Purpose. To investigate the expression of the ADP-ribosylation factor (ARF)-like proteins (ARLs) and ARL4C in clear cell renal cell carcinoma (ccRCC) based on bioinformatics analysis and experimentally determine the effect and mechanism of ARL4C on cellular properties involved in ccRCC progression. Methods. After downloading the data of cancer patients from the TCGA database, we used various bioinformatics analysis websites and methods to analyze the expression and function of ARLs and ARL4C. The differential expression of ARL4C in clinical renal cancer tissues versus adjacent normal tissues was further verified using immunohistochemistry and real-time quantitative reverse-transcription (qRT-PCR). qRT-PCR was used to explore the expression of ARL4C mRNA in normal renal cells versus different ccRCC cell lines, and the protein expression of ARL4C was further verified using western blotting. CCK-8, colony formation, and EdU assays were used to determine the effect of ARL4C knockdown on ccRCC cell proliferation. We also used wound healing and Transwell assays to analyze the changes in ccRCC cell migration and invasion following ARL4C knockdown. Finally, we used western blotting to probe the molecular mode of action of ARL4C in ccRCC cells after exposure to Wnt signaling pathway agonists. Results. Biological function analysis showed that methylation of ARL4C and changes in immune cell infiltration and targeted drug sensitivity caused by altered ARL4C expression affected the prognosis of ccRCC. Further bioinformatics analysis suggested that the expression of ARL4C mRNA was increased in ccRCC, and this was associated with a poor prognosis in ccRCC patients. Increased expression of ARL4C was further verified using qRT-PCR and western blotting of human ccRCC tissue samples. Downregulation of ARL4C significantly inhibited the proliferation, migration, and invasion of ccRCC cells, and activation of the Wnt/β-catenin pathway promoted the expression of ARL4C. As an essential downstream effector of the Wnt signaling pathway, ARL4C increased the expression of cyclin D1 and c-myc, thereby increasing the ability of the cells to undergo epithelial-mesenchymal transition (EMT) and ccRCC progression. Conclusions. As a critical factor in the Wnt/β-catenin pathway, ARL4C regulates EMT and progression in ccRCC.

Mitochondrial function, as the core of the cell's energy metabolism, is firmly connected to cancer metabolism and growth. However, the involvement of long noncoding RNAs (lncRNAs) related to mitochondrial function in breast cancer (BRCA) has not been thoroughly investigated. As a result, the objective of this research was to dissect the prognostic implication of mitochondrial function-related lncRNAs and their link to the immunological microenvironment in BRCA. The Cancer Genome Atlas (TCGA) database was used to acquire clinicopathological and transcriptome information for BRCA samples. Mitochondrial function-related lncRNAs were recognized by coexpression analysis of 944 mitochondrial function-related mRNAs obtained from the MitoMiner 4.0 database. A novel prognostic signature was built in the training cohort using integrated analysis of mitochondrial function-related lncRNA and the corresponding clinical information through univariate analysis, lasso regression, and stepwise multivariate Cox regression analysis. The prognostic worth was judged in the training cohort and validated in the test cohort. In addition, functional enrichment and immune microenvironment analyses were performed to explore the risk score on the basis of the prognostic signature. An 8-mitochondrial function-related lncRNA signature was generated by integrated analysis. Individuals within the higher-risk category had a worse overall survival rate (OS) (training cohort: P < 0.001; validation cohort: P < 0.001; whole cohort: P < 0.001). The risk score was identified as an independent risk factor by multivariate Cox regression analysis (training cohort: HR 1.441, 95% CI 1.229–1.689, P < 0.001; validation cohort: HR 1.343, 95% CI 1.166–1.548, P < 0.001; whole cohort: HR 1.241, 95% CI 1.156–1.333, P < 0.001). Following that, the predictive accuracy of the model was confirmed by the ROC curves. In addition, nomograms were generated, and the calibration curves revealed that the model had excellent prediction accuracy for 3- and 5-year OS. Besides, the higher-risk BRCA individuals have relatively decreased amounts of infiltration of tumor-killing immune cells, lower levels of immune checkpoint molecules, and immune function. We constructed and verified a novel mitochondrial function-related lncRNA signature that might accurately predict the outcome of BRCA, play an essential role in immunotherapy, and might be exploited as a therapeutic target for precise BRCA therapy.

