Biology subjects

Puram, S. V.

Publications and source records attributed to Puram, S. V..

11 recordsLinked to original sources

bioRxiv2026

High-avidity TCR signaling induces a distinct KLR-positive exhaustion state in human tumor-infiltrating CD8 T cells associated with immunotherapy response

T cells adopt diverse states in human disease, with tumor-specific CD8 T cells serving as the quintessential example. These cells are critical for immunotherapy response, yet acquire hypofunctional states of exhaustion that impair treatment efficacy. While significant heterogeneity is observed among exhausted CD8 T cells (TEX), the mechanisms directing their unique phenotypes remain unresolved, limiting our efforts to augment TEX cell function. Here, we profile TEX cells in human head and neck squamous cell carcinoma (HNSCC) tumors and define a major mechanism regulating their cell state. With single-cell RNA and T cell receptor (TCR) sequencing of 106,667 tumor-infiltrating CD8 T cells, we define and validate three fundamental TEX subsets, each harboring dominant clonotypes: a progenitor subset (TPEX) and two intra-tumoral populations marked by intermediate (TEX-int) or high expression of inhibitory receptors, including killer cell lectin-like receptors, such as KLRC1/NKG2A (TEX-KLR). Using an in vitro model, we show that TCR avidity-dependent NFAT signaling governs an axis between the TEX-int and TEX-KLR states across human cancers, with high-avidity signaling driving the TEX-KLR state. Additionally, we uncover that interleukin-12 signaling selectively antagonizes high-avidity TEX-KLR-specific genes, despite broadly potentiating activation and cytotoxicity. Finally, we find that TEX-int and TEX-KLR cells are associated with anti-PD-1 response in HNSCC, with both of these cell types enriched near viable cancer cells following treatment. Together, these findings reveal that TCR avidity orchestrates tumor-infiltrating TEX cell states through NFAT signaling, a tunable axis that may be targeted to improve TEX cell function.

immunology↗

bioRxiv2026

Isoform-specific cofactor recruitment through the intrinsically disordered N-terminus of p63 underlies differential transcriptional activities

The transcription factor p63 is critical for epithelial development and implicated in tumorigenesis. However, our understanding of the role of p63 in development and disease has been complicated by its diverse isoforms. As a member of the p53 family member of genes, TP63 encodes for numerous isoforms, including the N-terminal variants TAp63 and {Delta}Np63, which are generated through alternative promoter usage. TAp63 and {Delta}Np63 share various structural domains, including the DNA-binding domain, and primarily differ in their N-terminus which consists of intrinsically disordered regions (IDRs). The isoforms are known to have different functions, including tumor suppression in the case of TAp63 and pro-tumor formation for {Delta}Np63, but how the N-terminus contributes to isoform-specific gene regulatory effects has yet to be elucidated. Using both genomic and TurboID proximity-labeling proteomic approaches, we show that the N-terminus mediates differential interactions with cofactors that have direct effects on isoform function, specifically the regulation of apoptosis. We find that the N-terminus of TAp63 interacts with more transcriptional machinery, leading to stronger transcriptional activity by TAp63 than {Delta}Np63. However, {Delta}Np63 maintains interactions with coactivators, suggesting it can retain some transactivation capabilities. Strikingly, the N-terminus of TAp63 displays enriched interactions with chromatin modifiers, including the histone acetyltransferase KAT2A, that result in TAp63-specific binding at inaccessible sites. We find that an IDR-mediated interaction with KAT2A is involved in regulation of apoptosis by TAp63. Collectively, our results suggest a model in which TAp63 and {Delta}Np63 broadly share genomic occupancy, but differential interactions with cofactors contribute to isoform-specific regulation by TAp63 and {Delta}Np63.

molecular biology↗

bioRxiv2025

Scalable transcription factor mapping uncovers the regulatory dynamics of natural and synthetic transcription factors in human T cell states

