ACSM3 suppresses the pathogenesis of high-grade serous ovarian carcinoma via promoting AMPK activity

Liver ACSM3 deficiency mediates metabolic syndrome via a lauric acid-HNF4α-p38 MAPK axis

Metabolic syndrome combines major risk factors for cardiovascular disease, making deeper insight into its pathogenesis important. We here explore the mechanistic basis of metabolic syndrome by recruiting an essential patient cohort and performing extensive gene expression profiling. The mitochondrial fatty acid metabolism enzyme acyl-CoA synthetase medium-chain family member 3 (ACSM3) was identified to be significantly lower expressed in the peripheral blood of metabolic syndrome patients. In line, hepatic ACSM3 expression was decreased in mice with metabolic syndrome. Furthermore, Acsm3 knockout mice showed glucose and lipid metabolic abnormalities, and hepatic accumulation of the ACSM3 fatty acid substrate lauric acid. Acsm3 depletion markedly decreased mitochondrial function and stimulated signaling via the p38 MAPK pathway cascade. Consistently, Acsm3 knockout mouse exhibited abnormal mitochondrial morphology, decreased ATP contents, and enhanced ROS levels in their livers. Mechanistically, Acsm3 deficiency, and lauric acid accumulation activated nuclear receptor Hnf4α-p38 MAPK signaling. In line, the p38 inhibitor Adezmapimod effectively rescued the Acsm3 depletion phenotype. Together, these findings show that disease-associated loss of ACSM3 facilitates mitochondrial dysfunction via a lauric acid-HNF4a-p38 MAPK axis, suggesting a novel therapeutic vulnerability in systemic metabolic dysfunction.

The fatty acid-related gene signature stratifies poor prognosis patients and characterizes TIME in cutaneous melanoma

BACKGROUND

The aim of this study is to build a prognostic model for cutaneous melanoma (CM) using fatty acid-related genes and evaluate its capacity for predicting prognosis, identifying the tumor immune microenvironment (TIME) composition, and assessing drug sensitivity.

METHODS

Through the analysis of transcriptional data from TCGA-SKCM and GTEx datasets, we screened for differentially expressed fatty acids-related genes (DEFAGs). Additionally, we employed clinical data from TCGA-SKCM and GSE65904 to identify genes associated with prognosis. Subsequently, utilizing all the identified prognosis-related fatty acid genes, we performed unsupervised clustering analysis using the ConsensusClusterPlus R package. We further validated the significant differences between subtypes through survival analysis and pathway analysis. To predict prognosis, we developed a LASSO-Cox prognostic signature. This signature's predictive ability was rigorously examined through multivariant Cox regression, survival analysis, and ROC curve analysis. Following this, we constructed a nomogram based on the aforementioned signature and evaluated its accuracy and clinical utility using calibration curves, cumulative hazard rates, and decision curve analysis. Using this signature, we stratified all cases into high- and low-risk groups and compared the differences in immune characteristics and drug treatment responsiveness between these two subgroups. Additionally, in this study, we provided preliminary confirmation of the pivotal role of CD1D in the TIME of CM. We analyzed its expression across various immune cell types and its correlation with intercellular communication using single-cell data from the GSE139249 dataset.

RESULTS

In this study, a total of 84 DEFAGs were identified, among which 18 were associated with prognosis. Utilizing these 18 prognosis-related genes, all cases were categorized into three subtypes. Significant differences were observed between subtypes in terms of survival outcomes, the expression of the 18 DEFAGs, immune cell proportions, and enriched pathways. A LASSO-Cox regression analysis was performed on these 18 genes, leading to the development of a signature comprising 6 DEFAGs. Risk scores were calculated for all cases, dividing them into high-risk and low-risk groups. High-risk patients exhibited significantly poorer prognosis than low-risk patients, both in the training group (p < 0.001) and the test group (p = 0.002). Multivariate Cox regression analysis indicated that this signature could independently predict outcomes [HR = 2.03 (1.69-2.45), p < 0.001]. The area under the ROC curve for the training and test groups was 0.715 and 0.661, respectively. Combining risk scores with clinical factors including metastatic status and patient age, a nomogram was constructed, which demonstrated significant predictive power for 3  and 5 years patient outcomes. Furthermore, the high and low-risk subgroups displayed differences in the composition of various immune cells, including M1 macrophages, M0 macrophages, and CD8+ T cells. The low-risk subgroup exhibited higher StromalScore, ImmuneScore, and ESTIMATEScore (p < 0.001) and demonstrated better responsiveness to immune therapy for patients with PD1-positive and CTLA4-negative or positive expressions (p < 0.001). The signature gene CD1D was found to be mainly expressed in monocytes/macrophages and dendritic cells within the TIME. Through intercellular communication analysis, it was observed that cases with high CD1D expression exhibited significantly enhanced signal transductions from other immune cells to monocytes/macrophages, particularly the (HLA-A/B/C/E/F)-CD8A signaling from natural killer (NK) cells to monocytes/macrophages (p < 0.01).