PurposeThe mitogen-activated protein kinase (MAPK) signaling pathway is often studied in oncology as the most easily mentioned signaling pathway. This study aims to establish a new prognostic risk model of MAPK pathway related molecules in kidney renal clear cell carcinoma (KIRC) based on genome and transcriptome analysis.MethodsIn our study, RNA-seq data were acquired from the KIRC dataset of The Cancer Genome Atlas (TCGA) database. MAPK signaling pathway-related genes were obtained from the gene enrichment analysis (GSEA) database. We used “glmnet” and the “survival” extension package for LASSO (Least absolute shrinkage and selection operator) regression curve analysis and constructed a prognosis-related risk model. The survival curve and the COX regression analysis were used the “survival” expansion packages. The ROC curve was plotted using the “survival ROC” extension package. We then used the “rms” expansion package to construct a nomogram plot. We performed a pan-cancer analysis of CNV (copy number variation), SNV (single nucleotide variant), drug sensitivity, immune infiltration, and overall survival (OS) of 14 MAPK signaling pathway-related genes using several analysis websites, such as GEPIA website and TIMER database. Besides, the immunohistochemistry and pathway enrichment analysis used The Human Protein Atlas (THPA) database and the GSEA method. Finally, the mRNA expression of risk model genes in clinical renal cancer tissues versus adjacent normal tissues was further verified by real-time quantitative reverse transcription (qRT-PCR).ResultsWe performed Lasso regression analysis using 14 genes and created a new KIRC prognosis-related risk model. High-risk scores suggested that KIRC patients with lower-risk scores had a significantly worse prognosis. Based on the multivariate Cox analysis, we found that the risk score of this model could serve as an independent risk factor for KIRC patients. In addition, we used the THPA database to verify the differential expression of proteins between normal kidney tissues and KIRC tumor tissues. Finally, the results of qRT-PCR experiments suggested large differences in the mRNA expression of risk model genes.ConclusionsThis study constructs a KIRC prognosis prediction model involving 14 MAPK signaling pathway-related genes, which is essential for exploring potential biomarkers for KIRC diagnosis.

Breast cancer (BC) is a lethal malignancy with a poor prognosis. Necroptosis is critical in the progression of cancer. However, the expression of genes involved in necroptosis in BC and their association with prognosis remain unclear. We investigated the predictive potential of necroptosis-related genes in BC samples from the TCGA dataset. We used LASSO regression to build a risk model consisting of twelve necroptosis-related genes in BC. Using the necroptosis-related risk model, we were able to successfully classify BC patients into high- and low-risk groups with significant prognostic differences (p = 4.872 × 10 −7). Additionally, we developed a matched nomogram predicting 5, 7, and 10-year overall survival in BC patients based on this necroptosis-related risk model. Our next step was to perform multiple GSEA analyses to explore the biological pathways through which these necroptosis-related risk genes influence cancer progression. For these twelve risk model genes, we analyzed CNV, SNV, OS, methylation, immune cell infiltration, and drug sensitivity in pan-cancer. In addition, immunohistochemical data from the THPA database were used to validate the protein expression of these risk model genes in BC. Taken together, we believe that necroptosis-related genes are considered potential therapeutic targets in BC and should be further investigated.

Objective This study aimed to evaluate the expression level of long chain acyl-CoA synthase 1 (ACSL1) in clear cell renal cell carcinoma (ccRCC) tissue and explore its biological role in the progression of ccRCC.Methods Using Reversed Phase Protein Array (RPPA) sequencing technology, we identified ACSL1 as the target gene of interest. We then used the TCGA database to analyze the mRNA expression level of ACSL1 in ccRCC tissue and its clinical relevance. Immunohistochemistry and qRT-PCR were used to measure the expression level of ACSL1 in ccRCC tissue and investigate the correlation between ACSL1 expression level and clinicopathological characteristics and patient prognosis. CCK-8 technology and ferrostatin-1 were used to investigate the correlation between ACSL1 and ferroptosis in renal cancer cells. We also measured the content of malondialdehyde, glutathione, reactive oxygen species level, and degree of mitochondrial damage under electron microscopy to detect the effect of ACSL1 on ferroptosis of renal cancer cells. Additionally, we used RNA-Seq and Western blotting techniques to explore the potential mechanism of ACSL1 in renal cancer cells. Finally, we investigated the effect of ACSL1 on tumor growth using a xenotransplantation model.Results Our results showed that the expression level of ACSL1 in ccRCC tissue was significantly decreased and was correlated with clinical characteristics. The low expression level of ACSL1 was associated with poor patient prognosis. Overexpression of ACSL1 in renal cancer cells led to a significant decrease in GSH content, an improvement in the ability of lipid peroxidation, a significant increase in ROS level, significant shrinkage of intracellular mitochondria, and decreased expression of GPX4 and SLC7A11. RNA-Seq and KEGG enrichment analysis revealed that ACSL1 regulates ferroptosis in ccRCC through the HO-1/GPX4 axis. Western blotting confirmed that ACSL1 upregulated the expression of HO-1 and inhibited the expression of GPX4.Conclusion The expression of ACSL1 is low in human ccRCC tissue, and ACSL1 may be a potential target and prognostic marker for the treatment of ccRCC.