Journal articles on the topic 'Gene burden analysis'
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1
Sadler, Brooke, Charles G. Minard, Gabe Haller, Christina A. Gurnett, Sarah H. O’Brien, Allison Wheeler, Shilpa Jain, et al. "Whole-exome analysis of adolescents with low VWF and heavy menstrual bleeding identifies novel genetic associations." Blood Advances 6, no. 2 (January 17, 2022): 420–28. http://dx.doi.org/10.1182/bloodadvances.2021005118.
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Abstract Adolescents with low von Willebrand factor (VWF) levels and heavy menstrual bleeding (HMB) experience significant morbidity. There is a need to better characterize these patients genetically and improve our understanding of the pathophysiology of bleeding. We performed whole-exome sequencing on 86 postmenarchal patients diagnosed with low VWF levels (30-50 IU/dL) and HMB and compared them with 660 in-house controls. We compared the number of rare stop-gain/stop-loss and rare ClinVar “pathogenic” variants between cases and controls, as well as performed gene burden and gene-set burden analyses. We found an enrichment in cases of rare stop-gain/stop-loss variants in genes involved in bleeding disorders and an enrichment of rare ClinVar “pathogenic” variants in genes involved in anemias. The 2 most significant genes in the gene burden analysis, CFB and DNASE2, are associated with atypical hemolytic uremia and severe anemia, respectively. VWF also surpassed exome-wide significance in the gene burden analysis (P = 7.31 × 10−6). Gene-set burden analysis revealed an enrichment of rare nonsynonymous variants in cases in several hematologically relevant pathways. Further, common variants in FERMT2, a gene involved in the regulation of hemostasis and angiogenesis, surpassed genome-wide significance. We demonstrate that adolescents with HMB and low VWF have an excess of rare nonsynonymous and pathogenic variants in genes involved in bleeding disorders and anemia. Variants of variable penetrance in these genes may contribute to the spectrum of phenotypes observed in patients with HMB and could partially explain the bleeding phenotype. By identifying patients with HMB who possess these variants, we may be able to improve risk stratification and patient outcomes.
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Wang, Shuangkuai, Yuantao Tong, Hui Zong, Xuewen Xu, M. James C. Crabbe, Ying Wang, and Xiaoyan Zhang. "Multi-Level Analysis and Identification of Tumor Mutational Burden Genes across Cancer Types." Genes 13, no. 2 (February 17, 2022): 365. http://dx.doi.org/10.3390/genes13020365.
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Tumor mutational burden (TMB) is considered a potential biomarker for predicting the response and effect of immune checkpoint inhibitors (ICIs). However, there are still inconsistent standards of gene panels using next-generation sequencing and poor correlation between the TMB genes, immune cell infiltrating, and prognosis. We applied text-mining technology to construct specific TMB-associated gene panels cross various cancer types. As a case exploration, Pearson’s correlation between TMB genes and immune cell infiltrating was further analyzed in colorectal cancer. We then performed LASSO Cox regression to construct a prognosis predictive model and calculated the risk score of each sample for receiver operating characteristic (ROC) analysis. The results showed that the assessment of TMB gene panels performed well with fewer than 500 genes, highly mutated genes, and the inclusion of synonymous mutations and immune regulatory and drug-target genes. Moreover, the analysis of TMB differentially expressed genes (DEGs) suggested that JAKMIP1 was strongly correlated with the gene expression level of CD8+ T cell markers in colorectal cancer. Additionally, the prognosis predictive model based on 19 TMB DEGs reached AUCs of 0.836, 0.818, and 0.787 in 1-, 3-, and 5-year OS models, respectively (C-index: 0.810). In summary, the gene panel performed well and TMB DEGs showed great potential value in immune cell infiltration and in predicting survival.
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Jiao, Xiaodong, Xiaochun Zhang, Baodong Qin, Dong Liu, Liang Liu, Jianjiao Ni, Ningyu Zhou, et al. "Tumor mutation burden analysis in a 5,660 cancer patient cohort reveals cancer type-specific mechanisms for high mutation burden." Journal of Clinical Oncology 37, no. 15_suppl (May 20, 2019): 2589. http://dx.doi.org/10.1200/jco.2019.37.15_suppl.2589.
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2589 Background: Tumor mutation burden (TMB), calculated by whole-exome sequencing (WES) or large NGS panels, has an important association with immunotherapy responses. Elucidating the underlying biological mechanisms of high TMB might help develop more precise and effective means for TMB and immunotherapy response prediction. Meanwhile, the landscape of TMB across different cancer types and its association with other molecular features have not been well investigated in large cohorts in China. Methods: Cancer patients whose fresh tissue (n = 1556), formalin-fixed, paraffin-embed (FFPE) specimen (n = 1794), and pleural fluid (n = 84) were profiled using 295- or 520-gene NGS panel. The association of the TMB status with a series of molecular features and biological pathways was interrogated using bootstrapping. Results: TMB, measured by 295- or 520-cancer-related gene panels, were correlated with WES TMB based on in silico simulation in the TCGA cohort. We compared the TMB landscape across 11 cancer type groups and found the highest average TMB in lung squamous cell carcinoma, whereas the lowest TMB was established in sarcoma. High microsatellite instability, DNA damage response deficiency, and homologous recombination repair deficiency indicated significantly higher TMB. The independent predictive power for TMB of twenty-six biological pathways was tested in 10 cancer groups. FoxO signaling pathway most commonly correlated with low-TMB; significant association was identified in four cancer groups. In contrast, no pathway was significantly correlated with high-TMB in more than two cancer groups. Overall, we discovered that the underlying pathways which may be the main drivers of TMB status varied greatly and sometimes had an opposite association with TMB across different cancer types. Moreover, we developed a 14- and 22-gene signature for TMB prediction for LUAD and LUSC, respectively, with only 10 genes shared by both signatures, indicating a histology-specific mechanism for driving high-TMB in lung cancer. Conclusions: The findings extended the knowledge of the underlying biological mechanisms for high TMB and might be helpful for developing more precise and accessible TMB assessment panels and algorithms in more cancer types.
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Cooper-Knock, Johnathan, Sai Zhang, Kevin P. Kenna, Tobias Moll, John P. Franklin, Samantha Allen, Helia Ghahremani Nezhad, et al. "Rare variant burden analysis within enhancers identifies CAV1 as an ALS risk gene." Cell Reports 34, no. 5 (February 2021): 108730. http://dx.doi.org/10.1016/j.celrep.2021.108730.
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Cooper-Knock, Johnathan, Sai Zhang, Kevin P. Kenna, Tobias Moll, John P. Franklin, Samantha Allen, Helia Ghahremani Nezhad, et al. "Rare Variant Burden Analysis within Enhancers Identifies CAV1 as an ALS Risk Gene." Cell Reports 33, no. 9 (December 2020): 108456. http://dx.doi.org/10.1016/j.celrep.2020.108456.
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Seo, Eun Seop, Eun-jin Lee, Boram Lee, Muheon Shin, Young-Seok Cho, Ju Kyung Hyun, Hee Won Cho, et al. "Metastatic Burden Defines Clinically and Biologically Distinct Subgroups of Stage 4 High-Risk Neuroblastoma." Journal of Clinical Medicine 9, no. 9 (August 24, 2020): 2730. http://dx.doi.org/10.3390/jcm9092730.
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This study aimed to identify the prognostic subgroups of stage 4 high-risk neuroblastoma based on metastatic burden and explore their distinct clinical and genomic features. Patients aged ≥18 months with stage 4 and metaiodobenzylguanidine-avid neuroblastoma were enrolled. One hundred and thirty eligible patients were treated under the tandem high-dose chemotherapy scheme. Prognostic significance of metastatic burden measured by the modified Curie score was analyzed using a competing risk approach, and the optimal cut-point was determined. Metastasis-specific subgroups (cut-point: 26) were compared using clinicopathological variables, and differential gene expression analysis and gene set variation analysis (GSVA) were performed using RNA sequencing (RNA-seq). Metastatic burden at diagnosis showed a progressive association with relapse/progression. After applying the cut-point, patients with high metastatic burden showed >3-fold higher risk of relapse/progression than those with low metastatic burden. Moreover, patients with high metastatic burden showed smaller primary tumors and higher biochemical marker levels than those with low metastatic burden. In the genomic analysis, 51 genes were found to be differentially expressed based on the set criteria. GSVA revealed 55 gene sets, which significantly distinguished patients with high metastatic burden from those with low metastatic burden at a false discovery rate <0.25. The results indicated the prognostic significance of metastatic burden in stage 4 high-risk neuroblastoma, and we identified the distinct clinicopathological and genomic features based on metastatic burden. This study may aid in the better understanding and risk-stratification of stage 4 high-risk neuroblastoma patients.
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Frampton, Matthew, Elena R. Schiff, Nikolas Pontikos, Anthony W. Segal, and Adam P. Levine. "Seqfam: A python package for analysis of Next Generation Sequencing DNA data in families." F1000Research 7 (March 6, 2018): 281. http://dx.doi.org/10.12688/f1000research.13930.1.
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This article introduces seqfam, a python package which is primarily designed for analysing next generation sequencing (NGS) DNA data from families with known pedigree information in order to identify rare variants that are potentially causal of a disease/trait of interest. It uses the popular and versatile Pandas library, and can be straightforwardly integrated into existing analysis code/pipelines. Seqfam can be used to verify pedigree information, to perform Monte Carlo gene dropping, to undertake regression-based gene burden testing, and to identify variants which segregate by affection status in families via user-defined pattern of occurrence rules. Additionally, it can generate scripts for running analyses in a “MapReduce pattern” on a computer cluster, something which is usually desirable in NGS data analysis and indeed “big data” analysis in general. This article summarises how seqfam’s main user functions work and motivates their use. It also provides explanatory context for example scripts and data included in the package which demonstrate use cases. With respect to verifying pedigree information, software exists for efficiently calculating kinship coefficients, so seqfam performs the necessary extra steps of mapping pedigrees and kinship coefficients to expected and observed degrees of relationship respectively. Gene dropping and the application of variant pattern of occurrence rules in families can provide evidence for a variant being causal. The authors are unaware of other software which performs these tasks in familial cohorts, so seqfam fulfils this need. Gene burden rather than single marker tests are often used to detect rare causal variants due to greater power. Seqfam may be an attractive alternative to existing gene burden testing software due to its flexibility, particularly in grouping and aggregating variants.
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Taylor, Jacquelyn Y., Erin B. Ware, Michelle L. Wright, Jennifer A. Smith, and Sharon L. R. Kardia. "Using Genetic Burden Scores for Gene-by-Methylation Interaction Analysis on Metabolic Syndrome in African Americans." Biological Research For Nursing 21, no. 3 (February 19, 2019): 279–85. http://dx.doi.org/10.1177/1099800419828486.
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With the rapid advancement of omics-based research, particularly big data such as genome- and epigenome-wide association studies that include extensive environmental and clinical variables, data analytics have become increasingly complex. Researchers face significant challenges regarding how to analyze multifactorial data and make use of the findings for clinical translation. The purpose of this article is to provide a scientific exemplar for use of genetic burden scores as a data analysis method for studies with both genotype and DNA methylation data in which the goal is to evaluate associations with chronic conditions such as metabolic syndrome (MetS). This study included 739 African American men and women from the Genetic Epidemiology Network of Arteriopathy Study who met diagnostic criteria for MetS and had available genetic and epigenetic data. Genetic burden scores for evaluated genes were not significant after multiple testing corrections, but DNA methylation at 2 CpG sites (dihydroorotate dehydrogenase cg22381196 pFDR = .014; CTNNA3 cg00132141 pFDR = .043) was significantly associated with MetS after controlling for multiple comparisons. Interactions between the marginally significant CpG sites and burden scores, however, were not significant. More work is required in this area to identify intermediate biological pathways influenced by environmental, genetic, and epigenetic variation that may explain the high prevalence of MetS among African Americans. This study does serve, however, as an example of the use of the genetic burden score as an alternative data analysis approach for complex studies involving the analysis of genetic and epigenetic data simultaneously.
