Biology subjects

Kochat, V.

Publications and source records attributed to Kochat, V..

14 recordsLinked to original sources

bioRxiv2026

Chromatin Landscape of Cancer Cell Lines Identifies Enhancer Subtypes

Epigenetic aberrations are a hallmark of cancer; however, systematic chromatin state maps of cancer cells are unavailable. We generated and analyzed 803 histone mark profiles in 142 cancer cell lines and 114 human tumors belonging to 9 solid tumor types. Irrespective of their cell-of-origin, cancer cells segregate from normal tissues based on their enhancer patterns, suggesting enhancer deregulation is a fundamental epigenetic feature in cancer. Enhancer based clustering defined 5 distinct subgroups of cancer cells (EpiC1-5) with unique developmental trajectories, molecular features and dependencies. Importantly, we define a set of core TFs that are critical for EpiC-specific enhancer patterns and survival. Notably, EpiC4 represented a predominantly epigenetic, pan-cancer subtype that displays poor survival, activation and dependence on a FN1-CAV1-SRC-PI3K-AKT signaling network. Together, these data uncover enhancer heterogeneity in pan-cancer systems with identification of a novel enhancer-based subtype and identify potential new therapeutic targets associated with unique epigenetic features.

cancer biology↗

bioRxiv2026

NanoCellAnnotator: Formalizing Expert Cell Type Annotation with Large Language Models

MotivationCell-type annotation in spatial transcriptomics is challenging due to sparse gene panels, spatial heterogeneity, and limited availability of tissue-matched reference atlases. Recent approaches have explored large language models (LLMs) for integrating biological knowledge during annotation, but unconstrained inference can produce biologically unsupported predictions and hallucinated cell types. In addition, many LLM-based pipelines rely on large cloud-hosted models that limit reproducibility and deployment in privacy-sensitive environments. ResultsWe introduce NanoCellAnnotator, a biologically constrained and confidence-aware framework for automated cell-type annotation in spatial transcriptomics. The framework de-couples spatial structure discovery, deterministic biological evidence construction, and language-model-based semantic inference. Spatial clusters are identified using hybrid spatially regularized non-negative matrix factorization (hSNMF), after which cluster-level marker genes are abstracted into ontology-derived functional programs using Gene Ontology enrichment and GO-slim projection. A lightweight locally executable language model performs constrained label selection within a curated admissible label space derived from PanglaoDB and CellMarker. Annotation confidence is estimated independently using marker support strength and lineage separation, enabling ambiguous or heterogeneous clusters to be explicitly flagged. We evaluate NanoCellAnnotator on Xenium spatial transcriptomics data from intrahepatic cholangiocarcinoma and an independent breast cancer spatial transcriptomics dataset. The framework recovers canonical cell populations with high confidence while identifying heterogeneous or transitional spatial domains as ambiguous. Agreement with manual annotations was evaluated using accuracy and adjusted Rand index. AvailabilityCode available at https://github.com/ishtyaqmahmud/NanoCellAnnotator.

bioinformatics↗

bioRxiv2026

Ambiguity-Aware Multi-Stage Cell-Type Annotation for Spatial Transcriptomics

Spatial transcriptomics enables characterization of cellular organization in intact tissue, but robust cell-type annotation remains challenging due to heterogeneous expression profiles, mixed populations, and transitional states. Existing methods often enforce a single label per cluster, obscuring biologically meaningful ambiguity and producing overconfident assignments. We propose an ambiguity-aware, multi-stage framework for spatial cell-type annotation. The method combines hybrid spatial-feature clustering with constrained language-model inference over curated label sets, and assigns confidence scores based on marker coverage, candidate separation, and entropy. Low-confidence clusters are selectively refined via local reclustering of ambiguous regions, while unresolved clusters are preserved as mixed rather than forcibly labeled. Applied to 10x Genomics Xenium spatial transcriptomics data from cholangiocarcinoma, the proposed refinement reduces cluster-level ambiguity from 16.1% to 2.27% and cell-level ambiguity from 18.4% to 0.86%, while improving confidence calibration. Spatial ablation confirms that topological integration resolves structural ambiguity over feature-only baselines, while constrained inference via a lightweight language model ensures scalable and biologically coherent annotations. These results highlight the importance of explicit ambiguity handling for reliable spatial annotation in heterogeneous tumors.

