Ali Rajabi, Ali Rajabi, Maryam Ghaffari Laleh, Reza Safaralizadeh, Asma Rajabi, Asma Rajabi, Samaneh Tayefeh-Gholami, Ali Saber
Abstract Background Diffuse Large B-cell lymphoma (DLBCL) is subdivided into the Germinal Center B-cell (GCB) and non-Germinal Center B-cell (non-GCB)/Activated B-cell (ABC) subtypes, with significant clinical, phenotypic, and genetic variability. Investigating DLBCL’s molecular mechanisms and developing tailored treatment strategies at the molecular level could improve diagnostic precision and treatment outcomes. Advances in sequencing technologies have enabled the identification of numerous lncRNAs with abnormal expression in DLBCL. This study aimed to identify lncRNAs with diagnostic potential in DLBCL using bioinformatics, confirmed through laboratory experiments. Method The gene expression dataset for GSE207388 was obtained from the Gene Expression Omnibus database. Significance analysis of the RNA sequencing algorithm was used to identify differentially expressed genes (DEGs), followed by GO and KEGG enrichment analyses of co-expressed genes. Lymph node tissue specimens were collected from 261 DLBCL patients and 123 controls at two hospitals in Iran between 2023 and 2024. Quantitative real-time PCR was performed to evaluate gene expression, and ROC curve analysis was conducted to assess the diagnostic potential of the selected lncRNAs. Results & conclusion The dataset included the expression profiles of 19,305 genes, of which 299 were selected using the cut-off criteria of fold change > 2 and p ≤ 0.001. Based on GO and KEGG enrichment analyses, four key lncRNAs—ROCR, CFLAR-AS1, ST7-AS1, and ST7-AS2—were selected for further analysis. Elevated expression levels of ROCR, CFLAR-AS1, ST7-AS1, and ST7-AS2 were observed when comparing DLBCL versus control groups and non-GCB versus GCB subtypes. Additionally, ROC curve analysis revealed the strong diagnostic potential of these lncRNAs, particularly ST7-AS2. These findings significantly enhance our understanding of the molecular mechanisms underlying DLBCL, potentially leading to more precise therapeutic strategies.