Different opinion on the reported role of Poldip2 and ACSM1 in a mammalian lipoic acid salvage pathway controlling HIF-1 activation

METTL3-mediated m6A modification of ZNF384 promotes hepatocellular carcinoma progression by transcriptionally activating ACSM1

BACKGROUND

Hepatocellular carcinoma (HCC) is a lethal disease with a high mortality rate, and its development is influenced by various molecular mechanisms. Zinc finger protein 384 (ZNF384) has been reported to be involved in the progression of several cancers; however, its role in HCC remains elusive.

METHODS

mRNA expression levels were analyzed by quantitative real-time polymerase chain reaction, while western blotting and immunohistochemistry were performed to validate protein expression. Cell proliferation, apoptosis, and metabolic activities were examined using clonogenicity, flow cytometry, and specific assay kits. A xenograft mouse model was employed to assess the impact of acyl-CoA synthetase medium-chain family member 1 (ACSM1) depletion on HCC cell malignancy in vivo. Chromatin immunoprecipitation assay and dual-luciferase reporter assay were conducted to explore the association between ZNF384 and ACSM1.

RESULTS

We found that ACSM1 and ZNF384 were significantly upregulated in HCC tissues and cells when compared with normal liver tissues and human liver immortalized cells. Knockdown of ACSM1 inhibited HCC cell proliferation and glucose metabolism and induced cell apoptosis. Furthermore, ACSM1 depletion suppressed the malignant progression of HCC cells in vivo. Our data indicated that ZNF384 transcriptionally activated ACSM1 in HCC cells. Overexpression of ACSM1 reversed the inhibitory effect of ZNF384 depletion on HCC cell malignancy. Further, methyltransferase-like 3 (METTL3) stabilized ZNF384 mRNA through m6A methylation.

CONCLUSION

METTL3-mediated m6A modification of ZNF384 contributed to the progression of HCC by transcriptionally activating ACSM1. This finding suggests potential therapeutic targets for this devastating disease.

Establishing a prediction model of severe acute mountain sickness using machine learning of support vector machine recursive feature elimination

Severe acute mountain sickness (sAMS) can be life-threatening, but little is known about its genetic basis. The study was aimed to explore the genetic susceptibility of sAMS for the purpose of prediction, using microarray data from 112 peripheral blood mononuclear cell (PBMC) samples of 21 subjects, who were exposed to very high altitude (5260 m), low barometric pressure (406 mmHg), and hypobaric hypoxia (VLH) at various timepoints. We found that exposure to VLH activated gene expression in leukocytes, resulting in an inverted CD4/CD8 ratio that interacted with other phenotypic risk factors at the genetic level. A total of 2286 underlying risk genes were input into the support vector machine recursive feature elimination (SVM-RFE) system for machine learning, and a model with satisfactory predictive accuracy and clinical applicability was established for sAMS screening using ten featured genes with significant predictive power. Five featured genes (EPHB3, DIP2B, RHEBL1, GALNT13, and SLC8A2) were identified upstream of hypoxia- and/or inflammation-related pathways mediated by microRNAs as potential biomarkers for sAMS. The established prediction model of sAMS holds promise for clinical application as a genetic screening tool for sAMS.

Oncogenic ACSM1 in prostate cancer is through metabolic and extracellular matrix-receptor interaction signaling pathways

Acyl-coenzyme A synthetase medium chain family member 1 (ACSM1) is a medium chain Acyl-CoA Synthetase family member and plays an important role in fatty acid metabolism. The oncogenic roles of ACSM1 are largely unknown. Using comprehensive approaches, we analyzed gene expression profiles and genomic datasets and identified that the expression of ACSM1 was specifically increased in prostate cancer in comparison to the adjacent non-tumor tissues. The increased expression of ACSM1 was associated with increased risks of poor prognosis and shorter survival time. Moreover, genomic copy number alterations of ACSM1, including deletion, amplification, and amino acid changes were frequently observed in prostate cancers, although these mutations did not correlate with gene expression levels. However, ACSM1 gene amplifications were significantly corrected with increased risks of prostate cancer metastasis, and ACSM1 genetic alterations were significantly associated with worse disease-free. And progress-free survival. Gene function stratification and gene set enrichment analysis revealed that the oncogenic roles of ACSM1 in prostate cancer were mainly through metabolic pathways and extracellular matrix (ECM)-receptor interaction signaling pathways, but not associated with microenvironmental immunological signaling pathways, and that ACSM1 expression was not associated with immune cell infiltration in the cancer microenvironment or prostate cancer immune subtypes. In conclusion, the present work has demonstrated that ACSM1 can be specifically and significantly elevated in prostate cancer. ACSM1 gene expression and genomic amplification exhibit important clinical significance through metabolic and ECM-receptor interaction signaling pathways. Thus, ACSM1 may be a novel oncogene and serve as a biomarker for prostate cancer screening and prognosis prediction, and/or a therapeutic target.