Exploring the correlation of glycolysis-related chondroitin polymerizing factor (CHPF) with clinical characteristics, immune infiltration, and cuproptosis in bladder cancer.

Bladder cancer (BLCA) is a common malignant neoplasm of the urinary system. Glycolysis is an essential metabolic pathway regulated by various genes with implications for tumor progression and immune escape. Scoring the glycolysis for each sample in the TCGA-BLCA dataset was done using the ssGSEA algorithm for quantification. The results showed that the score in BLCA tissues was markedly greater than those in adjacent tissues. Additionally, the score was found to be correlated with metastasis and high pathological stage. Functional enrichment analyses of the glycolysis-related genes showed they were related to roles associated with tumor metastasis, glucose metabolism, cuproptosis, and tumor immunotherapy in BLCA. Using 3 different machine learning algorithms, we identified chondroitin polymerizing factor (CHPF) as a central glycolytic gene with high expression in BLCA. In addition, we showed CHPF is a valuable diagnostic marker of BLCA with an area under the ROC (AUC) of 0.81. Sequencing BLCA 5637 cells after siRNA-mediated CHPF silencing and bioinformatics revealed that CHPF positively correlated with the markers of epithelial-to-mesenchymal transformation (EMT), glycometabolism-related enzymes, and immune cell infiltration. In addition, CHPF silencing inhibited the infiltration of multiple immune cells in BLCA. Genes that promote cuproptosis negatively correlated with CHPF expression and were up-regulated after CHPF silencing. High CHPF expression was a risk factor for overall and progression-free survival of patients who received immunotherapy for BLCA. Finally, using immunohistochemistry, we demonstrated that the CHPF protein had high expression in BLCA, increasing in high-grade tumors and those with muscle invasion. The CHPF expression levels were also positively associated with 18F-fluorodeoxyglucose uptake in PET/CT images. We conclude that the glycolysis-related gene CHPF is an effective diagnostic and treatment target for BLCA.

Clock gene NR1D1 might be a novel target for the treatment of bladder cancer.

PURPOSE: To explore the role of circadian clock gene NR1D1 (REV-erbα) in bladder cancer (BC). METHODS: Firstly, the association of NR1D1 level with clinical characteristics and prognosis was investigated among patients diagnosed with BC. Secondly, CCK-8, transwell, and colony formation experiments were performed among BC cells treated with Rev-erbα agonist (SR9009), as well as lentivirus and siRNA, for which NR1D1 were overexpressed (OE) and knocked down (KD), respectively. Thirdly, cell cycle and apoptosis were tested by flowcytometry. PI3K/AKT/mTOR pathway proteins were determined in OE-NR1D1 cells. Finally, OE-NR1D1 and OE-Control BC cells were subcutaneously implanted in BALB/c nude mice. The tumor size and protein levels were compared between groups. A P < 0.05 was considered as statistically significant. RESULTS: Patients with NR1D1 positive status had a longer disease-free survival than those with negative expression. The cell viability, migration, and colony formation of BC cells after treated with SR9009 were significantly suppressed. OE-NR1D1 cells had obviously inhibited cell viability, migration, and colony formation, while those were found strengthened in KD-NR1D1 cells. Besides, KD-NR1D1 cells were observed with a lower proportion of dead cells and G0/G1 cells, but a higher ratio of G2/M. The changes of p-AKT, p-S6, p-4EBP1, and FASN involved in PI3K/AKT/mTOR pathway were detected in OE- and KD-NR1D1 BC cells. Finally, in vivo data demonstrated that overexpression of NR1D1 suppressed the tumorigenicity of BC cells. CONCLUSION: NR1D1 played a role of tumor suppressor and it might become a novel target for the treatment of BC.

Prognostic value of COL10A1 and its correlation with tumor-infiltrating immune cells in urothelial bladder cancer: A comprehensive study based on bioinformatics and clinical analysis validation.

