5mC regulator-mediated molecular subtypes depict the hallmarks of the tumor microenvironment and guide precision medicine in bladder cancer.

BACKGROUND: Depicting the heterogeneity and functional characteristics of the tumor microenvironment (TME) is necessary to achieve precision medicine for bladder cancer (BLCA). Although classical molecular subtypes effectively reflect TME heterogeneity and characteristics, their clinical application is limited by several issues. METHODS: In this study, we integrated the Xiangya cohort and multiple external BLCA cohorts to develop a novel 5-methylcytosine (5mC) regulator-mediated molecular subtype system and a corresponding quantitative indicator, the 5mC score. Unsupervised clustering was performed to identify novel 5mC regulator-mediated molecular subtypes. The principal component analysis was applied to calculate the 5mC score. Then, we correlated the 5mC clusters (5mC score) with classical molecular subtypes, immunophenotypes, clinical outcomes, and therapeutic opportunities in BLCA. Finally, we performed pancancer analyses on the 5mC score. RESULTS: Two 5mC clusters, including 5mC cluster 1 and cluster 2, were identified. These novel 5mC clusters (5mC score) could accurately predict classical molecular subtypes, immunophenotypes, prognosis, and therapeutic opportunities of BLCA. 5mC cluster 1 (high 5mC score) indicated a luminal subtype and noninflamed phenotype, characterized by lower anticancer immunity but better prognosis. Moreover, 5mC cluster 1 (high 5mC score) predicted low sensitivity to cancer immunotherapy, neoadjuvant chemotherapy, and radiotherapy, but high sensitivity to antiangiogenic therapy and targeted therapies, such as blocking the ß-catenin, FGFR3, and PPAR-γ pathways. CONCLUSIONS: The novel 5mC regulator-based subtype system reflects many aspects of BLCA biology and provides new insights into precision medicine in BLCA. Furthermore, the 5mC score may be a generalizable predictor of immunotherapy response and prognosis in pancancers.

LncRNA AGAP2-AS1 interacts with IGF2BP2 to promote bladder cancer progression via regulating LRG1 mRNA stability.

BACKGROUND: The long non-coding RNA (lncRNA) AGAP2-AS1 was implicated in tumorigenesis, yet with unclear mechanism in the development of Bladder Cancer (BCa). METHODS: We collected the clinicopathological features and tissue samples of 45 patients with BCa in Xiangya Hospital. Expressions of AGAP2-AS1 and LRG1 were detected by RT-qPCR in BCa tissues and normal tissues as well as in BCa cells. The roles of AGAP2-AS1 and LRG1 were investigated by CCK-8, colony formation assay, transwell assays and tube formation assay. The subcellular localization of AGAP2-AS1 was detected by Fluorescence in situ hybridization. Bioinformatics method, RNA immunoprecipitation, RNA pull-down assay and Actinomycin D test were used to predict and identify the relationships between AGAP2-AS1, LRG1 and IGF2BP2. Xenografted tumors were produced to explore the function of AGAP2-AS1 in BCa in vivo. RESULTS: AGAP2-AS1 and LRG1 were highly upregulated in BCa. AGAP2-AS1 positively correlated with T stage, grade and vascular invasion, but negatively correlated with the survival of patients. Overexpressions of AGAP2-AS1 promoted proliferation, migration, invasion, tumor angiogenesis in vitro and tumor growth, metastasis in vivo, knockdown of AGAP2-AS1 exhibited the opposite effects. AGAP2-AS1 localized mainly in the cytoplasm. AGAP2-AS1 directly bound to IGF2BP2 protein to enhance LRG1 mRNA stability. Inhibition of BCa progression by AGAP2-AS1 knockdown may be reversed by LRG1 overexpression. CONCLUSION: AGAP2-AS1 can promote BCa progression and metastasis by recruiting IGF2BP2 to stabilize LRG1.

Computer-aided diagnosis of prostate cancer based on deep neural networks from multi-parametric magnetic resonance imaging.

