FGD1 exhibits oncogenic properties in hepatocellular carcinoma through regulating cell morphology, autophagy and mitochondrial function

RBCK1 overexpression is associated with immune cell infiltration and poor prognosis in hepatocellular carcinoma

RBCK1 is an important E3 ubiquitin ligase, which plays an important role in many major diseases. However, the function and mechanism of RBCK1 in pan-cancer and its association with immune cell infiltration have not been reported. The purpose of this study is to find out the expression of RBCK1 in cancer, and to explore the relationship between RBCK1 and the prognosis of patients. Our results show that the expression of RBCK1 is up-regulated in a variety of malignant tumors, and is closely related to the prognosis of patients. Further studies have shown that RBCK1 regulates protein expression in the nucleus and plays an important role in ribosome and valine, leucine, and isoleucine degradation. Genetic variation analysis showed that RBCK1 was mainly involved in missense mutations in multiple tumors, and mutated patients showed poor prognoses. Further studies showed that RBCK1 may be interacted with proteins such as RNRPB, MCRS1, TRIB3, MKKS and ARPC3. Through protein interaction analysis, we found 43 proteins interacting with RBCK1 in liver cancer. We also analyzed immune cell infiltration and found that RBCK1 expression was positively correlated with T cells and macrophages, while it was negatively correlated with neutrophils, NK cells, and DCs in liver cancer. Finally, we confirmed experimentally that RBCK1 can significantly inhibit the apoptosis and invasion of HCC. Therefore, we speculate that RBCK1 plays an important regulatory role in the occurrence and development of HCC.

Overexpression of MTFR1 promotes cancer progression and drug-resistance on cisplatin and is related to the immune microenvironment in lung adenocarcinoma

OBJECTIVE

The roles of MTFR1 in the drug resistance of lung adenocarcinoma (LAC) to cisplatin remain unexplored. In this study, the expression, clinical values and mechanisms of MTFR1 were explored, and the relationship between MTFR1 expression and immune microenvironment was investigated in LAC using bioinformatics analysis, cell experiments, and meta-analysis.

METHODS

MTFR1 expression and clinical values, and the relationship between MTFR1 expression and immunity were explored, through bioinformatics analysis. The effects of MTFR1 on the growth, migration and cisplatin sensitivity of LAC cells were identified using cell counting kit-8, wound healing and Transwell experiments. Additionally, the mechanisms of drug resistance of LAC cells involving MTFR1 were investigated using western blotting.

RESULTS

MTFR1 was elevated in LAC tissues. MTFR1 overexpression was associated with sex, age, primary therapy outcome, smoking, T stage, unfavourable prognosis and diagnostic value and considered an independent risk factor for an unfavourable prognosis in patients with LAC. MTFR1 co-expressed genes involved in the cell cycle, oocyte meiosis, DNA replication and others. Moreover, interfering with MTFR1 expression inhibited the proliferation, migration and invasion of A549 and A549/DDP cells and promoted cell sensitivity to cisplatin, which was related to the inhibition of p-AKT, p-P38 and p-ERK protein expression. MTFR1 overexpression was associated with stromal, immune and estimate scores along with natural killer cells, pDC, iDC and others in LAC.

CONCLUSIONS

MTFR1 overexpression was related to the unfavourable prognosis, diagnostic value and immunity in LAC. MTFR1 also participated in cell growth and migration and promoted the drug resistance of LAC cells to cisplatin via the p-AKT and p-ERK/P38 signalling pathways.

