A novel hypoxic tumor microenvironment signature for predicting the survival, progression, immune responsiveness and chemoresistance of glioblastoma: a multi-omic study

Wang, Zihao; Gao, Lu; Guo, Xiaopeng; Wang, Yaning; Wang, Yu; Ma, Wenbin; Guo, Yi; Xing, Bing

doi:10.18632/aging.103626

Cited by 7 publications

(6 citation statements)

References 43 publications

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“…Principal component analysis displayed that there were significant differences among the three different clusters (Figure 1C). What's more, the heat map showed that the expression of differential genes between different clusters was significantly different, which proved the reliability and stability of the three clusters (Figure 1D) (11).…”

Section: Cluster Analysis Of Five Geo Data Sets Based On Hrgsmentioning

confidence: 77%

Characteristics of hypoxic tumor microenvironment in non-small cell lung cancer, involving molecular patterns and prognostic signature

Huang¹,

Wang²,

Zhang³

et al. 2021

Transl Lung Cancer Res

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Background: The mechanisms of hypoxia or immune microenvironment in cancer have been studiedrespectively, but the role of hypoxia immune microenvironment in non-small cell lung cancer (NSCLC) still needs further exploration.Methods: By applying the K-means algorithm, 1,121 patients with NSCLC were divided into three categories. We evaluated the constructed signature in order to link it with the prognosis, which was constructed by univariate and least absolute shrinkage operator (LASSO) Cox regression analysis.Results: A total of three clusters were obtained by clustering five Gene Expression Omnibus (GEO) data sets. Gene Set Variation Analysis (GSVA) and immune infiltration analysis were performed to explore the biological behavior. Cluster one presented an activated state of oncogenic pathways, and compared with the other two clusters, the median risk score was the highest, which was the reason for its poor survival. Cluster three showed that the immune pathway was active and the median risk score was the lowest, so the survival was the best. However, cluster two presented a state in which both immune and matrix pathways were activate. This was manifested as mutual antagonism, and its risk score was in the middle. Its survival was in the middle.Conclusions: This work revealed the role of hypoxia related genes (HRGs) modification in tumor microenvironment, which was conducive to our comprehensive analysis of the prognosis of NSCLC, and provided direction and guidance for clinical immunotherapy.

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Section: Cluster Analysis Of Five Geo Data Sets Based On Hrgsmentioning

confidence: 77%

Characteristics of hypoxic tumor microenvironment in non-small cell lung cancer, involving molecular patterns and prognostic signature

Huang¹,

Wang²,

Zhang³

et al. 2021

Transl Lung Cancer Res

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“…Hypoxia-associated genes (such as HIFs, ARD1A, FIH) and their target gene products are known to be hyperactivated in tumor, which involved in different tumoral mechanisms of cancer. Previous studies have addressed the vital roles hypoxia status plays in the failure of conventional cancer therapies and poor prognosis of multiple cancer such as liver cancer ( Bao and Wong, 2021 ), bladder cancer ( Zhang et al, 2021 ), glioblastoma ( Wang et al, 2020 ) and breast cancer ( McAleese et al, 2021 ). Therefore, Hypoxia-associated genes can be widely used as promising prognostic predictors and therapeutic targets for breast cancer.…”

Section: Discussionmentioning

confidence: 99%

Breast Cancer Subtypes Based on Hypoxia-Related Gene Sets Identify Potential Therapeutic Agents

Xiong

Huang

Zhong

et al. 2022

Front. Mol. Biosci.

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Purpose: The hypoxic tumor microenvironment was reported to be involved in different tumorigenesis mechanisms of breast cancer (BC). We aimed to establish a hypoxia-related gene signature to identify a new BC subtype through the clustering analysis and explore potential compounds targeting the BC subtypes.Methods: Gene expression data and clinical features of BC and adjacent non-tumor tissues were downloaded from the Cancer Genome Atlas-Breast cancer (TCGA-BRCA) database. We comprehensively revealed the activity changes of Gene Ontology (GO) biological processes (BP) gene sets in BC by gene set variation analysis (GSVA) and identified three hypoxia-related BC subtypes. We then matched the differentially expressed gene profile of each subtype with the gene profile in CMap database to identify the potential agents targeting the BC subtypes.Results: 562 of Gene Ontology biological processes gene sets significantly correlated with hypoxia score in breast cancer. 969 BC patients were clustered into three subtypes based on the enrichment score of hypoxia-associated gene sets. Subtype 1 patients displayed better survival than subtype 2 and 3. KEGG pathway enrichment analysis of each subtype was performed based on the unique differential expression genes profile. In subtype 1, the upregulated genes were associated with lipid and amino acid metabolism regulation; in subtype 2, the upregulated genes were associated with metabolic energy regulation, while in subtype 3, the upregulated genes were associated with apoptosis and protein process. Using the CMap database, 55, 111 and 63 compounds were identified, targeting subtype 1, 2, and 3, respectively.Conclusion: In this study, novel hypoxia-related subtypes were developed for patients with BC. In addition, biological processes associated with differential expression genes profile and potential therapeutic target compounds were identified in each subtype. The new classification might provide a better understanding of the role of hypoxia in breast cancer and more individualized treatment for patients.

