Tapper, Nicola J. Weston-Bell, Arnold Bolomsky, Li Song, Shengtao Xu, Andrew R. Collins, Niklas Zojer, and Surinder Singh Sahota. "Single Cell Whole Exome Sequencing in an Index Case of Amp1q21 Multiple Myeloma to Define Intraclonal Variation." Blood 128, no. 22 (December 2, 2016): 5651. http://dx.doi.org/10.1182/blood.v128.22.5651.5651.

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Abstract Introduction Multiple myeloma (MM) is a largely incurable plasma cell malignancy characterised by marked genomic heterogeneity, in which chromosome 1q21 amplification (amp1q21) associates with poor prognosis. Genomic analysis using next generation sequencing has identified recurrent mutations, but no universal acquired somatic mutation(s) have emerged in MM, suggesting that understanding pathways of survival will require analysis of individual tumours in distinct disease subsets. To compound complexity of the problem, intraclonal variation (ICV), known as a major driver mechanism in cancer plasticity, in which clonal competitor cells undergo selection during disease evolution and progression by Darwinian principles, will need to be fully mapped at the genome level. Identifying the true level of ICV in a tumour will thus require analysis at the level of whole exome sequencing (WES) in single cells (SCs). In this study, we sought to establish WES methodology able to identify ICV in SCs in an index case of amp1q21 MM. Methods Cell selection and sequencing CD138+ tumour cells and CD3+ T-cells were isolated from a presentation case of amp1q21 MM as bulk populations to high purity (>97%). Single MM cells and normal T cells were individually isolated and used for single cell (SC) whole exome sequencing (WES). Whole genome amplification (WGA) was performed by multiple displacement amplification (Qiagen REPLI-g Mini kit), and exome capture was performed using Agilent SureSelect. Libraries were then 90 bp paired end sequenced on an Illumina HiSeq2000 (BGI, China). Data analysis Data was produced for bulk (1000 cells) MM and bulk germline T cells, twenty MM SCs and five T cell SCs. Raw data was aligned to hg19 reference sequence using NovoAlignMPI (v3.02.03). Variant calling was performed using SAMtools (v1.2.1) and VarScan (v2.3.6) and variants were annotated using ANNOVAR. High confidence variants were called in the bulk tumour WES by pairwise comparison with bulk germline WES. Variant lists were also cross-searched against various variant databases (CG46, 1000 genomes, dbSNP, esp650 and in-house database) in order to exclude variants that occur in the general population. Multiple quality control measures were employed to reduce the number of false positive calls. Results and Discussion Data and bioinformatics pipelines are of a high quality SC WES generated raw data reads that were similar to bulk WES of 1000 cells, with comparable mapping to Agilent SureSelect target exome (69-76% SC vs. 70% bulk) and mean fold coverage (56.8-59.1x vs. 59.7x bulk). On average, 82% of the exome was covered sufficiently for somatic variant (SV) calling (often considered as ≥ 5x), which was higher than seminal published SC WES studies (70-80%) (Hou et al., Cell, 2012; Xu et al., Cell, 2012). We identified 33 potentially deleterious SVs in the bulk tumour exome with high confidence bioinformatics, 21 of which were also identified in one or more SC exomes. The variants identified include suspected deleterious mutations in genes involved in MAPK pathway, plasma cell differentiation, and those with known roles in B cell malignancies. To confirm SV calls, randomly selected variants were validated by conventional Sanger sequencing, and of 15/15 variants in the bulk WES and of 55/55 variants in SCs, to obtain 100% concordance. Intraclonal variation in MM Significantly, ICV was apparent from the SC exome variant data. Total variant counts varied considerably among SCs and most variant positions had at least several cells where no evidence of the variant existed. Bulk WES lacks crucial information We identified an additional 23 variants that were present in 2+ SC exomes, but absent in the bulk MM tumour exomes. Of these, 30% (7 variants) were examined for validation, and were amplifiable in at least one cell to deliver 100% concordance with variant calls. These variants are of significant interest as they reveal a marked occurrence of subclonal mutations in the MM tumour population that are not identified by bulk exome sequencing. They indicate that the mutational status of the MM genome may be substantially underestimated by analysis at the bulk tumour population level. Conclusion In this work we establish the feasibility of SC WES as a method for defining intraclonal genetic variation in MM. Disclosures No relevant conflicts of interest to declare.

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G, Dhanyakumar, and Maheswari L Patil. "Whole Exome Sequencing Data Analysis for Detection of Breast Cancer Gene Variants and Pathway Study." International Journal of Current Research and Review 14, no. 06 (2022): 17–26. http://dx.doi.org/10.31782/ijcrr.2022.14603.

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Introduction: Whole Exome Sequencing (WES) involves sequencing, analysis of protein coding regions in genome. In present investigation, the potential gene variants were identified in human breast cancer genome using WES data analysis. Materials and Method: The NGS data samples with accession numbers (SRR1274896_1, SRR1274896_2) and (SRR1275000_1, SRR1275000_2) were collected from ENA database. The quality of the samples was assessed by using FastQC tool and followed by aligning samples with reference genome sequence hg38 using Bowtie2 tool. The results were retrieved in SAM format and converted to BAM format and then to sorted bam file using SAM tools, then duplicates were removed using Picard tool. Finally, Variant Calling format file was generated using BCF tools which projected the possible gene variants in the samples. Results: The results showed variant types out of them MUC3A1 showed an average of 53 mutations, highlighting its importance as a potential gene variant observed in breast cancer. Out of nonsynonymous mutations of samples, common gene variants in samples that possess 5 and more mutations were selected. The study was carried out on pathway analysis, domain analysis, gene involvement in biological processes and gene function. Conclusion: Majority of gene variants were involved in DNA Biosynthesis and Protein Biosynthesis and also resulted in tissue specific location. The location of these genes showed mutated genes in cytoplasm and in nucleus indicating the impact of gene variation on intracellular process.

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Chang, Ya-Sian, Chieh-Min Chang, Chien-Yu Lin, Dy-San Chao, Hsi-Yuan Huang, and Jan-Gowth Chang. "Pathway Mutations in Breast Cancer Using Whole-Exome Sequencing." Oncology Research Featuring Preclinical and Clinical Cancer Therapeutics 28, no. 2 (March 27, 2020): 107–16. http://dx.doi.org/10.3727/096504019x15698362825407.

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The genomic landscape of breast cancer (BC) is complex. The purpose of this study was to decipher the mutational profiles of Taiwanese patients with BC using next-generation sequencing. We performed whole-exome sequencing on DNA from 24 tumor tissue specimens from BC patients. Sanger sequencing was used to validate the identified variants. Sanger sequencing was also performed on paired adjacent nontumor tissues. After genotype calling and algorithmic annotations, we identified 49 deleterious variants in canonical cancer-related genes in our BC cohort. The most frequently mutated genes were PIK3CA (16.67%), FKBP9 (12.5%), TP53 (12.5%), ATM (8.33%), CHEK2 (8.33%), FOXO3 (8.33%), NTRK1 (8.33%), and NUTM2B (8.33%). Seven mutated variants (ATR p.V1581fs, CSF1R p.R579Q, GATA3 p.T356delinsTMKS, LRP5 p.W389*, MAP3K1 p.T918fs, MET p.K1161fs, and MTR p.P1178S) were novel variants that are not present in any gene mutation database. After grouping the samples according to molecular subtype, we found that the cell cycle, MAPK, and chemokine signaling pathways in the luminal A subtype of BC; the focal adhesion, axon guidance, and endocytosis pathways in the luminal B subtype; and amyotrophic lateral sclerosis in the basal-like subtype were exclusively altered. Survival curve analysis showed that the presence of the MAPK signaling pathway and endocytosis mutations were correlated with a poor prognosis. These survival data were consistent with cBioPortal analyses of 2,051 BC cases. We discovered novel mutations in patients with BC. These results have implications for developing strategic, adjuvant, and gene-targeted therapies.

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Koh, Youngil, Daeyoon Kim, Woo-June Jung, Kwang-Sung Ahn, and Sung-Soo Yoon. "Revealing Genomic Profile That Underlies Tropism of Myeloma Cells Using Whole Exome Sequencing." International Journal of Genomics 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/675379.

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Background.Previously we established two cell lines (SNU_MM1393_BM and SNU_MM1393_SC) from different tissues (bone marrow and subcutis) of mice which were injected with single patient’s myeloma sample. We tried to define genetic changes specific for each cell line using whole exome sequencing (WES).Materials and Methods.We extracted DNA from SNU_MM1393_BM and SNU_MM1393_SC and performed WES. For single nucleotide variants (SNV) calling, we used Varscan2. Annotation of mutation was performed using ANNOVAR.Results.When calling of somatic mutations was performed, 68 genes were nonsynonymously mutated only in SNU_MM1393_SC, while 136 genes were nonsynonymously mutated only in SNU_MM1393_BM.KIAA1199, FRY, AP3B2,andOPTCwere representative genes specifically mutated in SNU_MM1393_SC. When comparison analysis was performed using TCGA data, mutational pattern of SNU_MM1393_SC resembled that of melanoma mostly. Pathway analysis using KEGG database showed that mutated genes specific of SNU_MM1393_BM were related to differentiation, while those of SNU_MM1393_SC were related to tumorigenesis.Conclusion.We found out genetic changes that underlie tropism of myeloma cells using WES. Genetic signature of cutaneous plasmacytoma shares that of melanoma implying common mechanism for skin tropism.KIAA1199, FRY, AP3B2,andOPTCare candidate genes for skin tropism of cancers.

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Zhang, Zhihui, Qian Vicky Wu, Christopher I. Amos, Yanhong Liu, Hong Wei, Chao Cheng, Spiridon Tsavachidis, et al. "Rare Variant Genetic Association Study for Transplant-Associated Thrombotic Microangiopathy (TA-TMA) Via Whole Exome Sequencing." Blood 138, Supplement 1 (November 5, 2021): 745. http://dx.doi.org/10.1182/blood-2021-149438.

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Abstract Introduction: Transplant-associated thrombotic microangiopathy (TA-TMA) is an increasingly recognized hematologic complication after allogeneic hematopoietic cell transplantation (HCT). While few studies have reported germline association with rare variants in complement genes using targeted next generation sequencing (NGS) method, they were limited by small sample size (≤40 TMA cases) and lack of analysis of non-complement genes (PMIDs 26603840, 32131130). In the present study, we employed whole exome sequencing (WES) to assess rare variant contribution to the development of TMA in a hypothesis-driven pathway-specific approach. Methods: In the current case-control genetic association study conducted at Fred Hutchinson Cancer Research Center, we selected 100 patients with a diagnosis of TMA and pre-transplant DNA samples (case definition described previously in PMID 30940363, 33836868). We then performed incidence density sampling to randomly select 100 non-TMA controls after allogeneic HCT matching by age, sex, race, and year of HCT. WES (germline variant detection 40x) was conducted using Illumina NovaSeq. Sequence reads were mapped to hg38 reference genome followed by deduplication and base quality score recalibration. Joint-genotyping was performed to call single nucleotide polymorphism (SNPs) and insertion/deletion (indels) using the GATK v3.3 and Atlas2. Variants were filtered during quality control (QC) and variant quality score recalibration (VQSR) and annotated using ANNOVAR and Ensembl VEP. To optimize signal detection by reducing neutral background variation, we defined qualifying variants as those meeting all 3 criteria: 1) novel or rare variants with a minor allele frequency (MAF) <1% in the reference database gnomAD; 2) functional variants with missense, frameshift, indel, splice region/acceptor/donor, start/stop gained/lost, coding sequence, and protein altering in VEP; and 3) missense variants previously reported to be likely pathogenic from the ClinVar database or predicted to be deleterious from 4/6 in-silico prediction tools (SIFT, Polyphen-2, MutationTaster, MutationAssessor, FATHMM, and FATHMM-MKL) (Figure 1). We then focused on the exome profiles of 5 a priori selected genetic pathways: complement regulation (17 genes), VWF and coagulation (7 genes), VWF clearance (10 genes), ADAMTS13 mimics or interacting proteins (10 genes), and angiopoietin family and endothelial activation (7 genes). Pathway-based and gene-based collapsing association tests were performed using the Optimized Sequence Kernel Association (SKAT-O) test as an optimal test combining burden test and SKAT. Results: After joint variant calling, 91 TMA cases and 93 non-TMA controls passed all QC filters (Table 1). Among 1,485 variants detected in the 5 pathways after QC, 60 variants (73 total mutations) were considered as qualifying variants with MAF <1%, functional coding, and in-silico pathogenic prediction (Figure 1). From pathway-based analysis, a significant association was observed in the VWF clearance pathway (p=0.041) but not in the complement regulation pathway (p=0.308) or the other 3 pathways (Table 2). From gene-based analysis, the significant association in the VWF clearance pathway appeared to be driven by rare variants within the LRP1 gene (Figure 2), which encodes a member of the low-density lipoprotein receptor family of proteins that contributes to the clearance of VWF (PMID 22234691). Sensitivity analyses performed including all rare variants without in-silico pathogenicity prediction resulted in similar findings. Conclusion: Contrary to the initial hypothesis, we did not observe pathogenic germline rare variants in the complement regulation pathway in patients with TA-TMA. Instead, we found a significant association in the VWF clearance pathway, particularly that of the LRP1 gene. In recent years, researchers have shown that VWF can bind to and activate complement proteins. Impaired VWF clearance could lead to the higher predisposition for complement activation observed in patients with TA-TMA. Future functional studies are needed to determine the impact of VWF clearance on the pathogenesis of the disease. Figure 1 Figure 1. Disclosures Sartain: Alexon Pharamaceuticals: Membership on an entity's Board of Directors or advisory committees. Lee: Incyte: Research Funding; Janssen: Other; Takeda: Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Research Funding; Kadmon: Research Funding; National Marrow Donor Program: Membership on an entity's Board of Directors or advisory committees; Syndax: Research Funding; AstraZeneca: Research Funding; Amgen: Research Funding.

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Chang, Ting-Chia, Li Chen, Biswajit Das, Yvonne A. Evrard, Chris A. Karlovich, Tomas Vilimas, Alyssa Chapman, et al. "Abstract 1913: Quality control workflows developed for the NCI Patient-Derived Models Repository using low pass whole genome sequencing and whole exome sequencing." Cancer Research 82, no. 12_Supplement (June 15, 2022): 1913. http://dx.doi.org/10.1158/1538-7445.am2022-1913.

