Predicting Response to Neoadjuvant Chemotherapy in Bladder Cancer

A novel mitochondrial-related lncRNA signature mediated prediction of overall survival, immune landscape, and the chemotherapeutic outcomes for bladder cancer patients

OBJECTIVE

To develop a prognostic risk model for Bladder Cancer (BLCA) based on mitochondrial-related long non-coding RNAs (lncRNAs).

METHODS

Transcriptome and clinical data of BLCA patients were retrieved from the TCGA database. Mitochondrial-related lncRNAs with independent prognostic significance were screened to develop a prognostic risk model. Patients were categorized into high- and low-risk groups using the model. Various methods including Kaplan-Meier (KM) analysis, ROC curve analysis, Gene Set Enrichment Analysis (GSEA), immune analysis, and chemotherapy drug analysis were used to verify and evaluate the model.

RESULTS

A mitochondrial-associated lncRNA prognostic risk model with independent prognostic significance was developed. High-risk group (HRG) patients exhibited significantly shorter survival periods compared to low-risk group (LRG) patients (P < 0.01). The risk score from the model was an independent predictor of BLCA prognosis, correlating with tumor grade, pathological stage, and lymph node metastasis (P < 0.05). The HRG showed significant positive correlations with high expressions of immune checkpoints (CTLA4, LAG3, PD-1, TIGIT, PD-L1, PD-L2, and TIM-3) and lower IC50 for chemotherapy drugs (cisplatin, docetaxel, paclitaxel, methotrexate, and vinblastine) (P < 0.001).

CONCLUSIONS

The mitochondrial-related lncRNA-based prognostic risk model effectively predicts BLCA prognosis and can guide individualized treatment for BLCA patients.

Bioinformatics in urology - molecular characterization of pathophysiology and response to treatment

The application of bioinformatics has revolutionized the practice of medicine in the past 20 years. From early studies that uncovered subtypes of cancer to broad efforts spearheaded by the Cancer Genome Atlas initiative, the use of bioinformatics strategies to analyse high-dimensional data has provided unprecedented insights into the molecular basis of disease. In addition to the identification of disease subtypes - which enables risk stratification - informatics analysis has facilitated the identification of novel risk factors and drivers of disease, biomarkers of progression and treatment response, as well as possibilities for drug repurposing or repositioning; moreover, bioinformatics has guided research towards precision and personalized medicine. Implementation of specific computational approaches such as artificial intelligence, machine learning and molecular subtyping has yet to become widespread in urology clinical practice for reasons of cost, disruption of clinical workflow and need for prospective validation of informatics approaches in independent patient cohorts. Solving these challenges might accelerate routine integration of bioinformatics into clinical settings.

Does Bladder Cancer Subtype Influence Pathologic Complete Response (pCR) and Pelvic Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI) Response Evaluation After Neoadjuvant Chemotherapy? Pathological Perspective

INTRODUCTION

We aimed to provide a pathological perspective on the management of muscle-invasive bladder cancer (MIBC) by correlating the prechemotherapy transurethral resection of bladder tumor findings and postchemotherapy radiologic evaluation with final radical cystectomy (RC) findings.

MATERIALS AND METHODS

This retrospective study included 79 MIBC patients treated with neoadjuvant chemotherapy (NAC) and RC. Pelvic diffusion-weighted magnetic resonance imaging (DW-MRI) and pathologic reports were retrieved from our institutional database. All pathology slides were reviewed based on diagnostic criteria with high interobserver reproducibility.

RESULTS

Pathologic complete response (pCR) was confirmed in 32 patients (40.5%). The concordance and discordance between MRI and RC findings occurred in 68.3% and 31.7% of cases, respectively. The 21.5% of cases that were clinical CR (cCR) on MRI actually achieved pCR on RC specimens and 46.8% of cases that were non-cCR on MRI were actually non-pCR on RC specimens. In 19.0% of cases, RC findings were pCR, but MRI demonstrated residual tumor and the opposite was 12.7%. The greatest discrepancy between the 2 methods (75%, 3/4) was for the plasmacytoid subtype. Plasmacytoid histology was the most common histological subtype identified in RC specimens after NAC, followed by micropapillary and squamous histologies.