Introduction: Bladder cancer (BLCA) is one of the most lethal diseases. COL10A1 is secreted small-chain collagen in the extracellular matrix associated with various tumors, including gastric, colon, breast, and lung cancer. However, the role of COL10A1 in BLCA remains unclear. This is the first research focusing on the prognostic value of COL10A1 in BLCA. In this research, we aimed to uncover the association between COL10A1 and the prognosis, as well as other clinicopathological parameters in BLCA. Methods: We obtained gene expression profiles of BLCA and normal tissues from the TCGA, GEO, and ArrayExpress databases. Immunohistochemistry staining was performed to investigate the protein expression and prognostic value of COL10A1 in BLCA patients. GO and KEGG enrichment along with GSEA analyses were performed to reveal the biological functions and potential regulatory mechanisms of COL10A1 based on the gene co-expression network. We used the "maftools" R package to display the mutation profiles between the high and low COL10A1 groups. GIPIA2, TIMER, and CIBERSORT algorithms were utilized to explore the effect of COL10A1 on the tumor immune microenvironment. Results: We found that COL10A1 was upregulated in the BLCA samples, and increased COL10A1 expression was related to poor overall survival. Functional annotation of 200 co-expressed genes positively correlated with COL10A1 expression, including GO, KEGG, and GSEA enrichment analyses, indicated that COL10A1 was basically involved in the extracellular matrix, protein modification, molecular binding, ECM-receptor interaction, protein digestion and absorption, focal adhesion, and PI3K-Akt signaling pathway. The most commonly mutated genes of BLCA were different between high and low COL10A1 groups. Tumor immune infiltrating analyses showed that COL10A1 might have an essential role in recruiting infiltrating immune cells and regulating immunity in BLCA, thus affecting prognosis. Finally, external datasets and biospecimens were used, and the results further validated the aberrant expression of COL10A1 in BLCA samples. Conclusions: In conclusion, our study demonstrates that COL10A1 is an underlying prognostic and predictive biomarker in BLCA.

Leaching characteristics and pollution risk assessment of potentially harmful elements from coal gangue exposed to weathering for different periods of time.

To explore the leaching behavior and potential degree of pollution that can result from the backfilling of goafs with different types of coal gangue (CG), fresh CG from the Hongqi Coal Mine goaf and surface CG (weathered for 1 year) were selected as the research objects in this study. A series of leaching experiments were carried out using the Ordovician limestone karst waters of the mining areas as the soaking solution. A comparative study on the dissolution characteristics of Fe3+, Mn2+, and SO42- and on the traditional water quality parameters of the two types of CG was conducted. The results showed that the soaked, weathered CG displayed a higher ion dissolution value than fresh CG. The ratio of each ion was as follows: Fe3+ was 1, Mn2+ was 2.86 ~ 68.18, and SO42- was 1.34 ~ 2.09. Over time, the ion concentration of water samples that initially contained high ion concentration values showed a decreasing trend after CG was soaked in these waters, but the values were still in the range of high ion release concentrations. The pH and oxidation‒reduction potential (ORP) values of the leachate of both CG types indicated that the leachates were weakly alkaline and weakly oxidizing, and the overall change in total dissolved solids (TDS) was small and consistent with the SO42- trend. SO42- in the leachate of the weathered CG showed a more significant correlation with the pH and TDS of the soaking solution, and it was the major pollutant. According to the geoaccumulation index evaluation, weathered CG had higher pollution potential than fresh CG. Fe3+ presented a slight and moderate risk for contamination.

An autophagy-related gene prognostic index predicting biochemical recurrence, metastasis, and drug resistance for prostate cancer.

Given the dual role of autophagy presenting in tumorigenesis and inhibition, we established an autophagy-related gene prognostic index (ARGPI) with validation to well predict the biochemical recurrence (BCR), metastasis, as well as chemoresistance for patients with prostate cancer (PCa) who underwent radical radiotherapy or prostatectomy. Then, Lasso and COX regression was used to develop the ARGPI. We performed the whole analyses through R packages (version 3.6.3). Secreted phosphoprotein 1 (SPP1), single-minded 2 (SIM2), serine protease inhibitor b5 (SERPINB5), aldehyde dehydrogenase 2 (ALDH2), and acyl-CoA synthetase long-chain 3 (ACSL3) were eventually used to establish the ARGPI score. Patients were divided into two different-risk groups based on the median ARGPI score, high-risk patients with a higher risk of BCR than low-risk patients (hazard ratio [HR]: 5.46, 95% confidence interval [CI]: 3.23-9.24). The risk of metastasis of high-risk patients was higher than low-risk patients (HR: 11.31, 95% CI: 4.89-26.12). In The Cancer Genome Atlas (TCGA) dataset, we observed similar prognostic value of ARGPI in terms of BCR-free survival (HR: 1.79, 95% CI: 1.07-2.99) and metastasis-free survival (HR: 1.80, 95% CI: 1.16-2.78). ARGPI score showed a diagnostic accuracy of 0.703 for drug resistance. Analysis of gene set enrichment analysis (GSEA) indicated that patients in the high-risk group were significantly positively related to interleukin (IL)-18 signaling pathway. Moreover, ARGPI score was significantly related to cancer-related fibroblasts (CAFs; r = 0.36), macrophages (r = 0.28), stromal score (r = 0.38), immune score (r = 0.35), estimate score (r = 0.39), as well as tumor purity (r = -0.39; all P < 0.05). Drug analysis showed that PI-103 was the common sensitive drug and cell line analysis indicated that PC3 was the common cell line of PI-103 and the definitive gene. In conclusion, we found that ARGPI could predict BCR, metastasis, and chemoresistance in PCa patients who underwent radical radiotherapy or prostatectomy.

