Evidence map›Paper›PMID 40603489›Full record

ArticleScientific reports2025

Roles of MARCKSL1, MCM6, RFC4, and PLAU genes in esophageal cancer and their association with radiotherapy response.

Bin Zeng, Xiaoqin Liu, Jun Liu, Hongbo Qiu, Tianwei Zhang, Xiaomei Chen, Lin Wang

Abstract read
In one paragraph

Article in Scientific reports, 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. Article
  2. miR-452-3p Targets Adenomatous Polyposis Coli to Regulate the Malignant Phenotypes and Prognosis of Esophageal Cancer.The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology · 2026
    Article
  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

7 authors.

Bin Zeng *Department of Oncology, Zigong First People's Hospital, Zigong Medical Science Academ, Zigong, 643200, Sichuan, China. Zengbin252@163.com.
Xiaoqin Liu *Department of Oncology, Zigong First People's Hospital, Zigong Medical Science Academ, Zigong, 643200, Sichuan, China.
Jun LiuDepartment of Oncology, Zigong First People's Hospital, Zigong Medical Science Academ, Zigong, 643200, Sichuan, China.
Hongbo QiuDepartment of Oncology, Zigong First People's Hospital, Zigong Medical Science Academ, Zigong, 643200, Sichuan, China.
Tianwei ZhangDepartment of Oncology, Zigong First People's Hospital, Zigong Medical Science Academ, Zigong, 643200, Sichuan, China.
Xiaomei ChenDepartment of Oncology, Zigong First People's Hospital, Zigong Medical Science Academ, Zigong, 643200, Sichuan, China.
Lin WangDepartment of Oncology, Zigong First People's Hospital, Zigong Medical Science Academ, Zigong, 643200, Sichuan, China. 58774988@qq.com.

Funding

2023 Zigong Key Science and Technology Plan (Collaborative Innovation class of Zigong Academy of Medical Sciences) Project 2023YKYXT02Zigong City Key Research and Development Technology Project for High-Quality Development 2024GZL07Zigong Municipal Health System Key Medical Research Project 24zd004
6 · The paper itself

Abstract

Esophageal cancer is a highly lethal malignancy with high incidence and mortality rates, which continue to pose a significant threat to public health worldwide. Despite the adoption of multidisciplinary treatments, improving long-term survival rates remains a major challenge. Therefore, conducting in-depth research into the molecular mechanisms of esophageal cancer, identifying predictive biomarkers, and developing personalized treatment and monitoring strategies are crucial to enhancing clinical outcomes and patient prognosis. This study utilized advanced bioinformatics techniques to construct a gene co-expression network for esophageal cancer and compared it with sequencing data from real-world esophageal cancer samples. This approach successfully identified four key genes closely associated with the progression of esophageal cancer: MARCKSL1, MCM6, RFC4, and PLAU. A risk assessment model based on these genes demonstrated high predictive accuracy, particularly in assessing the risk of early-stage esophageal cancer, highlighting its significant potential for clinical application. Functional validation experiments and clinical data analysis further revealed that these genes play critical roles in esophageal cancer cell metastasis, glycolysis, and response to radiation therapy. These findings provide a new molecular basis for radiotherapy prognosis, helping to formulate more precise radiotherapy protocols and optimize treatment outcomes. Additionally, the regulatory networks of these genes revealed a complex molecular regulatory mechanism, offering new perspectives for precision treatment in esophageal cancer. In summary, these genes not only offer new insights into the early diagnosis and personalized treatment of esophageal cancer but also improve patient prognosis by correlating with radiotherapy response, thus laying a solid scientific foundation for future advancements.

Indexed as

Esophageal NeoplasmsIntracellular Signaling Peptides and ProteinsMembrane ProteinsMinichromosome Maintenance Complex Component 6Replication Protein CBiomarkers, TumorComputational BiologyFemaleGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansPrognosisBiomarkers, TumorIntracellular Signaling Peptides and ProteinsMCM6 protein, humanMembrane ProteinsMinichromosome Maintenance Complex Component 6Replication Protein CEsophageal cancerMARCKSL1MiRNARadiotherapyRFC4

Identifiers

PMID40603489
PMCPMC12223209

What OpenQuestion holds

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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.