Heterogeneous T cell states are critical in immune responses and have been explored by CRISPR-based and synthetic domain-swapped transcription factor (TF) screens, yielding novel insights and immunotherapeutics. However, a scalable strategy to map TFs in primary human T cells is lacking, which limits our understanding of the functions of critical TFs. We therefore adapted a transposon-based TF mapping strategy termed Calling Cards for primary human CD8 T cells, applying it to five key TFs with undefined binding sites in this cell type: TOX, TOX2, TCF7, SOX4, and RBPJ. To derive biological insights from these data, we developed an analytical framework to integrate TF binding with multi-omic sequencing data, revealing convergence of TOX and TCF7 binding at dynamic enhancers of memory CD8 T cells. We then identified TF co-bound gene programs related to memory and exhaustion states in addition to putative gene targets of known and unappreciated TF roles, including TOX binding at critical genes of both exhaustion and terminal effector memory differentiation. To further scale our TF analysis platform, we modified Calling Cards to create TFlex: a method uniquely suited for multiplexed mapping of paralogous TFs. We applied TFlex to simultaneously map eight natural and domain-swapped TFs in primary human CD8 T cells, which demonstrated that domain-swapped TFs display emergent behavior in binding site selection and transcriptional effects on target genes that cannot be estimated as the sum of their constituent domains. Collectively, our data highlight the importance of scalable TF mapping in primary human T cells to elucidate TF function and the transcriptional regulation of cell states.

immunology↗

bioRxiv2025

Single-cell transcriptomic analysis of HPV-related multiphenotypic sinonasal carcinoma uncovers MYB-HPV association

Human papillomavirus (HPV)-related multiphenotypic sinonasal carcinoma (HMSC) is a rare tumor that morphologically resembles high grade adenoid cystic carcinoma (ACC), yet exhibits indolent clinical behavior. Both demonstrate MYB proto-oncogene upregulation, but HMSC lacks the MYB translocation typically seen in ACC. Transcriptional changes in HMSC tumors remain uncharacterized. We performed single-cell RNA sequencing (scRNA-seq) on a human HMSC tumor and compared expression profiles with published ACC and oropharyngeal squamous cell carcinoma (OPSCC) scRNA-seq datasets. Primary malignant cells from HMSC (n=134) and ACC (n=980) clustered separately, and HMSC lacked bicellular differentiation into luminal and myoepithelial cells, distinguishing it from ACC. A greater proportion of HMSC cells expressing HPV-related genes (HPVon) expressed MYB (83% vs. 62%, p=0.022) and MYB targets (p=6.4*10-6), suggesting an HPV-MYB association. This finding was validated in HPV-positive OPSCC, with 7/10 tumors showing MYB upregulation in HPVon versus HPVoff cells (p<0.05). A 264-gene signature from HPVon HMSC cells was also associated with worse prognosis in HPV+ OPSCC (p<0.003), suggesting an alternate role for HPV that has not been well characterized. Further validation of the HPV-MYB association and prognostically relevant HPV gene signature may improve patient stratification and therapeutic strategies in HPV-related malignancies.

cancer biology↗

bioRxiv2024

The Curated Cancer Cell Atlas: comprehensive characterisation of tumours at single-cell resolution

Single-cell RNA-seq (scRNA-seq) has transformed the study of cancer biology. Recent years have seen a rapid expansion in the number of single-cell cancer studies, yet most of these studies profiled few tumours, such that individual datasets have limited statistical power. Combining the data and results across studies holds great promise but also involves various challenges. We recently began to address these challenges by curating a large collection of cancer scRNA-seq datasets, and leveraging it for systematic analyses of tumor heterogeneity. Here we significantly extend this repository to 124 datasets for over 40 cancer types, together comprising 2,822 samples, with improved data annotations, visualisations and exploration. Utilising this vast cohort, we systematically quantified context-dependent gene expression and proliferation patterns across cell types and cancer types. These data, annotations and analysis results are all freely available for exploration and download via the Curated Cancer Cell Atlas (3CA) website (https://www.weizmann.ac.il/sites/3CA/), a central source of data and analyses for the cancer research community that opens new avenues in cancer research.

cancer biology↗

bioRxiv2023

Targeted proteomic quantitation of NRF2 signaling and predictive biomarkers in HNSCC

