Identification of molecular subtypes and diagnostic model in clear cell renal cell carcinoma based on collagen-related genes may predict the response of immunotherapy.

Background: Collagen represents a prominent constituent of the tumor's extracellular matrix (ECM). Nonetheless, its correlation with the molecular subtype attributes of clear cell renal cell carcinoma (ccRCC) remains elusive. Our objective is to delineate collagen-associated molecular subtypes and further construct diagnostic model, offering insights conducive to the precise selection of ccRCC patients for immunotherapeutic interventions. Methods: We performed unsupervised non-negative matrix factorization (NMF) analysis on TCGA-KIRC samples, utilizing a set of 33 collagen-related differentially expressed genes (33CRDs) for clustering. Our analysis encompassed evaluations of subtype-associated differences in pathways, immune profiles, and somatic mutations. Through weighted gene co-expression network analysis (WGCNA) and four machine learning algorithms, two core genes were found and a diagnostic model was constructed. This was subsequently validated in a clinical immunotherapy cohort. Single cell sequencing analysis and experiments demonstrated the role of core genes in ccRCC. Finally, we also analyzed the roles of MMP9 and SCGN in pan-cancer. Results: We described two novel collagen related molecular subtypes in ccRCC, designated subtype 1 and subtype 2. Compared with subtype 1, subtype 2 showed more infiltration of immune components, but had a higher TIDE (tumor immunedysfunctionandexclusion) score and increased levels of immune checkpoint molecules. Furthermore, reduced prognosis for subtype 2 was a consistent finding in both high and low mutation load subgroups. MMP9 and SCGN were identified as key genes for distinguishing subtype 1 and subtype 2. The diagnostic model based on them could better distinguish the subtype of patients, and the differentiated patients had different progression free survival (PFS) in the clinical immunotherapy cohort. MMP9 was predominantly expressed in macrophages and has been extensively documented in the literature. Meanwhile, SCGN, which was overexpressed in tumor cells, underwent experimental validation, emphasizing its role in ccRCC. In various cancers, MMP9 and SCGN were associated with immune-related molecules and immune cells. Conclusion: Our study identifies two collagen-related molecular subtypes of ccRCC and constructs a diagnostic model to help select appropriate patients for immunotherapy.

Patients with high nuclear grade pT1-ccRCC are more suitable for radical nephrectomy than partial nephrectomy: a multicenter retrospective study using propensity score.

BACKGROUND: Partial nephrectomy (PN) is usually recommended for T1 stage clear cell renal cell carcinoma (ccRCC) regardless of the nuclear grades. However, the question remains unresolved as to whether PN is non-inferior to RN in patients with T1-ccRCC at higher risk of recurrence. In fact, we found that patients with high nuclear grades treated with PN had poorer prognosis compared with those treated with radical nephrectomy (RN). Therefore, this study was designed to evaluate the associations of PN and RN in the four nuclear grade subsets with oncologic outcomes. METHODS: A retrospective study was conducted in three Chinese urological centers that included 1,714 patients who underwent PN or RN for sporadic, unilateral, pT1, N0, and M0 ccRCC without positive surgical margins and neoadjuvant therapy between 2010 and 2019. Associations of nephrectomy type with local ipsilateral recurrence, distant metastases, and all-cause mortality (ACM) were evaluated using the Kaplan-Meier method and multivariable Cox proportional hazards regression models after overlap weighting (OW). RESULTS: A total of 1675 patients entered the OW cohort. After OW, in comparison to PN, RN associated with a reduced risk of local ipsilateral recurrence in the G2 subset (HR = 0.148, 95% CI 0.046-0.474; p < 0.05), G3 subset (HR = 0.097, 95% CI 0.021-0.455; p < 0.05), and G4 subset (HR = 0.091, 95% CI 0.011-0.736; p < 0.05), and resulting in increased five-year local recurrence-free survival rates of 7.0%, 17.9%, and 36.2%, respectively. An association between RN and a reduced risk of distant metastases in the G4 subset (HR = 0.071, 95% CI 0.016-0.325; p < 0.05), with the five-year distant metastases-free survival rate increasing by 33.1% was also observed. No significant difference in ACM between PN and RN was identified. CONCLUSIONS: Our findings substantiate that opting for RN, as opposed to PN, is more advantageous for local recurrence-free survival and distant metastases-free survival in patients with high nuclear grade (especially G4) pT1-ccRCC. We recommend placing a heightened emphasis on enhancing preoperative nuclear grade assessment, as it can significantly influence the choice of surgical plan. TRIAL REGISTRATION: This study was registered at Chinese Clinical Trial Registry (ID: ChiCTR2200063333).

circWSB1 promotes tumor progression in ccRCC via circWSB1/miR-182-5p/WSB1 axis.

Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent urological carcinomas with a low overall 5-year survival rate, and its prognosis remains dismal. circular RNAs (circRNAs) has been discovered to be important regulators in ccRCC. However, the specific regulatory mechanisms of circRNAs and their impact on phenotypes require further in-depth research. circRNA microarray sequencing analysis was used in this study to explore the expression pattern of circRNAs in ccRCC. circWSB1 was discovered, and we evaluated its derivation, potential diagnostic efficacy, and prognostic significance in ccRCC tissues. We discovered that circWSB1 is highly expressed in ccRCC. We identified that circWSB1 interacts with miR-182-5p and upregulates the expression of its host gene, WSB1. Through models in vivo and in vitro models, we found that circWSB1 increases WSB1 expression via the circWSB1/miR-182-5p/WSB1 axis, which promotes ccRCC cell proliferation and migration. The high expression of circWSB1 and WSB1 is correlated with poorer clinical prognosis and pathological grading. circWSB1 diminishes the inhibitory impact of miR-182-5p on WSB1 and increases WSB1 expression, thereafter promoting ccRCC development. Our findings provide a promising predictive biomarker and therapeutic target for ccRCC.

Cuproptosis-related long noncoding RNAs predicts overall survival and reveal immune microenvironment of bladder cancer.

Background: Recently, a newly programmed cell death has been discovered, namely cuproptosis. It is considered a novel copper-dependent cell death model. Long non-coding RNA (lncRNA) influence the prognosis of bladder cancer. In this study, we established a scoring system based on 7 cuproptosis-related lncRNA to predict the prognosis and immune landscape of bladder cancer (BCa). Method: Gene expression and clinical data of 431 tissues were downloaded from The Cancer Genome Atlas (TCGA), including 19 normal samples and 419 cancer samples. All samples were randomly categorized into train and test cohorts. Cuproptosis-related lncRNA were distinguished. Then we conduct univariate COX and multivariate COX regression, paralleled with LASSO regression to cultivate a cuproptosis-related lncRNA risk model. Kaplan-Meier curves, scatter diagram, C-index, ROC curves, nomogram, PCA analysis and univariate and multivariate Cox regression were used to test the accuracy of risk model and to predict patient survival. Additional, gene mutation status between high- and low-risk groups was calculated.GO and KEGG were used to access the DEGs (different expression genes)-related pathway.The ssGSEA and ESTIMATE algorithms were used to assess the immune function in different tumor samples. Besides, patient's response to immunotherapy and drug susceptibility were also been estimated. Results: 7 cuproptosis-related lncRNA (LINC01184, LINC00513, LINC02443, SMARCA5-AS1, BDNF-AS, SOD2-OT1, HYI-AS1) were selected to construct the risk model in the train cohort. This model can well predict the overall survival (OS) in test group and entire cohort with different stage. Despite no significant different is observed in gene mutation between high- and low-risk group, different immune infiltration, different survival and sensitivity to drugs are discovered. Conclusion: We established a novel cuproptosis-related lncRNA risk model which can predict the outcome and immunotherapy response with satisfactory predictive effects. This risk model can provide a new insight into prognostic evaluation and may have potential to guide comprehensive treatment in bladder cancer.

A five necroptosis-related lncRNA signature predicts the prognosis of bladder cancer and identifies hot or cold tumors.

Bladder cancer (BC) is a leading cause of male cancer-related deaths globally. Immunotherapy is showing promise as a treatment option for BC. Numerous studies suggested that necroptosis and long noncoding RNAs (lncRNAs) were critical players in the development of cancers and interacting with cancer immunity. However, the prognostic value of necroptosis-related lncRNAs and their impact on immunotherapeutic response in patients with BC have yet to be well examined. Thus, this study aims to find new biomarkers for predicting prognosis and determining immune subtypes of BC to select appropriate patients from a heterogeneous population. The clinicopathology and transcriptome information from The Cancer Genome Atlas (TCGA) was downloaded, and coexpression analysis was performed to identify necroptosis-related lncRNAs. Then LASSO regression was employed to construct a prediction signature. The signature performance was evaluated by Kaplan-Meier (K-M) method, Time-dependent receiver operating characteristics (ROC). The functional enrichment, immune infiltration, immune checkpoint activation, and the half-maximal inhibitory concentration (IC50) of common drugs in risk groups were compared. The consensus clustering analysis based on lncRNAs associated with necroptosis was made to get 2 clusters to identify hot and cold tumors further. Lastly, the immune response between cold and hot tumors was discussed. In this study, a model containing 5 necroptosis-related lncRNAs was constructed. The risk score distribution of these lncRNAs was compared between low- and high-risk groups in the training, testing, and entire sets. K-M analysis showed that the low-risk patients had significantly better prognosis. The area under the ROC curve (AUC) for the 1-, 3-, and 5-year ROC curves in the entire sets were 0.690, 0.709, and 0.722, respectively. High-risk patients were enriched in lncRNAs related to tumor immunity and had better immune cell infiltration and immune checkpoint activation. Hot tumors and cold tumors were effectively distinguished by clusters 1 and cluster 2, respectively. We developed a necroptosis-related signature based on 5 prognostic lncRNAs, expected to become a new tool for evaluating the prognosis of patients with BC and classifying hot or cold tumors, thus facilitating the development of precision therapy for BC.

