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

Abstract

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.

Computed Tomography Imaging-Based Radiogenomics Analysis Reveals Hypoxia Patterns and Immunological Characteristics in Ovarian Cancer

“…p -value <0.05 were set as the thresholds ( 23 ). Meanwhile, 1,694 genes identified in previous literature were used as HRGs from the Molecular Signatures Database (MsigDB) ( 24 ). Specific hypoxia-related genes in OC were screened by the overlap of the HRGs and the DEGs.…”

A novel hypoxia- and lactate metabolism-related signature to predict prognosis and immunotherapy responses for breast cancer by integrating machine learning and bioinformatic analyses

“…Simultaneously, lactate metabolism was related to the outcomes and immune microenvironment in skin cutaneous melanoma, kidney renal clear cell carcinoma, and BC (37)(38)(39). In BC, prognostic models have been developed solely using lactate metabolism-related genes (LMRGs) or hypoxia-related genes [HRGs] (39)(40)(41). However, considering the heterogeneity of BC and the complex interactions between hypoxia and lactate metabolism, these alone cannot fully identify the relevant characteristics of BC.…”

Adaptation to Hypoxia May Promote Therapeutic Resistance to Androgen Receptor Inhibition in Triple-Negative Breast Cancer

“…Positive HIF-1α IHC expression significantly correlated with greater tumor size, higher histological grade, positive lymph node status, and higher tumor TNM stage as well as poorer postoperative survival [ 66 ]. The enrichment of a hypoxia-related three-gene signature model was shown to predict poorer overall survival (OS) in TNBC patients [ 67 ]. Furthermore, a high combined hypoxia and immune-base gene signature score predicted a poorer prognosis among TNBC patients [ 68 ].…”

“…Thus, targeting hypoxia along with AR in AR-enriched TNBCs may also circumvent AR-targeted therapy resistance. Furthermore, Wnt/β-catenin signaling has been reported to be one of the most significantly deregulated pathways in CRPC and is considered a compensatory pathway that PCs activate in response to ADT [ 67 , 78 , 79 , 80 , 81 ]. Lee and colleagues showed that AR growth-driven PCs are likely low in Wnt/β-catenin signaling due to the increased affinity of β-catenin for AR rather than TCF4, as the suppression of AR activity via androgen deprivation in PC cells increased β-catenin/TCF4 target gene transcription [ 82 ].…”