Research Paper Volume 13, Issue 19 pp 22947—22962

A novel prognostic signature based on immune-related genes of diffuse large B-cell lymphoma

Zizheng Wu1, *, , Qingpei Guan1, *, , Xue Han1, *, , Xianming Liu1, , Lanfang Li1, , Lihua Qiu1, , Zhengzi Qian1, , Shiyong Zhou1, , Xianhuo Wang1, , Huilai Zhang1, ,

  • 1 Departments of Lymphoma, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center of Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin’s Clinical Research Center for Cancer, Sino-US Center for Lymphoma and Leukemia Research, Tianjin 300060, China
* Equal contribution

Received: May 20, 2021       Accepted: September 18, 2021       Published: October 5, 2021      

https://doi.org/10.18632/aging.203587
How to Cite

Copyright: © 2021 Wu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Diffuse large B-cell lymphoma (DLBCL) presents a great clinical challenge and has a poor prognosis, with immune-related genes playing a crucial role. We aimed to develop an immune-related prognostic signature for improving prognosis prediction in DLBCL.

Samples from the GSE31312 dataset were randomly allocated to discovery and internal validation cohorts. Univariate Cox, random forest, LASSO regression and multivariate Cox analyses were utilized to develop a prognostic signature, which was verified in the internal validation cohort, entire validation cohort and external validation cohort (GSE10846). The tumor microenvironment was investigated using the CIBERSORT and ESTIMATE tools. Gene set enrichment analysis (GSEA) was further applied to analyze the entire GSE31312 cohort. We identified four immune-related genes (CD48, IL1RL, PSDM3, RXFP3) significantly associated with overall survival. Based on discovery and validation cohort analyses, this four-gene signature could classify patients into high- and low-risk groups, with significantly different prognoses. Activated memory CD4 T cells and activated dendritic cells were significantly decreased in the high-risk group, and these patients had lower immune scores. GSEA revealed enrichment of signaling pathways, such as T cell receptor, antigen receptor-mediated, antigen processing and presentation of peptide antigen via MHC class I, in the low-risk group. In conclusion, a robust signature based on four immune-related genes was successfully constructed for predicting prognosis in DLBCL patients.

Abbreviations

DLBCL: diffuse large B-cell lymphoma; ECOG: Eastern Cooperative Oncology Group; LDH: lactate dehydrogenase; GCB: germinal center B-cell-like lymphoma; ABC: activated B-cell-like; UC: unclassified type; OS: overall survival; CI: confidence interval; HR: hazard ratio; NES: normalized enrichment score; FDR: false discovery rate; DC: discovery cohort; IVC: internal validation cohort; EGC: entire GSE31312 cohort; PS: prognostic signature; RS: risk score.