Objectives: To evaluate a new deep neural network (DNN)-based computer-aided diagnosis (CAD) method, namely, a prostate cancer localization network and an integrated multi-modal classification network, to automatically localize prostate cancer on multi-parametric magnetic resonance imaging (mp-MRI) and classify prostate cancer and non-cancerous tissues. Materials and methods: The PROSTAREx database consists of a "training set" (330 suspected lesions from 204 cases) and a "test set" (208 suspected lesions from 104 cases). Sequences include T2-weighted, diffusion-weighted, Ktrans, and apparent diffusion coefficient (ADC) images. For the task of abnormal localization, inspired by V-net, we designed a prostate cancer localization network with mp-MRI data as input to achieve automatic localization of prostate cancer. Combining the concepts of multi-modal learning and ensemble learning, the integrated multi-modal classification network is based on the combination of mp-MRI data as input to distinguish prostate cancer from non-cancerous tissues through a series of operations such as convolution and pooling. The performance of each network in predicting prostate cancer was examined using the receiver operating curve (ROC), and the area under the ROC curve (AUC), sensitivity (TPR), specificity (TNR), accuracy, and Dice similarity coefficient (DSC) were calculated. Results: The prostate cancer localization network exhibited excellent performance in localizing prostate cancer, with an average error of only 1.64 mm compared to the labeled results, an error of about 6%. On the test dataset, the network had a sensitivity of 0.92, specificity of 0.90, PPV of 0.91, NPV of 0.93, and DSC of 0.84. Compared with multi-modal classification networks, the performance of single-modal classification networks is slightly inadequate. The integrated multi-modal classification network performed best in classifying prostate cancer and non-cancerous tissues with a TPR of 0.95, TNR of 0.82, F1-Score of 0.8920, AUC of 0.912, and accuracy of 0.885, which fully confirmed the feasibility of the ensemble learning approach. Conclusion: The proposed DNN-based prostate cancer localization network and integrated multi-modal classification network yielded high performance in experiments, demonstrating that the prostate cancer localization network and integrated multi-modal classification network can be used for computer-aided diagnosis (CAD) of prostate cancer localization and classification.

Filling the gaps in the research about second primary malignancies after bladder cancer: Focus on race and histology.

Purpose: Previous research has shown that bladder cancer has one of the highest incidences of developing a second primary malignancy. So, we designed this study to further examine this risk in light of race and histology. Patients and methods: Using the surveillance, epidemiology, and end results (SEER) 18 registry, we retrospectively screened patients who had been diagnosed with bladder cancer between 2000 and 2018. We then tracked these survivors until a second primary cancer diagnosis, the conclusion of the trial, or their deaths. In addition to doing a competing risk analysis, we derived standardized incidence ratios (SIRs) and incidence rate ratios (IRRs) for SPMs by race and histology. Results: A total of 162,335 patients with bladder cancer were included, and during follow-ups, a second primary cancer diagnosis was made in 31,746 of these patients. When the data were stratified by race, SIRs and IRRs for SPMs showed a significant difference: Asian/Pacific Islanders (APIs) had a more pronounced increase in SPMs (SIR: 2.15; p 0.05) than White and Black individuals who had an SIRs of 1.69 and 1.94, respectively; p 0.05. In terms of histology, the epithelial type was associated with an increase in SPMs across all three races, but more so in APIs (IRR: 3.51; 95% CI: 2.11-5.85; p 0.001). Conclusion: We found that race had an impact on both the type and risk of SPMs. Additionally, the likelihood of an SPM increases with the length of time between the two malignancies and the stage of the index malignancy.

THEM6: A Novel Molecular Biomarker Predicts Tumor Microenvironment, Molecular Subtype, and Prognosis in Bladder Cancer.

Background: Thioesterase superfamily member 6 (THEM6) has been implicated in the development and progression of various cancers. However, prior research emphasized on its regulatory role merely, we aim to investigate the effect of THEM6 gene on the immunological role and its relationship with molecular subtype in bladder cancer (BLCA). Methods: Through pan-cancer analysis, we explored the THEM6 expression pattern and immunological role using The Cancer Genome Atlas (TCGA) database. In addition, we performed a correlation of THEM6 and its immunological functions, including immunomodulators, immune checkpoints, cancer immunity cycles, T cell inflamed score, and tumor-infiltrating immune cells in the BLCA tumor microenvironment (TME) based on TCGA and BLCA microarray cohort from Xiangya Hospital. We also assessed the accuracy of THEM6 in predicting the molecular subtype and its response to different interventions in BLCA. Finally, we computed and validated a prediction model established by THEM6-related different expressed immune-related genes that might help in BLCA prognosis. Results: THEM6 led to immunosuppression in BLCA TME. Furthermore, there was a downregulation in the immunological functions. Besides, THEM6 could effectively distinguish BLCA molecular subtypes, and THEM6 low expression implied basal subtype that was more effective to several interventions, such as immune checkpoint blockade (ICB) therapies, neoadjuvant chemotherapy, and radiotherapy. While THEM6 high expression indicated luminal subtype, hyperprogression and better response to targeted therapies, such as blocking THEM6 and several immune-inhibited oncogenic pathways. Conclusions: THEM6 may be with potential immune-modulating properties and may become a potential new immunotherapy target for BLCA. THEM6 could accurately predict the molecular subtype of BLCA, which was helpful for guiding the treatment. Simultaneously, the prediction model may exhibit an excellent predictive value in patients with BLCA.