CONCLUSIONS

The prognostic signature constructed in this study, based on six fatty acid-related genes, exhibits strong capabilities in predicting patient outcomes, identifying the TIME, and assessing drug sensitivity. This signature can aid in patient risk stratification and provide guidance for clinical treatment strategies. Additionally, our research highlights the crucial role of CD1D in the CM's TIME, laying a theoretical foundation for future related studies.

A novel lipid metabolism-based risk model associated with immunosuppressive mechanisms in diffuse large B-cell lymphoma

BACKGROUND

The molecular diversity exhibited by diffuse large B-cell lymphoma (DLBCL) is a significant obstacle facing current precision therapies. However, scoring using the International Prognostic Index (IPI) is inadequate when fully predicting the development of DLBCL. Reprogramming lipid metabolism is crucial for DLBCL carcinogenesis and expansion, while a predictive approach derived from lipid metabolism-associated genes (LMAGs) has not yet been recognized for DLBCL.

METHODS

Gene expression profiles of DLBCL were generated using the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. The LASSO Cox regression was used to construct an effective predictive risk-scoring model for DLBCL patients. The Kaplan-Meier survival assessment was employed to compare a given risk score with the IPI score and its impact on the survival of DLBCL patients. Functional enrichment examination was performed utilizing the KEGG pathway. After identifying hub genes via single-sample GSEA (ssGSEA), immunohistochemical staining and immunofluorescence were performed on lymph node samples from control and DLBCL patients to confirm these identified genes.

RESULTS

Sixteen lipid metabolism- and survival-associated genes were identified to construct a prognostic risk-scoring approach. This model demonstrated robust performance over various datasets and emerged as an autonomous risk factor for predicting the development of DLBCL patients. The risk score could significantly distinguish the development of DLBCL patients from the low-risk and elevated-risk IPI classes. Results from the inhibitory immune-related pathways and lower immune scores suggested an immunosuppressive phenotype within the elevated-risk group. Three hub genes, MECR, ARSK, and RAN, were identified to be negatively correlated with activated CD8 T cells and natural killer T cells in the elevated-risk score class. Ultimately, it was determined that these three genes were expressed by lymphoma cells but not by T cells in clinical samples from DLBCL patients.

CONCLUSION

The risk level model derived from 16 lipid metabolism-associated genes represents a prognostic biomarker for DLBCL that is novel, robust, and may have an immunosuppressive role. It can compensate for the limitations of the IPI score in predicting overall survival and has potential clinical application value.

FAK inhibitor PF-562271 inhibits the migration and proliferation of high-grade serous ovarian cancer cells through FAK and FAK mediated cell cycle arrest

Focal adhesion kinase (FAK) is a promising therapeutic target for various cancers and its inhibitor development is in full swing. PF-562271 is a classic FAK inhibitor that has shown promising preclinical data and has been found to exhibit an anti-migration effect on some cancer cells. However, its anticancer effect on high-grade serous ovarian cancer (HGSOC) has not been reported. In this study, we evaluated the anti-migration and anti-proliferation effects of PF-562271 against HGSOC SKOV3 and A2780 cells, as well as the underlying mechanism. The results demonstrated that FAK was overexpressed in clinical HGSOC tissues and was positively correlated with the pathological progression of HGSOC. Moreover, HGSOC patients with high FAK expression levels exhibited low survival rates. PF-562271 treatment significantly inhibited the cell adhesion and migration of SKOV3 and A2780 cells by inhibiting p-FAK expression and decreasing the FA surface area. Additionally, PF-562271 treatment inhibited colony formation and induced cell senescence through G1 phase cell cycle arrest mediated DNA replication inhibition. Taken together, the findings demonstrated that FAK inhibitor PF-562271 significantly inhibits HGSOC cell adhesion, migration, and proliferation process through FAK and/or FAK mediated cell cycle arrest, and suggested that PF-562271 could serve as a potential oncotherapeutic agent for HGSOC targeting treatment.