The NFE2L2/NRF2 oncogene and transcription factor drives a gene expression program that promotes cancer progression, metabolic reprogramming, immune evasion and chemoradiation resistance. Patient stratification by NRF2 activity may guide treatment decisions to improve outcome. Here, we developed a mass spectrometry (MS)-based targeted proteomics assay based on internal standard triggered parallel reaction monitoring (IS-PRM) to quantify 69 NRF2 pathway components and targets as well as 21 proteins of broad clinical significance in head and neck squamous cell carcinoma (HNSCC). We improved the existing IS-PRM acquisition algorithm, called SureQuant, to increase throughput, sensitivity, and precision. Testing the optimized platform on 27 lung and upper aerodigestive cancer cell models revealed 35 NRF2 responsive proteins. In formalin-fixed paraffin-embedded (FFPE) HNSCCs, NRF2 signaling intensity positively correlated with NRF2 activating mutations and with SOX2 protein expression. PD-L2/CD273 and protein markers of T-cell infiltration correlated positively with one another and with human papilloma virus (HPV) infection status. p16/CDKN2A protein expression positively correlated with the HPV oncogenic E7 protein, and confirmed the presence of translationally active virus. This work establishes a clinically actionable HNSCC protein biomarker assay capable of quantifying over 600 peptides from frozen or FFPE archived tissues in under 90 minutes.

cancer biology↗

bioRxiv2022

Single-cell multi-omic analysis of the vestibular schwannoma ecosystem uncovers a nerve injury-like state

Vestibular schwannomas (VS) are benign tumors that lead to significant neurologic and otologic morbidity. How VS heterogeneity and the tumor microenvironment (TME) contribute to the pathogenesis of these tumors remains poorly understood. We performed scRNA-seq on 15 VS samples, with paired scATAC-seq in six samples. We identified diverse Schwann cell (SC), stromal, and immune populations in the VS TME and found that repair-like and MHC-II antigen presenting subtype SCs are associated with increased myeloid cell infiltrate, implicating a nerve injury-like process. Deconvolution analysis of RNA-expression data from 175 tumors revealed Injury-like tumors are associated with larger tumor size, and scATAC-seq identified transcription factors associated with nerve repair among SCs from Injury-like tumors. Ligand-receptor analysis and functional in vitro experiments suggested that SCs recruit monocytes. Our study indicates that Injury-like SCs may cause tumor growth via myeloid cell recruitment and identifies molecular pathways that may be targeted to prevent tumor progression.

cancer biology↗

bioRxiv2021

The transcriptional hallmarks of intra-tumor heterogeneity across a thousand tumors

Each tumor contains malignant cells that differ in genotype, phenotype, and in their interactions with the tumor micro-environment (TME). This results in distinct integrated cellular states that govern intra-tumor heterogeneity (ITH), a central challenge of cancer therapeutics. Dozens of recent studies have begun to describe ITH by single cell RNA-seq, but each study typically profiledonly a small number of tumors and provided a narrow view of transcriptional ITH. Here, we curate, annotate and integrate the data from 77 different studies to reveal the patterns of ITH across 1,163 tumor samples covering 24 tumor types. Focusing on the malignant cells, we find thousands of transcriptional ITH programs that can be described by 41 consensus meta-programs (MPs), each consisting of dozens of genes that are coordinately upregulated in subpopulations of cells within many different tumors. The MPs cover diverse cellular processes and differ in their cancer-type distribution. General MPs associated with processes such as cell cycle and stress vary within most tumors, while context-specific MPs reflect the unique biology of particular cancer types, often resembling developmental cell types and suggesting the co-existence of variable differentiation states within tumors. Some of the MPs are further associated with overall tumor proliferation or immune state, highlighting their potential clinical significance. Based on functional similarities among MPs, we propose a set of 11 hallmarks that together account for the majority of observed ITH programs. Given the breadth and scope of the investigated cohort, the MPs and hallmarks described here reflect the first comprehensive pan-cancer description of transcriptional ITH.

cancer biology↗

bioRxiv2021

Spatial drivers and pre-cancer populations collaborate with the microenvironment in untreated and chemo-resistant pancreatic cancer

