AUTHOR=Liu Chen , Liu Lin 

TITLE=Hypoxia-related tumor environment correlated with immune infiltration and therapeutic sensitivity in diffuse large B-cell lymphoma

JOURNAL=Frontiers in Genetics

VOLUME=13

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.1037716

DOI=10.3389/fgene.2022.1037716

ISSN=1664-8021

ABSTRACT=<p><bold>Background:</bold> Due to the high heterogeneity of diffuse large B-cell lymphoma (DLBCL), traditional chemotherapy treatment ultimately failed in one-third of the patients. Big challenges existed in finding how to accurately predict prognosis and provide individualized treatment. Hypoxia, although being a key factor in the development and progression of DLBCL, plays its role in DLBCL prognosis, which has yet to be fully explored.</p><p><bold>Methods:</bold> Data used in the current study were sourced from the Gene Expression Omnibus (GEO) database. DLBCL patients were divided according to different hypoxia-related subtypes based on the expressions of hypoxia-related genes (HRGs) relevant to survival. Differentially expressed genes (DEGs) between subtypes were identified using the limma package. Using univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analyses, the prognostic signature was established to calculate risk scores. The tumor microenvironment (TME) in low- and high-risk groups was evaluated by single-sample gene set enrichment analysis (ssGSEA) and ESTIMATE. The chemotherapeutic sensitivity in two groups was assessed by IC50 values.</p><p><bold>Results:</bold> DLBCL patients were clustered into two hypoxia-related subtype groups according to different gene survival and expressions associated with increasing oxygen delivery and reducing oxygen consumption, and these two subtype groups were compared. Based on the differential expression, a risk model was established using univariate cox and LASSO regression analyses, FNDC1, ANTXR1, RARRES2, S100A9, and MT1M. The performance of the risk signature in predicting the prognosis of DLBCL patients was validated in the internal and external datasets, as evidenced by receiver operating characteristic (ROC) curves. In addition, we observed significant differences in the tumor microenvironment and chemotherapeutic response between low- and high-risk groups.</p><p><bold>Conclusion:</bold> Our study developed novel hypoxia-related subtypes in DLBCL and identified five prognostic signatures for DLBCL patients. These findings may enrich our understanding of the role of hypoxia in DLBCL and help improve the treatment of DLBCL patients.</p>