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Abstract Background: The National Cancer Institute's Patient-Derived Models Repository (NCI PDMR; pdmr.cancer.gov) is developing a variety of patient-derived xenograft (PDX) models for pre-clinical drug studies. All NCI PDMR models undergo quality control (QC) processes. Two unique QC challenges are: a) to assess genomic stability across PDX model passages; and b) to confirm the suitability of PDX-derived cancer associated fibroblasts (CAFs) as germline surrogates when blood is not available. Multiple bioinformatics QC assessments have been developed to measure the genomic fidelity in these PDX models using low-pass whole genome sequencing (LP-WGS) and in CAFs using whole exome sequencing (WES). Methods: LP-WGS was performed on 502 PDX samples from 38 models of rare cancer across passages 2 through 9 and WES was performed on 92 CAFs from 32 different histologies. In the QC workflow for estimating the genomic stability of passages within models, BBSplit was used for the assessment of human/mouse DNA content. CNVkit was utilized for copy number (CN) detection. The fraction of genome changed was calculated by comparing the copy numbers of each passage sample to the original patient sample. To evaluate purity of CAFs, three QC steps were constructed: a) plot of SNP variant allele frequency (ideogram); b) variant annotation using OncoKB (www.oncokb.org); c) percentage of genomic loss of heterozygosity (LOH), based on a set of ~800,000 heterozygous SNPs from a population-level genomic database (gnomAD) based on WES data. Results: PDX models showed genomic stability in CN profile when measured by LP-WGS. Human tumor DNA content remains stable ranging from 75-85% across different tiers of PDX passages from Donor +1 to Donor +6 and more. No models showed statistically significant evolution in CN profile, given the average 5 samples per model in each tier of passages. The QC workflow for CAFs generated five categories based on SNP ideograms, the presence/absence of oncogenic variants and LOH. Following observations were made: a) 72.5% CAFs were confirmed as matched diploid CAFs (category 1); b) 6.6% of CAFs were diploid and had >= 1 germline oncogenic variant - classified as category 2. CAFs in category 1&2 were suitable as germline surrogates; c) 12% of CAFs (category 3) showed putative polyploidy on SNP ideograms with no oncogenic variants and suitable for somatic variant calling; d) 8.8% of CAFs (category 4) had polyploidy and oncogenic variants present; e) LOH high CAF (category 5) - we identified a CAF with 42% LOH, later confirmed to be a tumor cell line by immunohistochemistry (IHC). Other CAFs (n=91) showed little variance, ranging from 0.6%-1.7% LOH. Conclusions: We developed standard QC workflows to evaluate genomic stability of PDX models during passaging and qualify CAFs as germline surrogates for pre-clinical study. Citation Format: Ting-Chia Chang, Li Chen, Biswajit Das, Yvonne A. Evrard, Chris A. Karlovich, Tomas Vilimas, Alyssa Chapman, Nikitha Nair, Luis Romero, Anna J. Lee Fong, Amanda Peach, Brandie Fullmer, Lindsay Dutko, Kelly Benauer, Gloryvee Rivera, Erin Cantu, Shahanawaz Jiwani, Nastaran Neishaboori, Tomas Forbes, Corinne Camalier, Luke Stockwin, Michael Mullendore, Michelle A. Eugeni, Dianne Newton, Melinda G. Hollingshead, Mickey P. Williams, James H. Doroshow. Quality control workflows developed for the NCI Patient-Derived Models Repository using low pass whole genome sequencing and whole exome sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1913.

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Zheng, Yan, Ti-Cheng Chang, Gang Wu, Jane S. Hankins, Mitchell J. Weiss, Connie M. Westhoff, and Stella T. Chou. "Accurate Prediction of RH Genotypes Using Whole Genome Sequencing Data." Blood 132, Supplement 1 (November 29, 2018): 2332. http://dx.doi.org/10.1182/blood-2018-99-119681.

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Abstract Introduction RBC alloimmunization is common in patients with sickle cell disease (SCD). Despite serological matching RBCs for major Rh antigens, Rh alloimmunization remains problematic. The Rh blood group is encoded by two genes RHD and RHCE, which exhibit extensive nucleotide polymorphism and chromosome structural changes, resulting in the formation of Rh variant antigens. Rh variants can result in loss of protein epitopes or expression of neo-epitopes, and are common in SCD patients. Hence SCD patients harboring Rh variants can be predisposed to Rh alloimmunization. Given the limitation of traditional serologic antigen typing for detection of Rh variants, molecular genotyping has become required. A DNA microarray-based platform, BioArray RHCE and RHD BeadChip (Immuncor) is available for RH genotyping. However, it detects the most common, but not all, variants. Whole exome sequence data have been used for prediction of Rh variants (Chou, et. al, Blood Adv., 2017), offer some advantages, including detection of rare variants, structural rearrangements and copy number variation. However, whole genome sequence (WGS) analysis of RHD/RHCE is challenging due to difficulties in mapping next generation sequencing (NGS) reads to this duplicated gene family. We developed a computational algorithm to identify RH variants using WGS data. Methods The pipeline included three major components, RH allele database construction, RH variant calling, and classification of Rh blood group according the identified variants. The RH allele database was built based on NCBI Blood Group Antigen Gene Mutation (BGMUT) and International Society of Blood Transfusion (ISBT) database. Since the alleles in the BGMUT and ISBT databases were specified according to conventional RH genes (RHD, L08429; RHCE, DQ322275) that are different from those on reference human genome, we first called the variations based on the reference human genome. The positions of the identified variations were subsequently corrected to match with the BGMUT and ISBT annotation system. Next, the NGS reads with low base quality and/or mapping quality were discarded during the variation calling step. Synonymous and non-synonymous amino acid changes were characterized for each polymorphism. Haplotypes were constructed for the segments with NGS read support. Gene sequencing coverage was calculated to determine gene deletions or amplifications. Lastly, we implemented an algorithm to predict RH genotypes based on a selection of candidate alleles by read-mapping profile which considers both sequence variations and sequence consistency followed by a likelihood-based ranking of all pairwise combinations of the selected alleles. The allele combination with the highest likelihood is considered the most likely pair of alleles at a given locus. Patient specimens used in this study were from participants of the Sickle Cell Clinical Research and Intervention Program (SCCRIP, Hankins et al. Pediatr Blood Cancer. 2018). Results We validated our method in a cohort of 58 SCD patients whose RH genotypes had been determined by BioArray RhCE and RhD BeadChip and supplementary molecular tests that identify the most common variants among individuals of African descent. In this validation cohort including a total of 11 RHD and 13 RHCE alleles, our approach achieved a concordance rate of 85.85% (91 of 106 alleles) for RHD and 83.02% (88 of 106 alleles) for RHCE genotyping. WGS was highly sensitive in distinguishing homozygosity from heterozygosity of genes. By comparing the numbers of NGS reads on RH regions and whole genome average coverage, heterozygous deletion can be determined. Since WGS provides comprehensive genotyping, our analysis identified single nucleotide polymorphisms that were not identified by the BeadChip and supplemental molecular testing. The final source of discordance was likely due to the short read length of NGS such that haplotype phases cannot be correctly predicted if the variations are separated by thousands of base pairs, for which long read DNA sequencing or RNA/cDNA sequencing are required. Evaluation of the identified discrepancies is ongoing. Conclusions We developed and validated a diagnostic method for RH genotyping that leveraged the accuracy and flexibility of RH genotyping based on WGS data. With further optimization of our method, this may be useful for RBC genotype matching sickle cell patients to blood donors in the future. Disclosures Hankins: Novartis: Research Funding; Global Blood Therapeutics: Research Funding; NCQA: Consultancy; bluebird bio: Consultancy.

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Waller, Rosalie G., Karen Curtin, Djordje Atanackovic, Guido J. Tricot, Steven M. Lipkin, and Nicola J. Camp. "Exome Sequencing in Myeloma Pedigrees Implicates RAS1 and NOTCH Signaling Are Involved in Inherited Myeloma Risk." Blood 126, no. 23 (December 3, 2015): 2976. http://dx.doi.org/10.1182/blood.v126.23.2976.2976.

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Abstract Multiple Myeloma (MM) is a cancer of plasma cells with poor prognosis. Although, MM has been shown to be highly heritable in genealogy studies, no inherited risk-alleles have been identified. We hypothesize MM heritability is in part due to rare, germline variation that can be discovered in high-risk pedigrees. High-risk MM pedigrees were identified using the Utah Population Database which contains both genealogical and state cancer records. High-risk pedigrees were defined to have statistical excess of MM (p < 0.05). In this study we whole-exome sequenced germline DNA from 42 MM cases from high-risk pedigrees. Best practice variant calling, joint genotyping, and quality control were performed on the cases, a set of background controls from the 1000 Genome Project (1000G), and a small set of local controls (for technical artifacts), and resulted in 607,908 variants. We prioritized variants that were: 1) shared by at least 3 related MM cases, 2) absent in local controls, and 3) rare (frequency ≤ 0.01 in 1000G). This prioritization resulted in 116 variants of interest. Of the 116 variants, 3 MM cases in one high-risk pedigree shared multiple variants on chromosome 1p36.11-35.1. To formally assess whether these variants were inherited from a common founder we performed shared genome segment analysis using high-density SNP genotyping. We identified a region at 1p36.11-35.1, 8.9 Mb in length (p = 6.0 × 10-4; 22,000 simulations), providing positive evidence for segregation from a common founder. The segregating variants identified from exome sequencing in this region are in the genes CNKSR1, ARID1A, and SDC3. All three variants are individually predicted to be moderately deleterious. The variant in CNKSR1 falls in a splice region and has minor allele frequency of 0.004 in the 1000G Europeans. This variant was also observed in 3 additional cases in our sequencing set, indicating a strong enrichment of this variant in our high-risk MM cases (6/42 = 0.143). CNKSR1 is involved in the RAS1 and NOTCH signaling pathways and is a known target for cancer therapy. The variants in ARID1A and SDC3 both result in non-synonymous codon changes. ARID1A is commonly mutated across cancers and has been associated with accelerated tumor growth in hepatocellular carcinomas. SDC3 also interacts with NOTCH signaling, a pathway involved in MM growth (especially in patients with MAF translocations) and osteoclastogenesis. The variants in ARID1A and SDC3 are not carried by other cases in our sequencing set, which may indicate the combination of these variants is important to confer risk in the pedigree, or merely that the variants are hitchhikers on the segregating chromosome. Germline risk-alleles will shed light on the genetic factors involved in MM susceptibility and ultimately may provide new avenues for screening, diagnosis and treatment. Here we have identified evidence for segregating variants in a high-risk pedigree that implicate the RAS1 and NOTCH signaling pathways as involved in MM risk. Future work includes confirmation sequencing in the pedigree and a broader set of MM cases, and functional follow-up of the variants and their role in disruption of the genes and pathways. Disclosures No relevant conflicts of interest to declare.

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Kueffner, Robert, Hui Li, Kakit Cheung, Marc Fink, Zachry Soens, Jinlian Wang, Osman Siddiqui, et al. "VONC: A solution for the clinical assessment of somatic genomic alterations." Journal of Clinical Oncology 37, no. 15_suppl (May 20, 2019): e13155-e13155. http://dx.doi.org/10.1200/jco.2019.37.15_suppl.e13155.

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e13155 Background: Next generation sequencing (NGS) technology is transforming the diagnosis and treatment of cancer. However, the massive scale of data has overwhelmed pathologists who need streamlined tools to process this data, automate report generation and minimize human errors. Methods: We developed the Variant interpretation station for ONCology, VONC, as an end-to-end solution for moving from NGS whole exome and transcriptome data to actionable clinical reports that support cancer diagnosis, prognosis, and personalized treatment strategies for solid and hematologic malignancies. Results: VONC integrates all steps for moving from raw NGS data, variant calling and LIMS, to comprehensive annotation of variants. The main functional feature of VONC is a transparent process that effectively combines automated and expert curation to identify clinically relevant and actionable driver variants. VONC also enables efficient management of multi-group, -role, -system and -site curation processes. In contrast to current tools, VONC handles all somatic and constitutional genomic alterations including SNV, indel, CNV, fusion, splicing, and gene expression. Key data sources include 1) 350,000 variants for 50 tumor types across 57,000 sequenced cancer patients; 2) variant frequencies estimated from 1.5M cancer patients; 3) expert curated literature evidence from 16,818 papers covering 26,496 alterations spanning 2,448 cancer driver genes; and 4) curated database of FDA-approved drugs and recruiting clinical trials. VONC presents a prioritized list of variants in oncogenes and tumor suppressors through functional (literature-based) and structure-based (hotspots) algorithms. This is coupled to all supporting information necessary for clinical decision making. Curators can quickly screen variant type, QC metrics, and frequency in sequencing cohorts of cancer patients as well as healthy subjects. Within minutes, variants can be triaged and annotated with FDA approved, NCCN guidelines reported, or literature supported therapeutics, including resistance and contraindicated. Conclusions: VONC is a clinically-ready tool with an intuitive end-user interface tailored for the rapid assessment of variants in cancer patients, to facilitate personalized cancer medicine in a high-throughput laboratory.

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Vaske, Charles Joseph, Chad Garner, Tara Elisabeth Seery, Christopher Szeto, and Sandeep K. Reddy. "Clinical trial screening of CDKN2A genomic alterations in patients with pancreatic cancer and hepatobiliary cancers requires greater precision than somatic sequencing alone." Journal of Clinical Oncology 37, no. 4_suppl (February 1, 2019): 287. http://dx.doi.org/10.1200/jco.2019.37.4_suppl.287.

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287 Background: The TAPUR Study is a phase II multi‐basket study that evaluates the anti‐tumor activity of commercially available targeted agents in pts with advanced cancers with genomic alterations known to be drug targets. Results in two cohorts of PC and GBC pts each with CDKN2A loss or mutation were reported at ASCO 2018. The conclusion was that monotherapy with palbocicilib is not associated with clinical activity in these patients. This may be a false conclusion if the genomic targets were absent in these patients. Methods: A total of 158 GI pts (P = 123, GB = 20, Bile Duct = 15) with deep whole exome sequencing (WES) of tumor and blood samples, and whole transcriptomic sequencing (RNA-Seq) (∼200x106 reads per tumor) were available for this analysis from a commercial database. Variant calling was performed through joint probabilistic analysis of tumor and normal DNA reads, with germline status of variants being determined by heterozygous or homozygous alternate allele fraction in the germline sample. Results: 26 somatic variants and 12 germline variants were detected, with one sample overlapping with a germline and a somatic variant (p.A148T and p.A76Rfs∗44). Counting all 11 discrete germline variants as false positives, a total 37 of 158 samples would be positive for CDKN2A mutant status, a rate of 23% (17%-31% CI). However, if the 8 common germline variants are excluded, the call rate is 29/158 = 18% (12%-25% CI). The false positive rate is 4/158 = 14% (4%-31% CI). By RNAseq, true somatic CDKN2A variants had significantly higher TPM counts than germline variants (T-test p = 0.0002). RB expression was not significantly different between the two groups. Conclusions: The failure of palbociclib to show benefit in CDKN2A mutated PC and GBC patients in the 20 patient cohort of the TAPUR study could possibly be explained by patient selection rather than solely drug failure. It is unlikely related to RB loss.

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Kalmar, Alexandra, Gitta Szabo, Orsolya Galamb, Barbara Kinga Bartak, Zsofia Brigitta Nagy, Sara Zsigrai, Krisztina Andrea Szigeti, et al. "Abstract 2945: Comprehensive analysis of tissue and plasma-related genetic alterations in Hungarian colorectal cancer patients." Cancer Research 82, no. 12_Supplement (June 15, 2022): 2945. http://dx.doi.org/10.1158/1538-7445.am2022-2945.