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Choi, Sungkyoung, Sungyoung Lee, Yongkang Kim, Heungsun Hwang, and Taesung Park. "HisCoM-GGI: Hierarchical structural component analysis of gene–gene interactions." Journal of Bioinformatics and Computational Biology 16, no. 06 (December 2018): 1840026. http://dx.doi.org/10.1142/s0219720018400267.
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Although genome-wide association studies (GWAS) have successfully identified thousands of single nucleotide polymorphisms (SNPs) associated with common diseases, these observations are limited for fully explaining “missing heritability”. Determining gene–gene interactions (GGI) are one possible avenue for addressing the missing heritability problem. While many statistical approaches have been proposed to detect GGI, most of these focus primarily on SNP-to-SNP interactions. While there are many advantages of gene-based GGI analyses, such as reducing the burden of multiple-testing correction, and increasing power by aggregating multiple causal signals across SNPs in specific genes, only a few methods are available. In this study, we proposed a new statistical approach for gene-based GGI analysis, “Hierarchical structural CoMponent analysis of Gene–Gene Interactions” (HisCoM-GGI). HisCoM-GGI is based on generalized structured component analysis, and can consider hierarchical structural relationships between genes and SNPs. For a pair of genes, HisCoM-GGI first effectively summarizes all possible pairwise SNP–SNP interactions into a latent variable, from which it then performs GGI analysis. HisCoM-GGI can evaluate both gene-level and SNP-level interactions. Through simulation studies, HisCoM-GGI demonstrated higher statistical power than existing gene-based GGI methods, in analyzing a GWAS of a Korean population for identifying GGI associated with body mass index. Resultantly, HisCoM-GGI successfully identified 14 potential GGI, two of which, (NCOR2 [Formula: see text] SPOCK1) and (LINGO2 [Formula: see text] ZNF385D) were successfully replicated in independent datasets. We conclude that HisCoM-GGI method may be a valuable tool for genome to identify GGI in missing heritability, allowing us to better understand the biological genetic mechanisms of complex traits. We conclude that HisCoM-GGI method may be a valuable tool for genome to identify GGI in missing heritability, allowing us to better understand biological genetic mechanisms of complex traits. An implementation of HisCoM-GGI can be downloaded from the website ( http://statgen.snu.ac.kr/software/hiscom-ggi ).
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Trimarchi, Matteo, Giacomo Bertazzoni, Alessandro Vinciguerra, Celia Pardini, Fabio Simeoni, Davide Cittaro, Mario Bussi, and Dejan Lazarevic. "Gene Expression Analysis in Patients with Cocaine-Induced Midline Destructive Lesions." Medicina 57, no. 9 (August 24, 2021): 861. http://dx.doi.org/10.3390/medicina57090861.
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Background and Objectives: Cocaine users may present with positive antineutrophil cytoplasmic antibodies (ANCA) and severe midline destructive lesions (CIMDL) which are histologically characterized by massive apoptosis. However, histopathological and laboratory studies suggest that autoimmunity may not be the main pathogenic driver. We analyzed gene expression both in cell lines of nasal mucosa exposed to cocaine and in CIMDL patients to determine whether genetic predisposition might cause such lesions, which are observed in a minority of cocaine abusers. Materials and Methods: The genetic expression profile of nasal mucosa exposed to cocaine was analyzed. Rare variants of expressed genes were searched in patients with CIMDL using exome sequencing and bio-informatics. Results: We identified 462 genes that were induced by cocaine, mainly related to apoptosis and autophagy in response to oxidative stress. Under the hypothesis that genes linked to the phenotype are also induced by cocaine itself, a rare variants burden test was performed to select genes that were significantly enriched in rare mutations. Next, 11 cocaine abusers with CIMDL and no other relevant medical comorbidities underwent exome sequencing, and 12 genes that were significantly enriched in the burden test and present in at least 10 patients were identified. An in-depth analysis of these genes revealed their involvement in apoptosis, tissue homeostasis, autophagy, and response to oxidative stress. Conclusions: Oxidative stress and rare genetic alterations in the response to reactive oxygen species, apoptosis, autophagy, and tissue regeneration are plausible drivers of damage affecting nasal mucosa exposed to cocaine crystals and, consequently, the pathogenic mechanism behind CIMDL.
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Owada, Yuki, Satoshi Muto, Hironori Takagi, Takuya Inoue, Yuzuru Watanabe, Takumi Yamaura, Mitsuro Fukuhara, et al. "Correlation between mutation burden of tumor and immunological/clinical parameters in considering biomarkers of immune checkpoint inhibitors for non-small cell lung cancer (NSCLC)." Journal of Clinical Oncology 35, no. 15_suppl (May 20, 2017): e23184-e23184. http://dx.doi.org/10.1200/jco.2017.35.15_suppl.e23184.
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e23184 Background: There has been reported that mutation burden of solid tumor might probably be a predictive biomarker of efficacy of immune check point inhibitors, and the number of researches are still ongoing. Although the correlation of mutation burden between by whole exome sequence and by large targeted panel sequence has also been reported, neither method can be said to have solved technical and economical difficulty of using in clinical practice. Here we describe more convenient factors that can be used instead of mutation burden. Methods: 92 NSCLC patients with surgery during 2013-2015 in our institution were subjected for this study. Mutation burden in tumor samples was analyzed by whole exome sequence using Next Generation Sequencer. The major gene alteration was also analyzed by small targeted panel sequence. As immunological parameters, tumor infiltrating lymphocyte and PD-L1 expression in tumor were assessed by immunohistochemistry test using anti-CD8 antibody and anti-PD-L1 antibody. Statistical analysis was performed on mutation burden and the result of major gene alternation, immunohistochemistry, and clinical parameters. Results: There were 64 adenocarcinomas and 28 squamous cell carcinomas. The median value of mutation burden was 60 genes (10-502). The factors including squamous cell carcinoma, male, smoking history, EGFR-mutation negative, and TP53 alteration positive indicated close connection with higher mutation burden (p < 0.001) There were no significant difference in PD-L1 expression of tumor and tumor infiltrating lymphocyte. Multiple regression analysis showed that negative EGFR-mutation and positive TP53 alteration contribute to higher mutation burden (p < 0.05). Conclusions: Mutation burden in NSCLC tumor could be associated with EGFR-mutation and TP53 alteration status. These findings suggest that some major gene alteration make it possible to predict mutation burden, and could potentially be more simple predictive biomarkers of immune check point inhibitors.
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Lee, Sungyoung, Min-Seok Kwon, and Taesung Park. "CARAT-GxG: CUDA-Accelerated Regression Analysis Toolkit for Large-Scale Gene–Gene Interaction with GPU Computing System." Cancer Informatics 13s7 (January 2014): CIN.S16349. http://dx.doi.org/10.4137/cin.s16349.
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In genome-wide association studies (GWAS), regression analysis has been most commonly used to establish an association between a phenotype and genetic variants, such as single nucleotide polymorphism (SNP). However, most applications of regression analysis have been restricted to the investigation of single marker because of the large computational burden. Thus, there have been limited applications of regression analysis to multiple SNPs, including gene–gene interaction (GGI) in large-scale GWAS data. In order to overcome this limitation, we propose CARAT-GxG, a GPU computing system-oriented toolkit, for performing regression analysis with GGI using CUDA (compute unified device architecture). Compared to other methods, CARAT-GxG achieved almost 700-fold execution speed and delivered highly reliable results through our GPU-specific optimization techniques. In addition, it was possible to achieve almost-linear speed acceleration with the application of a GPU computing system, which is implemented by the TORQUE Resource Manager. We expect that CARAT-GxG will enable large-scale regression analysis with GGI for GWAS data.
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Kurochkin, D. V., I. E. Maslyukova, T. N. Subbotina, A. S. Khazieva, E. V. Vasiliev, M. A. Mikhalev, E. A. Dunaeva, and K. O. Mironov. "Screening of somatic mutations in the JAK2 and CALR genes by high-resolution melting curve analysis." Russian Clinical Laboratory Diagnostics 66, no. 5 (May 23, 2021): 315–20. http://dx.doi.org/10.51620/0869-2084-2021-66-5-315-320.
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Somatic mutations associated with oncological diseases, including Ph-myeloproliferative neoplasms (Ph-MPN), are very diverse, occur with different frequencies and different allelic burden levels. Therefore, at the initial stage of performing molecular-genetic diagnostic procedures, it is desirable to be able to conduct screening tests in the laboratory. This is especially important when analyzing rare and diverse mutations. Analysis of high resolution melting curves (HRM analysis), which has high sensitivity and is suitable for screening all types of mutations, in a number of studies is proposed for the analysis of Ph-MPN associated mutations in the JAK2 and CALR genes. For analysis of somatic mutations in the majority of literature sources that we reviewed, the authors use the LightCycler (Roche) thermocycler and much rarely the CFX96 (Bio-Rad), which is often presented in Russian scientific and practical and medical organizations. The aim of the study was to screen the somatic JAK2 and CALR mutations by HRM analysis using the CFX96 thermocycler and the Precision Melt Analysis software (Bio-Rad, USA) for patients with Ph-MPN. In the present research, HRM analysis was conducted on the DNA samples from patients with mutations in the JAK2 or in the CALR gene. The Precision Melt Analysis software identified all variants of the analyzed mutations, both a single nucleotide substitution in the JAK2 gene (with allelic burden level in the range of 5-40%), and various indel mutations in the CALR gene (with allelic burden level in the range of 40-50%) Therefore, the HRM analysis that was conducted on the CFX96 allows screening of highly specific mutation for the diagnosis of Ph-MPN in the exon 14 of the JAK2 gene and in the exon 9 of the CALR gene. The inclusion of this screening research in the laboratory testing algorithm improves the efficiency and accessibility of molecular genetic technologies in the diagnosis of Ph-MPN.
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Ravi, Dashnamoorthy, Afshin Beheshti, Kristine Burgess, Athena Kritharis, Ying Chen, Andrew M. Evens, and Biju Parekkadan. "An Analysis of Transcriptomic Burden Identifies Biological Progression Roadmaps for Hematological Malignancies and Solid Tumors." Biomedicines 10, no. 11 (October 27, 2022): 2720. http://dx.doi.org/10.3390/biomedicines10112720.
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Biological paths of tumor progression are difficult to predict without time-series data. Using median shift and abacus transformation in the analysis of RNA sequencing data sets, natural patient stratifications were found based on their transcriptomic burden (TcB). Using gene-behavior analysis, TcB groups were evaluated further to discover biological courses of tumor progression. We found that solid tumors and hematological malignancies (n = 4179) share conserved biological patterns, and biological network complexity decreases at increasing TcB levels. An analysis of gene expression datasets including pediatric leukemia patients revealed TcB patterns with biological directionality and survival implications. A prospective interventional study with PI3K targeted therapy in canine lymphomas proved that directional biological responses are dynamic. To conclude, TcB-enriched biological mechanisms detected the existence of biological trajectories within tumors. Using this prognostic informative novel informatics method, which can be applied to tumor transcriptomes and progressive diseases inspires the design of progression-specific therapeutic approaches.
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Rampal, Raajit, Fatima Al-Shahrour, Omar Abdel-Wahab, Jay P. Patel, Jean-Philippe Brunel, Craig H. Mermel, Adam J. Bass, et al. "Integrated genomic analysis illustrates the central role of JAK-STAT pathway activation in myeloproliferative neoplasm pathogenesis." Blood 123, no. 22 (May 29, 2014): e123-e133. http://dx.doi.org/10.1182/blood-2014-02-554634.
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Key Points A gene expression profile consistent with activated JAK2 signaling is seen in all MPN patients, including in patients with CALR mutations. Transcriptional profiling discriminates subsets of MPNs based on JAK2V617F allele burden and on the presence of CALR and TET2 mutations.
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Nyangiri, Oscar A., Sokouri A. Edwige, Mathurin Koffi, Estelle Mewamba, Gustave Simo, Joyce Namulondo, Julius Mulindwa, et al. "Candidate gene family-based and case-control studies of susceptibility to high Schistosoma mansoni worm burden in African children: a protocol." AAS Open Research 4 (December 15, 2021): 36. http://dx.doi.org/10.12688/aasopenres.13203.2.
