Targeting the transcription factor receptor LXR to treat clear cell renal cell carcinoma: agonist or inverse agonist?

Growing evidence indicates that clear cell renal cell carcinoma (ccRCC) is a metabolism-related disease. Changes in fatty acid (FA) and cholesterol metabolism play important roles in ccRCC development. As a nuclear transcription factor receptor, Liver X receptor (LXR) regulates a variety of key molecules associated with FA synthesis and cholesterol transport. Therefore, targeting LXR may provide new therapeutic targets for ccRCC. However, the potential regulatory effect and molecular mechanisms of LXR in ccRCC remain unknown. In the present study, we found that both an LXR agonist and an XLR inverse agonist could inhibit proliferation and colony formation and induce apoptosis in ccRCC cells. We observed that the LXR agonist LXR623 downregulated the expression of the low-density lipoprotein receptor (LDLR) and upregulated the expression of ABCA1, which resulted in reduced intracellular cholesterol and apoptosis. The LXR inverse agonist SR9243 downregulated the FA synthesis proteins sterol regulatory element-binding protein 1c (SREBP-1c), fatty acid synthase (FASN) and stearoyl-coA desaturase 1 (SCD1), causing a decrease in intracellular FA content and inducing apoptosis in ccRCC cells. SR9243 and LXR623 induced apoptosis in ccRCC cells but had no killing effect on normal renal tubular epithelial HK2 cells. We also found that SRB1-mediated high-density lipoprotein (HDL) in cholesterol influx is the cause of high cholesterol in ccRCC cells. In conclusion, our data suggest that an LXR inverse agonist and LXR agonist decrease the intracellular FA and cholesterol contents in ccRCC to inhibit tumour cells but do not have cytotoxic effects on non-malignant cells. Thus, LXR may be a safe therapeutic target for treating ccRCC patients.

A new survival model based on ferroptosis-related genes for prognostic prediction in clear cell renal cell carcinoma

In this study, we analyzed the clinical significance of ferroptosis-related genes (FRGs) in 32 cancer types in the GSCA database. We detected a 2-82% mutation rate among 36 FRGs. In clear cell renal cell carcinoma (ccRCC; n=539) tissues from the The Cancer Genome Atlas database, 30 of 36 FRGs were differentially expressed (up- or down-regulated) compared to normal kidney tissues (n=72). Consensus clustering analysis identified two clusters of FRGs based on similar co-expression in ccRCC tissues. We then used LASSO regression analysis to build a new survival model based on five risk-related FRGs (CARS, NCOA4, FANCD2, HMGCR, and SLC7A11). Receiver operating characteristic curve analysis confirmed good prognostic performance of the new survival model with an area under the curve of 0.73. High FANCD2, CARS, and SLC7A11 expression and low HMGCR and NCOA4 expression were associated with high-risk ccRCC patients. Multivariate analysis showed that risk score, age, stage, and grade were independent risk factors associated with prognosis in ccRCC. These findings demonstrate that this five risk-related FRG-based survival model accurately predicts prognosis in ccRCC patients, and suggest FRGs are potential prognostic biomarkers and therapeutic targets in several cancer types.

Glycolysis-Related Genes Serve as Potential Prognostic Biomarkers in Clear Cell Renal Cell Carcinoma

Metabolic rearrangement is a marker of cancer that has been widely studied in recent years. One of the major metabolic characteristics of tumor cells is the high levels of glycolysis, even under aerobic conditions, a phenomenon that is called the "Warburg effect." We investigated the expression and copy number variation (CNV) frequency of all glycolysis-related genes in multiple cancer types and found many differentially expressed genes, particularly in clear cell renal cell carcinoma (ccRCC). Single nucleotide variants (SNVs) showed that the overall average mutation frequency for all genes was low. The purpose of this study was to establish a predictive model by studying glycolysis-related genes in ccRCC. We compared the expression of glycolysis-related genes in 539 ccRCC tissues and 72 normal renal tissues from The Cancer Genome Atlas dataset and identified 17 upregulated and 26 downregulated genes. Pathway analysis revealed that PSAT1 and SDHB could activate the cell cycle, RPIA could activate the DNA damage response, and HK3 could activate apoptosis and EMT signaling, while PDK2 could inhibit apoptosis. The results of the drug sensitivity analysis suggested that some of these differentially expressed genes were positively correlated with drug sensitivity. Thirteen genes were selected from the gene coexpression network and the LASSO regression analysis. The Kaplan-Meier overall survival curves showed that the expression of upregulated genes in ccRCC patients was associated with lower overall survival. We established a predictive model consisting of 13 genes (RPIA, G6PD, PSAT1, ENO2, HK3, IDH1, PDK4, PGM2, PGK1, FBP1, OGDH, SUCLA2, and SUCLG2). This predictive model correlated well with the development and progression of ccRCC. Thus, it is of great value in the diagnosis and prognostic evaluation of ccRCC and may aid the identification of potential prognostic biomarkers and drug targets.