A pan-cancer analysis of the oncogenic role of leucine zipper protein 2 in human cancer.

In this study, we aimed to perform a pan-cancer analysis of leucine zipper protein 2 (LUZP2). A standardized TCGA pan-cancer dataset was downloaded. Differential expression, clinical prognosis, genetic mutations, immune infiltration, epigenetic modifications, tumor stemness and heterogeneity were analyzed. We conducted all analyses through software R 3.6.3 and its suitable packages. Compared to normal samples, we observed that the LUZP2 mRNA expression was significantly upregulated in LGG, PRAD, LUSC and downregulated in KIRC and other eleven cancer species patients. In terms of overall survival, low-expression of LUZP2 was significantly associated with poor prognosis in lower grade glioma (LGG), lung squamous cell carcinoma (LUSC), kidney renal clear cell carcinoma (KIRC) and prostate adenocarcinoma (PRAD). For progression-free survival, we observed that downregulation of LUZP2 was significantly related to LGG, KIRC, LUSC, and PRAD. Our results observed negative correlations of the stemness of LGG and PRAD with the mRNA expression of LUZP2, whose downregulation was closely associated with poor prognosis. The mutation frequencies of LGG, PRAD, KIRC, and LUSC were 0.4%, 0.4%, 0.3%, and 2.1%, respectively. We detected that the LUZP2 level was negatively associated with TILs in most cancers, including LGG, LUSC, PRAD, and KIRC, while the LUZP2 methylation showed the opposite results. In conclusion, the results of our initial pan-cancer investigation provided a somewhat thorough understanding of the functions of LUZP2 on KIRC, LGG, PRAD, and LUSC.

Prognostic Value of Platelet-to-Lymphocyte Ratio in Non-Muscle Invasive Bladder Cancer Patients: Intravesical Bacillus Calmette-Guerin Treatment After Transurethral Resection of Bladder Tumor.

The objective of this study was to investigate the platelet-to-lymphocyte ratio (PLR) in patients who underwent intravesical treatment for non-muscle invasive bladder cancer (NMIBC). A total of 197 patients who underwent intravesical Bacillus Calmette-Guerin treatment after transurethral resection of bladder (TURB) were included. We divided the patients into different groups according to the treatment stage before and during induction treatment as Group 1 and Group 2, and set the change value of PLR as the Group 3. The cutoff values of PLR were determined through receiver operation characteristics curves analysis. we found a significant difference in recurrence-free survival (RFS) and progression-free survival (PFS) between patients with high serum PLR and those with low serum PLR in Group 1, as well as Group 2. Cox multivariate analysis revealed that tumor number ≥3, high grade, and history of carcinoma in situ (CIS) were significant factors predicting RFS and PFS. The PLR values before and during induction therapy could be used as predictors for the progression and recurrence of NMIBC patients receiving BCG immunotherapy. the PLR values after induction therapy have a stronger predictive power.

An inflammation-related signature could predict the prognosis of patients with kidney renal clear cell carcinoma.

Background: Kidney renal clear cell carcinoma (KIRC) is an inflammation-related carcinoma, and inflammation has been recognized as an important factor in inducing carcinogenesis. To further explore the role of inflammation in KIRC, we developed an inflammation-related signature and verified its correlation with the tumor micro-environment. Methods: After the differential inflammation-related prognostic genes were screened by Lasso regression, the inflammation-related signature (IRS) was constructed based on the risk score of multivariate Cox regression. Then, the prognostic value of the IRS was evaluated by Kaplan-Meier analysis, receiver operating characteristic (ROC) curve analysis and multivariate Cox regression. Gene set variation analysis (GSVA) was applied to screen out enriched signaling pathways. Infiltrated immune cells, tumor mutational burden (TMB) and immune checkpoints were explored by CIBERSORTx and maftool. Results: Four genes (TIMP1, PLAUR, CCL22, and IL15RA) were used to construct the IRS in patients with KIRC. Kaplan-Meier analysis and multivariate Cox regression identified that the IRS could independently predict the prognosis of patients with KIRC in the training and validation groups. The diagnostic value of the nomogram increased from 0.811 to 0.845 after adding the IRS to the multiparameter ROC analysis. The GSVA results indicated that IRS was closely related to primary immunodeficiency and antigen processing and presentation. The immune checkpoint LAG3 was highly expressed in patients with high-risk score (p < 0.05), while CD274 (PD-L1) and HAVCR2 were highly expressed in patients with low-risk score (p < 0.001). There was a significant positive correlation between the high-risk score group and CD8+ T, activated CD4+ memory T, gamma and delta regulatory T and M0 macrophage cells, while the low-risk score group was negatively associated with B memory, plasma, resting CD4+ memory T, activated NK, M1 macrophages and resting mast cells. Conclusion: We found that the IRS might serve as a biomarker to predict the survival of KIRC. Moreover, patients with high or low-risk score might be sensitive to immune drugs at different immune checkpoints.

