Biology subjects

Korah, M.

Publications and source records attributed to Korah, M..

3 recordsLinked to original sources

bioRxiv2026

A Pan-Cancer Single-Cell Atlas to Evaluate Tumor Identity, Cell Line Concordance, and Dependency Mapping

Bulk RNA sequencing enables pan-cancer transcriptional analyses, but obscures cancer cell-specific programs due to admixture with nonmalignant cells, thereby limiting direct comparison between experimental models and primary tumors. Single-cell RNA sequencing (scRNA-seq) overcomes these limitations; however, the biological interpretability of public datasets is often compromised by variable data quality, inconsistent annotation, and atlas-scale aggregation strategies that prioritize data volume over biological coherence. We therefore developed a stringent integration framework that prioritizes representative malignant transcriptional states. Using Mahalanobis distance-based selection within batch-corrected latent space, we constructed a pan-cancer atlas comprising 135,424 high-quality malignant cells from 499 samples across 36 adult and pediatric cancers. Atlas-derived cancer signatures were used to determine tumor-cell line concordance and project ElasticNet models trained on DepMap CRISPR screens to infer cancer-specific gene dependencies. The scTumor Atlas establishes a scalable framework for tumor identity inference, cancer cell line benchmarking, and systematic identification of genetic vulnerabilities.

cancer biology↗

bioRxiv2025

Multidimensional Single-Cell Transcriptomic Profiling of Uterine Leiomyosarcomas Identifies Molecular Subtypes with Distinct Therapeutic Vulnerabilities

Uterine leiomyosarcoma (ULMS) is an orphan disease that frequently recurs and metastasizes, with patients undergoing multiple lines of chemotherapy due to lack of effective therapeutic targets. To address this gap, we used single-cell RNA sequencing and spatial transcriptomic analysis to comprehensively profile ULMS. We uncovered multiple states of tumor cells, including tumor cells with mesenchyme-like features, ischemic tumor cells defined by a MYC program, inflammatory tumor cells with active interferon signaling, and stem cell-like hormone receptor-positive cells. The inferred spatial correlates of these tumor cell states demonstrated unique localization patterns. By correlating these signatures to bulk RNA sequencing data, we demonstrate the relevance of these findings to clinical outcomes. Finally, using the single-cell integration and drug response prediction algorithm (scIDUC), we propose drug predictions that may target specific tumor states. Our findings suggest new avenues for further exploration of individualized and multifaceted therapeutic strategies to treat ULMS.

cancer biology↗

bioRxiv2025

T Cells Tear Apart Confining Extracellular Matrix Via a Breaststroke-like Motion to Generate Migration Paths

T cells adeptly migrate through soft tissues to target aberrant cells and regulate immunity. However, how they establish migration paths in confining nanoporous extracellular matrices (ECMs), and why they often fail to do so in dense ECMs that occur during fibrosis and around tumors, remain unclear. Here, we studied T cell migration in confining collagen-rich hydrogels spanning a range of stiffness, viscoelasticity, mechanical plasticity, and shear strength. Strikingly, only shear strength--the stress required for material failure--correlated strongly with migration, challenging the long-held focus on stiffness and pore size in cell motility. During migration, T cells extend actin-rich, finger-like protrusions into the ECM, which then undergo divergent breaststroke-like motion. Thus, T cells tear apart confining matrices using breaststroke-like motion to generate migration paths.

biophysics↗