18F-prostate specific membrane antigen positron emission tomography/computerized tomography for lymph node staging in medium/high risk prostate cancer: A systematic review and meta-analysis.

BACKGROUND: Lymph node staging of prostate cancer (PCa) is important for planning and monitoring of treatment. 18F-prostate specific membrane antigen positron emission tomography/computerized tomography (18F-PSMA PET/CT) has several advantages over 68Ga-PSMA PET/CT, but its diagnostic value requires further investigation. This meta-analysis focused on establishing the diagnostic utility of 18F-PSMA PET/CT for lymph node staging in medium/high-risk PCa. METHODS: We searched the EMBASE, PubMed, Cochrane library, and Web of Science databases from inception to October 1, 2022. Prostate cancer, 18F, lymph node, PSMA, and PET/CT were used as search terms and the language was limited to English. We additionally performed a manual search using the reference lists of key articles. Patients and study characteristics were extracted and the QUADAS-2 tool was employed to evaluate the quality of included studies. Sensitivity, specificity, the positive and negative likelihood ratio (PLR and NLR), diagnostic odds ratio (DOR), area under the curve (AUC), and 95% confidence interval (CI) were used to evaluate the diagnostic value of 18F-PSMA PET/CT. Stata 17 software was employed for calculation and statistical analyses. RESULTS: A total of eight diagnostic tests including 734 individual samples and 6346 lymph nodes were included in this meta-analysis. At the patient level, the results of each consolidated summary were as follows: sensitivity of 0.57 (95% CI 0.39-0.73), specificity of 0.95 (95% CI 0.92-0.97), PLR of 11.2 (95% CI 6.6-19.0), NLR of 0.46 (95% CI 0.31-0.68), DOR of 25 (95% CI 11-54), and AUC of 0.94 (95% CI 0.92-0.96). At the lesion level, the results of each consolidated summary were as follows: sensitivity of 0.40 (95% CI 0.21-0.62), specificity of 0.99 (95% CI 0.95-1.00), PLR of 40.0 (95% CI 9.1-176.3), NLR of 0.61 (95% CI 0.42-0.87), DOR of 66 (95% CI 14-311), and AUC of 0.86 (95% CI 0.83-0.89). CONCLUSIONS: 18F-PSMA PET/CT showed moderate sensitivity but high specificity in lymph node staging of medium/high-risk PCa. The diagnostic efficacy was almost equivalent to that reported for 68Ga-PSMA PET/CT. REGISTRATION: International Prospective Register of Systematic Reviews (PROSPERO), No. CRD42023391101.

FOXM1-regulated ZIC2 promotes the malignant phenotype of renal clear cell carcinoma by activating UBE2C/mTOR signaling pathway.

Background: As a transcription factor, Zic family member 2 (ZIC2) has been involved in more and more studies of tumorigenesis, which has been proved by our research team to be an effective prognostic marker for Pan-cancer. However, the prognosis, tumor promoting effect and regulatory mechanism of ZIC2 in clear cell renal cell carcinoma (ccRCC) are still unknown. Methods: The potential clinical significance of ZIC2 was evaluated by bioinformatics analysis using data from TCGA, GEO, and ArrayExpress data sets. WB and IHC were used to detect ZIC2 expression in tumors and adjacent tissues. CCK-8, EdU, colony formation, cell cycle, wound healing, transwell, subcutaneous xenograft, and lung metastasis models were used to detect the biological function of ZIC2. The regulatory mechanism of ZIC2 was confirmed by data of RNA-seq, ATAC-seq, MS-PCR, Chip-PCR, and luciferase reporter experiments. Results: ZIC2 was markedly upregulated and correlated with poor clinicopathological features in ccRCC. Knockdown of ZIC2 resulted in reduced cell proliferation, invasion, migration, induction of G2/M phase arrest, and reduced tumor formation and lung metastasis in nude mice. The opposite was observed after overexpression. Mechanistically, the high expression of ZIC2 is regulated by hypomethylation and high H3K4Me3 in the promoter region, as well as positive transcriptional regulation by FOXM1. And then, ZIC2 transcriptase-positively regulates UBE2C and activates AKT/mTOR signaling pathway to promote tumor malignant progression. Conclusion: This study reveals that FOXM1-ZIC2-UBE2C-mTOR signaling axis promotes the progression of ccRCC, which can be used as a prognostic indicator and potential therapeutic target.

Survival After Cryotherapy Versus Radiotherapy in Low and Intermediate Risk Localized Prostate Cancer.

