Single-cell multi-omics analysis reveals cancer regulatory elements of transcriptional programs and clinical implications

The regulatory mechanisms governing transcriptional programs in the cancer genome remain elusive, particularly those concerning cell-type specificity. We carefully curated single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) and single-cell RNA sequencing (scRNA-seq) data from eight distinct carcinoma tissues, including breast, skin, colon, endometrium, lung, ovary, liver, and kidney. Using single-cell multi-omics analysis, we identified extensive open chromatin regions and constructed peak-gene link networks, which can reveal distinct cancer gene regulation and genetic risks. We further explored conserved epigenetic regulation across cell types within cancer and elucidated their functional implications. Moreover, we identified cell-type-associated transcription factors (TFs) that regulate key cellular functions, such as the TEAD family of TFs, which widely control cancer-related signaling pathways in tumor cells. In colon cancer, we further identified tumor-specific TFs that are more highly activated in tumor cells than in normal epithelial cells, including CEBPG, LEF1, SOX4, TCF7, and TEAD4, which are pivotal in driving malignant transcriptional programs and represent potential therapeutic targets, as corroborated by single-cell sequencing data from multiple sources and in vitro experiments. Our findings provide a comprehensive understanding of the regulatory dynamics underlying carcinomas and offer valuable insights into potential therapeutic interventions.

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Publication Details

Journal
Cell Death and Disease
Published
2025-10-21
DOI
https://doi.org/10.1038/s41419-025-08060-7
Citations
1
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.81

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article

Single-cell multi-omics analysis reveals cancer regulatory elements of transcriptional programs and clinical implications

Xiaowei Tang, Guangze Zhang, Jianbo Xiao, Chenyi Wang et al.
1 citations
Cell Death and Disease
Single-cell and spatial transcriptomics
0.81
article

Single-cell multi-omics analysis reveals cancer regulatory elements of transcriptional programs and clinical implications

Xiaowei Tang, Guangze Zhang, Jianbo Xiao, Chenyi Wang, Zichu Shen, Yuxin Yin, Xiangyan Meng, Qiaoling Zhang, Anhang Liu, Minghao Li
article en
1 citations

Abstract

The regulatory mechanisms governing transcriptional programs in the cancer genome remain elusive, particularly those concerning cell-type specificity. We carefully curated single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) and single-cell RNA sequencing (scRNA-seq) data from eight distinct carcinoma tissues, including breast, skin, colon, endometrium, lung, ovary, liver, and kidney. Using single-cell multi-omics analysis, we identified extensive open chromatin regions and constructed peak-gene link networks, which can reveal distinct cancer gene regulation and genetic risks. We further explored conserved epigenetic regulation across cell types within cancer and elucidated their functional implications. Moreover, we identified cell-type-associated transcription factors (TFs) that regulate key cellular functions, such as the TEAD family of TFs, which widely control cancer-related signaling pathways in tumor cells. In colon cancer, we further identified tumor-specific TFs that are more highly activated in tumor cells than in normal epithelial cells, including CEBPG, LEF1, SOX4, TCF7, and TEAD4, which are pivotal in driving malignant transcriptional programs and represent potential therapeutic targets, as corroborated by single-cell sequencing data from multiple sources and in vitro experiments. Our findings provide a comprehensive understanding of the regulatory dynamics underlying carcinomas and offer valuable insights into potential therapeutic interventions.

Cell Death and DiseaseVol. 16(1)
Peking University (CN), Peking University People's Hospital (CN), Peking University Shenzhen Hospital (CN), Center for Life Sciences (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Openalex Percentile: Top 22%
Single-cell and spatial transcriptomics
0.81
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