2024 Recipient — Nidhi Sahni, PhD

Nidhi Sahni, PhD

AI-guided single-cell transfer learning model to predict precision medicine in ovarian cancer

Project Summary

Ovarian cancer patients are often diagnosed at advanced stage and develop resistance to standard-of-care therapy. Recent studies have produced clinical drug predictions by machine learning. Insufficient patient numbers and lack of knowledge of drug targets limit their use. Our goal is to accelerate the discovery of innovative, actionable therapies through integrative network-based AI models in an individualized manner. Specifically, we will first develop and optimize multiomics-based biomarkers to predict clinical outcomes to standard of care therapies. For most of the non-responders to conventional treatment, we will then establish and validate a novel AI framework to identify actionable drugs for personalized therapy by “transfer learning” using integrated single cell data. By AI-guided transfer learning, we aim to contextualize ovarian cancer patients’ tumor cells to best match cell lines with known susceptibility to drugs and drug combinations. We will further integrate clinical features with multi-omics data to predict new treatment options for ovarian cancer patients by AI. Taken together, this proposal develops systems-level network-based AI models to prioritize personalized therapies based on tumor compositions at various resolution levels. This collaborative team work is only made possible due to availability of comprehensive clinical data across diverse populations of ovarian cancer patients from the Ovarian Cancer Moon Shot program at MD Anderson Cancer Center.


Dr. Nidhi Sahni is an Assistant Professor in the Department of Epigenetics and Molecular Carcinogenesis at The University of Texas MD Anderson Cancer Center. She is also a faculty member of the Department of Bioinformatics and Computational Biology at MD Anderson, and an affiliated faculty member at Baylor College of Medicine. Dr. Sahni has received several prestigious academic awards, including Sloan Scholar, CPRIT Scholar, Rising STARs Award, Pinnacle Research Award, among others. She received a PhD degree in Biology from the University of Iowa, and then completed her postdoctoral fellowship at Dana-Farber Cancer Institute and Harvard Medical School. During her postdoc training Dr. Sahni worked with Dr. Marc Vidal and Dr. Susan Lindquist, and developed a keen interest in cancer systems biology and precision medicine. Dr. Sahni’s laboratory seeks a systems-level understanding of the underlying genetic and epigenetic aberrations in cancer heterogeneity and progression. She aims to identify novel biomarkers and drug targets, and to have a major impact on cancer by translating into more effective prognosis and therapy for human cancer. Her current focus is to identify PARP-based novel combination therapy in ovarian cancer using a novel systems biology approach.