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). We sequentially used the univariate, least absolute shrinkage and selector operation (LASSO), and multivariate Cox regression analyses to build a gene signature. The Kaplan-Meier curve and the area under the 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. 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. 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.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9280409PMC
http://dx.doi.org/10.3389/fgene.2022.862179DOI Listing

Publication Analysis

Top Keywords

gene signature
24
autophagy-related gene
12
diffuse large
8
large b-cell
8
b-cell lymphoma
8
survival outcomes
8
gsea analysis
8
estimate ssgsea
8
high-risk group
8
signature
6

Similar Publications

Background: Alzheimer's disease (AD) presents challenges with its complex neurodegenerative mechanisms, leading to a high failure rate in clinical trials. While drug repositioning offers a cost-effective solution, the lack of a subtype-driven strategy hinders success. Previously, we defined genetic subtypes and their prioritized genes for each genetic subtype (Sahelijo et al.

View Article and Find Full Text PDF

Introduction: Ovarian Cancer (OC) was known for its high mortality rate among gynecological malignancies, often resulting in a poor prognosis. This study sought to identify prognostic necroptosis-related long non-coding RNAs (lncRNAs) (NRlncRNAs) with prognostic potential and to construct a reliable risk prediction model for OC patients.

Method: The transcriptome and clinic data were sourced from TCGA and GTEx databases.

View Article and Find Full Text PDF

Background: Stomach adenocarcinoma (STAD) is the fifth most common tumor worldwide, imposing a significant disease burden on populations, particularly in Asia. Oxidative stress is well-known to play an essential role in the occurrence and progression of malignancies. Our study aimed to construct a prediction model by exploring the correlation between oxidative stress-related genes and the prognosis of patients with STAD.

View Article and Find Full Text PDF

The ubiquitin-proteasome system influences cancer progression through multiple mechanisms. Due to the extensive proteasomal modifications observed in cancer tissues, ubiquitination is closely related to various biological functions with cancer. However, the roles of ubiquitin-related genes (UbRGs) in breast cancer (BC) have not been thoroughly investigated.

View Article and Find Full Text PDF

In prokaryotes, DNA methylation plays roles in DNA repair, gene expression, cell cycle progression, and immune recognition of foreign DNA. Genome-wide methylation patterns can vary between strains, influencing phenotype, and gene transfer. However, broader evolutionary studies on bacterial epigenomic variation remain limited.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!