Current issue
Archive
Manuscripts accepted
About the Journal
Editorial office
Editorial board
Section Editors
Abstracting and indexing
Subscription
Contact
Ethical standards and procedures
Most read articles
Instructions for authors
Article Processing Charge (APC)
Regulations of paying article processing charge (APC)
IMMUNOLOGY / BASIC RESEARCH
A prognostic model for stomach adenocarcinoma based on hypoxia- and immune-related genes
1
Department of General Surgery, Center of Gastrointestinal and Minimally Invasive Surgery, The Third People’s Hospital of Chengdu, Affiliated Hospital of Southwest Jiaotong University and The Second Affiliated Hospital of Chengdu, Chongqing Medical University, Chengdu, China
Submission date: 2023-01-13
Final revision date: 2023-06-06
Acceptance date: 2023-06-06
Online publication date: 2023-06-17
Corresponding author
Xing Wen
Department of General Surgery Center of Gastrointestinal and Minimally Invasive Surgery The Third People’s Hospital of Chengdu, Affiliated Hospital of Southwest Jiaotong University, The Second Affiliated Hospital of Chengdu Chongqing Medical University Chengdu 610031, China
Department of General Surgery Center of Gastrointestinal and Minimally Invasive Surgery The Third People’s Hospital of Chengdu, Affiliated Hospital of Southwest Jiaotong University, The Second Affiliated Hospital of Chengdu Chongqing Medical University Chengdu 610031, China
Arch Med Sci 2025;21(3):1018-1035
KEYWORDS
TOPICS
ABSTRACT
Introduction:
Characterized by vast heterogeneity, gastric cancer (GC) is one of the leading causes of cancer-related deaths. A specific prognostic model is necessary for the improvement of clinical treatment strategies. Hypoxia is a common feature in the tumor microenvironment that promotes tumor progression. However, the current evaluation of the hypoxic tumor immune microenvironment in GC is still inadequate.
Material and methods:
With sequence data and single nucleotide variants data obtained from The Cancer Genome Atlas-STAD dataset as well as hypoxia- and immune-related genes acquired from MsigDB and ImmPort, a hypoxia-immune-based gene signature of stomach adenocarcinoma (STAD) was built by Cox regression analysis. The risk score could be used as an independent prognostic factor.
Results:
The receiver operating characteristic curve and survival curve showed the accuracy of the model. Pearson correlation analysis showed that DUSP1, one of the hypoxia- and immune-related feature genes, was positively correlated with immune cell scores and immune-related function scores. In addition, low-risk group peers were found to be in higher immune infiltration status and had a higher immunophenoscore as demonstrated by single-sample Gene Set Enrichment Analysis (GSEA), indicating a better response to immune checkpoint inhibitor (ICI) treatment among the low-risk group. q-PCR results showed that DUSP1, IGFBP1, CGB5, GPC3 and EGF were significantly highly expressed in STAD cells, while FAM3D and FGF8 were significantly down-regulated.
Conclusions:
Overall, our study not only paves the way for future studies focusing on hypoxia and the immune microenvironment but also improves STAD patients’ prognosis and their response to immunotherapy.
Characterized by vast heterogeneity, gastric cancer (GC) is one of the leading causes of cancer-related deaths. A specific prognostic model is necessary for the improvement of clinical treatment strategies. Hypoxia is a common feature in the tumor microenvironment that promotes tumor progression. However, the current evaluation of the hypoxic tumor immune microenvironment in GC is still inadequate.
Material and methods:
With sequence data and single nucleotide variants data obtained from The Cancer Genome Atlas-STAD dataset as well as hypoxia- and immune-related genes acquired from MsigDB and ImmPort, a hypoxia-immune-based gene signature of stomach adenocarcinoma (STAD) was built by Cox regression analysis. The risk score could be used as an independent prognostic factor.
Results:
The receiver operating characteristic curve and survival curve showed the accuracy of the model. Pearson correlation analysis showed that DUSP1, one of the hypoxia- and immune-related feature genes, was positively correlated with immune cell scores and immune-related function scores. In addition, low-risk group peers were found to be in higher immune infiltration status and had a higher immunophenoscore as demonstrated by single-sample Gene Set Enrichment Analysis (GSEA), indicating a better response to immune checkpoint inhibitor (ICI) treatment among the low-risk group. q-PCR results showed that DUSP1, IGFBP1, CGB5, GPC3 and EGF were significantly highly expressed in STAD cells, while FAM3D and FGF8 were significantly down-regulated.
Conclusions:
Overall, our study not only paves the way for future studies focusing on hypoxia and the immune microenvironment but also improves STAD patients’ prognosis and their response to immunotherapy.
REFERENCES (50)
1.
Sung H, Ferlay J, Siegel RL, et al. Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2021; 71: 209-49.
2.
Niclauss N, Gutgemann I, Dohmen J, Kalff JC, Lingohr P. Novel biomarkers of gastric adenocarcinoma: current research and future perspectives. Cancers (Basel) 2021; 13: 5660.
