A new metabolic signature contributes to disease progression and predicts worse survival in melanoma

Metabolism-associated molecular classification of cervical cancer

OBJECTIVE

This study aimed to explore metabolic abnormalities in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) for metabolism-related genes.

METHODS

We downloaded expression data for metabolism-related genes, performed differential expression analysis, and applied weighted gene co-expression network analysis (WGCNA) to identify metabolism-related functional modules. We obtained normalised miRNA expression data and identified master methylation regulators for metabolism-related genes. Cox regression of data on metabolism-related genes was performed to screen for genes that affect the prognosis of patients with CESC. Furthermore, we selected key genes for validation.

RESULTS

Our results identified 3620 metabolism-related genes in CESC, 2493 of which contained related mutations. The co-occurrence of CUBN, KALRN, and HERC1 was related to the prognosis of CESC. The fraction of genome altered (FGA) closely correlated with overall survival. In expression analysis, 374 genes were related to the occurrence and prognosis of CESC. We then identified four metabolic pathway modules in WGCNA. Further analysis revealed that glycolysis/gluconeogenesis was related to endothelial cells and that arachidonic acid metabolism was related to cell proliferation. These four modules were also related to the prognosis of CESC. Among CESC-related metabolic genes, two genes were found to be regulated by microRNAs (miRNAs) and methylation, whereas another two genes were coregulated by miRNAs and mutations.

CONCLUSIONS

Among metabolism-related genes, 15 genes were related to the prognosis of CESC. The co-occurrence of CUBN/KALRN/HERC1 was associated with CESC prognosis. Glycolysis/gluconeogenesis was related to endothelial cells, and arachidonic acid metabolism was related to cell proliferation.

MCT4/Lactate Promotes PD-L1 Glycosylation in Triple-Negative Breast Cancer Cells

Triple-negative breast cancer (TNBC) has the highest percentage of lymphocytic infiltration among breast cancer subtypes, and TNBC patients may benefit from anti-PD-1/PD-L1 immunotherapy. However, some cases whether the immune checkpoint blockade (ICB) shows low targeting efficiency have occurred and effective synergistic targets need to be found, which inspired our exploration of the co-expression analysis of MCT4 (SLC16A3) and PD-L1 (CD274) and their potential regulatory mechanisms. After bioinformatic analysis of the relationship between MCT4 and PD-L1, we validated their positive co-expression relationship in triple-negative breast cancer through multiple immunohistochemical staining (mIHC), CRISPR/Cas9, and lentiviral transduction for MCT4 knockout (sgMCT4/231 KO) or overexpression (pEGFP-N1-MCT4/231). We examined the effect of lactate treatment on PD-L1 expression in triple-negative breast cancer cells by qRT-PCR and Western blot. Combined with our results, we found that MCT4 positively regulated PD-L1 expression through discharging lactate and stabilized PD-L1 through promoting its glycosylation by the classic WNT pathway in MDA-MB-231 cells. More importantly, the high co-expression of MCT4 and PD-L1 appears to predict more effective targets for treating TNBC, which would improve immune checkpoint therapy for TNBC.

Overcoming chemoresistance to b-raf inhibitor in melanoma via targeted inhibition of phosphoenolpyruvate carboxykinase1 using 3-mercaptopropionic acid

The resistance of melanoma to BRAF inhibitors remains a tough clinical challenge. In order to explore the underlying mechanism of drug resistance in melanoma, we established the resistant cell line to vemurafenib, and assessed the changes of drug-resistant cells on proliferation, apoptosis, oxidative stress and tumor stemness. Our results suggest that phosphoenolpyruvate carboxykinase1 (PCK1) is activated and inhibits the oxidative stress caused by vemurafenib in drug-resistant cells. Long term treatment of vemurafenib increases the expression of PCK1 which reduces the production of reactive oxygen species (ROS) by activating PI3K/Akt pathway. After the inhibition of PCK1 by 3-mercaptopropionic acid (3-MPA), the therapeutic sensitivity of vemurafenib is restored. In conclusion, this study disclosed that drug-resistant cells appeared to regulate their own proliferation, oxidative stress and tumor dryness by activating Akt/PCK1/ROS pathway, and shed new insights into acquiring drug resistance in melanoma.

