Lipoic acid synthetase (LIAS) has been demonstrated to play a crucial role in the progression of cancer. Exploring the underlying mechanisms and biological functions of LIAS could have potential therapeutic guidance for cancer treatment. Our study has explored the expression levels and prognostic values of LIAS in pan-cancer through several bioinformatics platforms, including TIMER2.0, Gene Expression Profiling Interactive Analysis, version 2 (GEPIA2.0), and Human Protein Atlas (HPA). We found that a high LIAS expression was related to the good prognosis in patients with kidney renal clear cell carcinoma (KIRC), rectum adenocarcinoma (READ), breast cancer, and ovarian cancer. Inversely, a high LIAS expression showed unfavorable prognosis in lung cancer patients. In addition, the genetic alteration, methylation levels, and immune analysis of LIAS in pan-cancer have been evaluated. To elucidate the underlying molecular mechanism of LIAS, we conduct the single-cell sequencing to implicate that LIAS expression was related to hypoxia, angiogenesis, and DNA repair. Thus, these comprehensive pan-cancer analyses have conveyed that LIAS could be potentially significant in the progression of various cancers. Moreover, the LIAS expression could predict the efficacy of immunotherapy in cancer patients.

Exosomes are nanovesicles secreted into biofluids by various cell types and have been implicated in different physiological and pathological processes. Interestingly, a plethora of studies emphasized the mediating role of exosomes in the bidirectional communication between donor and recipient cells. Among the various cargoes of exosomes, long non-coding RNAs (lncRNAs) have been identified as crucial regulators between cancer cells and immune cells in the tumor microenvironment (TME) that can interfere with innate and adaptive immune responses to affect the therapeutic efficiency. Recently, a few major studies have focused on the exosomal lncRNA-mediated interaction between cancer cells and immune cells infiltrated into TME. Nevertheless, a dearth of studies pertains to the immune regulating role of exosomal lncRNAs in cancer and is still in the early stages. Comprehensive mechanisms of exosomal lncRNAs in tumor immunity are not well understood. Herein, we provide an overview of the immunomodulatory function of exosomal lncRNAs in cancer and treatment resistance. In addition, we also summarize the potential therapeutic strategies toward exosomal lncRNAs in TME.

Drug metabolism-associated genes have been clarified to play a vital role in the process of cancer cell growth and migration. Nevertheless, the correlation between drug metabolism-associated genes and gastric cancer (GC) has not been fully explored and clarified. This paper has focused on the role of aldehyde dehydrogenase 6 family member A1 (ALDH6A1), a drug metabolism-associated gene, in the immune regulation and prognosis of GC patients. Using several bioinformatics platforms and immunohistochemistry (IHC) assay, we found that ALDH6A1 expression was significantly down-regulated in GC tissues. Moreover, higher expression of ALDH6A1 was related to the better prognosis of GC patients. ALDH6A1 was also found to be involved in the regulation of several immune-associated signatures, including immunoinhibitors. In conclusion, the above results have concluded that aberrant expression of ALDH6A1 might be served as the promising predictor for prognosis and clinical immunotherapy response in GC patients.

