Evidence map›Paper›PMID 41120274›Full record

ArticleCell death & disease2025

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

Xiaowei Tang, Qiaoling Zhang, Zichu Shen, Jian Xiao, Minghao Li, Xiangyan Meng, Chenyi Wang, Guangze Zhang, Anhang Liu, Yuxin Yin

Abstract read
In one paragraph

Article in Cell death & disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Xiaowei Tang *Department of Pathology, Institute of Systems Biomedicine, School of Basic Medical Sciences, Peking-Tsinghua Center for Life Sciences, Peking University Health Science Center, Beijing, 100191, China.ORCID http://orcid.org/0009-0007-7375-9885
Qiaoling Zhang *Department of Pathology, Institute of Systems Biomedicine, School of Basic Medical Sciences, Peking-Tsinghua Center for Life Sciences, Peking University Health Science Center, Beijing, 100191, China.
Zichu ShenDepartment of Pathology, Institute of Systems Biomedicine, School of Basic Medical Sciences, Peking-Tsinghua Center for Life Sciences, Peking University Health Science Center, Beijing, 100191, China.
Jian XiaoDepartment of Pathology, Institute of Systems Biomedicine, School of Basic Medical Sciences, Peking-Tsinghua Center for Life Sciences, Peking University Health Science Center, Beijing, 100191, China.
Minghao LiDepartment of Pathology, Institute of Systems Biomedicine, School of Basic Medical Sciences, Peking-Tsinghua Center for Life Sciences, Peking University Health Science Center, Beijing, 100191, China.
Xiangyan MengDepartment of Pathology, Institute of Systems Biomedicine, School of Basic Medical Sciences, Peking-Tsinghua Center for Life Sciences, Peking University Health Science Center, Beijing, 100191, China.
Chenyi WangDepartment of Gastroenterological Surgery, Peking University People's Hospital, Beijing, 100044, China.
Guangze ZhangDepartment of Pathology, Institute of Systems Biomedicine, School of Basic Medical Sciences, Peking-Tsinghua Center for Life Sciences, Peking University Health Science Center, Beijing, 100191, China.
Anhang LiuDepartment of Pathology, Institute of Systems Biomedicine, School of Basic Medical Sciences, Peking-Tsinghua Center for Life Sciences, Peking University Health Science Center, Beijing, 100191, China.
Yuxin YinDepartment of Pathology, Institute of Systems Biomedicine, School of Basic Medical Sciences, Peking-Tsinghua Center for Life Sciences, Peking University Health Science Center, Beijing, 100191, China. yinyuxin@bjmu.edu.cn.ORCID http://orcid.org/0000-0003-4102-0043

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Gene Expression Regulation, NeoplasticNeoplasmsSingle-Cell AnalysisTranscription, GeneticCell Line, TumorEpigenesis, GeneticGene Regulatory NetworksHumansMultiomicsTranscription FactorsTranscription Factors

Identifiers

PMID41120274
PMCPMC12541060

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.