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Background: Approximately 25% of the risk of Schistosoma mansoni is associated with host genetic variation. We will test 24 candidate genes, mainly in the Th2 and Th17 pathways, for association with S. mansoni infection intensity in four African countries, using family based and case-control approaches. Methods: Children aged 5-15 years will be recruited in S. mansoni endemic areas of Ivory Coast, Cameroon, Uganda and the Democratic Republic of Congo (DRC). We will use family based (study 1) and case-control (study 2) designs. Study 1 will take place in Ivory Coast, Cameroon, Uganda and the DRC. We aim to recruit 100 high worm burden families from each country except Uganda, where a previous study recruited at least 40 families. For phenotyping, cases will be defined as the 20% of children in each community with heaviest worm burdens as measured by the circulating cathodic antigen (CCA) assay. Study 2 will take place in Uganda. We will recruit 500 children in a highly endemic community. For phenotyping, cases will be defined as the 20% of children with heaviest worm burdens as measured by the CAA assay, while controls will be the 20% of infected children with the lightest worm burdens. Deoxyribonucleic acid (DNA) will be genotyped on the Illumina H3Africa SNP (single nucleotide polymorphisms) chip and genotypes will be converted to sets of haplotypes that span the gene region for analysis. We have selected 24 genes for genotyping that are mainly in the Th2 and Th17 pathways and that have variants that have been demonstrated to be or could be associated with Schistosoma infection intensity. Analysis: In the family-based design, we will identify SNP haplotypes disproportionately transmitted to children with high worm burden. Case-control analysis will detect overrepresentation of haplotypes in extreme phenotypes with correction for relatedness by using whole genome principal components.
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Nyangiri, Oscar A., Sokouri A. Edwige, Mathurin Koffi, Estelle Mewamba, Gustave Simo, Joyce Namulondo, Julius Mulindwa, et al. "Candidate gene family-based and case-control studies of susceptibility to high Schistosoma mansoni worm burden in African children: a protocol." AAS Open Research 4 (June 29, 2021): 36. http://dx.doi.org/10.12688/aasopenres.13203.1.
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Background: Approximately 25% of the risk of Schistosoma mansoni is associated with host genetic variation. We will test 24 candidate genes, mainly in the Th2 and Th17 pathways, for association with S. mansoni infection intensity in four African countries, using family based and case-control approaches. Methods: Children aged 5-15 years will be recruited in S. mansoni endemic areas of Ivory Coast, Cameroon, Uganda and the Democratic Republic of Congo (DRC). We will use family based (study 1) and case-control (study 2) designs. Study 1 will take place in Ivory Coast, Cameroon, Uganda and the DRC. We aim to recruit 100 high worm burden families from each country except Uganda, where a previous study recruited at least 40 families. For phenotyping, cases will be defined as the 20% of children in each community with heaviest worm burdens as measured by the circulating cathodic antigen (CCA) assay. Study 2 will take place in Uganda. We will recruit 500 children in a highly endemic community. For phenotyping, cases will be defined as the 20% of children with heaviest worm burdens as measured by the CAA assay, while controls will be the 20% of infected children with the lightest worm burdens. Deoxyribonucleic acid (DNA) will be genotyped on the Illumina H3Africa SNP (single nucleotide polymorphisms) chip and genotypes will be converted to sets of haplotypes that span the gene region for analysis. We have selected 24 genes for genotyping that are mainly in the Th2 and Th17 pathways and that have variants that have been demonstrated to be or could be associated with Schistosoma infection intensity. Analysis: In the family-based design, we will identify SNP haplotypes disproportionately transmitted to children with high worm burden. Case-control analysis will detect overrepresentation of haplotypes in extreme phenotypes with correction for relatedness by using whole genome principal components.
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Hancock, Edward J., Guy-Bart Stan, James A. J. Arpino, and Antonis Papachristodoulou. "Simplified mechanistic models of gene regulation for analysis and design." Journal of The Royal Society Interface 12, no. 108 (July 2015): 20150312. http://dx.doi.org/10.1098/rsif.2015.0312.
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Simplified mechanistic models of gene regulation are fundamental to systems biology and essential for synthetic biology. However, conventional simplified models typically have outputs that are not directly measurable and are based on assumptions that do not often hold under experimental conditions. To resolve these issues, we propose a ‘model reduction’ methodology and simplified kinetic models of total mRNA and total protein concentration, which link measurements, models and biochemical mechanisms. The proposed approach is based on assumptions that hold generally and include typical cases in systems and synthetic biology where conventional models do not hold. We use novel assumptions regarding the ‘speed of reactions’, which are required for the methodology to be consistent with experimental data. We also apply the methodology to propose simplified models of gene regulation in the presence of multiple protein binding sites, providing both biological insights and an illustration of the generality of the methodology. Lastly, we show that modelling total protein concentration allows us to address key questions on gene regulation, such as efficiency, burden, competition and modularity.
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Sadler, Brooke, Charles Minard, Gabe Haller, Christina Gurnett, Sarah H. O'Brien, Allison P. Wheeler, Eric S. Mullins, et al. "Genotype Analysis of Adolescents with Heavy Menstrual Bleeding and Low Von Willebrand Activity - Report of a Multi-Center Study." Blood 136, Supplement 1 (November 5, 2020): 19–20. http://dx.doi.org/10.1182/blood-2020-135886.
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Introduction: Low von Willebrand factor (VWF) activity is prevalent in adolescents with heavy menstrual bleeding (HMB). There is a need to better genetically characterize these patients and improve our understanding of the pathophysiology of their bleeding risk. Methods: One of the main objectives of this multi-center, single arm, observational cohort study was to genotype adolescent females with HMB and low VWF (≥ 30 and ≤ 50 IU/dL) by means of whole exome sequencing (WES), to identify variants throughout the exome that may modulate risk for bleeding. Post-menarchal females < 21 years with HMB (defined as PBAC score >100) and low VWF were eligible for the study. All patients were enrolled by participating centers where blood samples were collected. Exome data for 86 cases and 900 unrelated pediatric (<21 years) controls taken from a genetic study on Chiari 1 Malformation (CM1) were aligned and sorted, and variants called using the Sentieon software package. Annotation including allele frequencies, function, amino acid change and Clinvar rating among others was obtained using ANNOVAR. Variants were retained if there was a genotype call rate of >0.8, GQ>20, AB between 0.3-0.7 and min DP>8. Case/control analyses included common and rare SNP associations, gene burden analysis of both rare nonsynonymous variants and ClinVar 'pathogenic' variants, and gene-set burden analyses. Variants were considered rare if they had a minor allele frequency of <1% in the Genome Aggregation Database (gnomAD). Count differences between cases/controls were determined by Fisher's Exact test. Results: Of the 113 subjects enrolled, 86 had sufficient blood samples collected for WES. The median age was 16.2 years (range: 11.5-19.6). 36% of cases showed variants in VWF vs. 26% of controls (p=0.14). After multiple test correction, WES revealed a significant common variant association in FERMT2 with an LD block with a frequency of 24% in cases and 6% in controls (p=7.5x10-7). Rare variant analysis showed a significant association with an intronic variant in ABCA13 (p=1.6x10-7). Among the gene burden analysis using rare nonsynonymous variants, 2 genes of interest passed multiple test correction: IL12B and DTNBP1. When using ClinVar 'pathogenic' variants as the input for the gene burden analysis, 4 genes of interest passed multiple test correction: HBM, MYLK, RUNX1 and CD36. Gene-set burden analysis revealed 5 significant pathways of interest, including platelet degranulation, platelet alpha granule lumen and erythrocyte differentiation. We then focused a subset of known risk genes and compared the number of missense, nonsense and ClinVar 'pathogenic' variants between cases and controls. GP6, and MTHFR had significantly more missense variants in controls vs. cases (p=0.003 and 0.01, respectively), and F13B approached significance, with more missense variants in controls than cases (p=0.07). Conclusion: We found VWF variants in 36% of subjects, in accordance with previous reports. We found novel SNP associations with variants in FERMT2 and ABCA13.FERMT2 encodes for the integrin, Kindlin 2, which has been shown to be critical for supporting vascular integrity. Several other relevant genes passed multiple test correction in gene burden analyses, including genes known to cause Hermansky-Pudlak syndrome (DTNBP1), familial platelet disorder (RUNX1), platelet glycoprotein IV deficiency (CD36) and aortic aneurysm (MYLK). This association with platelet disorders was strengthened by our gene-set burden results, which implicate several platelet-related pathways. These data suggest that while a subset of HMB patients may have their bleeding explained by variants in VWF, there is a role for other hemostasis, platelet biology and vascular integrity related gene variants which can contribute to the variation in bleeding severity in adolescents with low-VWF related HMB. Study supported by an investigator-initiated research grant from Shire US Inc., now part of Takeda Disclosures O'Brien: Bristol Myers Squibb: Consultancy, Membership on an entity's Board of Directors or advisory committees. Mullins:Takeda, Bayer: Other: Advisory Board. Sidonio:Takeda: Research Funding. Ragni:Sangamo: Consultancy, Research Funding; Takeda: Research Funding; Bioverativ: Consultancy, Research Funding; Spark: Consultancy, Research Funding; BioMarin: Consultancy, Research Funding; Alnylam/Sanofi, ATHN, BioMarin, Bioverativ, Sangamo, Spark: Research Funding; Alnylam/Sanofi, BioMarin, Bioverativ, Spark: Consultancy; Alnylam Pharmaceuticals Inc., Baxalta/Takeda, BioMarin, Bioverativ, and Spark Therapeutics: Membership on an entity's Board of Directors or advisory committees; American Thrombosis Hemostasis Network: Other: Committee work; Baxalta/Takeda, CSL Behring, Genentech, a member of the Roche Group, OPKO Biologics, and Vascular Medicine Institute: Research Funding. Kulkarni:Sanofi/ Bioverativ, Bayer, Biomarin, Shire/Takeda, Novo Nordisk, Freeline: Other: clinical trial research grants ; Bioverativ/Sanofi, BPL, Genentech, Kedrion, Novo Nordisk, Octapharma, Pfizer, Takeda, Catalyst Bioscience Bayer: Membership on an entity's Board of Directors or advisory committees. Srivaths:Shire US Inc., now part of Takeda: Research Funding.
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Cokic, Vladan P., Pascal Mossuz, Jing Han, Milos Diklic, Mirela Budec, Dijana Sefer, Danijela Lekovic, et al. "Microarray and Proteomic Analysis of Myeloproliferative Neoplasms,." Blood 118, no. 21 (November 18, 2011): 3856. http://dx.doi.org/10.1182/blood.v118.21.3856.3856.
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Abstract Abstract 3856 The gene and protein expression profiles in myeloproliferative neoplasms (MPN) may reveal gene markers of a potential clinical function in diagnosis and prediction of response to therapy. Using cDNA microarray analysis, involving 25,100 unique genes, we studied the gene expression profile of hematopoietic CD34+ progenitor cells and granulocytes obtained from peripheral blood of patients with essential thrombocythemia (ET), polycythemia vera (PV) and primary myelofibrosis (PMF) compared with healthy individuals. The microarray analyses of the hematopoietic progenitor cells and granulocytes have been performed on 9 patients with ET, 8 patients with PV, 4 patients with PMF and 8 healthy donors. The granulocytes for proteomic studies have been pooled in 4 groups: PV with JAK2 mutant allele burden above 80%, ET with JAK2 mutation, PMF with JAK2 mutation and ET/PMF with no JAK2 mutation. We focused our analysis to hematopoiesis related genes. In the collected patient samples, the increased number of granulocytes allowed for further validation by protein analysis of microarray gene expression suggested from less differentiated hematopoietic progenitor cells. Folate receptor 3 (FOLR3), constitutively secreted in hematopoietic tissues, has increased protein levels in granulocytes of JAK2V617F homozygous PV as well as mRNA levels in hematopoietic progenitor cells of patients with PV. The enzyme matrix metallopeptidase 9 (MMP9), involved in IL-8-induced mobilization of hematopoietic progenitor cells from bone marrow, also has significantly increased protein levels in granulocytes of PV patients with increased JAK2 mutation allele burden. In addition, Ras-related C3 botulinum toxin substrate 2 (RAC2) protein level, essential for erythropoiesis, is increased specifically in PV granulocytes with JAK2V617F homozygosity. Moreover, RAC2 gene expression is significantly increased in hematopoietic progenitor cells of PV, with no changes in its granulocytes. Although, like PV, RAC2 gene expression was also increased in ET and PMF hematopoietic progenitor cells compared to healthy individuals, in granulocytes of ET and PMF patients with JAK2 mutation RAC2 protein levels were decreased, contrary to the elevated level in PV. Furthermore, inconsistent with JAK2V617F homozygous PV patients, granulocytes of ET and PMF with the JAK2 mutation exhibit FOLR3 protein at levels lower than the ET and PMF with no JAK2 mutation. Investigating the extent to which these genes participate in the complex molecular and cellular mechanisms of MPN will likely lead to new insights of malignancy development. In conclusion, molecular profiling of hematopoietic progenitor cells and granulocytes of MPN patients revealed gene expression patterns that are beyond their recognized function in disease pathogenesis and can be related to patients' clinical characteristics with imminent prognostic relevance. Disclosures: No relevant conflicts of interest to declare.
