Evidence map›Paper›PMID 40213562›Full record

ArticleFrontiers in immunology2025

Comprehensive pan-cancer analysis indicates key gene of p53-independent apoptosis is a novel biomarker for clinical application and chemotherapy in colorectal cancer.

Jianing Yan, Jingzhi Wang, Min Miao, Yongfu Shao

Abstract read
In one paragraph

Article in Frontiers in immunology, 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

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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.

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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

4 authors.

Jianing Yan *Department of Gastroenterology, The First Affiliated Hospital of Ningbo University, Ningbo, China.
Jingzhi Wang *Department of Radiotherapy Oncology, The First People's Hospital of Yancheng, Jiangsu, Yancheng, China.
Min MiaoDepartment of Gastroenterology, The First Affiliated Hospital of Ningbo University, Ningbo, China.
Yongfu ShaoDepartment of Gastroenterology, The First Affiliated Hospital of Ningbo University, Ningbo, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Schlafen11 (SLFN11) is a key gene in p53-independent apoptosis through ribosome stalling; however, systematic research has been conducted on its role in the tumor immune microenvironment, clinical application, and immunotherapy response across pan-cancer. Method: Public data were downloaded and multi-omics approaches were used to investigate the relationship between the expression level of SLFN11 and spatial position, biological function, immune landscape, and clinical application values. Cell Counting Kit-8 assay and quantitative real-time PCR were used to validate the expression level of SLFN11 and drug sensitivity in colorectal cancer samples. Result: Our study revealed that SLFN11 was downregulated in most cancers and correlated with DNA repair, the P53 pathway and immune response in tumor development progress by multi-omics analysis. Dysregulated SLFN11 is accompanied by several immune cell infiltrations and immune-related regulators, which can be a promising screening and prognostic biomarker and chemotherapy predictive target for clinical application. Conclusion: The expression level of SLFN11 has a substantial promise as a valuable biomarker for diagnosis and a predictive indicator for assessing the effectiveness of chemotherapy and immunotherapy in human cancers, which deserves further additional basic experiments and clinical trials to prove.

Indexed as

ApoptosisBiomarkers, TumorColorectal NeoplasmsNuclear ProteinsTumor Suppressor Protein p53Cell Line, TumorDrug Resistance, NeoplasmGene Expression Regulation, NeoplasticHumansPrognosisTumor MicroenvironmentBiomarkers, TumorNuclear ProteinsSLFN11 protein, humanTP53 protein, humanTumor Suppressor Protein p53immune infiltrationmultiomicspan-cancerSLFN11spatial transcriptome

Identifiers

PMID40213562
PMCPMC11983446

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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.