FABP5 is correlated with poor prognosis and promotes tumour cell growth and metastasis in clear cell renal cell carcinoma

To support proliferation, tumour cells often undergo a metabolic switch to aerobic glycolysis, and a large amount of fatty acids (FAs) is produced to provide conditions for the formation of cell membrane structures. This phenomenon is particularly prominent in clear cell renal cell carcinoma (ccRCC). FAs need to be combined with fatty acid binding proteins (FABPs) for transport. Fatty Acid Binding Protein 5 (FABP5) is an important chaperone protein of FAs that is upregulated in a variety of tumours. However, to date, the potential regulatory role and molecular mechanisms of FABP5 in the development and progression of cancers, including ccRCC, remain unknown. Herein, we demonstrate that FABP5 is upregulated in human ccRCC tissues and cell lines and is positively correlated with the progression of ccRCC. FABP5 deletion inhibits the proliferation, colony-forming ability and migration of ccRCC cells, suggesting that FABP5 may be a cancer-promoting protein in ccRCC. Mechanistically, FABP5 deletion significantly downregulated MMP9 and the transcription factor Snail1 in addition to upregulating E-cadherin and downregulating N-cadherin and Vimentin to inhibit epithelial-mesenchymal transition (EMT) in the ACHN cell line. In summary, our data suggest that FABP5 may be a potential therapeutic target in ccRCC.

Screening and Identification of Key Biomarkers for Bladder Cancer: A Study Based on TCGA and GEO Data

Bladder cancer (BLCA) is a common malignant cancer, and it is the most common genitourinary cancer in the world. The recurrence rate is the highest of all cancers, and the treatment of BLCA has only slightly improved over the past 30 years. Genetic and environmental factors play an important role in the development and progression of BLCA. However, the mechanism of cancer development remains to be proven. Therefore, the identification of potential oncogenes is urgent for developing new therapeutic directions and designing novel biomarkers for the diagnosis and prognosis of BLCA. Based on this need, we screened overlapping differentially expressed genes (DEG) from the GSE7476, GSE13507, and TCGA BLCA datasets. To identify the central genes from these DEGs, we performed a protein-protein interaction network analysis. To investigate the role of DEGs and the underlying mechanisms in BLCA, we performed Gene Ontology (GO) and Kyoto Gene and Genomic Encyclopedia (KEGG) analysis; we identified the hub genes via different evaluation methods in cytoHubba and then selected the target genes by performing survival analysis. Finally, the relationship between these target genes and tumour immunity was analysed to explore the roles of these genes. In summary, our current studies indicate that both cell division cycle 20 (CDC20) and abnormal spindle microtubule assembly (ASPM) genes are potential prognostic biomarkers for BLCA. It may also be a potential immunotherapeutic target with future clinical significance.

Roles of Reactive Oxygen Species in Biological Behaviors of Prostate Cancer

Prostate cancer (PCa), known as a heterogenous disease, has a high incidence and mortality rate around the world and seriously threatens public health. As an inevitable by-product of cellular metabolism, reactive oxygen species (ROS) exhibit beneficial effects by regulating signaling cascades and homeostasis. More and more evidence highlights that PCa is closely associated with age, and high levels of ROS are driven through activation of several signaling pathways with age, which facilitate the initiation, development, and progression of PCa. Nevertheless, excessive amounts of ROS result in harmful effects, such as genotoxicity and cell death. On the other hand, PCa cells adaptively upregulate antioxidant genes to detoxify from ROS, suggesting that a subtle balance of intracellular ROS levels is required for cancer cell functions. The current review discusses the generation and biological roles of ROS in PCa and provides new strategies based on the regulation of ROS for the treatment of PCa.

A New Prognostic Risk Model Based on PPAR Pathway-Related Genes in Kidney Renal Clear Cell Carcinoma

OBJECTIVE

This study is aimed at using genes related to the peroxisome proliferator-activated receptor (PPAR) pathway to establish a prognostic risk model in kidney renal clear cell carcinoma (KIRC).

