Sanju Sinha, Ph.D.

Sanju Sinha's Research Focus

Cancer Biology, Aging
Drug Discovery, Machine Learning, Computational Biology, Bioinformatics

Developing cancer preventive therapies using the power of AI.

At the heart of our research is the mission to develop cancer-preventive therapies using the power of artificial intelligence. Our current focus lies in dissecting the role of aging in cancer susceptibility, a crucial factor often overlooked in conventional research. We employ computational tools to analyze multi-omics data to understand the aging-induced alterations in the tissue microenvironment that increase cancer risk. But we don't stop at understanding these changes. We apply this knowledge in designing preventive therapy candidates that specifically target these alterations. Drawing on my experience in machine learning, drug discovery, and precision oncology, our lab is on a quest to reimagine the drug discovery pipeline.

As we aim to push the boundaries of cancer prevention research, we are hiring individuals eager to contribute to this mission at multiple levels including postdoctoral researchers, experienced computational biologists, and, Ph.D. students.

Sanju Sinha's Research Report

My key contributions to the field of computational oncology during my Ph.D. and postdoctoral tenure are outlined below:

DeepTarget: A Computational Tool for Decoding the Mechanism of Action for Cancer Drugs DeepTarget, our innovative computational tool, integrates data from genetic and drug screens to intricately understand the mechanism of action of cancer drugs. It identifies both primary and secondary drug targets, paving the way for a comprehensive understanding of drug function, its optimal indications, and clinical potential.

Revealing the Potential Cancer Risks associated with Genetic Editing Through computational analyses of vast genetic screens, we shed light on the inherent selection potential of specific cancer gene mutations associated with CRISPR-Knockout editing. This work has significantly enhanced our understanding of the risks associated with gene editing.

First Single-cell based Precision Oncology Framework: A Proof-of-concept Our innovative approach to precision oncology utilizes single-cell transcriptomics to predict patient treatment responses and detect resistance. We demonstrated its efficacy using patient-derived primary cells and three recent single-cell clinical cohorts, providing a powerful tool for the next generation of precision oncology approaches.

Why High Tumor Mutation Burden Biomarker of Immunotherapy is only effective for Certain Cancer Types? We unveiled the microenvironment context that can determine if the high-tumor mutation burden (TMB) biomarker will be effective in a certain cancer type - High M1 Macrophage levels and Low Resting Dendritic Cells. Based on this, we also predicted the rare tumor types with High-TMB where immunotherapy is most likely to be successful.

Uncovering Therapeutic Prospects for African Americans: A Step Forward in Inclusive Cancer Research Our work revealed distinct biological differences in tumors across African American and European American patients. Most notably, we identified a higher prevalence of homologous recombination deficiency in African American patients, pointing towards promising, personalized treatment options.

Sanju Sinha's Bio

Dr. Sanju Sinha earned his Bachelor of Technology in Bioengineering at the Indian Institute of Technology in Guwahati, India. He recently completed his postdoctoral research and Ph.D. in computational biology at the National Cancer Institute (NCI) with Dr. Eytan Ruppin with a co-mentorship of Dr. Brid Ryan during his Ph.D. His Ph.D. was earned in a joint University of Maryland and NCI program.

"At the core of my work is the desire to make a lasting impact on patient's lives, offering patients not just better treatment, but an opportunity to avoid the disease altogether. Sanford Burnham Prebys is renowned for its work in understanding aging and developing new drugs—two areas that are key to my research. This makes it the perfect place for what I'm hoping to achieve."



2021: Ph.D., Computational Biology, University of Maryland and National Cancer Institute
2016: B.Tech., Bioengineering, Indian Institute of Technology, Guwahat


Honors and Recognition

2023: Top Five Outstanding NCI Postdoctoral Fellow 
2023: Transition to Industry Fellowship 
2021: Emerging Leaders of Computational Oncology by MSKCC. 
2020: NCI Outstanding Ph.D. award
2020: NCI CCR milestone 
2019: NCI Fellows Award for Research Excellence 

scientist at work


Higher prevalence of homologous recombination deficiency in tumors from African Americans versus European Americans.

