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

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...

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Autores principales: Bu, Fanqin, Nie, Han, Zhu, Xiaojian, Wu, Ting, Lin, Kang, Zhao, Jiefeng, Huang, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7654420/
https://www.ncbi.nlm.nih.gov/pubmed/33128857
http://dx.doi.org/10.1002/iid3.363
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author Bu, Fanqin
Nie, Han
Zhu, Xiaojian
Wu, Ting
Lin, Kang
Zhao, Jiefeng
Huang, Jun
author_facet Bu, Fanqin
Nie, Han
Zhu, Xiaojian
Wu, Ting
Lin, Kang
Zhao, Jiefeng
Huang, Jun
author_sort Bu, Fanqin
collection PubMed
description 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.
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spelling pubmed-76544202020-11-16 A signature of 18 immune‐related gene pairs to predict the prognosis of pancreatic cancer patients Bu, Fanqin Nie, Han Zhu, Xiaojian Wu, Ting Lin, Kang Zhao, Jiefeng Huang, Jun Immun Inflamm Dis Original Research 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. John Wiley and Sons Inc. 2020-10-31 /pmc/articles/PMC7654420/ /pubmed/33128857 http://dx.doi.org/10.1002/iid3.363 Text en © 2020 The Authors. Immunity, Inflammation and Disease published by John Wiley & Sons Ltd This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Research
Bu, Fanqin
Nie, Han
Zhu, Xiaojian
Wu, Ting
Lin, Kang
Zhao, Jiefeng
Huang, Jun
A signature of 18 immune‐related gene pairs to predict the prognosis of pancreatic cancer patients
title A signature of 18 immune‐related gene pairs to predict the prognosis of pancreatic cancer patients
title_full A signature of 18 immune‐related gene pairs to predict the prognosis of pancreatic cancer patients
title_fullStr A signature of 18 immune‐related gene pairs to predict the prognosis of pancreatic cancer patients
title_full_unstemmed A signature of 18 immune‐related gene pairs to predict the prognosis of pancreatic cancer patients
title_short A signature of 18 immune‐related gene pairs to predict the prognosis of pancreatic cancer patients
title_sort signature of 18 immune‐related gene pairs to predict the prognosis of pancreatic cancer patients
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7654420/
https://www.ncbi.nlm.nih.gov/pubmed/33128857
http://dx.doi.org/10.1002/iid3.363
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