Loss of ACSM3 confers worsened prognosis and immune exclusion to cutaneous melanoma

Delineation of renal protein profiles in aristolochic acid I-induced nephrotoxicity in mice by label-free quantitative proteomics

Introduction: Aristolochic acid nephropathy (AAN) is a kidney injury syndrome caused by aristolochic acids exposure. Our study used label-free quantitative proteomics to delineate renal protein profiles and identify key proteins after exposure to different doses of aristolochic acid I (AAI). Methods: Male C57BL/6 mice received AAI (1.25 mg/kg/d, 2.5 mg/kg/d, or 5 mg/kg/d) or vehicle for 5 days. Results and discussion: The results showed that AAI induced dose-dependent nephrotoxicity. Differences in renal protein profiles between the control and AAI groups increased with AAI dose. Comparing the control with the low-, medium-, and high-dose AAI groups, we found 58, 210, and 271 differentially expressed proteins, respectively. Furthermore, protein-protein interaction network analysis identified acyl-CoA synthetase medium-chain family member 3 (Acsm3), cytochrome P450 family 2 subfamily E member 1 (Cyp2e1), microsomal glutathione S-transferase 1 (Mgst1), and fetuin B (Fetub) as the key proteins. Proteomics revealed that AAI decreased Acsm3 and Cyp2e1 while increasing Mgst1 and Fetub expression in mice kidneys, which was further confirmed by Western blotting. Collectively, in AAI-induced nephrotoxicity, renal protein profiles were dysregulated and exacerbated with increasing AAI dose. Acsm3, Cyp2e1, Mgst1, and Fetub may be the potential therapeutic targets for AAN.

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.

Genetic alterations in the neuronal development genes are associated with changes of the tumor immune microenvironment in pancreatic cancer

Background

Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis and is highly metastatic. Our prior studies have demonstrated the critical role of axon guidance pathway genes in PDAC and the connection between neuronal development and the tumor microenvironment. A recent study newly identified 20 neuronal development genes [disks large homolog 2 (DLG2), neuron-glial-related cell adhesion molecule (NRCAM), neurexin3 (NRXN3), mitogen-activated protein kinase 10 (MAPK10), platelet-derived growth factor D (PDGFD), protein kinase C epsilon (PRKCE), potassium calcium-activated channel subfamily M alpha 1 (KCNMA1), polycystic kidney and hepatic disease 1 (PKHD1), neural cell adhesion molecule 1 (NCAM1), neuregulin-1 (NRG1), zinc finger protein 667 (ZNF667), cystic fibrosis transmembrane conductance regulator (CFTR), acyl-CoA medium-chain synthetase-3 (ACSM3), complement 6 (C6), protein tyrosine phosphatase receptor type M (PTPRM), hypoxia-inducible factor 1 alpha (HIF1A), adenylyl cyclase 5 (ADCY5), adherens junctions-associated protein 1 (AJAP1), neurobeachin (NBEA), sodium voltage-gated channel alpha subunit 9 (SCN9A)] that are associated with perineural invasion and poor prognosis of PDAC. The relationship between genetic alterations in these 20 genes and tumor immune microenvironment (TME) has not previously been investigated.

Methods

We hence applied the sequential multiplex immunohistochemistry results of biopsy specimens from 63 PDAC patients to investigate this relationship.

Results

We found that, except for PTPRM and NBEA, genetic alterations involving these 20 genes are associated with significant changes in the densities of major immune cell subtypes. Except for AJAP1, the copy number loss involving this panel of neuronal development genes is significantly associated with changes in immune cell infiltrates. In contrast, the copy number gain in fewer genes, including NRXN3, ZNF667, ACSM3, C6, ADCY5, SCN9A, and PRKCE, is significantly associated with changes in immune cell infiltrates.

Conclusions

Our study suggested that neuronal development genes play a role in modulating TME in a pancreatic cancer setting.

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.

KLF10 upregulates ACSM3 via the PI3K/Akt signaling pathway to inhibit the malignant progression of melanoma