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Abstract Background: Analysis of circulating cell-free DNA (cfDNA) of colorectal cancer (CRC) patients provides an ideal approach to explore genetic alterations in a minimally invasive way. Aims: We aimed to perform a comprehensive analysis of tissue-originated genomic DNA and plasma-derived cfDNA from CRC patients by whole-exome and targeted panel sequencing. Materials & methods: DNA was isolated from tissue and plasma samples of 55 [7 healthy (N), 16 adenomas (AD), and 32 CRC] patients using the High Pure PCR Template Kit (Roche) and the Quick cfDNA Serum & Plasma Kit (Zymo). cfDNA quality was assessed with the High Sensitivity DNA kit on BioAnalyzer 2100 and quantified by the Qubit dsDNA HS assay. Exome libraries from tissue samples were constructed by the Nextera DNA Exome Kit (Illumina). For the cfDNA samples, we used the QIAseq cfDNA All-in-One kit combined with the QIASeq Human Exome Kit, and in the case of 12 patients, CRC-specific oncogenes were further analyzed with a solution developed by QIAGEN for reliable calling of low frequency variants in cfDNA samples. Exome libraries were quantified with the KAPA Library Quantification Kit and the QIAseq™ Library Quant Assay Kit (Qiagen) and were sequenced using the NextSeq 500/550 High Output v2 kit on a NextSeq 500 Instrument (Illumina). Raw data analysis and demultiplexing were completed on the BaseSpace Sequence Hub. Variants of the tissue and cfDNA samples were determined by the Mutect2 and Haplotype caller algorithms of GATK 4.1.4.1, respectively. Clinical significance was evaluated according to the OncoKB database. Results: The most frequently mutated genes were APC, KRAS, DYNC1H1, KCNO5, and MARCH6 in the colorectal adenoma tissue samples, while those in CRC samples were APC, TP53, TTN, KRAS, and DYNCC2H1. CfDNA quantity was significantly higher in the CRC group compared to the AD (p<0.02) and N (p<0.005) patients. Based on the plasma exome results, 4.4-59.4% of the tumor somatic variants could be found in 12.5% of the patients. These patients were above 60 years of age and had Dukes D stage CRC. Panel sequencing of the circulating DNA samples detected tumor somatic variants in 8 out of the 12 enrolled patients. This method could identify 60% of all tumor somatic variants falling on its targeted regions, while whole-exome sequencing recovered only 20% of tumor somatic variants in the respective regions in cfDNA of the same patients. Conclusion: We have performed a comprehensive genetic analysis on CRC tissue and cfDNA samples in the Hungarian population. Exome sequencing offers a broad overview of the coding regions, however, targeted panel sequencing with a higher coverage depth can detect tumor somatic variants more reliably in cfDNA, therefore, it can hold a relevant clinical potential. Citation Format: Alexandra Kalmar, Gitta Szabo, Orsolya Galamb, Barbara Kinga Bartak, Zsofia Brigitta Nagy, Sara Zsigrai, Krisztina Andrea Szigeti, William Kothalawala, Peter Igaz, Istvan Takacs, Bela Molnar. Comprehensive analysis of tissue and plasma-related genetic alterations in Hungarian colorectal cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2945.

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Newton, Yulia, Justin Golovato, Iain Beehuat Tan, Justina Yick Ching Lam, Guo Yu, Si-Lin Koo, Clarinda Chua, et al. "Genomic and immune infiltration differences between MSI and MSS GI tumors." Journal of Clinical Oncology 37, no. 4_suppl (February 1, 2019): 528. http://dx.doi.org/10.1200/jco.2019.37.4_suppl.528.

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528 Background: Dysregulation of DNA mismatch repair pathway can lead to microsatellite instability in many GI tumors, and microsatellite instability is an important diagnostic and prognostic marker. Microsatellite instable (MSI) tumors comprise about 15% of colorectal malignancies and can be found in other gastrointestinal (GI) tumor types. We present results of analysis of genomic and immune infiltration differences between MSI and microsatellite stable (MSS) GI tumors spanning multiple cancer types. Methods: A total of 521 GI patients with deep whole exome sequencing (WES) of tumor and blood samples, and whole transcriptomic sequencing (RNA-Seq) (∼200M reads per tumor) were available for this analysis from a commercial database. Variant calling was performed through joint probabilistic analysis of tumor and normal DNA reads, with germline status of variants being determined by heterozygous or homozygous alternate allele fraction in the germline sample. Results: Gene expression and pathway analysis found significantly higher immune signaling in MSI cohort and higher metabolic signaling in MSS cohort. We also found upregulation of structural cellular integrity pathways in MSI tumors. Per-sample deconvolution of immune infiltration using cell type gene markers shows some MSI samples with high CD8 T-cells. Co-expression analysis of checkpoint and TME genes shows higher correlation of FOXP3 and CTLA4 in the MSS cohort compared to the MSI samples, whereas correlation between FOXP3 and PDL1 is decreased. TIM3, LAG3, and OX40 are significantly more expressed in MSI samples than MSS samples. Within the subset of colorectal tumors, additional checkpoints are significantly differentially overexpressed in MSI malignancies. 50 somatic variants are significantly differential in MSI tumors. Conclusions: MSI tumors demonstrably exhibit higher immune signaling, with many immune and checkpoint markers expressed at higher levels in MSI tumors. Some cellular integrity pathways also appear to be up in MSI cohort. A number of potentially important somatic variants are associated with MSI samples.

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Michuda, Jackson, Ben Ho Park, Amy Lauren Cummings, Siddhartha Devarakonda, Bert O'Neil, Sumaiya Islam, Jerod Parsons, et al. "Use of clinical RNA-sequencing in the detection of actionable fusions compared to DNA-sequencing alone." Journal of Clinical Oncology 40, no. 16_suppl (June 1, 2022): 3077. http://dx.doi.org/10.1200/jco.2022.40.16_suppl.3077.

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3077 Background: While targeted DNA-seq can detect clinically actionable fusions in tumor tissue samples, technical and analytical challenges may give rise to false negatives. RNA-based, whole-exome sequencing provides a complementary method for fusion detection, and may improve the identification of actionable variants. In this study, we quantify this benefit using a large, real-world clinical dataset to assess actionable fusions detected from RNA in conjunction with DNA profiling. Methods: Using the Tempus Research Database, we retrospectively analyzed a de-identified dataset of ̃80K samples (77.4K patients) profiled with the Tempus xT assay (both DNA-seq with fusion detection in 21 genes and whole exome capture RNA-seq). Only patients that had successful RNA- and DNA-seq were included. Fusions were detected using the Tempus bioinformatic and clinical workflow. Candidate fusions were filtered based on read support thresholds, fusion annotation ( i.e., breakpoints, reading frame, conserved domains), and manual review. OncoKB was used to select fusion alterations in levels 1 and 2 and to identify those indication-matched to targeted therapies. Results: We identified 2118 level 1 and 2 fusion events across 1945 patients across 20 different cancer types. Most fusions were observed in non-small cell lung cancer (NSCLC) (25%) and biliary cancer (9%) samples. Of the 2118 fusion events, 29.1% (616) were detected only through RNA-seq while 4.8% (101) of the events were identifiable only through DNA-seq. Notably, 69.4% of fusions in low-grade glioma and 58.2% in sarcomas were detected only by RNA-seq. When evaluating specific gene fusion events, RNA-seq consistently improved the detection of fusions compared to DNA-seq alone (Table) across all cancer types. A total of 1106 fusions were classified as targetable by OncoKB indication-matched therapies with 19% (214) of these identifiable through RNA-seq alone, 5% (54) by DNA-seq alone, and 76% (838) identifiable through RNA- and DNA-seq. Overall, fusions identified through RNA-seq alone led to a 24% increase in the number of patients who were eligible to receive matched therapies (214 / 892). This included imatinib for patients with CML/BLCL (69.8%), crizotinib for NSCLC (40.3%) and entrectinib for NTRK and ROS1 fusions (32.5%). Conclusions: The addition of RNA-seq to DNA-seq significantly increased the detection of fusion events and ability to match patients to targeted therapies. Results support consideration of combined RNA-DNA-seq for standard-of-care fusion calling. [Table: see text]

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Michuda, Jackson, Ben Ho Park, Amy Lauren Cummings, Siddhartha Devarakonda, Bert O'Neil, Sumaiya Islam, Jerod Parsons, et al. "Use of clinical RNA-sequencing in the detection of actionable fusions compared to DNA-sequencing alone." Journal of Clinical Oncology 40, no. 16_suppl (June 1, 2022): 3077. http://dx.doi.org/10.1200/jco.2022.40.16_suppl.3077.

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3077 Background: While targeted DNA-seq can detect clinically actionable fusions in tumor tissue samples, technical and analytical challenges may give rise to false negatives. RNA-based, whole-exome sequencing provides a complementary method for fusion detection, and may improve the identification of actionable variants. In this study, we quantify this benefit using a large, real-world clinical dataset to assess actionable fusions detected from RNA in conjunction with DNA profiling. Methods: Using the Tempus Research Database, we retrospectively analyzed a de-identified dataset of ̃80K samples (77.4K patients) profiled with the Tempus xT assay (both DNA-seq with fusion detection in 21 genes and whole exome capture RNA-seq). Only patients that had successful RNA- and DNA-seq were included. Fusions were detected using the Tempus bioinformatic and clinical workflow. Candidate fusions were filtered based on read support thresholds, fusion annotation ( i.e., breakpoints, reading frame, conserved domains), and manual review. OncoKB was used to select fusion alterations in levels 1 and 2 and to identify those indication-matched to targeted therapies. Results: We identified 2118 level 1 and 2 fusion events across 1945 patients across 20 different cancer types. Most fusions were observed in non-small cell lung cancer (NSCLC) (25%) and biliary cancer (9%) samples. Of the 2118 fusion events, 29.1% (616) were detected only through RNA-seq while 4.8% (101) of the events were identifiable only through DNA-seq. Notably, 69.4% of fusions in low-grade glioma and 58.2% in sarcomas were detected only by RNA-seq. When evaluating specific gene fusion events, RNA-seq consistently improved the detection of fusions compared to DNA-seq alone (Table) across all cancer types. A total of 1106 fusions were classified as targetable by OncoKB indication-matched therapies with 19% (214) of these identifiable through RNA-seq alone, 5% (54) by DNA-seq alone, and 76% (838) identifiable through RNA- and DNA-seq. Overall, fusions identified through RNA-seq alone led to a 24% increase in the number of patients who were eligible to receive matched therapies (214 / 892). This included imatinib for patients with CML/BLCL (69.8%), crizotinib for NSCLC (40.3%) and entrectinib for NTRK and ROS1 fusions (32.5%). Conclusions: The addition of RNA-seq to DNA-seq significantly increased the detection of fusion events and ability to match patients to targeted therapies. Results support consideration of combined RNA-DNA-seq for standard-of-care fusion calling. [Table: see text]

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Fogelstrand, Linda, Sara Ståhlman, Tore Samuelsson, Jonas Abrahamsson, and Lars Palmqvist. "Identification Of Leukemia-Specific Mutations For Detection Of Minimal Residual Disease In Acute Myeloid Leukemia Using Cell Sorting and Whole Exome Sequencing." Blood 122, no. 21 (November 15, 2013): 2575. http://dx.doi.org/10.1182/blood.v122.21.2575.2575.

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Abstract The introduction of next generation sequencing techniques into the field of leukemia research has revealed that acute myeloid leukemia (AML) is characterized by a limited number of somatic mutations, in most cases single nucleotide variations (SNVs). In addition to providing insight into the pathogenesis of AML, this information can potentially be used for detection of small amounts of leukemic cells in follow-up samples (minimal residual disease, MRD). The aim of this study was to identify leukemia-specific mutations in AML cells that can serve as leukemia-specific MRD-markers. Identification of leukemia-specific mutations was performed using whole exome sequencing of DNA from sorted leukemic cells and comparison with sorted lymphocytes from the same individual. Cells were obtained from 8 cases of AML, age 30-71 years old, from blood samples taken at the time of diagnosis of AML. Cell sorting was carried out by fluorescence activated cell sorter (FACS), where leukemic cells were defined by their FSC and SSC properties and expression of CD45, CD34, CD117, and HLA-DR. Lymphocytes were sorted based on FSC, SSC and CD45 expression. Purity of cell populations were >98% for leukemic cells and >99% for lymphocytes (with undetectable amounts of leukemic cells). Exome sequencing of sorted cell populations was performed on the Illumina platform with HiScanSQ yielding around 4^107reads per sample. Data were quality assessed by FastQC, aligned to the reference human genome, processed for PCR duplicate removal, variant calling with Genome Analysis Toolkit (GATK) package, annotation of variants with ANNOVAR, and verification in Integrative Genomic Viewer. SNVs and short insertions or deletions present in the dbSNP database were excluded and the resulting SNVs and short insertions and deletions with minimum coverage of 10 were compared between leukemic cells and lymphocytes from the same individual. Leukemia-specific heterozygous mutations were defined as present in >40% of the reads in the leukemic cell sample and present in none of the reads from the corresponding lymphocyte sample. By using these rather strict criteria at least three leukemia-specific SNVs were found in each AML case. Leukemia-specific SNVs (with coverage spanning between 10 and 250) were detected in recurrently mutated genes but also in genes not previously reported to be mutated in AML, e.g. CNNM4, GLYAT, NCKAP1L, PPBP, and PRB1. In the case of previously reported recurrently mutated genes in AML, at least one SNV was found in most AML cases. SNVs in recurrently mutated genes were found to be leukemia-specific in most cases, but in some cases, including PRPF40B, ETV6, and EZH2, SNVs were present in a heterozygous pattern in both leukemic cells and in lymphocytes, indicating that they are germ-line mutations. Genes with leukemia-specific insertions or deletions included NPM1, STAG2, RUNX1, and BCOR. The finding of the insertion in NPM1 in two cases was confirmed by detection of the insertion with conventional fragment analysis used in our clinical laboratory. When the same data analysis was used on exome sequencing data of neutrophilic cells and lymphocytes sorted from normal control samples (n=2), no SNVs or short insertions or deletions were found to differ between these two cell populations. Our results show that by using exome sequencing on sorted cell populations with high purity, leukemia-specific mutations can be identified in AML samples already at diagnosis without the need for additional sampling of normal material or access to remission samples. Information on leukemia-specific mutations at diagnosis could provide a basis for detection of MRD in follow-up samples, either by polymerase chain reaction or targeted deep sequencing. Disclosures: No relevant conflicts of interest to declare.

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Hansen, Marcus Celik, Charlotte Guldborg Nyvold, Anne Stidsholt Roug, Line Nederby, and Peter Hokland. "A New Approach to Identify Pathogenic Mutations and Inherited Variants By Exome Sequencing – Using a Pair of Identical Twins with Monoclonal Lymphosis As Case Model." Blood 124, no. 21 (December 6, 2014): 1979. http://dx.doi.org/10.1182/blood.v124.21.1979.1979.

