A combined hypoxia and immune gene signature for predicting survival and risk stratification in triple-negative breast cancer

Xia, Yang; Weng, Xin; Yang, Yong; Zhang, Meng; Xiu, Yingjie; Peng, Wenfeng; Liao, Xuhui; Xu, Meiquan; Sun, Yan; Liu, Xia

doi:10.18632/aging.203360

Cited by 36 publications

(25 citation statements)

References 49 publications

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“…Our present work identified that hypoxia-related genes and the risk score model built on them were significantly correlated with the prognosis of CC patients. Similar results were found in ovarian cancer ( Chen et al, 2021 ), triple-negative breast cancer ( Yang et al, 2021a ), osteosarcoma in children ( Jiang et al, 2021a ), acute myeloid leukemia ( Jiang et al, 2021b ), and so on. It indicated that along with other factors, hypoxia might play an important role in the development and progression of cancer.…”

Section: Discussionsupporting

confidence: 75%

Novel Hypoxia-Associated Gene Signature Depicts Tumor Immune Microenvironment and Predicts Prognosis of Colon Cancer Patients

Cao

Zhu

et al. 2022

Front. Genet.

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Hypoxia, a typical hallmark of numerous tumors, indicates poor infiltration of antitumor lymphocytes, as well as facilitates the development, progression, and drug resistance of malignant cells. Here, the present research was performed to identify novel hypoxia-related molecular markers and their correlation to the tumor immune microenvironment (TIME) in colon cancer. The expression of hypoxia-related gene signature was extracted from The Cancer Genome Atlas (TCGA) COAD cohort. Based on this signature, a risk score model was constructed using the Lasso regression model. Its discrimination ability and stability were validated in another independent cohort (GSE17536) from Gene Expression Omnibus (GEO) database. Moreover, molecular biology experiments (quantitative real-time PCR and multiple immunohistochemistry) were performed to validate the results of bioinformatics analyses. Three hub genes, including PPFIA4, SERPINE1, and STC2, were chosen to build the risk score model. All of these genes were increasingly expressed in the hypoxia subgroup (HS). Compared with the normoxia subgroup (NS), HS had worse pathological features (T, N, M, and stage) and overall survival (OS), more expression of immune checkpoint molecules, poorer infiltration of some pro-inflammation immune cells (CD4+ T cells and CD8+ T cells), and enriched infiltration of M0/M2 macrophages. After the risk model was proven to be valuable and stable, a nomogram was built based on this model and some clinicopathological factors. Moreover, it had been identified that three hub genes were all increasingly expressed in hypoxic conditions by quantitative real-time PCR (qPCR). The results of multiple immunohistochemistry (mIHC) also showed that higher expression of hub genes was associated with poorer infiltration of pro-inflammation immune cells (CD8+ T cells and M1 macrophages) and richer infiltration of anti-inflammation immune cells (Treg cells and M2 macrophages). In conclusion, the present study uncovered the relations among hypoxia, TIME, and clinicopathological features of colon cancer. It might provide new insight and a potential therapeutic target for immunotherapy.

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Section: Discussionsupporting

confidence: 75%

Novel Hypoxia-Associated Gene Signature Depicts Tumor Immune Microenvironment and Predicts Prognosis of Colon Cancer Patients

Cao

Zhu

et al. 2022

Front. Genet.

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“…Previous studies also identified that hypoxia could induce the high expression of immune checkpoint molecules, such as indoleamine 2,3-dioxygenase (IDO) and PD-L1 [ 50 , 51 ]. The expression of immune checkpoint molecules might be negatively associated with the infiltration of TILs and the prognosis in types of cancers [ 7 , 52 , 53 ].…”

Section: Discussionmentioning

confidence: 99%

Distinct Hypoxia-Related Gene Profiling Characterizes Clinicopathological Features and Immune Status of Mismatch Repair-Deficient Colon Cancer

