A novel 8-genome instability-associated lncRNAs signature predicting prognosis and drug sensitivity in gastric cancer

Long Non-Coding RNAs in Drug Resistance of Gastric Cancer: Complex Mechanisms and Potential Clinical Applications

Gastric cancer (GC) ranks as the third most prevalent malignancy and a leading cause of cancer-related mortality worldwide. However, the majority of patients with GC are diagnosed at an advanced stage, highlighting the urgent need for effective perioperative and postoperative chemotherapy to prevent relapse and metastasis. The current treatment strategies have limited overall efficacy because of intrinsic or acquired drug resistance. Recent evidence suggests that dysregulated long non-coding RNAs (lncRNAs) play a significant role in mediating drug resistance in GC. Therefore, there is an imperative to explore novel molecular mechanisms underlying drug resistance in order to overcome this challenging issue. With advancements in deep transcriptome sequencing technology, lncRNAs-once considered transcriptional noise-have garnered widespread attention as potential regulators of carcinogenesis, including tumor cell proliferation, metastasis, and sensitivity to chemo- or radiotherapy through multiple regulatory mechanisms. In light of these findings, we aim to review the mechanisms by which lncRNAs contribute to drug therapy resistance in GC with the goal of providing new insights and breakthroughs toward overcoming this formidable obstacle.

Genomic instability-related twelve-microRNA signatures for predicting the prognosis of gastric cancer

Gastric cancer (GC) ranks fifth among all malignant tumors globally, especially in East Asia, and has attracted extensive attention and research. MicroRNA (miRNA) modulation during genomic instability (GI) may be associated with the development and metastasis of malignant tumors. We aimed to identify GI-related miRNA signatures for the prediction of GC prognosis. We constructed a GI-related miRNA signature (GIMiSig) scheme based on The Cancer Genome Atlas (TCGA) training set (n = 389), which was later verified based on the TCGA test set (n = 194). GI-related miRNAs were identified by analyzing somatic mutation profiles and miRNA expression. A GI-related miRNA-gene co-expression network was also constructed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were analyzed to reveal possible biological pathways associated with GI-related miRNAs. The correlation of the GIMiSig with clinical factors of the TCGA dataset was analyzed. MiRNA mimics and inhibitors were used to evaluate the biological functions of miR-100-5p and miR-145-3p in GC cell lines AGS and MKN-45. This study identified a GI-related 12-miRNA signature for the prediction of GC prognosis. GIMiSig scores, similar to tumor stages, showed significant correlations with overall survival (OS, p < 0.05). GIMiSig showed high accuracy in predicting GC prognosis. MiR-100-5p and miR-145-3p promoted cell growth, invasion, and migration but inhibited apoptosis in GC cells. We report a reliable GI-related 12-miRNA signature for predicting GC prognosis. Furthermore, miR-100-5p and miR-145-3p may promote GC cell growth, invasion, and migration.