METHODS

For this study, we first found the PPAR pathway-related genes on the gene set enrichment analysis (GSEA) website and found the KIRC mRNA expression data and clinical data through TCGA database. Subsequently, we used R language and multiple R language expansion packages to analyze the expression, hazard ratio analysis, and coexpression analysis of PPAR pathway-related genes in KIRC. Afterward, using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) website, we established the protein-protein interaction (PPI) network of genes related to the PPAR pathway. After that, we used LASSO regression curve analysis to establish a prognostic survival model in KIRC. Finally, based on the model, we conducted correlation analysis of the clinicopathological characteristics, univariate analysis, and multivariate analysis.

RESULTS

We found that most of the genes related to the PPAR pathway had different degrees of expression differences in KIRC. Among them, the high expression of 27 genes is related to low survival rate of KIRC patients, and the high expression of 13 other genes is related to their high survival rate. Most importantly, we used 13 of these genes successfully to establish a risk model that could accurately predict patients' prognosis. There is a clear correlation between this model and metastasis, tumor, stage, grade, and fustat.

CONCLUSIONS

To the best of our knowledge, this is the first study to analyze the entire PPAR pathway in KIRC in detail and successfully establish a risk model for patient prognosis. We believe that our research can provide valuable data for future researchers and clinicians.

MiR-9-5p could promote angiogenesis and radiosensitivity in cervical cancer by targeting SOCS5

OBJECTIVE

The aim of this study was to investigate the molecular mechanism of miRNA-9-5p in cervical cancer.

PATIENTS AND METHODS

The expression level of microRNA-9-5p (miR-9-5p) in cervical cancer (CC) tissues and cell lines was examined by quantitative Real Time-Polymerase Chain Reaction. Cells were transfected with Lipofectamine 3000. Cell proliferation was measured by Cell Counting Kit-8 (CCK-8). Invasion assays were performed in 24-well transwell chambers system with 8 μm pores. Cell invasion was evaluated by transwell assay. Western blot was used to detect the changes of epithelial-mesenchymal transition (EMT) and SOCS5. The effects of miR-9-5p on tubule formation were examined under different doses of γ radiation. Immunohistochemistry assay was used to analyze the protein expression of SOCS5. Fluorescence microscopy analysis was used to measure autophagosomes after cells treated with γ irradiation.

RESULTS

From the Cancer Genome Atlas (TCGA) database, the expression of miR-9-5p was significantly higher in cervical cancer patients than in the negative ones, and it was verified in 22 paired of lymph node-positive patient tissues and negative. The overexpression of miR-9-5p promoted proliferation and invasion of cervical cancer cells in vitro and primary tumor growth in vivo. MiR-9-5p reduced the tubule generation after the radiation dose of 4Gy. Besides, we identified SOCS5 as the target of miR-9-5p, and the overexpression of SOCS5 could inhibit miR-9-5p mimics from promoting tubule formation.

CONCLUSIONS

MiR-9-5p could promote proliferation and invasion of CC cells in vitro and in vivo. MiR-9-5p could affect angiogenesis and radiosensitivity of CC cells by targeting SOCS5.

Berbamine Suppresses the Progression of Bladder Cancer by Modulating the ROS/NF-κB Axis

Berbamine (BBM), one of the bioactive ingredients extracted from Berberis plants, has attracted intensive attention because of its significant antitumor activity against various malignancies. However, the exact role and potential molecular mechanism of berbamine in bladder cancer (BCa) remain unclear. In the present study, our results showed that berbamine inhibited cell viability, colony formation, and proliferation. Additionally, berbamine induced cell cycle arrest at S phase by a synergistic mechanism involving stimulation of P21 and P27 protein expression as well as downregulation of CyclinD, CyclinA2, and CDK2 protein expression. In addition to suppressing epithelial-mesenchymal transition (EMT), berbamine rearranged the cytoskeleton to inhibit cell metastasis. Mechanistically, the expression of P65, P-P65, and P-IκBα was decreased upon berbamine treatment, yet P65 overexpression abrogated the effects of berbamine on the proliferative and metastatic potential of BCa cells, which indicated that berbamine attenuated the malignant biological activities of BCa cells by inhibiting the NF-κB pathway. More importantly, berbamine increased the intracellular reactive oxygen species (ROS) level through the downregulation of antioxidative genes such as Nrf2, HO-1, SOD2, and GPX-1. Following ROS accumulation, the intrinsic apoptotic pathway was triggered by an increase in the ratio of Bax/Bcl-2. Furthermore, berbamine-mediated ROS accumulation negatively regulated the NF-κB pathway to a certain degree. Consistent with our in vitro results, berbamine successfully inhibited tumor growth and blocked the NF-κB pathway in our xenograft model. To summarize, our data demonstrated that berbamine exerts antitumor effects via the ROS/NF-κB signaling axis in bladder cancer, which provides a basis for further comprehensive study and presents a potential candidate for clinical treatment strategies against bladder cancer.