Unraveling the Janus-Faced Role of Autophagy in Hepatocellular Carcinoma: Implications for Therapeutic Interventions

This review aims to provide a comprehensive understanding of the molecular mechanisms underlying autophagy and mitophagy in hepatocellular carcinoma (HCC). Autophagy is an essential cellular process in maintaining cell homeostasis. Still, its dysregulation is associated with the development of liver diseases, including HCC, which is one of leading causes of cancer-related death worldwide. We focus on elucidating the dual role of autophagy in HCC, both in tumor initiation and progression, and highlighting the complex nature involved in the disease. In addition, we present a detailed analysis of a small subset of autophagy- and mitophagy-related molecules, revealing their specific functions during tumorigenesis and the progression of HCC cells. By understanding these mechanisms, we aim to provide valuable insights into potential therapeutic strategies to manipulate autophagy effectively. The goal is to improve the therapeutic response of liver cancer cells and overcome drug resistance, providing new avenues for improved treatment options for HCC patients. Overall, this review serves as a valuable resource for researchers and clinicians interested in the complex role of autophagy in HCC and its potential as a target for innovative therapies aimed to combat this devastating disease.

Peonidin-3-O-Glucoside from Purple Corncob Ameliorates Nonalcoholic Fatty Liver Disease by Regulating Mitochondrial and Lysosome Functions to Reduce Oxidative Stress and Inflammation

A frequent chronic liver condition across the world is nonalcoholic fatty liver disease (NAFLD). Oxidative stress caused by lipid accumulation is generally considered to be the main cause of NAFLD. Anthocyanins can effectively inhibit the production of reactive oxygen species and improve oxidative stress. In this work, six major anthocyanins were separated from purple corncob by semi-preparative liquid chromatography. The effects of the 6 kinds of anthocyanins against NAFLD were investigated using a free fatty acid (FFA)-induced cell model. The results showed that peonidin 3-O-glucoside (P3G) can significantly reduce lipid accumulation in the NAFLD cell model. The treatment with P3G also inhibited oxidative stress via inhibiting the excessive production of reactive oxygen species and superoxide anion, increasing glutathione levels, and enhancing the activities of SOD, GPX, and CAT. Further studies unveiled that treatment with P3G not only alleviated inflammation but also improved the depletion of mitochondrial content and damage of the mitochondrial electron transfer chain developed concomitantly in the cell model. P3G upregulated transcription factor EB (TFEB)-mediated lysosomal function and activated the peroxisome proliferator-activated receptor alpha (PPARα)-mediated peroxisomal lipid oxidation by interacting with PPARα possibly. Overall, this study added to our understanding of the protective effects of purple corn anthocyanins against NAFLD and offered suggestions for developing functional foods containing these anthocyanins.

Machine learning algorithm and deep neural networks identified a novel subtype in hepatocellular carcinoma

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors. Due to the lack of specific characteristics in the early stage of the disease, patients are usually diagnosed in the advanced stage of disease progression. OBJECTIVE: This study used machine learning algorithms to identify key genes in the progression of hepatocellular carcinoma and constructed a prediction model to predict the survival risk of HCC patients. METHODS: The transcriptome data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The differential expression analysis and COX proportional-hazards model participated in the identification of survival-related genes. K-Means, Random forests, and LASSO regression are involved in identifying novel subtypes of HCC and screening key genes. The prediction model was constructed by deep neural networks (DNN), and Gene Set Enrichment Analysis (GSEA) reveals the metabolic pathways where key genes are located. RESULTS: Two subtypes were identified with significantly different survival rates (p< 0.0001, AUC = 0.720) and 17 key genes associated with the subtypes. The accuracy rate of the deep neural network prediction model is greater than 93.3%. The GSEA analysis found that the survival-related genes were significantly enriched in hallmark gene sets in the MSigDB database. CONCLUSIONS: In this study, we used machine learning algorithms to screen out 17 genes related to the survival risk of HCC patients, and trained a DNN model based on them to predict the survival risk of HCC patients. The genes that make up the model are all key genes that affect the formation and development of cancer.

