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Gray, Stacy

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Gray

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Stacy

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Gray, Stacy

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2013 - 20175

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Author's Publications: search.filters.isAuthorOfPublication.7c535b5c-87a5-4c32-af23-8be6f1944cc2

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Now showing 1 - 5 of 5
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    Whole-exome sequencing and clinical interpretation of FFPE tumor samples to guide precision cancer medicine
    (2013) Allen, Eliezer M. Van; Wagle, Nikhil; Stojanov, Petar; Perrin, Danielle L.; Cibulskis, Kristian; Marlow, Sara; Jane-Valbuena, Judit; Friedrich, Dennis C.; Kryukov, Gregory; Carter, Scott L.; McKenna, Aaron; Sivachenko, Andrey; Rosenberg, Mara; Kiezun, Adam; Voet, Douglas; Lawrence, Michael; Lichtenstein, Lee T.; Gentry, Jeff G.; Huang, Franklin; Fostel, Jennifer; Farlow, Deborah; Barbie, David; Gandhi, Leena; Lander, Eric; Gray, Stacy; Joffe, Steven; Janne, Pasi; Garber, Judy; MacConaill, Laura; Lindeman, Neal; Rollins, Barrett; Kantoff, Philip; Fisher, Sheila A.; Gabriel, Stacey; Getz, Gad; Garraway, Levi
    Translating whole exome sequencing (WES) for prospective clinical use may impact the care of cancer patients; however, multiple innovations are necessary for clinical implementation. These include: (1) rapid and robust WES from formalin-fixed paraffin embedded (FFPE) tumor tissue, (2) analytical output similar to data from frozen samples, and (3) clinical interpretation of WES data for prospective use. Here, we describe a prospective clinical WES platform for archival FFPE tumor samples. The platform employs computational methods for effective clinical analysis and interpretation of WES data. When applied retrospectively to 511 exomes, the interpretative framework revealed a “long tail” of somatic alterations in clinically important genes. Prospective application of this approach identified clinically relevant alterations in 15/16 patients. In one patient, previously undetected findings guided clinical trial enrollment leading to an objective clinical response. Overall, this methodology may inform the widespread implementation of precision cancer medicine.
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    The impact of tumor profiling approaches and genomic data strategies for cancer precision medicine
    (BioMed Central, 2016) Garofalo, Andrea; Sholl, Lynette; Reardon, Brendan; Taylor-Weiner, Amaro; Amin-Mansour, Ali; Miao, Diana; Liu, David; Oliver, Nelly; MacConaill, Laura; Ducar, Matthew; Rojas-Rudilla, Vanesa; Giannakis, Marios; Ghazani, Arezou; Gray, Stacy; Janne, Pasi; Garber, Judy; Joffe, Steve; Lindeman, Neal; Wagle, Nikhil; Garraway, Levi; Van Allen, Eliezer
    Background: The diversity of clinical tumor profiling approaches (small panels to whole exomes with matched or unmatched germline analysis) may engender uncertainty about their benefits and liabilities, particularly in light of reported germline false positives in tumor-only profiling and use of global mutational and/or neoantigen data. The goal of this study was to determine the impact of genomic analysis strategies on error rates and data interpretation across contexts and ancestries. Methods: We modeled common tumor profiling modalities—large (n = 300 genes), medium (n = 48 genes), and small (n = 15 genes) panels—using clinical whole exomes (WES) from 157 patients with lung or colon adenocarcinoma. We created a tumor-only analysis algorithm to assess germline false positive rates, the impact of patient ancestry on tumor-only results, and neoantigen detection. Results: After optimizing a germline filtering strategy, the germline false positive rate with tumor-only large panel sequencing was 14 % (144/1012 variants). For patients whose tumor-only results underwent molecular pathologist review (n = 91), 50/54 (93 %) false positives were correctly interpreted as uncertain variants. Increased germline false positives were observed in tumor-only sequencing of non-European compared with European ancestry patients (p < 0.001; Fisher’s exact) when basic germline filtering approaches were used; however, the ExAC database (60,706 germline exomes) mitigated this disparity (p = 0.53). Matched and unmatched large panel mutational load correlated with WES mutational load (r2 = 0.99 and 0.93, respectively; p < 0.001). Neoantigen load also correlated (r2 = 0.80; p < 0.001), though WES identified a broader spectrum of neoantigens. Small panels did not predict mutational or neoantigen load. Conclusions: Large tumor-only targeted panels are sufficient for most somatic variant identification and mutational load prediction if paired with expanded germline analysis strategies and molecular pathologist review. Paired germline sequencing reduced overall false positive mutation calls and WES provided the most neoantigens. Without patient-matched germline data, large germline databases are needed to minimize false positive mutation calling and mitigate ethnic disparities. Electronic supplementary material The online version of this article (doi:10.1186/s13073-016-0333-9) contains supplementary material, which is available to authorized users.
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    Medical Oncologists’ Experiences in Using Genomic Testing for Lung and Colorectal Cancer Care
    (American Society of Clinical Oncology (ASCO), 2017) Gray, Stacy; Kim, Benjamin; Sholl, Lynette; Cronin, Angel; Parikh, Aparna R.; Klabunde, Carrie N.; Kahn, Katherine L.; Haggstrom, David A.; Keating, Nancy