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Abstract Genome-wide association studies (GWAS) have identified common susceptibility loci in developing chronic lymphocytic leukemia (CLL). As the price on whole exome and genome sequencing continues to drop, large sequencing studies become more feasible and will change our understanding of the biological fundament of malignancy - and of the premalignant state of monoclonal lymphocytosis toward leukemic status. However, CLL is heterogeneous and, while co-inheritance of multiple low-risk variants govern predisposition, GWAS cannot yet be expected to contribute sufficiently in delineating individual molecular drivers. There is a need to be able to determine likely drivers in single patients, while GWAS continue to add information to draw from. We hypothesized that with the right tool much information can be extracted from the patient specific analysis - with direct implications in the clinic. The production cost is already within range of other lab analyses, but the interpretative work is still in its infancy in the clinical settings. AIM: We set out to engineer a method to automatically rank and annotate whole exome data efficiently, pointing to most likely contributing variants in the development of MBL and CLL - with direct practical implications for the clinic and research. METHODS: As testing ground and model for the tool we analysed a pair of identical twins in whom one had developed B-CLL and the other monoclonal lymphocytosis (notably with different clonal usage of light chains). In this setting extensive variant and mutation annotation, filtering, analysis and ranking were carried out through variant calling and MuTect output post-processing tool written in the versatile Wolfram programming language (Mathematica 9, Wolfram Research, Oxfordshire, UK) tied to external data sources (Fig. 1). Variants are automatically evaluated and ranked on the basis of 1) allele frequency, predicted damage, non-synonymous change (e.g. charge or polarity change), affected region or predicted size of frameshift, 2) functional annotation of gene and 3) automated literature search and gene-disease association. 4) Querying COSMIC database determines calculated mutational frequency (normalized to size) of the affected gene in human cancers and whether the gene is known to be involved in oncogenesis. 5) Finally, graphical representation of expected expression is provided to assist interpretation. RESULTS: Rare inherited variants in the B-Cell Receptor and Wnt/beta-catenin Signaling Pathway and tumor suppressors were found in the germline set (Fig. 1). These results also showed IRF8 mutation, recently linked to CLL susceptibility loci, and a reported susceptibility loci (rs17246404). Twin A could be distinguished from B by a series of high-ranked mutations with myeloid association (RUNX1, TET2, PLCB1 and ELF4 etc, fig. 1C), a nonsense mutation affecting MAP2K3 and a frameshifting indel in CHST15 - a gene suggested to act as a B-cell receptor important for B-cell development. Also, a missense mutation with altered charge in the helicase domain of CLL-associated CHD2 was found. Twin B was found to have a different set of relevant mutations that may also be drivers in inducing a proliferative disorder (e.g. ABL2 SH2 domain, MYH1 motor domain, TNFAIP6 CUB domain, NOTCH4 EGF-like calcium-binding domain). Twin B, although following a benign course, had an overall higher number of mutations was backed by affected genes involved in DNA repair response (TOPBP1 and DNMT1). Also a key feature was chromatin, histone and DNA modifiers (CHD7, SETD1B and likewise DNMT1). DISCUSSION: The use of a new set of scripts allowed for the easy interpretation of variants in these twins, in whom it can be surmised that master genes underlying the B-cell proliferation in B-CLL can be found. We suggest that this analysis method can be used for individual assessment in close collaboration or directly by the clinician. As example, primary refractoriness to chemotherapy is an evident problem, but much data is already at hand to evaluate potential problematic variants. In our case doxorubicin and imatinib influx transporters were reported as possibly affected. There is a need for constructing analysis methods that assist the clinician in evaluating the disease on a genomic level. Hopefully, this kind of approach will make similar ventures in the single patient a clinical reality within a short span of time - benefitting patient and clinics. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

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Alzahrani, Ali, Abdulghani Bin Nafisah, Meshael Alswailem, Burair Alsaihati, Anhar Alnassar, Ahmed Bin Afeef, Reem AlQuraa, et al. "LBMON174 Germline Molecular Genetics Of Pituitary Adenomas." Journal of the Endocrine Society 6, Supplement_1 (November 1, 2022): A471—A472. http://dx.doi.org/10.1210/jendso/bvac150.980.

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Abstract Introduction Pituitary adenomas (PA) are common. Considered to be mostly sporadic tumors for a long time, it has become clear over the last decade that a significant proportion of PA carry germline and/or somatic mutations. This study investigated the germline genetics of a large series of patients (pts) with PA using whole-exome sequencing (WES) and found a high rate of germline mutations in a number of genes including genes that were only known to be somatically mutated in PA. Methods After obtaining ethical approval and informed consent, we randomly included 128 pts (65 Females and 63 males, median age 33 years, IQ range 25-44) with PA (34 microadenomas and 94 macroadenomas). The diagnosis includes acromegaly in 16 pts, Cushing disease in 10 pts, prolactinomas in 50 pts, non-functioning PA in 37 pts, TSHoma in 1 pt, and gonadotrophinoma in 14 pts. None of those pts had a family history of PA or known syndromes. We isolated DNA from peripheral blood and performed WES using Illumina platform (Illumina NovaSeq 6000). For bioinformatics analysis, we removed all intronic and ncRNA variants and focused on exonic, exonic-splicing and splicing variants. We applied strict quality filters within the variant calling pipeline to exclude artifacts arising from the DNA sequencing and subsequent steps. We also removed all synonymous variants and variants marked as benign or likely benign by either Clinvar or ACMG Intervar databases. We followed the ACMG criteria in assigning pathogenicity levels to the variants. We focused on genes that were reported before to be involved in the germline, mosaic or somatic genetics of PA (AIP, GNAS, MEN1, DICER1, CDKN1B, PIK3CA, NF1, USP48 and USP8, GPR101, PRKARIA, PRKACB, MAX, CABLES1, SF3B1 and the SDHx group). Results We found 35 different variants in the PA-associated genes in 60 pts (46.9%). Some of these variants occurred in more than one patient with a total number of occurrences of 80. Most of these variants are mono-allelic (96.25%). These variants were found in the following genes: GNAS (10 variants in 39 pts), AIP (one variant in 1 patient), CDKN1B (2 variants in 2 pts), DICER1 (1 variant in 1 patient), MEN1 (2 variants in 3 pts), NF1 (3 variants in 3 pts), PIK3CA (1 variant in 1 patient), SDHA (3 variants in 3 pts), SDHAF2 (2 variants in 5 pts), SDHB (4 variants in 3 pts), SDHD (3 variants in 3 pts), USP48 (2 variants in 8 pts) and USP8 (1 variant in 1 patient). These variants included missense, non-sense, and small indels. Conclusions Germline variants in genes previously reported to be associated with PA are common in apparently sporadic PA occurring in about 47% of cases. For the first time, we report a significant occurrence of germline variants in genes that were previously known to be only somatically mutated (e. g., USP8, USP48, GNAS). Presentation: Monday, June 13, 2022 12:30 p.m. - 2:30 p.m.

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Mc Dermott, Sarah, Midhat S. Farooqi, Azhar Saeed, Byunggil Yoo, Emily Farrow, Neil Miller, Patrick A. Brown, and Erin Guest. "Germline Variants Associated with Cancer Predisposition and Bone Marrow Failure Are Common in KMT2A-r Infant Acute Lymphoblastic Leukemia Patients." Blood 136, Supplement 1 (November 5, 2020): 41. http://dx.doi.org/10.1182/blood-2020-139564.

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Introduction: Infant acute lymphoblastic leukemia (ALL), is a particularly aggressive subtype of leukemia with an early onset and unfavorable clinical outcome. Most (~70%) cases of infant ALL involve chromosomal rearrangement of KMT2A (KMT2A-r) on chromosome 11q23, the strongest independent predictor of a poor prognosis. To date, genomics studies have consistently demonstrated KMT2A-r infant ALL to have a strikingly silent landscape of DNA mutations, aside from the KMT2A-r itself. Germline mutations in cancer predisposition genes are found in 8.6% of pediatric malignancies and 4.4% of pediatric leukemias, compared to 1.1% in persons in the 1000 Genomes Project (Zhang J et al., N Engl J Med 2015). We hypothesized that germline variants may contribute to the development of KMT2A-r ALL in infants. We examined the germline variants in remission blood samples from a large cohort of infants with KMT2A-r ALL who were enrolled in Children's Oncology Group (COG) trial AALL15P1. Methods: We performed whole genome sequencing (WGS) and whole exome sequencing (WES) on DNA isolated from peripheral blood from 36 KMT2A-r cases at time of remission. Sequencing was performed using an Illumina Hiseq 4000 or 2500 to a minimum depth of 90Gb (WGS) and 15Gb (WES). Alignment and variant calling were performed using the Dragon Bio-IT platform (v 3.2.8, Illumina). Blueprint Genetics clinical panels and the medical literature (Xa M et al., Nature 2018) were used to comprise a list of 346 genes associated with cancer predisposition and bone marrow failure syndromes. From this gene pool, variants were selected for analysis based on a variant allele frequency of ~50% and minor allele frequency <0.1% in control population databases (gnomAD). Variants were analyzed for pathogenicity per the 2015 ACMG/AMP interpretation guidelines for sequence variants. Results: Of 351 variants initially identified, we found 3 likely pathogenic (LP) and 6 pathogenic(P) non-synonymous germline variants (for a total of 9 LP/P variants) and 144 variants of unknown significance (VUS). In total, 19.4% (n=7) of patient samples displayed at least one LP/P variant. Two patient samples contained 2 variants each. Variants classified as VUS, LP, or P were further characterized by possible causative pathway: 37.9% (n=58) of variants were in genes associated with bone marrow failure (BMF), 17.6% (n=27) in driver genes, 13.1% (n=20) in genes associated with inherited leukemias, 11.1% (n=17) in tumor suppressor genes, 7.8% (n=12) in tyrosine kinase genes, and 29.4% (n=45) in other predisposition genes . Many variants were present in more than one pathway and are represented as such. Table 1 demonstrates the genetic characteristics of the 9 P/LP variants found in our cohort. ERCC2 was the only gene with multiple LP/P variants across samples, accounting for 2 (1 LP, 1 P) of the 9 deleterious variants identified (22%). Conclusion: We identified germline variants in cancer predisposition genes in 19.4% of this cohort of infant ALL patients, a higher mutation rate than has previously been reported. Among pathways evaluated, variants in genes associated with bone marrow failure predisposition were the most frequent. Interestingly, variants in ERCC2, which encodes a protein involved with repair of damaged DNA, were recurrent among infants with KMT2A-r ALL. Future directions include comparison to germline variants in cancer predisposition genes in other infant and non-infant ALL cohorts. Disclosures Brown: Novartis: Membership on an entity's Board of Directors or advisory committees; Jazz: Membership on an entity's Board of Directors or advisory committees; Servier: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees. Guest:Syndax Pharmaceuticals: Consultancy.

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Pleines, Irina, Joanne Woods, Ernest Turro, Nicola Foad, Stephane Chappaz, Rachael M. Lane, Harriet Manning, et al. "Mutations in Tropomyosin 4 Cause Macrothrombocytopenia in Mice and Humans." Blood 124, no. 21 (December 6, 2014): 571. http://dx.doi.org/10.1182/blood.v124.21.571.571.

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Abstract A genome-wide scan in nearly 70,000 individuals showed that the common SNP rs8109288 in the first intron of the human TPM4 gene exerts an effect on the volume and count of platelets (Gieger et al. Nature 2011). We isolated a mouse line with an ENU-induced missense mutation in Tpm4. Mice carrying this mutation exhibited dose-dependent macrothrombocytopenia, while other blood cell counts were normal. Bone marrow transplant experiments demonstrated that the phenotype is intrinsic to hematopoietic cells. Notably, Tpm4 insufficiency did not affect the life span or in vitro function of mutant platelets, and there was no evidence of an increased propensity to bleeding. Megakaryocyte numbers in the bone marrow were increased, although maturation as measured by ploidy appeared normal. Mutant megakaryocytes displayed altered morphology indicating fragmentation, and markedly decreased proplatelet formation in vitro. Based on Gieger et al., we examined the functional requirement for TPM4 in human megakaryocytes. We found that the localisation of TPM4 in proplatelet-forming megakaryocytes was extremely similar to the localisation in their mouse counterparts, suggesting an identical role. Furthermore, knock down of TPM4by shRNA in human megakaryocytes did not affect maturation as measured by CD41 and CD42 expression, but significantly reduced the number of proplatelet-forming cells. The occasional megakaryocyte that did form proplatelets did not exhibit the typical “beads-on-a-string” phenotype. Typically, one large bulb at the end of a protrusion or a string with no clearly distinguishable beads was observed. We therefore performed a look-up in the BRIDGE consortium database, which enrolled 542 cases with inherited bleeding and platelet disorders of unknown aetiology in the NIHR BioResource for exome sequencing. Calling of variants revealed single nucleotide variants with consequences in TPM4which were absent from ~30,000 control haplotypes, in three BRIDGE cases. Two cases with a stop codon at residue 105 and R91H variant presented with macrothrombocytopenia and mild bleeding symptoms with platelet counts of 103 and 128 x10e9/L and volumes of 15.10 and 14.00 fl, respectively. The remaining case with variant D20N (not conserved, genomic evolutionary rate profiling score of 2.68 compared to 4.62 for the other variants) had a count in the normal range (232 x10e9/L) and a reduced platelet volume of 7.20 fl. Together, these results provide compelling evidence that Tropomyosin 4 is a crucial regulator of platelet production in mice and humans, being specifically required for the terminal stages of platelet formation. Our studies demonstrate that the common intronic variant exerts a subtle effect, whilst two extremely rare variants have a more robust effect on platelet formation leading to counts and volumes at the tails of the population distribution. The lack of concordance between mice and humans with regard to bleeding may be explained by strong modifiers at loci other than TPM4. Disclosures No relevant conflicts of interest to declare.

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Meggendorfer, Manja, Wencke Walter, Claudia Haferlach, Wolfgang Kern, and Torsten Haferlach. "Challenging Blast Counts By Machine Learning Techniques and Genome Sequencing for Discriminating AML and MDS." Blood 134, Supplement_1 (November 13, 2019): 4663. http://dx.doi.org/10.1182/blood-2019-126449.