Lymphocyte-to-Monocyte Ratio (LMR) During Induction Is a Better Predictor Than Preoperative LMR in Patients Receiving Intravesical Bacillus Calmette -Guerin for Non-Muscle-Invasive Bladder Cancer.

The prognostic value of the lymphocyte-to-monocyte ratio during induction (ILMR) remains unclear in non-muscle-invasive bladder cancer (NMIBC) patients receiving Bacillus Calmette-Guérin (BCG). We aimed to determine and compare the prognostic value of the ILMR, preoperative lymphocyte-to-monocyte ratio (PLMR) and their dynamic changes (PILMR). This study collected the data from NMIBC patients receiving BCG treatment in our institution. The prognostic value of the PLMR, ILMR and PILMR was analyzed by the Kaplan-Meier method and Cox proportional hazard regression models. The concordance index and receiver operating characteristic curve analysis were employed to compare the prognostic value of these three factors. Our study enrolled 197 patients. These patients included 170 male patients, and the mean age was 64.17 years. During the follow-up time, 85 patients experienced recurrence, and 55 patients experienced progression. According to the results of COX multivariable analysis, PLMR (P=0.011) and ILMR (P<0.001) could independently predict the recurrence of NMIBC patients receiving BCG. Meanwhile, ILMR (P=0.001) and PILMR (P=0.036) were also the independent prognostic factors of progression. Compared with PLMR and PILMR, ILMR was associated with better accuracy for NMIBC patients receiving BCG. This study first found that the ILMR could independently predict the prognosis of NMIBC patients receiving BCG. Furthermore, we also identified that ILMR was associated with higher prognostic value than PLMR and PILMR, which might help to select an optimal treatment schedule for patients with NMIBC.

A gene prognostic index from cellular senescence predicting metastasis and radioresistance for prostate cancer.

BACKGROUND: Senescent cells have been identified in the aging prostate, and the senescence-associated secretory phenotype might be linked to prostate cancer (PCa). Thus, we established a cellular senescence-related gene prognostic index (CSGPI) to predict metastasis and radioresistance in PCa. METHODS: We used Lasso and Cox regression analysis to establish the CSGPI. Clinical correlation, external validation, functional enrichment analysis, drug and cell line analysis, and tumor immune environment analysis were conducted. All analyses were conducted with R version 3.6.3 and its suitable packages. RESULTS: We used ALCAM and ALDH2 to establish the CSGPI risk score. High-risk patients experienced a higher risk of metastasis than their counterparts (HR: 10.37, 95% CI 4.50-23.93, p < 0.001), consistent with the results in the TCGA database (HR: 1.60, 95% CI 1.03-2.47, p = 0.038). Furthermore, CSGPI had high diagnostic accuracy distinguishing radioresistance from no radioresistance (AUC: 0.938, 95% CI 0.834-1.000). GSEA showed that high-risk patients were highly associated with apoptosis, cell cycle, ribosome, base excision repair, aminoacyl-tRNA biosynthesis, and mismatch repair. For immune checkpoint analysis, we found that PDCD1LG2 and CD226 were expressed at significantly higher levels in patients with metastasis than in those without metastasis. In addition, higher expression of CD226 significantly increased the risk of metastasis (HR: 3.65, 95% CI 1.58-8.42, p = 0.006). We observed that AZD7762, PHA-793887, PI-103, and SNX-2112 might be sensitive to ALDH2 and ALCAM, and PC3 could be the potential cell line used to investigate the interaction among ALDH2, ALCAM, and the above drugs. CONCLUSIONS: We found that CSGPI might serve as an effective biomarker predicting metastasis probability and radioresistance for PCa and proposed that immune evasion was involved in the process of PCa metastasis.

Metformin exerts an antitumor effect by inhibiting bladder cancer cell migration and growth, and promoting apoptosis through the PI3K/AKT/mTOR pathway.

