Evidence map›Paper›PMID 41496411›Full record

ArticleTranslational oncology2026

Single-cell analysis identifies a stemness-associated tumor cell subpopulation and develops a prognostic scoring model in esophageal squamous cell carcinoma.

Wei Ye, Wei Su, Chang Lei, Chenjun Huang, Mingjun Du

Abstract read
In one paragraph

Article in Translational oncology, 2026. 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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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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

5 authors.

Wei YeDepartment of Thoracic Surgery, The First Affiliated Hospital with Nanjing Medical University, Nanjing 210029, China.
Wei SuDepartment of Lung Cancer, Tianjin Lung Cancer Center, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China; Department of Endoscopy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Chang LeiDepartment of Urology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
Chenjun HuangDepartment of Thoracic Surgery, The First Affiliated Hospital with Nanjing Medical University, Nanjing 210029, China. Electronic address: huangchenjun@jsph.org.cn.
Mingjun DuDepartment of Thoracic Surgery, The First Affiliated Hospital with Nanjing Medical University, Nanjing 210029, China; The Affiliated Suqian First People's Hospital of Nanjing Medical University, Suqian, China. Electronic address: dumingjun1989@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Esophageal squamous cell carcinoma (ESCC) exhibits marked heterogeneity and poor prognosis, but the contribution of stemness‑related tumor cells remains unclear. Using single‑cell RNA sequencing, we identified eight tumor subpopulations in ESCC, among which one cluster displayed prominent stem‑like and proliferative features with high expression of MKI67, STMN1, and UBE2C. Based on its marker genes, we established a stemness‑associated scoring model (SASM). Validation in independent TCGA and GSE53624 cohorts confirmed that higher SASM scores predicted shorter overall survival and reduced immune infiltration, particularly of CD8⁺ T cells. SASM scores were positively correlated with tumor mutational burden (TMB), and patients with high SASM and low TMB exhibited the poorest outcomes. Further analysis identified TFDP1 as a key gene associated with SASM and adverse prognosis, which was upregulated in tumor tissues and promoted ESCC cell proliferation in vitro. Overall, our study delineates stemness‑related tumor heterogeneity in ESCC, proposes a prognostic scoring system with immunological relevance, and highlights TFDP1 as a potential therapeutic target.

Indexed as

Esophageal squamous cell carcinomaSingle-cell RNA sequencingStemness-associated scoring modelTFDP1Tumor microenvironment

Identifiers

PMID41496411
PMCPMC12813221

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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.