Nature CommunicationsGenomicsPeer-reviewed journal article
Single-cell multimodal profiling of pan-cancer cell lines uncovers gene regulatory principles underlying intrinsic cell states and environmental features
Zihan XuiD, Aileen UgurbiliD, Joshua Kwan, Chloe SchaeferiD, Abdulraouf AbdulraoufiD, Ziyu LuiD, Erting TangiD, Wei You ZhouiD, Junyue CaoiD
Abstract
Cancer arises from extensive genetic and epigenetic alterations that reshape chromatin, transcriptional regulation, and malignant cell states. To systematically chart cancer-intrinsic regulatory programs, we constructed a pan-cancer single-cell transcriptomic and epigenomic atlas encompassing 60 human cell lines representing 16 tissue origins and 20 cancer types, comprising 240,957 single-nucleus RNA-seq and 223,347 single-nucleus ATAC-seq profiles. Integrative analyses revealed extensive pan-cancer cell-state heterogeneity, core gene-regulatory networks, and a conserved epithelial-mesenchymal transition (EMT) axis that transcends tissue of origin. Copy-number variation analysis identified transcription factor amplification and downstream hyperactivation as key drivers of cancer cell-state reprogramming. To further examine how regulatory programs diverge within a cancer lineage and contribute to clinically divergent outcomes, we performed a focused comparison of cutaneous melanoma with acral melanoma, a rare, UV-independent subtype underrepresented in existing pan-cancer atlases. The comparison uncovered a universal inflammation-suppressive program in acral melanoma and an inflamed regulatory landscape in cutaneous melanoma, with the JAK-STAT pathway and downstream transcriptional responses as central discriminators. Integration of single-cell and bulk datasets across models and patient cohorts further linked in vitro tumor-intrinsic gene regulations with in vivo microenvironmental composition and immunotherapy responses. Together, by extending single-cell multi-omic profiling to rare alongside common cancer subtypes, this atlas offers a resource for mapping pan-cancer and subtype-specific gene-regulatory programs that shape cancer cell-state plasticity.
- organism: human
- assay: scRNA-seq
- assay: scATAC-seq
- research focus: gene regulatory network inference
- research focus: clustering
- research focus: differential expression
- approach: statistical model
- approach: matrix factorization
- Citations
- 1
- FWCI
- 2.08
- Field percentile
- top 11%
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