Evidence map›Paper›PMID 31102348›Full record

ArticleMolecular genetics & genomic medicine2019

Gene signature associated with neuro-endocrine activity predicting prognosis of pancreatic carcinoma.

Ke Chen, Yiping He, Yuan Liu, Xiujiang Yang

Abstract read
In one paragraph

Article in Molecular genetics & genomic medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

14 citing papers in PubMed.

  1. Article
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  4. Mitochondrial Ribosomal Proteins and Cancer.Medicina (Kaunas, Lithuania) · 2025
    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.

Ke ChenDepartment of Endoscopy, Fudan University Shanghai Cancer Center, Shanghai, China.ORCID 0000-0002-3070-7926
Yiping HeDepartment of Endoscopy, Fudan University Shanghai Cancer Center, Shanghai, China.
Yuan LiuDepartment of Endoscopy, Fudan University Shanghai Cancer Center, Shanghai, China.
Xiujiang YangDepartment of Endoscopy, Fudan University Shanghai Cancer Center, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGenomic analysis is the promising tool to clear understanding of the tumorigenesis and guide molecular classification for pancreatic cancer. Our purpose was to develop a critical predictive model for prognosis in pancreatic carcinoma, based on the genomic data.

methodsThe online The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets were queried as training and validation cohorts for comprehensive bioinformatic analysis. We applied Lasso and multivariate Cox regression to shrink genes and construct predictive model.

resultsA four genes model (DNAH10: HR = 0.71, 95% CI = 0.57-0.88, HSBP1L1: HR = 1.51, 95% CI = 1.18-1.92, KIAA0513: HR = 0.69, 95% CI = 0.50-0.96, and MRPL3: HR = 3.73, 95% CI = 2.03-6.86), was proposed and validated. The C-index was 0.73 (95% CI: 0.7-0.77). Patients in high-risk and low-risk group, stratified by model, suffered significantly different overall survival time (15.1 vs. 49.3 months, p < 0.0001 in TCGA; 423 vs. 618 days, p = 0.038 in ICGC). Taken clinical parameters into consideration, the risk-score was independent marker in clinical subpopulation. To explore the molecular mechanisms, 579 differential expression genes (DEG) in two groups were identified by edgeR. Functional enrichment of DEG indicated neuro-endocrine activity was the potential mechanism for the discrepant prognosis.

conclusionA specific four genes signature with the ability to predicted survival of pancreatic carcinoma was generated, which may indicate the connection between neuro-endocrine activity and patients' prognosis.

Indexed as

TranscriptomeAgedCarcinomaDyneinsFemaleHeat-Shock ProteinsHumansMaleMiddle AgedMitochondrial ProteinsNerve Tissue ProteinsNeurosecretory SystemsPancreatic NeoplasmsRibosomal ProteinsDyneinsHeat-Shock ProteinsHSBP1 protein, humanKIAA0513 protein, humanMitochondrial ProteinsMRPL3 protein, humanNerve Tissue ProteinsRibosomal Proteinscarcinomaneuro-endocrinepancreasprognosisTCGA

Identifiers

PMID31102348
PMCPMC6625361

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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.