Identification of prognostic immune-related gene signature associated with tumor microenvironment of colorectal cancer.
Biomarkers, Tumor
Cancer-Associated Fibroblasts
/ metabolism
Colorectal Neoplasms
/ etiology
Computational Biology
Databases, Genetic
Gene Expression Profiling
Gene Expression Regulation, Neoplastic
Humans
Kaplan-Meier Estimate
Prognosis
Protein Interaction Mapping
Protein Interaction Maps
ROC Curve
Stromal Cells
/ metabolism
Transcriptome
Tumor Microenvironment
/ genetics
Colorectal cancer
GEO
Immune-related gene signature
Prognosis
TCGA
Tumor microenvironment
Journal
BMC cancer
ISSN: 1471-2407
Titre abrégé: BMC Cancer
Pays: England
ID NLM: 100967800
Informations de publication
Date de publication:
08 Aug 2021
08 Aug 2021
Historique:
received:
10
12
2020
accepted:
13
07
2021
entrez:
8
8
2021
pubmed:
9
8
2021
medline:
21
10
2021
Statut:
epublish
Résumé
The tumor microenvironment (TME) has significantly correlation with tumor occurrence and prognosis. Our study aimed to identify the prognostic immune-related genes (IRGs)in the tumor microenvironment of colorectal cancer (CRC). Transcriptome and clinical data of CRC cases were downloaded from TCGA and GEO databases. Stromal score, immune score, and tumor purity were calculated by the ESTIMATE algorithm. Based on the scores, we divided CRC patients from the TCGA database into low and high groups, and the differentially expressed genes (DEGs) were identified. Immune-related genes (IRGs) were selected by venn plots. To explore underlying pathways, protein-protein interaction (PPI) networks and functional enrichment analysis were used. After utilizing LASSO Cox regression analysis, we finally established a multi-IRGs signature for predicting the prognosis of CRC patients. A nomogram consists of the thirteen-IRGs signature and clinical parameters was developed to predict the overall survival (OS). We investigated the association between prognostic validated IRGs and immune infiltrates by TIMER database. Gene expression profiles and clinical information of 1635 CRC patients were collected from the TCGA and GEO databases. Higher stromal score, immune score and lower tumor purity were observed positive correlation with tumor stage and poor OS. Based on stromal score, immune score and tumor purity, 1517 DEGs, 1296 DEGs, and 1892 DEGs were identified respectively. The 948 IRGs were screened by venn plots. A thirteen-IRGs signature was constructed for predicting survival of CRC patients. Nomogram with a C-index of 0.769 (95%CI, 0.717-0.821) was developed to predict survival of CRC patients by integrating clinical parameters and thirteen-IRGs signature. The AUC for 1-, 3-, and 5-year OS were 0.789, 0.783 and 0.790, respectively. Results from TIMER database revealed that CD1B, GPX3 and IDO1 were significantly related with immune infiltrates. In this study, we established a novel thirteen immune-related genes signature that may serve as a validated prognostic predictor for CRC patients, thus will be conducive to individualized treatment decisions.
Sections du résumé
BACKGROUND
BACKGROUND
The tumor microenvironment (TME) has significantly correlation with tumor occurrence and prognosis. Our study aimed to identify the prognostic immune-related genes (IRGs)in the tumor microenvironment of colorectal cancer (CRC).
METHODS
METHODS
Transcriptome and clinical data of CRC cases were downloaded from TCGA and GEO databases. Stromal score, immune score, and tumor purity were calculated by the ESTIMATE algorithm. Based on the scores, we divided CRC patients from the TCGA database into low and high groups, and the differentially expressed genes (DEGs) were identified. Immune-related genes (IRGs) were selected by venn plots. To explore underlying pathways, protein-protein interaction (PPI) networks and functional enrichment analysis were used. After utilizing LASSO Cox regression analysis, we finally established a multi-IRGs signature for predicting the prognosis of CRC patients. A nomogram consists of the thirteen-IRGs signature and clinical parameters was developed to predict the overall survival (OS). We investigated the association between prognostic validated IRGs and immune infiltrates by TIMER database.
RESULTS
RESULTS
Gene expression profiles and clinical information of 1635 CRC patients were collected from the TCGA and GEO databases. Higher stromal score, immune score and lower tumor purity were observed positive correlation with tumor stage and poor OS. Based on stromal score, immune score and tumor purity, 1517 DEGs, 1296 DEGs, and 1892 DEGs were identified respectively. The 948 IRGs were screened by venn plots. A thirteen-IRGs signature was constructed for predicting survival of CRC patients. Nomogram with a C-index of 0.769 (95%CI, 0.717-0.821) was developed to predict survival of CRC patients by integrating clinical parameters and thirteen-IRGs signature. The AUC for 1-, 3-, and 5-year OS were 0.789, 0.783 and 0.790, respectively. Results from TIMER database revealed that CD1B, GPX3 and IDO1 were significantly related with immune infiltrates.
