Single-cell multimodal profiling of pan-cancer cell lines uncovers gene regulatory principles underlying intrinsic cell states and environmental features
A pan-cancer single cell transcriptomic and epigenomic atlas is generated and subtype-specific gene-regulatory programs that shape cancer cell-state plasticity are identified that shape cancer cell-state plasticity.
Abstract
Cancer arises from genetic and epigenetic alterations that reshape chromatin, transcriptional regulation, and malignant cell states. To chart cancer-intrinsic regulatory programs, we build a pan-cancer single-cell atlas of 60 cancer cell lines spanning 16 tissue origins and 20 cancer types, comprising 240,957 snRNA-seq and 223,347 snATAC-seq profiles. Integrative analyses reveal cell-state heterogeneity, core gene-regulatory networks, and a conserved EMT axis transcending tissue of origin; copy-number analysis identifies transcription factor amplification and hyperactivation as drivers of state reprogramming. Comparing cutaneous melanoma with acral melanoma, a rare subtype underrepresented in previous studies, uncovers a universal inflammation-suppressive program in acral and an inflamed landscape in cutaneous melanoma, with JAK-STAT activity as the central discriminator. Integrating data across models and patient cohorts links tumor-intrinsic regulation to microenvironmental composition and therapeutic response. By profiling rare alongside common subtypes, this atlas offers a resource for mapping pan-cancer and subtype-specific regulatory programs shaping cell-state plasticity. ‘The characterization of cancer intrinsic regulatory landscape remains elusive. Here, the authors generate a pan-cancer single cell transcriptomic and epigenomic atlas and identify subtype-specific gene-regulatory programs that shape cancer cell-state plasticity.
Integrative single-cell RNA sequencing analysis of publicly available datasets from non-small cell lung cancer and breast cancer is performed to systematically map transcriptional heterogeneity and regulatory networks within the TME, providing a systems-level framework of TME organization.
M. O. Odubote, Chiemeka Elochi Emeribe· bioRxiv· 0 citations
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.
M. Mattohti, E. Arslan, Ayush T. Raman et al.· bioRxiv· 0 citations
Migratory selection was accompanied by extensive transcriptional change within each model, yet across five models spanning three tissue types these changes converged on shared biological processes rather than shared genes.
I. Ortiz, Paul V. Taufalele, Victor L. Dunagan et al.· Genes· 0 citations
A unified, multi-cohort transcriptional landscape of breast cancer that organizes canonical subtypes along continuous biological axes and reveals spatially structured regions of therapeutic sensitivity and resistance is presented.
Sonali Arora, Ramya Suresh, N. Holland et al.· bioRxiv· 0 citations
This study identified UBE2C+ proliferative tumor cells as a functionally relevant malignant subpopulation in SCLC and links this state to immune-stromal communication networks within the tumor microenvironment and provides a systems-level framework for investigating the cancer-immunity regulome in SCLC.
Hong-Ling Jia, Yongxuan An, Bing Chen et al.· Frontiers in Immunology· 0 citations
Single-cell transcriptomics of publicly available BLCA data identifies two transcriptionally distinct fibroblast states in adjacent tissue and supports an exploratory ligand–receptor interaction framework, warranting prospective validation with primary CAF populations and adequately powered multi-specimen cohorts.
Yan-Dong He, Wen-Long Lu, Guan-Qun Ju et al.· Frontiers in Cell and Develo...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.