3.
King R, Hayes C, Donohoe CL, Dunne MR, Davern M, Donlon NE. Hypoxia and its impact on the tumour microenvironment of gastroesophageal cancers. World J Gastrointest Oncol 2021; 13: 312-31.
4.
Kung-Chun Chiu D, Pui-Wah Tse A, Ming-Jing Xu I, et al. Hypoxia inducible factor HIF-1 promotes myeloid-derived suppressor cells accumulation through ENTPD2/CD39L1 in hepatocellular carcinoma. Nat Commun 2017; 8: 517.
5.
Zhihua Y, Yulin T, Yibo W, et al. Hypoxia decreases macrophage glycolysis and M1 percentage by targeting microRNA-30c and mTOR in human gastric cancer. Cancer Sci 2019; 110: 2368-77.
6.
Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 2010; 26: 139-40.
7.
Therneau TM, Grambsch PM. Modeling Survival Data: Extending the Cox Model. Springer-Verlag, New York 2000.
8.
Friedman J, Hastie T, Tibshirani R. Regularization paths for generalized linear models via coordinate descent. J Stat Softw 2010; 33: 1-22.
9.
Maag JLV. gganatogram: An R package for modular visualisation of anatograms and tissues based on ggplot2. F1000Res 2018; 7: 1576.
10.
Blanche P, Dartigues JF, Jacqmin-Gadda H. Estimating and comparing time-dependent areas under receiver operating characteristic curves for censored event times with competing risks. Stat Med 2013; 32: 5381-97.
11.
Huang C, Liu Z, Xiao L, et al. Clinical significance of serum CA125, CA19-9, CA72-4, and fibrinogen-to-lymphocyte ratio in gastric cancer with peritoneal dissemination. Front Oncol 2019; 9: 1159.
12.
Yu G, Wang LG, Han Y, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. Omics 2012; 16: 284-7.
13.
Skidmore ZL, Wagner AH, Lesurf R, et al. GenVisR: genomic visualizations in R. Bioinformatics 2016; 32: 3012-4.
14.
Fan MK, Zhang GC, Chen W, et al. Siglec-15 promotes tumor progression in osteosarcoma via DUSP1/MAPK pathway. Front Oncol 2021; 11: 710689.
15.
Xu T, Gao S, Liu J, Huang Y, Chen K, Zhang X. MMP9 and IGFBP1 regulate tumor immune and drive tumor progression in clear cell renal cell carcinoma. J Cancer 2021; 12: 2243-57.
16.
Chen Y, Kibriya MG, Jasmine F, Santella RM, Senie RT, Ahsan H. Do placental genes affect maternal breast cancer? Association between offspring’s CGB5 and CSH1 gene variants and maternal breast cancer risk. Cancer Res 2008; 68: 9729-34.
17.
Peng X, Xu E, Liang W, et al. Identification of FAM3D as a new endogenous chemotaxis agonist for the formyl peptide receptors. J Cell Sci 2016; 129: 1831-42.
18.
Wagner AE, Schwarzmayr T, Häberle B, et al. SP8 promotes an aggressive phenotype in hepatoblastoma via FGF8 activation. Cancers (Basel) 2020; 12: 2294.
19.
Valsechi MC, Bortolozo Oliveira AB, Giacometti Conceição AL, et al. GPC3 reduces cell proliferation in renal carcinoma cell lines. BMC Cancer 2014; 14: 631.
20.
Veltmann M, Hollborn M, Reichenbach A, Wiedemann P, Kohen L, Bringmann A. Osmotic induction of angiogenic growth factor expression in human retinal pigment epithelial cells. PLoS One 2016; 11: e0147312.
21.
Mortimer AM. Update on the management of symptoms in schizophrenia: focus on amisulpride. Neuropsychiatr Dis Treat 2009; 5: 267-77.
22.
D’Ignazio L, Batie M, Rocha S. Hypoxia and inflammation in cancer, focus on HIF and NF-kappaB. Biomedicines 2017; 5: 21.
23.
Mortezaee K, Majidpoor J. The impact of hypoxia on immune state in cancer. Life Sci 2021; 286: 120057.
24.
Xu C, Chen Z, Pan X, et al. Construction of a prognostic evaluation model for stomach adenocarcinoma on the basis of immune-related lncRNAs. Appl Biochem Biotechnol 2022; 194: 6255-69.
25.
Liu C, Shi Y, Du Y, et al. Dual-specificity phosphatase DUSP1 protects overactivation of hypoxia-inducible factor 1 through inactivating ERK MAPK. Exp Cell Res 2005; 309: 410-8.
26.
Semenza GL. Defining the role of hypoxia-inducible factor 1 in cancer biology and therapeutics. Oncogene 2010; 29: 625-34.
27.
Jing X, Yang F, Shao C, et al. Role of hypoxia in cancer therapy by regulating the tumor microenvironment. Mol Cancer 2019; 18: 157.
