Up-regulation of S100P predicts the poor long-term survival and construction of prognostic signature for survival and immunotherapy in patients with pancreatic cancer.


Journal

Bioengineered
ISSN: 2165-5987
Titre abrégé: Bioengineered
Pays: United States
ID NLM: 101581063

Informations de publication

Date de publication:
12 2021
Historique:
pubmed: 17 10 2021
medline: 17 2 2022
entrez: 16 10 2021
Statut: ppublish

Résumé

Pancreatic cancer is associated with a high mortality rate, and the prognosis is positively related to immune status. In this study, we constructed a prognostic signature from survival- and immune-related genes (IRGs) to guide treatment and assess prognosis of patients with pancreatic cancer. The transcriptomic data were obtained from The Cancer Genome Atlas (TCGA) database, and IRGs were extracted from the ImmPort database. Univariate and LASSO regression analysis were used to obtain survival-related IRGs. Finally, the prognostic signature was constructed using multivariate regression analysis. The laboratory experiments were conducted to verify the key IRG expression. Immune cells infiltration was analyzed using the CIBERSORT algorithm and TIMER database. Prognostic signature containing four IRGs (ADA2, TLR1, PTPN6, S100P) was constructed with good predictive performance; in particular, S100P played a significant role in the immune microenvironment, and tumorigenesis of pancreatic cancer. Moreover, we found that CD8

Identifiants

pubmed: 34654352
doi: 10.1080/21655979.2021.1992331
pmc: PMC8806945
doi:

Substances chimiques

Biomarkers, Tumor 0
Calcium-Binding Proteins 0
Neoplasm Proteins 0
S100P protein, human 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

9006-9020

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Auteurs

Wenbo Zou (W)

Medical School of Chinese PLA, Beijing, China.
Faculty of Hepato-Pancreato-Biliary Surgery, The First Medical Center of Chinese People's Liberation Army (PLA) General Hospital, Beijing, China.
Key Laboratory of Digital Hepetobiliary Surgery, PLA, Beijing, China.

Lincheng Li (L)

Medical School of Chinese PLA, Beijing, China.
Faculty of Hepato-Pancreato-Biliary Surgery, The First Medical Center of Chinese People's Liberation Army (PLA) General Hospital, Beijing, China.
Key Laboratory of Digital Hepetobiliary Surgery, PLA, Beijing, China.

Zizheng Wang (Z)

Faculty of Hepato-Pancreato-Biliary Surgery, The First Medical Center of Chinese People's Liberation Army (PLA) General Hospital, Beijing, China.
Key Laboratory of Digital Hepetobiliary Surgery, PLA, Beijing, China.

Nan Jiang (N)

Faculty of Hepato-Pancreato-Biliary Surgery, The First Medical Center of Chinese People's Liberation Army (PLA) General Hospital, Beijing, China.
Key Laboratory of Digital Hepetobiliary Surgery, PLA, Beijing, China.

Fei Wang (F)

Faculty of Hepato-Pancreato-Biliary Surgery, The First Medical Center of Chinese People's Liberation Army (PLA) General Hospital, Beijing, China.
Key Laboratory of Digital Hepetobiliary Surgery, PLA, Beijing, China.

Minggen Hu (M)

Faculty of Hepato-Pancreato-Biliary Surgery, The First Medical Center of Chinese People's Liberation Army (PLA) General Hospital, Beijing, China.
Key Laboratory of Digital Hepetobiliary Surgery, PLA, Beijing, China.

Rong Liu (R)

Faculty of Hepato-Pancreato-Biliary Surgery, The First Medical Center of Chinese People's Liberation Army (PLA) General Hospital, Beijing, China.
Key Laboratory of Digital Hepetobiliary Surgery, PLA, Beijing, China.

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Classifications MeSH