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1
Schmandt, R., and G. B. Mills. "Genomic components of carcinogenesis." Clinical Chemistry 39, no. 11 (November 1, 1993): 2375–85. http://dx.doi.org/10.1093/clinchem/39.11.2375.
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Abstract Many of the genes encoding growth factors, growth factor receptors, enzymes, and other effector molecules that regulate normal cell growth are designated protooncogenes. Oncogenes, those genes associated with cellular transformation, differ from their protooncogenic progenitors by being mutated, overexpressed, or expressed at inappropriate times or locations in the cell. One of the activities of growth factors is to prime cells to undergo programmed cell death, which is characterized by a series of morphologic changes called apoptosis. In normal cells, specific mediators must be activated or suppressed to bypass programmed cell death. In tumor cells, either the pathways leading to apoptosis are not functional or the mediators that normally "rescue" cells from this fate are overexpressed or constitutively activated. In addition to the biochemical pathways that drive cell division, there are others that limit cell proliferation; these, designated tumor suppressors, anti-oncogenes, or recessive oncogenes, must be inactivated in normal cells to allow passage through the cell cycle and cell proliferation. In contrast to oncogenes, which are overexpressed or activated in tumors, tumor-suppressor genes are frequently inactivated in tumor cells, either by mutation or deletion. Thus, in normal cells a series of checks and balances must be overcome to allow initiation and continuation of cell division. In tumors, these processes are aberrant, resulting in increased rates of cell division, increases in the proportion of cells in the cell cycle, or increased survival of activated cells. Therefore, tumor cells frequently accumulate genomic alterations, which may result in the activation of a particular array of oncogenes, the inactivation of specific tumor-suppressor genes, and the bypassing of programmed cell death. Trials of antitumor agents that act by exploiting the overexpression of oncogenes in tumors and of the biochemical pathways by which they mediate cell proliferation are currently underway.
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Ellsworth, Rachel E., Jeffrey A. Hooke, Craig D. Shriver, and Darrell L. Ellsworth. "Genomic Heterogeneity of Breast Tumor Pathogenesis." Clinical medicine. Oncology 3 (January 2009): CMO.S2946. http://dx.doi.org/10.4137/cmo.s2946.
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Pathological grade is a useful prognostic factor for stratifying breast cancer patients into favorable (low-grade, well-differentiated tumors) and less favorable (high-grade, poorly-differentiated tumors) outcome groups. Under the current system of tumor grading, however, a large proportion of tumors are characterized as intermediate-grade, making determination of optimal treatments difficult. In an effort to increase objectivity in the pathological assessment of tumor grade, differences in chromosomal alterations and gene expression patterns have been characterized in low-grade, intermediate-grade, and high-grade disease. In this review, we outline molecular data supporting a linear model of progression from low-grade to high-grade carcinomas, as well as contradicting genetic data suggesting that low-grade and high-grade tumors develop independently. While debate regarding specific pathways of development continues, molecular data suggest that intermediate-grade tumors do not comprise an independent disease subtype, but represent clinical and molecular hybrids between low-grade and high-grade tumors. Finally, we discuss the clinical implications associated with different pathways of development, including a new clinical test to assign grade and guide treatment options.
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Brastianos, Priscilla Kaliopi, Peleg Horowitz, Sandro Santagata, Robert T. Jones, Aaron McKenna, Keith Ligon, Emanuele Palescandolo, et al. "Genomic characterization of meningiomas." Journal of Clinical Oncology 30, no. 15_suppl (May 20, 2012): 2020. http://dx.doi.org/10.1200/jco.2012.30.15_suppl.2020.
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2020 Background: Understanding the genetic alterations in cancer has lead to groundbreaking discoveries in targeted therapies. Meningiomas are among the most common primary brain tumors, with approximately 18,000 new cases diagnosed annually. Though certain genes have been associated with the development of meningiomas, most notably the tumor suppressor gene neurofibromatosis 2 (NF2), the genetic changes that drive meningiomas remain poorly understood. Our objective was to comprehensively characterize the somatic genetic alterations of meningiomas to gain insight into the molecular pathways that drive this disease. Methods: Fresh frozen specimens and paired blood were collected from 16 consented patients. DNA was extracted from regions of high tumor purity determined by evaluation of H&E slides. Whole-genome sequencing from 10 tumor-normal pairs and whole-exome sequencing from 6 tumor-normal pairs was carried out. We performed an unbiased screen for point mutations, insertions-deletions, rearrangements and copy-number changes across the exomes and genomes. Recurrent (potential driver) events were then analyzed with additional algorithms for statistical significance. Results: Alterations in the NF2 gene were present in 9 of 16 patients. Multiple novel rearrangements and recurrent non-NF2 mutations were also identified in the cohort. Massive genomic rearrangement termed chromothripsis was observed in chromosome 1 in one sample, which has never previously been described in meningiomas, and represents a potentially new mechanism of malignant transformation in this tumor type. Conclusions: While NF2 mutations appear to drive a majority of these tumors, our analysis has uncovered additional potential driver genes in meningiomas, particularly in those tumors negative for NF2 alterations. To our knowledge, this is the first study to comprehensively characterize the totality of somatic genetic alterations in meningiomas, and brings us closer to the development of new therapeutic targets for this disease.
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Garraway, Levi A. "Genomics-Driven Oncology: Framework for an Emerging Paradigm." Journal of Clinical Oncology 31, no. 15 (May 20, 2013): 1806–14. http://dx.doi.org/10.1200/jco.2012.46.8934.
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A majority of cancers are driven by genomic alterations that dysregulate key oncogenic pathways influencing cell growth and survival. However, the ability to harness tumor genetic information for its full clinical potential has only recently become manifest. Over the past several years, the convergence of discovery, technology, and therapeutic development has created an unparalleled opportunity to test the hypothesis that systematic knowledge of genomic information from individual tumors can improve clinical outcomes for many patients with cancer. Rigorous evaluation of this genomics-driven cancer medicine hypothesis will require many logistic innovations that are guided by overarching conceptual advances in tumor genomic profiling, data interpretation, clinical trial design, and the ethical return of genetic results to oncologists and their patients. The results of these efforts and the rigor with which they are implemented will determine whether and how comprehensive tumor genomic information may become incorporated into the routine care of patients with cancer.
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Chen, Mingjiu, Haitao Ma, Haoda Yu, Chen Chen, Pingping Dai, Zhiyi He, Pengcheng Li, et al. "Genomic heterogeneity of multifocal NSCLC." Journal of Clinical Oncology 38, no. 15_suppl (May 20, 2020): e21595-e21595. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.e21595.
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e21595 Background: Distinguishing multiple primary lung cancer (MPLC) and intrapulmonary metastasis (IPM) remains a common diagnostic dilemma but critical for developing a therapeutic strategy. Methods: In this study, we analyse genomic features of 584 tissue samples from 258 NSCLC patients with > 1 surgically-resected tumor. NGS was performed using panels of 1021/59 genes. Results: Among 80 patients with definite diagnosis, 23 patients (46 tumors) were diagnosed with IPM. And 57 patients (145 tumors) were MPLC, consisting of 53 synchronous and 3 metachronous tumor pairs. Among 23 IPM tumor pairs, we identified at least one shared somatic mutation. By contrast, 93%(53/57) MPLC tumor pairs exhibited entirely unique mutation profiles in each tumor. Of 57 MPLCs, 4(7%) had no driver alteration ( EGFR, KRAS, BRAF, ALK, ERBB2, MET Exon 14). 9(16%) had a driver in only one of the tumors. In the remaining 44 MPLCs, 40 had unique driver mutation in each tumor. 50%(20/40) had distinct EGFR mutations, the most common combination was L858R and delins in exon 19. Specifically, 8(20%) patients resided ≥3 unique driver mutations simultaneously. This observation indicated that multiple lesions in the same individual can be driven by distinct molecular events. In contrast, 21 available IPM tumor pairs shared the same driver mutation. Pathogenic germline mutations were also analysed. Two were found in 2 MPLCs, involving PLAB2 and BLM, which were both null variants. While there were no pathogenic germline mutations found in IPMs. Regarding the MSI status, all samples from either MPLCs and IPMs displayed MSS, unexpectedly. To further verify the findings above, the remaining 393 samples with uncertain diagnosis were classified into group M (no shared mutation, 218 samples /97 patients) and I (≥1 shared mutation, 175 samples/81 patients). We find the similarity results among all available patients, driver mutation profiles exhibited completely unique and multiple in group M and fully consistent in group I. Conclusions: Taken together, our analyses indicated that the genomic heterogeneity of multifocal NSCLC may be a potential strategy for differentiating IPM and MPLC. This may hold implications for prioritizing therapeutic strategies.
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Pawloski, Jacob A., Hassan A. Fadel, Yi-Wen Huang, and Ian Y. Lee. "Genomic Biomarkers of Meningioma: A Focused Review." International Journal of Molecular Sciences 22, no. 19 (September 23, 2021): 10222. http://dx.doi.org/10.3390/ijms221910222.