Porcupine Inhibitor LGK974 Downregulates the Wnt Signaling Pathway and Inhibits Clear Cell Renal Cell Carcinoma

Targeted therapy for kidney cancer has achieved significant clinical results. However, because most patients who use targeted therapy will develop drug resistance, we still need to constantly explore new therapeutic targets. Although porcupine (PORCN) as a palmitoyltransferase plays a crucial role in the activation and secretion of Wnt proteins and affects the activity of the Wnt signaling pathway, little is known about the role of PORCN in clear cell renal cell carcinoma (ccRCC). We found that PORCN is highly expressed in renal cancer cell lines and patients with renal cell carcinoma with high expression of PORCN have a poor prognosis. Pathway analysis of PORCN and its related proteins showed that PORCN played a role through the Wnt signaling pathway, and there was a strong coexpression relationship between PORCN and Wnt proteins. Therefore, PORCN may be a potential and effective target for ccRCC. In the present study, we found that LGK974 could inhibit proliferation and colony formation and induce apoptosis in ccRCC cells. We also found that LGK974 could inhibit the migration and invasion of renal cell carcinoma and reduce the expression of mesenchymal markers. After treatment with LGK974, the expression level of β-catenin, a key protein in the classical Wnt pathway, was significantly decreased, and the expression levels of the target genes cyclin D1, c-Myc, MMP9, and MMP2 in the Wnt signaling pathway were also significantly decreased, which represented a significant decrease in the activity of the Wnt signaling pathway. At the same time, the cycle of renal cancer cells was significantly blocked. In conclusion, our results indicate that LGK974 could significantly inhibit the progression of renal cancer cells in a safe concentration range, so PORCN may be a safe and effective target for patients with renal cancer.

RPN2 Predicts Poor Prognosis and Promotes Bladder Cancer Growth and Metastasis via the PI3K-Akt Pathway

BACKGROUND

Ribophorin II (RPN2) is a highly conserved glycoprotein involved in the N-linked glycosylation of multiple proteins. RPN2 was reported to be associated with malignant phenotype in several tumors. However, the function of RPN2 in bladder cancer (BCa) remains unclear.

METHODS

Expression of RPN2 in BCa and adjacent tissues was compared by bioinformatics analysis, immunohistochemistry, and Western blotting. qRT-PCR was performed to explore the correlation between RPN2 expression and various clinical features in 38 patients. We assessed the effects of RPN2 on the biological activity of BCa both in vitro and in vivo, and explored its potential mechanisms based on gene set enrichment analysis (GSEA).

RESULTS

We found that RPN2 was highly expressed in human BCa compared with normal adjacent tissues. There was a significant positive correlation between higher RPN2 mRNA levels and tumor T stage, lymph node (LN) metastasis and the degree of pathological differentiation in 38 patients with BCa. We further demonstrated that RPN2 silencing inhibited the growth and metastasis of BCa both in vitro and in vivo. Western blotting revealed that RPN2 knockdown suppressed epithelial-mesenchymal transition (EMT) and inhibited the PI3K-Akt pathway.

CONCLUSION

These data suggest that RPN2 functions as an oncogene to promote tumor development and is a promising prognostic factor and therapeutic target in BCa.