BACKGROUND: Focal therapy, including cryotherapy, reduces overtreatment in low- and intermediate-risk prostate cancer (PCa) patients with multiple comorbidities, which seems to increase in popularity compared with whole gland treatment. However, there is currently no consensus regarding the medium-term outcomes of cryosurgery as a prospective alternative to radiotherapy (RT) for such patients. Our study aims to find the available evidence that directly compares the medium-term overall survival (OS) and cancer-specific mortality (CSM) outcomes between cryotherapy and RT in patients with low- and intermediated-risk PCa. MATERIALS AND METHOD: Using the Surveillance, Epidemiology, and End Results (SEER) database, we identified 47,787 patients with low- and intermediate-risk PCa diagnosed between 2004 and 2015, of which 46,853 (98%) received treatment with RT, while only 934 (2.0%) received treatment with cryotherapy. Kaplan-Meier methods were used to estimateOS and cancer-specific survival (CSS) between the 2 groups. We performed multivariable Cox regression analysis to assess overall mortality (OM), while the cumulative incidence function (CIF) was used to illustrate cancer-specific mortality (CSM) and noncancer-specific mortality (non-CSM) for all patients. Additionally, competing risks regression (Fine-Gray) was implemented to evaluate any differences. After propensity score matching (PSM), all the aforementioned analyses were repeated. After the inverse probability of treatment weighting (IPTW), we repeated Kaplan-Meier methods on OS and CSS, and performed multivariable Cox regression analysis to assess OM in cryotherapy versus RT. Sensitivity analyses were conducted by excluding patients who died of cardiovascular disease. RESULTS: After applying 1:4 PSM to the cryotherapy group with the RT group, the resulting RT cohort consisted of 3,736 patients who were matched with 934 patients in the cryotherapy cohort. The 5-year OS and cumulative CSM rates for PS-matched groups (N = 4670) receiving cryotherapy (N = 934) or RT (N = 3736) were 89% versus 91.8%, 0.65% versus 0.57, respectively. Multivariable Cox regression analysis demonstrated that cryotherapy was associated with a poorer OS outcome compared to RT (hazard ratio [HR] 1.29, 95% confidence interval [CI]: 1.07-1.55, p < .01). Multivariate competing risk regression analysis revealed that both treatments were not associated with CSS, with HR = 1.07 (95% CI: 0.55-2.08, p = .85). IPTW-adjusted analyses showed that the 5-years OS rates were 89.6% versus 91.8% for cryotherapy versus RT, respectively. Multivariate regression analysis for OS demonstrated that cryotherapy was more likely to have inferior OS in comparison to RT (HR = 1.30; 95%CI: 1.09-1.54; p < .01). The outcome of sensitivity analyses indicates that there was no significant difference in OS and CSS between the 2 groups. CONCLUSION: For low- and intermediate-risk PCa patients treated by cryotherapy or RT, we could not demonstrate a survival difference. Cryotherapy may be a feasible option as a viable alternative to traditional radiation therapy.

Is it necessary for all patients with suspicious lesions undergo systematic biopsy in the era of MRI-TRUS fusion targeted biopsy?

ABSTRACT Purpose Targeted biopsy (TB) combined with systematic biopsy (SB) is an optimized mode of prostate biopsy but can often lead to oversampling and overdiagnosis accompanied by potential biopsy-related complications and patient discomfort. Here, we attempted to reasonably stratify the patient population based on multi-parameter indicators with the aim of avoiding unnecessary SB. Methods In total, 340 biopsy-naïve men with suspected lesions, prostate-specific antigen (PSA) < 20 ng/mL and prostate imaging-reporting and data system (PI-RADS) ≥ 3 enrolled for study underwent both TB and SB. The primary outcome was to determine independent predictors for a valid diagnosis, assuming that only TB was performed and SB omitted (defined as mono-TB), taking TB + SB as the reference standard. The secondary outcomes were exploration of the predictive factors of mono-TB and TB + SB in detection of prostate cancer (PCa) and clinically significant PCa (csPCa). Results The mean PSA density (PSAD) of patient group was 0.27 ng/mL/mL. Multiparametric MRI PI-RADS scores were 3-5 in 146 (42.94%), 105 (30.88%), and 89 (26.18%) cases, respectively. PCa and csPCa were detected in 178/340 (52.35%) and 162/340 (47.65%) patients, respectively. Overall, 116/178 (65.17%) patients diagnosed with PCa displayed pathological consistencies between mono-TB and TB + SB modes. PSAD and PI-RADS were independent predictors of valid diagnosis using mono-TB. Conclusions PSAD combined with PI-RADS showed utility in guiding optimization of the prostate biopsy mode. Higher PSAD and PI-RADS values were associated with greater confidence in implementing mono-TB and safely omitting SB, thus effectively balancing the benefits and risks.

Is it necessary for all patients with suspicious lesions undergo systematic biopsy in the era of MRI-TRUS fusion targeted biopsy?