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Meningiomas represent a phenotypically and genetically diverse group of tumors which often behave in ways that are not simply explained by their pathologic grade. The genetic landscape of meningiomas has become a target of investigation as tumor genomics have been found to impact tumor location, recurrence risk, and malignant potential. Additionally, targeted therapies are being developed that in the future may provide patients with personalized chemotherapy based on the genetic aberrations within their tumor. This review focuses on the most common genetic mutations found in meningiomas of all grades, with an emphasis on the impact on tumor location and clinically relevant tumor characteristics. NF-2 and the non-NF-2 family of genetic mutations are summarized in the context of low-grade and high-grade tumors, followed by a comprehensive discussion regarding the genetic and embryologic basis for meningioma location and phenotypic heterogeneity. Finally, targeted therapies based on tumor genomics currently in use and under investigation are reviewed and future avenues for research are suggested. The field of meningioma genomics has broad implications on the way meningiomas will be treated in the future, and is gradually shifting the way clinicians approach this diverse group of tumors.
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MacConaill, Laura E. "Existing and Emerging Technologies for Tumor Genomic Profiling." Journal of Clinical Oncology 31, no. 15 (May 20, 2013): 1815–24. http://dx.doi.org/10.1200/jco.2012.46.5948.
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Ongoing global genome characterization efforts are revolutionizing our knowledge of cancer genomics and tumor biology. In parallel, information gleaned from these studies on driver cancer gene alterations—mutations, copy number alterations, translocations, and/or chromosomal rearrangements—can be leveraged, in principle, to develop a cohesive framework for individualized cancer treatment. These possibilities have been enabled, to a large degree, by revolutionary advances in genomic technologies that facilitate systematic profiling for hallmark cancer genetic alterations at increasingly fine resolutions. Ongoing innovations in existing genomics technologies, as well as the many emerging technologies, will likely continue to advance translational cancer genomics and precision cancer medicine.
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de Moor, Janet S., Stacy W. Gray, Sandra A. Mitchell, Carrie N. Klabunde, and Andrew N. Freedman. "Oncologist Confidence in Genomic Testing and Implications for Using Multimarker Tumor Panel Tests in Practice." JCO Precision Oncology, no. 4 (September 2020): 620–31. http://dx.doi.org/10.1200/po.19.00338.
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PURPOSE The evolution of precision oncology increasingly requires oncologists to incorporate genomic testing into practice. Yet, providers’ confidence with genomic testing is poorly documented. This article describes medical oncologists’ confidence with genomic testing and the association between genomic confidence and test use. METHODS We used data from the 2017 National Survey of Precision Medicine in Cancer Treatment to characterize oncologists’ confidence with genomic testing. Genomic confidence was examined separately by type of test user: next-generation sequencing (NGS) only, gene expression (GE) only, both NGS and GE, or nonuser. Predictors of genomic confidence were examined with multinomial logistic regression. The association between genomic confidence and test use was examined with multivariable linear regression. RESULTS More than 75% of genomic test users were either moderately or very confident about using results from multimarker tumor panel tests to guide patient care. Confidence with using multimarker tumor panel tests was highest among both NGS and GE test users, with 60.1% very confident in using test results, and lowest among NGS-only test users, with 38.2% very confident in using test results. Oncologists were most confident in using single-gene tests and least confident in using whole-genome or -exome sequencing to guide patient care. Genomic confidence was positively associated with self-reported test use. In adjusted models, training in genomics, larger patient volume, and treating patients with solid tumors predicted higher genomic confidence. Onsite pathology services and receipt of electronic medical record alerts for genomic testing predicted lower genomic confidence. CONCLUSION Oncologists’ confidence varies by testing platform, patient volume, genomic training, and practice infrastructure. Research is needed to identify modifiable factors that can be targeted to enhance provider confidence with genomic testing.
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Starr, Jason Scott, Kabir Mody, Ali Roberts, and Pashtoon Murtaza Kasi. "Circulating tumor DNA analysis of neuroendocrine tumors." Journal of Clinical Oncology 37, no. 15_suppl (May 20, 2019): e15698-e15698. http://dx.doi.org/10.1200/jco.2019.37.15_suppl.e15698.
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e15698 Background: Neuroendocrine tumors (NETs) and carcinomas (NECs) are a diverse group of tumors with an equally diverse biology and clinical behavior. Data on tissue-based genomic profiling of NETs exists, however, there is limited data using circulating tumor DNA (ctDNA) technology. We sought out to characterize NETs via ctDNA to identify genomic alterations. Methods: 27 patients with metastatic NET/NEC with 32 total plasma samples were analyzed using Guardant360 ctDNA assay. Breakdown of NET/NEC by location: 14 pancreatic NET (pNET), 11 NEC, 1 small bowel NET, 1 lung NET. The ctDNA test detects single nucleotide variants in 54-73 genes, copy number amplifications, fusions, and indels in selected genes. Results: Of the 27 patients, 19 (70%) had a detectable genomic alteration. The detectable (non-synonymous) alterations are as follows: TP53 (n = 14, 70%), NF1 (n = 8, 40%), EGFR (n = 5, 25%), BRCA2 (n = 4, 20%), KRAS (n = 4, 20%), ARID1A (n = 3, 15%), CDK6 (n = 3, 15%), ALK (n = 3, 15%), MET (n = 2, 10%), PTEN (n = 2, 10%), BRAF (n = 2, 10%), MTOR (n = 2, 10%) AKT1 (n = 1), BRCA1 (n = 1), CCND2 (n = 1), CCNE1 (n = 1), CTNNB1 (n = 1), ESR1 (n = 1), FGFR2 (n = 1), HRAS (n = 1), IDH1 (n = 1), KIT (n = 1), MYC (n = 1), NOTCH1 (n = 1), NRAS (n = 1), PDGFRA (n = 1), RAF1 (n = 1), RB1 (n = 1), SMAD4 (n = 1), STK11 (n = 1), TSC1 (n = 1), ERBB2 (n = 1), PIK3CA (n = 1). Conclusions: This experience highlights the feasibility of ctDNA to help identify genomic alterations in this patient population. Further studies incorporating ctDNA testing in this patient population are warranted.
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Surrey, Lea F., Minjie Luo, Fengqi Chang, and Marilyn M. Li. "The Genomic Era of Clinical Oncology: Integrated Genomic Analysis for Precision Cancer Care." Cytogenetic and Genome Research 150, no. 3-4 (2016): 162–75. http://dx.doi.org/10.1159/000454655.
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Genomic alterations are important biological markers for cancer diagnosis and prognosis, disease classification, risk stratification, and treatment selection. Chromosomal microarray analysis (CMA) and next-generation sequencing (NGS) technologies are superb new tools for evaluating cancer genomes. These state-of-the-art technologies offer high-throughput, highly accurate, targeted and whole-genome evaluation of genomic alterations in tumor tissues. The application of CMA and NGS technologies in cancer research has generated a wealth of useful information about the landscape of genomic alterations in cancer and their implications in cancer care. As the knowledge base in cancer genomics and genome biology grows, the focus of research is now shifting toward the clinical applications of these technologies to improve patient care. Although not yet standard of care in cancer, there is an increasing interest among the cancer genomics communities in applying these new technologies to cancer diagnosis in the Clinical Laboratory Improvement Amendments (CLIA)-certified laboratories. Many clinical laboratories have already started adopting these technologies for cancer genomic analysis. We anticipate that CMA and NGS will soon become the major diagnostic means for cancer genomic analysis to meet the increasing demands of precision cancer care.
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Liu, Edison T., and Susan M. Mockus. "Tumor Origins Through Genomic Profiles." JAMA Oncology 6, no. 1 (January 1, 2020): 33. http://dx.doi.org/10.1001/jamaoncol.2019.3981.
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Eng, Charis, Gustavo Leone, Mohammed S. Orloff, and Michael C. Ostrowski. "Genomic Alterations in Tumor Stroma." Cancer Research 69, no. 17 (August 25, 2009): 6759–64. http://dx.doi.org/10.1158/0008-5472.can-09-0985.
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Moulton, Thomas, Wai-Yee Chung, Luwa Yuan, Terrence Hensle, Pamela Waber, Perry Nisen, and Benjamin Tycko. "Genomic imprinting and Wilms' tumor." Medical and Pediatric Oncology 27, no. 5 (November 1996): 476–83. http://dx.doi.org/10.1002/(sici)1096-911x(199611)27:5<476::aid-mpo15>3.0.co;2-8.
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Chiu, Yu-Chiao, Siyuan Zheng, Li-Ju Wang, Brian S. Iskra, Manjeet K. Rao, Peter J. Houghton, Yufei Huang, and Yidong Chen. "Predicting and characterizing a cancer dependency map of tumors with deep learning." Science Advances 7, no. 34 (August 2021): eabh1275. http://dx.doi.org/10.1126/sciadv.abh1275.