Cuprotosis-Related Genes: Predicting Prognosis and Immunotherapy Sensitivity in Pancreatic Cancer Patients

Based on TCGA, GTEx, and TIMER databases and various bioinformatics analysis methods, the potential biological roles of cuprotosis-related genes in pancreatic cancer were deeply explored, and a predictive model for pancreatic cancer patients was constructed. We downloaded the RNA-Seq data and clinicopathological and predictive data of 179 pancreatic cancer tissues and 332 adjacent normal tissues from TCGA and GTEx databases. The differential expression of cuprotosis-related genes in pancreatic cancer tissue and adjacent normal tissue was analyzed, and the LASSO regression algorithm was used to construct a prediction model and verify the validity of the model prediction. Based on the LASSO regression algorithm, a predictive model composed of three genes LIPT1, LIAS, and DLAT was screened. The corresponding survival curves showed that the constructed prediction model could significantly distinguish the prognosis of pancreatic cancer patients, and the prognosis of patients in the high-risk group was worse (P = 0.00557). The ROC curve showed that the area under the curve of the predictive model for predicting the 4-, 5-, and 6-year survival rates in pancreatic cancer was 0.816, 0.836, and 0.956, respectively. The AUC value of this risk model was significantly higher than 0.7, which could more accurately predict the prognosis of pancreatic cancer patients. This study determined a risk-scoring model of cuprotosis-related genes, which can provide an essential basis for judging the prognosis of pancreatic cancer patients.

LAPTM5 Plays a Key Role in the Diagnosis and Prognosis of Testicular Germ Cell Tumors

OBJECTIVE

Testicular germ cell tumors (TGCT) are a serious malignant tumor with low early diagnosis rates and high mortality.

METHODS

To investigate novel biomarkers to predict the diagnosis and prognosis of this cancer, bioinformatics analysis was used as an accurate, efficient, and economical method.

RESULTS

Our study detected 39 upregulated and 589 downregulated differentially expressed genes (DEGs) using the GEO and TCGA databases. To identify the function of DEGs, GO functional analysis, three pathway analysis (KEGG, REACTOME, and PANTHER), and protein-protein interaction network were performed using the KOBAS website, as well as the String database. After a series of analyses in GEPIA and TIMER, including differential expression, we found one candidate gene related to the prognosis and diagnosis of TGCT. LAPTM5 was also associated with CD8+ T cell and PDCD1 expression, which suggests that it may affect immune infiltration.

CONCLUSIONS

LAPTM5 was identified as a hub gene, which could be used as a potential biomarker for TGCT diagnosis and prognosis.

GBP2 enhances paclitaxel sensitivity in triple‑negative breast cancer by promoting autophagy in combination with ATG2 and inhibiting the PI3K/AKT/mTOR pathway

Chemoresistance is a major challenge in treating triple‑negative breast cancer (TNBC); chemotherapy remains the primary approach. The present study aimed to elucidate the role of guanylate‑binding protein 2 (GBP2) in activating autophagy in TNBC and its impact on the sensitivity of TNBC cells to paclitaxel (PTX). Transfection with lentivirus was performed to establish TNBC cell lines with stable, high GBP2 expression. The mRNA and protein levels of GBP2 expression were evaluated utilizing reverse transcription‑quantitative PCR and western blotting, respectively. Autophagy in TNBC cells was evaluated using immunoblotting, transmission electron microscopy and fluorescence microscopy. The PI3K/AKT/mTOR pathway proteins and their phosphorylation were detected by immunoblotting, and fluorescence co‑localization analysis was performed to evaluate the association between GBP2 and autophagy‑related protein 2 (ATG2). BALB/c NUDE mice were subcutaneously injected with GBP2 wild‑type/overexpressing MDA‑MB‑231 cells. Low GBP2 expression was detected in TNBC, which was associated with a poor prognosis. Overexpression of GBP2 suppressed cell growth, and especially enhanced autophagy in TNBC. Forced expression of GBP2 significantly increased the PTX sensitivity of TNBC cells, and the addition of autophagy inhibitors reversed this effect. GBP2 serves as a prognostic marker and exerts a notable inhibitory impact on TNBC. It functions as a critical regulator of activated autophagy by co‑acting with ATG2 and inhibiting the PI3K/AKT/mTOR pathway, which contributes to increasing sensitivity of TNBC cells to PTX. Therefore, GBP2 is a promising therapeutic target for enhancing TNBC treatment.