bioinformatics↗

bioRxiv2026

Spatially-Resolved Multiomic Atlas of Leiomyosarcoma Identifies Two Clinically Relevant Epigenetically-Driven Cell States

Leiomyosarcoma is a smooth muscle-derived malignancy marked by significant clinical heterogeneity. The extent and nature of cellular heterogeneity and molecular underpinnings remain poorly understood. To address this at transcriptomic and epigenomic levels, we performed single-nucleus multiome sequencing on untreated primary leiomyosarcoma tissues. Malignant cells segregated almost exclusively into two previously unrecognized and epigenetically distinct states: a dedifferentiated, mesenchymal-like subtype (MES) and a differentiated smooth muscle-enriched subtype (SMC). Chromatin accessibility profiling revealed strong enrichment of nuclear factor I (NFI) transcription factor motifs in MES cells, whereas AP-1 family motifs--most prominently FOSL2--were selectively accessible in SMC cells. Established leiomyosarcoma cell lines faithfully recapitulated these subtypes, and targeted depletion of NFI or AP-1 factors suppressed proliferation, invasion, and in vivo tumor growth, demonstrating functional dependency on these transcriptional programs. Spatial transcriptomics across 328 tissue cores from 128 leiomyosarcomas showed that immunosuppressive macrophages preferentially cluster around MES regions, revealing a subtype-specific tumor-immune niche. Clinically, MES-dominant tumors were associated with significantly worse patient outcomes. Through an epigenetic inhibitor screen, we identify and validate SMARCA4/2 inhibition as a promising therapeutic vulnerability for MES leiomyosarcomas. Together, this work defines two epigenetically driven, transcription factor-regulated, and clinically relevant states of leiomyosarcoma, revealing mechanistic underpinnings of tumor heterogeneity and uncovering actionable therapeutic strategies. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=93 HEIGHT=200 SRC="FIGDIR/small/726988v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@132928eorg.highwire.dtl.DTLVardef@133e3b7org.highwire.dtl.DTLVardef@1ab4398org.highwire.dtl.DTLVardef@e2de25_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2026

Cellular stemness identifies high-risk ductal carcinoma in situ and offers a therapeutic interception opportunity

Ductal carcinoma in situ (DCIS) exhibits substantial heterogeneity in its risk of progression to invasive breast cancer, yet the cellular and molecular determinants of high-risk lesions remain incompletely defined. Using spatially resolved single-cell transcriptomic and epigenomic profiling of 43 patient-derived DCIS and DCIS/invasive ductal carcinoma (IDC) samples, we delineate cellular programs, spatial organization, and epigenetic regulatory mechanisms associated with invasive potential. We identify an epithelial population with stemness features within luminal hormone-responsive (LumHR) cells that progressively expands from benign tissue to DCIS and IDC, and is strongly associated with invasive progression and recurrence-linked transcriptional programs. Spatial mapping reveals discrete DCIS niches enriched for stem-like LumHR cells, characterized by elevated CEACAM6 expression and enhanced ligand-receptor interactions, including CEACAM6-EGFR signaling between epithelial and stromal compartments, including cancer-associated fibroblasts, macrophages (APOC1-positive) and perivascular cells. These niches define a microenvironmental context that supports stemness and invasive potential. Epigenomic analyses implicate FOXA1 as a key regulator of these stem-like transcriptional states. Pharmacologic disruption of FOXA1-regulatory network using LSD1 inhibition suppresses stemness-associated transcriptional programs in vitro and significantly restrains tumor growth in vivo. Collectively, these findings define high-risk DCIS as a stemness-driven disease embedded within specialized microenvironments, and identify associated regulatory networks as candidate biomarkers and therapeutic vulnerabilities.

cancer biology↗

bioRxiv2026

Counterfactual Modeling of Directional Cell Cell Influence in Spatial Transcriptomics

