Telomerase related molecular subtype and risk model reveal immune activity and evaluate prognosis and immunotherapy response in prostate cancer.

BACKGROUND: Prostate cancer ranks among the six most lethal malignancies worldwide. Telomerase, a reverse transcriptase enzyme, plays a pivotal role in extending cellular telomeres and is intimately associated with cell proliferation and division. However, the interconnection between prostate cancer and telomerase-related genes (TEASEs) remains unclear. METHODS: Somatic mutations and copy number alterations of TEASEs were comprehensively analyzed. Subsequently, the transcripts of prostate cancer patients in TCGA and GEO databases were integrated to delineate new molecular subtypes. Followed by constructing a risk model containing nine characteristic genes through Lasso regression and Cox prognostic analysis among different subtypes. Various aspects including prognosis, tumor microenvironment (TME), landscape of immunity, tumor mutational burden (TMB), stem cell correlation, and median inhibitory concentration amongst different risk groups were compared. Finally, the expression, prognosis, and malignant biological behavior of ZW10 interactor (ZWINT) in vitro was explored. RESULTS: TEASEs exhibited a notably high mutation frequency. Three distinct molecular subtypes and two gene subclusters based on TEASEs were delineated, displaying significant associations with prognosis, immune function regulation, and clinical characteristics. Low-risk patients demonstrated superior prognosis and better response to immunotherapy. Conversely, high-risk patients exhibited higher TMB and stronger stem cell correlations. It was also found that the patients' sensitivity to chemotherapy agents was impacted by the risk score. Finally, ZWINT's potential as a novel diagnostic and prognostic biomarker for prostate cancer was validated. CONCLUSIONS: TEASEs play a pivotal role in modulating immune regulation and immunotherapeutic responses, thereby significantly impacting the diagnosis, prognosis, and treatment strategies for affected patients.

Inflammatory cytokine profiles in erectile dysfunction: a bidirectional Mendelian randomization.

Objectives: Inflammatory cytokines (ICs) play an important role in erectile dysfunction (ED). Previous studies have demonstrated that most ED patients have high levels of tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6) and interleukin-8 (IL-8). The causality between 41 ICs and ED is investigated using the Mendelian randomization (MR) approach. Methods: Single nucleotide polymorphisms (SNPs) exposure data of 41 ICs came from a genome-wide association study (GWAS) of 8293 subjects. At the same time, the FINNGEN R9 database provided the ED outcome data containing 2205 ED patients and 164104 controls. MR-Egger (ME), inverse variance weighting (IVW), and weighted median (WM) were applied to conduct the MR study and IVW was taken as the main criterion. Results: From a genetic perspective, the increase of interferon-inducible protein-10 (IP-10) level significantly increased the risk of ED (P=0.043, odds ratio (OR)=1.269, 95% confidence interval (95%CI): 1.007-1.600), while the increase of interleukin-1 receptor antagonist (IL-1RA) markedly decreased the risk of ED (P=0.037, OR=0.768, 95%CI: 0.600-0.984). Meanwhile, IP-10 (p=0.099) and IL-1RA (p=0.135) failed to demonstrate causality in reverse MR analysis. Conclusions: Changes in ICs levels will significantly affect the risk of ED, especially IP-10 as a risk component for ED and IL-1RA as a protective component for ED. In the future, we can achieve targeted treatment and prevention of ED by intervening with specific inflammatory factors.

Comprehensive analysis of disulfidptosis-related genes: a prognosis model construction and tumor microenvironment characterization in clear cell renal cell carcinoma.

BACKGROUND: Disulfidptosis, a form of cell death induced by abnormal intracellular accumulation of disulfides, is a newly recognized variety of cell death. Clear cell renal cell carcinoma (ccRCC) is a usual urological tumor that poses serious health risks. There are few studies of disulfidptosis-related genes (DRGs) in ccRCC so far. METHODS: The expression, transcriptional variants, and prognostic role of DRGs were assessed. Based on DRGs, consensus unsupervised clustering analysis was performed to stratify ccRCC patients into various subtypes and constructed a DRG risk scoring model. Patients were stratified into high or low-risk groups by this model. We focused on assessing the discrepancy in prognosis, TME, chemotherapeutic susceptibility, and landscape of immune between the two risk groups. Finally, we validated the expression and explored the biological function of the risk scoring gene FLRT3 through in vitro experiments. RESULTS: The different subtypes had significantly different gene expression, immune, and prognostic landscapes. In the two risk groups, the high-risk group had higher TME scores, more significant immune cell infiltration, and a higher probability of benefiting from immunotherapy, but had a worse prognosis. There were also remarkable differences in chemotherapeutic susceptibility between the two risk groups. In ccRCC cells, the expression of FLRT3 was shown to be lower and its overexpression caused a decrease in cell proliferation and metastatic capacity. CONCLUSIONS: Starting from disulfidptosis, we established a new risk scoring model which can provide new ideas for doctors to forecast patient survival and determine clinical treatment plans.

