Significance of Spliceosome-Related Genes in the Prediction of Prognosis and Treatment Strategies for Lung Adenocarcinoma

Construction of a prognostic model for lung adenocarcinoma based on m6A/m5C/m1A genes

BACKGROUND

Developing a prognostic model for lung adenocarcinoma (LUAD) that utilizes m6A/m5C/m1A genes holds immense importance in providing precise prognosis predictions for individuals.

METHODS

This study mined m6A/m5C/m1A-related differential genes in LUAD based on public databases, identified LUAD tumor subtypes based on these genes, and further built a risk prognostic model grounded in differential genes between subtypes. The immune status between high- and low-risk groups was investigated, and the distribution of feature genes in tumor immune cells was analyzed using single-cell analysis. Based on the expression levels of feature genes, a projection of chemotherapeutic and targeted drugs was made for individuals identified as high-risk. Ultimately, cell experiments were further verified.

RESULTS

The 6-gene risk prognosis model based on differential genes between tumor subtypes had good predictive performance. Individuals classified as low-risk exhibited a higher (P < 0.05) abundance of infiltrating immune cells. Feature genes were mainly distributed in tumor immune cells like CD4+T cells, CD8+T cells, and regulatory T cells. Four drugs with relatively low IC50 values were found in the high-risk group: Elesclomol, Pyrimethamine, Saracatinib, and Temsirolimus. In addition, four drugs with significant positive correlation (P < 0.001) between IC50 values and feature gene expression were found, including Alectinib, Estramustine, Brigatinib, and Elesclomol. The low expression of key gene NTSR1 reduced the IC50 value of irinotecan.

CONCLUSION

Based on the m6A/m5C/m1A-related genes in LUAD, LUAD patients were divided into 2 subtypes, and a m6A/m5C/m1A-related LUAD prognostic model was constructed to provide a reference for the prognosis prediction of LUAD.

The mechanism of LSM2 in the progression of live hepatocellular carcinoma was analyzed based on bioinformatics

Comprehensive analysis of the expression and probable function of LSM2 in Live hepatocellular carcinoma (LIHC), and validation via in vitro experiments. Integrated use of database resources to examine the differential expression, survival prognosis, clinicopathological characteristics, and functional enrichment of LSM2 in LIHC. The expression level of LSM2 in LIHC tissues and adjacent tissues was proven via immunohistochemical staining. The biological function of LSM2 in LIHC was detected by cell proliferation, cell cloning, cell scratch, cell migration, and invasion experiments in vitro. TIMER 2.0 and GEPIA indicated that LSM2 was highly expressed in cancers and was strongly associated with survival rates in LIHC, cholangiocarcinoma, breast cancer, and renal clear cell carcinoma. LSM2 was highly expressed in LIHC, which was closely associated to the clinicopathological characteristics of patients, and the overall survival rate and disease-free survival rate of patients with high expression of LSM2 were lower than those with low expression of LSM2. Functional enrichment results revealed that LSM2 was involved to ribosome formation, DNA replication, cell cycle, metabolic processes, JAK-STAT signaling pathways, and FoxO signaling pathways. Knockdown of LSM2 inhibited the proliferation, migration, and invasion of LIHC cells in vitro experiments. LSM2 was highly expressed in LIHC and was related to a poor prognosis. Knockdown of LSM2 could inhibit the proliferation, migration, and invasion of LIHC cells.