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MDS and AML are separated according to the percentage of bone marrow blasts. Although this is an arbitrary threshold, it leads to different thinking and therapeutic strategies. Following the WHO classification for myeloid neoplasms an increasing number of specific genetic aberrations are incorporated in the classification, like t(15;17), t(8;21), inv(16) or NPM1 and CEBPA mutations for AML. Some of these are classified as AML even irrespective of blast counts. Our aim was to stratify today´s AML and MDS patients by using genome sequencing data and a combination of machine learning techniques to identify the most prominent discriminative features, challenging the blast count as gold standard for discriminating AML from MDS. The analysis was based on a cohort of 1,292 patients (pts) morphologically diagnosed according to WHO classification: 591 AML and 701 MDS. Whole genome sequencing (WGS) was performed with 90x coverage for all samples to assess their mutational profiles. The Illumina tumor/unmatched normal workflow was used for variant calling. To remove the most frequent germline variants, each variant was queried against the gnomAD database, variants in non-coding regions and with global population frequencies >1% where excluded. The resulting dataset was filtered to exclude genes with a mutation frequency <1% resulting in a variant list assigned to 2,918 different genes. Additionally, the 10 most abundant cytogenetic aberrations in AML and MDS were used to train the model. The dataset was randomly divided into a training (90%) and validation (10%) set ensuring that all morphology based AML and MDS phenotypes according to WHO were present in both sets. Subsequently we applied LASSO regression to identify the features that optimize the classification accuracy of AML versus MDS. 500 models were built with 10-fold cross-validation to stratify the patients with an accuracy range from 66.7% - 95.2%. All the models differed slightly in their composition of selected features and, hence, the models with the highest accuracy (top 5%) were chosen, the selected features assessed and features that occurred in more than 50% of the models were kept to train a Naïve Bayes classifier. Using this final model to stratify patients of the validation cohort we achieved an accuracy of 83.7%. The model consisted of only 74 genetic markers, covering 8 cytogenetic aberrations and 66 affected genes. 26 of those genes belong to the COSMIC cancer gene list and of these 21 are well known markers included in myeloid screening panels. 40 genes and their variants (including rare polymorphisms, as well as variants or somatic mutations) have not been described in association with myeloid neoplasms so far. The model assigned 35/132 (27%) AML cases and 10/140 (7%) MDS cases to their respective counterparts. The median bone marrow blast count was 72% for concordant AML cases, 4% for concordant MDS cases, 44% for the falsely assigned AML cases and 8% for falsely assigned MDS patients, indicating that the blast count was lower in patients assigned to MDS instead of AML. However, the classification was based on the sample genetic background only and, hence, we grouped the model features based on relational self organizing maps (SOM) to identify entity-specific co-occurrence networks (7 AML and 4 MDS clusters, Figure 1). In AML the dominant cluster features were: normal karyotype with NPM1 mutation, t(8;21), t(15;17), inv(16), WT1 mutation, KRAS mutation, and TP53 mutation with co-occurring del(7) and del(5q). In MDS the 4 clusters were described by: del(5q), SF3B1 mutation, normal karyotype, and del(20q). All the misclassified cases showed a molecular profile that could be clearly associated with the ascertained entity-defining molecular features, explaining the divergent group assignment. Therefore, the molecular profiles indicate a considerable genetic similarity of the two diseases independent of the blast count. Considering the possible synergistic effects of co-occurring variants, the higher density of the interaction network in AML compared to MDS is noteworthy. In conclusion, our study shows that a depth of information is hidden in the exome of myeloid neoplasms that can be uncovered by machine learning techniques and allows a genetic-based classification of AML and MDS. These techniques not only challenge the morphological classification, but also suggest that blast counts might not be the best parameter for treatment decision. Disclosures Meggendorfer: MLL Munich Leukemia Laboratory: Employment. Walter:MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

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Herold, Sylvia, Thoralf Stange, Matthias Kuhn, Ingo Roeder, Christoph Röllig, Gerhard Ehninger, and Christian Thiede. "Targeted Resequencing of MLL-PTD Positive AML Patients Reveals a High Prevalence of Co-Ocurring Mutations in Epigenetic Regulator Genes." Blood 124, no. 21 (December 6, 2014): 1035. http://dx.doi.org/10.1182/blood.v124.21.1035.1035.

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Abstract Background Partial tandem duplication mutations of the Mixed Lineage Leukemia gene (MLL-PTD) can be found in about 10% of patients with AML, especially in patients with normal karyotype AML. The mutation generates a self-fusion within the N-terminal part of MLL and has been shown to be leukemogenic in mouse models. In patients, the presence of the mutation is associated with poor prognosis. Little is known on the molecular profile of patients with MLL-PTD and on the cooperating mutations. In order to identify accompanying molecular alterations, we performed whole exome sequencing (WES) of eight AML patients harbouring MLL-PTD mutations. Based on the observed alterations we then designed a custom amplicon panel and performed targeted resequencing in a cohort of 90 MLL-PTD mutated AML patients. Materials and Methods All patients included in this analysis were treated in prospective treatment protocols of the Study Alliance Leukemia (SAL). To enrich for malignant cells and to obtain germline reference material (T-cells), FACS sorting was performed on viable cells banked at diagnosis. After whole genome amplification of the primary DNA, whole exomes were enriched (TruSeq chemistry; Illumina), and paired-end sequenced using Illumina HiSeq2000 2x100 bp runs. Resulting data were mapped against human genome (Hg19). Only somatic single nucleotide variants (SNVs) were included in the final analysis. Based on the SNVs identified by whole exome sequencing (WES), a custom amplicon panel (TruSeq Custom Amplicon, TSCA, Illumina) for targeted resequencing was designed. The assay included either the entire coding region or mutational hot spots of 56 genes (Fig.1). In total, 700 targets were amplified in a single reaction for each patient and paired end sequenced on a MiSeq NGS system (Illumina). Paired end reads were BWA mapped against targeted regions and data analysis was done using the Sequence Pilot software package (JSI Medical Systems) with a 20% variant allele frequency (VAF) mutation calling cutoff. Only non-synonymous variants not specified as SNP in the db137 database and predicted as deleterious (Provean) were included in the final analysis. All variations were confirmed by Sanger sequencing. Results WES of eight MLL-PTD (7/8 FLT3-ITD negativ) patients revealed a total 490 SNVs (range 13-254 per patient). Most frequently mutated genes were DNMT3A, IDH1/2 and TET2. Somatic mutations were also found in genes rarely mutated in AML, such as ATM, GNAS, TET1 and EP300. Based on the WES-data, 90 MLL-PTD patients were screend for a panel of 56 genes using the TSCA assay, which revealed in total of 169 mutations. 18 genes were not found to be mutated and in 8 patients, no co-occurring mutations were identified. Due bad assay performance EP300, EZH1, JAK3, MLL2, MLL3 and NOTCH1 were excluded from the data analysis. Here again, the most frequently mutated genes were DNMT3A (34.4%), IDH1 (20.0%), IDH2R140 (18.9%), IDH2R172 (7.9%), TET2 (16.7%) and FLT3 (11.3%). Mutations were less frequently found in RUNX1 (8.9%) and ASXL1, SMC1A, U2AF1 (5.6% each) (Fig. 1). In addition to these known genes, most prevalent mutations were found in ATM (8.9%) as well as DNMT3B and TET1 (4.4% each). Overall, we oberserved a low frequency of mutations in typical class 1 genes such as NRAS, KRAS and FLT3, which was lower than reported in the TCGA data set. Conclusions This analysis in a large set of patients with MLL-PTD mutations did not reveal any new and specific individual mutation present in patients with this alteration. Instead, our finding of a very high prevalence of alterations in epigenetic regulator genes, found in more than 85% of patients with MLL-PTD, strongly argues for a particular disease biology in these patients. These findings might also implicate that treatment based on demethylating agents or histone-deacetylase inhibitors might be especially attractive in patients with MLL-PTD. Figure 1: Figure 1:. Distribution of mutations in MLL-PTD patients The assay included either the entire coding region or mutational hot spots of the following 56 genes; ASXL1, ATM, BCOR, BRAF, CBL, DDR1, DNMT1, DNMT3A, DNMT3B, EIF4A2, EP300, ETV6, EZH1, EZH2, FLT3, GATA1, GATA2, GNAS, HRAS, IDH1, IDH2, JAK1, JAK2, JAK3, KDM4A, KDM5A, KDM5C, KDM6A, KIT, KRAS, MET, MLL, MLL2, MLL3, NOTCH1, NOTCH4, NPM1, NRAS, PDGFRA, PDGFRB, PHF6, PTEN, PTPN11, RAD21, RUNX1, SF3A1, SF3B4, SMC1A, SMC3, SMC4, TET1, TET2, TP53, U2AF1 and WT1. Disclosures Thiede: AgenDix GmbH: Equity Ownership, Research Funding; Illumina: Research Support, Research Support Other.

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Cagirici, H. Busra, Bala Ani Akpinar, Taner Z. Sen, and Hikmet Budak. "Multiple Variant Calling Pipelines in Wheat Whole Exome Sequencing." International Journal of Molecular Sciences 22, no. 19 (September 27, 2021): 10400. http://dx.doi.org/10.3390/ijms221910400.

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The highly challenging hexaploid wheat (Triticum aestivum) genome is becoming ever more accessible due to the continued development of multiple reference genomes, a factor which aids in the plight to better understand variation in important traits. Although the process of variant calling is relatively straightforward, selection of the best combination of the computational tools for read alignment and variant calling stages of the analysis and efficient filtering of the false variant calls are not always easy tasks. Previous studies have analyzed the impact of methods on the quality metrics in diploid organisms. Given that variant identification in wheat largely relies on accurate mining of exome data, there is a critical need to better understand how different methods affect the analysis of whole exome sequencing (WES) data in polyploid species. This study aims to address this by performing whole exome sequencing of 48 wheat cultivars and assessing the performance of various variant calling pipelines at their suggested settings. The results show that all the pipelines require filtering to eliminate false-positive calls. The high consensus among the reference SNPs called by the best-performing pipelines suggests that filtering provides accurate and reproducible results. This study also provides detailed comparisons for high sensitivity and precision at individual and population levels for the raw and filtered SNP calls.

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Schischlik, Fiorella, Jelena D. Milosevic Feenstra, Elisa Rumi, Daniela Pietra, Bettina Gisslinger, Martin Schalling, Edith Bogner, Heinz Gisslinger, Mario Cazzola, and Robert Kralovics. "Fusion Gene Detection Using Whole Transcriptome Analysis in Patients with Chronic Myeloproliferative Neoplasms and Secondary Acute Myeloid Leukemia." Blood 126, no. 23 (December 3, 2015): 4093. http://dx.doi.org/10.1182/blood.v126.23.4093.4093.

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Abstract Fusion oncogenes resulting from chromosomal aberrations are common disease drivers in myeloid malignancies. The most prominent example is BCR-ABL1 fusion present in chronic myeloid leukemia, which together with essential thromobocythemia (ET), primary myelofibrosis (PMF) and polycythemia vera (PV) belongs to the classic myeloproliferative neoplasms (MPN). The BCR-ABL1 negative MPNs are driven by somatic mutations in JAK2, MPL and CALR. MPN patients can progress to acute myeloid leukemia (AML) but the transformation process is not well understood. Studies using standard karyotyping and SNP microarrays have shown that disease progression is characterized by an increase in karyotype complexity. We aimed to identify novel fusion oncogenes in patients with BCR-ABL1 negative MPN during chronic phase and disease progression in high-throughput and cost-efficient manner using RNA-seq technology. In addition this approach enabled us to perform RNA-seq variant calling for identification of gene mutations on the same cohort of patients. Whole transcriptome sequencing was performed on 121 patients (112 chronic phase MPN and 9 secondary AML samples) and 23 healthy controls in a 100 base pair paired-end manner. The cohort consisted of 44% PMF, 22% ET, 12% PV and 6% secondary AML patients. The output of three fusion detection tools (Defuse, Tophat-fusion and SOAPfuse) was combined in order to increase sensitivity. Extensive filtering steps were applied in order to enrich for cancer specific fusion events, including filtering for fusions appearing in healthy individuals, filtering for read-throughs and false positives with external databases and manual inspection of sequencing reads. The outcome of analysis for Defuse, Tophat-fusion and SOAPfuse resulted in the total of 52, 54 and 38 candidate fusions, respectively. Candidate fusions were Sanger-sequenced and for Tophat-fusion and Defuse the validation rate was 60%, while for SOAPfuse only 20% could be validated. Approximately 70% of the fusion candidates were not shared among the 3 tools which underlines the importance of selecting the union of all calls from each tool rather than the intersect. We did not observe clustering of breakpoints along the genome. Most fusion candidates could be detected in PMF which corresponds to the disease entity that was most represented in the cohort (44% of patients). No enrichment for fusions was found in 7 triple negative (no JAK2, CALR, MPL mutations) cases. 42% of chromosomal aberrations were translocations, followed by duplication (31%), inversion (14%) and deletion events (11%). Among the intragenic fusions, approximately half had genomic breakpoints less than 1 Mb apart. 70% of validated fusions were out of frame, while 28% were in frame. In the leukemic samples a higher abundance of fusions was found (4/9). Typical fusions for de novo AML were not detected within secondary AML (sAML) samples. We did not detect a recurrent fusion oncogene in our patient cohort. In a PMF patient with JAK2-V617F mutation we identified a BCR-ABL1 fusion, indicating a clonal exchange which was consistent with patient's phenotype. Another PMF patient exhibited an inversion event involving the first exon of CUX1, causing a CUX1 loss of function. Other fusions in chronic MPN patients affected genes involved in histone modifications (SMYD3-AHCTF1, KDM4B-CYHR1). In post-MPN AML patients we identified a somatic in frame-fusion involving INO80D and GPR1 and a fusion truncating the first 3 exons of RUNX2 (XPO5-RUNX2). The high quality of RNA sequencing data, allowed us to set up a variant detection workflow that will be compared with matched samples that have been exome sequenced. Preliminary results could demonstrate that mutations in the JAK2 gene in a cohort of 96 patients were all correctly recalled, emphasizing its sensitivity. Fusion events among patients in chronic phase MPN are rare and the majority of these events imply loss of function of both fusion gene partners. This approach adds valuable information on the true frequency of inactivation of genes such as CUX1 in patients, as small inversions like the one described above would not be detectable by other methods. Detection of a subclone with BCR-ABL1 fusion underlines the strength of the fusion detection workflow for diagnostic purposes. Typical de novo AML fusions were not found in sAML and further suggests that de novo AML and sAML are distinct disease entities on a genetic level. Disclosures Gisslinger: Janssen Cilag: Honoraria, Speakers Bureau; Sanofi Aventis: Consultancy; AOP ORPHAN: Consultancy, Honoraria, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Research Funding, Speakers Bureau; Novartis: Honoraria, Research Funding, Speakers Bureau; Geron: Consultancy. Kralovics:AOP Orphan: Research Funding; Qiagen: Membership on an entity's Board of Directors or advisory committees.

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Verrou, Kleio-Maria, Georgios A. Pavlopoulos, and Panagiotis Moulos. "Protocol for unbiased, consolidated variant calling from whole exome sequencing data." STAR Protocols 3, no. 2 (June 2022): 101418. http://dx.doi.org/10.1016/j.xpro.2022.101418.