BACKGROUND: To observe and explore the effect of metformin on the migration and proliferation of bladder cancer T24 and 5637 cells in vitro. METHODS: Bladder cancer T24 and 5637 cell lines were cultured in vitro, and were divided into group A (blank control group) and group B (metformin group: 5, 10, 15, and 20 mmol/L); both groups were plated on 6-well plates at the same time. Culture in 24-well plates was used for wound healing assays and in 96-well plates for Transwell migration and invasion, and Cell Counting Kit-8 proliferation experiments. We observed and detected the cell migration and proliferation ability of each group at 48 h, and calculated the cell migration area and survival rate. Flow cytometry was used to detect cell apoptosis in the groups. The apoptosis-related proteins, cleaved-caspase 3, cleaved-PARP, and the PI3K/AKT/mTOR signaling pathway member proteins PI3K, phosphorylated (p)-PI3K, AKT, p-AKT, mTOR, and p-mTOR were detected using western blotting. RESULTS: After 48 h of treatment with different concentrations of metformin, the cell migration and proliferation capabilities were significantly lower than those in the blank control group. The proliferation and migration abilities of T24 and 5637 cells decreased in a metformin concentration-dependent manner (P < 0.05). The apoptosis rate under different concentrations of metformin, as detected by flow cytometry, showed a significantly higher rate in the metformin group than in the control group (P < 0.05). Compared with that in the control group, the level of cleaved-caspase 3 and cleaved-PARP protein in the metformin group was increased in each treatment group, and the levels of p-mTOR, p-AKT, and p-PI3K decreased significantly compared with those in the control group (P < 0.05). CONCLUSION: Metformin inhibited bladder cancer T24 and 5637 cell migration and proliferation, and induced their apoptosis. The mechanism might involve inhibition of the activation of the PI3K/AKT/mTOR signaling pathway.

Mitochondria Dysfunction-Mediated Molecular Subtypes and Gene Prognostic Index for Prostate Cancer Patients Undergoing Radical Prostatectomy or Radiotherapy.

Background: Given the age relevance of prostate cancer (PCa) and the role of mitochondrial dysfunction (MIDS) in aging, we orchestrated molecular subtypes and identified key genes for PCa from the perspective of MIDS. Methods: Cluster analysis, COX regression analysis, function analysis, and tumor immune environment were conducted. We performed all analyses using software R 3.6.3 and its suitable packages. Results: CXCL14, SFRP4, and CD38 were eventually identified to classify the PCa patients in The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) dataset into two distinct clusters. Patients in the cluster 2 had shorter BCR-free survival than those in the cluster 1 in terms of both TCGA database and GEO dataset. We divided the patients from the TCGA database and the GEO dataset into high- and low-risk groups according to the median of MIDS-related genetic prognostic index. For patients in the TCGA database, the biochemical recurrence (BCR) risk in high-risk group was 2.34 times higher than that in low-risk group. Similarly, for patients in the GEO dataset, the risk of BCR and metastasis in high-risk group was 2.35 and 3.04 times higher than that in low-risk group, respectively. Cluster 2 was closely associated with advanced T stage and higher Gleason score for patients undergoing radical prostatectomy or radiotherapy. For patients undergoing radical prostatectomy, the number of CD8+ T cells was significantly lower in cluster 2 than in cluster 1, while cluster 2 had significantly higher stromal score than cluster 1. For patients undergoing radical radiotherapy, cluster 2 had significantly higher level of CD8+ T cells, neutrophils, macrophages, dendritic cells, stromal score, immune score, and estimate score, but showed lower level of tumor purity than cluster 1. Conclusions: We proposed distinctly prognosis-related molecular subtypes at genetic level and related formula for PCa patients undergoing radical prostatectomy or radiotherapy, mainly to provide a roadmap for precision medicine.

Bioinformatics and System Biology Approach to Identify the Influences of COVID-19 on Rheumatoid Arthritis.

Background: Severe coronavirus disease 2019 (COVID -19) has led to a rapid increase in mortality worldwide. Rheumatoid arthritis (RA) was a high-risk factor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, whereas the molecular mechanisms underlying RA and CVOID-19 are not well understood. The objectives of this study were to analyze potential molecular mechanisms and identify potential drugs for the treatment of COVID-19 and RA using bioinformatics and a systems biology approach. Methods: Two Differentially expressed genes (DEGs) sets extracted from GSE171110 and GSE1775544 datasets were intersected to generate common DEGs, which were used for functional enrichment, pathway analysis, and candidate drugs analysis. Results: A total of 103 common DEGs were identified in the two datasets between RA and COVID-19. A protein-protein interaction (PPI) was constructed using various combinatorial statistical methods and bioinformatics tools. Subsequently, hub genes and essential modules were identified from the PPI network. In addition, we performed functional analysis and pathway analysis under ontological conditions and found that there was common association between RA and progression of COVID-19 infection. Finally, transcription factor-gene interactions, protein-drug interactions, and DEGs-miRNAs coregulatory networks with common DEGs were also identified in the datasets. Conclusion: We successfully identified the top 10 hub genes that could serve as novel targeted therapy for COVID-19 and screened out some potential drugs useful for COVID-19 patients with RA.

Developing an immune-related gene prognostic index associated with progression and providing new insights into the tumor immune microenvironment of prostate cancer.