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Genome-wide loss-of-function screens have revealed genes essential for cancer cell proliferation, called cancer dependencies. It remains challenging to link cancer dependencies to the molecular compositions of cancer cells or to unscreened cell lines and further to tumors. Here, we present DeepDEP, a deep learning model that predicts cancer dependencies using integrative genomic profiles. It uses a unique unsupervised pretraining that captures unlabeled tumor genomic representations to improve the learning of cancer dependencies. We demonstrated DeepDEP’s improvement over conventional machine learning methods and validated the performance with three independent datasets. By systematic model interpretations, we extended the current dependency maps with functional characterizations of dependencies and a proof-of-concept in silico assay of synthetic essentiality. We applied DeepDEP to pan-cancer tumor genomics and built the first pan-cancer synthetic dependency map of 8000 tumors with clinical relevance. In summary, DeepDEP is a novel tool for investigating cancer dependency with rapidly growing genomic resources.
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Paratala, Bhavna S., Sonia C. Dolfi, Hossein Khiabanian, Lorna Rodriguez-Rodriguez, Shridar Ganesan, and Kim M. Hirshfield. "Emerging Role of Genomic Rearrangements in Breast Cancer: Applying Knowledge from Other Cancers." Biomarkers in Cancer 8s1 (January 2016): BIC.S34417. http://dx.doi.org/10.4137/bic.s34417.
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Significant advances in our knowledge of cancer genomes are rapidly changing the way we think about tumor biology and the heterogeneity of cancer. Recent successes in genomically-guided treatment approaches accompanied by more sophisticated sequencing techniques have paved the way for deeper investigation into the landscape of genomic rearrangements in cancer. While considerable research on solid tumors has focused on point mutations that directly alter the coding sequence of key genes, far less is known about the role of somatic rearrangements. With many recurring alterations observed across tumor types, there is an obvious need for functional characterization of these genomic biomarkers in order to understand their relevance to tumor biology, therapy, and prognosis. As personalized therapy approaches are turning toward genomic alterations for answers, these biomarkers will become increasingly relevant to the practice of precision medicine. This review discusses the emerging role of genomic rearrangements in breast cancer, with a particular focus on fusion genes. In addition, it raises several key questions on the therapeutic value of such rearrangements and provides a framework to evaluate their significance as predictive and prognostic biomarkers.
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Persi, Erez, Davide Prandi, Yuri I. Wolf, Yair Pozniak, Georgina D. Barnabas, Keren Levanon, Iris Barshack, et al. "Proteomic and genomic signatures of repeat instability in cancer and adjacent normal tissues." Proceedings of the National Academy of Sciences 116, no. 34 (August 6, 2019): 16987–96. http://dx.doi.org/10.1073/pnas.1908790116.
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Repetitive sequences are hotspots of evolution at multiple levels. However, due to difficulties involved in their assembly and analysis, the role of repeats in tumor evolution is poorly understood. We developed a rigorous motif-based methodology to quantify variations in the repeat content, beyond microsatellites, in proteomes and genomes directly from proteomic and genomic raw data. This method was applied to a wide range of tumors and normal tissues. We identify high similarity between repeat instability patterns in tumors and their patient-matched adjacent normal tissues. Nonetheless, tumor-specific signatures both in protein expression and in the genome strongly correlate with cancer progression and robustly predict the tumorigenic state. In a patient, the hierarchy of genomic repeat instability signatures accurately reconstructs tumor evolution, with primary tumors differentiated from metastases. We observe an inverse relationship between repeat instability and point mutation load within and across patients independent of other somatic aberrations. Thus, repeat instability is a distinct, transient, and compensatory adaptive mechanism in tumor evolution and a potential signal for early detection.
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Riesco-Eizaguirre, Garcilaso, and Pilar Santisteban. "ENDOCRINE TUMOURS: Advances in the molecular pathogenesis of thyroid cancer: lessons from the cancer genome." European Journal of Endocrinology 175, no. 5 (November 2016): R203—R217. http://dx.doi.org/10.1530/eje-16-0202.
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Thyroid cancer is the most common endocrine malignancy giving rise to one of the most indolent solid cancers, but also one of the most lethal. In recent years, systematic studies of the cancer genome, most importantly those derived from The Cancer Genome Altas (TCGA), have catalogued aberrations in the DNA, chromatin, and RNA of the genomes of thousands of tumors relative to matched normal cellular genomes and have analyzed their epigenetic and protein consequences. Cancer genomics is therefore providing new information on cancer development and behavior, as well as new insights into genetic alterations and molecular pathways. From this genomic perspective, we will review the main advances concerning some essential aspects of the molecular pathogenesis of thyroid cancer such as mutational mechanisms, new cancer genes implicated in tumor initiation and progression, the role of non-coding RNA, and the advent of new susceptibility genes in thyroid cancer predisposition. This look across these genomic and cellular alterations results in the reshaping of the multistep development of thyroid tumors and offers new tools and opportunities for further research and clinical development of novel treatment strategies.
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Shen, Yaoqing, Cameron J. Grisdale, Sumaiya A. Islam, Pinaki Bose, Jake Lever, Eric Y. Zhao, Natalie Grinshtein, et al. "Comprehensive genomic profiling of glioblastoma tumors, BTICs, and xenografts reveals stability and adaptation to growth environments." Proceedings of the National Academy of Sciences 116, no. 38 (August 30, 2019): 19098–108. http://dx.doi.org/10.1073/pnas.1813495116.
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Glioblastoma multiforme (GBM) is the most deadly brain tumor, and currently lacks effective treatment options. Brain tumor-initiating cells (BTICs) and orthotopic xenografts are widely used in investigating GBM biology and new therapies for this aggressive disease. However, the genomic characteristics and molecular resemblance of these models to GBM tumors remain undetermined. We used massively parallel sequencing technology to decode the genomes and transcriptomes of BTICs and xenografts and their matched tumors in order to delineate the potential impacts of the distinct growth environments. Using data generated from whole-genome sequencing of 201 samples and RNA sequencing of 118 samples, we show that BTICs and xenografts resemble their parental tumor at the genomic level but differ at the mRNA expression and epigenomic levels, likely due to the different growth environment for each sample type. These findings suggest that a comprehensive genomic understanding of in vitro and in vivo GBM model systems is crucial for interpreting data from drug screens, and can help control for biases introduced by cell-culture conditions and the microenvironment in mouse models. We also found that lack of MGMT expression in pretreated GBM is linked to hypermutation, which in turn contributes to increased genomic heterogeneity and requires new strategies for GBM treatment.
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Mack, Stephen C., and Paul A. Northcott. "Genomic Analysis of Childhood Brain Tumors: Methods for Genome-Wide Discovery and Precision Medicine Become Mainstream." Journal of Clinical Oncology 35, no. 21 (July 20, 2017): 2346–54. http://dx.doi.org/10.1200/jco.2017.72.9921.
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Recent breakthroughs in next-generation sequencing technology and complementary genomic platforms have transformed our capacity to interrogate the molecular landscapes of human cancers, including childhood brain tumors. Numerous high-throughput genomic studies have been reported for the major histologic brain tumor entities diagnosed in children, including interrogations at the level of the genome, epigenome, and transcriptome, many of which have yielded essential new insights into disease biology. The nature of these discoveries has been largely platform dependent, exemplifying the usefulness of applying different genomic and computational strategies, or integrative approaches, to address specific biologic and/or clinical questions. The goal of this article is to summarize the spectrum of molecular profiling methods available for investigating genomic aspects of childhood brain tumors in both the research and the clinical setting. We provide an overview of the main next-generation sequencing and array-based technologies currently being applied in this field and draw from key examples in the recent neuro-oncology literature to illustrate how these genomic approaches have profoundly advanced our understanding of individual tumor entities. Moreover, we discuss the current status of genomic profiling in the clinic and how different platforms are being used to improve patient diagnosis and stratification, as well as to identify actionable targets for informing molecularly guided therapies, especially for patients for whom conventional standard-of-care treatments have failed. Both the demand for genomic testing and the main challenges associated with incorporating genomics into the clinical management of pediatric patients with brain tumors are discussed, as are recommendations for incorporating these assays into future clinical trials.
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Vignot, Stéphane, Garrett M. Frampton, Jean-Charles Soria, Roman Yelensky, Frédéric Commo, Christian Brambilla, Gary Palmer, et al. "Next-Generation Sequencing Reveals High Concordance of Recurrent Somatic Alterations Between Primary Tumor and Metastases From Patients With Non–Small-Cell Lung Cancer." Journal of Clinical Oncology 31, no. 17 (June 10, 2013): 2167–72. http://dx.doi.org/10.1200/jco.2012.47.7737.
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Purpose Characterization of the genomic changes that drive an individual patient's disease is critical in management of many cancers. In patients with non–small-cell lung cancer (NSCLC), obtaining tumor samples of sufficient size for genomic profiling on recurrence is often challenging. We undertook this study to compare genomic alterations identified in archived primary tumors from patients with NSCLC with those identified in metachronous or synchronous metastases. Patients and Methods Primary and matched metastatic tumor pairs from 15 patients were analyzed by using a targeted next-generation sequencing assay in a Clinical Laboratory Improvement Amendments laboratory. Genomic libraries were captured for 3,230 exons in 182 cancer-related genes plus 37 introns from 14 genes often rearranged in cancer and sequenced to high coverage. Results Among 30 tumors, 311 genomic alterations were identified of which 63 were known recurrent (32 in primary tumor, 31 in metastasis) and 248 were nonrecurrent (likely passenger). TP53 mutations were the most frequently observed recurrent alterations (12 patients). Tumors harbored two or more (maximum four) recurrent alterations in 10 patients. Comparative analysis of recurrent alterations between primary tumor and matched metastasis revealed a concordance rate of 94% compared with 63% for likely passenger alterations. Conclusion This high concordance suggests that for the purposes of genomic profiling, use of archived primary tumor can identify the key recurrent somatic alterations present in matched NSCLC metastases and may provide much of the relevant genomic information required to guide treatment on recurrence.