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Nagao, Yuhei, Naoya Mimura, June Takeda, Motohiko Oshima, Kenichi Yoshida, Yusuke Shiozawa, Kazumasa Aoyama, et al. "Distinctive Genetic Features of Plasma Cells in POEMS Syndrome." Blood 128, no. 22 (December 2, 2016): 4404. http://dx.doi.org/10.1182/blood.v128.22.4404.4404.

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Abstract Introduction: Polyneuropathy, organomegaly, endocrinopathy, monoclonal gammopathy, and skin changes (POEMS) syndrome is a rare paraneoplastic disease due to an underlying monoclonal plasma cell (PC) dyscrasia. Despite of dynamic symptoms associated with highly elevated VEGF, monoclonal PCs are thought to be quite small, and pathogenic significance of these PCs remains undetermined. In this study, we performed whole exome sequencing (WES), target sequencing, and RNA sequencing of PCs in patients with POEMS syndrome in order to define its genetic profiles. Methods: Patients diagnosed with POEMS syndrome at Chiba University Hospital from July 2014 to June 2016 were enrolled. DNA was extracted from either PCs which were isolated from patients' bone marrow (BM) using CD138 MACS (Miltenyi) or buccal cells as controls. WES and target sequencing were performed using HiSeq2500 (Illumina) and MiSeq (Illumina), respectively. The data of WES and target sequencing were analyzed by Empirical Bayesian mutation Calling (EBCall). Copy number was analyzed using the data of WES. RNA sequencing of PCs isolated by MACS and FACS sorting was conducted using HiSeq 1500 (Illumina). PCs from some patients diagnosed with multiple myeloma (MM) and monoclonal gammopathy of undetermined significance (MGUS) were also collected as controls for RNA sequencing. Results: Twenty POEMS patients (M:F 12:8, mean age 42.6, range 16-78; 15 newly diagnosed, 5 refractory or relapsed cases) were included in this study. Regarding the types of M protein, 55% (11/20) were IgA-λ, 25% (5/20) were IgG-λ, and each individual case of the following; IgA-λ+IgG-λ, BJP-λ, IgG-κ, and Castleman's variant with no M protein. The mean serum VEGF was 6,471 pg/ml (range 1,190-13,800), and the mean PCs percentage in the BM was 4.4% (range 0.8-10.5). WES was performed in 15 cases; a total of 359 somatic mutations in 334 genes were revealed in 93.3% of cases (14/15) with a mean number of 23.9 (range 0-119) in each. All these mutated genes were significantly enriched in several pathways related to cell adhesion. Importantly, frequently mutated genes in MM such as NRAS, KRAS, and TP53 were not identified. Among all mutations, 1.7% were frameshift insertions, 2.0% were frameshift deletions, 4.2% were stop gains, 0.8% were non-frameshift deletions, 60.2% were other non-synonymous single nucleotide variants (SNVs), 29.5% were synonymous SNVs, and 1.7% were splicing mutations which were within 2-bp of a splicing junction. Copy-number variations were detected in 33.3% of cases (5/10) including -13 (2 cases), +1q (2 cases), and hyperdiploidy (2 cases). To carry out target sequencing in all 20 cases, we defined 51 target genes which included recurrently mutated genes from our WES data, frequently mutated genes in hematopoietic and lymphoid tissues according to the database (COSMIC), and 15 frequently mutated genes in MM (NRAS, KRAS, TP53, BRAF, CDKN2C, FGFR3, BIRC3, DIS3, CYLD, KDM6A, LRP1B, FAM46C, COL6A3, DNAH5, and KRT6A). A total of 60 somatic mutations were revealed in 65% of cases (13/20), and 9 new somatic mutations were found in the cases in which WES was also performed. Ten recurrently mutated genes were identified; KLHL6 in 20% of cases (4/20), each of LTB, RYR1 in 15% of cases (3/20), and each of EHD1, EML4, HEPHL1, HIPK1, PCDH10, USH2A, and ZNF645 in 10% of cases (2/20). Among frequently mutated genes in MM, only 3 genes (FAM46C, LRP1B, and DNAH5) were mutated, each in a single case. We finally conducted RNA sequencing of the FACS-sorted PCs in 5 POEMS patients compared to 5 MGUS and 4 MM patients. Upregulated genes were significantly enriched in some gene sets, gene ontology terms, and pathways related to immune response and cell adhesion, whereas downregulated genes were related to tumorigenesis. Of note, VEGF was not significantly upregulated in POEMS patients. Principal component analysis distinguished the 3 disease groups of patients with marginal overlaps between POEMS and MGUS, and also MGUS and MM. Conclusions: Our data clearly demonstrate that the genetic profiles of PCs in POEMS syndrome are distinct from those in MM and MGUS. Notably, PCs may not be the main source of extremely elevated VEGF in POMES syndrome. On-going further investigation will help clarify the molecular pathogenesis of POEMS syndrome. Disclosures Ogawa: Takeda Pharmaceuticals: Consultancy, Research Funding; Sumitomo Dainippon Pharma: Research Funding; Kan research institute: Consultancy, Research Funding.

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Zhang, Yanfeng, Bingshan Li, Chun Li, Qiuyin Cai, Wei Zheng, and Jirong Long. "Improved Variant Calling Accuracy by Merging Replicates in Whole-Exome Sequencing Studies." BioMed Research International 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/319534.

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In large scale population-based whole-exome sequencing (WES) studies, there are some samples occasionally sequenced two or more times due to a variety of reasons. To investigate how to efficiently utilize these duplicated sequencing data, we conducted comprehensive evaluation of variant calling strategies. 92 samples subjected to WES twice were selected from a large population study. These 92 duplicated samples were divided into two groups: group H consisting of the higher sequencing depth for each subject and group L consisting of the lower depth for each subject. The merged samples for each subject were put in a third group M. Using the GATK multisample toolkit, we compared variant calling accuracy among three strategies. Hierarchical clustering analysis indicated that the two replicates for each subject showed high homogeneity. The comparative analyses on the basis of heterozygous-homozygous ratio (Hete/Homo), transition-transversion ratio (Ti/Tv), and overlapping rate with the 1000 Genomes Project consistently showed that the data quality of the SNPs detected from the M group was more accurate than that of SNPs detected from the H and L groups. These results suggested that merging homogeneous duplicated exomes instead of using one of them could improve variant calling accuracy.

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Herzeel, Charlotte, Pascal Costanza, Dries Decap, Jan Fostier, Roel Wuyts, and Wilfried Verachtert. "Multithreaded variant calling in elPrep 5." PLOS ONE 16, no. 2 (February 4, 2021): e0244471. http://dx.doi.org/10.1371/journal.pone.0244471.

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We present elPrep 5, which updates the elPrep framework for processing sequencing alignment/map files with variant calling. elPrep 5 can now execute the full pipeline described by the GATK Best Practices for variant calling, which consists of PCR and optical duplicate marking, sorting by coordinate order, base quality score recalibration, and variant calling using the haplotype caller algorithm. elPrep 5 produces identical BAM and VCF output as GATK4 while significantly reducing the runtime by parallelizing and merging the execution of the pipeline steps. Our benchmarks show that elPrep 5 speeds up the runtime of the variant calling pipeline by a factor 8-16x on both whole-exome and whole-genome data while using the same hardware resources as GATK4. This makes elPrep 5 a suitable drop-in replacement for GATK4 when faster execution times are needed.

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Bao, Riyue, Lei Huang, Jorge Andrade, Wei Tan, Warren A. Kibbe, Hongmei Jiang, and Gang Feng. "Review of Current Methods, Applications, and Data Management for the Bioinformatics Analysis of Whole Exome Sequencing." Cancer Informatics 13s2 (January 2014): CIN.S13779. http://dx.doi.org/10.4137/cin.s13779.

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The advent of next-generation sequencing technologies has greatly promoted advances in the study of human diseases at the genomic, transcriptomic, and epigenetic levels. Exome sequencing, where the coding region of the genome is captured and sequenced at a deep level, has proven to be a cost-effective method to detect disease-causing variants and discover gene targets. In this review, we outline the general framework of whole exome sequence data analysis. We focus on established bioinformatics tools and applications that support five analytical steps: raw data quality assessment, preprocessing, alignment, post-processing, and variant analysis (detection, annotation, and prioritization). We evaluate the performance of open-source alignment programs and variant calling tools using simulated and benchmark datasets, and highlight the challenges posed by the lack of concordance among variant detection tools. Based on these results, we recommend adopting multiple tools and resources to reduce false positives and increase the sensitivity of variant calling. In addition, we briefly discuss the current status and solutions for big data management, analysis, and summarization in the field of bioinformatics.

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Dolled-Filhart, Marisa P., Michael Lee, Chih-wen Ou-yang, Rajini Rani Haraksingh, and Jimmy Cheng-Ho Lin. "Computational and Bioinformatics Frameworks for Next-Generation Whole Exome and Genome Sequencing." Scientific World Journal 2013 (2013): 1–10. http://dx.doi.org/10.1155/2013/730210.

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It has become increasingly apparent that one of the major hurdles in the genomic age will be the bioinformatics challenges of next-generation sequencing. We provide an overview of a general framework of bioinformatics analysis. For each of the three stages of (1) alignment, (2) variant calling, and (3) filtering and annotation, we describe the analysis required and survey the different software packages that are used. Furthermore, we discuss possible future developments as data sources grow and highlight opportunities for new bioinformatics tools to be developed.

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Martinez, Nerea, Ignacio Varela, Jose P. Vaque, Sophia Derdak, Sergi Beltran, Manuela Mollejo, Margarita Sanchez-Beato, et al. "Mutational Status of Splenic Marginal Zone Lymphoma Revealed by Whole Exome Sequencing." Blood 120, no. 21 (November 16, 2012): 2698. http://dx.doi.org/10.1182/blood.v120.21.2698.2698.

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Abstract Abstract 2698 Background: Splenic marginal zone lymphoma (SMZL) is a small B cell neoplasm whose molecular pathogenesis is still unknown. It has a relatively indolent course, but a fraction of the cases may show an aggressive behavior. The lack of comprehensive molecular analysis for SMZL precludes the development of targeted therapy. Here we studied the mutational status of 6 SMZL samples using Whole Exome Next Generation Sequencing. Methods: Genomic DNA was extracted from splenic tumor or peripheral blood samples and oral mucosa as the corresponding non-tumor control. Whole exome sequencing was performed at CNAG (Barcelona, Spain) following standard protocols for high-throughput paired-end sequencing on the Illumina HiSeq2000 instruments (Illumina Inc., San Diego, CA). The variant calling was performed using an in house written software calling potential mutations showing a minimum independent multi-aligner evidence. Results: We performed paired-end-76pb whole exome sequencing on 6 SMZL samples and the corresponding normal counterpart. Three of the samples corresponded to CD19 isolated cells from peripheral blood, while other three corresponded to spleen freshly frozen tissue. The mean coverage obtained was 104.07 (82.46–119.59) with a mean of 91.41% (90.41–93.73) of bases with at least 15× coverage. After filtering, 237 substitutions and 21 indels where obtained. No recurrent variation was found. Six of the variations found here were already described in other malignancies. Variations were classified into silent (75), missense (147), nonsense (8), and essential splice (5), according to their potential functional effect, and into tolerated (54) and deleterious (76) according to the “variant effect predictor” tool of Ensembl Genome Browser. Whole exome sequencing permitted us to identify variations in several genes of TLR/NFkB pathway (Myd88, Peli3), BCR (Myd88, Arid3A) or signal transduction (ARHGAP32), essential pathways for B-cell differentiation. These variations and other involving selected genes, such as the Bcl6 repressor BCOR, were validated by capillary sequencing. These results were confirmed and expanded in a second series of 10 new cases by exome sequencing. Conclusions: SMZL samples contain somatic mutation involving genes regulating BCR signaling, TLR/NFKB pathways and chromatin remodeling. Disclosures: No relevant conflicts of interest to declare.

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Tung, Nguyen Van, Nguyen Thi Kim Lien, and Nguyen Huy Hoang. "A comparison of three variant calling pipelines using simulated data." Academia Journal of Biology 43, no. 2 (June 30, 2021): 47–53. http://dx.doi.org/10.15625/2615-9023/16006.

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Advances in next generation sequencing allow us to do DNA sequencing rapidly at a relatively low cost. Multiple bioinformatics methods have been developed to identify genomic variants from whole genome or whole exome sequencing data. The development of better variant calling methodologies is limited by the difficulty of assessing the accuracy and completeness of a new method. Normally, computational methods can be benchmarked using simulated data which allows us to generate as much data as desired and under controlled scenarios. In this study, we compared three variant calling pipelines: Samtools/VarScan, Samtools/Bcftools, and Picard/GATK using two simulated datasets. The result showed a significant difference between the three pipelines in two cases. In Chromosome 6 dataset, GATK and Bcftools pipelines detected more than 90% of variants. Meanwhile, only 82.19% of mutations were detected by VarScan. In NA12878 datasets, the result showed GATK pipeline was more sensitive than Bcftools and Varscan pipeline. All pipelines showed a high Positive Predictive Value. Moreover, by a measure of run time, VarScan was the highest pipeline but GATK has an option for multithreading which is a way to make a program run faster. Therefore, GATK is more effective than Bcftools and Varscan to variant calling with a lower coverage dataset.

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Mizrahi-Man, Orna, Marcos H. Woehrmann, Teresa A. Webster, Jeremy Gollub, Adrian Bivol, Sara M. Keeble, Katherine H. Aull, et al. "Novel genotyping algorithms for rare variants significantly improve the accuracy of Applied Biosystems™ Axiom™ array genotyping calls: Retrospective evaluation of UK Biobank array data." PLOS ONE 17, no. 11 (November 17, 2022): e0277680. http://dx.doi.org/10.1371/journal.pone.0277680.

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The UK Biobank genotyped about 500k participants using Applied Biosystems Axiom microarrays. Participants were subsequently sequenced by the UK Biobank Exome Sequencing Consortium. Axiom genotyping was highly accurate in comparison to sequencing results, for almost 100,000 variants both directly genotyped on the UK Biobank Axiom array and via whole exome sequencing. However, in a study using the exome sequencing results of the first 50k individuals as reference (truth), it was observed that the positive predictive value (PPV) decreased along with the number of heterozygous array calls per variant. We developed a novel addition to the genotyping algorithm, Rare Heterozygous Adjusted (RHA), to significantly improve PPV in variants with minor allele frequency below 0.01%. The improvement in PPV was roughly equal when comparing to the exome sequencing of 50k individuals, or to the more recent ~200k individuals. Sensitivity was higher in the 200k data. The improved calling algorithm, along with enhanced quality control of array probesets, significantly improved the positive predictive value and the sensitivity of array data, making it suitable for the detection of ultra-rare variants.

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Huang, Weitai, Yu Amanda Guo, Karthik Muthukumar, Probhonjon Baruah, Mei Mei Chang, and Anders Jacobsen Skanderup. "SMuRF: portable and accurate ensemble prediction of somatic mutations." Bioinformatics 35, no. 17 (January 12, 2019): 3157–59. http://dx.doi.org/10.1093/bioinformatics/btz018.