ACSM6 overexpression indicates a non-inflammatory tumor microenvironment and predicts treatment response in bladder cancer: results from multiple real-world cohorts

Background: ACSMs play critical roles in lipid metabolism; however, their immunological function within the tumor microenvironment (TME) remains unclear, especially that of ACSM6. In this study, we investigate the latent effect of ACSM6 on bladder cancer (BLCA). Methods: Several real-world cohorts, including the Xiangya (in-house), The Cancer Genome Atlas (TCGA-BLCA), and IMvigor210 cohorts, with TCGA-BLCA cohort serving as the discovery cohort were compared. We investigated the potential immunological effects of ACSM6 in regulating the BLCA tumor microenvironment by analyzing its correlation with immunomodulators, anti-cancer immune cycles, immune checkpoints, tumor-infiltrating immune cells, and the T-cell inflamed score (TIS). Additionally, we assessed the precision of ACSM6 in predicting BLCA molecular subtypes and responses to several treatments using ROC analysis. To ensure the robustness of our findings, all results were confirmed in two independent external cohorts: the IMvigor210 and Xiangya cohorts. Results: ACSM6 expression was markedly upregulated in BLCA. Our analysis suggests that ACSM6 might have significant impact to promote the formation of a non-inflamed tumor microenvironment because of its negative correlation with immunomodulators, anticancer immune cycles, immune checkpoints, tumor-infiltrating immune cells, and the T-cell inflamed score (TIS). Additionally, high ACSM6 expression levels in BLCA may predict the luminal subtype, which is typically associated with resistance to chemotherapy, neoadjuvant chemotherapy, and radiotherapy. These findings were consistent across both the IMvigor210 and Xiangya cohorts. Conclusion: ACSM6 has the potential to serve as a valuable predictor of the tumor microenvironment phenotypes and treatment outcomes in BLCA, thereby contributing to more precise treatment.

ACSM3 suppresses proliferation and induces apoptosis and cell cycle arrest in acute myeloid leukemia cells via the regulation of IGF2BP2

Acyl-CoA medium-chain synthetase-3 (ACSM3) has been reported to be involved in the malignant progression of multiple types of human cancer. Nevertheless, the role of ACSM3 in acute myeloid leukemia (AML) and its exact mechanism of action are as yet undefined. In the present study, the expression levels of ACSM3 and IGF2 mRNA-binding protein 2 (IGF2BP2) were evaluated using the Gene Expression Profiling Interactive Analysis database and AML cells. The Cell Counting Kit-8 assay and 5-ethynyl-2'-deoxyuridine staining were employed for the estimation of the cell proliferative activity. Induction of apoptosis and the assessment of the cell cycle were measured using flow cytometry and western blotting, respectively. The interaction of ACSM3 with IGF2BP2 was confirmed using an RNA immunoprecipitation assay. mRNA stabilization of ACSM3 following actinomycin D treatment was evaluated using reverse transcription-quantitative PCR analysis. The data indicated that the expression levels of ACSM3 were significantly downregulated, whereas those of IGF2BP2 were upregulated in tissues and AML cells. Downregulation of ACSM3 expression was closely associated with poor overall survival of patients with AML. ACSM3 overexpression repressed cell proliferative activity and induced apoptosis and cell cycle arrest. IGF2BP2 downregulated ACSM3 expression by reducing the stability of ACSM3 mRNA. In addition, IGF2BP2 overexpression counteracted the effects of ACSM3 overexpression noted on proliferation, induction of apoptosis and cell cycle arrest of HL-60 cells. In conclusion, ACSM3 repressed the cell proliferative activity and facilitated induction of apoptosis and cell cycle arrest in AML cells by modulating the expression of IGF2BP2.