Understanding how neighboring cells influence cellular states is central to spatial transcriptomics, yet most existing methods rely on correlation or predefined ligand-receptor (LR) pairs and do not explicitly test directionality. We introduce a counterfactual, intervention-based framework for inferring directional cell-cell influence that is LR-agnostic and tests sender specificity. A neighborhood-conditioned graph model predicts receiver cell state from local spatial context. Directional influence is quantified by counterfactually replacing neighbors of a candidate sender type and measuring the resulting displacement in predicted receiver state. We define a Counterfactual Directionality Score (CDS) that quantifies directional influence, and compute pair-level CDS by aggregating across receiver cells and test cores for each ordered sender-receiver pair. Applied to Xenium cholangiocarcinoma tissue microarrays (38 cores), the framework identified reproducible, asymmetric interactions between tumor, immune, and stromal compartments, most prominently Tumor-EMT [->] Macrophage (CDS = 0.0828) and Fibroblast [->] Macrophage (CDS = 0.0582). Effects exceeded label-permutation and spatial-shuffle null models (p < 0.001, FDR-controlled) and remained stable under core-level bootstrap resampling. Inferred directional strengths correlated strongly with matched LR scores (r = 0.758, p = 0.0027), supporting biological concordance. These results demonstrate counterfactual testing as a statistically rigorous and scalable approach for directional cell-cell communication analysis in spatial transcriptomics.

cell biology↗

bioRxiv2026

Spatially Anchored Regulatory State Inference in Melanoma

Spatial transcriptomics (ST) captures gene expression within tissue architecture but lacks direct regulatory information, while single-cell multiome assays profile transcriptional and chromatin states without spatial context. We present a framework for spatially anchored regulatory inference that integrates Visium ST with single-cell multiome data to infer spatially resolved regulatory programs. Building upon GraphST, we introduce spatially regularized cell-to-spot mapping and propagate chromatin accessibility and transcription factor motif activity into tissue space. Regulatory analysis is performed at the spatial domain level via joint differential expression and accessibility testing, along with quantitative concordance assessment. Applied to melanoma tissue sections, the framework reveals spatially localized regulatory programs and shows that assignment strategy substantially affects downstream regulatory stability. This modular approach enables interpretable gene-, peak-, and transcription factor-level outputs for multimodal spatial analysis.

bioinformatics↗

bioRxiv2026

Spatially-resolved single cell atlas of liposarcoma reveals lineage hierarchies, immune niches, and regulatory circuits

Well-differentiated and dedifferentiated liposarcoma (WDLPS and DDLPS) exhibit markedly different clinical behaviors, with DDLPS showing greater aggressiveness, higher recurrence and metastasis rates, and worse outcomes. Using single-nucleus multiome sequencing, epigenomic profiling, and spatial transcriptomics, we characterized cellular and epigenetic heterogeneity between these subtypes at single-cell and spatial resolution. We found distinct phenotypic states reflecting altered lineage differentiation and plasticity: DDLPS is dominated by early-differentiated progenitor-like cells, sclerotic WDLPS displays broader mesenchymal lineage plasticity, and adipocytic WDLPS contains abundant committed adipocytes. The DDLPS immune microenvironment was dominated by immunosuppressive macrophages, whereas WDLPS harbored more T cells and inflammatory macrophages. Notably, sclerotic WDLPS displayed intermediate cellular and molecular features, suggesting it may represent a distinct WDLPS subtype. Importantly, we identified novel gene regulatory circuits underlying each state, including FABP4/PPARG programs in adipocytic WDLPS, GLI2/TCF7L2/RBPJ/KLF7 programs in sclerotic WDLPS, and KLF7/FOSL2/SP3/GLI2/RBPJ programs in DDLPS. H3K27ac-marked enhancers were enriched near adipocytic marker genes in WDLPS and mesenchymal markers in DDLPS. Together, these findings reveal the cellular heterogeneity of tumor and immune compartments across liposarcoma subtypes and identify regulatory programs driving their differentiation states. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=155 SRC="FIGDIR/small/713651v1_ufig1.gif" ALT="Figure 1"> View larger version (73K): org.highwire.dtl.DTLVardef@1c84ee1org.highwire.dtl.DTLVardef@1b2ad42org.highwire.dtl.DTLVardef@18ce5a6org.highwire.dtl.DTLVardef@138f615_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2025

A poly(A) isoform-aware single-cell and spatial atlas defines fibroblast niches in the human bladder

Bladder function relies on coordinated interactions among epithelial, stromal, vascular, and neural compartments, but high-resolution molecular and spatial features remain undefined. We generated a publicly accessible, poly(A) isoform-aware single-nucleus and spatial reference of the adult human bladder spanning four anatomical regions and both sexes. Integrating 74,694 snRNA-seq profiles with 168,476 Xenium-resolved cells, we identified 22 cell types and 23,489 polyadenylation sites, with isoform usage improving stromal resolution beyond gene expression alone. Spatial mapping revealed layered fibroblast niches aligned with epithelial, vascular, and neural structures, supported by Visium data. This multimodal reference links isoform regulation to anatomical context and provides a reusable framework for cell-type annotation, cross-study integration, and analyses of bladder physiology and disease.

