Identification of Novel Hypoxia Subtypes for Prognosis Based on Machine Learning Algorithms

Jiawei Wang; Tuo Li; Songquan Wei; Gengye Zhao; Cong Ye; Qiuping Ma; Jinchun Ma; Xiaoyan Cheng

doi:10.1155/2022/1508113

Identification of Novel Hypoxia Subtypes for Prognosis Based on Machine Learning Algorithms

J Oncol. 2022 Sep 12:2022:1508113. doi: 10.1155/2022/1508113. eCollection 2022.

Authors

Jiawei Wang¹, Tuo Li², Songquan Wei³, Gengye Zhao³, Cong Ye⁴, Qiuping Ma⁴, Jinchun Ma⁴, Xiaoyan Cheng¹

Affiliations

¹ Department of Obstetrics and Gynecology, Nantong Maternity and Child Health Care Hospital Affiliated to Nantong University, Nantong 226018, Jiangsu Province, China.
² Department of Endocrinology, Second Affiliated Hospital of Naval Medical University, Shanghai 200003, China.
³ The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510000, China.
⁴ Department of Obstetrics and Gynecology, Soochow University Affiliated Taicang Hospital (The First People's Hospital of Taicang), Suzhou, Jiangsu 215400, China.

Abstract

Objective: A reduced level or tension or the deprivation of oxygen is termed hypoxia. It is common for tumours to outgrow their natural source of nutrients, which causes hypoxia in some tumour regions. Hypoxia affects ovarian cancer (OC) in several ways.

Methods: In this study, the expression patterns of prognostic hypoxia-related genes were curated, and consensus clustering analyses were performed to determine hypoxia subtypes in OC included in The Cancer Genome Atlas cohort. Two hypoxia-related subtypes were observed and considered for further investigation. The analyses of differentially expressed genes (DEGs), gene ontology, mutation, and immune cell infraction were performed to explore the underlying molecular mechanisms.

Results: In total, 377 patients with OC were classified into two subgroups based on the subtype of hypoxia. The clinical outcome was considerably poor for patients with hypoxia subtype 2. DEG and protein-protein interaction analyses revealed that the expression levels of CLIP2 and SH3PXD2A were low in OC tissues. Immune cell infarction analysis revealed that the subtypes were associated with the tumour microenvironment (TME).

Conclusion: Our findings established the existence of two distinctive, complex, and varied hypoxia subtypes in OC. Findings from the quantitative analysis of hypoxia subtypes in patients improved our understanding of the characteristics of the TME and may facilitate the development of more efficient treatment regimens.