Development and Validation of a Novel PPAR Signaling Pathway-Related Predictive Model to Predict Prognosis in Breast Cancer

This study is aimed at exploring the potential mechanism of the PPAR signaling pathway in breast cancer (BRCA) and constructing a novel prognostic-related risk model. We used various bioinformatics methods and databases to complete our exploration in this research. Based on TCGA database, we use multiple extension packages based on the R language for data conversion, processing, and statistics. We use LASSO regression analysis to establish a prognostic-related risk model in BRCA. And we combined the data of multiple online websites, including GEPIA, ImmuCellAI, TIMER, GDSC, and the Human Protein Atlas database to conduct a more in-depth exploration of the risk model. Based on the mRNA data in TCGA database, we conducted a preliminary screening of genes related to the PPAR signaling pathway through univariate Cox analysis, then used LASSO regression analysis to conduct a second screening, and successfully established a risk model consisting of ten genes in BRCA. The results of ROC curve analysis show that the risk model has good prediction accuracy. We can successfully divide breast cancer patients into high- and low-risk groups with significant prognostic differences (P = 1.92e - 05) based on this risk model. Combined with the clinical data in TCGA database, there is a correlation between the risk model and the patient's N, T, gender, and fustat. The results of multivariate Cox regression show that the risk score of this risk model can be used as an independent risk factor for BRCA patients. In particular, we draw a nomogram that can predict the 5-, 7-, and 10-year survival rates of BRCA patients. Subsequently, we conducted a series of pancancer analyses of CNV, SNV, OS, methylation, and immune infiltration for this risk model gene and used GDSC data to investigate drug sensitivity. Finally, to gain insight into the predictive value and protein expression of these risk model genes in breast cancer, we used GEO and HPA databases for validation. This study provides valuable clues for future research on the PPAR signaling pathway in BRCA.

A New Survival Model Based on Cholesterol Biosynthesis-Related Genes for Prognostic Prediction in Clear Cell Renal Cell Carcinoma

In our study, the value of cholesterol biosynthesis is related to clinical analysis in 32 cancer forms in the GSEA database facility. We have a mutation between 25 CBRGs. In The Cancer Genome Atlas database, clear cell renal cell carcinoma (ccRCC, n = 539) was upregulated or downregulated in 22 out of 25 cases (n = 72) compared with normal kidney tissue. Then, using LASSO regression analysis, the survival model that is based on nine risk-related CBRGs (CYP51A1, HMGCR, HMGCS1, IDI1, FDFT1, SQLE, ACAT2, FDPS, and NSDHL) is established. ROC curves confirmed the good omen of the new survival mode, and the area under the curve is 0.72 (5 years) and 0.709 (10 years). High SQLE and ACAT2 expression and low NSDHL, FDPS, CYP51A1, FDFT1, HMGCS1, HMGCR, and IDI1 expression were closely related to patients with high-risk renal clear cell carcinoma. Two types of Cox regression, uni- and multivariate, were used to determine risk scores, age, staging, and grade as independent risk factors for prognosis in patients with clear cell renal cell carcinoma. The results showed the prediction model established by 9 selected CBRGs could predict the prognosis more accurately.

Identification of a New Prognostic Risk Signature of Clear Cell Renal Cell Carcinoma Based on N6-Methyladenosine RNA Methylation Regulators

As the most prevalent internal eukaryotic modification, N6-methyladenosine (m6A) is installed by methyltransferases, removed by demethylases, and recognized by readers. However, there are few studies on the role of m6A in clear cell renal cell carcinoma (ccRCC). In this study, we researched the RNA-seq transcriptome data of ccRCC in the TCGA dataset and used bioinformatics analyses to detect the relationship between m6A RNA methylation regulators and ccRCC. First, we compared the expression of 18 m6A RNA methylation regulators in ccRCC patients and normal tissues. Then, data from ccRCC patients were divided into two clusters by consensus clustering. LASSO Cox regression analysis was used to build a risk signature to predict the prognosis of patients with ccRCC. An ROC curve, univariate Cox regression analysis, and multivariate Cox regression analysis were used to verify this risk signature's predictive ability. Then, we internally validated this signature by random sampling. Finally, we explored the role of the genes in the signature in some common pathways. Gene distribution between the two subgroups was different; cluster 2 was gender-related and had a worse prognosis. IGF2BP3, IGF2BP2, HNRNPA2B1, and METTL14 were chosen to build the risk signature. The overall survival of the high- and low-risk groups was significantly different (p = 7.47e - 12). The ROC curve also indicated that the risk signature had a decent predictive significance (AUC = 0.72). These results imply that the risk signature has a potential value for ccRCC treatment.

