Evidence map›Paper›PMID 38582059›Full record

ArticleTranslational oncology2024

Comprehensive single-cell transcriptomic profiling reveals molecular subtypes and prognostic biomarkers with implications for targeted therapy in esophageal squamous cell carcinoma.

Dengfeng Zhang, Fangchao Zhao, Jing Li, Pengfei Guo, Haitao Liu, Tianxing Lu, Shujun Li, Zhirong Li, Yishuai Li

Open access · goldAbstract read
In one paragraph

Article in Translational oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.3field-weighted citation impact, top 13% of its field
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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Mast cell driven immunometabolism as a therapeutic entry point in ESCC.Frontiers in cell and developmental biology · 2026
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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

9 authors at 3 institutions in 1 country.

Dengfeng ZhangDepartment of Thoracic Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang 050000, China.
Fangchao ZhaoDepartment of Thoracic Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang 050000, China.
Jing LiDepartment of Thoracic Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang 050000, China.
Pengfei GuoDepartment of Thoracic Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang 050000, China.
Haitao LiuCollege of Life Science, Inner Mongolia University, Hohhot 010000, China.
Tianxing LuDepartment of Thoracic Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang 050000, China.
Shujun LiDepartment of Thoracic Surgery, The Second Hospital of Hebei Medical University, Shijiazhuang 050000, China. Electronic address: lishujun2333@163.com.
Zhirong LiProvincial Center for Clinical Laboratories, The Second Hospital of Hebei Medical University, Shijiazhuang 050000, China. Electronic address: lizhirong@hebmu.edu.cn.
Yishuai LiDepartment of Thoracic Surgery, Hebei Chest Hospital, Shijiazhuang 050000, China; Hebei Provincial Key Laboratory of Pulmonary Diseases, Shijiazhuang 050000, China. Electronic address: liyishuai66@126.com.
Hebei Medical University · CNHospital of Hebei Province · CNInner Mongolia University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEsophageal squamous cell carcinoma (ESCC) is a genetically heterogeneous disease with poor clinical outcomes. Identification of biomarkers linked to DNA replication stress may enable improved prognostic risk stratification and guide therapeutic decision making. We performed integrated single-cell RNA sequencing and computational analyses to define the molecular determinants and subtypes underlying ESCC heterogeneity.

methodsSingle-cell RNA sequencing was performed on ESCC samples and analyzed using Seurat. Differential gene expression analysis was used to identify esophageal cell phenotypes. DNA replication stress-related genes were intersected with single-cell differential expression data to identify potential prognostic genes, which were used to generate a DNA replication stress (DRS) score. This score and associated genes were evaluated in survival analysis. Putative prognostic biomarkers were evaluated by Cox regression and consensus clustering. Mendelian randomization analyses assessed the causal role of PRKCB.

resultsHigh DRS score associated with poor survival. Four genes (CDKN2A, NUP155, PPP2R2A, PRKCB) displayed prognostic utility. Three molecular subtypes were identified with discrete survival and immune properties. A 12-gene signature displayed robust prognostic performance. PRKCB was overexpressed in ESCC, while PRKCB knockdown reduced ESCC cell migration.

conclusionsThis integrated single-cell sequencing analysis provides new insights into the molecular heterogeneity and prognostic determinants underlying ESCC. The findings identify potential prognostic biomarkers and a gene expression signature that may enable improved patient risk stratification in ESCC. Experimental validation of the role of PRKCB substantiates the potential clinical utility of our results.

Indexed as

DNA replication stress response genesEsophageal squamous cell carcinomaImmune infiltrationMendelian randomizationMolecular subtypesPRKCB

Identifiers

PMID38582059
PMCPMC11004200
OpenAlexW4394018492

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.