PURPOSE: Targeted biopsy (TB) combined with systematic biopsy (SB) is an optimized mode of prostate biopsy but can often lead to oversampling and overdiagnosis accompanied by potential biopsy-related complications and patient discomfort. Here, we attempted to reasonably stratify the patient population based on multi-parameter indicators with the aim of avoiding unnecessary SB. METHODS: In total, 340 biopsy-naïve men with suspected lesions, prostate-specific antigen (PSA) < 20 ng/mL and prostate imaging-reporting and data system (PI-RADS) ≥ 3 enrolled for study underwent both TB and SB. The primary outcome was to determine independent predictors for a valid diagnosis, assuming that only TB was performed and SB omitted (defined as mono-TB), taking TB + SB as the reference standard. The secondary outcomes were exploration of the predictive factors of mono-TB and TB + SB in detection of prostate cancer (PCa) and clinically significant PCa (csPCa). RESULTS: The mean PSA density (PSAD) of patient group was 0.27 ng/mL/mL. Multiparametric MRI PI-RADS scores were 3-5 in 146 (42.94%), 105 (30.88%), and 89 (26.18%) cases, respectively. PCa and csPCa were detected in 178/340 (52.35%) and 162/340 (47.65%) patients, respectively. Overall, 116/178 (65.17%) patients diagnosed with PCa displayed pathological consistencies between mono-TB and TB + SB modes. PSAD and PI-RADS were independent predictors of valid diagnosis using mono-TB. CONCLUSIONS: PSAD combined with PI-RADS showed utility in guiding optimization of the prostate biopsy mode. Higher PSAD and PI-RADS values were associated with greater confidence in implementing mono-TB and safely omitting SB, thus effectively balancing the benefits and risks.

Construction and validation of N6-methyladenosine long non-coding RNAs signature of prognostic value for early biochemical recurrence of prostate cancer.

PURPOSE: Early biochemical recurrence (eBCR) indicated a high risk for potential recurrence and metastasis in prostate cancer. The N6-methyladenosine (m6A) methylation modification played an important role in prostate cancer progression. This study aimed to develop a m6A lncRNA signature to accurately predict eBCR in prostate cancer. METHODS: Pearson correlation analysis was first conducted to explore m6A lncRNAs and univariate Cox regression analysis was further performed to identify m6A lncRNAs of prognostic roles for predicting eBCR in prostate cancer. The m6A lncRNA signature was constructed by least absolute shrinkage and selection operator analysis (LASSO) in training cohort and further validated in test cohort. Furthermore, half maximal inhibitory concentration (IC50) values were utilized to explore potential effective drugs for high-risk group in this study. RESULTS: Five hundred and thirty-eighth m6A lncRNAs were searched out through Pearson correlation analysis and 25 out of 538 m6A lncRNAs were identified to pose prediction roles for eBCR in prostate cancers. An m6A lncRNA signature including 5 lncRNAs was successfully built in training cohort. The high-risk group derived from m6A lncRNA signature could efficiently predict eBCR occurrence in both training (p < 0.001) and test cohort (p = 0.002). ROC analysis also confirmed that lncRNA signature in this study posed more accurate prediction roles for eBCR occurrence when compared with PSA, TNM stages and Gleason scores. Drug sensitivity analysis further discovered that various drugs could be potentially utilized to treat high-risk samples in this study. CONCLUSIONS: The m6A lncRNA signature in this study could be utilized to efficiently predict eBCR occurrence, various clinical characteristic and immune microenvironment for prostate cancer.

Biochemical recurrence related metabolic novel signature associates with immunity and ADT treatment responses in prostate cancer.

BACKGROUND: Prostate cancer (PCa) is a unique cancer from a metabolic perspective. Androgen receptor assumes a vital part in normal and malignant prostate cells regarding almost all aspects of cell metabolism, such as glucose, fat, amino acids, nucleotides, and so on. METHODS: We used The Cancer Genome Atlas database as training set, Memorial Sloan-Kettering Cancer Center cohort as validation set, and Gene Expression Omnibus database (GSE70769) as test set to identify the optimal prognostic signature. We evaluated the signature in terms of biochemical progression-free survival (bPFS), ROC curve, clinicopathological features, independent prognostic indicators, tumor microenvironment, and infiltrating immune cells. Nomogram was built dependent on the results of cox regression analyses. GSEA algorithm was used to evaluate differences in metabolism. The signature's prediction of androgen deprivation therapy (ADT) response was validated based on two groups of basic cytological experiments treat with ADT (GSE143408 and GSE120343) and the transcriptional information of pre-ADT/post-ADT of six local PCa patients. RESULTS: We finally input four screened genes into the stepwise regression model to construct metabolism-related signature. The signature shows good prediction performance in training set, verification set, and test set. A nomogram based on the PSA, Gleason score, T staging, and the signature risk score could predict 1-, 3-, and 5-year bPFS with the high area under curve values. Based on gene-set enrichment analysis, the characteristics of four genes signature could influence some important metabolic biological processes of PCa and were serendipitously found to be significantly related to androgen response. Subsequently, two cytological experimental data sets and our local patient sequencing data set verified that the signature may be helpful to evaluate the therapeutic response of PCa to ADT. CONCLUSIONS: Our systematic study definite a metabolism-related gene signature to foresee prognosis of PCa patients which might add to individual prevention and treatment.

