Biology subjects

Sangurdekar, D.

Publications and source records attributed to Sangurdekar, D..

3 recordsLinked to original sources

bioRxiv2026

Tumor reactivity assessment using clonal expression (TRACE) reveals tumor reactive CD8+ T cell heterogeneity across solid tumors

1IntroductionTumor infiltrating lymphocytes (TIL) drive the anti-tumor activity of a broad class of immunotherapies. In situ TIL are composed of T cells that recognize tumor antigens (Tumor Reactive T cells, or TRTs) as well as bystander T cells with specificity for other antigens. TRT clonotypes are associated with a unique and tumor-driven exhausted transcriptional state, enabling single-cell RNA sequencing (scRNA-seq)-based predictive models for TRTs using experimentally validated clone labels. MethodsIn this study, a clonotype-level CD8+ TRT classifier (TRACE) was built using an aggregated dataset of validated tumor reactive clonotypes and associated scRNA-seq data from multiple publications that overcomes the limitations of training on a single dataset, donor, or indication. TRACE does not require dataset manipulation for training or prediction, enabling it to be easily applied to new test datasets as they emerge. ResultsTRACE exhibited robust performance on held-out TIL and PBMC clones - achieving a mean Matthews correlation coefficient of 0.84 and F1-score of 0.85 - comparable to or outperforming other TRT prediction methods. We experimentally confirmed the reactivity of TRACE-identified TRT clones by co-culturing engineered, ex vivo expanded TIL with autologous melanoma tumor cell lines. Finally, we applied TRACE to evaluate the frequency of TRT across hundreds of patient samples from multiple tumor atlases spanning lung, colorectal, and pancreatic cancer. TRACE scores were observed to be significantly higher in exhausted CD8 T cells in tumors but not in exhausted cells in normal adjacent or non-cancer samples, suggesting specificity towards identifying tumor-antigen experienced T cells. ConclusionTRACE is a tumor reactivity scoring algorithm released with open model weights that can be applied to tissue or blood single-cell RNAseq datasets. Its application should be of general interest for characterizing the fraction of TRTs in TIL and for establishing correlations with clinical response to immunotherapies.

immunology↗

bioRxiv2026

Dual-inactivation of Regnase-1 and SOCS1 rewires exhausted CD8+ T cell fate to enhance anti-tumor functionality

The solid tumor microenvironment inhibits the functionality of tumor infiltrating T cells recognizing cognate tumor antigen, driving their differentiation towards terminal exhaustion. Interventions are sought to enhance the anti-tumor functionality of tumor-reactive T cells for clinical benefit. The functional genome regulating CD8+ T cell function against solid tumors was mapped by performing genome-wide, focused, and combination in vivo CRISPR/Cas9 screens using OT1 and PMEL TCR transgenic T cells in B16-OVA, MC38-gp100 and EG7-OVA syngeneic tumor models. The ability of the top single hits and combinations, which include Regnase-1 and SOCS1, to enhance CD8+ T cell anti-tumor function was evaluated in the OT1/B16-OVA model with large and established tumors, the disseminated PMEL/B16F10 tumor model, and in a novel murine TIL syngeneic model. The impact of Regnase-1 and SOCS1 single and dual-inactivation on the differentiation of exhausted CD8+ T cell subsets and on long-term persistent memory following tumor clearance was evaluated in OT1 CD8+ T cells in the B16-OVA model. The impact of single and dual-inactivation of Regnase-1 and SOCS1 on the anti-tumor function of experimental human T cell therapeutics was characterized in CRISPR/Cas9-engineered human TIL derived in vitro and in mesothelin-targeting CAR-Ts in vivo. NF-{kappa}B and cytokine signaling were identified as the top pathways regulating CD8+ T cell anti-tumor function, with Regnase-1 and Suppressor of Cytokine Signaling 1 (SOCS1) the top single and combination edits regulating the accumulation of tumor-specific TCR transgenic CD8+ T cells in syngeneic tumor models. Dual-inactivation of Regnase-1 and SOCS1 cooperated through non-redundant mechanisms to strongly expand intermediate (Texint) and effector (Texeff) exhausted CD8+ T cells within lymphoid tissues and tumor, with CD8+ T cells rewired to display an enhanced effector state and suppressed expression of TOX. Dual-edited persistent T effector memory cells (Tem) were formed following tumor clearance. Lastly, Regnase-1 and SOCS1 inactivation enhanced human Tumor Infiltrating Lymphocyte (TIL) and chimeric antigen receptor T cells (CAR-T) therapy functionality. Collectively, this study systematically mapped pathways regulating CD8+ T cell anti-tumor functionality, with Regnase-1 and SOCS1 dual-inactivation found to maximize anti-tumor function through non-redundant mechanisms.

immunology↗

bioRxiv2024

Pan-cancer Analysis of Homologous Recombination Deficiency in Cell Lines

Homologous Recombination Deficiency (HRD) drives genomic instability in multiple cancer types and renders tumors vulnerable to certain DNA damaging agents such as PARP inhibitors. Thus, HRD is emerging as an attractive biomarker in oncology. A variety of in silico methods are available for predicting HRD; however, few of these methods have been applied to cell lines in a comprehensive manner. Here we utilized two of these methods, "CHORD" and "HRDsum" scores, to predict HRD for 1,332 cancer cell lines and 84 non-cancerous cell lines. Cell lines with biallelic mutations in BRCA1 or BRCA2, which encode key components of the homologous recombination pathway, showed the strongest HRD predictions, validating the two methods in cell lines. A small subset of BRCA1/2-wildtype cell lines were also classified as HRD, several of which showed evidence of epigenetic BRCA1 silencing. Similar to HRD in patient samples, HRD in cell lines was associated with p53 loss, was mutually exclusive with microsatellite instability and occurred most frequently in breast and ovarian cancer types. In addition to validating previously identified associations with HRD, we leveraged cell line-specific datasets to gain new insights into HRD and its relation to various genetic dependency and drug sensitivity profiles. We found that in cell lines, HRD was associated with sensitivity to PARP inhibition in breast cancer, but not at a pan-cancer level. By generating large-scale, pan-cancer datasets on HRD predictions in cell lines, we aim to facilitate efforts to improve our understanding of HRD and its utility as a biomarker. SIGNIFICANCE STATEMENTHomologous Recombination Deficiency (HRD) is common in cancer and can be exploited therapeutically, as it sensitizes cells to DNA damaging agents. Here we scored over 1,300 cancer cell lines for HRD using two different bioinformatic approaches, thereby enabling large-scale analyses that provide insight into the etiology and features of HRD.

cancer biology↗