molecular biology↗

bioRxiv2025

ATRX Loss Predicts Poor Outcomes and Reveals a Therapeutic Vulnerability to TEAD Inhibition in Soft Tissue Sarcomas

ATRX is one of the most frequently altered genes in sarcoma and encodes an ATP-dependent chromatin remodeler implicated in maintaining heterochromatin. However, ATRX alterations have not been leveraged for sarcoma treatment. We observed loss of ATRX protein in 14% of soft tissue leiomyosarcoma (STLMS, n =127), 53% of uterine leiomyosarcoma (ULMS, n = 95), 37% of undifferentiated pleomorphic sarcoma (UPS, n = 82), and 8% of dedifferentiated liposarcoma (DDLPS, n = 84). ATRX loss was associated with significantly worse outcomes in ULMS, UPS, and DDLPS. ATRX knockout in sarcoma cells increased proliferation in cooperation with TP53 deletion. ATRX knockout led to chromatin de-repression and enrichment of PRDM4 and NFIX transcription factor (TF) motifs. PRDM4 and NFIX knockdown in ATRX-mutant sarcoma lines resulted in reduced proliferation and invasion suggesting epistatic relationship. Consistent with the known functional relationship between PRMD4 and YAP1, we observed that ATRX/TP53 KO cells were more sensitive to the TEAD inhibitor VT103 compared to TP53 KO and ATRX WT controls. Overall, our results identify ATRX loss as a prognostic factor of worse outcomes, implicate the ATRX-PRDM4-YAP1 axis as a novel underlying mechanism, and suggest use of TEAD inhibition as a potential therapeutic strategy for ATRX-deficient sarcomas. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=45 SRC="FIGDIR/small/689992v1_ufig1.gif" ALT="Figure 1"> View larger version (13K): org.highwire.dtl.DTLVardef@a759ecorg.highwire.dtl.DTLVardef@100c580org.highwire.dtl.DTLVardef@1a675c9org.highwire.dtl.DTLVardef@17f1f91_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2025

Reprogramming of Cellular Plasticity via ETS and MYC Core-regulatory Circuits During Response to MAPK Inhibition in BRAF-mutant Colorectal Cancer

BackgroundAberrant enhancer dynamics play a critical role in the initiation and progression of colorectal cancer (CRC). BRAFV600E-mutated metastatic CRC may be a unique subtype, exhibiting a strong epigenetic phenotype. Interestingly, bromodomain 2, a reader protein for H3K27ac-marked enhancers, was found to be synthetically lethal in CRC with BRAF + EGFR inhibition. DesignWe evaluated the effectiveness of targeting aberrant enhancers with bromodomain and extraterminal (BET) + MAPK pathway inhibitors in patient-derived xenograft models of metastatic CRC, followed by comprehensive profiling of transcriptomic and chromatin dynamics upon BET inhibitor combination treatment. ResultsThe combination of BET and standard MAPK inhibitors has demonstrated improved efficacy against BRAFV600E CRC and selective improvements against RAS-mutant CRC in vivo. We showed that BET + MAPK inhibition induced a profound downregulation of the MAPK signaling pathway compared to MAPK inhibition alone. The loss of activation signal on enhancers, as determined by H3K27ac, led to dysregulation of core-regulatory circuitries of CRC, especially loss of the auto-regulatory mechanism of the MAPK downstream E26 transformation-specific transcription factor family. Single nucleus multiome (RNA + ATAC) sequencing further distinguished differential transcriptomic and chromatin dynamics at cell type levels. Profound downregulation of well-differentiated cell types confirmed deep inhibition of MAPK signaling and downstream transcription factors. On the other hand, dedifferentiated cell populations were abundant after MAPK or combination inhibition, suggesting therapy-induced cell state switching and adaptation. ConclusionWe are evaluating BET + BRAF + EGFR inhibition in patients with treatment-refractory BRAFV600E metastatic CRC. ClinicalTrial.gov identifier: NCT06102902. What is already known on this topicEnhancer aberrations emerge as critical epigenetic features in the progression of colorectal cancer (CRC). However, the dynamics of active enhancer and the therapeutic potential of enhancer blockade, particularly in CRC tumors with BRAFV600E mutation, is not well understood. What this study addsThis study demonstrates improved efficacy of BET inhibitor combination therapies in diverse patient-derived models and reveals epigenetic reprogramming driven cellular plasticity in BRAFV600E-mutated CRC. How this study might affect research, practice or policyOur findings support treatment with BET + BRAF + EGFR inhibitors for patients with BRAFV600E-mutant mCRC [NCT06102902]. This study also highlights the potential of combining epigenetic agents to standard targeted therapy, offering a novel treatment option for this subset of patients.

