Ann Arbor
MI, 48109 USA
Available to mentor
My clinical interests revolve around the provision of clinical genetics care to the adult population. This includes clinical time spent between Adult Medical Genetics and Cancer Genetics. I initiated a clinical cancer genetics program at the VA Ann Arbor Healthcare System, where I have a partial clinical appointment. I am especially interested in providing cancer genetic counseling services to the Veteran community and performing cancer surveillance of individuals with hereditary cancer syndromes. Additionally, I am coordinating the return of over 2,000 clinically actionable results identified as part of the Michigan Genomics Initiative.
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Medical Genetics FellowshipUniversity of Michigan Medical School, Ann Arbor, 2021
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Internal Medicine ResidencyUniversity of Michigan Medical School, Ann Arbor, 2019
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MD, PhDCase Western Reserve University, Cleveland, 2016
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BSUniversity of Rochester, Rochester, 2008
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Center MemberPrecision Health Initiative
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Center MemberRogel Cancer Center
My main research interest deals with improving clinical variant interpretation via a high-throughput method called deep mutational scanning to interrogate thousands of variants simultaneously. Primarily, this involves the use of a cellular model to identify pathogenic variants in Lynch Syndrome, a hereditary cancer syndrome, to help reclassify variants of uncertain significance recovered from clinical genetics testing. I am also applying these methods to an endometrial cancer model to determine how different mutations can affect tumor development and/or treatment efficacy. Moreover, I am participating in research collaborations with Ambry Genetics to identify novel variants associated with Peutz-Jeghers and Juvenile Polyposis Syndromes, as well as with Karmanos Cancer Institute to improve variant classification in African-American cancer patients.
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Jiang CY, Zhao L, Green MD, Ravishankar S, Towlerton AMH, Scott AJ, Raghavan M, Cusick MF, Warren EH, Ramnath N. Sci Rep, 2024 Jan 3; 14 (1): 345Journal ArticleClass II HLA-DRB4 is a predictive biomarker for survival following immunotherapy in metastatic non-small cell lung cancer.
DOI:10.1038/s41598-023-48546-y PMID: 38172168 -
Jiang C, Ravishankar S, Zhao L, Green M, Towlerton A, Scott A, Raghavan M, Cusick M, Warren EH, Ramnath N. Journal of Clinical Oncology, 2023 Jun 1; 41 (16_suppl): e21005 - e21005.Proceeding / Abstract / PosterRole of HLA-DRB4 as a biomarker for endocrine toxicity and survival outcomes after immunotherapy in metastatic non-small cell lung cancer.
DOI:10.1200/jco.2023.41.16_suppl.e21005 -
Jiang C, Zhao L, Green M, Ravishankar S, Towlerton A, Scott A, Raghavan M, Cusick M, Warren E, Ramnath N. 2023 Research Square,PreprintClass II HLA-DRB4 is a predictive biomarker for survival following immunotherapy in metastatic non-small cell lung cancer
DOI:10.21203/rs.3.rs-2929223/v1 -
Jiang C, Ravishankar S, Zhao L, Green M, Towlerton A, Scott A, Raghavan M, Cusick M, Warren EH, Ramnath N. JOURNAL OF CLINICAL ONCOLOGY, 2023 41 (16):Proceeding / Abstract / PosterRole of HLA-DRB4 as a biomarker for endocrine toxicity and survival outcomes after immunotherapy in metastatic non-small cell lung cancer
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Scott A, Hernandez F, Chamberlin A, Smith C, Karam R, Kitzman JO. Genome Biol, 2022 Dec 22; 23 (1): 266Journal ArticleSaturation-scale functional evidence supports clinical variant interpretation in Lynch syndrome.
DOI:10.1186/s13059-022-02839-z PMID: 36550560 -
Scott A, Hernandez F, Chamberlin A, Smith C, Karam R, Kitzman J. 2022 medRxiv,PreprintSaturation-scale functional evidence supports clinical variant interpretation in Lynch Syndrome
DOI:10.1101/2022.08.08.22278549 -
Scott A, Mohan A, Austin S, Amini E, Raupp S, Pannecouk B, Kelley MJ, Narla G, Ramnath N. JCO Oncol Pract, 2022 Jun; 18 (6): e966 - e973.Journal ArticleIntegrating Medical Genetics Into Precision Oncology Practice in the Veterans Health Administration: The Time Is Now.
DOI:10.1200/OP.21.00693 PMID: 35258993 -
Scott A, Martin DM. Genet Med, 2021 May; 23 (5): 972 - 975.Journal ArticleDevelopment and implementation of an electronic medical record module to track genetic testing results.
DOI:10.1038/s41436-020-01057-x PMID: 33500566