28.
Labani-Motlagh A, Ashja-Mahdavi M, Loskog A. The tumor microenvironment: a milieu hindering and obstructing antitumor immune responses. Front Immunol 2020; 11: 940.
29.
Noman MZ, Desantis G, Janji B, et al. PD-L1 is a novel direct target of HIF-1alpha, and its blockade under hypoxia enhanced MDSC-mediated T cell activation. J Exp Med 2014; 211: 781-90.
30.
Deng B, Zhu JM, Wang Y, et al. Intratumor hypoxia promotes immune tolerance by inducing regulatory T cells via TGF-beta1 in gastric cancer. PLoS One 2013; 8: e63777.
31.
Multhoff G, Vaupel P. Hypoxia compromises anti-cancer immune responses. Adv Exp Med Biol 2020; 1232: 131-43.
32.
Siska PJ, Rathmell JC. T cell metabolic fitness in antitumor immunity. Trends Immunol 2015; 36: 257-64.
33.
Qin M, Liang Z, Qin H, et al. Novel prognostic biomarkers in gastric cancer: CGB5, MKNK2, and PAPPA2. Front Oncol 2021; 11: 683582.
34.
Park CH, Hong C, Lee AR, Sung J, Hwang TH. Multi-omics reveals microbiome, host gene expression, and immune landscape in gastric carcinogenesis. iScience 2022; 25: 103956.
35.
Liang W, Peng X, Li Q, et al. FAM3D is essential for colon homeostasis and host defense against inflammation associated carcinogenesis. Nat Commun 2020; 11: 5912.
36.
Jomrich G, Hudec X, Harpain F, et al. Expression of FGF8, FGF18, and FGFR4 in gastroesophageal adenocarcinomas. Cells 2019; 8: 1092.
37.
Li CW, Lim SO, Xia W, et al. Glycosylation and stabilization of programmed death ligand-1 suppresses T-cell activity. Nat Commun 2016; 7: 12632.
38.
Shen J, Zhang Y, Yu H, et al. Role of DUSP1/MKP1 in tumorigenesis, tumor progression and therapy. Cancer Med 2016; 5: 2061-8.
39.
Chen Z, Chen Q, Cheng Z, et al. Long non-coding RNA CASC9 promotes gefitinib resistance in NSCLC by epigenetic repression of DUSP1. Cell Death Dis 2020; 11: 858.
40.
Lin YW, Weng XF, Huang BL, Guo HP, Xu YW, Peng YH. IGFBP-1 in cancer: expression, molecular mechanisms, and potential clinical implications. Am J Transl Res 2021; 13: 813-32.
41.
Liu Q, Jiang J, Zhang X, Zhang M, Fu Y. Comprehensive analysis of IGFBPs as biomarkers in gastric cancer. Front Oncol 2021; 11: 723131.
42.
Ribas A, Wolchok JD. Cancer immunotherapy using checkpoint blockade. Science 2018; 359: 1350-5.
43.
Ren Q, Zhu P, Zhang H, et al. Identification and validation of stromal-tumor microenvironment-based subtypes tightly associated with PD-1/PD-L1 immunotherapy and outcomes in patients with gastric cancer. Cancer Cell Int 2020; 20: 92.
44.
Wang F, Wei XL, Wang FH, et al. Safety, efficacy and tumor mutational burden as a biomarker of overall survival benefit in chemo-refractory gastric cancer treated with toripalimab, a PD-1 antibody in phase Ib/II clinical trial NCT02915432. Ann Oncol 2019; 30: 1479-86.
45.
Khouzam RA, Brodaczewska K, Filipiak A, et al. Tumor hypoxia regulates immune escape/invasion: influence on angiogenesis and potential impact of hypoxic biomarkers on cancer therapies. Front Immunol 2020; 11: 613114.
46.
Mouillot G, Marcou C, Zidi I, et al. Hypoxia modulates HLA-G gene expression in tumor cells. Hum Immunol 2007; 68: 277-85.
47.
Yaghi L, Poras I, Simoes RT, et al. Hypoxia inducible factor-1 mediates the expression of the immune checkpoint HLA-G in glioma cells through hypoxia response element located in exon 2. Oncotarget 2016; 7: 63690-707.
48.
Murdaca G, Calamaro P, Lantieri F, et al. HLA-G expression in gastric carcinoma: clinicopathological correlations and prognostic impact. Virchows Arch 2018; 473: 425-33.
49.
Liu L, Wang L, Zhao L, He C, Wang G. The role of HLA-G in tumor escape: manipulating the phenotype and function of immune cells. Front Oncol 2020; 10: 597468.
50.
You L, Wu W, Wang X, et al. The role of hypoxia-inducible factor 1 in tumor immune evasion. Med Res Rev 2021; 41: 1622-43.
Share
RELATED ARTICLE
| eISSN: | 1896-9151 |
| ISSN: | 1734-1922 |
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
