Evidence map›Paper›PMID 37592152›Full record

ArticleMolecular biotechnology2024

A Novel Gene Signature Associated with Protein Post-translational Modification to Predict Clinical Outcomes and Therapeutic Responses of Colorectal Cancer.

Jun Liu, Peng Zhu

Abstract read
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In one paragraph

Article in Molecular biotechnology, 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
–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. Review
  2. 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

2 authors.

Jun LiuDepartment of Gastrointestinal Surgery, The Second Affiliated Hospital of Chongqing Medical University, 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China.
Peng ZhuDepartment of Gastrointestinal Surgery, The Second Affiliated Hospital of Chongqing Medical University, 74 Linjiang Road, Yuzhong District, Chongqing, 400010, China. zupeng@cqmu.edu.cn.ORCID http://orcid.org/0000-0002-4992-6731

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accumulated evidence highlights the biological significance of diverse protein post-translational modifications (PTMs) in tumorigenicity and progression of colorectal cancer (CRC). In this study, ten PTM patterns (ubiquitination, methylation, phosphorylation, glycosylation, acetylation, SUMOylation, citrullination, neddylation, palmitoylation, and ADP-ribosylation) were analyzed for model construction. A post-translational modification index (PTMI) with a 14-gene signature was established. CRC patients with high PTMI had a worse prognosis after validating in nine independent datasets. By incorporating PTMI with clinical features, a nomogram with excellent predictive performance was constructed. Two molecular subtypes of CRC with obvious difference in survival time were identified by unsupervised clustering. Furthermore, PTMI was related to known immunoregulators and key tumor microenvironment components. Low-PTMI patients responded better to fluorouracil-based chemotherapy and immune checkpoint blockade therapy compared to high-PTMI patients, which was validated in multiple independent datasets. However, patients with high PTMI might be sensitive to bevacizumab. In short, we established a novel PTMI model by comprehensively analyzing diverse post-translational modification patterns, which can accurately predict clinical prognosis and treatment response of CRC patients.

Indexed as

Colorectal NeoplasmsProtein Processing, Post-TranslationalBiomarkers, TumorFemaleFluorouracilGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMaleMiddle AgedPrognosisTreatment OutcomeTumor MicroenvironmentBiomarkers, TumorFluorouracilChemotherapyColorectal cancerImmunotherapyPost-translational modificationPrognosisTumor microenvironment

Identifiers

What Socratic 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 Socratic graph.