A comprehensive analysis of different gene classes in pancreatic cancer: SIGLEC15 may be a promising immunotherapeutic target.
Expression
Immune escape
Pancreatic cancer
Prognosis
SIGLEC15
Journal
Investigational new drugs
ISSN: 1573-0646
Titre abrégé: Invest New Drugs
Pays: United States
ID NLM: 8309330
Informations de publication
Date de publication:
02 2022
02 2022
Historique:
received:
16
08
2021
accepted:
02
09
2021
pubmed:
14
9
2021
medline:
8
3
2022
entrez:
13
9
2021
Statut:
ppublish
Résumé
Pancreatic cancer (PC) is one of the most lethal cancer types with an extremely poor diagnosis and prognosis. This study aimed to comprehensively analyze the relationships between PC and different gene classes. Numerous genes from different categories were selected from the UALCAN database. Expression and survival analysis of these genes were performed via GEPIA, starBase and Kaplan-Meier Plotter tools. The correlations between PC-related genes and frequently mutated genes in PC as well as myeloid-derived suppressor cells (MDSCs) infiltration levels were explored by TIMER tool. The associations between PC-related genes, immune checkpoints and 182 core cancer-intrinsic CTLs-evasion genes were analyzed by R software. Besides, KEGG analysis were performed for the PC-related genes. 14 genes were identified to be highly expressed in pancreatic cancer and significantly associated with poor prognosis. Besides, high expression of these genes were observed in patients with KRAS or TP53 mutations. Most genes were significantly positively associated with immune checkpoint SIGLEC15, however, showed negative relations to PDCD1, CTLA4, LAG3, TIGIT, PDCD1LG2. In addition, all 14 genes exhibited close relationships with MDSC infiltration levels and various core cancer-intrinsic CTLs-evasion genes, especially DNTTIP1, FADD, ARF6, BCL2L1, CEP55, GALE, PDCD6IP, and RCE1. We also explored the most related pathways with these genes to further reveal the pathogenesis and metastatic mechanisms of PC. Our study analyzed the relationships between 14 PC-related genes and pancreatic cancer from different angles, which may contribute to a better understanding of unsolved mystery in PC.
Sections du résumé
BACKGROUND
Pancreatic cancer (PC) is one of the most lethal cancer types with an extremely poor diagnosis and prognosis. This study aimed to comprehensively analyze the relationships between PC and different gene classes.
METHODS
Numerous genes from different categories were selected from the UALCAN database. Expression and survival analysis of these genes were performed via GEPIA, starBase and Kaplan-Meier Plotter tools. The correlations between PC-related genes and frequently mutated genes in PC as well as myeloid-derived suppressor cells (MDSCs) infiltration levels were explored by TIMER tool. The associations between PC-related genes, immune checkpoints and 182 core cancer-intrinsic CTLs-evasion genes were analyzed by R software. Besides, KEGG analysis were performed for the PC-related genes.
RESULTS
14 genes were identified to be highly expressed in pancreatic cancer and significantly associated with poor prognosis. Besides, high expression of these genes were observed in patients with KRAS or TP53 mutations. Most genes were significantly positively associated with immune checkpoint SIGLEC15, however, showed negative relations to PDCD1, CTLA4, LAG3, TIGIT, PDCD1LG2. In addition, all 14 genes exhibited close relationships with MDSC infiltration levels and various core cancer-intrinsic CTLs-evasion genes, especially DNTTIP1, FADD, ARF6, BCL2L1, CEP55, GALE, PDCD6IP, and RCE1. We also explored the most related pathways with these genes to further reveal the pathogenesis and metastatic mechanisms of PC.
CONCLUSION
Our study analyzed the relationships between 14 PC-related genes and pancreatic cancer from different angles, which may contribute to a better understanding of unsolved mystery in PC.
Identifiants
pubmed: 34515878
doi: 10.1007/s10637-021-01176-5
pii: 10.1007/s10637-021-01176-5
doi:
Substances chimiques
Immune Checkpoint Proteins
0
Immunoglobulins
0
Membrane Proteins
0
SIGLEC15 protein, human
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
58-67Informations de copyright
© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
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