Evidence map›Paper›PMID 34993253›Full record

ArticleJournal of immunology research2021

Identifying and Validating an Acidosis-Related Signature Associated with Prognosis and Tumor Immune Infiltration Characteristics in Pancreatic Carcinoma.

Pingfei Tang, Weiming Qu, Dajun Wu, Shihua Chen, Minji Liu, Weishun Chen, Qiongjia Ai, Haijuan Tang, Hongbing Zhou

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of immunology research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.6field-weighted citation impact, top 28% of its field
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

7 citing papers in PubMed, 11 citations in OpenAlex.

  1. Multifaceted Roles of Guanylate-Binding Proteins in Cancer.International journal of molecular sciences · 2025
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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

9 authors at 1 institution in 1 country.

Pingfei TangDepartment of Digestive Diseases, Zhuzhou Central Hospital, The Affiliated Zhuzhou Hospital of Xiangya Medical College of Central South University, Zhuzhou, Hunan, China.
Weiming QuDepartment of Digestive Diseases, Zhuzhou Central Hospital, The Affiliated Zhuzhou Hospital of Xiangya Medical College of Central South University, Zhuzhou, Hunan, China.
Dajun WuDepartment of Digestive Diseases, Zhuzhou Central Hospital, The Affiliated Zhuzhou Hospital of Xiangya Medical College of Central South University, Zhuzhou, Hunan, China.
Shihua ChenDepartment of Digestive Diseases, Zhuzhou Central Hospital, The Affiliated Zhuzhou Hospital of Xiangya Medical College of Central South University, Zhuzhou, Hunan, China.
Minji LiuDepartment of Digestive Diseases, Zhuzhou Central Hospital, The Affiliated Zhuzhou Hospital of Xiangya Medical College of Central South University, Zhuzhou, Hunan, China.
Weishun ChenDepartment of Digestive Diseases, Zhuzhou Central Hospital, The Affiliated Zhuzhou Hospital of Xiangya Medical College of Central South University, Zhuzhou, Hunan, China.
Qiongjia AiDepartment of Digestive Diseases, Zhuzhou Central Hospital, The Affiliated Zhuzhou Hospital of Xiangya Medical College of Central South University, Zhuzhou, Hunan, China.
Haijuan TangDepartment of Digestive Diseases, Zhuzhou Central Hospital, The Affiliated Zhuzhou Hospital of Xiangya Medical College of Central South University, Zhuzhou, Hunan, China.
Hongbing ZhouDepartment of Digestive Diseases, Zhuzhou Central Hospital, The Affiliated Zhuzhou Hospital of Xiangya Medical College of Central South University, Zhuzhou, Hunan, China.ORCID https://orcid.org/0000-0003-4591-0625
Central South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcidosis in the tumor microenvironment (TME) is involved in tumor immune dysfunction and tumor progression. We attempted to develop an acidosis-related index (ARI) signature to improve the prognostic prediction of pancreatic carcinoma (PC).

methodsDifferential gene expression analyses of two public datasets (GSE152345 and GSE62452) from the Gene Expression Omnibus database were performed to identify the acidosis-related genes. The Cancer Genome Atlas-pancreatic carcinoma (TCGA-PAAD) cohort in the TCGA database was set as the discovery dataset. Univariate Cox regression and the Kaplan-Meier method were applied to screen for prognostic genes. The least absolute shrinkage and selection operator (LASSO) Cox regression was used to establish the optimal model. The tumor immune infiltrating pattern was characterized by the single-sample gene set enrichment analysis (ssGSEA) method, and the prediction of immunotherapy responsiveness was conducted using the tumor immune dysfunction and exclusion (TIDE) algorithm.

resultsWe identified 133 acidosis-related genes, of which 37 were identified as prognostic genes by univariate Cox analysis in combination with the Kaplan-Meier method (

conclusionsWe developed a reliable acidosis-related signature that showed excellent performance in prognostic prediction and correlated with tumor immune infiltration, providing a new direction for prognostic evaluation and immunotherapy management in PC.

Indexed as

Biomarkers, TumorTumor MicroenvironmentAcidosisComputational BiologyDatabases, GeneticGene Expression ProfilingGene Expression Regulation, NeoplasticGene OntologyHumansPancreatic NeoplasmsPrognosisProportional Hazards ModelsROC CurveTranscriptomeBiomarkers, Tumor

Identifiers

PMID34993253
PMCPMC8727107
OpenAlexW4200235731

What OpenQuestion 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 OpenQuestion graph.