AUTHOR=Zhou Xuan , He Ying-Zhi , Liu Dan , Lin Chao-Ran , Liang Dan , Huang Rui , Wang Liang 

TITLE=An Autophagy-Related Gene Signature can Better Predict Prognosis and Resistance in Diffuse Large B-Cell Lymphoma

JOURNAL=Frontiers in Genetics

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.862179

DOI=10.3389/fgene.2022.862179

ISSN=1664-8021

ABSTRACT=Background: Diffuse large B-cell lymphoma (DLBCL) is a highly heterogeneous disease, and about 30%-40% of patients will develop relapsed/refractory DLBCL. In this study, we aimed to develop a gene signature to predict survival outcomes of DLBCL patients based on the autophagy-related genes (ARGs).
Methods: We sequentially used the univariate, least absolute shrinkage and selector operation (LASSO) and multivariate Cox regression analysis to build gene signature. Kaplan-Meier curve and the area under receiver operating characteristic curve (AUC) were performed to estimate the prognostic capability of the gene signature. GSEA analysis, estimate and ssGSEA algorithms, and one-class logistic regression were performed to analyze differences in pathways, immune response and tumor stemness between the high and low-risk groups.
Results: Both in the training cohort and validation cohorts, high-risk patients had inferior overall survival compared with low-risk patients. The nomogram consisted of the autophagy-related gene signature and clinical factors had better discrimination of survival outcomes, and it also had a favorable consistency between the predicted and actual survival. GSEA analysis found that patients in the high-risk group were associated with the activation of doxorubicin resistance, NF-κB, cell cycle and DNA replication pathways. The results of estimate, ssGSEA and mRNAsi showed that the high-risk group exhibited lower immune cell infiltration and immune activation responses and had higher similarity to cancer stem cells. 
Conclusions: We proposed a novel and reliable autophagy-related gene signature that was capable of predicting the survival and resistance of patients with DLBCL and could guide individualized treatment in future.