cancer biology↗

bioRxiv2025

Alternative polyadenylation regulates human urothelial differentiation

The urothelium is stratified into progenitor basal cells, intermediate cells, and terminally differentiated umbrella cells. Proper renewal of umbrella cells is necessary for maintaining urinary tract barrier integrity. To investigate whether mRNA alternative cleavage and polyadenylation (APA) regulates urothelial differentiation, we developed a single-cell polyadenylation site usage (scPASU) computational pipeline to map cell state-specific polyadenylation sites in single-cell RNA-seq data from 13,544 urothelial cells. Leveraging single-cell spatial imaging, we directly visualized APA events in situ, revealing their spatial specificity within the adult human ureter. APA shaped urothelial differentiation, independent of gene expression changes. Furthermore, key APA-regulated genes shared conserved motifs in their 3 UTRs, often containing Alu elements, suggesting a potential mechanism regulating poly(A) site selection. Our study establishes APA as a driver of urothelial transcriptome diversity.

systems biology↗

bioRxiv2021

High Enhancer Activity is an Epigenetic Feature of HPV Negative Atypical Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous disease with significant morbidity and mortality and frequent recurrence. Pre-NGS efforts to transcriptionally classify HNSCC into groups of varying prognosis have identified four accepted molecular subtypes of disease: Atypical (AT), Basal (BA), Classical (CL), and Mesenchymal (MS). Here, we investigated the active enhancer landscapes of these subtypes using representative HNSCC cell lines and identified samples belonging to the AT subtype as having increased enhancer activity compared to the other 3 HNSCC subtypes. Cell lines belonging to atypical subtype were more resistant to bromodomain inhibitors (BETi). PRO-Seq experiments that both TCGA tumors and AT cell lines showed higher eRNA transcripts for enhancers controlling BETi resistance pathways, such as lipid metabolism and MAPK signaling. Additionally, HiChIP experiments suggested higher enhancer-promoter (E-P) contacts in the AT subtype, including on genes identified in the eRNA analysis. Consistently, known BETi resistance pathways were upregulated upon exposure to these inhibitors. Together, our results identify that the AT subtype of HNSCC is associated with high enhancer activity, resistance to BET inhibition, and signaling pathways that could serve as future targets for sensitizing HNSCC to BET inhibition.

cancer biology↗

bioRxiv2021

New cellular models of undifferentiated pleomorphic sarcoma and malignant peripheral nerve sheath tumor

Undifferentiated pleomorphic sarcoma (UPS) and malignant peripheral nerve sheath tumor (MPNST) are aggressive soft tissue sarcomas that do not respond well to current treatment modalities. The limited availability of UPS and MPNST cell lines makes it challenging to identify potential therapeutic targets in a laboratory setting. Understanding the urgent need for improved treatments for these tumors and the limited cellular models led us to generate additional cell lines to study these rare cancers further. Patient-derived tumors were used to establish 5 new UPS models, including one radiation-associated UPS--UPS060.1, UPS271.1, UPS511, UPS0103, and RIS620--and 3 new models of MPNST--MPNST007, MPNST3813E, and MPNST4970. This study examined the utility of the new cell lines as sarcoma models by assessing tumorigenic potential and mutation status for known sarcoma-related genes. All the cell lines formed colonies and migrated in vitro. The in vivo tumorigenic potential of each cell line was determined by either subcutaneous injection of cells or implantation of tumor tissue into immunocompromised mice. UPS060.1, UPS271.1, and UPS511 cells formed tumors in mice upon subcutaneous injection. UPS0103 and RIS620 tumor implants formed tumors in vivo, as did MPNST007 and MPNST3813E tumor implants. Mutation analysis of a panel of genes frequently mutated in sarcomas showed that two of the three MPNST cell lines had NF1 mutations. Two of the three MPNST cell lines had mutations in polycomb repressive complex 2 members. These new cellular models provide the scientific community with powerful tools for detailed studies of sarcomagenesis and investigate novel therapies for UPS and MPNST.

cancer biology↗