CONCLUSIONS
CONCLUSIONS
In this study, we established a novel thirteen immune-related genes signature that may serve as a validated prognostic predictor for CRC patients, thus will be conducive to individualized treatment decisions.
Identifiants
pubmed: 34364366
doi: 10.1186/s12885-021-08629-3
pii: 10.1186/s12885-021-08629-3
pmc: PMC8349485
doi:
Substances chimiques
Biomarkers, Tumor
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
905Informations de copyright
© 2021. The Author(s).
Références
Gut. 2015 Oct;64(10):1637-49
pubmed: 26041752
Int J Environ Res Public Health. 2019 Nov 27;16(23):
pubmed: 31783478
JCO Precis Oncol. 2018 Jun 13;2018:
pubmed: 30088816
PLoS Med. 2013;10(5):e1001453
pubmed: 23700391
Gut. 2002 Jul;51(1):65-9
pubmed: 12077094
Eur J Cancer. 2017 May;76:68-75
pubmed: 28284171
Cell Mol Life Sci. 2019 Sep;76(17):3383-3406
pubmed: 31087119
Cancer Microenviron. 2010 Mar 05;3(1):149-66
pubmed: 21209781
Lung Cancer. 2019 Feb;128:26-32
pubmed: 30642449
J Mol Med (Berl). 2009 Jun;87(6):633-44
pubmed: 19399471
Oncotarget. 2017 Jul 26;8(35):59376-59386
pubmed: 28938643
Immunity. 2013 Jul 25;39(1):11-26
pubmed: 23890060
J Cell Biochem. 2018 Mar;119(3):2460-2469
pubmed: 28230287
Aging (Albany NY). 2018 Apr 16;10(4):592-605
pubmed: 29676997
Cancer Res. 2017 Nov 1;77(21):e108-e110
pubmed: 29092952
Cancer Treat Rev. 2012 Aug;38(5):451-66
pubmed: 21945823
Cancer Lett. 2013 Nov 28;341(1):80-96
pubmed: 23376253
J Clin Invest. 2009 Jun;119(6):1420-8
pubmed: 19487818
J Immunother Cancer. 2019 Aug 7;7(1):210
pubmed: 31391111
Nucleic Acids Res. 2015 Jan;43(Database issue):D447-52
pubmed: 25352553
Curr Drug Targets. 2014;15(14):1302-11
pubmed: 25382190
Biomed Res Int. 2020 Mar 17;2020:4360930
pubmed: 32258122
Nat Med. 2013 Nov;19(11):1423-37
pubmed: 24202395
OMICS. 2012 May;16(5):284-7
pubmed: 22455463
Elife. 2017 Sep 11;6:
pubmed: 28891793
Nat Commun. 2015 Dec 04;6:8971
pubmed: 26634437
Carcinogenesis. 2013 Nov;34(11):2512-20
pubmed: 23803696
Ann Oncol. 2013 Jan;24(1):179-85
pubmed: 22865778
Nat Methods. 2015 May;12(5):453-7
pubmed: 25822800
J Cell Physiol. 2017 Oct;232(10):2657-2673
pubmed: 28075018
Nucleic Acids Res. 2015 Apr 20;43(7):e47
pubmed: 25605792
BMC Cancer. 2016 Nov 4;16(1):841
pubmed: 27809802
Ann Oncol. 2018 Mar 1;29(3):616-623
pubmed: 29293881
J Clin Oncol. 2019 Mar 1;37(7):559-569
pubmed: 30650045
Clin Cancer Res. 2013 Sep 15;19(18):4905-7
pubmed: 24009149
Genome Res. 2003 Nov;13(11):2498-504
pubmed: 14597658
Breast Cancer Res. 2015 Aug 20;17:114
pubmed: 26289960
Int J Biochem Cell Biol. 2014 Aug;53:450-8
pubmed: 24955488
Clin Cancer Res. 2004 Nov 1;10(21):7252-9
pubmed: 15534099
J Cell Biochem. 2017 Aug;118(8):1979-1983
pubmed: 28109136
Ann Surg. 2014 Jun;259(6):1156-65
pubmed: 24100338
Proc Natl Acad Sci U S A. 2009 Apr 28;106(17):7131-6
pubmed: 19359472
Cancer Lett. 2019 Aug 28;458:123-135
pubmed: 31121212
Nature. 2012 Jul 18;487(7407):330-7
pubmed: 22810696
Genome Biol. 2016 Aug 22;17(1):174
pubmed: 27549193
J Cell Physiol. 2018 Mar;233(3):2162-2169
pubmed: 28407239
Mol Cancer. 2011 Jul 21;10:85
pubmed: 21777459
J Cell Physiol. 2020 Feb;235(2):1025-1035
pubmed: 31240705
Nat Commun. 2013;4:2612
pubmed: 24113773
Genome Biol. 2016 Nov 17;17(1):231
pubmed: 27855702