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Huang, Taobi, Yuan Liang, Huiyun Zhang, Xia Chen, Hui Wei, Weiming Sun, and Yuping Wang. "CSMD1 Mutations Are Associated with Increased Mutational Burden, Favorable Prognosis, and Anti-Tumor Immunity in Gastric Cancer." Genes 12, no. 11 (October 28, 2021): 1715. http://dx.doi.org/10.3390/genes12111715.
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Tumor mutational burden (TMB) is considered a potential biomarker for predicting the response and effect of immune checkpoint inhibitors (ICIs). To find specific gene mutations related to TMB and the prognosis of patients, the frequently mutated genes in gastric cancer patients from TCGA and ICGC were obtained and the correlation between gene mutation, TMB, and prognosis was analyzed. Furthermore, to clarify whether specific gene mutations can be used as predictive biomarkers of ICIs, a gene set enrichment analysis (GSEA) for immune pathways and an immune infiltration analysis were conducted. The results showed that CUB and Sushi multiple domains 1 (CSMD1) mutation (CSMD1-mut) were associated with higher TMB and better prognosis in patients. The genetic map showed that, compared with wild-type samples, the loss of chromosomes 4q, 5q, 8p, and 9p decreased and the status of microsatellite instability increased in the CSMD1-mut samples. The GSEA analysis showed that immune-related pathways were enriched in the CSMD1-mut samples. The immune infiltration analysis showed that the anti-tumor immune cells were upregulated and that the tumor-promoting immune cells were downregulated in the CSMD1-mut samples. The gene co-expression analysis showed that PD-L1 expression was higher in the CSMD1-mut samples. In summary, CSMD1-mut in gastric cancer was associated with increased TMB and favorable survival and may have potential significance in predicting the efficacy of anti-PD-L1.
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Li, Zhenxiang, Jiamao Lin, Lijuan Zhang, Jingchao Li, Yingyun Zhang, Chenglong Zhao, and Haiyong Wang. "Comprehensive analysis of multiple parameters associated with tumor immune microenvironment in ARID1A mutant cancers." Future Oncology 16, no. 29 (October 2020): 2295–306. http://dx.doi.org/10.2217/fon-2020-0243.
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Aim: To verify the relationship between ARID1A and tumor immune microenvironment thus immune checkpoint inhibitors (ICIs) response. Material & methods: Several public databases were used to characterize the association between ARID1A gene alteration and tumor immunity. Results: The gene mutation frequency was 8.2% in all cancer types. The ARID1A-mutated cancers have higher scores of mutation count, tumor mutational burden, neoantigen load (p < 0.001) and T cell repertoire, B cell repertoire diversity (p < 0.05). The gene mutation has tight association with multiple-activated immune cells. Survival analysis suggested that patients with ARID1A mutant cancers benefit more from ICIs treatment (p = 0.013). Conclusion: The ARID1A gene mutation was correlated with higher tumor immunogenicity and activated antitumor immune microenvironment, resulting in superior cohort that respond well to ICIs.
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Lu, Haodong, Qian Liu, Qing Chang, Jinghai Du, Chunying Zhang, Wang Chang, Xin Guo, et al. "Construction and Evaluation of a Tumor Mutation Burden-Related Prognostic Signature for Thyroid Carcinoma." Computational and Mathematical Methods in Medicine 2021 (October 14, 2021): 1–13. http://dx.doi.org/10.1155/2021/1435827.
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Thyroid carcinoma is a type of prevalent cancer. Its prognostic evaluation depends on clinicopathological features. However, such conventional methods are deficient. Based on mRNA, single nucleotide variants (SNV), and clinical information of thyroid carcinoma from The Cancer Genome Atlas (TCGA) database, this study statistically analyzed mutational signature of patients with this disease. Missense mutation and SNV are the most common variant classification and variant type, respectively. Next, tumor mutation burden (TMB) of sample was calculated. Survival status of high/low TMB groups was analyzed, as well as the relationship between TMB and clinicopathological features. Results revealed that patients with high TMB had poor survival status, and TMB was related to several clinicopathological features. Through analysis on DEGs in high/low TMB groups, 381 DEGs were obtained. They were found to be mainly enriched in muscle tissue development through enrichment analysis. Then, through Cox regression analysis, a 5-gene prognostic signature was established, which was then evaluated through survival curves and receiver operation characteristic (ROC) curves. The result showed that the signature was able to effectively predict patient’s prognosis and to serve as an independent prognostic risk factor. Finally, through Gene Set Enrichment Analysis (GSEA) on high/low-risk groups, DEGs were found to be mainly enriched in signaling pathways related to DNA repair. Overall, based on the TCGA-THCA dataset, we constructed a 5-gene prognostic signature through a trail of bioinformatics analysis.
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Jia, Yuanyuan, Ning He, Yadong Yang, Yuliang Huang, Xiaoyu Zhang, Zhichao Fu, Xiaohong Xu, Jianjun Cao, and Jianfei Wang. "Tumor mutation burden and immune microenvironment analysis of urothelial carcinoma." Journal of Clinical Oncology 39, no. 6_suppl (February 20, 2021): 494. http://dx.doi.org/10.1200/jco.2021.39.6_suppl.494.
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494 Background: Tumor mutation burden (TMB) has been established as a biomarker for response to immune therapy and prognosis in various cancers. However, the correlation between TMB and immune microenvironment remains unwell studied, especially in urothelial carcinoma. This study was aimed to investigate the relationship between TMB and other immunotherapy related biomarkers, including genetic alterations, APOBEC signature, microsatellite instability (MSI), PD-L1 expression and immune cell infiltration in urothelial carcinoma. Methods: 131 patients with urothelial carcinoma admitted from October 2018 to May 2020 were included. Total DNA was isolated from FFPE or fresh tissues. Mutation profiles, APOBEC signature and MSI scores were obtained by next-generation sequencing based a 642 cancer genes panel assay. PD-L1 expression, CD8+ T-cells and tumor-infiltrating lymphocytes density were evaluated by immunohistochemistry. The correlation was analyzed by Wilcoxon signed-rank test. Results: The mutation landscape showed that TP53 mutation is the most common alterations (n = 64/131, 48.9%), followed by KMT2D alterations (n = 49/131, 37.4%), KDM6A mutations (n = 42/131, 32.1%), MUC17 mutations (n = 42/131, 32.1%). The median TMB was 5.06 Muts/Mb (0-118 Muts/Mb). 2 of 131 patients showed MSI-H, who exhibited a much higher TMB (41, 118 Muts/Mb). Further analysis showed that TMB in the patients with certain gene mutations (such as TP53, KMT2D, KDM6A and MUC17) was significantly higher than those wild type ones (p < 0.05). Meanwhile, the high APOBEC-enrichment group has a higher TMB than the low APOBEC-enrichment group (p = 0.045). Furthermore,we observed that the patients with a higher PD-L1 expression (n = 28/131, 21.4%, at a combined positive score cut-off value of 10) also showed a significantly higher TMB (p = 0.016), and TMB in the patients with higher density of CD8+ T-cells (n = 42/131, 32.1%, at a cut-off value of 5%) was also significantly higher than that of the group with lower density of CD8+ T-cells (p = 0.039). Conclusions: This study provides new insights into the correlation between the TMB and the immune microenvironment in urothelial carcinoma. The result may be a reference to immunotherapy.
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Homeier-Bachmann, Timo, Anne K. Schütz, Sylvia Dreyer, Julien Glanz, Katharina Schaufler, and Franz J. Conraths. "Genomic Analysis of ESBL-Producing E. coli in Wildlife from North-Eastern Germany." Antibiotics 11, no. 2 (January 18, 2022): 123. http://dx.doi.org/10.3390/antibiotics11020123.
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Antimicrobial resistance (AMR) is a serious global health threat and extended-spectrum beta-lactamase (ESBL)-producing Enterobacterales are a major contributor. This study aimed to gain a deeper insight into the AMR burden of wild animals. In total, 1595 fecal samples were collected by two systematic searches in Mecklenburg-Western Pomerania, north-east Germany. Samples were screened for ESBL-carrying Escherichia (E.) coli and isolates found were further analyzed using antimicrobial susceptibility testing and whole-genome sequencing. We found an estimated prevalence of 1.2% ESBL-producing E. coli in wild boar and 1.1% in wild ruminants. CTX-M-1 was the most abundant CTX-M type. We also examined fecal samples from wild boar and wild ruminants using shotgun metagenomics to gain insight into the resistome in wild animals. The latter revealed significantly lower normalized counts for AMR genes in wildlife samples compared to farm animals. The AMR gene levels were lower in wild ruminants than in wild boar. In conclusion, our study revealed a low prevalence of ESBL-producing E. coli and a low overall AMR gene burden in wild boar and wild ruminants, probably due to the secluded location of the search area.
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Bu, Fengxiao, Yuzhou Zhang, Kai Wang, Nicolo Ghiringhelli Borsa, Michael B. Jones, Amanda O. Taylor, Erika Takanami, et al. "Genetic Analysis of 400 Patients Refines Understanding and Implicates a New Gene in Atypical Hemolytic Uremic Syndrome." Journal of the American Society of Nephrology 29, no. 12 (October 30, 2018): 2809–19. http://dx.doi.org/10.1681/asn.2018070759.
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BackgroundGenetic variation in complement genes is a predisposing factor for atypical hemolytic uremic syndrome (aHUS), a life-threatening thrombotic microangiopathy, however interpreting the effects of genetic variants is challenging and often ambiguous.Methods We analyzed 93 complement and coagulation genes in 400 patients with aHUS, using as controls 600 healthy individuals from Iowa and 63,345 non-Finnish European individuals from the Genome Aggregation Database. After adjusting for population stratification, we then applied the Fisher exact, modified Poisson exact, and optimal unified sequence kernel association tests to assess gene-based variant burden. We also applied a sliding-window analysis to define the frequency range over which variant burden was significant.ResultsWe found that patients with aHUS are enriched for ultrarare coding variants in the CFH, C3, CD46, CFI, DGKE, and VTN genes. The majority of the significance is contributed by variants with a minor allele frequency of <0.1%. Disease-related variants tend to occur in specific complement protein domains of FH, CD46, and C3. We observed no enrichment for multiple rare coding variants in gene-gene combinations.ConclusionsIn known aHUS-associated genes, variants with a minor allele frequency >0.1% should not be considered pathogenic unless valid enrichment and/or functional evidence are available. VTN, which encodes vitronectin, an inhibitor of the terminal complement pathway, is implicated as a novel aHUS-associated gene. Patients with aHUS are not enriched for multiple rare variants in complement genes. In aggregate, these data may help in directing clinical management of aHUS.
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He, Xinwei, Ming Yu, Xuezhong Wang, Jixian Chen, and Xianglin Li. "Analysis of Threshold Change of Tumor Mutation Burden in Gastric Cancer." Journal of Oncology 2021 (July 22, 2021): 1–6. http://dx.doi.org/10.1155/2021/3374939.