    Purpose: Genomic testing improves outcomes for many at-risk individuals and patients with cancer; however, little is known about how genomic testing for non–small-cell lung cancer (NSCLC) and colorectal cancer (CRC) is used in clinical practice. Patients and Methods: In 2012 to 2013, we surveyed medical oncologists who care for patients in diverse practice and health care settings across the United States about their use of guideline- and non–guideline-endorsed genetic tests. Multivariable regression models identified factors that are associated with greater test use. Results: Of oncologists, 337 completed the survey (participation rate, 53%). Oncologists reported higher use of guideline-endorsed tests (eg, KRAS for CRC; EGFR for NSCLC) than non–guideline-endorsed tests (eg, OncotypeDX Colon; ERCC1 for NSCLC). Many oncologists reported having no patients with CRC who had mismatch repair and/or microsatellite instability (24%) or germline Lynch syndrome (32%) testing, and no patients with NSCLC who had ALK testing (11%). Of oncologists, 32% reported that five or fewer patients had KRAS and EGFR testing for CRC and NSCLC, respectively. Oncologists, rather than pathologists or surgeons, ordered the vast majority of tests. In multivariable analyses, fewer patients in nonprofit integrated health care delivery systems underwent testing than did patients in hospital or office-based single-specialty group settings (all P < .05). High patient volume and patient requests (CRC only) were also associated with higher test use (all P < .05). Conclusion: Genomic test use for CRC and NSCLC varies by test and practice characteristics. Research in specific clinical contexts is needed to determine whether the observed variation reflects appropriate or inappropriate care. One potential way to reduce unwanted variation would be to offer widespread reflexive testing by pathology for guideline-endorsed predictive somatic tests.
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    Combined Use of ALK Immunohistochemistry and FISH for Optimal Detection of ALK-Rearranged Lung Adenocarcinomas
    (Elsevier BV, 2013) Sholl, Lynette; Weremowicz, Stanislawa; Gray, Stacy; Wong, Kwok-Kin; Chirieac, Lucian; Lindeman, Neal; Hornick, Jason
    INTRODUCTION ALK gene rearrangements occur in ~5% of lung adenocarcinomas (ACA), leading to ALK overexpression and predicting response to targeted therapy. Fluorescence in situ hybridization (FISH) is the gold standard for detection of ALK rearrangements in lung ACA but requires specialized equipment and expertise. Immunohistochemistry (IHC) for ALK protein overexpression is a promising screening modality, with reports of newer antibodies showing excellent sensitivity and specificity for ALK-rearranged lung ACA. METHODS In this study, we analyze ALK IHC (5A4 clone) in 186 cases from our clinical service and compare with ALK FISH and EGFR and KRAS mutation status. RESULTS Twelve cases had concordant ALK protein overexpression and ALK rearrangement by FISH. Three ALK-rearranged cases lacked ALK protein expression. Of these discrepant cases, one had a coexisting EGFR mutation and a subtle “atypical” ALK rearrangement with a break in the 5’ centromeric portion of the FISH probe. One case had a concurrent BRAF mutation; followup testing on a metastasis revealed absence of the ALK-rearrangement with persistent BRAF mutation. In one ALK-rearranged, protein negative case, very limited tissue remained for ALK IHC, raising the possibility of false negativity due to protein expression heterogeneity. Importantly, ALK protein expression was detected in one case initially thought not to have an ALK rearrangement. In this case, FISH was falsely negative due to interference by benign reactive nuclei. After correcting for these cases, ALK IHC was 93% sensitive and 100% specific as compared to FISH. CONCLUSIONS ALK IHC improves the detection of ALK rearrangements when used together with FISH, and its use in lung adenocarcinoma genetic testing algorithms should be considered.
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    Oncologists' and Cancer Patients' Views on Whole-Exome Sequencing and Incidental Findings: Results from The CanSeq Study
    (2016) Gray, Stacy; Park, Elyse; Najita, Julie; Martins, Yolanda; Traeger, Lara; Bair, Elizabeth; Gagne, Joshua; Garber, Judy; Janne, Pasi; Lindeman, Neal; Lowenstein, Carol; Oliver, Nelly; Sholl, Lynette; Van Allen, Eliezer; Wagle, Nikhil; Wood, Sam; Garraway, Levi; Joffe, Steven
    Purpose While targeted sequencing improves outcomes for many cancer patients, how somatic and germline whole-exome sequencing (WES) will integrate into care remains uncertain. Methods: We conducted surveys and interviews, within a study of WES integration at an academic center, to determine oncologists' attitudes about WES and to identify lung and colorectal cancer patients' preferences for learning WES findings. Results: 167 patients (85% white, 58% female, mean age 60) and 27 oncologists (22% female) participated. Although oncologists had extensive experience ordering somatic tests (median 100/year), they had little experience ordering germline tests. Oncologists intended to disclose most WES results to patients but anticipated numerous challenges in using WES. Patients had moderately low levels of genetic knowledge (mean 4 correct of 7). Most patients chose to learn results that could help select a clinical trial, pharmacogenetic and positive prognostic results, and results suggesting inherited predisposition to cancer and treatable non-cancer conditions (all ≥95%). Fewer chose to receive negative prognostic results (84%) and results suggesting predisposition to untreatable non-cancer conditions (85%). Conclusion: The majority of patients want most cancer-related and incidental WES results. Patients' low levels of genetic knowledge and oncologists' inexperience with large-scale sequencing presage challenges to implementing paired WES in practice.