N6-methyladenosine long non-coding RNAs reveal novel tool to implicate overall survival and immune microenvironment in renal clear cell carcinoma.

PURPOSE: This study aimed to investigate whether N6-methyladenosine (m6A)-related long non-coding RNAs (m6ARelncRNAs) could provide novel tools to predict overall survival of renal clear cell carcinoma. METHODS: The transcriptomic data and clinical information of patients with renal clear cell carcinoma from The Cancer Genome Atlas (TCGA) were analysed. Distinct m6A modification patterns were systemically analysed via consensus clustering analysis. An m6ARelncRNA signature was constructed in the training cohort using the least absolute shrinkage and selection operator (LASSO) analysis and validated in the test cohort. Potential predictive accuracy of the signature was further assessed via Kaplan-Meier survival, univariate and multivariate Cox regression and subgroup analyses. The Tumour Immune Dysfunction and Exclusion (TIDE) algorithm was used to investigate the role of m6ARelncRNAs in guiding immunotherapy for patients with renal carcinoma. RESULTS: An m6ARelncRNA signature based on only six lncRNAs was successfully constructed. The high-risk group derived from this signature had significantly poorer overall survival in both training and test cohorts (p < 0.001). Independent prognostic analysis further revealed that m6ARelncRNA risk (p < 0.01) was an independent risk factor for survival outcomes of renal carcinoma. TIDE algorithm revealed that immunotherapy response was poorer in the high-risk group than in the low-risk group. Drug sensitivity analysis based on IC50 revealed that high-risk patients were potentially sensitive to various anti-tumour drugs, including bortezomib, cisplatin, docetaxel, etoposide and sunitinib. CONCLUSION: m6ARelncRNAs provide novel tools that can be used to predict overall survival and examine the immune microenvironment of renal clear cell carcinoma.

A Novel Gene Signature Associated With "E2F Target" Pathway for Predicting the Prognosis of Prostate Cancer.

Background: The effect of the adenoviral early region 2 binding factors (E2Fs) target pathway on prostate cancer is not clear. It is necessary to establish an E2F target-related gene signature to predict prognosis and facilitate clinical decision-making. Methods: An E2F target-related gene signature was established by univariate and LASSO Cox regression analyses, and its predictive ability was verified in multiple cohorts. Moreover, the enrichment pathway, immune microenvironment, and drug sensitivity of the activated E2F target pathway were also explored. Results: The E2F target-related gene signature consisted of MXD3, PLK1, EPHA10, and KIF4A. The patients with high-risk scores showed poor prognosis, therapeutic resistance, and immunosuppression, along with abnormal growth characteristics of cells. Tinib drugs showed high sensitivity to the expression of MXD3 and EPHA10 genes. Conclusion: Our research established an E2F target-related signature for predicting the prognosis of prostate cancer. This study provides insights into formulating individualized detection and treatment as well as provides a theoretical basis for future research.

Ferroptosis Mediation Patterns Reveal Novel Tool to Implicate Immunotherapy and Multi-Omics Characteristics in Bladder Cancer.

Background: The regulatory role of ferroptosis in malignant tumours has been recently demonstrated. However, the potential roles of ferroptosis mediation patterns in bladder cancer remain elusive. Materials and Methods: The ferroptosis mediation patterns of 889 bladder cancer samples were comprehensively evaluated based on ferroptosis-related genes. The underlying correlations between these mediation patterns and multi-omic characteristics of bladder cancer were systematically analysed. The ferroptosis mediation patterns of individual samples were quantified by ferropscore using the principal component analysis algorithm. The typical ferroptosis-related genes with prognostic roles were further randomly validated using immunohistochemical staining, real-time polymerase chain reaction and western blotting. Results: Three different ferroptosis mediation patterns were identified. The abundance of infiltration of 23 immune cells was different among the three mediation patterns. The quantification of ferroptosis mediation patterns in individual samples served as a promising tool for predicting patient survival outcomes; immune cell infiltration abundance; tumour mutation burden; oncogenic mutation status and tumour grade, stage and molecular subtypes. Low ferropscore combined with high tumour mutation burden was associated with the best survival prognosis. Expressions of PD-L1 (p < 0.001), PD-1 (p = 0.002) and CTLA-4 (p = 0.003) were all significantly upregulated in the high ferropscore group. Low ferropscores also predicted good immunotherapy response for anti-CTLA4 strategy. The mRNA and protein levels of FADS2, a typical ferroptosis-related gene used in the study, were higher in bladder cancer cell lines than in controlled SV-HUC-1 cells. In addition, immunohistochemical staining revealed significantly higher expression levels of FADS2 in human bladder cancer tumour tissues than in normal tissues. Conclusion: This study identified three distinct ferroptosis mediation patterns in bladder cancer. Quantification of ferroptosis mediation patterns in individual samples may help to improve the understanding of multiomic characteristics and guide future immunotherapy responses to bladder cancer.