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Sidhu, Stan, Deborah J. Marsh, George Theodosopoulos, Jeanette Philips, Christopher P. Bambach, Peter Campbell, Christopher J. Magarey, et al. "Comparative Genomic Hybridization Analysis of Adrenocortical Tumors." Journal of Clinical Endocrinology & Metabolism 87, no. 7 (July 1, 2002): 3467–74. http://dx.doi.org/10.1210/jcem.87.7.8697.
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Comparative genomic hybridization (CGH) is a molecular cytogenetic technique that allows the entire genome of a tumor to be surveyed for gains and losses of DNA copy sequences. A limited number of studies reporting the use of this technique in adult adrenocortical tumors have yielded conflicting results. In this study we performed CGH analysis on 13 malignant, 18 benign, and 1 tumor of indeterminate malignant potential with the aim of identifying genetic loci consistently implicated in the development and progression of adrenocortical tumors. Tissue samples from 32 patients with histologically proven adrenocortical tumors were available for CGH analysis. CGH changes were seen in all cancers, 11 of 18 (61%) adenomas, and the 1 tumor of indeterminate malignant potential. Of the adrenal cancers, the most common gains were seen on chromosomes 5 (46%), 12 (38%), 19 (31%), and 4 (31%). Losses were most frequently seen at 1p (62%), 17p (54%), 22 (38%), 2q (31%), and 11q (31%). Of the benign adenomas, the most common change was gain of 4q (22%). Mann-Whitney analysis showed a highly significant difference between the cancer group (mean changes, 7.6) and the adenoma group (mean changes, 1.1) for the number of observed CGH changes (P < 0.01). Logistic regression analysis showed that the number of CGH changes was highly predictive of tumor type (P < 0.01). This study has identified several chromosomal loci implicated in adrenocortical tumorigenesis. Activation of a protooncogene(s) on chromosome 4 may be an early event, with progression from adenoma to carcinoma involving activation of oncogenes on chromosomes 5 and 12 and inactivation of tumor suppressor genes on chromosome arms 1p and 17p.
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Koduru, Srinivas, Ellice Wong, Till Strowig, Ranjini Sundaram, Lin Zhang, Matthew P. Strout, Richard A. Flavell, David G. Schatz, Kavita M. Dhodapkar, and Madhav V. Dhodapkar. "Dendritic cell–mediated activation-induced cytidine deaminase (AID)–dependent induction of genomic instability in human myeloma." Blood 119, no. 10 (March 8, 2012): 2302–9. http://dx.doi.org/10.1182/blood-2011-08-376236.
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Abstract Tumor microenvironment (TME) is commonly implicated in regulating the growth of tumors, but whether it can directly alter the genetics of tumors is not known. Genomic instability and dendritic cell (DC) infiltration are common features of several cancers, including multiple myeloma (MM). Mechanisms underlying genomic instability in MM are largely unknown. Here, we show that interaction between myeloma and DCs, but not monocytes, leads to rapid induction of the genomic mutator activation-induced cytidine deaminase (AID) and AID-dependent DNA double-strand breaks (DSBs) in myeloma cell lines as well as primary MM cells. Both myeloid as well as plasmacytoid DCs have the capacity to induce AID in tumor cells. The induction of AID and DSBs in tumor cells by DCs requires DC-tumor contact and is inhibited by blockade of receptor activator of NF-κB/receptor activator of NF-κB ligand (RANKL) interactions. AID-mediated genomic damage led to altered tumorigenicity and indolent behavior of tumor cells in vivo. These data show a novel pathway for the capacity of DCs in the TME to regulate genomic integrity. DC-mediated induction of AID and resultant genomic damage may therefore serve as a double-edged sword and be targeted by approaches such as RANKL inhibition already in the clinic.
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Moreno, Fernando, Javier Gayarre, Sara López-Tarruella, María del Monte-Millán, Antonio C. Picornell, Enrique Álvarez, José Ángel García-Saenz, et al. "Concordance of Genomic Variants in Matched Primary Breast Cancer, Metastatic Tumor, and Circulating Tumor DNA: The MIRROR Study." JCO Precision Oncology, no. 3 (December 2019): 1–16. http://dx.doi.org/10.1200/po.18.00263.
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PURPOSE Genetic heterogeneity between primary tumors and their metastatic lesions has been documented in several breast cancer studies. However, the selection of therapy for patients with metastatic breast cancer and the search for biomarkers for targeted therapy are often based on findings from the primary tumor, mainly because of the difficulty of distant metastasis core biopsies. New methods for monitoring genomic changes in metastatic breast cancer are needed (ie, circulating tumor DNA [ctDNA] genomic analysis). The objectives of this study were to assess the concordance of genomic variants between primary and metastatic tumor tissues and the sensitivity of plasma ctDNA analysis to identify variants detected in tumor biopsies. PATIENTS AND METHODS Next-generation sequencing technology was used to assess the genomic mutation profile of a panel of 54 cancer genes in matched samples of primary tumor, metastatic tumor, and plasma from 40 patients with metastatic breast cancer. RESULTS Using Ion Torrent technology (ThermoFisher Scientific, Waltham, MA), we identified 110 variants that were common to the primary and metastatic tumors. ctDNA analysis had a sensitivity of 0.972 in detecting variants present in both primary and metastatic tissues. In addition, we identified 13 variants in metastatic tissue and ctDNA not present in primary tumor. CONCLUSION We identified genomic variants present in metastatic biopsies and plasma ctDNA that were not present in the primary tumor. Deep sequencing of plasma ctDNA detected most DNA variants previously identified in matched primary and metastatic tissues. ctDNA might aid in therapy selection and in the search for biomarkers for drug development in metastatic breast cancer.
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van Oost, Siddh, Debora M. Meijer, Marieke L. Kuijjer, Judith V. M. G. Bovée, and Noel F. C. C. de Miranda. "Linking Immunity with Genomics in Sarcomas: Is Genomic Complexity an Immunogenic Trigger?" Biomedicines 9, no. 8 (August 19, 2021): 1048. http://dx.doi.org/10.3390/biomedicines9081048.
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Sarcomas comprise a collection of highly heterogeneous malignancies that can be grossly grouped in the categories of sarcomas with simple or complex genomes. Since the outcome for most sarcoma patients has barely improved in the last decades, there is an urgent need for improved therapies. Immunotherapy, and especially T cell checkpoint blockade, has recently been a game-changer in cancer therapy as it produced significant and durable treatment responses in several cancer types. Currently, only a small fraction of sarcoma patients benefit from immunotherapy, supposedly due to a general lack of somatically mutated antigens (neoantigens) and spontaneous T cell immunity in most cancers. However, genomic events resulting from chromosomal instability are frequent in sarcomas with complex genomes and could drive immunity in those tumors. Improving our understanding of the mechanisms that shape the immune landscape of sarcomas will be crucial to overcoming the current challenges of sarcoma immunotherapy. This review focuses on what is currently known about the tumor microenvironment in sarcomas and how this relates to their genomic features. Moreover, we discuss novel therapeutic strategies that leverage the tumor microenvironment to increase the clinical efficacy of immunotherapy, and which could provide new avenues for the treatment of sarcomas.
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Carroll, William L., Elizabeth Raetz, and Julia Meyer. "State of the Art Discovery with Tumor Profiling in Pediatric Oncology." American Society of Clinical Oncology Educational Book, no. 35 (May 2015): e601-e607. http://dx.doi.org/10.14694/edbook_am.2015.35.e601.
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It is an exciting era in pediatric oncology with the advent of new technologies to comprehensively characterize cancer genomes in childhood tumors. Defining the genetic landscape of pediatric tumors has not only provided critical insight into tumor evolution, but it has also offered promise for more effective treatment in some cases, such as Philadelphia chromosome-positive acute lymphoblastic leukemia (ALL) and anaplastic lymphoma kinase (ALK)-mutated tumors. However, several challenges remain as the field of genomic tumor profiling emerges. This new technology is costly, and the overall impact on survival has yet to be determined. Tumor heterogeneity and clonal evolution have also presented challenges in the development of targeted therapy. In this article, we review breakthroughs in gene sequencing methodology and discuss examples where genomic discoveries have resulted in the recognition of tumor susceptibility as well as incorporation of targeted therapy. We also discuss how broad scale comprehensive tumor analyses have demonstrated the convergence of individual genetic alterations on common relevant pathways. Although the impact of tumor profiling is best studied within the context of rigorously designed clinical trials, there is promise that there will be growing opportunities for the adaption of precision medicine in pediatric oncology in the future.