m6A-induced lncDBET promotes the malignant progression of bladder cancer through FABP5-mediated lipid metabolism.

The limited effect of adjuvant therapy for advanced bladder cancer (BCa) leads to a poor prognosis. Increasing evidence has shown that RNA N6-methyladenosine (m6A) modification plays important functional roles in tumorigenesis. Nevertheless, the role and mechanism of m6A-modified noncoding RNAs (ncRNAs) in BCa remain largely unknown. Methods: RT-PCR, western blotting and ONCOMINE dataset were used to determine the dominant m6A-related enzyme in BCa. M6A-lncRNA epitranscriptomic microarray was used to screen candidate targets of METTL14. RT-PCR, MeRIP and TCGA dataset were carried out to confirm the downstream target of METTL14. CHIRP/MS was conducted to identify the candidate proteins binding to lncDBET. RT-PCR, western blotting, RIP and KEGG analysis were used to confirm the target of lncDBET. The levels of METTL14, lncDBET and FABP5 were tested in vitro and in vivo. CCK-8, EdU, transwell and flow cytometry assays were performed to determine the oncogenic function of METTL14, lncDBET and FABP5, and their regulatory networks. Results: We identified that the m6A level of total RNA was elevated and that METTL14 was the dominant m6A-related enzyme in BCa. m6A modification mediated by METTL14 promoted the malignant progression of BCa by promoting the expression of lncDBET. Upregulated lncDBET activated the PPAR signalling pathway to promote the lipid metabolism of cancer cells through direct interaction with FABP5, thus promoting the malignant progression of BCa in vitro and in vivo. Conclusions: Our study establishes METTL14/lncDBET/FABP5 as a critical oncogenic axis in BCa.

Neoadjuvant immunotherapy, chemotherapy, and combination therapy in muscle-invasive bladder cancer: A multi-center real-world retrospective study.

To parallelly compare the efficacy of neoadjuvant immunotherapy (tislelizumab), neoadjuvant chemotherapy (gemcitabine and cisplatin), and neoadjuvant combination therapy (tislelizumab + GC) in patients with muscle-invasive bladder cancer (MIBC) and explore the efficacy predictors, we perform a multi-center, real-world cohort study that enrolls 253 patients treated with neoadjuvant treatments (combination therapy: 98, chemotherapy: 107, and immunotherapy: 48) from 15 tertiary hospitals. We demonstrate that neoadjuvant combination therapy achieves the highest complete response rate and pathological downstaging rate compared with neoadjuvant immunotherapy or chemotherapy. We develop and validate an efficacy prediction model consisting of pretreatment clinical characteristics, which can pinpoint candidates to receive neoadjuvant combination therapy. We also preliminarily reveal that patients who achieve pathological complete response after neoadjuvant treatments plus maximal transurethral resection of the bladder tumor may be safe to receive bladder preservation therapy. Overall, this study highlights the benefit of neoadjuvant combination therapy based on tislelizumab for MIBC.

A Poliovirus Receptor (CD155)-Related Risk Signature Predicts the Prognosis of Bladder Cancer.