Predictive role of ferroptosis-related long non-coding RNAs in bladder cancer and their association with immune microenvironment and immunotherapy response.

BACKGROUND: We have previously reported that ferroptosis has an important role in bladder cancer development. In this study, we aimed to further explore the possible predictive ability of ferroptosis-related long non-coding RNAs (lncRNAs) in bladder cancer and their relation with immune microenvironment and immunotherapy response. MATERIALS AND METHODS: The ferroptosis-related lncRNAs were identified by Pearson's correlation analysis. The predictive lncRNA signature was developed by univariate and multivariate regression analyses. Only the main effects of independent variables in multivariate analysis were included in this signature. The TCGA dataset was defined as the training cohort and GEO was the validation cohort in this study. All samples were grouped into a high- or low-risk group depending on risk signature. The prognostic role of lncRNA signature was explored through survival analysis and receiver operating characteristic curve (ROC) analysis in both TCGA and GEO cohorts. Additionally, the independent prognostic ability of the lncRNA signature was confirmed by multivariate independent analysis. Furthermore, the relationship between lncRNAs and immune microenvironment as well as immunotherapy response in bladder cancers was studied. RESULTS: The Kaplan-Meier curves identified significantly poorer overall survival outcomes for high-risk groups in both TCGA (p < 0.001) and GEO (p < 0.001) cohorts. The area under the curve (AUC) during ROC analysis of 1, 3, and 5 years was 0.781 ± 0.046, 0.784 ± 0.027, and 0.817 ± 0.025, respectively, in the TCGA cohort and 0.665 ± 0.177, 0.719 ± 0.068, and 0.791 ± 0.055, respectively, in the GEO cohort. The multivariate independent analysis in TCGA cohort identified age (p = 0.003), stage (p < 0.001), and signature risk score (p < 0.001) as independent risk factors for overall survival. Furthermore, this study demonstrated a significant difference in infiltration levels of various immune cells between high- and low-risk groups. The high risk group tended to have a lower expression of proteins including PD1 (p < 0.01), PD-L1 (p < 0.01), CTLA-4 (p < 0.05), etc. corresponding to various immune checkpoints. Additionally, the immunotherapy trial confirmed that the high-risk group tended to have a poorer treatment response than the low-risk group (p < 0.001). CONCLUSIONS: The ferroptosis-related lncRNAs exhibited a good predictive capacity for overall survival in bladder cancer. Additionally, they could be utilized to reveal tumour-immune microenvironment and immunotherapy responses.

Identifying a Ferroptosis-Related Gene Signature for Predicting Biochemical Recurrence of Prostate Cancer.

Ferroptosis induced by lipid peroxidation is closely related to cancer biology. Prostate cancer (PCa) is not only a malignant tumor but also a lipid metabolic disease. Previous studies have identified ferroptosis as an important pathophysiological pathway in PCa development and treatment, but its role in the prognosis of PCa is less well known. In this study, we constructed a nine-ferroptosis-related gene risk model that demonstrated strong prognostic and therapeutic predictive power. The higher risk score calculated by the model was significantly associated with a higher ferroptosis potential index, higher Ki67 expression, higher immune infiltration, higher probability of biochemical recurrence, worse clinicopathological characteristics, and worse response to chemotherapy and antiandrogen therapy in PCa. The mechanisms identified by the gene set enrichment analysis suggested that this signature can accurately distinguish high- and low-risk populations, which is possibly closely related to variations in steroid hormone secretion, regulation of endocrine processes, positive regulation of humoral immune response, and androgen response. Results of this study were confirmed in two independent PCa cohorts, namely, The Cancer Genome Atlas cohort and the MSK-IMPACT Clinical Sequencing Cohort, which contributed to the body of scientific evidence for the prediction of biochemical recurrence in patients with PCa. In addition, as the main components of this signature, the effects of the AIFM2 and NFS1 genes on ferroptosis were evaluated and verified by in vivo and in vitro experiments, respectively. The above findings provided new insights and presented potential clinical applications of ferroptosis in PCa.

Identification of a Hypoxia-Related Gene Signature for Predicting Systemic Metastasis in Prostate Cancer.

