About

Ansuman Satpathy is an Assistant Professor of Pathology at Stanford University, affiliated with the Center for Artificial Intelligence in Medicine & Imaging (AIMI). His research focuses on the application of artificial intelligence in medicine and imaging, contributing to advancements in healthcare through innovative AI-driven solutions. As a faculty member at Stanford, he is involved in various educational and research initiatives aimed at integrating AI technologies into medical practice, fostering collaboration between academia and industry to improve diagnostic and therapeutic processes.

Research topics

• Immunology
• Biology
• Cancer research
• Medicine
• Genetics
• Cell biology
• Internal medicine
• Pathology
• Bioinformatics
• Computer Science
• Virology
• Microbiology
• Computational biology
• Neuroscience

Selected publications

• FAK Inhibition Remodels the Metastatic ECM and Restores CD8⁺ T Cell Trafficking and Immunosurveillance

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-01-23

  article

  ABSTRACT Metastatic breast cancer remains largely incurable, driven in part by immunosuppressive microenvironments that limit CD8 + T cell-mediated clearance. Using a murine pulmonary metastatic breast cancer model, we show that the focal adhesion kinase (FAK) inhibitor VS-4718 promotes a CD8 + T cell-dependent regression of metastatic lesions by reprograming the metastatic microenvironment. VS-4718 reduced immunosuppressive myeloid and regulatory T cells while increasing CD8 + T cell infiltration. Cellular and secreted proteome profiling revealed that VS-4718 downregulates ECM components such as laminin α5 and collagen VIIIα1, which we show impair CD8 + T cell migration and activity. In human breast cancer cohorts, elevated LAMA5/COL8A1 expression and a FAK-dependent ECM signature associate with poor outcome and prognostic for residual disease. Intravital imaging demonstrated that VS-4718 enhances CD8⁺ T cell extravasation and induces T cell-tumor cell contacts necessary for cytotoxicity. Ex vivo lung slice cultures recapitulated these findings, showing enhanced T cell swarming, metastatic cluster shrinkage, and apoptosis. These findings reveal how FAK inhibition remodels the metastatic ECM to potentiate coordinated CD8 + T cell responses. VS-4718 might aid in clearing metastases in breast cancer patients through modulating both stromal and immune components. STATEMENT OF SIGNIFICANCE Focal adhesion kinase (FAK) inhibition remodels collagen- and laminin-rich extracellular matrix barriers and alleviates physical constraints that limit CD8⁺ T cell access and activity in metastases. This enhances infiltration, migration, and tumor cell engagement, and synergizes with PD-1 blockade, supporting combined therapeutic strategies in metastatic breast cancer.

  PublisherDOI

• Systematic identification of seed-driven off-target effects in Perturb-seq experiments

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-03-28 · 1 citations

  articleOpen access

  Abstract Genome-wide Perturb-seq (GWPS) has emerged as a powerful approach for unbiased mapping of gene regulatory networks. A key assumption underlying many Perturb-seq analyses is that each guide RNA exclusively perturbs a single target locus. Without methods to identify and filter off-target events, erroneous gene-pathway associations driven by off-target activity can propagate into downstream analyses. Here, we present a workflow for the systematic identification of candidate off-target events in CRISPRi Perturb-seq experiments. Our approach exploits the observation that cells harboring a guide which represses an off-target gene display transcriptional similarity to cells in which that gene is directly targeted by an on-target guide. We apply our workflow to multiple GWPS datasets and nominate off-target events in which a guide nominally targeting one gene also represses a distinct gene producing a phenotype likely attributable to the off-target perturbation. We use both off-target gene repression and guide seed sequence alignments at the off-target promoter locus as evidence for off-target effects and find independent evidence of putative off-target events in separate GWPS datasets. Together, these results establish a principled framework for the identification and filtering of off-target guide effects in Perturb-seq experiments.

  PublisherDOI

• Molecular pixelation of the CAR T cell surface proteome

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-02-02

  articleOpen access

  Immunotherapies using CAR T cells are revolutionizing B-cell acute lymphoblastic leukemia treatments. However, the majority of patients remain unresponsive, and chronic stimulation of T cells is a common contributor that reduces effector function and persistence. We apply Molecular Pixelation, a recently developed single-cell technology for characterizing cellular surface proteomes, to determine characteristic topological surface-based proteomic signatures of CAR T cell exhaustion. We analyze 76 surface proteins on 8504 CAR T cells at a single-cell level, collected from three donors and either stimulated once or repeatedly, six times over two weeks. The abundances, polarizations, and colocalizations of surface proteins can each distinguish CAR T cells that were stimulated acutely or chronically, and all but one marker with polarization changes increased in polarization. These data also reveal disrupted adhesion signatures of protein colocalization in the peripheral supramolecular activation complex (pSMAC) and increased CD37/CD82 colocalization after chronic stimulation. These Molecular Pixelation results convey new spatial signatures for proteomic polarization and colocalization on the cell surface that represent new cell-state axes for immunology and systems biology.

