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  • 1
    In: JCO Precision Oncology, American Society of Clinical Oncology (ASCO), , No. 5 ( 2021-11), p. 1840-1852
    Abstract: Molecular tumor profiling is becoming a routine part of clinical cancer care, typically involving tumor-only panel testing without matched germline. We hypothesized that integrated germline sequencing could improve clinical interpretation and enhance the identification of germline variants with significant hereditary risks. MATERIALS AND METHODS Tumors from pediatric patients with high-risk, extracranial solid malignancies were sequenced with a targeted panel of cancer-associated genes. Later, germline DNA was analyzed for a subset of these genes. We performed a post hoc analysis to identify how an integrated analysis of tumor and germline data would improve clinical interpretation. RESULTS One hundred sixty participants with both tumor-only and germline sequencing reports were eligible for this analysis. Germline sequencing identified 38 pathogenic or likely pathogenic variants among 35 (22%) patients. Twenty-five (66%) of these were included in the tumor sequencing report. The remaining germline pathogenic or likely pathogenic variants were single-nucleotide variants filtered out of tumor-only analysis because of population frequency or copy-number variation masked by additional copy-number changes in the tumor. In tumor-only sequencing, 308 of 434 (71%) single-nucleotide variants reported were present in the germline, including 31% with suggested clinical utility. Finally, we provide further evidence that the variant allele fraction from tumor-only sequencing is insufficient to differentiate somatic from germline events. CONCLUSION A paired approach to analyzing tumor and germline sequencing data would be expected to improve the efficiency and accuracy of distinguishing somatic mutations and germline variants, thereby facilitating the process of variant curation and therapeutic interpretation for somatic reports, as well as the identification of variants associated with germline cancer predisposition.
    Type of Medium: Online Resource
    ISSN: 2473-4284
    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2021
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  • 2
    In: Current Problems in Cancer, Elsevier BV, Vol. 41, No. 3 ( 2017-05), p. 194-200
    Type of Medium: Online Resource
    ISSN: 0147-0272
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2017
    detail.hit.zdb_id: 2022907-0
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  • 3
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 80, No. 14_Supplement ( 2020-07-15), p. A06-A06
    Abstract: Introduction: Tumor profiling is becoming a more routine part of clinical care. Many academic centers and commercial entities offer tumor sequencing of cancer-related genes without matched germline profiling. We hypothesize that tumor-only sequencing may limit full clinical interpretation and have decreased sensitivity to identify significant germline variants. Methods: The Genomic Assessment Improves Novel Therapy (GAIN) Consortium is a clinical cancer genomics study for patients with high-risk solid malignancies. Patients in this study were selected for subanalysis if panel sequencing of 447 genes was performed on a tumor and interpreted by an expert panel prior to the availability of matched germline sequencing. Interpretation of tumor sequencing included both therapeutic recommendations and a curation of cancer-related variants of potential clinical significance if present in the germline. Germline sequencing was separately performed targeting 147 genes (a subset of the somatic panel) and analyzed with a germline-specific pipeline to identify and filter variants. We examined clinical recommendations in the somatic reports that were based on single-nucleotide variants identified from the 147 overlapping genes. We compared these interpretations with results from the matched germline data. Results: We identified 159 participants with somatic and germline sequencing reports meeting the eligibility criteria. Germline sequencing identified 38 pathogenic or likely pathogenic (P/LP) germline variants in 35 of 159 patients (22%). Of those 35 patients, 17 (49%) had a P/LP variant in an autosomal dominant cancer predisposition gene, 19 (54%) in an autosomal recessive gene, and 1 (2.9%) in a noncancer gene. Of the 38 total variants, 21 (55%) were identified by the analytic pipeline used for somatic sequencing and noted as potential germline variants in the somatic reports. Forty treatment recommendations were made from the somatic data within the overlapping genes. Ten (25%) treatment recommendations were based on variants that were later determined to be germline. These included variants in TP53, SDHA, SMARCA4, TSC2, FAM175A, CHEK2, and