Background: Systemic metastasis is the main cause of death in patients with prostate cancer. It is necessary to establish a more accurate model to distinguish and predict patients with a high risk of metastasis to optimize individualized treatment. Methods: In this study, it was determined that hypoxia could affect the metastasis-free survival of patients with prostate cancer, and a hypoxia-related gene signature composed of seven genes for predicting metastasis was established and verified in different cohorts. The study further evaluated the effects of ALDOB expression on the proliferation and invasion of the LNCaP and DU145 cell lines under hypoxia and finally constructed a nomogram containing specific clinical characteristics of prostate cancer combined with the hypoxia gene signature to quantify the metastasis risk of individual patients. Results: The hypoxia-related gene signature was identified as an independent risk factor for metastasis-free survival in patients with prostate cancer. The expression of ALDOB increased under hypoxia and promoted the proliferation and invasion of LNCaP and DU145 cells. In addition, patients with a high risk score showed therapeutic resistance and immunosuppression. Compared with other parameters, the nomogram had the strongest predictive power and net clinical benefit. Conclusion: The study established a hypoxia-related gene signature and a nomogram to distinguish and predict patients with a high risk of prostate cancer metastasis, which may help to optimize individualized treatment and explore possible therapeutic targets.

Construction and External Validation of a Ferroptosis-Related Gene Signature of Predictive Value for the Overall Survival in Bladder Cancer.

Purpose: To identify whether ferroptosis-related genes play predictive roles in bladder cancer patients and to develop a ferroptosis-related gene signature to predict overall survival outcomes. Materials and Methods: We downloaded the mRNA expression files and clinical data of 256 bladder samples (188 bladder tumour and 68 nontumour samples) from the GEO database and 430 bladder samples (411 bladder tumour and 19 nontumour samples) from the TCGA database. A multigene signature based on prognostic ferroptosis-related genes was constructed by least absolute shrinkage and selection operator Cox regression analysis in the GEO cohort. The TCGA cohort was used to validate the ferroptosis-related gene signature. Next, functional enrichment analysis, including both Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses, was performed to elucidate the mechanism underlying the signature. The ssGSEA scores of 16 immune cells and 13 immune-related pathway activities between the high-risk and low-risk groups were also analysed in our study. Results: Thirty-three (67.3%) ferroptosis-related genes were differentially expressed between bladder tumour samples and nontumour samples in the GEO cohort. The intersection of prognostic ferroptosis-related genes and differentially expressed genes identified four prognostic targets, including ALOX5, FANCD2, HMGCR and FADS2. The least absolute shrinkage and selection operator Cox regression successfully built a 4-gene signature: risk score value = esum (each gene's normalized expression * each gene's coefficient). Univariate and multivariate Cox regression analyses were performed in both the GEO and TCGA cohorts to test the independent prognostic value of the 4-gene risk signature. Multivariate Cox regression analysis in the GEO cohort identified age (p < 0.001), grade (p = 0.129) and risk score (p = 0.016) as independent prognostic predictors for overall survival. Multivariate Cox regression analysis in the TCGA cohort also identified age (p = 0.002), stage (p < 0.001) and risk score (p = 0.006) as independent prognostic predictors for overall survival. The type II IFN response was determined to be significantly weakened in the high-risk group in both the GEO and TCGA cohorts. Conclusion: We successfully built a ferroptosis-related gene signature of significant predictive value for bladder cancer. These results suggest a novel research direction for targeted therapy of bladder cancer in the future.

Identification of a Novel Glycolysis-Related Gene Signature Correlates With the Prognosis and Therapeutic Responses in Patients With Clear Cell Renal Cell Carcinoma.

BACKGROUND: Accumulating evidences indicate significant alterations in the aerobic glycolysis in clear cell renal cell carcinoma (ccRCC). We aim to develop and validate a glycolysis-related genes signature for predicting the clinical outcomes of patients with ccRCC. METHODS: mRNA expression profiling of ccRCC was obtained from The Cancer Genome Atlas database. Univariate Cox regression analysis and lasso Cox regression model were performed to identify and construct the prognostic gene signature. The protein expression levels of the core genes were obtained from the Human Protein Atlas database. We used four external independent data sets to verify the predictive power of the model for prognosis, tyrosine kinase inhibitor (TKI) therapy, and immunotherapy responses, respectively. Finally, we explored the potential mechanism of this signature through gene set enrichment analysis (GSEA). RESULTS: Through the GSEA, glycolysis-related gene sets were significantly different between ccRCC tissues and normal tissues. Next, we identified and constructed a seven-mRNA signature (GALM, TGFA, RBCK1, CD44, HK3, KIF20A, and IDUA), which was significantly correlated with worse survival outcome and was an independent prognostic indicator for ccRCC patients. Furthermore, the expression levels of hub genes were validated based on the Human Protein Atlas databases. More importantly, the model can predict patients' response to TKI therapy and immunotherapy. These findings were successfully validated in the external independent ccRCC cohorts. The mechanism exploration showed that the model may influence the prognosis by influencing tumor proliferation, base mismatch repair system and immune status of patients. CONCLUSIONS: Our study has built up a robust glycolysis-based molecular signature that predicts the prognosis and TKI therapy and immunotherapy responses of patients with ccRCC with high accuracy, which might provide important guidance for clinical assessment. Also, clinical investigations in large ccRCC cohorts are greatly needed to validate our findings.