  PublisherOA PDFDOI

• Comparing bulk and single-cell methodologies and models to profile gene expression, chromatin accessibility and regulatory links in endothelial cells treated with TNFα

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-03-16

  articleOpen access

  ABSTRACT Genome-wide association studies (GWAS) have identified thousands of non-coding variants associated with complex traits and diseases. However, it remains challenging to pinpoint the causal genes that are regulated by associated genetic variants. Connecting causal non-coding variants with genes can rely on methods that identify direct physical interactions (e.g. chromosome conformation capture) or on probabilistic models that predict regulatory links. These statistical models take advantage of gene expression and chromatin accessibility profiles generated in cells and tissues by bulk or single-cell (sc) methodologies. Here, we tested whether using bulk or sc RNAseq/ATACseq data and corresponding predictive enhancer-to-gene models impact the prioritization of causal GWAS genes. Using non-treated and TNFα-treated human endothelial cells in vitro as a well-controlled experimental system, we show that bulk and sc RNAseq/ATACseq profiles are similar and highlight the same biology (e.g. biological pathways). Despite these similarities, we show using GWAS results for coronary artery disease (CAD) and diastolic blood pressure that applying enhancer-to-gene models designed for bulk or sc methodologies can yield differences in terms of captured heritability, fine-mapped variants and linked genes. For instance, at one CAD locus, the bulk-based ABC model predicts a regulatory link with BCAR1 , whereas the sc-based model scE2G prioritizes a different gene ( CFDP1 ). On the same experimental model, our results indicate that choosing between a bulk or sc approach will influence regulatory link model predictions; this should be considered when planning functional experiments to characterize GWAS discoveries.

  PublisherOA PDFDOI

• In vivo site-specific engineering to reprogram T cells

  Nature · 2026-03-18 · 9 citations

  articleOpen access

  Abstract Engineered T cells, reprogrammed to express chimeric antigen receptors (CAR) or T cell receptors (TCR), have transformed cancer treatment and are being explored as therapeutics for autoimmune and infectious diseases. Enhancing T cell function through genome editing, either by disrupting endogenous genes or precisely inserting DNA payloads, has shown considerable promise 1 . However, the ex vivo manufacturing process is lengthy and costly, limiting accessibility of these therapies. In vivo generation of CAR T cells could overcome these barriers, but current methods rely either on transient expression with limited durability, or on random integration of DNA payloads that lack specificity. Here we demonstrate that stable and cell-specific transgene expression can be achieved through in vivo site-specific integration of large DNA payloads. We developed a two-vector system to deliver CRISPR–Cas9 ribonucleoproteins and a DNA donor template, using enveloped delivery vehicles and adeno-associated viruses, respectively. We optimized both vectors for T cell-specific delivery and gene-targeting efficiency. By integrating a CAR transgene into a T cell-specific locus, we generate therapeutic levels of CAR T cells in vivo in humanized mouse models of B cell aplasia, and haematological and solid malignancies. These findings offer a pathway to more efficient, precise and widely accessible T cell therapies.

  PublisherDOI

• Abstract 5205: Assessing donor heterogeneity in CAR-T cells with massively parallel mixed lymphocyte reactions

  Cancer Research · 2026-04-03

  article

  Abstract Donor heterogeneity is a major source of variation in CAR-T cell functions which leads to inconsistencies in both clinical efficacy and pre-clinical studies to enhance CAR-T cell functions. However, assessing T cell donor heterogeneity with a large sample size is costly and time-consuming. Here, we developed a Massively Parallel - Mixed Lymphocytes Reaction (MP-MLR) assay that allows pooling and simultaneously testing of CAR-T cells from multiple human donors. Combining with pooled genetic perturbation technologies, we conducted pooled screening in more than 50 T cell donors for enhanced CAR-T cell proliferation under repetitive tumor stimulations, with a library of candidate genetic perturbations proposed to enhance CAR-T or T cell functions. While we identified genetic perturbations with consistent effect on CAR-T cells across donors, the majority of perturbations showed various levels of donor dependencies, and this observation was confirmed with arrayed validation of selected perturbations on specific donors. Furthermore, we performed multi-parameters pooled screening in-vitro and in-vivo for systematic discovery of generalizable and donor specific genetic perturbations enhancing CAR-T cell pre-clinical therapeutic efficacies. Overall, we presented an efficient and cost-effective strategy for assessing donor variabilities in CAR-T cells, predicting patient specific effects of genetic perturbations on CAR-T cells efficacies, and potentially identifying of personalized optimal genetic perturbation for enhancing CAR-T cell functions. Citation Format: Lujing Wu, Lina Mohamad, Michelle Mantilla, Johnathan Lu, Ansuman T. Satpathy, Theodore Roth. Assessing donor heterogeneity in CAR-T cells with massively parallel mixed lymphocyte reactions [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 5205.