AKT1, many of which were noted in the somatic reports to be variants of uncertain significance or possibly germline. Conclusions: In this study, we found that clinically actionable germline variants were under-reported when relying on analytical pipelines and clinical interpretations developed for the analysis of tumor samples. In the absence of germline sequencing, we also found that cancer treatment recommendations can be made based on mutations identified from tumor sequencing that are germline variants. In many cases, these recommendations remain appropriate (e.g., PARP inhibitors for BRCA1/2) while in other cases germline data facilitated a more nuanced interpretation of actionability. These findings support the use of germline genetic testing and paired tumor-germline analysis in precision cancer medicine studies. Citation Format: Jaclyn Schienda, Catherine M. Clinton, Laura B. Corson, Alma Imamovic-Tuco, Navin Pinto, Luke Maese, Theodore W. Laetsch, AeRang Kim, Susan I. Vear, Margaret E. Macy, Mark A. Applebaum, Rochelle Bagatell, Amit J. Sabnis, Daniel A. Weiser, Julia L. Glade-Bender, Samuel L. Volchenboum, Wenjun Kang, Danielle Manning, Jonathan Nowak, Joshua Schiffman, Neal I. Lindeman, Alanna J. Church, Katherine A. Janeway, Brian D. Crompton, Junne Kamihara. The added value of examining germline variants in a precision cancer therapy study [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr A06.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2020
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    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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  • 4
    In: Nature Medicine, Springer Science and Business Media LLC, Vol. 28, No. 8 ( 2022-08), p. 1581-1589
    Type of Medium: Online Resource
    ISSN: 1078-8956 , 1546-170X
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 1484517-9
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  • 5
    In: JAMA Oncology, American Medical Association (AMA), Vol. 2, No. 5 ( 2016-05-01), p. 608-
    Type of Medium: Online Resource
    ISSN: 2374-2437
    Language: English
    Publisher: American Medical Association (AMA)
    Publication Date: 2016
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  • 6
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 79, No. 13_Supplement ( 2019-07-01), p. 3104-3104
    Abstract: The GAIN iCat2 Project is a collaboration between Dana-Farber/Boston Children's Cancer and Blood Disorder Center and eleven pediatric oncology centers across the United States to sequence relapsed, metastatic, difficult-to-diagnose, and high-risk extracranial solid tumors from 825 patients. The goals are to gain a better understanding of the genomic events in pediatric cancers and determine the clinical impact of matched targeted therapy. Tumor samples are sequenced on one of four gene panels performed in CLIA certified, CAP accredited laboratories, most often utilizing OncoPanel at the Center for Advanced Molecular Diagnostics, Brigham Women’s Hospital. This panel assesses SNVs and CNVs in 447 cancer-associated genes and interrogates intronic regions of 60 genes frequently involved in oncogenic translocation. For undifferentiated sarcomas and tumors in which oncogenic drivers are not identified by the gene panel, whole exome sequencing or RNA sequencing for fusion detection may be done. Interpretation of genomic results, including potential implications for diagnosis and hereditary risks, as well as assessment of possible matched targeted therapies and suitable trials are summarized in a report to the primary oncology provider. An interim analysis of tumors from the first 275 patients enrolled who have OncoPanel results was performed to assess genomic alterations most prevalent in this group of pediatric cancers. 50% (137/275) have structural alterations in their tumors with over half of these (74/137) harboring an oncogenic fusion that is the main, or only identified, driver of the cancer. These include fusions pathognomonic for diseases such as Ewing sarcoma, alveolar rhabdomyosarcoma, synovial sarcoma, desmoplastic small round cell tumors, mesenchymal chondrosarcoma, low grade fibromyxoid sarcoma, and NUT midline carcinoma. Other cases showed recurrent disruption of key tumor suppressors, such as TP53 intron 1 translocations in osteosarcoma. Lastly, more generalized, key, cancer-driving fusions were seen with rearrangements involving BRAF, NOTCH, and NTRK. In addition to aiding in diagnosis, identification of fusions has led to targeted therapy recommendations for many patients. SNVs and CNVs also helped clarify diagnoses, especially in the case of DICER1 and SMARCB1 alterations, and identified potential targeted therapies to consider for relapsed patients. Although patient recruitment is ongoing, this study shows promise for advancing our