Padma Sheila Rajagopal, M.D., M.P.H., M.Sc.

Center for Cancer Research
National Cancer Institute

Building 10, Room 4B54
Bethesda, MD 20892
240-858-3169
sheila.rajagopal@nih.gov

Physician-Scientist Early Investigator

Cancer Data Science Laboratory

RESEARCH SUMMARY

Dr. Rajagopal’s laboratory investigates how genomic and transcriptomic interactions between germline variants / inherited cancer syndromes and somatic development in tumors can improve clinical prediction and prognostication in patients with cancer.

Areas of Expertise

Cancer Genomics

Data Science and Computational Biology

Hereditary Cancer Syndromes

Cancer Transcriptomics

Statistical Genetics

Breast Cancer

Research
Publications
Biography
Job Vacancies
News
Team
Alumni

Research

Extensive molecular data is increasingly used in clinical oncology to identify predictors of response to therapeutic options or to gain prognostic information, including germline (hereditary) and somatic (tumor-specific) DNA sequencing and RNA/transcriptomic assays. However, use of these data types in the clinic remains limited to specific, narrow contexts, creating one of the largest hurdles in oncology’s current ability to leverage precision strategies.

The goal of this lab is to advance clinically relevant tools / information for treatment prediction and outcome prognostication in cancer through integration of data types and use of models from statistical genetics. To this end, the Rajagopal Lab currently works in two major domains:

Linking germline and somatic data to treatment outcomes across datasets
Adapting published computational approaches using transcriptomic data for applications in breast cancer, including hereditary cancer populations

Publications

Identification of Germline Population Variants Misclassified as Cancer-Associated Somatic Variants

Rebecca Pollard, Matthew Wilkerson, Padma S Rajagopal

Frontiers in Medicine. 2024.

Full-Text Article

Characterization of Oncology Clinical Trials Using Germline Genetic Data

Ashwin V. Kammula, BS1,2; Alejandro A. Schäffer, PhD1; Padma Sheila Rajagopal, MD, MPH, MSc1,3

Oncology. 2022.

Full-Text Article

Clinically oriented prediction of patient response to targeted and immunotherapies from the tumor transcriptome

Gal Dinstag 1, Eldad D Shulman 2, Efrat Elis 2, Doreen S Ben-Zvi 2, Omer Tirosh 2, Eden Maimon 2, Isaac Meilijson 3, Emmanuel Elalouf 2, Boris Temkin 2, Philipp Vitkovsky 2, Eyal Schiff 2, Danh-Tai Hoang 4, Sanju Sinha 5, Nishanth Ulhas Nair 5, Joo Sang Lee 6, Alejandro A Schäffer 5, Ze'ev Ronai 7, Dejan Juric 8, Andrea B Apolo 9, William L Dahut 9, Stanley Lipkowitz 10, Raanan Berger 11, Razelle Kurzrock 12, Antonios Papanicolau-Sengos 13, Fatima Karzai 9, Mark R Gilbert 14, Kenneth Aldape 13, Padma S Rajagopal 15, Tuvik Beker 16, Eytan Ruppin 17, Ranit Aharonov 18

Cell Press. 2022.

Full-Text Article

PhenomeXcan: Mapping the genome to the phenome through the transcriptome

Pividori M, Rajagopal PS, Barbeira A, Liang Y, Melia O, Bastarache L, Park Y, Consortium G, Wen X, Im HK.

Sci Adv.. 6(37):: eaba2083, 2020. [ Journal Article ]

Black Lives Matter Worldwide: Retooling Precision Oncology for True Equity of Cancer Care

Rajagopal PS, Olopade OI.

Cell Rep Med.. 25;1(5): 100079, 2020. [ Journal Article ]

Biography

Physician-Scientist Early Investigator

Padma Sheila Rajagopal, M.D., M.P.H., M.Sc.

Dr. Padma Sheila Rajagopal received her M.D. at Columbia University’s College of Physicians and Surgeons, during which she also received an M.P.H. in quantitative methods with a focus on genetic epidemiology at the Harvard School of Public Health. She completed her internal medicine residency training at the University of Pittsburgh and a fellowship in hematology/oncology and additional fellowship year focused on cancer genetics at the University of Chicago, where she received an M.Sc. in biomedical informatics.

Dr. Rajagopal is a recipient of the Ruth L. Kirschstein F32 Postdoctoral Fellowship and the American Society of Clinical Oncology / Breast Cancer Research Foundation Conquer Cancer Young Investigator Award for her research on integrating germline variants through a predicted transcriptome model of the breast and comparing prognostication of outcomes in breast cancer to the tumor transcriptome. She joined the Cancer Data Science Laboratory as an Assistant Clinical Investigator in 2021.