Experimental validation and pan-cancer analysis identified COL10A1 as a novel oncogene and potential therapeutic target in prostate cancer.

BACKGROUND: Type X collagen (COL10) is a homologous trimeric non-fibrillar collagen found in the extracellular matrix of human tissues, and it exhibits a distinctive white appearance. Type X collagen α1 chain (COL10A1) is a specific cleaved fragment of type X collagen. However, the expression, prognostic significance, clinicopathological attributes and immune-related associations of COL10A1 in prostate cancer as well as in pan-cancer contexts remain poorly understood. METHODS: Using bioinformatic analysis of data from the most recent databases (TCGA, GTEx and GEO databases), we have extensively elucidated the role played by COL10A1 in terms of its expression patterns, prognostic implications, and immune efficacy across a pan-cancer spectrum. Subsequently, the biological functions of COL10A1 in prostate cancer were elucidated by experimental validation. RESULTS: Our findings have confirmed that COL10A1 was highly expressed in most cancers and was associated with poorer prognosis in cancer patients. Immune correlation analysis of COL10A1 in various cancers showed its significant correlation with Tumor mutational burden (TMB), microsatellite instability (MSI) and immune cell infiltration. In addition, knockdown of COL10A1 in prostate cancer resulted in a substantial reduction in the proliferation, migration, and invasive potential of prostate cancer cells. CONCLUSION: Our pan-cancer analysis of COL10A1 gene provided novel insights into its pivotal role in cancer initiation, progression, and therapeutic implications, underscoring its potential significance in prognosis and immunotherapeutic interventions for cancer, particularly prostate cancer.

CHMP4C as a novel marker regulates prostate cancer progression through cycle pathways and contributes to immunotherapy.

Background: CHMP4C is one of the charged multivesicular protein (CHMP), and is involved in the composition of the endosomal sorting complex required for transport III (ESCRT-III), facilitating the necessary separation of daughter cells. CHMP4C has been proposed to be involved in the progression of different carcinomas. However, the value of CHMP4C in prostate cancer has not yet been explored. Prostate cancer is the most frequently occurring malignancy among male and remains a leading cause of deaths in cancers. So far, clinical therapy of prostate cancer is more inclined to molecular classification and specific clinical treatment and research. Our study investigated the expression and clinical prognosis of CHMP4C and explored its potential regulatory mechanism in prostate cancer. The immune status of CHMP4C in prostate cancer and relative immunotherapy were then analyzed in our study. Based on CHMP4C expression, a new subtype of prostate cancer was established for precision treatment. Methods: We studied the expression of CHMP4C and relative clinical outcome using the online databases TIMER, GEPIA2, UALCAN, and multiple R packages. Meanwhile, the biological function, immune microenvironment and immunotherapy value of CHMP4C in prostate cancer were further explored on the R software platform with different R packages. Then we performed qRT-PCR, Western Blotting, transwell, CCK8, wound healing assay, colony formation assay and immunohistochemistry to verify the expression of CHMP4C, carcinogenesis and potential regulatory mechanisms in prostate cancer. Results: We found that the expression of CHMP4C is significant in prostate cancer and the high expression of CHMP4C represents a poor clinical prognosis and malignant progression of prostate cancer. In subsequent vitro validation, CHMP4C promoted the malignant biological behavior of prostate cancer cell lines by adjusting the cell cycle. Based on CHMP4C expression, we established two new subtypes of prostate cancer and found that low CHMP4C expression has a better immune response while high CHMP4C expression was more sensitive to paclitaxel and 5-fluorouracil. Above findings revealed a new diagnostic marker for prostate cancer and facilitated the subsequent precise treatment of prostate cancer.

Pan-cancer analysis reveals the prognostic and immunotherapeutic value of cytoskeleton-associated protein 2-like.