Breast cancer (BC) represents one of the most prevalent malignancies among women worldwide. Despite substantial advances in diagnostic and therapeutic modalities and pharmacological interventions in recent years, the accurate assessment of prognosis continues to pose formidable challenges. Exosomes exert pivotal roles in tumorigenesis, tumor progression, and immune modulation, with exosome-related mRNAs emerging as promising novel prognostic biomarkers. Nevertheless, the role of exosome-related mRNA in BC oncogenesis, progression, and prognostic prediction warrants further extensive investigation. The study constructed the exosome-related signature and validated the results in the Gene Expression Omnibus database (GSE9893). Candidate genes were selected based on differential expression, univariate Cox, and LASSO regression to build a prognostic risk model. Its predictive accuracy was evaluated using Kaplan-Meier (K-M) survival curves and time-dependent ROC analysis. Furthermore, the ESTIMATE and CIBERSORT algorithms were employed to elucidate the association between the prognostic risk signature and tumor immune microenvironment (TIME), alongside comparative analyses of HLA gene and immune checkpoint expression differences. GSEA was subsequently conducted to explore the potential biological pathways associated with the prognostic risk signature and individual signature genes. In addition, qRT-PCR was performed in breast cancer cell lines to experimentally validate the expression of signature genes. Finally, a nomogram was developed by combining risk scores with clinical features. Ultimately, four exosome-related mRNAs were identified to construct a prognostic risk signature. In the TCGA cohort, this signature effectively stratified patients into high- and low-risk groups with respect to overall survival (OS), as evidenced by robust predictive performance in ROC analysis. In the GEO validation cohort (GSE9893), results aligned with the training cohor. Immunological analyses showed the risk score's association with the tumor microenvironment (TME), encompassing stromal scores, immune cell abundance, and HLA gene and immune checkpoint levels. In vitro qRT-PCR validation demonstrated expression trends consistent with the computational predictions. The nomogram integrating clinical characteristics demonstrated calibration and substantial clinical utility. This study innovatively developed a BC prognostic risk signature based on exosome-related mRNAs, which not only effectively predicts patient survival but also elucidates its intimate association with the TIME. This signature offers novel insights and substantial clinical utility for personalized prognostic evaluation and treatment decision-making in BC patients.

Objectives: The mechanism of action of genes related to lactate metabolism in papillary thyroid carcinoma (PTC) is still unclear. In this study, key genes that play a role in PTC were selected from the known genes related to lactate metabolism, and their roles in promoting lactate metabolism in PTC cells were investigated. Methods: Through bioinformatics analysis and cell experiments, the roles of the relevant genes in lactate metabolism and their roles in the occurrence and development of PTC were verified. Results: Through bioinformatics analysis, 12 candidate genes were obtained. Through qRT-PCR experiments, it was confirmed that the expressions of TIMP1 and DPP4 were higher in thyroid papillary carcinoma than in normal PTC cells. By inhibiting the expression of TIMP1 and DPP4 using siRNA, the invasion and proliferation abilities of PTC could be reduced. Compared with normal thyroid cells, the contents of lactic acid and LDHA in PTC cells were higher. Knocking down the expression of TIMP1 and DPP4 would reduce the lactate production ability of PTC cells, and TIMP1 and DPP4 promoted the accumulation of lactate in PTC cells.Conclusions: In this study, by screening the differentially expressed lactate metabolism genes in PTC, different prognostic subtypes were constructed based on the molecular expression patterns. Multi-group student’s t-tests were conducted on the differential signaling pathways and tumor immune regulation of the prognostic subtypes, and a PTC prognosis prediction model was constructed. It was further confirmed that the lactate metabolism genes TIMP1 and DPP4 are highly expressed in PTC and can regulate the proliferation, invasion, metastasis and lactate metabolism of PTC cells.

Objectives: The mechanism of action of genes related to lactate metabolism in papillary thyroid carcinoma (PTC) is still unclear. In this study, key genes that play a role in PTC were selected from the known genes related to lactate metabolism, and their roles in promoting lactate metabolism in PTC cells were investigated. Methods: Through bioinformatics analysis and cell experiments, the roles of the relevant genes in lactate metabolism and their roles in the occurrence and development of PTC were verified. Results: Through bioinformatics analysis, 12 candidate genes were obtained. Through qRT-PCR experiments, it was confirmed that the expressions of TIMP1 and DPP4 were higher in thyroid papillary carcinoma than in normal PTC cells. By inhibiting the expression of TIMP1 and DPP4 using siRNA, the invasion and proliferation abilities of PTC could be reduced. Compared with normal thyroid cells, the contents of lactic acid and LDHA in PTC cells were higher. Knocking down the expression of TIMP1 and DPP4 would reduce the lactate production ability of PTC cells, and TIMP1 and DPP4 promoted the accumulation of lactate in PTC cells.