Identification of ASMTL-AS1 and LINC02604 lncRNAs as novel biomarkers for diagnosis of colorectal cancer.

PURPOSE: Colorectal cancer is one of the major leading causes of death worldwide, and available treatments for advanced colorectal cancer are not successful. Therefore, early detection of colorectal cancer is essential to improve patient survival, and biomarkers are potential tools to achieve this goal. Considering the key role of lncRNAs in cancers, the aim of this study is to identify lncRNAs involved in colorectal cancer as new potential prognosis biomarkers for CRC. METHODS: In this observational study, gene expression data obtained from the TCGA database were analyzed, Identification of differentially expressed mRNAs, miRNAs, and lncRNAs was performed, and ceRNA network was drawn. Also, survival analysis of patients was performed in order to identify potential biomarkers related to the diagnosis and prognosis of colon cancer. After confirming the results using the GSE39582 dataset, the expression of target lncRNAs in colorectal tumor tissues was also investigated to confirm the bioinformatic data. RESULTS: Analysis of the TCGA data showed that the expression of three lncRNAs-SNHG7, ASMTL-AS1, and LINC02604-that had the highest interaction with other miRNAs and mRNAs identified based on the ceRNA network was increased in colorectal cancer. Also, based on the ceRNA network, three microRNAs, hsa-let-7d-5p, hsa-mir-92a-3p, and hsa-mir-423-5p, and eight mRNAs, including CPA4, MSI2, RRM2, IGF2BP1, ONECUT2, HMGA1, SOX4, and SRM, were associated with all three mentioned lncRNAs, the expression of microRNAs was decreased and the expression of mRNAs was increased. By enrichment analysis, it was found that the target lncRNAs are involved in the processes of cell proliferation, apoptosis, and metastasis, indicating their importance in the development and malignancy of colorectal cancer. Furthermore, Kaplan-Meier analysis showed a significant increase in mortality in patients with higher expression levels of these lncRNAs. Analysis of the GSE39582 dataset, and real-time RT-PCR analysis, confirmed our bioinformatic results. Also, ROC analysis showed that SNHG7 was a relatively good promising biomarker (AUC = 0.73, p value = 0.02), while ASMTL-AS1 (AUC = 0.92, p value < 0.0001) and LINC02604 (AUC = 1.00, p value < 0.0001) emerged as excellent diagnostic biomarkers in colorectal cancer. CONCLUSION: It seems that increased expression of lncRNAs ASMTL-AS1 and LINC02604 can serve as molecular biomarkers for CRC, possibly through the sponge hsa-let-7d-5p, hsa-mir-92a-3p, and hsa-mir-423 5p, which increases target mRNAs, which are effective in the carcinogenesis process.

Integrative bioinformatics analysis reveals ECM and nicotine-related genes in both LUAD and LUSC, but different lung fibrosis-related genes are involved in LUAD and LUSC.

There are several bioinformatics studies related to lung cancer, but most of them have mainly focused on either microarray data or RNA-Seq data alone. In this study, we have combined both types of data to identify differentially expressed genes (DEGs) specific to lung cancer subtypes. We obtained six microarray datasets from the GEO and also the expression matrix of LUSC and LUAD from TCGA, which were analyzed by GEO2R tool and GEPIA2, respectively. Enrichment analyses of DEGs were performed using the Enrichr database. Protein module identification was done by MCODE plugin in cytoscape software. We identified 30 LUAD-specific, 17 LUSC-specific, and 17 DEGs shared between LUAD and LUSC. Enrichment analyses revealed that LUSC-specific DEGs are involved in lung fibrosis. In addition, DEGs shared between LUAD and LUSC are involved in extracellular matrix (ECM), nicotine metabolism, and lung fibrosis. We identified lung fibrosis-related genes, including SPP1, MMP9, and CXCL2, involved in both LUAD and LUSC, but SERPINA1 and PLAU genes involved only in LUSC. We also found an important module separately for LUAD-specific, LUSC-specific, and shared DEGs between LUSC and LUAD. S100P, GOLM, AGR2, AK1, TMEM125, SLC2A1, COL1A1, and GHR genes were significantly associated with survival. Our findings suggest that different lung fibrosis-related genes may play roles in LUSC and LUAD. Additionally, nicotine metabolism and ECM remodeling were found to be associated with both LUSC and LUAD, regardless of subtype, emphasizing the role of smoking in the development of lung cancer and ECM in the high aggressiveness and mortality of lung cancer.