A new prognostic risk model based on autophagy-related genes in kidney renal clear cell carcinoma

This study aimed to explore the potential role of autophagy-related genes in kidney renal clear cell carcinoma (KIRC) and develop a new prognostic-related risk model. In our research, we used multiple bioinformatics methods to perform a pan-cancer analysis of the CNV, SNV, mRNA expression, and overall survival of autophagy-related genes, and displayed the results in the form of heat maps. We then performed cluster analysis and LASSO regression analysis on these autophagy-related genes in KIRC. In the cluster analysis, we successfully divided patients with KIRC into five clusters and found that there was a clear correlation between the classification and two clinicopathological features: tumor, and stage. In LASSO regression analysis, we used 13 genes to create a new prognostic-related risk model in KIRC. The model showed that the survival rate of patients with KIRC in the high-risk group was significantly lower than that in the low-risk group, and that there was a correlation between this grouping and the patients' metastasis, tumor, stage, grade, and fustat. The results of the ROC curve suggested that this model has good prediction accuracy. The results of multivariate Cox analysis show that the risk score of this model can be used as an independent risk factor for patients with KIRC. In summary, we believe that this research provides valuable data supporting future clinical treatment and scientific research.

Analysis of genomes and transcriptomes of clear cell renal cell carcinomas identifies mutations and gene expression changes in the TGF-beta pathway

The occurrence of clear cell renal cell carcinoma (ccRCC) is related to changes in the transforming growth factor-β (TGF-β) signaling pathway. In this study, we adopted an integrated approach to identify and verify the effects of changes in this pathway on ccRCC and provide a guide for identifying new therapeutic targets. We performed transcriptome analysis of 539 ccRCC cases from The Cancer Genome Atlas (TCGA) and divided the samples into different TGF-β clusters according to unsupervised hierarchical clustering. We found that 76 of the 85 TGF-β pathway genes were dysregulated, and 55 genes were either protective or risk factors affecting the prognosis of ccRCC. The survival time of patients with tumors with low TGF-β scores was shorter than that of patients with tumors with high TGF-β scores. The overall survival (OS) of patients with ccRCC with high TGF-β scores was better than that of patients with low TGF-β scores. The TGF-β score correlated with the expression of key ccRCC and deacetylation genes. The sensitivity of tumor patients to targeted drugs differed between the high and low TGF-β score groups. Therefore, a prognostic model based on the TGF-β gene pathway can predict the prognosis of ccRCC patients. Grouping patients with ccRCC according to their TGF-β score is of great significance for evaluating the prognosis of patients, selecting targeted drugs, and identifying new therapeutic targets.

A mitochondrial function-related LncRNA signature predicts prognosis and immune microenvironment for breast cancer

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.

ARL4C Regulates the Progression of Clear Cell Renal Cell Carcinoma by Affecting the Wnt/β-Catenin Signaling Pathway

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.

Genetic alteration and clinical significance of SUMOylation regulators in multiple cancer types

The purpose of this study was to investigate the genetic variation, gene expression differences, and clinical significance of SUMOylation regulators in pan-cancers. Based on previous studies, we gained a better understanding of the biological process of SUMOylation and the status of current research. In the present study, we employed a wide range of bioinformatics methods. We used genetic variation and mRNA expression data in the Cancer Genome Atlas (TCGA) to construct a panoramic view of the single nucleotide variants, copy number variants, and gene expression changes in SUMOylation regulators in various tumors. Subsequently, we used the String website and the Cytoscape tool to construct the PPI network between these regulators. We used the GSCALite website to determine the relationship between these regulators and cancer pathways and drug sensitivity. We constructed images of co-expression between these regulators using the R programming language. Using clinical data from TCGA, we performed hazard ratio analysis for these regulators in pan-cancer. Most importantly, we used these regulators to successfully establish risk signatures related to patient prognosis in multiple tumors. Finally, in KIRC, we conducted gene-set enrichment analysis (GSEA) of the five molecules in its risk signatures. We found that these five molecules are involved in multiple cancer pathways. In short, we have comprehensively interpreted the detailed biological process of SUMOylation at the genetic level for the first time, successfully constructed multiple risk signatures, and conducted GSEA in KIRC. We believe that these findings provide credible and valuable information that is relevant for future clinical diagnoses and scientific research.