BACKGROUND: Bladder cancer is an aggressive and heterogeneous disease associated with high morbidity and mortality. And poliovirus receptor (PVR or CD155) played crucial roles in tumor immune microenvironment and cancer development. However, their association remains obscure. METHODS: A total of 797 patients from TCGA and GEO databases were employed in our study, in which 285 cases were set as the training cohort and 512 were defined as the validation cohort. Our own Xiangya cohort with 57 samples was also used for the validation. Survival differences were evaluated by Kaplan-Meier analysis between groups. The immune infiltration was evaluated by ESTIMATE, TIMER, and CIBERSORT algorithms. The risk signature was constructed by LASSO Cox regression analysis. And a nomogram model was generated subsequent to the multivariate Cox proportional hazards analysis to predict 3- and 5-year survival of patients with bladder cancer. RESULTS: PVR was overexpressed across various cancers including bladder cancer and related to poorer overall survival in bladder urothelial carcinoma (BLCA). Samples with higher World Health Organization (WHO) grade or higher tumor stage tended to express higher level of PVR. And PVR-related genes were involved in several immune processes and oncological pathways. When the patients were divided into low- and high-risk groups based on their risk scores, we found that patients in the high-risk group had shorter overall survival time. Besides, samples with high risk were consistently correlated with tumor hallmarks and higher abundance of immune infiltration. Additionally, chemotherapy showed potent efficacy in high-risk group. Moreover, a nomogram including clinicopathologic features and the established risk signature could predict 3- and 5-year survival in patients with bladder cancer. CONCLUSION: Our study revealed that PVR was overexpressed and related to poor prognosis in bladder cancer. A risk signature and nomogram model based on PVR-related genes could predict the prognosis and therapeutic efficacy and were also associated with the immune infiltration in bladder cancer.

Emerging Biomarkers for Predicting Bladder Cancer Lymph Node Metastasis.

Bladder cancer is one of the leading causes of cancer deaths worldwide. Early detection of lymph node metastasis of bladder cancer is essential to improve patients' prognosis and overall survival. Current diagnostic methods are limited, so there is an urgent need for new specific biomarkers. Non-coding RNA and m6A have recently been reported to be abnormally expressed in bladder cancer related to lymph node metastasis. In this review, we tried to summarize the latest knowledge about biomarkers, which predict lymph node metastasis in bladder cancer and their mechanisms. In particular, we paid attention to the impact of non-coding RNA on lymphatic metastasis of bladder cancer and its specific molecular mechanisms, as well as some prediction models based on imaging, pathology, and biomolecules, in an effort to find more accurate diagnostic methods for future clinical application.

Effects of Fibrin Clot Inhibitors and Statins on the Intravesical Bacille Calmette-Guérin Therapy for Bladder Cancer: A Systematic Review and Meta-Analysis.

OBJECTIVE: To assess the effect of fibrin clot inhibitors (aspirin, clopidogrel, and warfarin) and statins on intravesical BCG therapy. METHOD: A systematic literature search was carried out through PubMed, Embase, and the Cochrane Central Search Library in March 2020. Accumulative analyses of odds ratios (ORs), hazard ratio (HR), and corresponding 95% confidence intervals (CIs) were performed. All analyses were performed by using Review Manager software version 5.3 and Stata 15.1. RESULTS: Four cohort studies and nine case-control studies containing 3,451 patients were included. The pooled analysis indicated that statins (HR = 1.00; 95%CI, 0.82 to 1.22; p = 1.00) and fibrin clot inhibitors (HR = 1.01; 95%CI, 0.64 to 1.59; p = 0.98) did not affect the efficacy of BCG on recurrence-free survival. The cumulative analysis showed that statins (HR = 0.79; 95%CI, 0.41 to 1.49; p = 0.46) and fibrin clot inhibitors (HR = 1.62; 95%CI, 0.90 to 2.91; p = 0.11) did not affect the efficacy of BCG on progression-free survival. There were no differences on cancer-specific survival (HR = 1.68; 95%CI, 0.64 to 4.40; p = 0.29) and overall survival (HR = 1.13; 95%CI, 0.73 to 1.78; p = 0.58) after taking statins. CONCLUSION: The present study shows that the application of fibrin clot inhibitors and statins do not influence the efficacy of BCG on oncological prognosis. Consequently, we do not need to stop using them or change to other drugs during intravesical BCG treatment. However, large-scale multi-center prospective research is still needed to confirm the above conclusions.

RNA Modification of N6-Methyladenosine Predicts Immune Phenotypes and Therapeutic Opportunities in Kidney Renal Clear Cell Carcinoma.