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Background. The purpose of this study was to investigate the change of tumor mutation burden (TMB) in gastric cancer (GC) and its relationship with prognosis. Methods. A total of 262 patients with GC from January 2018 to December 2019 were included in this study. All patients were in the advanced stage and were treated with surgical removal of D2 lymph nodes and dissection. Clinical data and gene expression profile data of the GC dataset in The Cancer Genome Atlas were collected. Patients were randomly divided into a high-level group and a low-level group according to the TMB of 8 mutations/Mb. TMB of GC was calculated based on cell mutation data. Cox regression model was used to evaluate the relationship between TMB and prognosis of GC patients. Results. The total mutation rate of 262GC patients was 92.85%. The top 5 mutant genes were TP53, RB1, ARID1A, KMT2B, and RET. The expression level of TMB in GC patients was statistically significant with age, drinking history, and differentiation type. 94 of the 262 patients died, and 168 survived during the follow-up period. Patients with a high level of TMB had a worse prognosis than those with low level of TMB. The results of univariate and multivariate logistic analysis showed that the overall survival rate of GC patients was statistically significant with age, drinking history, clinical stage, differentiation type, and TMB. Conclusion. GC patients are often accompanied by changes in TMB, and its expression level is closely related to the degree of pathological differentiation, which is an independent factor affecting the prognosis of GC patients. High TMB value can evaluate the prognosis and provide a reference for the formulation of clinical treatment plans for GC patients.
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Xie, Yihui, Ziqian Xu, Xingyu Mei, and Weimin Shi. "A Necroptosis-Related Gene Signature to Predict the Prognosis of Skin Cutaneous Melanoma." Disease Markers 2022 (November 16, 2022): 1–18. http://dx.doi.org/10.1155/2022/8232024.
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The prognosis of skin cutaneous melanoma (SKCM) remains poor, and patients with SKCM show a poor response to immunotherapy. Thus, we aimed to identify necroptosis-related biomarkers, which can help predict the prognosis of SKCM and improve the effectiveness of precision medicine. Data of SKCM were obtained from The Cancer Genome Atlas (TCGA) and GEO databases. TCGA samples were classified into two clusters by consensus clustering of necroptosis-related genes. Univariate Cox and least absolute shrinkage and selection operator regression analyses led to the identification of 11 genes, which were used to construct a prognostic model. GSE65904 was used as the test set. Principal component, t-distributed stochastic neighbor embedding, and Kaplan–Meier survival analyses indicated that samples in the train and test sets could be divided into two groups, with the high-risk group showing a worse prognosis. Univariate and multivariate Cox regression analyses were performed, and a nomogram, calibration curve, and time-dependent receiver operating characteristic curve were constructed to verify the efficacy of our model. The 1-, 3-, and 5-year areas under the receiver operating characteristic curves for the train set were 0.702, 0.663, and 0.701 and for the test set were 0.613, 0.627, and 0.637, respectively. Moreover, we performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses between the high- and low-risk groups. Single sample gene set enrichment analysis, immune cell infiltration analysis, tumor microenvironment scores, immune checkpoint analysis, and half-maximal inhibitory concentration prediction indicated that the high-risk group showed weaker antitumor immunity; further, the response to immune checkpoint inhibitors was worse, and the high-risk group was sensitive to fewer antitumor drugs. Tumor mutational burden analysis, Kaplan–Meier survival analysis, and correlation analysis between risk score and RNA stemness score revealed that the high-risk group with low tumor mutational burden and high RNA stemness score was potentially associated with poor prognosis. To conclude, our model, which was based on 11 necroptosis-related genes, could predict the prognosis of SKCM; in addition, it has guiding significance for the selection of clinical treatment and provides new research directions to enhance necroptosis against SKCM.
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Shao, Ting, Xiling Jiang, Guochang Bao, Chunsheng Li, and Changgang Guo. "Comprehensive Analysis of the Oncogenic Role of Targeting Protein for Xklp2 (TPX2) in Human Malignancies." Disease Markers 2022 (October 18, 2022): 1–13. http://dx.doi.org/10.1155/2022/7571066.
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Mitosis and spindle assembly require the microtubule-associated protein Xenopus kinesin-like protein 2 (TPX2). Although TPX2 is highly expressed in several malignant tumor forms, little is known about its role in cancer. In this study, we performed the gene set enrichment analysis of TPX2 in 33 types of cancers and an extensive pan-cancer bioinformatic analysis using prognosis, tumor mutational burdens, microsatellite instability, tumor microenvironment, and immune cell infiltration data. According to the differential expression study, TPX2 was found to be overexpressed across all studied cancer types. Based on the survival analysis, increased TPX2 expression was associated with a poor prognosis for most cancers. The TPX2 expression level was confirmed to correlate with the clinical stage, microsatellite instability, and tumor mutational burden across all cancer types. Furthermore, TPX2 expression has been linked to tumor microenvironments and immune cell infiltration, particularly in bladder urothelial carcinoma, liver hepatocellular carcinoma, lung adenocarcinoma, stomach adenocarcinoma, and uterine corpus endometrial carcinoma. Finally, the gene set enrichment analysis implicated TPX2 in the regulation of aminoacyl tRNA biosynthesis, which is the most important tumor cell cycle signaling pathway. This comprehensive pan-cancer analysis shows that TPX2 is a prognostic molecular biomarker for most cancers and suggests its potential as an effective therapeutic target for the treatment of these diseases.
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Hwang, William L., Rachel L. Wolfson, Andrzej Niemierko, Karen J. Marcus, Steven G. DuBois, and Daphne Haas-Kogan. "Clinical Impact of Tumor Mutational Burden in Neuroblastoma." JNCI: Journal of the National Cancer Institute 111, no. 7 (October 10, 2018): 695–99. http://dx.doi.org/10.1093/jnci/djy157.
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Abstract Background Neuroblastoma is the most common pediatric extracranial solid tumor. Within conventional risk groups, there is considerable heterogeneity in outcomes, indicating the need for improved risk stratification. Methods In this study we analyzed the somatic mutational burden of 515 primary, untreated neuroblastoma tumors from three independent cohorts. Mutations in coding regions were determined by whole-exome/genome sequencing of tumor samples compared to matched blood leukocytes. Survival data for 459 patients were available for analysis of 5-year overall survival using the Kaplan–Meier method and log-rank test. All statistical tests were two-sided. Results Despite a low overall somatic mutational burden (mean = 3, range = 0–56), 107 patients were considered to have high mutational burden (>3 mutations). Unfavorable histology and age 18 months and older were associated with high mutational burden. Patients with high mutational burden had inferior 5-year overall survival (29.0%, 95% confidence interval [CI] = 17.2 to 41.8%) vs those with three or fewer somatic mutations (76.2%, 95% CI = 71.5 to 80.3%) (log-rank P < .001) and this association persisted when limiting the analysis to genes included on a 447-gene panel commonly used in clinical practice. On multivariable analysis, mutational burden remained prognostic independent of age, stage, histology and MYCN status. Conclusions This study demonstrates that mutational burden of primary neuroblastoma may be useful in combination with conventional risk factors to optimize risk stratification and guide treatment decisions, pending prospective validation.
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Khvostyk, Viktor. "Hereditary burden in poultry of different species of the Ukrainian gene pool." Scientific Horizons 23, no. 12 (December 29, 2020): 29–35. http://dx.doi.org/10.48077/scihor.23(12).2020.29-35.
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The relevance of the study is conditioned by the need to continually conduct autopsy analysis of dead embryos as an integral part of genetic monitoring of harmful mutations, which may reduce the level of genetic burden in the gene pool of poultry. The study was conducted on poultry of different species of the Ukrainian gene pool: chickens of meat and egg area of productivity, turkeys of the original family lines of the Kharkiv crossing. The purpose of the study was to determine the spectrum and frequency of manifestation of hereditary genetic defects in the development of embryos in land birds of different species, to establish the level of genetic burden. The spectrum and frequency of morphological and anatomical hereditary defects of chicken and turkey embryos were established during pathological and anatomical examination of incubation waste. Visual examination of dead embryos allowed identifying morphological abnormalities in the structure of the skeleton, as well as various disproportions of its individual parts. In chickens of subpopulations with black-striped and white plumage, among birds of all studied groups, the widest range of morphological abnormalities of embryo development was discovered. In meat and egg hens with golden plumage, three anomalies with the same frequency of manifestation of 33.3% were found among the examined dead embryos. Only 1 anomaly “exencephaly” was found in birds with mottled plumage. Two cases of double mutation were found in birds with silver plumage among the examined dead embryos. The level of genetic burden in the studied subpopulations of meat and egg chickens was in the range of 3.45-8.72%. In birds with white and silver plumage, this figure was higher than the maximum allowable value, therefore it is necessary to carry out selection measures to eliminate lethal genes from these populations of chickens. In turkeys of the paternal line 5 and maternal line 6 of the Kharkiv crossing, 2 morphological anomalies of embryo development were found among the examined dead embryos. The level of genetic burden in turkeys of related forms is low – 1.60-1.89%, which does not exceed the maximum allowable value (8.0%). This indicates a low share in the heredity of the used offspring of hidden carriers of “defective” genes. At this stage, the preservation of the gene pool of birds is not threatening for its further breeding
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Wang, Xuehu, Nie Li, Haifeng Guo, Xiaoping Yin, and Yongchang Zheng. "Correlation Analysis of Gene and Radiomic Features in Colorectal Cancer Liver Metastases." Computational and Mathematical Methods in Medicine 2022 (December 24, 2022): 1–13. http://dx.doi.org/10.1155/2022/8559011.
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Colorectal cancer liver metastasis (CRLM) was one of the cancers with high mortality. Clinically, the target point was determined by invasive detection, which increased the suffering of patients and the cost of treatment. If the target point was found through the relationship between early radiomic information and genetic information, it was expected to assist doctors in diagnosing disease, formulating treatment plans, and reducing the pain and burden of patients. In this study, gene coexpression analysis and hub gene mining were first performed on the gene data; secondly, quantitative radiomic features were extracted from CT-enhanced radiomic data to obtain features highly correlated with CRLM; and finally, we analyzed the relationship between gene features and radiomic feature correlations by establishing a link between early radiomic features and gene sequencing and finding highly correlated expressions. This experiment demonstrated that radiomic features could be used to mine gene attributes. Based on the four previously identified genes (NRAS, KRAS, BRAF, and PIK3CA), we identified two novel genes, MAPK1 and STAT1, highly associated with CRLM. There were specific correlations between these 6 genes and radiomic features (shape_elongation, glcm, glszm, firstorder_10percentile, gradient, exponent_firstorder_Range, and gradient_glszm_SmallAreaLowGrayLevel). Therefore, this paper established the correlation between radiomic features and genes, and through radiomic features, we could find the genes associated with them, which was expected to achieve noninvasive prediction of liver metastasis.
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Li, Ning, Ling Li, and Yongshun Chen. "The Identification of Core Gene Expression Signature in Hepatocellular Carcinoma." Oxidative Medicine and Cellular Longevity 2018 (May 27, 2018): 1–15. http://dx.doi.org/10.1155/2018/3478305.
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Hepatocellular carcinoma (HCC) is one of the most common malignancies, which causes serious financial burden worldwide. This study aims to investigate the potential mechanisms contributing to HCC and identify core biomarkers. The HCC gene expression profile GSE41804 was picked out to analyze the differentially expressed genes (DEGs). Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were carried out using DAVID. We constructed a protein-protein interaction (PPI) network to visualize interactions of the DEGs. The survival analysis of these hub genes was conducted to evaluate their potential effects on HCC. In this analysis, 503 DEGs were captured (360 downregulated genes and 143 upregulated genes). Meanwhile, 15 hub genes were identified. GO analysis showed that the DEGs were mainly enriched in oxidative stress, cell cycle, and extracellular structure. KEGG analysis suggested the DEGs were enriched in the absorption, metabolism, and cell cycle pathway. PPI network disclosed that the top3 modules were mainly enriched in cell cycle, oxidative stress, and liver detoxification. In conclusion, our analysis uncovered that the alterations of oxidative stress and cell cycle are two major signatures of HCC. TOP2A, CCNB1, and KIF4A might promote the development of HCC, especially in proliferation and differentiation, which could be novel biomarkers and targets for diagnosis and treatment of HCC.
