Biology subjects

MAITRA, A.

Publications and source records attributed to MAITRA, A..

5 recordsLinked to original sources

bioRxiv2025

Inhibitors of oncogenic Kras specifically prime CTLA4 blockade to transcriptionally reprogram Tregs and overcome resistance to suppress pancreas cancer

Lack of sustained response to oncogenic Kras (Kras*) inhibition in preclinical models and patients with pancreatic ductal adenocarcinoma (PDAC) emphasizes the need to identify impactful synergistic combination therapies to achieve robust clinical benefit. Kras* targeting results in an influx of T cell infiltrates including Tregs, effector CD8+ T cells and exhausted CD8+ T cells expressing several immune checkpoint molecules in PDAC. Here, we probe whether the T cell influx induced by different Kras* inhibitors enable a therapeutic window to prime adaptive immune response in PDAC. Here we report a specific synergy between KrasG12D allele specific inhibitor, MRTX1133 or multi-selective pan-RAS inhibitor, RMC-6236 and anti-CTLA4 immune checkpoint blockade. In contrast, attempted therapeutic combination with multiple other immune checkpoint inhibitors, including anti-PD1, anti-Tim3, anti-Lag3, anti-Vista and anti-4-1BB agonist antibody failed due to compensatory mechanisms mediated by other checkpoints on exhausted CD8+ T cells. Specifically, anti-CTLA4 therapy in Kras* targeted PDAC transcriptionally reprograms effector T regs to a naive phenotype, reverses CD8+ T cell exhaustion and is associated with recruitment of tertiary lymphoid structures (TLS) containing follicular B cells, interferon (IFN)- stimulated/ activated B cells, plasma cells and germinal center B cells to functionally enable efficacy of immunotherapy with long-term survival. In this regard, inhibition of the TLS with lymphotoxin-{beta} inhibitor (LTBi) or direct B cell depletion reversed the survival benefit conferred by the combination therapy and highlights the function of TLS in generating productive anti-tumor immune responses. Further, single cell ATAC sequencing analysis revealed that transcriptional reprogramming of Tregs is epigenetically regulated by downregulation of AP-1 family of transcription factors including Fos, Fos-b, Jun-b, Jun-d in the IL-35 promoter region. This study reveals an actionable vulnerability in the adaptive immune response in Kras* targeted PDAC with relevant clinical implications.

cancer biology↗

bioRxiv2024

Therapeutic targeting of Syndecan-1 axis overcomes acquired resistance to KRAS-targeted therapy in gastrointestinal cancers

The therapeutic benefit of recently developed mutant KRAS (mKRAS) inhibitors has been limited by the rapid onset of resistance. Here, we aimed to delineate the mechanisms underlying acquired resistance to mKRAS inhibition and identify actionable targets for overcoming this clinical challenge. Previously, we identified Syndecan-1 (SDC1) as a key effector for pancreatic cancer progression whose surface expression is driven by mKRAS. By leveraging both pancreatic and colorectal cancer models, we found that surface SDC1 expression was initially diminished upon mKRAS inhibition, but recovered in tumor cells that bypass mKRAS dependency. Functional studies showed that these tumors depended on SDC1 for survival, further establishing SDC1 as a driver for the acquired resistance to mKRAS inhibition. Mechanistically, we revealed that the YAP1-SDC1 axis was the major driving force for bypassing mKRAS dependency to sustain nutrient salvage machinery and tumor maintenance. Specifically, YAP1 activation mediated the recovery of SDC1 localization on cell surface that sustained macropinocytosis and enhanced the activation of multiple RTKs, promoting resistance to KRAS-targeted therapy. Overall, our study has provided the rationale for targeting the YAP-SDC1 axis to overcome resistance to mKRAS inhibition, thereby revealing new therapeutic opportunities for improving the clinical outcome of patients with KRAS-mutated cancers.

cancer biology↗

bioRxiv2024

TimiGP-Response: the pan-cancer immune landscape associated with response to immunotherapy

