Evidence map›Paper›PMID 40862277›Full record

ArticleBiochemistry and biophysics reports2025

Prognostic value and immune infiltration of novel markers TNRC6C/AMPD1 in pancreatic cancer microenvironment.

Yongting Lan, Wenyan Du, Yongfen Ma, Jingmei Cao

Abstract read
In one paragraph

Article in Biochemistry and biophysics reports, 2025. 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.

Yongting LanDepartment of Gastroenterology, Zibo Central Hospital, Zibo, 255036, China.
Wenyan DuDepartment of Clinical Laboratory, Zibo Central Hospital, Zibo, 255036, China.
Yongfen MaDepartment of Gastroenterology, Zibo Central Hospital, Zibo, 255036, China.
Jingmei CaoDepartment of Gastroenterology, Zibo Central Hospital, Zibo, 255036, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Pancreatic cancer (PC) is a highly lethal malignancy with limited treatment options. Identifying novel prognostic biomarkers and therapeutic targets is crucial for improving patient outcomes. Methods: A comprehensive bioinformatics analysis was conducted on the Gene Expression Omnibus (GEO, GSE79668, GSE183795) and The Cancer Genome Atlas- Pancreatic Adenocarcinoma (TCGA-PAAD) datasets to identify prognostic biomarkers. The prognostic value of these biomarkers was validated through survival analysis and a Cox proportional hazards model (Cox model). A clinical phenotypic prediction model was constructed using AMPD1 and TNRC6C expression levels, with logistic regression models being built for their combination. The nomogram was constructed to visually represent the model's predictive power. Additionally, immune infiltration and single-cell analyses were performed to explore the underlying mechanisms. Functional experiments were conducted to validate the effects of these biomarkers on PC cell behavior. Results: Adenosine Monophosphate Deaminase 1 (AMPD1) and Trinucleotide Repeat Containing Adaptor 6C (TNRC6C) were identified as key prognostic biomarkers for PC. High expression of these genes was associated with improved patient survival. Furthermore, AMPD1 and TNRC6C were found to be positively correlated with various immune cells, suggesting their potential role in modulating the tumor immune microenvironment. Functional experiments confirmed that these genes inhibited cancer cell proliferation, migration, invasion, and promoted apoptosis. The prognostic model based on AMPD1 and TNRC6C expression showed significant predictive accuracy, suggesting its potential clinical utility. Conclusion: This study highlights the prognostic significance of AMPD1 and TNRC6C in PC. These findings provide potential new therapeutic targets for PC and warrant further investigation. The developed clinical prediction model further supports their potential utility as biomarkers for patient stratification and prognosis.

Indexed as

Pancreatic cancerPrognostic biomarkersSurvival prediction modelTumor immune microenvironment

Identifiers

PMID40862277
PMCPMC12374436

What Socratic holds

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LicenceCC BY-NC-ND
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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.