Development and Validation of a Hypoxia-Associated Prognostic Signature Related to Osteosarcoma Metastasis and Immune Infiltration

Abstract

BackgroundIncreasing evidence has shown that hypoxia microenvironment relates to tumor initiation and progression. However, no studies focus on the application of hypoxia-associated genes in predicting osteosarcoma patients’ prognosis. This research aims to identify the hypoxia-associated genes related to osteosarcoma metastasis and construct a gene signature to predict osteosarcoma prognosis.MethodsThe differentially expressed messenger RNAs (DEmRNAs) related to osteosarcoma metastasis were identified from Therapeutically Applicable Research to Generate Effective Treatments (Target) database. Univariate and multivariate cox regression analyses were performed to develop the hypoxia-associated prognostic signature. The Kaplan–Meier (KM) survival analyses of patients with high and low hypoxia risk scores were conducted. The nomogram was constructed and the gene signature was validated in the external Gene Expression Omnibus (GEO) cohort. Single-sample gene set enrichment analysis (ssGSEA) was conducted to investigate the relationships between immune infiltration and gene signature.ResultsTwo genes, including decorin (DCN) and prolyl 4-hydroxylase subunit alpha 1 (P4HA1), were involved in the hypoxia-associated gene signature. In training and testing datasets, patients with high-risk scores showed lower survival rates and the gene signature was identified as the independent prognostic factor. Receiver operating characteristic (ROC) curves demonstrated the robustness of signature. Functional analyses of DEmRNAs among high- and low-risk groups revealed that immune-associated functions and pathways were significantly enriched. Furthermore, ssGSEA showed that five immune cells (DCs, macrophages, neutrophils, pDCs, and TIL) and three immune features (CCR, APC co inhibition, and Check-point) were down-regulated in the high-risk group.ConclusionThe current study established and validated a novel hypoxia-associated gene signature in osteosarcoma. It could act as a prognostic biomarker and serve as therapeutic guidance in clinical applications.

Prognostic Ferroptosis-Related lncRNA Signatures Associated With Immunotherapy and Chemotherapy Responses in Patients With Stomach Cancer

“…Patients with advanced non-small-cell lung cancer presenting with greater CD8 + T cell infiltration exhibit a superior treatment response to pembrolizumab, an anti-PD-1 drug ( Garon et al, 2019 ). Dendritic cells (DCs), which are antigen-presenting cells, often eliminate tumors by stimulating naive T cell differentiation ( Fu et al, 2021 ). HIF-1α inhibits plasmacytoid DC (pDC) differentiation, leading to tumor progression ( Labiano et al, 2015 ).…”

Identification of a Novel Prognostic Gene Signature From the Immune Cell Infiltration Landscape of Osteosarcoma

“…In addition, more and more studies are involved. For example, in the nine studies (Cao et al, 2020;Chen Z. et al, 2020;Song et al, 2020;Wen et al, 2020;Xiao et al, 2020;Yu et al, 2020;Zhu et al, 2020;Fu et al, 2021;Yang et al, 2021) we included in the study based on the inclusion criteria, they all looked for potential survival-related OS gene signatures from public datasets.However, after we validated them in the training and validation cohorts, we found that the nine-gene signature we generated was superior to others in predicting OS prognosis. Among the nine studies, the one by Yang et al (2021)revealed a gene signature that closely resembled ours.…”

Tumor hypoxia: an important regulator of tumor progression or a potential modulator of tumor immunogenicity?

“…Studies in cancer patient cohorts have similarly correlated the presence of hypoxia with an immunosuppressed TME in breast cancer, 45 , 46 clear cell renal cell carcinoma, 47 colorectal cancer, 48 hepatocellular carcinoma, 49–51 melanoma, 52 osteosarcoma, 53 neuroblastoma 43 and pancreatic cancer, 41 , 54 among others. 55 These studies used hypoxia gene signatures to determine the hypoxic state and immune fraction or gene set enrichment analysis to highlight the immune microenvironment.…”