We developed an immune-related gene prognostic index (IGPI) associated with progression and provided new insights into the tumour immune microenvironment (TIME) for prostate cancer (PCA) patients undergoing radical prostatectomy. All analyses were conducted with R software (version 3.6.3) and its suitable packages. Meta-analysis was performed with STATA 16.0. TUBB3, WDR62 and PPARGC1A were finally identified to establish the IGPI score. The IGPI score increased with the augment of the Gleason score and T stage, as well as biochemical recurrence (BCR) and prostate specific antigen (PSA). Patients with a higher IGPI score were at a higher risk of progress (HR: 2·88; 95%CI: 95%CI: 1·80-4·61). Gene set enrichment analysis indicated that patients in high-risk group were positively associated with mismatch repair, cell cycle, DNA replication, base excision repair, nucleotide excision repair, homologous recombination and pyrimidine metabolism. We observed that patients in the high-risk group had significantly higher tumour mutation burden score and microsatellite instability score than those in the low-risk group. For analysis of immune checkpoint, ADORA2A, CD80, TNFRSF4, TNFRSF18 and TNFRSF25 were differentially expressed between no progress and progress groups and were significantly associated with progress free survival. We observed positive correlations between the IGPI score and lymphoid immune cells, macrophages M2 and immune score, while negative association between the IGPI score and dendritic cells, fibroblasts, stromal score and microenvironment score. In conclusion, the IGPI score constructed in this study might serve as an independent risk factor associated with PCA progression. ADORA2A, CD80, TNFRSF4, TNFRSF18 and TNFRSF25 might be the potential targets in the treatment of PCA.

Energy Metabolism-Related Gene Prognostic Index Predicts Biochemical Recurrence for Patients With Prostate Cancer Undergoing Radical Prostatectomy.

Background: We aimed to construct and validate an energy metabolism-related gene prognostic index (EMRGPI) to predict biochemical recurrence (BCR) in patients undergoing radical prostatectomy. Methods: We used Lasso and COX regression analysis to orchestrate the EMRGPI in the TCGA database, and the prognostic value of EMRGPI was further validated externally using the GSE46602. All analyses were conducted with R version 3.6.3 and its suitable packages. Results: SDC1 and ADH1B were finally used to construct the risk formula. We classified the 430 tumor patients in the TCGA database into two groups, and patients in the high-risk group had a higher risk of BCR than those in the low-risk group (HR: 1.98, 95%CI: 1.18-3.32, p=0.01). Moreover, in the GSE46602, we confirmed that the BCR risk in the high-risk group was 3.86 times higher than that in the low-risk group (95%CI: 1.61-9.24, p=0.001). We found that patients in the high-risk group had significantly higher proportions of residual tumor, older age, and T stage. SDC1 and ADH1B were significantly expressed low in the normal tissues when compared to the tumor tissues, which were opposite at the protein level. The spearman analysis showed that EMRGPI was significantly associated with B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, dendritic cells, stromal score, immune score, and estimate score. In addition, the EMRGPI was positively associated with the 54 immune checkpoints, among which CD80, ADORA2A, CD160, and TNFRSF25 were significantly related to the BCR-free survival of PCa patients undergoing RP. Conclusions: The EMRGPI established in this study might serve as an independent risk factor for PCa patients undergoing radical prostatectomy.

MYBL2 is a Novel Independent Prognostic Biomarker and Correlated with Immune Infiltrates in Prostate Cancer.

Purpose: MYB proto-oncogene like 2 (MYBL2) is a member of the MYB family of transcription factor genes and overexpressed in many cancers. We investigated the role of MYBL2 in the malignant progression of prostate cancer (PCa) and its relationship with immune infiltrates in PCa. Methods: Gene expression level, clinicopathological parameters, Gene Ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway, tumor immune infiltration analysis were based on The Cancer Genome Atlas (TCGA) dataset. Gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA) were conducted to analyze the correlation between MYBL2 and immune infiltrates. The data processing analysis based on R language. The relationship between MYBL2 expression and immune response in PCa was analyzed on TIMER 2.0. Results: MYBL2 was overexpressed in PCa patients, and correlated with T-stage, Gleason score, primary therapy outcome and progress free interval (PFI) event. The multivariate Cox regression analysis revealed MYBL2 was an independent risk factor for PFI (HR=1.250, 95% CI=1.016-1.537, p=0.035). The receiver operating characteristic (ROC) curve for MYBL2 (AUC=0.887) and nomogram also confirmed the diagnostic value of MYBL2 in the treatment of PCa patients. Based on mRNA expression of MYBL2, PCa patients were divided into MYBL2-high group and MYBL2-low group, and analysis of MYBL2 associated KEGG and GO pathways using R language revealed that 6 immune-related signaling pathways were enriched in MYBL2-high expression phenotype. GSEA analysis showed that 3 hallmark gene sets related to immune response were significantly enriched in MYBL2-high group, ssGSEA analysis found that MYBL2 expression correlated with the expression of many tumor immune lymphocytes (CD8+T cells, neutrophil cells, macrophage cells and so on) and immune check point inhibitors (CD276, BTLA, TNFRSF18, HAVCR2 and CD70). Conclusion: MYBL2 is a novel independent prognostic biomarker and MYBL2 may play a crucial role in tumor immune microenvironment of PCa.