  PublisherDOI

• A unified genetic perturbation language for human cellular programming

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-11-20 · 4 citations

  preprintOpen access

  Evolution simultaneously and combinatorially explores complex genetic changes across perturbation classes, including gene knockouts, knockdowns, overexpression, and the creation of new genes from existing domains. Separate technologies are capable of genetic perturbations at scale in human cells, but these methods are largely mutually incompatible. Here we present CRISPR-All, a unified genetic perturbation language for programming of any major type of genetic perturbation simultaneously, in any combination, at genome scale, in primary human cells. This is enabled by a standardized molecular architecture for each major perturbation class, development of a functional syntax for combining arbitrary numbers of elements across classes, and linkage to unique single cell compatible barcodes. To facilitate use, CRISPR-All converts high level descriptions of desired complex genetic changes into a single DNA sequence that can rewire genomic programs within a cell. Using the CRISPR-All language allowed for head-to-head functional comparisons across perturbation types in a comprehensive analysis of all previously identified genetic enhancements of human CAR-T cells. Combining CRISPR-All programs with single cell RNA sequencing revealed a greater diversity of phenotypic states, including improved functional performance, only accessible through distinct perturbation classes. Finally, CRISPR-All combinatorial genome scale screening of up to four distinct perturbations simultaneously revealed additive functional improvements in human T cells accessible only through iterative multiplexing of modifications across perturbation classes. CRISPR-All enables exploration of a combinatorial genetic perturbation space, which may be impactful for biological and clinical applications.

  PublisherOA PDFDOI

• Translation dysregulation in cancer as a source for targetable antigens

  Cancer Cell · 2025-03-29 · 20 citations

  articleOpen access

  Aberrant peptides presented by major histocompatibility complex (MHC) molecules are targets for tumor eradication, as these peptides can be recognized as foreign by T cells. Protein synthesis in malignant cells is dysregulated, which may result in the generation and presentation of aberrant peptides that can be exploited for T cell-based therapies. To investigate the role of translational dysregulation in immunological tumor control, we disrupt translation fidelity by deleting tRNA wybutosine (yW)-synthesizing protein 2 (TYW2) in tumor cells and characterize the downstream impact on translation fidelity and immunogenicity using immunopeptidomics, genomics, and functional assays. These analyses reveal that TYW2 knockout (KO) cells generate immunogenic out-of-frame peptides. Furthermore, Tyw2 loss increases tumor immunogenicity and leads to anti-programmed cell death 1 (PD-1) checkpoint blockade sensitivity in vivo. Importantly, reduced TYW2 expression is associated with increased response to checkpoint blockade in patients. Together, we demonstrate that defects in translation fidelity drive tumor immunogenicity and may be leveraged for cancer immunotherapy.

  PublisherDOI

• Erythropoietin receptor on cDC1s dictates immune tolerance

  Nature · 2025-12-10 · 8 citations

  articleOpen access
  PublisherOA PDFDOI

• Engineering T cells with a membrane-tethered version of SLP-76 overcomes antigen-low resistance to CAR T cell therapy

  Nature Cancer · 2025-10-23 · 2 citations

  articleOpen access

  Chimeric antigen receptor (CAR) T cells can mediate durable complete responses in individuals with certain hematologic malignancies, but antigen downregulation is a common mechanism of resistance. Although the native T cell receptor can respond to very low levels of antigen, engineered CARs cannot, likely due to inefficient recruitment of downstream proximal signaling molecules. We developed a platform that endows CAR T cells with the ability to kill antigen-low cancer cells consisting of a membrane-tethered version of the cytosolic signaling adaptor molecule SLP-76 (MT-SLP-76). MT-SLP-76 can be expressed alongside any CAR to lower its activation threshold, overcoming antigen-low escape in multiple xenograft models. Mechanistically, MT-SLP-76 amplifies CAR signaling through recruitment of ITK and PLCγ1. MT-SLP-76 was designed based on biologic principles to render CAR T cell therapies less susceptible to antigen downregulation and is poised for clinical development to overcome this common mechanism of resistance.

  PublisherOA PDFDOI

Recent grants

• Single cell epigenomics in cancer immunity and immunotherapy

  NIH · $448k · 2018–2023

Frequent coauthors

• Howard Y. Chang

  Stanford University

  172 shared

• Alexander Marson

  University of California, San Francisco

  97 shared

• Caleb A. Lareau

  Memorial Sloan Kettering Cancer Center

  93 shared

• Bence Dániel

  Stanford University

  83 shared

• Julia A. Belk

  Stanford University

  83 shared

• Jennifer A. Doudna

  University of California, Berkeley

  80 shared

• Katalin Sándor

  Gladstone Institutes

  74 shared

• Kevin R. Parker

  Stanford University

  62 shared

Education

• Ph.D., Pathology

  Stanford University

  2010

• M.D., Medicine

  All India Institute of Medical Sciences (AIIMS)

  2005

• B.S., Biochemistry

  University of Delhi

  2001