Sinha S, Mitchell KA, Zingone A, Bowman E, Sinha N, Schäffer AA, Lee JS, Ruppin E, Ryan BM

Nat Cancer 2020 Jan ;1(1):112-121

A systematic genome-wide mapping of oncogenic mutation selection during CRISPR-Cas9 genome editing.

Sinha S, Barbosa K, Cheng K, Leiserson MDM, Jain P, Deshpande A, Wilson DM 3rd, Ryan BM, Luo J, Ronai ZA, Lee JS, Deshpande AJ, Ruppin E

Nat Commun 2021 Nov 11 ;12(1):6512

Big data in basic and translational cancer research.

Jiang P, Sinha S, Aldape K, Hannenhalli S, Sahinalp C, Ruppin E

Nat Rev Cancer 2022 Nov ;22(11):625-639

Show All Select Publications

PERCEPTION predicts patient response and resistance to treatment using single-cell transcriptomics of their tumors.

Sinha S, Vegesna R, Mukherjee S, Kammula AV, Dhruba SR, Wu W, Kerr DL, Nair NU, Jones MG, Yosef N, Stroganov OV, Grishagin I, Aldape KD, Blakely CM, Jiang P, Thomas CJ, Benes CH, Bivona TG, Schäffer AA, Ruppin E

Nat Cancer 2024 Apr 18 ;

Pan-Cancer Analysis of Patient Tumor Single-Cell Transcriptomes Identifies Promising Selective and Safe Chimeric Antigen Receptor Targets in Head and Neck Cancer.

Madan S, Sinha S, Chang T, Gutkind JS, Cohen EEW, Schäffer AA, Ruppin E

Cancers (Basel) 2023 Oct 8 ;15(19)

Prediction of cancer treatment response from histopathology images through imputed transcriptomics.

Hoang DT, Dinstag G, Hermida LC, Ben-Zvi DS, Elis E, Caley K, Sammut SJ, Sinha S, Sinha N, Dampier CH, Stossel C, Patil T, Rajan A, Lassoued W, Strauss J, Bailey S, Allen C, Redman J, Beker T, Jiang P, Golan T, Wilkinson S, Sowalsky AG, Pine SR, Caldas C, Gulley JL, Aldape K, Aharonov R, Stone EA, Ruppin E

Res Sq 2023 Sep 15 ;

The GPCR-Gα(s)-PKA signaling axis promotes T cell dysfunction and cancer immunotherapy failure.

Wu VH, Yung BS, Faraji F, Saddawi-Konefka R, Wang Z, Wenzel AT, Song MJ, Pagadala MS, Clubb LM, Chiou J, Sinha S, Matic M, Raimondi F, Hoang TS, Berdeaux R, Vignali DAA, Iglesias-Bartolome R, Carter H, Ruppin E, Mesirov JP, Gutkind JS

Nat Immunol 2023 Aug ;24(8):1318-1330

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

Dinstag G, Shulman ED, Elis E, Ben-Zvi DS, Tirosh O, Maimon E, Meilijson I, Elalouf E, Temkin B, Vitkovsky P, Schiff E, Hoang DT, Sinha S, Nair NU, Lee JS, Schäffer AA, Ronai Z, Juric D, Apolo AB, Dahut WL, Lipkowitz S, Berger R, Kurzrock R, Papanicolau-Sengos A, Karzai F, Gilbert MR, Aldape K, Rajagopal PS, Beker T, Ruppin E, Aharonov R

Med 2023 Jan 13 ;4(1):15-30.e8

Sex Biases in Cancer and Autoimmune Disease Incidence Are Strongly Positively Correlated with Mitochondrial Gene Expression across Human Tissues.

Crawford DR, Sinha S, Nair NU, Ryan BM, Barnholtz-Sloan JS, Mount SM, Erez A, Aldape K, Castle PE, Rajagopal PS, Day CP, Schäffer AA, Ruppin E

Cancers (Basel) 2022 Nov 29 ;14(23)

Show All Publications