Evidence map›Paper›PMID 40020124›Full record

ArticleMedicine2025

Mining TCGA to reveal immunotherapy-related genes for soft tissue sarcoma.

Ruixin Li, Fan Yao, Yijin Liu, Xiaodan Wu, Peng Su, Tianran Li, Nan Wu

Abstract read
In one paragraph

Article in Medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Ruixin LiDepartment of Breast Surgery, The First Hospital of China Medical University, Shenyang, China.
Fan YaoDepartment of Breast Surgery, The First Hospital of China Medical University, Shenyang, China.ORCID 0000-0001-8689-0291
Yijin LiuDepartment of Breast Surgery, The First Hospital of China Medical University, Shenyang, China.
Xiaodan WuDepartment of Breast Surgery, The First Hospital of China Medical University, Shenyang, China.
Peng SuDepartment of Breast Surgery, The First Hospital of China Medical University, Shenyang, China.
Tianran LiDepartment of Radiology, The Fourth Medical Center of Chinese PLA General Hospital, Beijing, China.
Nan WuDepartment of Breast Surgery, The First Hospital of China Medical University, Shenyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immunotherapy of soft tissue sarcoma is considered an important development direction for the future. Bioinformatics analysis of genetic changes in tumors and the immune microenvironment around tumors has proven to be a mature and reliable method for predicting tumor prognosis. By mining the Cancer Genome Atlas Program database, we found immunotherapy targets of soft tissue sarcoma and analyzed their biological behavior. The data of 265 samples were downloaded to analyze the expression profile of soft tissue sarcomas. This included calculating tumor purity through the estimation of stromal and immune cells in malignant tumors using expression data, acquisition of differential genes as prognostic factors, and enrichment analysis of the differential genes. Survival analysis showed longer overall survival times for patients with higher immune scores. We obtained 83 survival-related differential genes through survival analysis, and 23 genes that could be used as independent risk factors for the prognosis of soft tissue sarcoma were obtained by multiple regression analysis of the differential genes and other recognized risk factors. Gene set enrichment analysis of the differential genes obtained immune and inflammatory gene ontology terms and signal pathways, including regulation of the T-cell apoptotic process and leukocyte transendothelial migration. After validation in an independent data set of the Gene Expression Omnibus database, 12 genes were confirmed as a result. We believe that these differential genes will be new targets for sarcoma immunotherapy and key genes for the prognosis of soft tissue sarcoma.

Indexed as

ImmunotherapySarcomaSoft Tissue NeoplasmsComputational BiologyDatabases, GeneticData MiningGene Expression ProfilingGene Expression Regulation, NeoplasticHumansPrognosisSurvival AnalysisTumor Microenvironment

Identifiers

PMID40020124
PMCPMC11875607

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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.