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Sadaps, Meena, Pauline Funchain, Haider Mahdi, Petros Grivas, Amy Pritchard, Stefan Klek, Bassam Estfan, et al. "Precision Oncology in Solid Tumors: A Longitudinal Tertiary Care Center Experience." JCO Precision Oncology, no. 2 (November 2018): 1–11. http://dx.doi.org/10.1200/po.18.00186.
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Purpose Precision oncology is widely discussed, but cohort studies are limited. We previously reported our prospective experience of precision oncology in solid tumors, and here we report our longitudinal experience, focusing on therapeutic impact. Patients and Methods We conducted a retrospective review of 600 consecutive patients seen at Cleveland Clinic from 2013 to 2016 for treatment of incurable solid tumor malignancies for whom tumor genomic profiling was ordered using FoundationOne (Cambridge, MA). Results were discussed at our multidisciplinary genomics tumor board. Data analyzed included subsequent therapy and overall survival (OS). Results Median age was 59 years (range, 18 to 94 years), 308 (51.3%) were female, and 533 (88.8%) were white. Targeted therapy was recommended in 310 patients (51.7%). After results, 313 patients (52.2%) started any subsequent therapy; of these, 95 (30%; 15.8% overall) received genomics-driven therapy (G), and 218 (70%) received non–genomics-driven treatment (NG). For the G versus NG group, the on-label, off-label, and clinical trial therapy breakdowns were 23% versus 88%, 47% versus 3%, and 30% versus 9%, respectively. Median OS for patients receiving no therapy after tumor genomic profiling was 5.5 months; for the G and NG groups, it was 18 ( P < .001) and 14.4 ( P < .001) months, respectively ( P = NS for G v NG). The use of G increased from 10% in the first 250-patient cohort (reported earlier) to 20% in the subsequent 350-patient cohort. Conclusion Tumor genomic profiling influenced treatment in 15.8% of patients. More patients received treatment via clinical trials in the G cohort, and although not statistically significant, there was a trend toward increased OS in the G ( v NG) group. These data can further guide real-world applications of precision oncology.
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Baltić, Vladimir. "Application of Genomics in Clinical Oncology." Journal of Medical Biochemistry 26, no. 2 (January 1, 2007): 79–93. http://dx.doi.org/10.2478/v10011-007-0011-y.
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Application of Genomics in Clinical OncologyGenomics is a comprehensive study of the whole genome, genetic products, and their interactions. Human genome project has identified around 25,000-30,000 genes, and prevailing presence in tumor pathogenesis, high number of mutations, epigenetic changes, and other gene disorders have been identified. Microarrays technology is used for the analysis of these changes. Postgenome age has begun, and the initial results ensure the improvement of molecular tumor diagnostics and the making of a new taxonomic tumor classification, as well as the improvement, optimization and individualization of anti-tumor therapy. First genomic classifications have been made of leukemias, non-Hodgkin lymphoma, and many solid tumors. For example, 4 molecular types of breast carcinoma, three types of diffuse B cell lymphoma, two types of chromophobic renal carcinoma have been identified. Also, gene structures for favorable and unfavorable outcome in leukemia, breast cancer, prostate, bronchi, and other tumors have been identified. It is absolutely possible to diagnose the primary outcome of tumors with which standard tumor position may not be proved using standard diagnostic tools. Pharmacogenomic profiles have ensured better definition of interindividual differences during therapy using antineoplastic drugs and the decrease of their toxicity, as well as individual treatment approach and patient selection with which favorable clinical outcome is expected. Pharmacogenomics has impacted the accelerated development of target drugs, which have showed to be useful in practice. New genomic markers mtDNA, meDNA, and miRNA have been identified, which, with great certainty, help the detection and diagnostics of carcinoma. In the future, functional genomics in clinical oncology provides to gain knowledge about tumor pathogenesis; it will improve diagnostics and prognosis, and open up new therapeutic options.
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Samuel, Nardin, and Thomas J. Hudson. "Translating Genomics to the Clinic: Implications of Cancer Heterogeneity." Clinical Chemistry 59, no. 1 (January 1, 2013): 127–37. http://dx.doi.org/10.1373/clinchem.2012.184580.
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BACKGROUND Sequencing of cancer genomes has become a pivotal method for uncovering and understanding the deregulated cellular processes driving tumor initiation and progression. Whole-genome sequencing is evolving toward becoming less costly and more feasible on a large scale; consequently, thousands of tumors are being analyzed with these technologies. Interpreting these data in the context of tumor complexity poses a challenge for cancer genomics. CONTENT The sequencing of large numbers of tumors has revealed novel insights into oncogenic mechanisms. In particular, we highlight the remarkable insight into the pathogenesis of breast cancers that has been gained through comprehensive and integrated sequencing analysis. The analysis and interpretation of sequencing data, however, must be considered in the context of heterogeneity within and among tumor samples. Only by adequately accounting for the underlying complexity of cancer genomes will the potential of genome sequencing be understood and subsequently translated into improved management of patients. SUMMARY The paradigm of personalized medicine holds promise if patient tumors are thoroughly studied as unique and heterogeneous entities and clinical decisions are made accordingly. Associated challenges will be ameliorated by continued collaborative efforts among research centers that coordinate the sharing of mutation, intervention, and outcomes data to assist in the interpretation of genomic data and to support clinical decision-making.
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Doe-Tetteh, Seyram Adjoa, Sabrina Yvonne Camp, Jett Crowdis, Anne Marie Noronha, Dalicia Reales, Tina Alano, Agnes Viale, et al. "Overcoming barriers to tumor genomic profiling through direct patient social media outreach." Journal of Clinical Oncology 40, no. 16_suppl (June 1, 2022): 6532. http://dx.doi.org/10.1200/jco.2022.40.16_suppl.6532.
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6532 Background: Tumor genomic profiling is increasingly used to identify actionable genomic alterations as a guide to therapy selection. To overcome barriers to genomic testing for patients with rare cancers, we initiated a program to offer free clinical tumor genomic testing worldwide to patients with select rare cancer subtypes. Methods: Patients were recruited through social media outreach, engagement with disease advocacy groups, or via physician referral, with a focus on recruiting patients with histiocytosis, germ cell tumors and rare pediatric cancers. Tumor and patient-matched germline DNA were analyzed using the MSK-IMPACT targeted sequencing next generation sequencing panel with return of results to patients and their local physicians. Whole exome recapture of MSK-IMPACT DNA sequencing libraries was performed for patients with female germ cell tumors to define the genomic landscape of this rare cancer subtype. Results: 359 cancer patients expressed interest in the Make-an-IMPACT program, of whom 333 were enrolled. Tumor tissue was received for 288 (86.4%), with 250 (86.8%) having tumor DNA of sufficient quantity and quality for MSK-IMPACT testing. 14 histiocytosis patients have received genomically guided therapy to date, of whom 13 (93%) have had clinical benefit based on local MD response assessment with a mean treatment duration of 16.7 months (range 3-32+). Whole exome sequencing of ovarian GCTs identified a subset with fully haploid genotypes, a phenotype rarely observed in other cancer types. Actionable genomic alterations were rare in ovarian GCT (28%), however, 2 ovarian GCTs and squamous transformation had high tumor mutational burden, one of whom had a complete response to pembrolizumab. Conclusions: Social media outreach can facilitate the assembly of cohorts of rare cancers of sufficient size to define their genomic landscape. By profiling tumors in a clinical laboratory, results could be reported to patients and their local physicians where they could be used to guide treatment selection. This can also open the door to diversifying and being able to study the genomic landscape in a diverse cohort.
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Doe-Tetteh, Seyram Adjoa, Sabrina Yvonne Camp, Jett Crowdis, Anne Marie Noronha, Dalicia Reales, Tina Alano, Agnes Viale, et al. "Overcoming barriers to tumor genomic profiling through direct patient social media outreach." Journal of Clinical Oncology 40, no. 16_suppl (June 1, 2022): 6532. http://dx.doi.org/10.1200/jco.2022.40.16_suppl.6532.
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6532 Background: Tumor genomic profiling is increasingly used to identify actionable genomic alterations as a guide to therapy selection. To overcome barriers to genomic testing for patients with rare cancers, we initiated a program to offer free clinical tumor genomic testing worldwide to patients with select rare cancer subtypes. Methods: Patients were recruited through social media outreach, engagement with disease advocacy groups, or via physician referral, with a focus on recruiting patients with histiocytosis, germ cell tumors and rare pediatric cancers. Tumor and patient-matched germline DNA were analyzed using the MSK-IMPACT targeted sequencing next generation sequencing panel with return of results to patients and their local physicians. Whole exome recapture of MSK-IMPACT DNA sequencing libraries was performed for patients with female germ cell tumors to define the genomic landscape of this rare cancer subtype. Results: 359 cancer patients expressed interest in the Make-an-IMPACT program, of whom 333 were enrolled. Tumor tissue was received for 288 (86.4%), with 250 (86.8%) having tumor DNA of sufficient quantity and quality for MSK-IMPACT testing. 14 histiocytosis patients have received genomically guided therapy to date, of whom 13 (93%) have had clinical benefit based on local MD response assessment with a mean treatment duration of 16.7 months (range 3-32+). Whole exome sequencing of ovarian GCTs identified a subset with fully haploid genotypes, a phenotype rarely observed in other cancer types. Actionable genomic alterations were rare in ovarian GCT (28%), however, 2 ovarian GCTs and squamous transformation had high tumor mutational burden, one of whom had a complete response to pembrolizumab. Conclusions: Social media outreach can facilitate the assembly of cohorts of rare cancers of sufficient size to define their genomic landscape. By profiling tumors in a clinical laboratory, results could be reported to patients and their local physicians where they could be used to guide treatment selection. This can also open the door to diversifying and being able to study the genomic landscape in a diverse cohort.