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Lu, Lin, Peiling Zhang, Xiaofei Cao, and Mingmei Guan. "Prognosis and Characterization of Immune Microenvironment in Head and Neck Squamous Cell Carcinoma through a Pyroptosis-Related Signature." Journal of Oncology 2022 (April 6, 2022): 1–19. http://dx.doi.org/10.1155/2022/1539659.
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Pyroptosis, as a novel identified programmed cell death, is closely correlated with tumor immunity and shows potential roles in cancer treatment. Discerning a pyroptosis-related gene signature and its correlations with tumor immune microenvironment is critical in head and neck squamous cell carcinoma (HNSCC). Transcriptome data and corresponding clinical data were downloaded from TCGA and GEO databases. Tumor mutation burden (TMB) data were obtained from TCGA database. Firstly, univariate and least absolute shrinkage and selection operator (LASSO) regression analyses were used to construct a six pyroptosis-related gene signature. Kaplan–Meier analysis, receiver operating characteristic (ROC) curves, and principal component analysis (PCA) results verified that the risk model has good performance in predicting the survival. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed that the pyroptosis-related gene signature was immune related. Finally, the immune landscape and immunotherapy sensitivity prediction capabilities of the risk model were further explored. There were close correlations between the overall survival (OS) and various immune cells and immune functions. Single-sample gene set enrichment analysis (ssGSEA) showed that high risk group had decreased expression of various immune cells and lower activities of immune functions. Meanwhile, tumor mutation burden (TMB) data combining risk score could well predict the OS of HNSCC patients. However, tumor immune dysfunction and exclusion (TIDE) analysis revealed that there was no significant difference in the sensitivity to immunotherapies between high and low risk groups. Finally, a nomogram based on risk score and clinicopathological parameters was constructed. And, the risk model demonstrated better sensitivity and specificity than TIDE scores and T-cell-inflamed signature (TIS). In conclusion, although the risk model could not well predict the immune escape and response to immunotherapies, the signature established by pyroptosis-related genes, with better sensitivity and specificity than TIDE scores and TIS signature, could be used for predicting prognosis and immune status of HNSCC patients.
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Zhao, Yulan, Ting Huang, and Pintong Huang. "Integrated Analysis of Tumor Mutation Burden and Immune Infiltrates in Hepatocellular Carcinoma." Diagnostics 12, no. 8 (August 8, 2022): 1918. http://dx.doi.org/10.3390/diagnostics12081918.
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Tumor mutation burdens (TMBs) act as an indicator of immunotherapeutic responsiveness in various tumors. However, the relationship between TMBs and immune cell infiltrates in hepatocellular carcinoma (HCC) is still obscure. The present study aimed to explore the potential diagnostic markers of TMBs for HCC and analyze the role of immune cell infiltration in this pathology. We used OA datasets from The Cancer Genome Atlas database. First, the “maftools” package was used to screen the highest mutation frequency in all samples. R software was used to identify differentially expressed genes (DEGs) according to mutation frequency and perform functional correlation analysis. Then, the gene ontology (GO) enrichment analysis was performed with “clusterProfiler”, “enrichplot”, and “ggplot2” packages. Finally, the correlations between diagnostic markers and infiltrating immune cells were analyzed, and CIBERSORT was used to evaluate the infiltration of immune cells in HCC tissues. As a result, we identified a total of 359 DEGs in this study. These DEGs may affect HCC prognosis by regulating fatty acid metabolism, hypoxia, and the P53 pathway. The top 15 genes were selected as the hub genes through PPI network analysis. SRSF1, SNRPA1, and SRSF3 showed strong similarities in biological effects, NCBP2 was demonstrated as a diagnostic marker of HCC, and high NCBP2 expression was significantly correlated with poor over survival (OS) in HCC. In addition, NCBP2 expression was correlated with the infiltration of B cells (r = 0.364, p = 3.30 × 10−12), CD8+ T cells (r = 0.295, p = 2.71 × 10−8), CD4+ T cells, (r = 0.484, p = 1.37 × 10−21), macrophages (r = 0.551, p = 1.97 × 10−28), neutrophils (r = 0.457, p = 3.26 × 10−19), and dendritic cells (r = 0.453, p = 1.97 × 10−18). Immune cell infiltration analysis revealed that the degree of central memory T-cell (Tcm) infiltration may be correlated with the HCC process. In conclusion, NCBP2 can be used as diagnostic markers of HCC, and immune cell infiltration plays an important role in the occurrence and progression of HCC.
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Guo, Yang, Yu Heng, Hui Chen, Qiang Huang, Chunping Wu, Lei Tao, and Liang Zhou. "Prognostic Values of METTL3 and Its Roles in Tumor Immune Microenvironment in Pan-Cancer." Journal of Clinical Medicine 12, no. 1 (December 25, 2022): 155. http://dx.doi.org/10.3390/jcm12010155.
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Background: N6-methyladenosine (m6A) is among the most prevalent RNA modifications regulating RNA metabolism. The roles of methyltransferase-like 3 (METTL3), a core catalytic subunit, in various cancers remain unclear. Methods: The expression levels of METTL3 in pan-cancer were profiled and their prognostic values were examined. We assessed the relationships between METTL3 expression levels and tumor immune infiltration levels, immune checkpoint gene expression, immune neoantigens, tumor mutation burden, microsatellite instability, and DNA mismatch repair gene expression. Furthermore, a protein–protein interaction network was drawn, and gene set enrichment analysis was conducted to explore the functions of METTL3. Results: METTL3 expression levels were elevated in most cancers, with high expression associated with poorer overall and disease-free survival. METTL3 levels were significantly related to immune cell infiltration, tumor mutation burden, microsatellite instability, mismatch repair genes, and immune checkpoint gene levels. METTL3 was enriched in pathways related to RNA modification and metabolism and correlated with epithelial–mesenchymal transition. Conclusions: METTL3 serves as an oncogene in most cancer types and shows potential as a prognostic biomarker. Additionally, our comprehensive pan-cancer analysis suggested that METTL3 is involved in regulating the tumor immune microenvironments and epithelial–mesenchymal transition via modulating RNA modification and metabolism, making it a potential therapeutic target.
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Yang, Jian, Bin Yan, Yajuan Fan, Lihong Yang, Binbin Zhao, Xiaoyan He, Qingyan Ma, et al. "Integrative analysis of transcriptome-wide association study and gene expression profiling identifies candidate genes associated with stroke." PeerJ 7 (July 29, 2019): e7435. http://dx.doi.org/10.7717/peerj.7435.
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Background Stroke is a major public health burden worldwide. Although genetic variation is known to play a role in the pathogenesis of stroke, the specific pathogenic mechanisms are still unclear. Transcriptome-wide association studies (TWAS) is a powerful approach to prioritize candidate risk genes underlying complex traits. However, this approach has not been applied in stroke. Methods We conducted an integrative analysis of TWAS using data from the MEGASTROKE Consortium and gene expression profiling to identify candidate genes for the pathogenesis of stroke. Gene ontology (GO) enrichment analysis was also conducted to detect functional gene sets. Results The TWAS identified 515 transcriptome-wide significant tissue-specific genes, among which SLC25A44 (P = 5.46E−10) and LRCH1 (P = 1.54E−6) were significant by Bonferroni test for stroke. After validation with gene expression profiling, 19 unique genes were recognized. GO enrichment analysis identified eight significant GO functional gene sets, including regulation of cell shape (P = 0.0059), face morphogenesis (P = 0.0247), and positive regulation of ATPase activity (P = 0.0256). Conclusions Our study identified multiple stroke-associated genes and gene sets, and this analysis provided novel insights into the genetic mechanisms underlying stroke.
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Zhang, Lei, Dahai Hu, Shuchen Huangfu, Jiaxin Zhou, Wei Wang, Shijin Liu, Hui Tang, Jinghua Pan, and Yunlong Pan. "DNA Repair and Replication-Related Gene Signature Based on Tumor Mutation Burden Reveals Prognostic and Immunotherapy Response in Gastric Cancer." Journal of Oncology 2022 (January 11, 2022): 1–17. http://dx.doi.org/10.1155/2022/6469523.
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The genomic variant features (mutations, deletions, structural variants, etc.) within gastric cancer impact its evolution and immunogenicity. The tumor has developed several coping strategies to respond to these changes by DNA repair and replication (DRR). However, the intrinsic relationship between the associated DRR-related genes and gastric cancer progression remained unknown. This study selected DRR-related genes with tumor mutation burden based on the TCGA (The Cancer Genome Atlas) database of gastric cancer transcriptome and mutation data. The prognosis model of seven genes (LAMA2, CREB3L3, SELP, ABCC9, CYP1B1, CDH2, and GAMT) was constructed by a univariate and LASSO regression analysis and divided into high-risk and low-risk groups with the median risk score. Survival analysis showed that overall survival (OS) was lower in the high-risk group than that in the low-risk group. Moreover, patients with gastric cancer in the high-risk group have worse survival in different subgroups, including age, gender, histological grade, and TNM stage. The nomogram that included risk scores for DRR-related genes could accurately foresee OS of patients with gastric cancer. Interestingly, the tumor mutation burden score was higher in the low-risk group than that in the high-risk group, and the risk score for DRR-related genes was negatively correlated with tumor mutation burden in gastric cancer. Next, we further combined the risk score and tumor mutation burden to evaluate the prognosis of gastric cancer patients. The low-risk cohort had a better prognosis than the high-risk cohort in the high tumor mutation burden subgroup. The number of mutation types in the high-risk group was lower than that in the low-risk group. In the immune microenvironment of gastric cancer, more naïve B cells, memory resting CD4+ T cells, Treg cells, monocytes cells, and resting mast cells were infiltrated in the high-risk group. At last, PD-L1 and IAP expressions were negatively correlated with the risk scores; patients with gastric cancer in the low-risk group showed better immunotherapy outcomes than those in the high-risk group. Overall, the DRR-related gene signature based on tumor mutation burden is a novel biomarker for prognostic and immunotherapy response in patients with gastric cancer.
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Fu, Yue, Guanpingsheng Luo, Brad J. Spellberg, John E. Edwards, and Ashraf S. Ibrahim. "Gene Overexpression/Suppression Analysis of Candidate Virulence Factors of Candida albicans." Eukaryotic Cell 7, no. 3 (January 4, 2008): 483–92. http://dx.doi.org/10.1128/ec.00445-07.
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ABSTRACT We developed a conditional overexpression/suppression genetic strategy in Candida albicans to enable simultaneous testing of gain or loss of function in order to identify new virulence factors. The strategy involved insertion of a strong, tetracycline-regulated promoter in front of the gene of interest. To validate the strategy, a library of genes encoding glycosylphosphatidylinositol (GPI)-anchored surface proteins was screened for virulence phenotypes in vitro. During the screening, overexpression of IFF4 was found to increase the adherence of C. albicans to plastic and to human epithelial cells, but not endothelial cells. Consistent with the in vitro results, IFF4 overexpression modestly increased the tissue fungal burden during murine vaginal candidiasis. In addition to the in vitro screening tests, IFF4 overexpression was found to increase C. albicans susceptibility to neutrophil-mediated killing. Furthermore, IFF4 overexpression decreased the severity of hematogenously disseminated candidiasis in normal mice, but not in neutropenic mice, again consistent with the in vitro phenotype. Overexpression of 12 other GPI proteins did not affect normal GPI protein cell surface accumulation, demonstrating that the overexpression strategy did not affect the cell capacity for making such proteins. These data indicate that the same gene can increase or decrease candidal virulence in distinct models of infection, emphasizing the importance of studying virulence genes in different anatomical contexts. Finally, these data validate the use of a conditional overexpression/suppression genetic strategy to identify candidal virulence factors.
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Svishcheva, Gulnara R., Nadezhda M. Belonogova, Irina V. Zorkoltseva, Anatoly V. Kirichenko, and Tatiana I. Axenovich. "Gene-based association tests using GWAS summary statistics." Bioinformatics 35, no. 19 (March 12, 2019): 3701–8. http://dx.doi.org/10.1093/bioinformatics/btz172.