Ebola Virus Encodes Two microRNAs in Huh7-Infected Cells

MicroRNAs (miRNAs) are important gene regulatory molecules involved in a broad range of cellular activities. Although the existence and functions of miRNAs are clearly defined and well established in eukaryotes, this is not always the case for those of viral origin. Indeed, the existence of viral miRNAs is the subject of intense controversy, especially those of RNA viruses. Here, we characterized the miRNA transcriptome of cultured human liver cells infected or not with either of the two Ebola virus (EBOV) variants: Mayinga or Makona; or with Reston virus (RESTV). Bioinformatic analyses revealed the presence of two EBOV-encoded miRNAs, miR-MAY-251 and miR-MAK-403, originating from the EBOV Mayinga and Makona variants, respectively. From the miRDB database, miR-MAY-251 and miR-MAK-403 displayed on average more than 700 potential human host target candidates, 25% of which had a confidence score higher than 80%. By RT-qPCR and dual luciferase assays, we assessed the potential regulatory effect of these two EBOV miRNAs on selected host mRNA targets. Further analysis of Panther pathways unveiled that these two EBOV miRNAs, in addition to general regulatory functions, can potentially target genes involved in the hemorrhagic phenotype, regulation of viral replication and modulation of host immune defense.

Silencing FYVE, RhoGEF, and PH domain containing 1 (FGD1) suppresses melanoma progression by inhibiting PI3K/AKT signaling pathway

Cutaneous melanoma is the leading cause of death among skin cancers despite the availability of diverse treatments. FGD1 plays an important role in multiple cancers, but how it works in cutaneous melanoma has not been illustrated. Thus, this study was intended to investigate the roles of FGD1 and its underlying mechanisms in cutaneous melanoma. Bioinformatics tools and quantitative real-time polymerase chain reaction (qRT-PCR) were used to analyze the expression of FGD1 in cutaneous melanoma. After the knockdown of FGD1 in melanoma cells, the proliferation, migration, and invasion of cells were analyzed by cell counting kit-8 (CCK8) assay, colony formation assays and transwell assays. Western blot was used to check the expression of key factors in PI3K/AKT pathway. In addition, nude mice models were used to study the role of FGD1 in melanoma development and metastasis in vivo. The data demonstrated that FGD1 was up-regulated and predicted a poor clinical outcome for cutaneous melanoma patients. Knockdown of FGD1 inhibited melanoma cell proliferation, migration, and invasion. The expressions of p-PI3K and p-AKT were significantly decreased, while the expressions of PI3K and AKT showed no marked difference in the knockdown group. Meanwhile, knockdown of FGD1 suppressed the development of melanoma in vivo. This study suggested that knockdown of FGD1 could block melanoma formation and proliferation by inhibiting PI3K/AKT signaling pathway. FGD1 might be a promising therapeutic target for melanoma.

Development and Validation of Tumor Immunogenicity Based Gene Signature for Skin Cancer Risk Stratification

Melanoma is one of the most aggressive types of skin cancer, with significant heterogeneity in overall survival. Currently, tumor-node-metastasis (TNM) staging is insufficient to provide accurate survival prediction and appropriate treatment decision making for several types of tumors, such as those in melanoma patients. Therefore, the identification of more reliable prognosis biomarkers is urgently essential. Recent studies have shown that low immune cells infiltration is significantly associated with unfavorable clinical outcome in melanoma patients. Here we constructed a prognostic-related gene signature for melanoma risk stratification by quantifying the levels of several cancer hallmarks and identify the Wnt/β-catenin activation pathway as a primary risk factor for low tumor immunity. A series of bioinformatics and statistical methods were combined and applied to construct a Wnt-immune-related prognosis gene signature. With this gene signature, we computed risk scores for individual patients that can predict overall survival. To evaluate the robustness of the result, we validated the signature in multiple independent GEO datasets. Finally, an overall survival-related nomogram was established based on the gene signature and clinicopathological features. The Wnt-immune-related prognostic risk score could better predict overall survival compared with standard clinicopathological features. Our results provide a comprehensive map of the oncogene-immune-related gene signature that can serve as valuable biomarkers for better clinical decision making.