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O'Donnell, Elizabeth, Hope Feldman, Carlos Lago-Hernandez, Michelle S. Hirsch, Clair Beard, Eliezer Mendel Van Allen, Philip W. Kantoff, and Christopher Sweeney. "Tumor genomic mutation profiling of germ cell tumors using “Profile”." Journal of Clinical Oncology 32, no. 15_suppl (May 20, 2014): 4516. http://dx.doi.org/10.1200/jco.2014.32.15_suppl.4516.
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Pelosi, Giuseppe, Mauro Papotti, Guido Rindi, and Aldo Scarpa. "Unraveling Tumor Grading and Genomic Landscape in Lung Neuroendocrine Tumors." Endocrine Pathology 25, no. 2 (April 26, 2014): 151–64. http://dx.doi.org/10.1007/s12022-014-9320-0.
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Freitas, Monique Oliveira, John Gartner, Aline Rangel-Pozzo, and Sabine Mai. "Genomic Instability in Circulating Tumor Cells." Cancers 12, no. 10 (October 16, 2020): 3001. http://dx.doi.org/10.3390/cancers12103001.
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Circulating tumor cells (CTCs) can promote distant metastases and can be obtained through minimally invasive liquid biopsy for clinical assessment in cancer patients. Having both genomic heterogeneity and instability as common features, the genetic characterization of CTCs can serve as a powerful tool for a better understanding of the molecular changes occurring at tumor initiation and during tumor progression/metastasis. In this review, we will highlight recent advances in the detection and quantification of tumor cell heterogeneity and genomic instability in CTCs. We will focus on the contribution of chromosome instability studies to genetic heterogeneity in CTCs at the single-CTC level by discussing data from different cancer subtypes and their impact on diagnosis and precision medicine.
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Tang, Lin. "Genomic variation in non-tumor cells." Nature Methods 17, no. 1 (January 2020): 30. http://dx.doi.org/10.1038/s41592-019-0717-z.
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Navin, N., A. Krasnitz, L. Rodgers, K. Cook, J. Meth, J. Kendall, M. Riggs, et al. "Inferring tumor progression from genomic heterogeneity." Genome Research 20, no. 1 (November 10, 2009): 68–80. http://dx.doi.org/10.1101/gr.099622.109.
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Duhagon, Maria, Elaine M. Hurt, Jose R. Sotelo-Silveira, Xiaohu Zhang, and William L. Farrar. "Genomic profiling of tumor initiating prostatospheres." BMC Genomics 11, no. 1 (2010): 324. http://dx.doi.org/10.1186/1471-2164-11-324.
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Sato, Fumiaki, Shigehira Saji, and Masakazu Toi. "Genomic tumor evolution of breast cancer." Breast Cancer 23, no. 1 (May 22, 2015): 4–11. http://dx.doi.org/10.1007/s12282-015-0617-8.
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Grichnik, James M. "Genomic Instability and Tumor Stem Cells." Journal of Investigative Dermatology 126, no. 6 (June 2006): 1214–16. http://dx.doi.org/10.1038/sj.jid.5700240.
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Tan, Qiang, Jian Cui, Jia Huang, Zhengping Ding, Hao Lin, Xiaomin Niu, Zhiming Li, Guan Wang, Qingquan Luo, and Shun Lu. "Genomic Alteration During Metastasis of Lung Adenocarcinoma." Cellular Physiology and Biochemistry 38, no. 2 (2016): 469–86. http://dx.doi.org/10.1159/000438644.
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Background/Aims: Recurrent gene mutation has been identified by the analysis of exonic DNA from lung adenocarcinoma, but its progression has not been extensively profiled. The investigation of the mutational landscape of tumors provides new insights into cancer genome evolution and further discovers the interplay of somatic mutation, adaptation of clones to their environment and natural selection. Cancer development involves cycles of genomic damage, epigenetic deregulation, and increased cellular proliferation that eventually culminate in the carcinoma phenotype. Methods: Comparative whole exome sequencing of both primary and metastatic tumor tissues from four patients of stage IV lung adenocarcinoma patients with chest wall metastasis was performed. Both primary and metastatic tumors were diagnosed through biopsy followed by surgical resection. All tumor specimens were cut into several pieces to assess potential heterogenic clones within the tumor tissue. Adjacent normal lung tissue was also obtained to provide germline mutation background. Results: By modeling and analyzing progression of the cancer metastasis based on non-synonymous variants, we defined the extent of heterogeneity of cancer genomes and identified similar cancer evolution pattern in the four patients: metastasis was an early event occurring right after the primary cancer formation and evolution in the metastatic tumor was continuously and simultaneously in progression with that in the primary tumor. By characterizing the clonal hierarchy of genetic lesions, we further charted a pathway of oncogenic events along which genes may drive lung adenocarcinoma metastasis, such as TAS2R31 and UMODL1, involving in G-protein coupled receptor protein signaling pathway. Conclusion: The candidate genes identified in this study may become targets for the treatment of lung adenocarcinoma metastasis.
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Barnett, Christine M., Michael C. Heinrich, Dylan A. Nelson, Jeong Youn Lim, Carol Beadling, Andrea Warrick, Tanaya Neff, et al. "Genomic analysis of prostate cancer." Journal of Clinical Oncology 31, no. 6_suppl (February 20, 2013): 80. http://dx.doi.org/10.1200/jco.2013.31.6_suppl.80.
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80 Background: The characterization of actionable mutations is a prerequisite for the development of individualized, targeted therapy. We sought to characterize the prevalence of potentially therapeutically actionable mutations in patients with high risk prostate cancer. Methods: 48 samples of formalin fixed paraffin embedded prostatectomy tissue from a neoadjuvant chemotherapy trial (Garzotto M, Cancer 2010 Apr 1;116(7):1699-708) were analyzed. DNA was extracted from microdissected tumor. Tumor DNA was analyzed for 643 common solid tumor point mutations in 53 genes using mass spectroscopy based sequencing (Sequenom MassArray). Low level mutations were validated using ion chip pH based sequencing (Ion Torrent). In addition, PTEN loss and ERG translocations were examined using immunohistochemistry in associated tissue microarrays. Correlation with relapse during 5 years of follow-up was examined in exploratory analyses of the potential clinical relevance of the genetic alterations examined. Results: Of the 40 tumors evaluable for mutations, 10% had point mutations in potentially actionable cancer genes. Of the 45 tumors evaluable for IHC, 36% had PTEN loss (6% with a heterogenous pattern) and 40% had ERG rearrangement (2% with heterogeneous pattern). Individual mutations were not frequent enough to determine associations with progression. Using Kaplan-Meier analysis with a log-rank test, the 16 patients who had PTEN loss had a significantly shorter median progression free survival, 19 vs. 106 months (p = .01). Conclusions: This study confirms that point mutations in the most common cancer regulatory genes in prostate cancer are rare. However, the PIK3CA/AKT pathway was mutated in 10% of our samples. While point mutations alone did not have a statistically significant effect on relapse, PTEN loss was associated with an increased relapse in high risk prostate cancer treated with chemotherapy followed by surgery. It is yet unclear if the 16 weeks of chemotherapy played a role in selecting for tumors with these biologic features, and this will therefore be the subject of future investigations. [Table: see text]
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Tegally, Houriiyah, Kevin H. Kensler, Zahra Mungloo-Dilmohamud, Anisah W. Ghoorah, Timothy R. Rebbeck, and Shakuntala Baichoo. "Discovering novel driver mutations from pan-cancer analysis of mutational and gene expression profiles." PLOS ONE 15, no. 11 (November 24, 2020): e0242780. http://dx.doi.org/10.1371/journal.pone.0242780.