Comprehensive Analysis of Monocarboxylate Transporter 4 (MCT4) expression in breast cancer prognosis and immune infiltration via integrated bioinformatics analysis

Lactate blunts the anticancer immune response in breast cancer (BC). However, little is known about the exact effect of lactate transporters such as monocarboxylate transporter 4 (MCT4) on immunotherapy. In this study, we investigated the expression status and prognostic value of MCT4 in BC through large-scale transcriptome data. Our results showed that MCT4 was overexpressed in BC, particularly in the basal-like molecular subtype. Overexpression of MCT4 was significantly correlated with high BC lesion grade and poor prognosis. Enrichment analysis indicated that the MCT4-related genes were involved in immune- and metabolism-related bioprocesses, such as myeloid leukocyte activation, the adaptive immune system, and catabolic process. We also found that the expression of MCT4 in BC lesions was associated with immune cell infiltration and glycolytic rate-limiting enzymes like pyruvate kinase M2 (PKM2) and hexokinases-3 (HK3). Our observations indicate that MCT4 may play a pivotal role in the maintenance of the tumor immune microenvironment (TIME) through metabolic reprogramming. The enzymes of the glycolysis pathway (MCT4, PKM2, and HK3) may thus serve as new targets to modulate the TIME and enhance immunotherapy efficiency.[Figure: see text].

Value of glycogen synthase 2 in intrahepatic cholangiocarcinoma prognosis assessment and its influence on the activity of cancer cells

Intrahepatic cholangiocarcinoma (ICC) is the second most common primary liver tumor with increasing incidence worldwide. Metabolic reprogramming caused by metabolic related gene disorders is a prominent hallmark of tumors, among which Glycogen Synthase 2 (GYS2) is the key gene responsible for regulating cellular energy metabolism, and its expression disorders are closely related to various tumors and glycometabolic diseases. However, we still know nothing about its role in ICC. This study is intended to reveal the functional role of GYS2 in the ICC progress and explore the underlying mechanism. Based on the integrated pan-cancer analysis of GYS2 in the GEPIA database, the expression of GYS2 in paired ICC and adjacent non tumor tissues was detected by qPCR. It was found that the expression of GYS2 was significantly down-regulated in ICC. Further analysis showed that its low expression was not only associated with the degree of pathological differentiation, tumor size, microvascular invasion and lymph node metastasis, but also an independent risk factor for unfavorable prognosis. Functional studies have shown that GYS2 overexpression can significantly impair the proliferation, replication, cloning, migration and invasion of cholangiocarcinoma cells, while the silencing GYS2 dramatically promotes the development of the aforementioned phenotypes, the underlying mechanism may be that GYS2 activates the P53 pathway. In conclusions,low GYS2 expression in ICC predicted unfavorable patient outcomes; GYS2 overexpression could significantly impair the proliferation, migration and invasion of cholangiocarcinoma cells via activating the P53 pathway and GYS2 was expected to become a potential therapeutic target for such patients.

Transcriptome Analyses Identify a Metabolic Gene Signature Indicative of Antitumor Immunosuppression of EGFR Wild Type Lung Cancers With Low PD-L1 Expression

Purpose

With the development and application of targeted therapies like tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs), non-small cell lung cancer (NSCLC) patients have achieved remarkable survival benefits in recent years. However, epidermal growth factor receptor (EGFR) wild-type and low expression of programmed death-ligand 1 (PD-L1) NSCLCs remain unmanageable. Few treatments for these patients exist, and more side effects with combination therapies have been observed. We intended to generate a metabolic gene signature that could successfully identify high-risk patients and reveal its underlying molecular immunology characteristics.

Methods

By identifying the bottom 50% PD-L1 expression level as PD-L1 low expression and removing EGFR mutant samples, a total of 640 lung adenocarcinoma (LUAD) and lung squamous carcinoma (LUSC) tumor samples and 93 adjacent non-tumor samples were finally extracted from The Cancer Genome Atlas (TCGA). We identified differentially expressed metabolic genes (DEMGs) by R package limma and the prognostic genes by Univariate Cox proportional hazards regression analyses. The intersect genes between DEMGs and prognostic genes were put into the least absolute shrinkage and selection operator (LASSO) penalty Cox regression analysis. The metabolic gene signature contained 18 metabolic genes generated and successfully stratified LUAD and LUSC patients into the high-risk and low-risk groups, which was also validated by the Gene Expression Omnibus (GEO) database. Its accuracy was proved by the time-dependent Receiver Operating Characteristic (ROC) curve, Principal Components Analysis (PCA), and nomogram. Furthermore, the Single-sample Gene Set Enrichment Analysis (ssGSEA) and diverse acknowledged methods include XCELL, TIMER, QUANTISEQ, MCPcounter, EPIC, CIBERSORT-ABS, and CIBERSORT revealed its underlying antitumor immunosuppressive status. Besides, its relationship with somatic copy number alterations (SCNAs) and tumor mutational burden (TMB) was also discussed.