Cytoskeleton-associated protein 2-like (CKAP2L), a cell cycle-related protein, is correlated to tumor progression in some tumors. But there were no pan-cancer studies on CKAP2L, and its role in cancer immunotherapy is also unclear. The expression levels, expression activity, genomic alterations, DNA methylation and functions of CKAP2L in various tumors, as well as the associations between CKAP2L expression and patient prognosis, chemotherapy sensitivity, and tumor immune microenvironment, were all analyzed in a comprehensive pan-cancer analysis of CKAP2L by various databases, analysis websites, and R software. The experiments were also conducted to verify the analysis results. In the majority of cancers, CKAP2L expression and activity were markedly elevated. Elevated CKAP2L expression led to poor prognostic outcomes in patients, and is an independent risk factor for most tumors. Elevated CKAP2L causes decreased sensitivity to chemotherapeutic agents. Knockdown of CKAP2L significantly inhibited the proliferation and metastasis capacity of the KIRC cell lines and resulted in cell cycle G2/M arrest. In addition, CKAP2L was closely related to immune subtypes, immune cell infiltration, immunomodulators and immunotherapy markers (TMB, MSI), patients with high CKAP2L expression were more sensitive to immunotherapy in the IMvigor210 cohort. The results indicate that CKAP2L is a pro-cancer gene that serves as a potential biomarker for predicting patient outcomes. By inducing cells to transition from the G2 phase to the M phase, CKAP2L may promote cell proliferation and metastasis. Furthermore, CKAP2L is closely related to the tumor immune microenvironment and can be used as a biomarker to predict tumor immunotherapy.

Pan-cancer analysis of the prognostic and immunological role of PAQR4.

Progestin and adipoQ receptor family member 4 (PAQR4) is a protein-coding gene. Recent studies have shown that PAQR4 is related to the development of multiple cancers. However, there is no systematic pan-cancer analysis of this gene. In this study, the expression of PAQR4, correlations with clinical prognosis, immune situation, and its potential molecular functions and mechanisms in pan-cancer were explored by bioinformatics analysis. The Cancer Genome Atlas was applied to investigate the relations between PAQR4 and clinical features, prognostic effects, and tumor immune microenvironment. R software was used to perform statistical analysis and figure creation. The expression of PAQR4 in BLCA and KIRC was validated by qRT-PCR and immunohistochemistry, and its function was explored by cellular experiments. Bioinformatics analysis revealed that PAQR4 was up-regulated in multiple cancers and related to poor prognosis. The high expression of PAQR4 was closely associated with high tumor stage, immune cell infiltration, tumor mutation burden, and microsatellite instability in different cancer types. In addition, the high expression of PAQR4 also indicated involvement in the immune regulatory pathways. The involvement of PAQR4 in the immune regulation of different tumors was confirmed by GSEA enrichment analysis. Moreover, PAQR4 was highly expressed in bladder cancer and renal clear cell carcinoma tissues and cell lines. Cell proliferation, migration, and invasion of bladder cancer and renal clear cell carcinoma cell lines were significantly decreased after the knockdown of PAQR4. This study elucidated the role of PAQR4 in carcinogenesis as well as tumor immunity. PAQR4 may serve as a potential prognostic biomarker in a variety of cancers.

Cuproptosis-Associated lncRNA Establishes New Prognostic Profile and Predicts Immunotherapy Response in Clear Cell Renal Cell Carcinoma.

Background: Clear cell renal cell carcinoma (ccRCC) accounts for 80% of all kidney cancers and has a poor prognosis. Recent studies have shown that copper-dependent, regulated cell death differs from previously known death mechanisms (apoptosis, ferroptosis, and necroptosis) and is dependent on mitochondrial respiration (Tsvetkov et al., Science, 2022, 375 (6586), 1254-1261). Studies also suggested that targeting cuproptosis may be a novel therapeutic strategy for cancer therapy. In ccRCC, both cuproptosis and lncRNA were critical, but the mechanisms were not fully understood. The aim of our study was to construct a prognostic profile based on cuproptosis-associated lncRNAs to predict the prognosis of ccRCC and to study the immune profile of clear cell renal cell carcinoma (ccRCC). Methods: We downloaded the transcriptional profile and clinical information of ccRCC from The Cancer Genome Atlas (TCGA). Co-expression network analysis, Cox regression method, and least absolute shrinkage and selection operator (LASSO) method were used to identify cuproptosis-associated lncRNAs and to construct a risk prognostic model. In addition, the predictive performance of the model was validated and recognized by an integrated approach. We then also constructed a nomogram to predict the prognosis of ccRCC patients. Differences in biological function were investigated by GO, KEGG, and immunoassay. Immunotherapy response was measured using tumor mutational burden (TMB) and tumor immune dysfunction and rejection (TIDE) scores. Results: We constructed a panel of 10 cuproptosis-associated lncRNAs (HHLA3, H1-10-AS1, PICSAR, LINC02027, SNHG15, SNHG8, LINC00471, EIF1B-AS1, LINC02154, and MINCR) to construct a prognostic prediction model. The Kaplan-Meier and ROC curves showed that the feature had acceptable predictive validity in the TCGA training, test, and complete groups. The cuproptosis-associated lncRNA model had higher diagnostic efficiency compared to other clinical features. The analysis of Immune cell infiltration and ssGSEA further confirmed that predictive features were significantly associated with the immune status of ccRCC patients. Notably, the superimposed effect of patients in the high-risk group and high TMB resulted in shorter survival. In addition, the higher TIDE scores in the high-risk group suggested a poorer outcome for immune checkpoint blockade response in these patients. Conclusion: The ten cuproptosis-related risk profiles for lncRNA may help assess the prognosis and molecular profile of ccRCC patients and improve treatment options, which can be further applied in the clinic.