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As the genomic profile across cancers varies from person to person, patient prognosis and treatment may differ based on the mutational signature of each tumour. Thus, it is critical to understand genomic drivers of cancer and identify potential mutational commonalities across tumors originating at diverse anatomical sites. Large-scale cancer genomics initiatives, such as TCGA, ICGC and GENIE have enabled the analysis of thousands of tumour genomes. Our goal was to identify new cancer-causing mutations that may be common across tumour sites using mutational and gene expression profiles. Genomic and transcriptomic data from breast, ovarian, and prostate cancers were aggregated and analysed using differential gene expression methods to identify the effect of specific mutations on the expression of multiple genes. Mutated genes associated with the most differentially expressed genes were considered to be novel candidates for driver mutations, and were validated through literature mining, pathway analysis and clinical data investigation. Our driver selection method successfully identified 116 probable novel cancer-causing genes, with 4 discovered in patients having no alterations in any known driver genes: MXRA5, OBSCN, RYR1, and TG. The candidate genes previously not officially classified as cancer-causing showed enrichment in cancer pathways and in cancer diseases. They also matched expectations pertaining to properties of cancer genes, for instance, showing larger gene and protein lengths, and having mutation patterns suggesting oncogenic or tumor suppressor properties. Our approach allows for the identification of novel putative driver genes that are common across cancer sites using an unbiased approach without any a priori knowledge on pathways or gene interactions and is therefore an agnostic approach to the identification of putative common driver genes acting at multiple cancer sites.
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Abou Alaiwi, Sarah, Amin Nassar, Elio Adib, Elie W. Akl, Kent William Mouw, Catherine Curran, Dory Freeman, et al. "Genomic landscape of variant urinary tumor histologies." Journal of Clinical Oncology 39, no. 6_suppl (February 20, 2021): 467. http://dx.doi.org/10.1200/jco.2021.39.6_suppl.467.
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467 Background: The genetics of urothelial carcinoma (UC), the most common histology of urinary tract (UT) tumors, is well characterized; much less is known about the genomic features of rare histologic variants of UT tumors. We aim to compare the genomic alterations (GA) of UT tumors with adenocarcinoma (AD), small cell (SC), squamous cell (SQ), or plasmacytoid (PC) histologies, to UC tumors. Methods: We identified patients with pure variant (AD, SC, SQ, PC) or UC histology with genetic characterization through the GENIE registry. Patient tumor genomic data were captured by Memorial Sloan Kettering Cancer Center (MSK)-IMPACT and Dana-Farber Cancer Institute (DFCI)-Oncopanel NGS initiatives. Tumors with mixed histology were excluded. We limited our analysis to genes tested >1000 times (N=211). Mutation frequencies and copy number variants (CNVs), collectively called GAs, were determined for AD, SC, SQ, PC, and UC, and were compared using the Fisher’s Exact test and Kruskall Wallis test. Nominal p values were obtained, and FDR correction was employed (q < 0.1). Results: We identified 1199 patients with available genomic data who met the inclusion criteria. Histologic distribution was: 32 AD, 13 SC, 15 SQ, 11 PC, and 1128 UC tumors. The median age was 68 years and 77% of patients were male. Statistically significant differences in genetic alterations by subtype are shown in the table below. ARID1A and KDM6A GAs were higher in UC; PC and SC; CDH1 GAs higher in PC; RB1 and TP53 GAs higher in SC; SMAD4 GAs higher in AD; and NFE2L2 GAs higher in SQ. Conclusions: Variant UT histologies exhibit a distinct pattern of alterations compared to UC, consistent with their divergent clinical behavior. This suggests different biological origins for these variant histologies and possibly different therapeutic vulnerabilities. Exploring the GAs of these UT tumors in larger datasets is warranted. [Table: see text]
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Murphy, Stephen J., Marie-Christine Aubry, Faye R. Harris, Geoffrey C. Halling, Sarah H. Johnson, Simone Terra, Travis M. Drucker, et al. "Identification of Independent Primary Tumors and Intrapulmonary Metastases Using DNA Rearrangements in Non–Small-Cell Lung Cancer." Journal of Clinical Oncology 32, no. 36 (December 20, 2014): 4050–58. http://dx.doi.org/10.1200/jco.2014.56.7644.
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PurposeDistinguishing independent primary tumors from intrapulmonary metastases in non–small-cell carcinoma remains a clinical dilemma with significant clinical implications. Using next-generation DNA sequencing, we developed a chromosomal rearrangement–based approach to differentiate multiple primary tumors from metastasis.MethodsTumor specimens from patients with known independent primary tumors and metastatic lesions were used for lineage test development, which was then applied to multifocal tumors. Laser capture microdissection was performed separately for each tumor. Genomic DNA was isolated using direct in situ whole-genome amplification methodology, and next-generation sequencing was performed using an Illumina mate-pair library protocol. Sequence reads were mapped to the human genome, and primers spanning the fusion junctions were used for validation polymerase chain reaction.ResultsA total of 41 tumor samples were sequenced (33 adenocarcinomas [ADs] and eight squamous cell carcinomas [SQCCs]), with a range of three to 276 breakpoints per tumor identified. Lung tumors predicted to be independent primary tumors based on different histologic subtype did not share any genomic rearrangements. In patients with lung primary tumors and paired distant metastases, shared rearrangements were identified in all tumor pairs, emphasizing the patient specificity of identified breakpoints. Multifocal AD and SQCC samples were reviewed independently by two pulmonary pathologists. Concordance between histology and genomic data occurred in the majority of samples. Discrepant tumor samples were resolved by genome sequencing.ConclusionA diagnostic lineage test based on genomic rearrangements from mate-pair sequencing demonstrates promise for distinguishing independent primary from metastatic disease in lung cancer.
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Brune, Magdalena M., Darius Juskevicius, Jasmin Haslbauer, Stefan Dirnhofer, and Alexandar Tzankov. "Genomic Landscape of Hodgkin Lymphoma." Cancers 13, no. 4 (February 8, 2021): 682. http://dx.doi.org/10.3390/cancers13040682.
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Background: Hodgkin lymphoma (HL) is predominantly composed of reactive, non-neoplastic cells surrounding scarcely distributed tumor cells, that is, so-called Hodgkin and Reed-Sternberg (HRS) or lymphocyte predominant (LP) cells. This scarcity impeded the analysis of the tumor cell genomes for a long time, but recently developed methods (especially laser capture microdissection, flow cytometry/fluorescence-activated cell sorting) facilitated molecular investigation, elucidating the pathophysiological principles of “Hodgkin lymphomagenesis”. Methods: We reviewed the relevant literature of the last three decades focusing on the genomic landscape of classic and nodular lymphocyte predominant HL (NLPHL) and summarized molecular cornerstones. Results: Firstly, the malignant cells of HL evade the immune system by altered expression of PDL1/2, B2M and MHC class I and II due to various genetic alterations. Secondly, tumor growth is promoted by permanently activated JAK/STAT signaling due to pervasive mutations of multiple genes involved in the pathway. Thirdly, apoptosis of neoplastic cells is prevented by alterations of NF-κB compounds and the PI3K/AKT/mTOR axis. Additionally, Epstein-Barr virus infection can simultaneously activate JAK/STAT and NF-κB, similarly leading to enhanced survival and evasion of apoptosis. Finally, epigenetic phenomena such as promoter hypermethylation lead to the downregulation of B-lineage-specific, tumor-suppressor and immune regulation genes. Conclusion: The blueprint of HL genomics has been laid, paving the way for future investigations into its complex pathophysiology.
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van Beers, Erik H., Tibor van Welsem, Lodewyk F. A. Wessels, Yunlei Li, Rogier A. Oldenburg, Peter Devilee, Cees J. Cornelisse, et al. "Comparative Genomic Hybridization Profiles in Human BRCA1 and BRCA2 Breast Tumors Highlight Differential Sets of Genomic Aberrations." Cancer Research 65, no. 3 (February 1, 2005): 822–27. http://dx.doi.org/10.1158/0008-5472.822.65.3.
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Abstract BRCA1 or BRCA2 germline mutations cause ∼30% of breast cancers within high-risk families. This represents 5% of total breast cancer incidence. Although BRCA1 and BRCA2 are both implicated in DNA repair and genome stability, it is unknown whether BRCA1 and BRCA2 are associated with similar or distinct diseases. In a previous study we reported that BRCA1-related breast carcinomas show a distinct genomic profile as determined by comparative genomic hybridization (CGH). We now hypothesize that, if functionally equivalent, mutations in BRCA1 and BRCA2 would result in similar genomic profiles in tumors. Here we report the chromosomal gains and losses as measured by CGH in 25 BRCA2-associated breast tumors and compared them with our existing 36 BRCA1 and 30 control profiles. We compared all chromosomal regions and determined the regions of differential gain or loss between tumor classes and controls. BRCA2 and control tumors have very similar genomic profiles. As a consequence, and in contrast to BRCA1-associated tumors, CGH profiles from BRCA2-associated tumors could not be distinguished from control tumors using the classification methodology as we have developed before. The largest number of significant differences existed between BRCA1 and controls, followed by BRCA1 compared with BRCA2, suggesting different tumor development pathways for BRCA1 and BRCA2.
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Abida, Wassim, Ryan Brennan, Joshua Armenia, Kristen Rebecca Curtis, Anuradha Gopalan, Maria E. Arcila, Daniel Costin Danila, et al. "Genomic characterization of primary and metastatic prostate cancer (PC) using a targeted next-generation sequencing assay." Journal of Clinical Oncology 34, no. 2_suppl (January 10, 2016): 254. http://dx.doi.org/10.1200/jco.2016.34.2_suppl.254.
