Evidence map›Paper›PMID 33128857›Full record

ArticleImmunity, inflammation and disease2020

A signature of 18 immune-related gene pairs to predict the prognosis of pancreatic cancer patients.

Fanqin Bu, Han Nie, Xiaojian Zhu, Ting Wu, Kang Lin, Jiefeng Zhao, Jun Huang

Abstract read
In one paragraph

Article in Immunity, inflammation and disease, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Fanqin BuDepartment of Gastrointestinal Surgery, Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
Han NieDepartment of Vascular Surgery, Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
Xiaojian ZhuZhongshan School of Medicine, Research Center of the Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, China.
Ting WuInfection Department of Guixi Traditional Chinese Medicine Hospital, Guixi, Jiangxi, China.
Kang LinDepartment of Gastrointestinal Surgery, Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
Jiefeng ZhaoDepartment of Gastrointestinal Surgery, Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.
Jun HuangDepartment of Gastrointestinal Surgery, Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China.ORCID 0000-0002-6468-3715

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pancreatic cancer is one of the most lethal malignancies. With the promising prospects conveyed by immunotherapy in cancers, we aimed to construct an immune-related gene pairs (IRGPs) signature to predict the prognosis of pancreatic cancer patients. We downloaded clinical and transcriptional data of pancreatic cancer patients from The Cancer Genome Atlas data set as the training group and GSE57495 data set as the verification group. We filtered immune-related transcriptional data by IMMPORT. With the assistance of lasso penalized Cox regression, we constructed our prognostic IRGPs signature and divided all samples into high-/low-risk groups by receiver operating characteristic curve for further comparisons. The comparisons between high- and low-risk groups including survival rate, multivariate, and univariate Cox proportional-hazards analysis, infiltration of immune cells, and Gene Set Enrichment Analysis (GSEA). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) are facilitated to analyze the proceedings in which our IRGPs signature may involve in. The results revealed that 18 IRGPs were defined as our prognostic signature. The prognostic value of this IRGPs signature was verified from the GSE57495 data set. We further demonstrated the independent prognostic value of this IRGPs signature. The contents of six immune cells between high-/low-risk groups were different, which was associated with the progression of diverse cancers. Results from GO, KEGG, and GSEA revealed that this IRGPs signature was involved in extracellular space, immune response, cancer pathways, cation channel, and gated channel activities. Evidently, this IRGPs signature will provide remarkable value for the therapy of pancreatic cancer patients.

Indexed as

Pancreatic NeoplasmsBiomarkers, TumorFemaleHumansMaleMiddle AgedPrognosisROC CurveBiomarkers, Tumorimmune-related gene pairpancreatic cancerprognostic signature

Identifiers

PMID33128857
PMCPMC7654420

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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.