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“…Previous studies have addressed the vital roles of hypoxia status playing in the failure of conventional cancer therapies and poor prognosis of multiple cancer (15,16). Due to the significant roles of hypoxia, the hypoxia-related gene signatures of glioblastoma (12), colorectal cancer (17), hepatocellular carcinoma (18), bladder cancer (19), renal cell carcinoma (20), and breast cancer (21)(22)(23)(24) have been constructed to predict patient survival outcomes. As the most malignant and aggressive breast tumor, TNBC is characterized by severely low tumor oxygenation.…”

Section: Discussionmentioning

confidence: 99%

“…As reported by Wang et al. ( 12 ), a total of 1,694 genes in 65 gene sets were selected as HRGs with the following keywords: hypoxia AND Homo sapiens ( Supplementary Table S1 ). All the known HRGs were screened from GO, KEGG, and Reactome databases by using the Molecular Signatures Database (MSigDB), a collection of annotated gene sets.…”

Section: Methodsmentioning

confidence: 99%

Identification of a Hypoxia-Related Molecular Classification and Hypoxic Tumor Microenvironment Signature for Predicting the Prognosis of Patients with Triple-Negative Breast Cancer

et al. 2021

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PurposeThe hypoxic tumor microenvironment was reported to be involved in different tumorigenesis mechanisms of triple-negative breast cancer (TNBC), such as invasion, immune evasion, chemoresistance, and metastasis. However, a systematic analysis of the prognostic prediction models based on multiple hypoxia-related genes (HRGs) has not been established in TNBC before in the literature. We aimed to develop and verify a hypoxia gene signature for prognostic prediction in TNBC patients.MethodsThe RNA sequencing profiles and clinical data of TNBC patients were generated from the TCGA, GSE103091, and METABRIC databases. The TNBC-specific differential HRGs (dHRGs) were obtained from differential expression analysis of hypoxia cultured TNBC cell lines compared with normoxic cell lines from the GEO database. Non-negative matrix factorization (NMF) method was then performed on the TNBC patients using the dHRGs to explore a novel molecular classification on the basis of the dHRG expression patterns. Prognosis-associated dHRGs were identified by univariate and multivariate Cox regression analysis to establish the prognostic risk score model.ResultsBased on the expressions of 205 dHRGs, all the patients in the TCGA training cohort were categorized into two subgroups, and the patients in Cluster 1 demonstrated worse OS than those in Cluster 2, which was validated in two independent cohorts. Additionally, the effects of somatic copy number variation (SCNV), somatic single nucleotide variation (SSNV), and methylation level on the expressions of dHRGs were also analyzed. Then, we performed Cox regression analyses to construct an HRG-based risk score model (3-gene dHRG signature), which could reliably discriminate the overall survival (OS) of high-risk and low-risk patients in TCGA, GSE103091, METABRIC, and BMCHH (qRT-PCR) cohorts.ConclusionsIn this study, a robust predictive signature was developed for patients with TNBC, indicating that the 3-gene dHRG model might serve as a potential prognostic biomarker for TNBC.

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A novel hypoxic tumor microenvironment signature for predicting the survival, progression, immune responsiveness and chemoresistance of glioblastoma: a multi-omic study

Cited by 7 publications

References 43 publications

Characteristics of hypoxic tumor microenvironment in non-small cell lung cancer, involving molecular patterns and prognostic signature

Characteristics of hypoxic tumor microenvironment in non-small cell lung cancer, involving molecular patterns and prognostic signature

Breast Cancer Subtypes Based on Hypoxia-Related Gene Sets Identify Potential Therapeutic Agents

Identification of a Hypoxia-Related Molecular Classification and Hypoxic Tumor Microenvironment Signature for Predicting the Prognosis of Patients with Triple-Negative Breast Cancer

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