Evidence map›Paper›PMID 39031341›Full record

ArticleCancer biomarkers : section A of Disease markers2024

Identification of candidate biomarkers and prognostic analysis of recurrence in colorectal cancer.

Rui Xu, Huayun Feng, Haojie Liang, Yaoping Li

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancer biomarkers : section A of Disease markers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Rui XuThe Colorectal and Anal Surgery Department, Shanxi Provincial People's Hospital, Shanxi Medical University, Taiyuan, China.
Huayun FengThe Colorectal and Anal Surgery Department, Shanxi Provincial People's Hospital, Shanxi Medical University, Taiyuan, China.
Haojie LiangKey Laboratory of Interface Science and Engineering in Advanced Materials, Ministry of Education, Taiyuan University of Technology, Taiyuan, China.
Yaoping LiThe Colorectal and Anal Surgery Department, Shanxi Provincial People's Hospital, Shanxi Medical University, Taiyuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Colorectal cancer (CRC) is one of the most common digestive tract malignant tumors, which has a high mortality rate especially for patients with CRC recurrence. However, the pathological mechanism of recurrence of CRC is unclear. In this study, we integrated multiple cohort datasets and databases to clarify and verify potential key candidate biomarkers and signal transduction pathways in recurrence of CRC. As results, 628 DEGs were identified from GSE33113 and GSE2630 datasets and their function and pathway were analyzed. 14 hub genes related to CRC recurrence were screened from and their influence on survival were analyzed. Two key genes (IL1B and DDAH1) regarded as prognostic factors were further screened. Relapse-free survival results indicated the interaction between IL1B and DDAH1 genes and B cells was the most obvious and correlated with survival, with statistical significance (P< 0.05). Specially, cox regression analysis suggested that patients with T1 and N0 stages had a higher risk of recurrence than patients with T2 and N1. This work would provide potential value for prognosis, and would promote molecular targeting therapy for CRC recurrence.

Indexed as

Biomarkers, TumorColorectal NeoplasmsNeoplasm Recurrence, LocalDatabases, GeneticFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMalePrognosisBiomarkers, Tumorbiological informationColorectal cancerimmune infiltrationprognostic analysisrecurrence

Identifiers

PMID39031341
PMCPMC11380219

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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.