Results

It is noteworthy that metabolism reprogramming is associated with the survival of the double-negative LUAD and LUSC patients. The SCNAs and TMB of critical metabolic genes can inhibit the antitumor immune process, which might be a promising therapeutic target.

Novel natural inhibitors targeting B-RAF(V600E) by computational study

The aim of this research was to screen the ZINC15 database to select lead compounds and drug candidates which can inhibit B-RAF (V600E). In order to identify drugs potentially inhibited B-RAF (V600E), numerous modules of Discovery Studio 4.5 were employed. Structure-based screening using LibDock was carried out followed by ADME (absorption, distribution, metabolism, excretion) and toxicity prediction. CDOCKER was performed to demonstrate the binding affinity and mechanism between ligands and B-RAF(V600E). To evaluate whether ligand-receptor complexes were stable, molecular dynamics were employed. Two novel natural compounds (ZINC000100168592 and ZINC000049784088) from ZINC15 database were found binding to B-RAF(V600E) with more favorable interaction energy in comparison with the reference drug Vemurafenib. Also, they were predicted with less ames mutagenicity, rodent carcinogenicity, non-developmental toxic potential and tolerance to cytochrome P450 2D6 (CYP2D6). The molecular dynamics simulation analysis indicated that the compound-B-RAF(V600E) complexes had more favorable potential energy compared with Vemurafenib and they can exist in natural environments stably. The result of this study shows that ZINC000100168592 and ZINC000049784088 are ideal leading potential compounds to inhibit B-RAF(V600E). The findings of this study and these selected drug candidates greatly contributed to the medication design and improvement of B-RAF(V600E) and other proteins.

Identification of TYR, TYRP1, DCT and LARP7 as related biomarkers and immune infiltration characteristics of vitiligo via comprehensive strategies

This study aims to explore biomarkers associated with vitiligo and analyze the pathological role of immune cell infiltration in the disease. We used the robust rank aggregation (RRA) method to integrate three vitiligo data sets downloaded from gene expression omnibus database, identify the differentially expressed genes (DEGs) and analyze the functional correlation. Then, the comprehensive strategy of combined weighted gene coexpression network analysis (WGCNA) and logical regression of the selection operator (LASSO), support vector machine recursive feature elimination (SVM-RFE), and random forest (RF) machine learning algorithm are employed to screen and biomarkers associated with vitiligo. Finally, the immune cell infiltration of vitiligo was evaluated by CIBERSORT, and the correlation between biomarkers and infiltrating immune cells was analyzed. Herein, we identified 131 robust DEGs, and enrichment analysis results showed that robust DEGs and melanogenesis were closely associated with vitiligo development and progression. TYR, TYRP1, DCT and LARP7 were identified as vitiligo-related biomarkers. Immune infiltration analysis demonstrated that CD4 T Cell, CD8 T Cell, Tregs, NK cells, dendritic cells, and macrophages were involved in vitiligo’s pathogenesis. In summary, we adopted a comprehensive strategy to screen biomarkers related to vitiligo and explore the critical role of immune cell infiltration in vitiligo.

Abbreviations: TYR, Tyrosinase; TYRP1, Tyrosinase-related protein-1; DCT, dopachrome tautomerase; LARP7, La ribonucleoprotein domain family, member-7; RRA, robust rank aggregation; DEGs, differentially expressed genes; WGCNA, weighted gene coexpression network analysis; LASSO, logical regression of the selection operator; SVM-RFE, support vector machine recursive feature elimination; RF, random forest; GWAS, Genome-wide association study; FasL, Fas-Fas ligand; Tregs, T-regulatory cells; NK, natural killer; GEPCs, gene expression profiling chips; GO, gene ontology; GSEA, gene set enrichment analysis; FDR, false discovery rate; AUC, area under the curve; ROC, receiver-operating characteristic; BP, biological process; CC, cellular component; MF, molecular function.