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Abstract Motivation A huge number of genome-wide association studies (GWAS) summary statistics freely available in databases provide a new material for gene-based association analysis aimed at identifying rare genetic variants. Only a few of the many popular gene-based methods developed for individual genotype and phenotype data are adapted for the practical use of the GWAS summary statistics as input. Results We analytically prove and numerically illustrate that all popular powerful methods developed for gene-based association analysis of individual phenotype and genotype data can be modified to utilize GWAS summary statistics. We have modified and implemented all of the popular methods, including burden and kernel machine-based tests, multiple and functional linear regression, principal components analysis and others, in the R package sumFREGAT. Using real summary statistics for coronary artery disease, we show that the new package is able to detect genes not found by the existing packages. Availability and implementation The R package sumFREGAT is freely and publicly available at: https://CRAN.R-project.org/package=sumFREGAT. Supplementary information Supplementary data are available at Bioinformatics online.
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Zhou, Jiao, Qiumei Yao, Robert Peter Gale, Jinlan Li, Lingdi Li, Ning Li, Shanshan Chen, and Guorui Ruan. "A Rapid, Sensitive and Specific Method for Quantifying Calr Mutant Allele Burden in Persons with Myeloproliferative Neoplasms." Blood 126, no. 23 (December 3, 2015): 5210. http://dx.doi.org/10.1182/blood.v126.23.5210.5210.
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Abstract Background: CALR mutations were recently identified in a substantial proportion of persons with essential thrombocythemia (ET) and with primary myelofibrosis (PMF) without JAK2V617F. Consequently rapid, sensitive and specific methods to detect and quantify these mutations are needed. Methods: We studied samples from 1088 persons with myeloproliferative neoplasms (MPNs) including 421 JAK2V617F negative subjects with ET, PMF, polycythemia vera (PV), chronic myeloid leukemia (CML) and hyper-eosinophilic syndrome (HES). Detection of CALR exon 9 mutations was done by PCR amplification followed by fragment length analysis and direct sequencing. Dilution assays were used to determine CALR mutant allele burden. Results: We detected CALR mutations in blood and bone marrow samples from 152 subjects with ET and with PMF but not in samples from normal or persons with PV, CML or HES. CALR mutant peaks were distinct from wild-type peaks and dilution experiments indicated a sensitivity level of 0.5-5% for a CALR mutant allele in a wild-type background. Diverse types of mutations were detected including deletions, insertions and complex indels. All mutations were confirmed by direct sequencing. We also used dilution experiments to quantify mutant allele burden. We were able to reproducibly detect mutant allele levels as low 5% (0.5-5%) in a wild-type background. Conclusions: PCR amplification followed by fragment length analysis is a rapid, sensitive and specific method for screening persons with MPNs for CALR mutations, especially those with ET and PV with JAK2V617F and for estimating mutant allele burden. Figure 1. Standard curve for the detection of mutant allele burden. Figure 1. Standard curve for the detection of mutant allele burden. Figure 2. Titration analyses of sensitivity of CALR mutation screening by sequencing and fragment analyses. Figure 2. Titration analyses of sensitivity of CALR mutation screening by sequencing and fragment analyses. Figure 3. Figure 3 Sequencing traces show heterozygous mutation of CALR. Gene scan electropherogram from PCR method and partial sequence of CALR exon 9 from sequencing method (numbering according to GenBank access number: NC_000019.9). A-P: Detected a wild type and 15 CALR mutation types by sequencing and fragment analysis methods. A: wild type, B-I: deletions, H-L: insertions, M-P: complex indels. Figure 3. Figure 3 Sequencing traces show heterozygous mutation of CALR. Gene scan electropherogram from PCR method and partial sequence of CALR exon 9 from sequencing method (numbering according to GenBank access number: NC_000019.9). A-P: Detected a wild type and 15 CALR mutation types by sequencing and fragment analysis methods. A: wild type, B-I: deletions, H-L: insertions, M-P: complex indels. Disclosures No relevant conflicts of interest to declare.
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Tian, Wen-Juan, Shan-Shan Liu, and Bu-Rong Li. "The Combined Detection of Immune Genes for Predicting the Prognosis of Patients With Non-Small Cell Lung Cancer." Technology in Cancer Research & Treatment 19 (January 1, 2020): 153303382097750. http://dx.doi.org/10.1177/1533033820977504.
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Lung cancer is one of the leading causes of cancer-related death. In recent years, there has been an increasing interest in the fields of tumor and immunity. This study focused on the possible prognostic value of immune genes in non-small cell lung cancer patients. We used The Cancer Genome Atlas (TCGA) to download gene expression data and clinical information of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). The immune gene list was downloaded from the Immport database. We then constructed immune gene prognostic models on the basis of Cox regression analysis. We further evaluated the clinical significance of the models via survival analysis, receiver operating characteristic (ROC) curves, and independent prognostic factor analysis. Moreover, we analyzed the associations of prognostic models with both mutation burdens and neoantigens. Using the Gene Expression Omnibus (GEO) and Kaplan–Meier plotter databases, we evaluated the validity of the prognostic models. The prognostic model of LUAD included 13 immune genes, and the prognostic model of LUSC contained 10 immune genes. High-risk patients based on prognostic models had a lower 5-year survival rate than did low-risk patients. The ROC curve analysis demonstrated the prediction accuracy of the prognostic models, as the area under the curve (AUC) was 0.742, 0.707, and 0.711 for LUAD, and 0.668, 0.703, and 0.668 for LUSC, when the predicted survival times were 1, 3, and 5 years, respectively. The mutation burden analysis showed that mutation level was associated with the risk score in patients with LUAD. The analysis based on GEO and Kaplan–Meier plotter demonstrated the prognostic validity of the models. Therefore, immune gene-related models of LUAD and LUSC can predict prognosis. Further study of these genes may enable us to better distinguish between LUAD and LUSC and lead to improvement in immunotherapy for lung cancer.
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Lerner, Seth P., Gordon Robertson, Jaegil Kim, Andrew Cherniack, Guangwu Guo, Rehan Akbani, Rupa S. Kanchi, et al. "Comprehensive molecular characterization and analysis of muscle-invasive urothelial carcinomas." Journal of Clinical Oncology 35, no. 15_suppl (May 20, 2017): 4500. http://dx.doi.org/10.1200/jco.2017.35.15_suppl.4500.
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4500 Background: We reported the integrated molecular analysis of 131 tumors in 2014 (Nature 507:315, 2014) and now report on the entire cohort of 412 tumors from the TCGA project in chemotherapy-naïve, muscle-invasive urothelial bladder cancer. Methods: Following strict clinical and pathologic quality control, tumors were analyzed for DNA copy number variants, somatic mutations (WES), DNA methylation, mRNA, non-coding RNA (lncRNA and miRNA) and (phospho-) protein expression, gene fusions, viral integration, pathway perturbation, clinical correlates, outcomes, and histopathology. Results: There was a high overall somatic mutation rate (8.2/Mb), as previously reported. There were 58 significantly mutated genes (SMGs) (MutSig_2CV), increased from 32 in the original report. We identified 5 mutation signatures including APOBEC-a and b, ERCC2, C > T_CpG, and a single ultra-mutated sample with a functional POLE mutation. APOBEC mutagenesis explained 70% of the mutation burden and was associated with survival (p = 0.0013). High mutation burden and neoantigen load were also associated with improved outcome (p = 0.00014 and 0.00078). The previously identified four mRNA subtypes were predicted on the larger set and also identified a novel poor-survival ‘neuronal’ subtype that nevertheless lacked small cell or neuroendocrine histology. Clustering converged for mRNA, lncRNA and miRNA expression, and for inferred activity of gene sets associated with regulator expression. We identified subsets with differential epithelial-mesenchymal transition scores, carcinoma-in-situ scores, and survival, with implications for distinct therapeutic potential. Conclusions: This integrated analysis of 412 TCGA patient samples validates and extends observations from the first 131 patients and significantly increases our power to detect additional low-frequency aberrations. The results provide unique insights into mechanisms of bladder cancer development, and identify novel subsets of MIBC that may benefit from differential treatment approaches.
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Don, Janith, Sara A. Byron, Guangfa Zhang, Tyler Izatt, Jiaming Zhang, Bethany Davis, Bryce Turner, et al. "Abstract A006: Increased germline mutational burden in individuals of African ancestry: Implications for interpretation of tumor mutation burden." Cancer Epidemiology, Biomarkers & Prevention 32, no. 1_Supplement (January 1, 2023): A006. http://dx.doi.org/10.1158/1538-7755.disp22-a006.
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Abstract Introduction: Tumor mutation burden (TMB), defined as the number of somatic gene mutations per megabase in a tumor genome, is used clinically to identify cancer patients that may respond to immune checkpoint inhibitors. Recent studies suggest that patient ancestry can influence TMB, where individuals of African ancestry were found to have elevated TMB values based on tumor-only sequencing analysis. However, the impact of patient ancestry on germline mutational burden and implications for interpretation of tumor-only mutational burden data is largely unexplored. Methods: We examined the influence of patient ancestry on germline and tumor mutation burden using tumor-normal whole exome sequencing (WES) data from a pan-cancer cohort of 1228 individuals from a single institution. Genetic ancestry was estimated from constitutional WES data using single nucleotide polymorphism weights from external reference panels. Variant calling was performed using constitutional, tumor-only, and paired tumor-normal workflows. Total and loss-of-function burden scores were calculated for each participant from each workflow based on the total number of mutations detected in each sample and the total number of predicted loss-of-function mutations, based on snpEff annotations, respectively. Results: Genetic ancestry analysis found that one-third of this pan-cancer cohort was of non-European ancestry. 9.4% of individuals were of Eastern Asian ancestry, 5.3% of African ancestry, 1.0% of South Asian ancestry, 0.2% of Native American ancestry, and 17.1% of admixed ancestry, predominantly European and Native American admixed ancestry (15.6%). Total and loss-of-function germline burden scores varied across ancestral groups, with individuals of African ancestry showing significantly increased germline burden scores compared to other ancestral groups (p<0.0001). Tumor-only analysis also showed increased mutation burden for individuals of African ancestry. However, when private and rare germline variation was taken into account using paired tumor-normal analysis, tumor mutation burden did not differ based on patient ancestry, suggesting the differences seen in tumor-only analysis are due to germline variation rather than differences in true somatic mutation burden. Conclusion: Our study reveals that the paucity of knowledge of ancestry-specific reference genomes leads to unacceptable health disparities in cancer, specifically in patients with African ancestry. We show that germline mutational burden varies by ancestral background, with individuals of African ancestry displaying increased genetic variation compared to other ancestral populations. These results suggest that patient ancestry should be considered when interpreting tumor mutational burden values, particularly from tumor-only analysis. Approaches utilizing paired tumor-normal analysis or ancestry-specific reference genomes can aid in more accurate assessment of TMB, thereby avoiding futile treatments targeted at presumed high mutational burden tumors specifically in African American populations. Citation Format: Janith Don, Sara A. Byron, Guangfa Zhang, Tyler Izatt, Jiaming Zhang, Bethany Davis, Bryce Turner, Jonathan J. Keats, Jeffrey M. Trent, Lorna Rodriguez-Rodriguez, Nicholas J. Schork. Increased germline mutational burden in individuals of African ancestry: Implications for interpretation of tumor mutation burden [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr A006.
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Fornage, Myriam, Joshua C. Bis, Vincent Chouraki, Li An Lin, Anita DeStefano, Jennifer A. Brody, Donna M. Muzny, et al. "Abstract 148: Whole Exome Sequence Analysis of Cerebral White Matter Hyperintensities on MRI." Stroke 46, suppl_1 (February 2015). http://dx.doi.org/10.1161/str.46.suppl_1.148.