Predicting Prognosis and Distinguishing Cold and Hot Tumors in Bladder Urothelial Carcinoma Based on Necroptosis-Associated lncRNAs.

Background: In reference to previous studies, necroptosis played an important role in cancer development. Our team decided to explore the potential prognostic values of long non-coding RNAs (lncRNAs) associated with necroptosis in bladder urothelial carcinoma (BLCA) and their relationship with the tumor microenvironment (TME) and the immunotherapeutic response for accurate dose. Methods: To obtain the required data, bladder urothelial carcinoma transcriptome data were searched from Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov/). We used co-expression analysis, differential expression analysis, and univariate Cox regression to screen out prognostic lncRNAs associated with necroptosis in BLCA. Then the least absolute shrinkage and selection operator (LASSO) was conducted to construct the necroptosis-associated lncRNAs model. Based on this model, we also performed the Kaplan-Meier analysis and time-dependent receiver operating characteristics (ROC) to estimate the prognostic power of risk score. Multivariate and univariate Cox regression analysis were performed to build up a nomogram. Calibration curves, and time-dependent ROC were also conducted to evaluate nomogram. Principal component analysis (PCA) revealed a difference between high- and low-risk groups. In addition, we explored immune analysis, gene set enrichment analyses (GSEA), and evaluation of the half-maximal inhibitory concentration (IC50) in constructed model. Finally, the entire samples were divided into three clusters based on model of necroptosis-associated lncRNAs to further compare immunotherapy in cold and hot tumors. Results: A model was built up based on necroptosis-associated lncRNAs. The model revealed good consistence between calibration plots and prognostic prediction. The area of 1-, 3-, and 5-year OS under the ROC curve (AUC) were 0.707, 0.679, and 0.675. Risk groups could be helpful for systemic therapy due to the markedly diverse IC50 between risk groups. To our delight, clusters could effectively identify cold and hot tumors, which would be beneficial to accurate mediation. Clusters 2 and 3 were considered the hot tumor, which was more sensitive to immunotherapeutic drugs. Conclusions: The outcomes of our study suggested that necroptosis-associated lncRNAs could effectively predict patients with BLCA prognosis, which may be helpful for distinguishing the cold and hot tumors and improving individual treatment of BLCA.

Validation of a HILIC Method for the Analysis of Ergothioneine in Fermentation Broth.

A hydrophilic interaction liquid chromatography method has been established for the quantification of ergothioneine (EGT) in fermentation broth. Chromatographic separation was conducted on a Venusil hydrophilic interaction liquid chromatography (HILIC) column (250 × 4.6 mm, 5 µm) at an elution rate of 1.0 mL/min with an isocratic mobile phase consisting of acetonitrile/20 mmol/L ammonium acetate solution (85 : 15, v/v) adjusted to pH 6.0 with acetic acid. Analytes were detected at 254 nm using a UV-VIS detector. The injection volume was 10 µL, and the column temperature was 40°C. The limits of detection and limits of quantification were 63 and 21 µg/L, respectively. Excellent linearity [correlation coefficient (R(2)) = 0.9999] was achieved for EGT quantification in the range of 5-400 mg/L. The relative standard deviations of repeatability, intermediate precision and stability were 1.47, 1.03 and 1.66%, respectively, and EGT recoveries were within 99.2-100.8%. The chromatographic peak corresponding to EGT in the HILIC spectrum was confirmed using ESI-MS. In general, the method developed here is simple, reliable, accurate, and stable and may be useful for routine analyses in EGT biosynthesis research.