Identification and Assessment of Necroptosis-Related Genes in Clinical Prognosis and Immune Cells in Diffuse Large B-Cell Lymphoma - Zhang, Qikai; Zhu, Zongsi; Guan, Jiaqiang; Zheng, Cuiping (Frontiers in Oncology, 2022)
Background With the unveiling of new mechanisms and the advent of new drugs, the prognosis of DLBCL becomes promising, but some patients still progress to relapse or refractory stage. Necroptosis, as a relatively novel programmed cell death, involves the development of multiple tumors. There are no relevant studies on the prognostic significance of necroptosis in DLBCL to date. Methods We identified the differential necroptosis-related genes (NRGs) by comparing the DLBCL and normal control in GSE12195 and GSE56315. TCGA DLBC and GSE10846 containing clinical information and microarray expression profiling were merged as the entire cohort. We performed consensus clusters based on NRGs and two clusters were obtained. Kaplan-Meier survival analysis (K-M), GSVA, GO, KEGG, and ssGSEA were used to analyze the survival, function, and immune microenvironment between two clusters. With LASSO and proportional hazards model construction, we identified differentially expressed genes (DEGs) between NRG clusters, calculated the risk score, established a prognostic model, and validated its value by calibration and ROC curves. The entire cohort was divided into training and test cohort, and GSE87371 was an external validation cohort. K-M, copy number variation, tumor mutation burden, and drug sensitivity were analyzed, too. Results We found significant prognosis differences between the two NRG clusters. The cluster A with a poor prognosis had decreased expression of NRGs and a relatively suppressed immune microenvironment. GSVA analysis indicated that cluster A related to the downregulation of the TGF-β signal pathway and the activation of the Notch signal pathway. The risk score had an accurate predictive ability. The nomogram could help predict the survival probability of DLBCL patients. γ/δ T cell and Macrophage 1 cell decreased while Macrophage 2 cell and Natural Killer resting cell increased in the high-risk group. In addition, the high-risk group was more sensitive to PI3K inhibitor and PEK inhibitor. Conclusion We explored the potential role of necroptosis in DLBCL from multiple angles and provided a prognostic nomogram for the survival prediction of DLBCL. Our study may deepen the understanding and facilitate the new therapy targets for DLBCL.