RNA modification of N6-methyladenosine (m6A) plays critical roles in various biological processes, such as cancer development, inflammation, and the anticancer immune response. However, the role played by a comprehensive m6A modification pattern in regulating anticancer immunity in kidney renal clear cell carcinoma (KIRC) has not been fully elucidated. In this study, we identified two independent m6A modification patterns with distinct biological functions, immunological characteristics, and prognoses in KIRC. Next, we developed an m6A score algorithm to quantify an individual's m6A modification pattern, which was independently validated in external cohorts. The m6A cluster 1 and low m6A score groups were characterized by a hot tumor microenvironment with an increased infiltration level of cytotoxic immune cells, higher tumor mutation burden, higher immune checkpoint expression, and decreased stroma-associated signature enrichment. In general, the m6A cluster 1 and low m6A score groups reflected an inflammatory phenotype, which may be more sensitive to anticancer immunotherapy. The m6A cluster 2 and high m6A score groups indicated a non-inflammatory phenotype, which may not be sensitive to immunotherapy but rather to targeted therapy. In this study, we first identified m6A clusters and m6A scores to elucidate immune phenotypes and to predict the prognosis and immunotherapy response in KIRC, which can guide urologists for making more precise clinical decisions.

A Robust Hypoxia Risk Score Predicts the Clinical Outcomes and Tumor Microenvironment Immune Characters in Bladder Cancer.

Background: Bladder cancer (BLCA) is one of the most common urinary malignancies with poor prognosis. There is an unmet need to develop novel robust tools to predict prognosis and treatment efficacy for BLCA. Methods: The hypoxia-related genes were collected from the Molecular Signatures Database. The TCGA-BLCA cohort was downloaded from the Cancer Genome Atlas and then was randomly divided into training and internal validation sets. Two external validation cohorts were gathered from Gene Expression Omnibus. Also, another independent validation cohort (Xiangya cohort) was collected from our hospital. The Cox regression model with the LASSO algorithm was applied to develop the hypoxia risk score. Then, we correlated the hypoxia risk score with the clinical outcomes, the tumor microenvironment (TME) immune characteristics, and the efficacy prediction for several treatments, which included cancer immunotherapy, chemotherapy, radiotherapy, and targeted therapies. Results: Hypoxia risk score was an independent prognostic factor. A high-risk score indicated an inflamed TME based on the evidence that hypoxia risk score positively correlated with the activities of several cancer immunity cycles and the infiltration levels of many tumor-infiltrating immune cells, such as CD8 + T cells, Dendritic cells, and NK cells. Consistently, the hypoxia risk score was positively related to the expression of several immune checkpoints, such as PD-L1, PD-1, CTLA-4, and LAG-3, as well as the T cell inflamed score. Furthermore, the hypoxia risk score positively correlated with the enrichment scores of most immunotherapy-positive gene signatures. Therefore, patients with higher risk score may be more sensitive to cancer immunotherapy. Meanwhile, the hypoxia risk score was positively related to the sensitivities of several chemotherapeutic drugs, including Cisplatin, Docetaxel, Paclitaxel, Bleomycin, Camptothecin, and Vinblastine. Similarly, the enrichment scores for radiotherapy-predicted pathways and EGFR ligands were higher in the high-risk score group. Conversely, the enrichment scores of several immunosuppressive oncogenic pathways were significantly higher in the low-risk score group, such as the WNT-ß-catenin network, PPARG network, and FGFR3 network. Conclusions: We developed and validated a new hypoxia risk score, which could predict the clinical outcomes and the TME immune characteristics of BLCA. In general, the hypoxia risk score may aid in the precision medicine for BLCA.

A Novel TGF-ß Risk Score Predicts the Clinical Outcomes and Tumour Microenvironment Phenotypes in Bladder Cancer.

