Evidence map›Paper›PMID 35910195›Full record

ArticleFrontiers in genetics2022

A Diagnostic Model Using Exosomal Genes for Colorectal Cancer.

Tianxiang Lei, Yongxin Zhang, Xiaofeng Wang, Wenwei Liu, Wei Feng, Wu Song

Abstract read
In one paragraph

Article in Frontiers in genetics, 2022. 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
–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

2 citing papers in PubMed.

  1. Article
  2. Extracellular vesicles in colorectal cancer.Annals of coloproctology · 2025
    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

6 authors.

Tianxiang LeiDepartment of Gastrointestinal Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Yongxin ZhangDepartment of Gastrointestinal Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Xiaofeng WangDepartment of Gastrointestinal Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Wenwei LiuCenter for Digestive Disease, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.
Wei FengDepartment of Gastrointestinal Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Wu SongDepartment of Gastrointestinal Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Colorectal cancer (CRC) is a leading cause of cancer-related deaths worldwide. Exosomes have great potential as liquid biopsy specimens due to their presence and stability in body fluids. However, the function and diagnostic values of exosomal genes in CRC are poorly understood. In the present study, exosomal data of CRC and healthy samples from the exoRBase 2.0 and Gene Expression Omnibus (GEO) databases were used, and 38 common exosomal genes were identified. Through the least absolute shrinkage and selection operator (Lasso) analysis, support vector machine recursive feature elimination (SVM-RFE) analysis, and logistic regression analysis, a diagnostic model of the training set was constructed based on 6 exosomal genes. The diagnostic model was internally validated in the test and exoRBase 2.0 database and externally validated in the GEO database. In addition, the co-expression analysis was used to cluster co-expression modules, and the enrichment analysis was performed on module genes. Then a protein-protein interaction and competing endogenous RNA network were constructed and 10 hub genes were identified using module genes. In conclusion, the results provided a comprehensive understanding of the functions of exosomal genes in CRC as well as a diagnostic model related to exosomal genes.

Indexed as

bioinformatics analysiscolorectal cancerdiagnostic modelexosomefunctions

Identifiers

PMID35910195
PMCPMC9334773

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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.