Evidence map›Paper›PMID 37252337›Full record

ArticlePharmacogenomics and personalized medicine2023

Exploration and Validation of Pancreatic Cancer Hub Genes Based on Weighted Gene Co-Expression Network Analysis and Immune Infiltration Score Analysis.

Xiao-Xi Li, Hong Li, Li-Quan Jin, Yun-Bo Tan

Open access · goldAbstract read
In one paragraph

Article in Pharmacogenomics and personalized medicine, 2023. 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
0.8field-weighted citation impact, top 25% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
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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 at 2 institutions in 1 country.

Xiao-Xi Li *Dali University of Clinical Medicine School, Dali, Yunnan, 671000, People's Republic of China.
Hong Li *Department of Radiology, Affiliated Renhe Hospital of China Three Gorges University, Hubei, 443001, People's Republic of China.
Li-Quan JinDepartment of General Surgery, The First of Affiliated Hospital of Dali University, Dali, Yunnan, 671000, People's Republic of China.
Yun-Bo TanDali University of Clinical Medicine School, Dali, Yunnan, 671000, People's Republic of China.
Dali University · CNChina Three Gorges University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To find pancreatic cancer (PC)-related hub genes based on weighted gene co-expression network analysis (WGCNA) construction and immune infiltration score analysis and validate them immunohistochemically by clinical cases, to generate new concepts or therapeutic targets for the early diagnosis and treatment of PC. Material and Methods: In this study, WGCNA and immune infiltration score were utilized to identify the relevant core modules of PC and the hub genes within these core modules. Results: Using WGCNA analysis, data from PC and normal pancreas integrated with TCGA and GTEX were analyzed and brown modules were chosen from the six modules. Five hub genes, including DPYD, FXYD6, MAP6, FAM110B, and ANK2, were discovered to have differential survival significance via validation tests utilizing survival analysis curves and the GEPIA database. The DPYD gene was the only gene associated with PC survival side effects. Validation of the Human Protein Atlas (HPA) database and immunohistochemical testing of clinical samples showed positive results for DPYD expression in PC. Conclusion: In this study, we identified DPYD, FXYD6, MAP6, FAM110B, and ANK2, as immune-related candidate markers for PC. Only the DPYD gene had a negative impact on the survival of PC patients. Through validation of the HPA database and immunohistochemical testing of clinical cases, we believe that the DPYD gene brings novel ideas and therapeutic targets in the diagnosis and treatment of PC.

Indexed as

DPYDpancreatic cancertumor immunityWGCNA

Identifiers

PMID37252337
PMCPMC10216855
OpenAlexW4377205877

What OpenQuestion holds

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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.