Upregulated expression of MTFR2 as a novel biomarker predicts poor prognosis in hepatocellular carcinoma by bioinformatics analysis

Aim: The authors investigated the clinical role of MTFR2 in hepatocellular carcinoma (HCC) progression. Results: MTFR2 expression and methylation were abnormal in HCC tissues, and HCC patients with increased MTFR2 expression or methylation had poor or better overall survival, respectively. In addition, increased MTFR2 expression was correlated with age, grade, cancer stage and T stage. MTFR2 was an independent predictor of dismal prognosis in HCC patients. MTFR2 was involved in HCC progression by modulating the cell cycle, homologous recombination, DNA replication, p53 signaling pathway, etc. The ten hub genes were overexpressed in HCC tissues and were linked to cancer stage and dismal prognosis in HCC patients. Conclusion: MTFR2 could be a prospective biomarker of poor prognosis in individuals with HCC.

Evaluation of clinical value and potential mechanism of MTFR2 in lung adenocarcinoma via bioinformatics

Background

Mitochondrial fission regulator 2 (MTFR2) was involved in the progression and development of various cancers. However, the relationship between MTFR2 with lung adenocarcinoma (LUAD) had not been reported. Herein, this study analyzed the clinical significance and potential mechanisms of MTFR2 in LUAD via bioinformatics tools.

Results

We found that the level of MTFR2 was increased, and correlated with sex, age, smoking history, neoplasm staging, histological subtype and TP53 mutation status in LUAD patients. Kaplan-Meier survival analysis showed LUAD patients with increased MTFR2 had a poor prognosis. In addition, univariate COX regression analysis showed neoplasm staging, T stage, distant metastasis and MTFR2 level were risk factors for the prognosis of LUAD. A total of 1127 genes were coexpressed with MTFR2, including 840 positive and 208 negative related genes. KEGG and GSEA found that MTFR2 participated in the progression of LUAD by affecting cell cycle, DNA replication, homologous recombination, p53 signaling pathway and other mechanisms. The top 10 coexpressed genes, namely CDK1, CDC20, CCNB1, PLK1, CCNA2, AURKB, CCNB2, BUB1B, MAD2L1 and BUB1 were highly expressed, and were associated with poor prognosis in LUAD.

Conclusions

Consequently, we elucidated MTFR2 was a biomarker for diagnosis and poor prognosis in LUAD, and might participate in the progression of LUAD via affecting cell cycle, DNA replication, homologous recombination and p53 signaling pathway.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08378-3.

Identification of lncRNA-mRNA Regulatory Module to Explore the Pathogenesis and Prognosis of Melanoma

Skin cutaneous melanoma (SKCM) is an aggressive form of skin cancer that results in high mortality rate worldwide. It is vital to discover effective prognostic biomarkers and therapeutic targets for the treatment of melanoma. Long non-coding RNA (lncRNA) has been verified to play an essential role in the regulation of gene expression in diseases and tumors. Therefore, it is significant to explore the function of lncRNAs in the development and progression of SKCM. In this paper, a set of differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) were first screened out using 471 cutaneous melanoma samples and 813 normal skin samples. Gene Ontology and KEGG pathway enrichment analysis were performed to obtain the significant function annotations and pathways of DEmRNAs. We also ran survival analysis on both DElncRNAs and DEmRNAs to identify prognostic-related lncRNAs and mRNAs. Next, a set of hub genes derived from protein-protein interaction (PPI) network analysis and lncRNA target genes screened from starbase-ENCORI database were integrated to construct a lncRNA-mRNA regulatory module, which includes 6 lncRNAs 4 target mRNAs. We further checked the capacity of these lncRNA and mRNA in the diagnosis of melanoma, and found that single lncRNA can effectively distinguish tumor and normal tissue. Moreover, we ran CMap analysis to select a list of small molecule drugs for SKCM, such as EGFR inhibitor AG-490, growth factor receptor inhibitor GW-441756 and apoptosis stimulant betulinic-acid, which have shown therapeutic effect in the treatment of melanoma.