A Ferroptosis-Related Gene Prognostic Index Associated With Biochemical Recurrence and Radiation Resistance for Patients With Prostate Cancer Undergoing Radical Radiotherapy.

Background: Ferroptosis is a new type of programmed cell death which has been reported to be involved in the development of various cancers. In this study, we attempted to explore the possible links between ferroptosis and prostate cancer (PCa), and a novel ferroptosis-related gene prognostic index (FGPI) was constructed to predict biochemical recurrence (BCR) and radiation resistance for PCa patients undergoing radical radiotherapy (RRT). Moreover, the tumor immune microenvironment (TME) of PCa was analyzed. Methods: We merged four GEO datasets by removing batch effects. All analyses were conducted with R version 3.6.3 and its suitable packages. Cytoscape 3.8.2 was used to establish a network of transcriptional factor and competing endogenous RNA. Results: We established the FGPI based on ACSL3 and EPAS1. We observed that FGPI was an independent risk factor of BCR for PCa patients (HR: 3.03; 95% CI: 1.68-5.48), consistent with the result of internal validation (HR: 3.44; 95% CI: 1.68-7.05). Furthermore, FGPI showed high ability to identify radiation resistance (AUC: 0.963; 95% CI: 0.882-1.00). LncRNA PART1 was significantly associated with BCR and might modulate the mRNA expression of EPAS1 and ACSL3 through interactions with 60 miRNAs. Gene set enrichment analysis indicated that FGPI was enriched in epithelial-mesenchymal transition, allograft rejection, TGF beta signaling pathway, and ECM receptor interaction. Immune checkpoint and m6A analyses showed that PD-L2, CD96, and METTL14 were differentially expressed between BCR and no BCR groups, among which CD96 was significantly associated with BCR-free survival (HR: 1.79; 95% CI: 1.06-3.03). We observed that cancer-related fibroblasts (CAFs), macrophages, stromal score, immune score, estimate score, and tumor purity were differentially expressed between BCR and no BCR groups and closely related to BCR-free survival (HRs were 2.17, 1.79, 2.20, 1.93, 1.92, and 0.52 for cancer-related fibroblasts, macrophages, stromal score, immune score, estimate score, and tumor purity, respectively). Moreover, cancer-related fibroblasts (coefficient: 0.20), stromal score (coefficient: 0.14), immune score (coefficient: 0.14), estimate score (coefficient: 0.15), and tumor purity (coefficient: -0.15) were significantly related to FGPI, among which higher positive correlation between cancer-related fibroblasts and FGPI was observed. Conclusion: We found that FGPI based on ACSL3 and EPAS1 might be used to predict BCR and radiation resistance for PCa patients. CD96 and PD-L2 might be a possible target for drug action. Besides, we highlighted the importance of immune evasion in the process of BCR.

Identification of a Novel Nomogram to Predict Progression Based on the Circadian Clock and Insights Into the Tumor Immune Microenvironment in Prostate Cancer.

Background: Currently, the impact of the circadian rhythm on the tumorigenesis and progression of prostate cancer (PCA) has yet to be understood. In this study, we first established a novel nomogram to predict PCA progression based on circadian clock (CIC)-related genes and provided insights into the tumor immune microenvironment. Methods: The TCGA and Genecards databases were used to identify potential candidate genes. Lasso and Cox regression analyses were applied to develop a CIC-related gene signature. The tumor immune microenvironment was evaluated through appropriate statistical methods and the GSCALite database. Results: Ten genes were identified to construct a gene signature to predict progression probability for patients with PCA. Patients with high-risk scores were more prone to progress than those with low-risk scores (hazard ratio (HR): 4.11, 95% CI: 2.66-6.37; risk score cut-off: 1.194). CLOCK, PER (1, 2, 3), CRY2, NPAS2, RORA, and ARNTL showed a higher correlation with anti-oncogenes, while CSNK1D and CSNK1E presented a greater relationship with oncogenes. Overall, patients with higher risk scores showed lower mRNA expression of PER1, PER2, and CRY2 and higher expression of CSNK1E. In general, tumor samples presented higher infiltration levels of macrophages, T cells and myeloid dendritic cells than normal samples. In addition, tumor samples had higher immune scores, lower stroma scores and lower microenvironment scores than normal samples. Notably, patients with higher risk scores were associated with significantly lower levels of neutrophils, NK cells, T helper type 1, and mast cells. There was a positive correlation between the risk score and the tumor mutation burden (TMB) score, and patients with higher TMB scores were more prone to progress than those with lower TMB scores. Likewise, we observed similar results regarding the correlation between the microsatellite instability (MSI) score and the risk score and the impact of the MSI score on the progression-free interval. We observed that anti-oncogenes presented a significantly positive correlation with PD-L1, PD-L2, TIGIT and SIGLEC15, especially PD-L2. Conclusion: We identified ten prognosis-related genes as a promising tool for risk stratification in PCA patients from the fresh perspective of CIC.