understanding and treatment of pediatric cancers and highlights the critical importance of incorporating techniques for fusion detection in tumor profiling. Citation Format: Laura B. Corson, Alma Imamovic-Tuco, Gianna R. Strand, Deirdre Reidy, Duong Doan, Mark A. Applebaum, Rochelle Bagatell, Brian D. Crompton, Steven G. DuBois, Julia L. Glade Bender, AeRang Kim, Theodore W. Laetsch, Lobin A. Lee, Neal I. Lindeman, Laura E. MacConaill, Margaret E. Macy, Luke Maese, Seth Pinches, Navin Pinto, Amit J. Sabnis, Eliezer M. Van Allen, Susan I. Vear, Daniel A. Weiser, Catherine M. Clinton, Katherine A. Janeway, Alanna J. Church. A high prevalence of chromosomal translocations as drivers in high-risk pediatric solid cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3104.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2019
    detail.hit.zdb_id: 2036785-5
    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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  • 7
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 80, No. 14_Supplement ( 2020-07-15), p. B13-B13
    Abstract: Introduction: Gene fusions are important oncogenic drivers with significant clinical impact in some cancer types. This is particularly true in pediatric cancers that often have low mutational burden and lack other diagnostic markers and therapeutic targets. Many gene fusions are rare or private to the individual patient and can be difficult to detect with methods optimized for common fusions. Unbiased sequencing methods and expansive computational resources are needed for expanding our ability to characterize fusions. Building a comprehensive catalog of oncogenic gene fusions will improve our understanding of their diversity and fully harness their potential for clinical impact. Methods: Patients are eligible for the GAIN/iCat2 study if they have been diagnosed with high-risk or recurrent/refractory extracranial solid tumor at age 30 or less and have a sample available for sequencing. Enrolled patients with an unclear diagnosis after standard clinical testing are nominated for transcriptome sequencing by the study investigators. We developed a computational pipeline in Google Cloud for gene fusion discovery utilizing paired end Illumina RNA-Seq data, multiple fusion callers, and a custom algorithm for integrative data analysis. The multicaller fusion detection approach enables us to address the high false-positive rate typical for gene fusion calling in transcriptomic data while improving the sensitivity to detect the more challenging fusions. After filtering, the fusions are annotated using the databases of known fusions and cancer genes. The predicted fusion transcripts are inspected visually, and the fusions are selected based on relevance to diagnostic classification or therapy to be validated by an orthogonal method. Results: 41 tumor samples were sequenced and analyzed for gene fusions. A total of 203 candidate fusions were detected by two or more fusion callers. Based on functional annotations and potential impact on diagnosis or therapeutic approaches, 12 fusion transcripts of interest were identified, 10 of which were validated by either pre-enrollment testing or an orthogonal method. Of 16 mesenchymal cases, 6 validated fusions had diagnostic relevance and 3 validated fusions had therapeutic implications (ERC1-BRAF, RBPMS-NTRK2, and VCAN-IL23R). Two patients responded to matched targeted therapy. In one case, diagnostic classification was revised. Conclusions: Whole-transcriptome sequencing in this selected patient population identified some fusion transcripts with clinical relevance. Determining the biologic significance of previously unreported fusions will require orthogonal sequencing such as whole genome, functional studies, and analysis of larger patient populations. Improved accuracy and scalability of methods for large-scale gene fusion analysis in the growing public datasets are likely to expand the landscape of gene fusions in cancer. Citation Format: Alma Imamovic, Alanna J. Church, Laura B. Corson, Deirdre Reidy, Navin Pinto, Luke Maese, Theodore W. Laetsch, AeRang Kim, Susan I. Vear, Margaret E. Macy, Mark A. Applebaum, Rochelle Bagatell, Amit J. Sabnis, Daniel A. Weiser, Julia L. Glade-Bender, Gianna R. Strand, Lobin A. Lee, R. Seth Pinches, Catherine M. Clinton, Brian D. Crompton, Neal I. Lindeman, Steven G. DuBois, Katherine A. Janeway, Eliezer M. Van Allen. Leveraging cloud-based computational resources for gene fusion discovery with potential clinical implications for pediatric solid tumor patients [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr B13.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2020
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    detail.hit.zdb_id: 1432-1
    detail.hit.zdb_id: 410466-3
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