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Abstract Summary Somatic Mutation calling method using a Random Forest (SMuRF) integrates predictions and auxiliary features from multiple somatic mutation callers using a supervised machine learning approach. SMuRF is trained on community-curated matched tumor and normal whole genome sequencing data. SMuRF predicts both SNVs and indels with high accuracy in genome or exome-level sequencing data. Furthermore, the method is robust across multiple tested cancer types and predicts low allele frequency variants with high accuracy. In contrast to existing ensemble-based somatic mutation calling approaches, SMuRF works out-of-the-box and is orders of magnitudes faster. Availability and implementation The method is implemented in R and available at https://github.com/skandlab/SMuRF. SMuRF operates as an add-on to the community-developed bcbio-nextgen somatic variant calling pipeline. Supplementary information Supplementary data are available at Bioinformatics online.

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LaRochelle, Ethan, Donald Green, Edward Hughes, Diana Toledo, Parth Shah, Gregory Tsongalis, and Wahab Khan. "Developing an automated analysis framework to benchmark variant calling sensitivity and specificity of whole exome sequencing." Molecular Genetics and Metabolism 132 (April 2021): S233. http://dx.doi.org/10.1016/s1096-7192(21)00443-1.

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Ahn, Yong Ju, Kesavan Markkandan, In-Pyo Baek, Seyoung Mun, Wooseok Lee, Heui-Soo Kim, and Kyudong Han. "An efficient and tunable parameter to improve variant calling for whole genome and exome sequencing data." Genes & Genomics 40, no. 1 (August 29, 2017): 39–47. http://dx.doi.org/10.1007/s13258-017-0608-6.

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Oh, Sehyun, Ludwig Geistlinger, Marcel Ramos, Martin Morgan, Levi Waldron, and Markus Riester. "Reliable Analysis of Clinical Tumor-Only Whole-Exome Sequencing Data." JCO Clinical Cancer Informatics, no. 4 (September 2020): 321–35. http://dx.doi.org/10.1200/cci.19.00130.

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PURPOSE Allele-specific copy number alteration (CNA) analysis is essential to study the functional impact of single-nucleotide variants (SNVs) and the process of tumorigenesis. However, controversy over whether it can be performed with sufficient accuracy in data without matched normal profiles and a lack of open-source implementations have limited its application in clinical research and diagnosis. METHODS We benchmark allele-specific CNA analysis performance of whole-exome sequencing (WES) data against gold standard whole-genome SNP6 microarray data and against WES data sets with matched normal samples. We provide a workflow based on the open-source PureCN R/Bioconductor package in conjunction with widely used variant-calling and copy number segmentation algorithms for allele-specific CNA analysis from WES without matched normals. This workflow further classifies SNVs by somatic status and then uses this information to infer somatic mutational signatures and tumor mutational burden (TMB). RESULTS Application of our workflow to tumor-only WES data produces tumor purity and ploidy estimates that are highly concordant with estimates from SNP6 microarray data and matched normal WES data. The presence of cancer type–specific somatic mutational signatures was inferred with high accuracy. We also demonstrate high concordance of TMB between our tumor-only workflow and matched normal pipelines. CONCLUSION The proposed workflow provides, to our knowledge, the only open-source option with demonstrated high accuracy for comprehensive allele-specific CNA analysis and SNV classification of tumor-only WES. An implementation of the workflow is available on the Terra Cloud platform of the Broad Institute (Cambridge, MA).

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Peculis, Raitis, Vita Rovite, Kaspars Megnis, Inga Balcere, Austra Breiksa, Jurijs Nazarovs, Janis Stukens, et al. "Whole exome sequencing reveals novel risk genes of pituitary neuroendocrine tumors." PLOS ONE 17, no. 8 (August 26, 2022): e0265306. http://dx.doi.org/10.1371/journal.pone.0265306.

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Somatic genetic alterations in pituitary neuroendocrine tumors (PitNET) tissues have been identified in several studies, but detection of overlapping somatic PitNET candidate genes is rare. We sequenced and by employing multiple data analysis methods studied the exomes of 15 PitNET patients to improve discovery of novel factors involved in PitNET development. PitNET patients were recruited to the study before PitNET removal surgery. For each patient, two samples for DNA extraction were acquired: venous blood and PitNET tissue. Exome sequencing was performed using Illumina NexSeq 500 sequencer and data analyzed using two separate workflows and variant calling algorithms: GATK and Strelka2. A combination of two data analysis pipelines discovered 144 PitNET specific somatic variants (mean = 9.6, range 0–19 per PitNET) of which all were SNVs. Also, we detected previously known GNAS PitNET mutation and identified somatic variants in 11 genes, which have contained somatic variants in previous WES and WGS studies of PitNETs. Noteworthy, this is the third study detecting somatic variants in gene RYR1 in the exomes of PitNETs. In conclusion, we have identified two novel PitNET candidate genes (AC002519.6 and AHNAK) with recurrent somatic variants in our PitNET cohort and found 13 genes overlapping from previous PitNET studies that contain somatic variants. Our study demonstrated that the use of multiple sequencing data analysis pipelines can provide more accurate identification of somatic variants in PitNETs.

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Osei, Wilberforce A., Tyler Shugg, Reynold C. Ly, Steven M. Bray, Benjamin A. Salisbury, Ryan R. Ratcliff, Victoria M. Pratt, Ibrahim Numanagić, and Todd Skaar. "Abstract 1151: Pharmacogenomics genotyping from clinical somatic whole exome sequencing: Aldy, a computational tool." Cancer Research 82, no. 12_Supplement (June 15, 2022): 1151. http://dx.doi.org/10.1158/1538-7445.am2022-1151.

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Abstract Background Pharmacogenomics (PGx) testing can reduce toxicities and improve efficacy of several drugs used to treat cancer and associated symptoms. PGx results can be determined from germline whole-exome sequencing (WES), but somatic mutations may cause discordance between tumor and germline DNA. Since clinical diagnostic sequencing in oncology frequently only includes tumor DNA, there would be clinical value in calling germline PGx genotypes from tumor DNA. Thus, the purpose of this study was to assess the feasibility of using somatic WES data to call germline PGx genotypes. Methods Germline and somatic WES data were obtained as part of the clinical workflow for 64 patients treated at the solid molecular tumor board clinic at Indiana University. Aldy v3.3 was implemented in LifeOmic’s Precision Health Cloud™ to call PGx genotypes from somatic WES. Somatic Aldy calls were compared with previously validated Aldy germline calls for 8 genes: CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, CYP4F2, DPYD, and TPMT. Somatic read depth was >100x, except for the intronic CYP3A4*22 variant, which was >30x. Results Somatic and germline Aldy calls were compared for a total of 512 genotypes and 56 (11%) calls were discordant. Discordant calls were most common for CYP2B6 (23.4%), followed by CYP2D6 (14.1%), CYP2C19 (10.9%), CYP2C8 (6.3%), and DPYD (6.3%). In contrast, all Aldy calls were concordant for CYP3A5 and TPMT. 38 out of 64 subjects (59%) had discordant calls for at least one gene. The most common first cancer diagnoses in our cohort were colorectal (9.3%), breast (7.8%), and pancreatic (7.8%), and the rates of discordant Aldy calls did not differ by cancer type (p>0.05 for all cancer types). Based on our analyses of discordant calls, we anticipate that adjusting Aldy’s thresholds for variant calling may allow Aldy to determine genotypes from somatic WES data. Conclusion In most cases, genotype calls of drug metabolism genes from tumor DNA reflected the germline genotypes; however, additional work needs to be done to determine if the remaining discordant calls can be corrected by modifying the informatics tools or if they are due to somatic mutations. Citation Format: Wilberforce A. Osei, Tyler Shugg, Reynold C. Ly, Steven M. Bray, Benjamin A. Salisbury, Ryan R. Ratcliff, Victoria M. Pratt, Ibrahim Numanagić, Todd Skaar. Pharmacogenomics genotyping from clinical somatic whole exome sequencing: Aldy, a computational tool [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1151.

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Wu, Hsin-Ta, Ekaterina Kalashnikova, Samay Mehta, Raheleh Salari, Himanshu Sethi, Bernhard Zimmermann, Paul R. Billings, and Alexey Aleshin. "Characterization of clonal hematopoiesis of indeterminate potential mutations from germline whole exome sequencing data." Journal of Clinical Oncology 38, no. 15_suppl (May 20, 2020): 1525. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.1525.

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1525 Background: Clonal hematopoiesis of Indeterminate Potential (CHIP) is an age-related phenomenon where somatic mutations accumulate in cells of the blood or bone marrow. It is a source of biological noise that causes false-positives in ctDNA analysis and is present in up to 20% of individuals over the age of 70. The presence of CHIP has been linked to an increased risk of hematologic cancers and cardiovascular disease. The Signatera assay filters CHIP mutations through tumor tissue and germline sequencing thereby reducing false-positive results and focuses on tumor-specific mutations for each patient. Methods: Whole exome sequencing data (average depth ~250x) analyzed from patients’ buffy coat (n = 159) was used to characterize CHIP mutations. Variant calling was performed using Freebayes variant caller with allele frequency threshold between 1% and 10%. Following which variant annotation and selection was performed based on the top 54 genes that are most implicated in myeloid disorders. The selected variants were further screened based on the reported variants in the literature and/or the Catalog of Somatic Mutations in Cancer (COSMIC). Results: The analysis revealed an average of 0.14 (0-2) CHIP mutations per patient with an average variant allele frequency of 3.49% (1%-8.5%). The most common CHIP mutations were observed in DNMT3A, (n = 17), TET2 (n = 7) and TP53 (n = 7) genes. The percentage of patients with at least 1 mutation found in DNMT3A, TET2, and TP53 were 4.2%, 1.94%, and 1.38%, respectively. Other genes containing CHIP mutation included CEBPA, ETV6, HRAS, PDGFRA, NRAS, KMT2A, EZH2, GATA2, GNAS at a frequency below 1%. CHIP mutations were not observed in patients younger than 40 years, but they increased in frequency with every decade of life thereafter. The incidence of CHIP increased from 0.04 for the 40-50 yrs age group to 0.18 for individuals older than 60. Further analysis of associations between incidence of CHIP and cancer type, prior exposure to chemotherapy as well as longitudinal evolution of CHIP mutations during cytotoxic treatment are underway and will be presented. Conclusions: CHIP, a common finding in the elderly population is an important factor to consider in ctDNA analysis and most frequently involves DNMT3A, TET2, and TP53 genes. The frequency of CHIP can be impacted by a number of other factors such as cytotoxic chemo- or radiotherapy.

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de Boer, Elke, Charlotte W. Ockeloen, Leslie Matalonga, Rita Horvath, Enzo Cohen, Isabel Cuesta, Daniel Danis, et al. "A MT-TL1 variant identified by whole exome sequencing in an individual with intellectual disability, epilepsy, and spastic tetraparesis." European Journal of Human Genetics 29, no. 9 (June 1, 2021): 1359–68. http://dx.doi.org/10.1038/s41431-021-00900-2.

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AbstractThe genetic etiology of intellectual disability remains elusive in almost half of all affected individuals. Within the Solve-RD consortium, systematic re-analysis of whole exome sequencing (WES) data from unresolved cases with (syndromic) intellectual disability (n = 1,472 probands) was performed. This re-analysis included variant calling of mitochondrial DNA (mtDNA) variants, although mtDNA is not specifically targeted in WES. We identified a functionally relevant mtDNA variant in MT-TL1 (NC_012920.1:m.3291T > C; NC_012920.1:n.62T > C), at a heteroplasmy level of 22% in whole blood, in a 23-year-old male with severe intellectual disability, epilepsy, episodic headaches with emesis, spastic tetraparesis, brain abnormalities, and feeding difficulties. Targeted validation in blood and urine supported pathogenicity, with heteroplasmy levels of 23% and 58% in index, and 4% and 17% in mother, respectively. Interestingly, not all phenotypic features observed in the index have been previously linked to this MT-TL1 variant, suggesting either broadening of the m.3291T > C-associated phenotype, or presence of a co-occurring disorder. Hence, our case highlights the importance of underappreciated mtDNA variants identifiable from WES data, especially for cases with atypical mitochondrial phenotypes and their relatives in the maternal line.

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König, Eva, Johannes Rainer, Vinicius Verri Hernandes, Giuseppe Paglia, Fabiola Del Greco M., Daniele Bottigliengo, Xianyong Yin, et al. "Whole Exome Sequencing Enhanced Imputation Identifies 85 Metabolite Associations in the Alpine CHRIS Cohort." Metabolites 12, no. 7 (June 29, 2022): 604. http://dx.doi.org/10.3390/metabo12070604.

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Metabolites are intermediates or end products of biochemical processes involved in both health and disease. Here, we take advantage of the well-characterized Cooperative Health Research in South Tyrol (CHRIS) study to perform an exome-wide association study (ExWAS) on absolute concentrations of 175 metabolites in 3294 individuals. To increase power, we imputed the identified variants into an additional 2211 genotyped individuals of CHRIS. In the resulting dataset of 5505 individuals, we identified 85 single-variant genetic associations, of which 39 have not been reported previously. Fifteen associations emerged at ten variants with >5-fold enrichment in CHRIS compared to non-Finnish Europeans reported in the gnomAD database. For example, the CHRIS-enriched ETFDH stop gain variant p.Trp286Ter (rs1235904433-hexanoylcarnitine) and the MCCC2 stop lost variant p.Ter564GlnextTer3 (rs751970792-carnitine) have been found in patients with glutaric acidemia type II and 3-methylcrotonylglycinuria, respectively, but the loci have not been associated with the respective metabolites in a genome-wide association study (GWAS) previously. We further identified three gene-trait associations, where multiple rare variants contribute to the signal. These results not only provide further evidence for previously described associations, but also describe novel genes and mechanisms for diseases and disease-related traits.

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Hong, Y. B., J. Jung, S. C. Jung, K. W. Chung, and B. O. Choi. "Application of variant-calling algorithms for Mendelian disorders: lessons from whole-exome sequencing in Charcot-Marie-Tooth disease." Clinical Genetics 86, no. 3 (October 17, 2013): 298–99. http://dx.doi.org/10.1111/cge.12281.

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Bartha and Győrffy. "Comprehensive Outline of Whole Exome Sequencing Data Analysis Tools Available in Clinical Oncology." Cancers 11, no. 11 (November 4, 2019): 1725. http://dx.doi.org/10.3390/cancers11111725.