Background: The TGF-ß pathway plays critical roles in numerous malignancies. Nevertheless, its potential role in prognosis prediction and regulating tumour microenvironment (TME) characteristics require further elucidation in bladder cancer (BLCA). Methods: TGF-ß-related genes were comprehensively summarized from several databases. The TCGA-BLCA cohort (training cohort) was downloaded from the Cancer Genome Atlas, and the independent validation cohorts were gathered from Xiangya Hospital (Xinagya cohort) and Gene Expression Omnibus. Initially, we identified differentially expressed TGF-ß genes (DEGs) between cancer and normal tissues. Subsequently, univariate Cox analysis was applied to identify prognostic DEGs, which were further used to develop the TGF-ß risk score by performing LASSO and multivariate Cox analyses. Then, we studied the role of the TGF-ß risk score in predicting prognosis and the TME phenotypes. In addition, the role of the TGF-ß risk score in guiding precision treatments for BLCA has also been assessed. Results: We successfully constructed a TGF-ß risk score with an independent prognostic prediction value. A high TGF-ß risk score indicated an inflamed TME, which was supported by the positive relationships between the risk score, enrichment scores of anticancer immunity steps, and the infiltration levels of tumour-infiltrating immune cells. In addition, the risk score positively correlated with the expression of several immune checkpoints and the T cell inflamed score. Consistently, the risk score was positively related to the enrichment scores of most immunotherapy-positive pathways. In addition, the sensitivities of six common chemotherapeutic drugs were positively associated with the risk score. Furthermore, higher risk score indicated higher sensitivity to radiotherapy and EGFR-targeted therapy. On the contrary, patients with low-risk scores were more sensitive to targeted therapies, including the blockade of FGFR3 and WNT-ß-catenin networks. Conclusions: We first constructed and validated a TGF-ß signature that could predict the prognosis and TME phenotypes for BLCA. More importantly, the TGF-ß risk score could aid in individual precision treatment for BLCA.

N6-Methyladenosine Writer Gene ZC3H13 Predicts Immune Phenotype and Therapeutic Opportunities in Kidney Renal Clear Cell Carcinoma.

BACKGROUND: Although the RNA modification N6-methyladenosine ZC3H13 has been found to play vital regulatory roles in many types of cancers, its role in predicting the tumor immune microenvironment (TME) and response to immune checkpoint blockade (ICB) in kidney renal clear cell carcinoma (KIRC) remains unclear. METHODS: We comprehensively analyzed the expression, prognostic significance and immunological role of ZC3H13 in pan-cancers and systematically correlated ZC3H13 with TME cell-infiltration, ICB response and targeted therapy in KIRC. The data were collected from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Genotype-Tissue Expression (GTEx), Broad Institute Cancer Cell Line Encyclopedia (CCLE) and DrugBank database. Also, we performed RNA sequencing (RNA-seq) of 46 renal cell carcinoma tissues and 11 adjacent normal tissues to validate our result. All analyses were implemented using R software, version 3.6.3. RESULTS: ZC3H13 was significantly differentially expressed in most tumors. However, its expression profiles and prognostic significance were consistent only in KIRC, regardless of overall survival, progression-free survival and cancer-specific survival. Additionally, ZC3H13 expression was correlated with clinicopathological factors in KIRC. Furthermore, we found that ZC3H13 might shape a noninflamed phenotype and could predict a lower response to ICB in KIRC. These results could be validated in our own RNA-seq data. Tumor mutation burden (TMB) was significantly higher in the low ZC3H13 group. Finally, we found that ZC3H13 could predict the sensitivity of targeted therapy for KIRC. CONCLUSIONS: ZC3H13 might shape a noninflamed phenotype in KIRC. Moreover, ZC3H13 could predict the prognosis and clinical response of ICB and the sensitivity to targeted therapies in KIRC.

Recurrence factors in patients with Keratinizing squamous metaplasia of the bladder after surgical management: a single-center retrospective study.

BACKGROUND: Keratinizing squamous metaplasia (KSM) is a clinically heterogeneous disease that lacks research that provide definitive recurrent risk factors. Therefore, we identified the recurrence factors in patients with KSM of the bladder after transurethral resection (TUR). We also attempted to investigate the association between KSM and bladder cancer. METHODS: Clinical information of 257 patients diagnosed with KSM who underwent TUR in Xiangya Hospital from January 2010 to November 2018 were retrospectively collected. Clinical information was available for follow-up of 223 patients. To determine the risk factors for recurrence, we conducted univariate and multivariate cox regression analysis respectively. To explore the association between KSM and bladder cancer, we used clinical follow-up data. RESULTS: The median follow-up time is 49 (IQR, 12-121) months. Five-year recurrence-free rate (RFR) and 1-year RFR were 86.1% and 91.9%, respectively. Thirty-one patients (13.9%) relapsed of KSM after a median follow-up of 49 months (range, 12-121 months), and none of them developed subsequent bladder cancer. Univariate Cox analysis indicated that urinary tract infection [hazard ratio (HR) =2.111; 95% confidence interval (CI): 1.043-4.271; P=0.038], and atypical urothelial hyperplasia of the bladder (HR =4.191; 95% CI: 2.006-8.756; P<0.001) were significant recurrence factors. Multivariate Cox analysis suggested that atypical urothelial hyperplasia of the bladder (HR =3.506; 95% CI: 1.663-7.392; P=0.001) was the independent risk factor for postoperative recurrence of KSM. CONCLUSIONS: The recurrence rate in patients with KSM was about 13.9%, and atypical urothelial hyperplasia of the bladder was the independent risk factor in patients with KSM recurrence. In cases with bladder atypical urothelial hyperplasia, close follow-ups are necessary. Also, we demonstrated that KSM did not increase the subsequent risk of bladder cancer.

