Identification of Pyroptosis-Related Signature and Development of a Novel Prognostic Model in Diffuse Large B-Cell Lymphoma

Introduction Pyroptosis is a programmed cell death triggered by inflammatory vesicles, which is manifested by cellular distension until the cell membrane ruptures, leading to the release of cellular contents and thus an intense inflammatory response. Recently, emerging evidence suggests that pyroptosis plays an essential role in the development and progression of multiple cancers. However, the role of pyroptosis in diffuse large B-cell lymphoma (DLBCL) remains elusive. This study aimed to identify the pyroptosis-related signature in DLBCL, construct a novel prognostic model, and further analyze the involved immune infiltration features.

Methods The expression profile data of DLBCL and normal samples of pyroptosis-related genes (PRGs) were analyzed, and the clinical characteristics of 533 DLBCL patients were further investigated. A prognostic model based on six PRGs was established using Cox univariate and LASSO Cox regression analysis. The expression of differential expressed PRGs was validated by qRT-PCR in DLBCL cell lines. Single-sample gene set enrichment analysis (ssGSEA) was applied to compare immune infiltration characteristics in subgroups.

Results: To explore the expression profile characteristics of PRGs in DLBCL, the mRNA expression levels of PRGs were evaluated in DLBCL and normal samples. The results revealed that most PRGs were dysregulated in DLBCL samples. Subsequently, 8 hub genes, including PJVK, TNF, CASP1, CASP3, CASP5, CASP8, NLRP3, and IL18, were screened.

The clinical significance of the PRGs in DLBCL was further evaluated. 19 genes were significantly associated with overall survival (OS) of DLBCL patients in the univariate Cox regression. SCAF11, CASP8, CASP9, NLRP1, NLRP6, and TIRAP were selected for the risk model according to the minimum criteria of the LASSO Cox regression, and DLBCL patients were divided into groups of high and low. The low-risk group exhibited lower mortality rates and longer survival times than the high-risk group (Figure 1A). Significantly shorter OS was observed in DLBCL patients with high risks (Figure 1B). Additionally, the ROC curves indicated the excellent prediction performance of this model. To further verify the expression levels of PRGs in DLBCL, we assessed the mRNA expression levels of the above six PRGs by qRT-PCR in DLBCL cell lines. Compared with normal samples, CASP8, CASP9, NLRP1, NLRP6, and TIRAP were significantly down-regulated in DLBCL cell lines, while SCAF11 was significantly up-regulated. These results revealed the outstanding predictive efficacy and superiority of this model.

The potential biological role and the mechanism of PRGs causing different risks were further explored. GO and KEGG enrichment illuminated that these PRGs may be involved in cellular protein modification processes and regulation of JAK-STAT signaling pathway. Given the strongly correlated JAK-STAT signaling pathway and tumor immune environment, we analyzed the immune status of different risk groups by applying ssGSEA. The low-risk group showed higher activity immune infiltration and immune checkpoint pathways than the high-risk group. We found that the risk scores corresponded with the immune profile, and the elevated immune activity might contribute to the antitumor effect of DLBCL.

Conclusion In summary, our study identified for the first time that pyroptosis is closely associated with the development and progression of DLBCL. A comprehensive prognostic model was developed based on the characteristics of PRGs in DLBCL, which accurately predicts the prognosis of DLBCL patients. Pyroptosis-targeting coupled with immunotherapies would be a promising alternative treatment approach for DLBCL.

Keywords: Pyroptosis, DLBCL, Prognostic model, Immune infiltration features

No relevant conflicts of interest to declare.