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Whole exome sequencing (WES) enables the analysis of all protein coding sequences in the human genome. This technology enables the investigation of cancer-related genetic aberrations that are predominantly located in the exonic regions. WES delivers high-throughput results at a reasonable price. Here, we review analysis tools enabling utilization of WES data in clinical and research settings. Technically, WES initially allows the detection of single nucleotide variants (SNVs) and copy number variations (CNVs), and data obtained through these methods can be combined and further utilized. Variant calling algorithms for SNVs range from standalone tools to machine learning-based combined pipelines. Tools for CNV detection compare the number of reads aligned to a dedicated segment. Both SNVs and CNVs help to identify mutations resulting in pharmacologically druggable alterations. The identification of homologous recombination deficiency enables the use of PARP inhibitors. Determining microsatellite instability and tumor mutation burden helps to select patients eligible for immunotherapy. To pave the way for clinical applications, we have to recognize some limitations of WES, including its restricted ability to detect CNVs, low coverage compared to targeted sequencing, and the missing consensus regarding references and minimal application requirements. Recently, Galaxy became the leading platform in non-command line-based WES data processing. The maturation of next-generation sequencing is reinforced by Food and Drug Administration (FDA)-approved methods for cancer screening, detection, and follow-up. WES is on the verge of becoming an affordable and sufficiently evolved technology for everyday clinical use.

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Froukh, Tawfiq, and Ammar Hawwari. "Autosomal Recessive Non-syndromic Keratoconus: Homozygous Frameshift Variant in the Candidate Novel Gene GALNT14." Current Molecular Medicine 19, no. 9 (October 11, 2019): 683–87. http://dx.doi.org/10.2174/1566524019666190730095630.

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Background: Keratoconus (KC) is usually bilateral, noninflammatory progressive corneal ectasia in which the cornea becomes progressively thin and conical. Despite the strong evidence of genetic contribution in KC, the etiology of KC is not understood in most cases. Methods: In this study, we used whole-exome sequencing to identify the genetic cause of KC in two sibs in a consanguineous family. The Homozygous frameshift variant NM_001253826.1:c.60delC;p.Leu21Cysfs*6 was identified in the gene Nacetylgalactosaminyltransferase 14 (GALNT14). The variant does not exist in all public databases neither in our internal exome database. Moreover, no database harbours homozygous loss of function variants in the candidate gene. Result: GALNT14 catalyses the initial reaction in O-linked oligosaccharide biosynthesis, the transfer of an N-acetyl-D- galactosamine residue to a serine or threonine residue on target proteins especially Mucins. Conclusion: As alterations of mucin’s glycosylation are linked to a number of eye diseases, we demonstrate in this study an association between the truncated protein GALNT14 and KC.

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Hassan, Faaiz ul, Mohammed M. Aljeldah, Fozia Fozia, Mubbashir Hussain, Taj Ali Khan, Sami Siraj, Ijaz Ahmad, et al. "Whole Exome Sequence Analysis for Inborn Errors of IL-12/IFN-γ Axis in Patient with Recurrent Typhoid Fever." BioMed Research International 2023 (February 17, 2023): 1–6. http://dx.doi.org/10.1155/2023/1761283.

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Background. The IL-12/IFN-γ axis pathways play a vital role in the control of intracellular pathogens such as Salmonella typhi. Objective. The study is aimed at using whole exome sequencing (WES) to screen out genetic defects in IL-12/IFN-γ axis in patients with recurrent typhoid fever. Methods. WES using next-generation sequencing was performed on a single patient diagnosed with recurrent typhoid fever. Following alignment and variant calling, exomes were screened for mutations in 25 genes that are involved in the IL-12/IFN-γ axis pathway. Each variant was assessed by using various bioinformatics mutational analysis tools such as SIFT, Polyphen2, LRT, MutationTaster, and MutationAssessor. Results. Out of 25 possible variations in the IL-12/IFN-γ axis genes, only 2 probable disease-causing mutations were identified. These variations were rare and include mutations in IL23R and ZNFX I. Other pathogenic mutations were found, but they were not considered likely to cause disease based on various mutation predictors. Conclusion. Applying WES to the patient with recurrent typhoid fever detects variants that are not much important as other genes in the IL-12/IFN-γ axis. Results of the current study suggest that a large population sizes would be needed to examine the functional relevance of IL-12/IFN-γ axis genes with recurrent typhoid fever.

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Schneider, Bryan P., Leigh Anne Stout, Santosh Philips, Courtney Schroeder, Susanna F. Scott, Cynthia Hunter, Nawal Kassem, Patrick J. Kiel, and Milan Radovich. "Implications of Incidental Germline Findings Identified In the Context of Clinical Whole Exome Sequencing for Guiding Cancer Therapy." JCO Precision Oncology, no. 4 (October 2020): 1109–21. http://dx.doi.org/10.1200/po.19.00354.

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PURPOSE Identification of incidental germline mutations in the context of next-generation sequencing is an unintended consequence of advancing technologies. These data are critical for family members to understand disease risks and take action. PATIENTS AND METHODS A retrospective cohort analysis was conducted of 1,028 adult patients with metastatic cancer who were sequenced with tumor and germline whole exome sequencing (WES). Germline variant call files were mined for pathogenic/likely pathogenic (P/LP) variants using the ClinVar database and narrowed to high-quality submitters. RESULTS Median age was 59 years, with 16% of patients ≤ 45 years old. The most common tumor types were breast cancer (12.5%), colorectal cancer (11.5%), sarcoma (9.3%), prostate cancer (8.4%), and lung cancer (6.6%). We identified 3,427 P/LP variants in 471 genes, and 84% of patients harbored one or more variant. One hundred thirty-two patients (12.8%) carried a P/LP variant in a cancer predisposition gene, with BRCA2 being the most common (1.6%). Patients with breast cancer were most likely to carry a P/LP variant (19.2%). One hundred ten patients (10.7%) carried a P/LP variant in a gene that would be recommended by the American College of Medical Genetics and Genomics to be reported as a result of clinical actionability, with the most common being ATP7B (2.7%), BRCA2 (1.6%), MUTYH (1.4%), and BRCA1 (1%). Of patients who carried a P/LP variant in a cancer predisposition gene, only 53% would have been offered correct testing based on current clinical practice guidelines. Of 471 mutated genes, 231 genes had a P/LP variant identified in one patient, demonstrating significant genetic heterogeneity. CONCLUSION The majority of patients undergoing clinical cancer WES harbor a pathogenic germline variation. Identification of clinically actionable germline findings will create additional burden on oncology clinics as broader WES becomes common.

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Kaur, Jaspreet, Darshan S. Chandrashekar, Zsuzsanna Varga, Emiel Janssen, Khanjan Gandhi, Karuna Mittal, Umay Kiraz, Sooryanarayana Varambally, and Ritu Aneja. "Abstract P3-09-14: Whole exome sequencing of matched primary and metastatic triple-negative breast cancer samples." Cancer Research 82, no. 4_Supplement (February 15, 2022): P3–09–14—P3–09–14. http://dx.doi.org/10.1158/1538-7445.sabcs21-p3-09-14.

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Abstract Background: Triple-negative breast cancer (TNBC) is a heterogeneous breast cancer subtype with distinct biological features and clinical behavior. TNBC is associated with an increased risk of metastasis and recurrence. In this whole exome study, we investigated the genetic profiles of primary TNBC tumors and paired metastases using next-generation sequencing (NGS). Methods: Genomic DNA extracted from 35 paraffin-embedded formalin-fixed (FFPE) tissues (15 primary tumors that did not metastasize, 11 primary tumors that metastasized, and nine paired metastatic tumors to the lymph nodes) was analyzed by whole exome sequencing (WES). Reads were trimmed using Trim-Galore and were aligned to the reference genome GRCh38 using Burrows-Wheeler Aligner (BWA). BAM files were preprocessed to optimize variant calling, and variant calling was carried out using the GATK pipeline. Variants were annotated using SnpEff. Tumors were analyzed for single nucleotide variants (SNV), point mutations, and insertions/deletions (indels). Results: Primary tumors that did not metastasize had a higher number of variants (~13,500) than primary tumors that metastasized (~12,900). However, the number of variants was similar between the primary tumors (~12,900 variants) and their matched metastases (~12,500 variants). MUC3A was the top mutated gene both in primary tumors that did not metastasize and in those that metastasized. MUC3A was also the top mutated gene in matched metastatic lesions. Moreover, we compared the mutational status of the most frequently mutated genes in TNBC samples from the TCGA and METABRIC datasets. We found that in our dataset, TP53, MAP3K1, and PTEN were mutated in 60%, 93%, and 7% of primary TNBC tumors without metastases and in 36%, 0%, and 36% of primary TNBC tumors that metastasized. Mutations in TP53 and PTEN were found in 2/9 and 1/9 of primary and metastases pairs, respectively. No mutations in PI3KCA were observed in any of the primary or matched metastatic tumors. Conclusions: We used WES to compare the genomic landscapes of primary TNBC tumors and matched metastatic tumors, as well as of primary TNBC tumors that metastasized and those that did not metastasize. We found very similar genomic alterations between the primary and paired metastatic tumors, indicating that genomic features may be retained during metastasis. Primary tumors that did not metastasize showed a greater extent of genomic alterations than primary tumors that metastasized. Citation Format: Jaspreet Kaur, Darshan S. Chandrashekar, Zsuzsanna Varga, Emiel Janssen, Khanjan Gandhi, Karuna Mittal, Umay Kiraz, Sooryanarayana Varambally, Ritu Aneja. Whole exome sequencing of matched primary and metastatic triple-negative breast cancer samples [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-09-14.

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Malamon, John Stephen, and Adam C. Naj. "POST-VARIANT CALLING QUALITY CONTROL (QC) PIPELINE AND MULTI-PIPELINE GENOTYPE CONSENSUS CALLER FOR LARGE-SCALE WHOLE GENOME AND WHOLE EXOME SEQUENCING STUDIES." Alzheimer's & Dementia 13, no. 7 (July 2017): P956—P957. http://dx.doi.org/10.1016/j.jalz.2017.06.1275.

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Lin, Ting-Yi, Yun-Chia Chang, Yu-Jer Hsiao, Yueh Chien, Ying-Chun Jheng, Jing-Rong Wu, Lo-Jei Ching, et al. "Identification of Novel Genomic-Variant Patterns of OR56A5, OR52L1, and CTSD in Retinitis Pigmentosa Patients by Whole-Exome Sequencing." International Journal of Molecular Sciences 22, no. 11 (May 25, 2021): 5594. http://dx.doi.org/10.3390/ijms22115594.

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Inherited retinal dystrophies (IRDs) are rare but highly heterogeneous genetic disorders that affect individuals and families worldwide. However, given its wide variability, its analysis of the driver genes for over 50% of the cases remains unexplored. The present study aims to identify novel driver genes, disease-causing variants, and retinitis pigmentosa (RP)-associated pathways. Using family-based whole-exome sequencing (WES) to identify putative RP-causing rare variants, we identified a total of five potentially pathogenic variants located in genes OR56A5, OR52L1, CTSD, PRF1, KBTBD13, and ATP2B4. Of the variants present in all affected individuals, genes OR56A5, OR52L1, CTSD, KBTBD13, and ATP2B4 present as missense mutations, while PRF1 and CTSD present as frameshift variants. Sanger sequencing confirmed the presence of the novel pathogenic variant PRF1 (c.124_128del) that has not been reported previously. More causal-effect or evidence-based studies will be required to elucidate the precise roles of these SNPs in the RP pathogenesis. Taken together, our findings may allow us to explore the risk variants based on the sequencing data and upgrade the existing variant annotation database in Taiwan. It may help detect specific eye diseases such as retinitis pigmentosa in East Asia.

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Wang, Danyi, Juergen Scheuenpflug, and Zheng Feng. "84 Comparative analysis of ImmunoID NeXT™ and ACE ImmunoID™ next generation sequencing platforms for investigating tumor-immune interactions to enable precision oncology driven biomarker discovery." Journal for ImmunoTherapy of Cancer 9, Suppl 2 (November 2021): A92. http://dx.doi.org/10.1136/jitc-2021-sitc2021.084.

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BackgroundImmunoID NeXT is a comprehensive enhanced whole exome and whole transcriptome scale platform, that provides a multidimensional view of the molecular tumor microenvironment from a single tumor sample with augmented coverage and specific targeting.1 As ImmunoID NeXT is based on Accuracy and Content Enhanced (ACE) technology to further supplement gaps in all 20,000 human genes and target unique genomic regions for immuno-oncology, we assessed key sequencing metrics between the platforms to assure smooth platform migration.MethodsFifteen FFPE samples from late-stage, treatment-naive colorectal cancer patients were processed on both ACE ImmunoID and ImmunoID NeXT platforms. Specimens were evaluated using the same input criteria including the minimum 4 unstained slides per FFPE sample with 5–10 micro-meter thick sections, 25mm2 surface area each section, ≥ 20% tumor content. ACE ImmunoID sequencing was performed using ACE enrichment including library preparation and 2x150bp sequencing on the NovaSeq. Whereas, ImmunoID NeXT exome sequencing was performed using NeXT enrichment including library preparation and 2x150bp sequencing on the NovaSeq. We assessed the concordance of the assays in overlapping features with respect to sequencing quality metrics, somatic variant calling, tumor mutational burden, and gene expression. Tumor mutation burden (TMB) from the two platforms was re-computed to align with the FOCR guidelines, counting exome-wide non-synonymous somatic variants over the coding sequence footprint of each assay.ResultsThe sequencing average base quality (Q score) is equivalent (exome-Seq: NeXT = 36.17 vs. ACE = 36.02; Transcriptome-Seq: NeXT = 35.79 vs. ACE = 35.90;) and alignment coverage consistent with the platform design. To look at somatic variant concordance, the ACE ImmunoID and ImmunoID NeXT .bed files were intersected, and the analysis was focused on the overlapping target region. The following filters were applied to the variants detected with ACE ImmunoID: allelic frequency of >10%, read depth of >50, and a population frequency filter where any variant over 1% was excluded. The same population frequency filter was also applied to variants detected with ImmunoID NeXT. We observed a concordance of 89–98% in high confidence calls between the two platforms. Focused on the overlapping coding region in the intersection of ACE and NeXT, the consistent TMB results were achieved with both platforms.ConclusionsIt is demonstrated that both ImmunoID NeXT and ACE ImmunoID are high-performance platforms with consistently strong sequencing QC metrics. Collectively, ImmunoID NeXT, as the universal cancer immunogenomics platform, could provide end-to-end solution for immune/precision oncology clinical biomarker discovery.ReferencesZheng Feng, Danyi Wang, Mengyao Tan, Juergen Scheuenpflug. Whole-exome sequencing based immunogenomic profiling with potential clinical applicability in circulating cell-free DNA and tissue from advanced stage colorectal cancer patients [abstract]. In: Proceeding of the Annual Meeting of the Society for Immunotherapy for Cancer 2020; Nov 11–14: SITC; J Immunother Cancer 2020; 8 (16 Suppl 3): Abstract nr 19.Ethics ApprovalThe study protocol was in accordance with the tenets of the Declaration of Helsinki. Commercial samples used in this study were procured from BioIVT and BioChain following protocols approved by the local Institutional Review Board (IRB) committee. Informed consent forms were obtained from all the human subjects in this study.ConsentWritten informed consent was obtained from the patient for publication of this abstract and any accompanying images. A copy of the written consent is available for review by the Editor of this journal.

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Journal articles on the topic 'Variant calling, whole exome sequencing, database'

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