PMEPA1 Is a Prognostic Biomarker That Correlates With Cell Malignancy and the Tumor Microenvironment in Bladder Cancer.

Prostate transmembrane protein androgen induced 1 (PMEPA1) has been reported to promote cancer progression, but the potential role of PMEPA1 in bladder cancer (BLCA) remains elusive. We assess the role of PMEPA1 in BLCA, via a publicly available database and in vitro study. PMEPA1 was identified from 107 differentially expressed genes (DEGs) to have prognostic value. GO, KEGG, and GSEA analysis indicated that PMEPA1 was involved in cancer progression and the tumor microenvironment (TME). Then bioinformatical analysis in TCGA, GEO, TIMER, and TISIDB show a positive correlation with the inflammation and infiltration levels of three tumor-infiltrating immune cells (TAMs, CAFs, and MDSCs) and immune/stromal scores in TME. Moreover, in vitro study revealed that PMEPA1 promotes bladder cancer cell malignancy. Immunohistochemistry and survival analysis shed light on PMEPA1 potential to be a novel biomarker in predicting tumor progression and prognosis. At last, we also analyzed the role of PMEPA1 in predicting the molecular subtype and the response to several treatment options in BLCA. We found that PMEPA1 may be a novel potential biomarker to predict the progression, prognosis, and molecular subtype of BLCA.

Siglec15 shapes a non-inflamed tumor microenvironment and predicts the molecular subtype in bladder cancer.

Rationale: Siglec15 is an emerging target for normalization cancer immunotherapy. However, pan-cancer anti-Siglec15 treatment is not yet validated and the potential role of Siglec15 in bladder cancer (BLCA) remains elusive. Methods: We comprehensively evaluated the expression pattern and immunological role of Siglec15 using pan-cancer analysis based on RNA sequencing data obtained from The Cancer Genome Atlas. We then systematically correlated Siglec15 with immunological characteristics in the BLCA tumor microenvironment (TME), including immunomodulators, cancer immunity cycles, tumor-infiltrating immune cells (TIICs), immune checkpoints, and T cell inflamed score. We also analyzed the role of Siglec15 in predicting the molecular subtype and the response to several treatment options in BLCA. Our results were validated in several public cohorts as well as our BLCA tumor microarray cohort, the Xiangya cohort. We developed an immune risk score (IRS), validated it, and tested its ability to predict the prognosis and response to cancer immunotherapy. Results: We found that Siglec15 was specifically overexpressed in the TME of various cancers. We hypothesize that Siglec15 designs a non-inflamed TME in BLCA based on the evidence that Siglec15 negatively correlated with immunomodulators, TIICs, cancer immunity cycles, immune checkpoints, and T cell inflamed score. Bladder cancer with high Siglec15 expression was not sensitive to cancer immunotherapy, but exhibited a higher incidence of hyperprogression. High Siglec15 levels indicated a luminal subtype of BLCA characterized by lower immune infiltration, lower response to cancer immunotherapy and neoadjuvant chemotherapy, but higher response to anti-angiogenic therapy and targeted therapies such as blocking Siglec15, ß-catenin, PPAR-γ, and FGFR3 pathways. Notably, a combination of anti-Siglec15 and cancer immunotherapy may be a more effective strategy than monotherapy. IRS can accurately predict the prognosis and response to cancer immunotherapy. Conclusions: Anti-Siglec15 immunotherapy might be suitable for BLCA treatment as Siglec15 correlates with a non-inflamed TME in BLCA. Siglec15 could also predict the molecular subtype and the response to several treatment options.