NUDT1 Could Be a Prognostic Biomarker and Correlated with Immune Infiltration in Clear Cell Renal Cell Carcinoma.

Background: Clear cell renal cell carcinoma (ccRCC) is a malignant tumor with high morbidity and mortality. As a member of the Nudix hydrolase superfamily, Nudix (nucleoside diphosphate-linked moiety X)-type motif 1 (NUDT1) is closely related to the occurrence and development of cancer. Our study aims to explore the role of NUDT1 in ccRCC and its relationship with immune infiltration. Methods: The NUDT1 expression matrix and corresponding clinical information were obtained from The Cancer Genome Atlas (TCGA) database. The expression difference of NUDT1 in ccRCC and its relationship with the clinical characteristics were investigated using R software. Kaplan-Meier (K-M) analysis, univariate Cox regression, multivariate Cox regression, receiver operating characteristic (ROC) curve, and nomogram were utilized to evaluate the survival and prognosis of patients. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were utilized to explore the function of differential genes in low- or high-expression group of NUDT1. TCGA dataset and Tumor IMmune Estimation Resource (TIMER) database were utilized to explore the relationship between NUDT1 and immune infiltration. Finally, TCGA dataset was utilized for gene set enrichment analysis (GSEA). Results: NUDT1 was not only overexpressed in ccRCC but also significantly correlated with clinicopathological features (P < 0.05). K-M survival analysis showed that upregulated NUDT1 was closely related to the decrease of overall survival (OS) and progression-free survival (PFS) in ccRCC patients. Multivariate Cox regression revealed that NUDT1 was a independent prognostic indicator (HR = 1.437, 95% CI: 1.065-1.939, P=0.018). The ROC curve showed that NUDT1 had a certain accuracy in predicting the outcome of ccRCC patiens. Furthermore, a total of 150 coexpressed genes and 1,886 differentially expressed genes (DEGs) were identified. GO/KEGG and GSEA results suggested that NUDT1 and its DEGs were involved in the immune-related pathways. NUDT1 expression was positively correlated with infiltrating levels of regulatory T cells (Tregs), CD8+ T cells, follicular helper T cells, and M0 macrophages. In addition, NUDT1 was positively related to immune checkpoints, such as PD-1, LAG3, CTLA4, and CD70, in ccRCC. Conclusion: NUDT1 plays a key role in the prognosis and immune cell infiltration of ccRCC patients, indicating its potential use as a prognostic biomarker and therapeutic target.

SKA3 Serves as a Biomarker for Poor Prognosis in Kidney Renal Papillary Cell Carcinoma.

BACKGROUND: There is a surprising paucity of studies investigating the potential mechanism of SKA3 in the progression and prognosis of kidney renal papillary cell carcinoma (KIRP). METHODS: We used TCGA and other databases to analyze the expression, clinical value, and potential mechanisms of SKA3 in KIRP patients. We also explored therapeutic agents for KIRP through GSCALite. RESULTS: SKA3 mRNA expression was significantly upregulated and the area under the curve was 0.792 (95% CI 0.727-0.856). Increased SKA3 expression was related to shorter overall survival, disease-specific survival and progression-free survival. Hub genes in protein-protein interactions were CDK1, CDC20, CCNB1, CCNA2, BUB1, AURKB, BUB1B, PLK1, CCNB2, and MAD2L1, which were differentially expressed and also associated with KIRP prognosis. Gene-set enrichment analysis indicated that E2F targets, epithelial-mesenchymal transition, glycolysis, the WNT signaling pathway, and other pathways were highly enriched upon SKA3 upregulation. Gene-set variation analysis of SKA3 and its ten hub genes showed that the significant correlation of cancer-related pathways included the cell cycle, DNA damage, hormone androgen receptor, hormone estrogen receptor, PI3K/Akt, and Ras/MAPK. In addition, we found that MEK inhibitors, ie, trametinib, selumetinib, PD0325901, and RDEA119, may be feasible targeting agents for KIRP patients. CONCLUSION: SKA3 might contribute to poor prognosis of KIRP through cell cycle, DNA damage, hormone androgen receptor, hormone estrogen receptor, PI3K/Akt, and RAS/MAPK. SKA3 potentially serves as a prognostic biomarker and target for KIRP.