Pancreatic Ductal Adenocarcinoma (PDAC) is a lethal disease with limited treatment options and poor survival. We studied 73 samples from 21 patients (7 treatment-naive and 14 treated with neoadjuvant regimens), analyzing distinct spatial units and performing bulk proteogenomics, single cell sequencing, and cellular imaging. Spatial drivers, including mutant KRAS, SMAD4, and GNAQ, were associated with differential phosphosignaling and metabolic responses compared to wild type. Single cell subtyping discovered 12 of 21 tumors with mixed basal and classical features. Trefoil factor family members were upregulated in classical populations, while the basal populations showed enhanced expression of mesenchymal genes, including VIM and IGTB1. Acinar-ductal metaplasia (ADM) populations, present in 95% of patients, with 46% reduction of driver mutation fractions compared to tumor populations, exhibited suppressive and oncogenic features linked to morphologic states. We identified coordinated expression of TIGIT in exhausted and regulatory T cells and Nectin receptor expression in tumor cells. Higher expression of angiogenic and stress response genes in dendritic cells compared to tumor cells suggests they have a pro-tumorigenic role in remodeling the microenvironment. Treated samples contain a three-fold enrichment of inflammatory CAFs when compared to untreated samples, while other CAF subtypes remain similar. A subset of tumor and/or ADM-specific biomarkers showed differential expression between treatment groups, and several known drug targets displayed potential cross-cell type reactivities. This resolution that spatially defined single cell omics provides reveals the diversity of tumor and microenvironment populations in PDAC. Such understanding may lead to more optimal treatment regimens for patients with this devastating disease. HIGHLIGHTSO_LIAcinar-ductal metaplasia (ADM) cells represent a genetic and morphologic transition state between acinar and tumor cells. C_LIO_LIInflammatory cancer associated fibroblasts (iCAFs) are a major component of the PDAC TME and are significantly higher in treated samples C_LIO_LIReceptor-ligand analysis reveals tumor cell-TME interactions through NECTIN4-TIGIT C_LIO_LITumor and ADM cell proteogenomics differ between treated and untreated samples, with unique and shared potential drug targets C_LI

cancer biology↗

bioRxiv2019

Pan-cancer single cell RNA-seq uncovers recurring programs of cellular heterogeneity

Cultured cell lines are the workhorse of cancer research, but it is unclear to what extent they recapitulate the cellular heterogeneity observed among malignant cells in tumors, given the absence of a native tumor microenvironment. Here, we used multiplexed single cell RNA-seq to profile ~200 cancer cell lines. We uncovered expression programs that are recurrently heterogeneous within many cancer cell lines and are largely independent of observed genetic diversity. These programs of heterogeneity are associated with diverse biological processes, including cell cycle, senescence, stress and interferon responses, epithelial-to-mesenchymal transition, and protein maturation and degradation. Notably, some of these recurrent programs recapitulate those seen in human tumors, suggesting a prominent role of intrinsic plasticity in generating intra-tumoral heterogeneity. Moreover, the data allowed us to prioritize specific cell lines as model systems of cellular plasticity. We used two such models to demonstrate the dynamics, regulation and drug sensitivities associated with a cancer senescence program also observed in human tumors. Our work describes the landscape of cellular heterogeneity in diverse cancer cell lines, and identifies recurrent patterns of expression heterogeneity that are shared between tumors and specific cell lines and can thus be further explored in follow up studies.

cancer biology↗

bioRxiv2018

Expression variation analysis for tumor heterogeneity in single-cell RNA-sequencing data

Tumor heterogeneity provides a complex challenge to cancer treatment and is a critical component of therapeutic response, disease recurrence, and patient survival. Single-cell RNA-sequencing (scRNA-seq) technologies reveal the prevalence of intra-and inter-tumor heterogeneity. Computational techniques are essential to quantify the differences in variation of these profiles between distinct cell types, tumor subtypes, and patients to fully characterize intra-and inter-tumor molecular heterogeneity. We devised a new algorithm, Expression Variation Analysis in Single Cells (EVAsc), to perform multivariate statistical analyses of differential variation of expression in gene sets for scRNA-seq. EVAsc has high sensitivity and specificity to detect pathways with true differential heterogeneity in simulated data. We then apply EVAsc to several public domain scRNA-seq tumor datasets to quantify the landscape of tumor heterogeneity in several key applications in cancer genomics, i.e. immunogenicity, cancer subtypes, and metastasis. Immune pathway heterogeneity in hematopoietic cell populations in breast tumors corresponded to the amount diversity present in the T-cell repertoire of each individual. In head and neck squamous cell carcinoma (HNSCC) patients, we found dramatic differences in pathway dysregulation across basal primary tumors. Within the basal primary tumors we also identified increased immune dysregulation in individuals with a high proportion of fibroblasts present in the tumor microenvironment. Moreover, cells in HNSCC primary tumors had significantly more heterogeneity across pathways than cells in metastases, consistent with a model of clonal outgrowth. These results demonstrate the broad utility of EVAsc to quantify inter-and intra-tumor heterogeneity from scRNA-seq data without reliance on low dimensional visualization.

bioinformatics↗