Malignant melanoma is a type of skin cancer caused by mutations in the DNA of melanocytes. Melanoma is relatively rare compared with other types of skin tumors, but has a highly aggressive biological behavior and consequently, a poorer prognosis. Therefore, the present study aimed to explore the role and mechanism of Kruppel-like factor 10 (KLF10) and acyl-CoA medium-chain synthetase 3 (ACSM3) in melanoma progression. KLF10 expression in melanoma tissues was predicted using Gene Expression Profiling Interactive Analysis (GEPIA). KLF10 expression in healthy and melanoma cells was also detected using reverse transcription-quantitative PCR and western blotting. Cell transfection was performed to overexpress KLF10 or silence ACSM3. Cell viability, proliferation, migration, invasion and apoptosis were detected using Cell Counting Kit-8, colony formation, wound healing, Transwell and TUNEL assays, respectively. The activity of the ACSM3 promoter was detected using a dual-luciferase reporter assay, and the relationship between KLF10 and ACSM3 was detected using the GEPIA database and chromatin immunoprecipitation (ChIP). The results demonstrated that KLF10 expression was significantly downregulated in melanoma cells, especially in A375 cells. Compared with the Ov-NC group, KLF10 overexpression significantly inhibited the proliferation, invasion and migration of melanoma cells and promoted their apoptosis. Similar to KLF10, ACSM3 was also downregulated in A375 cells compared with that in the HEM group, and the GEPIA database analysis and ChIP assay results demonstrated that KLF10 expression was positively associated with ACSM3 expression. Furthermore, silencing ACSM3 significantly reversed the effect of KLF10 overexpression on cell proliferation, invasion and migration, and ACSM3 knockdown increased the levels of phosphorylated (p)-PI3K and p-Akt compared with the levels in the Ov-KLF10 + sh-NC group. Overall, the present study suggested that KLF10 inhibited the proliferation, invasion and migration of melanoma cells by targeting ACSM3 via the PI3K/Akt signaling pathway.

Predicting Panel of Metabolism and Immune-Related Genes for the Prognosis of Human Ovarian Cancer

Objective

Ovarian cancer (OC) is a high deadly gynecologic cancer with a poor prognosis. The identification of genomic aberrations could predict the clinical prognosis of OC patients and may eventually develop new therapeutic strategies in the future. The purpose of this study is to create comprehensive co-expressed gene networks correlated with metabolism and the immune process of OC.

Methods

The transcriptome profiles of TCGA OC datasets and GSE26193 datasets were analyzed. The mRNA expression level, hub genomic alteration, patient’s survival status, and tumor cell immune microenvironment of metabolism-related genes were analyzed from TCGA, GTEX, Oncomine, Kaplan-Meier Plotter, cBioPortal, TIMER, ESTIMATE, and CIBERSORT databases. We further validated the mRNA and protein expression levels of these hub genes in OC cell lines and tissues using qRT-PCR and immunohistochemistry.

Results

The LASSO-Cox regression analyses unveiled seven differently expressed metabolism-related genes, including GFPT2, DGKD, ACACB, ACSM3, IDO1, TPMT, and PGP. The Cox regression risk model could be served as an independent marker to predict the overall clinical survival of OC patients. The expression of GFPT2, DGKD, ACACB, and ACSM3 were downregulated in OC tissues, while IDO1, TPMT, and PGP were upregulated in OC tissues than in control. Moreover, DGKD and IDO1 were significantly associated with the human immune system.

Conclusion

The differently expressed metabolism-related genes were identified to be a risk model in the prediction of the prognosis of OC. The identified hub genes related to OC prognosis may play important roles in influencing both human metabolism and the immune system.

The Overexpression of Acyl-CoA Medium-Chain Synthetase-3 (ACSM3) Suppresses the Ovarian Cancer Progression via the Inhibition of Integrin β1/AKT Signaling Pathway

Ovarian cancer is considered as one of the most fatal gynecologic malignancies. This work aimed to explore the effects and regulatory mechanism of Acyl-CoA medium-chain synthetase-3 (ACSM3, a subunit of CoA ligases) in ovarian cancer progression. As well as employing CCK-8 assay, clone formation assay, and cell cycle analysis were carried out to investigate cell proliferation ability. Wound healing assay and transwell assay were subsequently used to assess cell migration and invasion. Mice xenografts were then conducted to measure the effects of ACSM3 on tumor development in vivo. Our bioinformatics analysis suggested that the expression of ACSM3 was down-regulated in ovarian cancer tissues, and the low expression level of ACSM3 might related with poorer overall survival than high mRNA expression of ACSM3 in ovarian cancer patients. We artificially regulated the expression of ACSM3 to evaluate its effects on ovarian cancer malignant phenotypes. Our data revealed that the overexpression of ACSM3 inhibited cell proliferation, migration, and invasion of ovarian cancer cells. In contrast, the knock-down of ACSM3 received the opposite results. Our western blot results showed that the Integrin β1/AKT signaling pathway was negatively regulated by ACSM3 expression. Moreover, ACSM3 overexpression-induced suppression of cell migration and invasion activities were abolished by the overexpression of ITG β1 (Integrin β1). Additionally, the growth of ovarian cancer xenograft tumors was also repressed by the overexpression of ACSM3. And ACSM3 interference obtained the contrary effects in vivo. In summary, ACSM3 acts as a tumor suppressor gene and may be a potential therapeutic target of ovarian cancer.