Accumulating evidence suggests that the tumor immune microenvironment (TIME) significantly influences the response to immunotherapy, yet this complex relationship remains elusive. To address this issue, we developed TimiGP-Response (TIME Illustration based on Gene Pairing designed for immunotherapy Response), a computational framework leveraging single-cell and bulk transcriptomic data, along with response information, to construct cell-cell interaction networks associated with responders and estimate the role of immune cells in treatment response. This framework was showcased in triple-negative breast cancer treated with immune checkpoint inhibitors targeting the PD-1:PD-L1 interaction, and orthogonally validated with imaging mass cytometry. As a result, we identified CD8+ GZMB+ T cells associated with responders and its interaction with regulatory T cells emerged as a potential feature for selecting patients who may benefit from these therapies. Subsequently, we analyzed 3,410 patients with seven cancer types (melanoma, non-small cell lung cancer, renal cell carcinoma, metastatic urothelial carcinoma, hepatocellular carcinoma, breast cancer, and esophageal cancer) treated with various immunotherapies and combination therapies, as well as several chemo- and targeted therapies as controls. Using TimiGP-Response, we depicted the pan-cancer immune landscape associated with immunotherapy response at different resolutions. At the TIME level, CD8 T cells and CD4 memory T cells were associated with responders, while anti-inflammatory (M2) macrophages and mast cells were linked to non-responders across most cancer types and datasets. Given that T cells are the primary targets of these immunotherapies and our TIME analysis highlights their importance in response to treatment, we portrayed the pan-caner landscape on 40 T cell subtypes. Notably, CD8+ and CD4+ GZMK+ effector memory T cells emerged as crucial across all cancer types and treatments, while IL-17-producing CD8+ T cells were top candidates associated with immunotherapy non-responders. In summary, this study provides a computational method to study the association between TIME and response across the pan-cancer immune landscape, offering resources and insights into immune cell interactions and their impact on treatment efficacy.

bioinformatics↗

bioRxiv2023

Oncogenic KrasG12D specific non-covalent small molecule inhibitor reprograms tumor microenvironment and reverses early precursor lesions and in combination with immunotherapy regresses advanced PDAC in a CD8+ T cells dependent manner

Pancreatic ductal adenocarcinoma (PDAC) is associated with mutations in Kras, a known oncogenic driver of PDAC; and the KRASG12D mutation is present in nearly half of PDAC patients. Recently, a non-covalent small molecule inhibitor (MRTX1133) was identified with specificity to the KrasG12D mutant protein. Here we explore the impact of KrasG12D inhibition by MRTX1133 on advanced PDAC and its influence on the tumor microenvironment. Employing different orthotopic xenograft and syngeneic tumor models, eight different PDXs, and two different autochthonous genetic models, we demonstrate that MRTX1133 reverses early PDAC growth, increases intratumoral CD8+ effector T cells, decreases myeloid infiltration, and reprograms cancer associated fibroblasts. Autochthonous genetic mouse models treated with MRTX1133 leads to regression of both established PanINs and advanced PDAC. Regression of advanced PDAC requires CD8+ T cells and immune checkpoint blockade therapy (iCBT) synergizes with MRTX1133 to eradicate PDAC and prolong overall survival. Mechanistically, inhibition of mutant Kras in advanced PDAC and human patient derived organoids (PDOs) induces Fas expression in cancer cells and facilitates CD8+T cell mediated death. These results demonstrate the efficacy of MRTX1133 in different mouse models of PDAC associated with reprogramming of stromal fibroblasts and a dependency on CD8+ T cell mediated tumor clearance. Collectively, this study provides a rationale for a synergistic combination of MRTX1133 with iCBT in clinical trials.

cancer biology↗

bioRxiv2022

Transcriptomic Profiling of Plasma Extracellular Vesicles Enables Reliable Annotation of the Cancer-specific Transcriptome and Molecular Subtype

Longitudinal monitoring of patients with advanced cancers is crucial to evaluate both disease burden and treatment response. Current liquid biopsy approaches mostly rely on the detection of DNA-based biomarkers. However, plasma RNA analysis can unleash tremendous opportunities for tumor state interrogation and molecular subtyping. Through the application of deep learning algorithms to the deconvolved transcriptomes of RNA within plasma extracellular vesicles (evRNA), we successfully predict consensus molecular subtypes in metastatic colorectal cancer patients. We further demonstrate the ability to monitor changes in transcriptomic subtype under treatment selection pressure and identify molecular pathways in evRNA associated with recurrence. Our approach also identified expressed gene fusions and neoepitopes from evRNA. These results demonstrate the feasibility of transcriptomic-based liquid biopsy platforms for precision oncology approaches, spanning from the longitudinal monitoring of tumor subtype changes to identification of expressed fusions and neoantigens as cancer-specific therapeutic targets, sans the need for tissue-based sampling. Statement of significanceWe have developed an approach to interrogate changes in cancer molecular subtypes and differentially expressed genes, through the analysis and deconvolution of RNA sequencing of plasma EVs. Serial analyses of tumor-encoded transcriptomes in liquid biopsies can enable facile cancer detection and monitor for recurrences and therapy-induced tumor evolution.

cancer biology↗