Cao

et al. 2021

Journal of Oncology

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Despite dramatic responses to immune checkpoint inhibitors (ICIs) in patients with colon cancer (CC) harboring deficient mismatch repair (dMMR), more than half of these patients ultimately progress and experience primary or secondary drug resistance. There is no useful biomarker that is currently validated to accurately predict this resistance or stratify patients who may benefit from ICI-based immunotherapy. As hypoxic and acidic tumor microenvironment would greatly impair tumor-suppressing functions of tumor-infiltrating lymphocytes (TILs), we sought to explore distinct immunological phenotypes by analysis of the intratumoral hypoxia state using a well-established gene signature. Based on the Gene Expression Omnibus (GEO) (n = 88) and The Cancer Genome Atlas (TCGA) (n = 49) databases of patients with CC, we found that dMMR CC patients could be separated into normoxia subgroup (NS) and hypoxia subgroup (HS) with different levels of expression of hypoxia-related genes (lower in NS group and higher in HS group) using NMF package. Tumoral parenchyma in the HS group had a relatively lower level of immune cell infiltration, particularly CD8+ T cells and M1 macrophages than the NS group, and coincided with higher expression of immune checkpoint molecules and C-X-C motif chemokines, which might be associated with ICI resistance and prognosis. Furthermore, three genes, namely, MT1E, MT2A, and MAFF, were identified to be differentially expressed between NS and HS groups in both GEO and TCGA cohorts. Based on these genes, a prognostic model with stable and valuable predicting ability has been built for clinical application. In conclusion, the varying tumor-immune microenvironment (TIME) classified by hypoxia-related genes might be closely associated with different therapeutic responses of ICIs and prognosis of dMMR CC patients.

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“…The Z-score method was used to standardize the ssGSEA scores and risk scores [ 18 ]. The Kaplan–Meier method was used to perform survival analysis.…”

Section: Methodsmentioning

confidence: 99%

Transcriptome analysis reveals the prognostic and immune infiltration characteristics of glycolysis and hypoxia in head and neck squamous cell carcinoma

2022

BMC Cancer

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Background This study aims to construct a new prognostic gene signature in survival prediction and risk stratification for patients with Head and neck squamous cell carcinoma (HNSCC). Method The transcriptome profiling data and hallmark gene sets in the Molecular Signatures Database was used to explore the cancer hallmarks most relevant to the prognosis of HNSCC patients. Differential gene expression analysis, weighted gene co-expression network analysis, univariate COX regression analysis, random forest algorithm and multiple combinatorial screening were used to construct the prognostic gene signature. The predictive ability of gene signature was verified in the TCGA HNSCC cohort as the training set and the GEO HNSCC cohorts (GSE41613 and GSE42743) as the validation sets, respectively. Moreover, the correlations between risk scores and immune infiltration patterns, as well as risk scores and genomic changes were explored. Results A total of 3391 differentially expressed genes in HNSCC were screened. Glycolysis and hypoxia were screened as the main risk factors for OS in HNSCC. Using univariate Cox analysis, 97 prognostic candidates were identified (P < 0.05). Top 10 important genes were then screened out by random forest. Using multiple combinatorial screening, a combination with less genes and more significant P value was used to construct the prognostic gene signature (RNF144A, STC1, P4HA1, FMNL3, ANO1, BASP1, MME, PLEKHG2 and DKK1). Kaplan–Meier analysis showed that patients with higher risk scores had worse overall survival (p < 0.001). The ROC curve showed that the risk score had a good predictive efficiency (AUC > 0.66). Subsequently, the predictive ability of the risk score was verified in the validation sets. Moreover, the two-factor survival analysis combining the cancer hallmarks and risk scores suggested that HNSCC patients with the high hypoxia or glycolysis & high risk-score showed the worst prognosis. Besides, a nomogram based on the nine-gene signature was established for clinical practice. Furthermore, the risk score was significantly related to tumor immune infiltration profiles and genome changes. Conclusion This nine-gene signature associated with glycolysis and hypoxia can not only be used for prognosis prediction and risk stratification, but also may be a potential therapeutic target for patients with HNSCC.

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A combined hypoxia and immune gene signature for predicting survival and risk stratification in triple-negative breast cancer

Cited by 36 publications

References 49 publications

Novel Hypoxia-Associated Gene Signature Depicts Tumor Immune Microenvironment and Predicts Prognosis of Colon Cancer Patients

Novel Hypoxia-Associated Gene Signature Depicts Tumor Immune Microenvironment and Predicts Prognosis of Colon Cancer Patients

Distinct Hypoxia-Related Gene Profiling Characterizes Clinicopathological Features and Immune Status of Mismatch Repair-Deficient Colon Cancer

Transcriptome analysis reveals the prognostic and immune infiltration characteristics of glycolysis and hypoxia in head and neck squamous cell carcinoma

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