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White matter hyperintensities (WMH) detected on MRI are commonly identified abnormalities in the adult brain, and are associated with a greater risk of stroke, dementia, and death. Genetic factors play a significant role in WMH etiology, yet, common genetic variants identified by GWAS explain little of the variance in WMH burden. Rare variants with larger effect on the phenotype may be identified from sequence analysis of the protein-coding region of the genome (exome). We sequenced the protein-coding regions of 16,541 genes in 2510 individuals of European or African ancestry from three NHLBI cohorts, and investigated whether putatively functional exomic variants were associated with WMH burden, either individually or in aggregate within a gene. Within each cohort, we used the SeqMeta R package to compute race-specific score statistics for each variant and genotypic covariance matrices within predefined gene regions. These were then combined by meta-analysis to generate single-variant and gene-based tests of association. Only missense, nonsense, and splice variants were included in the analyses. Analyses of 12,790 single variants with minor allele frequency (MAF)≥1% did not identify statistically significant associations based on a Bonferroni-corrected significance threshold. The most significantly associated variant was a common missense variant in the ELL gene (p=2.6x10-5). In the sequence kernel association test (SKAT), which included variants with MAF<5%, five genes were significantly associated with WMH burden (p<0.05/16,541). These have known function in phospholipid binding, transport, and signaling (3 genes); Abeta metabolism (1 gene); and have been previously implicated in microvascular complications of diabetes, hypertension, and obesity. Among 35 candidate genes mapping to five previously reported WMH GWAS loci, association of MRPL38 (chr17q25) was nominally significant by SKAT (p=0.011). This gene contained two missense variants (MAF~1%) also nominally significantly associated with WMH (p=0.040 and 0.017). This study suggests that rare and low frequency variants significantly influence WMH burden and that genes involved in cardiovascular health and disease play a role in WMH etiology.
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Au, Emily, Barbara Jean M. Waddell, Nicole Acosta, Kristine Du, Maria Bautista Chavarriaga, Janine McCalder, Jennifer Van Doorn, et al. "404. Surveillance of Clostridioides difficile Burden in Hospitals Through Wastewater Analysis." Open Forum Infectious Diseases 9, Supplement_2 (December 1, 2022). http://dx.doi.org/10.1093/ofid/ofac492.482.
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Abstract Background New tools capable of dynamic assessment of the varying burden of Clostridioides difficile infections are required to mitigate increased patient morbidity, mortality, and health costs. Wastewater (WW)-based epidemiology (WBE) is an emerging science, enabling comprehensive, inclusive, and unbiased assessment of populations, spatially and temporally. We sought to detect, quantify and track C. difficile across a range of scales using WBE. Methods WW collected from two hospitals; the Rockyview General Hospital (RGH; 600 beds) and Peter Lougheed Centre (PLC; 550 beds) both based in Calgary, were compared to that from a municipal WW Treatment Plant (WWTP) in Calgary, Canada. DNA was extracted from pellets collected after WW centrifugation. A multiplexed quantitative PCR assay was used to quantify the abundance of C. difficile 16S rRNA and toxin A (tcdA) genes. These were then assessed as raw values or as normalized ratios to three fecal biomarker genes: total bacterial 16S rRNA, human 18S rRNA, and Bacteroides HF183 16S rRNA. Kruskal-Wallis and Mann-Whitney tests were performed using RStudio and GraphPad Prism (version 9.3.1). Results Eight weekly samples collected from the RGH demonstrated significant changes in the levels of total C. difficile 16S rRNA gene and tcdA over time (P=0.0004 and P=0.0005, respectively, Kruskal-Wallis). Similar trends in total C. difficile and tcdA burden over time were observed when gene copies were normalized with the three fecal biomarker genes. Over a separate 13-week comparison, C. difficile and tcdA gene target abundance was greater in hospital WW (RGH and PLC) than in community-based samples from the WWTP (P=0.048 and P=0.012, respectively, Mann-Whitney). There was no significant difference in C. difficile and tcdA gene target abundance between RGH and PLC (P=0.896 and P=0.343, respectively, Mann-Whitney). Clostridioides difficile genes in wastewater measured by quantitative PCR. C. difficile 16S rRNA and tcdA gene abundance normalized as a ratio against total bacterial load (16S rRNA) varies over time and is markedly increased in hospitals relative to a municipal wastewater treatment plant in Calgary, Canada. Conclusion WW surveillance is a powerful tool that can monitor the burden the C. difficile across a range of scales in real-time. This tool could augment infection prevention and control and antimicrobial stewardship programs to better understand factors that contribute to colonization and infection. Disclosures Thomas J. Louie, MD, Artugen: Advisor/Consultant|Artugen: Grant/Research Support|Crestone: Advisor/Consultant|Crestone: Grant/Research Support|Finch Therapeutics: Advisor/Consultant|Finch Therapeutics: Grant/Research Support|Rebiotix: Advisor/Consultant|Rebiotix: Grant/Research Support|Seres Therapeutics: Advisor/Consultant|Seres Therapeutics: Grant/Research Support|summit plc: Advisor/Consultant|summit plc: Grant/Research Support|Vedanta Biosciences: Advisor/Consultant|Vedanta Biosciences: Grant/Research Support.
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Wang, Liwei, Fu Chen, Rui Liu, Lei Shi, Guosheng Zhao, and Zhengjian Yan. "Gene expression and immune infiltration in melanoma patients with different mutation burden." BMC Cancer 21, no. 1 (April 9, 2021). http://dx.doi.org/10.1186/s12885-021-08083-1.
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Abstract Background Immunotherapy is a vital component in cancer treatment. However, due to the complex genetic bases of cancer, a clear prediction index for efficacy has not been established. Tumor mutation burden (TMB) is one of the essential factors that affect immunotherapeutic efficacies, but it has not been determined whether the mutation is associated with the survival of Skin Cutaneous Melanoma (SKCM) patients. This study aimed at evaluating the correlation between TMB and immune infiltration. Methods Somatic mutation profiles (n = 467), transcriptome data (n = 471), and their clinical information (n = 447) of all SKCM samples were downloaded from The Cancer Genome Atlas (TCGA) database. For each sample, TMB was calculated as the number of variants per megabase. Based on K-M survival analysis, they were allocated into the high-TMB and low-TMB groups (the optimal cutoff was determined by the ‘surv_cutpoint’ algorithm of survival R package). Then, Gene ontology (GO) and Gene Set Enrichment Analyses (GSEA) were performed, with immune-associated biological pathways found to be significantly enriched in the low-TMB group. Therefore, immune genes that were differentially expressed between the two groups were evaluated in Cox regression to determine their prognostic values, and a four-gene TMB immune prognostic model (TMB-IP) was constructed. Results Elevated TMB levels were associated with better survival outcomes in SKCM patients. Based on the cutoff value in OS analysis, they were divided into high-TMB and low-TMB groups. GSEA revealed that the low-TMB group was associated with immunity while intersection analysis revealed that there were 38 differentially expressed immune-related genes between the two groups. Four TMB-associated immune genes were used to construct a TMB-IP model. The AUC of the ROC curve of this model reached a maximum of 0.75 (95%CI, 0.66–0.85) for OS outcomes. Validation in each clinical subgroup confirmed the efficacy of the model to distinguish between high and low TMB-IP score patients. Conclusions In SKCM patients, low TMB was associated with worse survival outcomes and enriched immune-associated pathways. The four TMB-associated immune genes model can effectively distinguish between high and low-risk patients.
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Lye, Zoe, Jae Young Choi, and Michael D. Purugganan. "Deleterious mutations and the rare allele burden on rice gene expression." Molecular Biology and Evolution, September 8, 2022. http://dx.doi.org/10.1093/molbev/msac193.
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Abstract Deleterious genetic variation is maintained in populations at low frequencies. Under a model of stabilizing selection, rare (and presumably deleterious) genetic variants are associated with increase or decrease in gene expression from some intermediate optimum. We investigate this phenomenon in a population of largely O. sativa ssp. indica rice landraces under normal unstressed wet and stressful drought field conditions. We include single nucleotide polymorphisms, insertion/deletion mutations and structural variants in our analysis and find a stronger association between rare variants and gene expression outliers under the stress condition. We also show an association of the strength of this rare variant effect with linkage, gene expression levels, network connectivity, local recombination rate, and fitness consequence scores, consistent with the stabilizing selection model of gene expression.
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Miao, Huikai, Qiannan Ren, Hongmu Li, Mingyue Zeng, Dongni Chen, Chunmei Xu, Youfang Chen, and Zhesheng Wen. "Comprehensive analysis of the autophagy-dependent ferroptosis-related gene FANCD2 in lung adenocarcinoma." BMC Cancer 22, no. 1 (March 2, 2022). http://dx.doi.org/10.1186/s12885-022-09314-9.
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Abstract Background The development of lung adenocarcinoma (LUAD) involves the interactions between cell proliferation and death. Autophagy-dependent ferroptosis, a distinctive cell death process, was implicated in a multitude of diseases, whereas no research revealing the relationship between autophagy-dependent ferroptosis and LUAD pathogenesis was reported. Thus, the primary objective was to explore the role and potential function of the autophagy-dependent ferroptosis-related genes in LUAD. Methods Clinical information and transcriptome profiling of patients with LUAD were retrieved and downloaded from open-source databases. Autophagy-dependent ferroptosis-related genes were screened by published articles. The critical gene was identified as the intersection between the differentially expressed genes and prognosis-related genes. Patients were divided into high- and low-risk groups using the expression level of the critical gene. The validity of the key gene prognosis model was verified by survival analysis. The correlation between the clinical characteristics of LUAD and the expression level of the key gene was analyzed to explore the clinical significance and prognosis value. And the roles of the key gene in response to chemotherapy, immune microenvironment, and tumor mutation burden were predicted. The validation of key gene expression levels was further performed by quantitative real-time PCR and immunohistochemistry staining. Results FANCD2, an essential autophagy-dependent ferroptosis-related gene by searching database, was confirmed as an independent prognostic factor for LUAD occurrence. The high expression level of FANCD2 was associated with an advantaged TNM stage, a less chemotherapy sensitivity, a low ImmuneScore, which indicated a deactivation status in an immune microenvironment, a high tumor mutation burden, and poor survival for LUAD patients. Pathway enrichment analysis showed that FANCD2 responded to oxidative stress and neutrophil-mediated immunity. Quantitative real-time PCR and immunohistochemistry staining showed that the expression level of FANCD2 is higher in LUAD patients than in normal tissue samples, which was in accordance with the database report. Conclusion FANCD2, an essential gene related to autophagy-dependent ferroptosis, could work as a biomarker, predicting the survival, chemotherapy sensitivity, tumor immunity, and mutation burden of LUAD. Researching autophagy-dependent ferroptosis and targeting the FANCD2 may offer a new perspective for treating and improving prognosis in LUAD.
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Li, Wenjie, Kezhi Zhou, Mengting Li, Qian Hu, Wanhui Wei, Lan Liu, and Qiu Zhao. "Identification of SCN7A as the key gene associated with tumor mutation burden in gastric cancer." BMC Gastroenterology 22, no. 1 (February 5, 2022). http://dx.doi.org/10.1186/s12876-022-02112-4.
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Abstract Objective Previous studies have shown that tumor mutation burden (TMB) in cancer is associated with prognosis. The purpose of this study is to identify TMB related genes in gastric cancer (GC) and to explore their prognostic value. Methods In our research, weighted gene coexpression network analysis (WGCNA) algorithm was used to cluster the most relevant TMB modules in the Cancer Genome Atlas (TCGA) database. Limma package was used to screen the differentially expressed genes, and the intersection was identified as hub genes. We used gene expression profiling interactive analysis (GEPIA) and survival algorithm to analyze the clinical characteristics and prognosis of hub genes in tumor and normal tissue samples of TCGA and Gene Expression Omnibus cohort respectively. We also used CIBERSORT algorithm to calculate the proportion of 22 tumor immune cells in the high and low expression subgroups of hub genes. In addition, we used gene set enrichment analysis (GSEA) to predict the biological function of hub genes. P < 0.05 was considered statistically significant. Results In the TCGA cohort, TMB was significantly correlated with the clinical features of GC (P < 0.05). Through WGCNA and differential gene analysis, we identified SCN7A as the hub gene (P < 0.05, |log2fc|> 1, and mm > 0.8). We found that the expression of SCN7A in tumor tissues was lower than that in normal tissues, and its expression level was also related to overall survival rate and tumor stage. GSEA analysis showed that SCN7A low expression group was enriched with "DNA replication", "base extension repair" and "proteasome" gene sets in GC. In addition, we found that there were significant differences in the infiltration degree of 7 kinds of immune cells between the two groups. Conclusion TMB can indicate the prognosis of gastric cancer. SCN7A is a hub gene associated with TMB, and its low expression is associated with better prognosis.