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254 Background: Genomic alterations in PC have been described across the disease continuum, creating opportunities for selective clinical trial enrollment of patients (pts) with high-risk or metastatic disease based on their tumor profile. MSK-IMPACT is an exon capture-based sequencing assay performed in a CLIA-certified laboratory that targets 410 cancer-associated genes, many of which are potential drug targets. We assessed mutations and copy number alterations (CNAs) in primary and metastatic samples from untreated, hormone-treated and castration resistant pts. Methods: PC pts were enrolled on an IRB-approved protocol for tumor genomic profiling. Fixed tumor and matched germline samples were subjected to DNA sequencing analysis using MSK-IMPACT for the identification of somatic mutations and CNAs. Results: 315 samples from 271 pts were successfully sequenced (Table). Overall success rate was 80% (67% for bone). 14 tumors were pathologically classified as neuroendocrine or had neuroendocrine features. 23% of patients had tumor somatic alterations in DNA repair genes (BRCA2, BRCA1, ATM, FANCA and CDK12). Additional alterations were observed in PI3K, MAPK and Wnt-βCatenin pathway genes. Common alterations in the metastatic tumors include TP53 deletion/mutation (42%), AR amplification/mutation (38%), PTEN deletion/mutation (27%), RB1 deletion/mutation (20%), BRCA2 deletion/mutation (11%), FOXA1 mutation (11%) and SPOP mutation (4%). Among metastatic samples, tumors from pts with castration-resistant disease had higher CNA burden when compared to tumors from non-castration-resistant pts (0.31 vs. 0.19 fraction genome altered, p < 0.05, unpaired t-test), as well as higher rates of AR amplification/mutation (49% vs. 3%, p < 0.01, Fisher’s exact test). Conclusions: Genomic profiling of primary and metastatic prostate tumors is feasible with the clinical MSK-IMPACT sequencing assay and has identified actionable alterations in > 40% of patients. This is allowing for selective trial enrollment and further investigation of PC genomics. [Table: see text]
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Baldeo, Candice, Tasneem Kaleem, Ricardo Paz-Fumagalli, John A. Copland, and Michael E. Menefee. "Mixed response to immunotherapy in lung cancer." Journal of Clinical Oncology 37, no. 8_suppl (March 10, 2019): 122. http://dx.doi.org/10.1200/jco.2019.37.8_suppl.122.
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122 Background: Mixed response (MR) to systemic therapy is common and associated with a poor prognosis. MR often represents a therapeutic dilemma resulting in the discontinuation of a therapy to which a portion of the tumor is still sensitive, due to the emergence of resistance in other metastatic deposits. We hypothesize that discordant responses in patients receiving immunotherapy may be associated with genomic variation within discordant tumors. Methods: We defined MR with the following criteria: 1) At least one tumor has increased in size while another tumor has decreased; 2) One or more tumors have remained stable while another has increased; 3) One or more tumors have remained stable while another has decreased. 4) A new tumor has developed while other tumors have decreased or remained stable. Between 2012 and 2017, we identified 112 patients with a MR. Two patients with metastatic lung cancer, treated with nivolumab underwent paired, simultaneous sampling of discordant tumors. Results: Both patients treated with nivolumab demonstrated genomic heterogeneity between discordant tumors on next-generation sequencing, including one patient with SCLC. Conclusions: MR remains a common and challenging therapeutic quandary. Genomic heterogeneity and differences in TMB of metastatic tumors demonstrating a MR, may be factors that contribute to this phenomenon. Further characterization of genomic discrepancies in MR may provide insights into mechanisms of emerging resistance, as well as, more rational and effective combinatorial therapies.[Table: see text]
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Chan, Hiu Ting, Yoon Ming Chin, and Siew-Kee Low. "Circulating Tumor DNA-Based Genomic Profiling Assays in Adult Solid Tumors for Precision Oncology: Recent Advancements and Future Challenges." Cancers 14, no. 13 (July 4, 2022): 3275. http://dx.doi.org/10.3390/cancers14133275.
Full textAbstract:
Genomic profiling using tumor biopsies remains the standard approach for the selection of approved molecular targeted therapies. However, this is often limited by its invasiveness, feasibility, and poor sample quality. Liquid biopsies provide a less invasive approach while capturing a contemporaneous and comprehensive tumor genomic profile. Recent advancements in the detection of circulating tumor DNA (ctDNA) from plasma samples at satisfactory sensitivity, specificity, and detection concordance to tumor tissues have facilitated the approval of ctDNA-based genomic profiling to be integrated into regular clinical practice. The recent approval of both single-gene and multigene assays to detect genetic biomarkers from plasma cell-free DNA (cfDNA) as companion diagnostic tools for molecular targeted therapies has transformed the therapeutic decision-making procedure for advanced solid tumors. Despite the increasing use of cfDNA-based molecular profiling, there is an ongoing debate about a ‘plasma first’ or ‘tissue first’ approach toward genomic testing for advanced solid malignancies. Both approaches present possible advantages and disadvantages, and these factors should be carefully considered to personalize and select the most appropriate genomic assay. This review focuses on the recent advancements of cfDNA-based genomic profiling assays in advanced solid tumors while highlighting the major challenges that should be tackled to formulate evidence-based guidelines in recommending the ‘right assay for the right patient at the right time’.
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Necchi, Andrea, Gennady Bratslavsky, Rubin Pinkhasov, Oleg Shapiro, Laurie M. Gay, Julia Andrea Elvin, Jo-Anne Vergilio, et al. "Genomic features of metastatic testicular sex cord stromal tumors." Journal of Clinical Oncology 37, no. 7_suppl (March 1, 2019): 532. http://dx.doi.org/10.1200/jco.2019.37.7_suppl.532.
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532 Background: Metastatic testicular sex cord stromal tumors of the testis (MSCST) comprise an extremely uncommon form of genitourinary malignancy. In a comparative genomic study, we performed comprehensive genomic profiling (CGP) to characterize the genomic alterations (GA) in MSCST and to enable the search for potential therapy targets. Methods: The MSCST were classified as metastatic Leydig Cell Tumors (LCT), Sertoli Cell Tumors (SCT) and Undifferentiated (USCST). In this study, 10 cases of LCT, 6 cases of SCT and 3 cases of USCST underwent hybrid-capture based CGP to evaluate all classes of genomic alterations. Tumor mutational burden (TMB) was determined on 1.1 Mbp of sequenced DNA and microsatellite instability (MSI) was determined on 114 loci. Results: All patients had clinically advanced recurrent and/or metastatic disease. The primary testis tumor was used for sequencing in 6 MSCST (32%) and a metastatic site in 9 (68%) of the MSCST. In 10 (91%) of 11 MSCST positively stained by IHC for inhibin expression. The overall frequencies of GA were similar in all LCT, SCT and UTST ranging from 3.0 to 3.5 GA/tumor. The most frequent untargetable GA found in all MSCST cases included CTNNB1 and CDKN2A/B, both ranging from 20-33% of cases. Targetable GA were uncommon in all MSCST sub-groups but several tumors featured potential for cell cycle inhibitors ( CDK4 in LCT), MTOR inhibitors ( RICTOR, NF2 and PTEN in all 3 tumor types), hedgehog inhibitors ( PTCH1 in LCT) and PARP inhibitors ( BAP1 in SCT). No MSI-High status was identified in any MSCST. The TMB was also low in all MSCST groups. Conclusions: Although the 3 subgroups of testicular MSCST feature defining histopathologic features, these tumors have similar genomic signatures on CGP. The low levels of GA per tumor, infrequent tumor aneuploidy, absence of MSI-High status and low TMB all indicate that testicular MSCST are genetically stable. However, rare cases of testicular MSCST reveal GA linked to potential targeted therapy benefits on CGP linked to dysregulation of multiple biologic pathways. In contrast, the lack of MSI-High status and overall low TMB in testicular MSCST indicates a likely lack of benefit for immunotherapies for these rare forms of malignancy.
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Subramanian, Ayshwarya, Stanley Shackney, and Russell Schwartz. "Inference of Tumor Phylogenies from Genomic Assays on Heterogeneous Samples." Journal of Biomedicine and Biotechnology 2012 (2012): 1–16. http://dx.doi.org/10.1155/2012/797812.
Full textAbstract:
Tumorigenesis can in principle result from many combinations of mutations, but only a few roughly equivalent sequences of mutations, or “progression pathways,” seem to account for most human tumors. Phylogenetics provides a promising way to identify common progression pathways and markers of those pathways. This approach, however, can be confounded by the high heterogeneity within and between tumors, which makes it difficult to identify conserved progression stages or organize them into robust progression pathways. To tackle this problem, we previously developed methods for inferring progression stages from heterogeneous tumor profiles through computational unmixing. In this paper, we develop a novel pipeline for building trees of tumor evolution from the unmixed tumor data. The pipeline implements a statistical approach for identifying robust progression markers from unmixed tumor data and calling those markers in inferred cell states. The result is a set of phylogenetic characters and their assignments in progression states to which we apply maximum parsimony phylogenetic inference to infer tumor progression pathways. We demonstrate the full pipeline on simulated and real comparative genomic hybridization (CGH) data, validating its effectiveness and making novel predictions of major progression pathways and ancestral cell states in breast cancers.