Evidence map›Paper›PMID 38273073›Full record

ArticleScientific reports2024

Establish a novel tumor budding-related signature to predict prognosis and guide clinical therapy in colorectal cancer.

Qixin Li, Gaixia Liu, Quanpeng Qiu, Jiaqi Zhang, Ruizhe Li, Jiamian Zhao, Junjun She, Yinnan Chen

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2024. 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
0.8field-weighted citation impact, top 28% 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

3 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
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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

8 authors at 2 institutions in 1 country.

Qixin LiDepartment of General Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Gaixia LiuDepartment of General Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Quanpeng QiuDepartment of General Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Jiaqi ZhangCenter for Gut Microbiome Research, Med-X Institute, The First Affiliated Hospital of Xi'an Jiao Tong University, Xi'an, Shaanxi, China.
Ruizhe LiDepartment of General Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Jiamian ZhaoDepartment of General Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Junjun SheDepartment of General Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China. sjuns@sina.com.
Yinnan ChenCenter for Gut Microbiome Research, Med-X Institute, The First Affiliated Hospital of Xi'an Jiao Tong University, Xi'an, Shaanxi, China. superyaami@163.com.
Xi'an Jiaotong University · CNFirst Affiliated Hospital of Xi'an Jiaotong University · CN

Funding

Medical Foundation-Clinical Integration Program of Xi'an Jiaotong University YXJLRH2022043National Natural Science Foundation of China 82003807Shaanxi Province Science Foundation 2023-GHZD-19
6 · The paper itself

Abstract

Tumor budding is a long-established independent adverse prognostic marker for colorectal cancer (CRC), yet assessment of tumor budding was not reproducible. Therefore, development of precise diagnostic approaches to tumor budding is in demand. In this study, we first performed bioinformatic analysis in our single-center CRC patients' cohort (n = 84) and identified tumor budding-associated hub genes using the weighted gene co-expression network analysis (WGCNA). A machine learning methodology was used to identify hub genes and construct a prognostic signature. Nomogram model was used to identified hub genes score for tumor budding, and the receiver operating characteristic (ROC) curve and calibration plot indicated high accuracy and stability of hub gene score for predicted the prognosis of CRC. The association between budding-associated hub genes and score and prognosis of CRC were further verified in TCGA CRC cohort (n = 342). Then gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were applied to explore the signaling pathways related to the tumor budding and validated by immunohistochemistry (IHC) of our clinical samples. Subsequently, immune infiltration analysis demonstrated that there was a high correlation between hub genes score and M2-like macrophages infiltrated in tumor tissue. In addition, somatic mutation and chemotherapeutic response prediction were analyzed based on the risk signature. In summary, we established a tumor budding diagnostic molecular model, which can improve tumor budding assessment and provides a promising novel molecular marker for immunotherapy and prognosis of CRC.

Indexed as

Colorectal NeoplasmsImmunotherapyCalibrationHumansNomogramsPrognosis

Identifiers

PMID38273073
PMCPMC10810877
OpenAlexW4391220751

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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.