Tripartite-motif family genes associated with cancer stem cells affect tumor progression and can assist in the clinical prognosis of kidney renal clear cell carcinoma

Ubiquitination is presently a hot topic in the field of oncology. The tripartite-motif (TRIM) family of proteins represents one of the largest classes of putative single protein RING-finger E3 ubiquitin ligases, which play an essential role in the ubiquitination of proteins in the body. At the same time, research related to cancer stem cells (CSCs) is increasing in popularity in the field of oncology. CSCs are potentially chemically resistant and can be selectively enriched in patients receiving chemotherapy, ultimately leading to adverse outcomes, such as treatment failure and cancer recurrence. There is a close relationship between multiple TRIM family genes and CSCs. Accumulating evidence suggests that TRIM family proteins are expressed in diverse human cancers and act as regulators of oncoproteins or tumor suppressor proteins. In this study, we used biological information to explore the potential function of TRIM family genes related to CSCs in the development of pan-cancer. Kidney renal clear cell carcinoma (KIRC) is one of the deadliest malignant tumors in the world. Owing to its complex molecular and cellular heterogeneity, the effectiveness of existing KIRC-related risk prediction models is not satisfactory at present. Therefore, we focused on the potential role of these TRIM family genes in KIRC and used seven TRIM family genes to establish a prognostic risk model. This model includes TRIM16, TRIM32, TRIM24, TRIM8, TRIM27, PML, and TRIM11. In conclusion, this study provides further insight into the prognosis of KIRC, which may guide treatment.

The role of prostate-specific antigen and multiparametric magnetic resonance imaging in the diagnosis of granulomatous prostatitis induced by intravesical Bacillus Calmette-Guérin vaccine therapy in patients with nonmuscle invasive bladder cancer

AIMS

This study aimed to evaluate the role of serum prostate-specific antigen (PSA) levels and multiparametric magnetic resonance imaging (mpMRI) in the diagnosis of granulomatous prostatitis (GP) induced by intravesical Bacillus Calmette-Guérin vaccine (BCG) therapy in patients with nonmuscle invasive bladder cancer (NMIBC).

SUBJECTS AND METHODS

We retrospectively analyzed eight patients with bladder cancer who underwent intravesical BCG therapy after transurethral resection of bladder tumor (TURBt) cancer. All these eight patients received 12-core transrectal ultrasound-guided prostate systemic biopsies. Clinical data on PSA with T1-weighted imaging (T1WI), T2WI, diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) on mpMRI were enrolled in the study. H and E and acid-fast staining was performed to pathologically prove GP.

RESULTS

Four of all eight cases were above 4 ng/ml total PSA (tPSA) levels and four cases were within normal ranges, while free PSA/tPSA levels decreased to lower than 16% in all patients. Every patient had hard prostatic nodules through digital rectal examination (DRE). All characters of prostate mpMRI did not show signal intensity (SI) of prostate cancer before BCG therapy but showed abnormal signals after BCG therapy. All nodular lesions showed equal SI on T1WI, lower SI on T2WI, higher SI on DWI, and lower SI on ADC after BCG therapy. Pathologic results were GP and acid-fast staining outcomes were positive in all biopsies.

CONCLUSIONS

Perioperative serum PSA levels, prostate magnetic resonance imaging, and DRE may help in the diagnosis of GP induced by intravesical BCG therapy. In general, male patients with middle- and high-risk NMIBC are recommended to undertake DRE, PSA, and prostate mpMRI, if possible, before and after TURBt."

Prognostic Signature and Therapeutic Value Based on Membrane Lipid Biosynthesis-Related Genes in Breast Cancer

There is a need to improve diagnostic and therapeutic approaches to enhance the prognosis of breast cancer, the most common malignancy worldwide. Membrane lipid biosynthesis is a hot biological pathway in current cancer research. It is unclear whether membrane lipid biosynthesis is involved in the prognosis of BRCA. With LASSO regression, a 14-gene prediction model was constructed using data from the TCGA-BRCA cohort. The prediction model includes GPAA1, PIGF, ST3GAL1, ST6GALNAC4, PLPP2, ELOVL1, HACD1, SGPP1, PRKD2, VAPB, CERS2, SGMS2, ALDH3B2, and HACD3. BRCA patients from the TCGA-BRCA cohort were divided into two risk subgroups based on the model. Kaplan-Meier survival curves showed that patients with lower risk scores had significantly improved overall survival (P=2.49e - 09). In addition, risk score, age, stage, and TNM classification were used to predict mortality in BRCA patients. In addition, the 14 genes in the risk model were analyzed for gene variation, methylation level, drug sensitivity, and immune cell infiltration, and the miRNA-mRNA network was constructed. Afterward, the THPA website then analyzed the protein expression of 14 of these risk model genes in normal and pathological BRCA tissues. In conclusion, the membrane lipid biosynthesis-related risk model and nomogram can be used to predict BRCA clinical prognosis.