Evidence map›Paper›PMID 40657372›Full record

ArticleJournal of Cancer2025

Multi-Omics Analysis Reveals the transforming growth factor-β Signaling-Driven Multicellular Interactions with Prognostic Relevance in Cervical Cancer Progression.

Yuhan Wang, Guangxu Cao, Huimin Zeng, Yong Zhi, Mengting Xu, Ying Wang, Min Liu, Yetian Ruan, Ka Yu Tse, Qingfeng Zhang and 3 more

Abstract read
In one paragraph

Article in Journal of Cancer, 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. Review
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

13 authors.

Yuhan WangDepartment of Obstetrics and Gynecology, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China.
Guangxu CaoDepartment of Obstetrics and Gynecology, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China.
Huimin ZengDepartment of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Yong ZhiDepartment of Obstetrics and Gynecology, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China.
Mengting XuDepartment of Obstetrics and Gynecology, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China.
Ying WangDepartment of Obstetrics and Gynecology, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China.
Min LiuDepartment of Obstetrics and Gynecology, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China.
Yetian RuanDepartment of Obstetrics and Gynecology, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China.
Ka Yu TseDepartment of Obstetrics and Gynaecology, Queen Mary Hospital, the University of Hong Kong, Hong Kong, China.
Qingfeng ZhangKey Laboratory of Pathogen-Host Interaction, Ministry of Education; State Key Laboratory of Cardiology and Research Center for Translational Medicine, Shanghai East Hospital; Clinical Center for Brain and Spinal Cord Research, School of Medicine, Tongji University, Shanghai, China.
Jinli GaoDepartment of Pathology, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China.
Zhiqiang HanDepartment of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Fang LiDepartment of Obstetrics and Gynecology, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While cervical cancer (CC) prognosis depends on tumor staging, the spatiotemporal evolution of tumor microenvironment (TME) heterogeneity during metastatic progression remains poorly characterized at single-cell resolution. We employed an integrative multi-omics approach, combining single-cell RNA sequencing (scRNA-seq; n = 11), spatial transcriptomics (ST), and bulk RNA-seq data from the TCGA-CESC cohort (n = 304), to systematically map TME remodeling across CC progression stages. scRNA-seq was performed on primary lesions from patients with localized (n = 3), regional (n = 4), and metastatic (n = 4) diseases, with in-depth analyses focusing on cellular characteristics, cell type composition alterations, functional changes, differentiation trajectories, and cell-cell interaction networks. These findings were further validated using spatial transcriptomics, bulk RNA-seq data, and multiple immunohistochemistry (mIHC) experiments. ScRNA-seq data revealed that the TME of the metastatic group displayed a distinct immunosuppressive phenotype. Three key subclusters closely linked to TME remodeling in this group were identified. Notably, a novel metastasis-associated epithelial subpopulation (Epi0_AGR2), characterized by both epithelial-mesenchymal transition (EMT) and chemokine secretory phenotypes, was discovered. Gene Set Variation Analysis (GSVA) revealed that transforming growth factor β (TGF-β) signaling activation served as its primary transcriptional driver. Additionally, a neutrophil subset with pro-tumor and immunosuppressive properties, as well as a cancer-associated fibroblasts (CAFs) subset that promoted angiogenesis, were enriched in the metastatic group. Cell-cell interaction analysis and spatial mapping further revealed the formation of coordinated Epi0-neutrophil-CAFs niches, which established TGF-β-CXCL1/2/8-OSM/OSMR feedforward loops. Importantly, a computational model derived from the TME metastatic niche signature demonstrated significant prognostic stratification in the TCGA cohort (HR = 2.5179, p = 0.0144). In all, this study provides the first comprehensive delineation of stage-specific TME dynamics in CC, revealing TGF-β-driven cellular cooperativity as a metastatic switch. The joint framework establishes a potential clinically translatable tool for precision prognosis and therapeutic targeting.

Indexed as

cervical cancermulti-omics analysisnicheTMEtumor progression

Identifiers

PMID40657372
PMCPMC12244011

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.