CONCLUSIONS

We found that all cases with plasmacytoid and micropapillary subtypes, and squamous differentiation did not show pCR. In particular, the largest discrepancy between MRI findings and RC pathology after NAC was seen in the plasmacytoid subtype. An accurate pathologic diagnosis based on strict criteria to identify histological subtypes of MIBC is necessary for proper treatment.

The potential mechanism of ursolic acid in the treatment of bladder cancer based on network pharmacology and molecular docking

OBJECTIVE

This study explored the potential molecular mechanisms of ursolic acid (UA) in bladder cancer treatment using network pharmacology and molecular docking.

METHODS

The Traditional Chinese Medicine Systems Pharmacology and UniProt databases were used to screen potential targets of UA. Relevant bladder cancer target genes were extracted using the GeneCards database. All data were pooled and intercrossed to obtain common target genes of UA and bladder cancer. Gene Ontology functional annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed. Molecular docking was conducted to verify the possible binding conformation between UA and bladder cancer cells. Then, in vitro experiments were performed to further validate the predicted results.

RESULTS

UA exerts anti-tumor effects on bladder cancer through multiple targets and pathways. Molecular docking indicated that UA undergoes stable binding with the proteins encoded by the top six core genes (STAT3, VEGFA, CASP3, TP53, IL1B, and CCND1). The in vitro experiments verified that UA can induce bladder cancer cell apoptosis by regulating the PI3K/Akt signaling pathway.

CONCLUSIONS

Our study illustrated the potential mechanism of UA in bladder cancer based on network pharmacology and molecular docking. The results will provide scientific references for follow-up studies and clinical treatment.

Systemic Inflammatory Index: A Promising Non-Invasive Marker for the Prediction of Response to Neoadjuvant Chemotherapy prior to Cystectomy

INTRODUCTION

The main challenge to the optimal use of neoadjuvant chemotherapy (NAC) is the difficulty in selecting patients who may or may not benefit from NAC. Our aim in this study was to investigate whether the Systemic Inflammatory Index (SII) predicts response to chemotherapy in patients who receive NAC prior to cystectomy.

METHODS

We retrospectively analysed the data of patients who underwent NAC followed by cystectomy at our institution between January 2010 and September 2015 and whose 5-year follow-up was completed. All patients who underwent diagnostic biopsy with complete transurethral resection of bladder tumour at our hospital and whose pathology result was muscle-invasive transitional cell carcinoma were included in the study. At least 3 courses of gemcitabine/cisplatin NAC were given to all patients. A pathological response was defined as a reduction in cystectomy to a lower pathological stage after NAC.

RESULTS

The SII was 320.8 ± 51 in the responders and 388.28 ± 50 in the non-responders. SII optimal cut-off of 350 was determined. The sensitivity and specificity of SII in predicting response were found to be 80% and 83%, respectively. Low SII (<350) was found to be a significant predictor of response compared with the other factors on multivariate analysis. The mean overall survival time was 55.4 months in patients with a low SII value and 40.3 months in the high SII group.

CONCLUSION

SII, together with known clinicopathological factors and newer genetic and molecular markers, can be used to select patients for NAC.

Bladder Cancer: Immunotherapy and Pelvic Lymph Node Dissection

Bladder cancer, a common malignancy of the urinary system, is routinely treated with radiation, chemotherapy, and surgical excision. However, these strategies have inherent limitations and may also result in various side effects. Immunotherapy has garnered considerable attention in recent years as a novel therapeutic approach. It harnesses and activates the patient's immune system to recognize and eliminate cancer cells, which not only prolongs therapeutic efficacy but also minimizes the toxic side effects. Several immune checkpoint inhibitors and cancer vaccines have been developed for the treatment of bladder cancer. Whereas blocking immune checkpoints on the surface of tumor cells augments the effect of immune cells, immunization with tumor-specific antigens can elicit the production of anti-tumor immune effector cells. However, there are several challenges in applying immunotherapy against bladder cancer. For instance, the efficacy of immunotherapy varies considerably across individual patients, and only a small percentage of cancer patients are responsive. Therefore, it is crucial to identify biomarkers that can predict the efficacy of immunotherapy. Pelvic lymph nodes are routinely dissected from bladder cancer patients during surgical intervention in order to remove any metastatic tumor cells. However, some studies indicate that pelvic lymph node dissection may reduce the efficacy of immunotherapy by damaging the immune cells. Therefore, the decision to undertake pelvic lymph node removal should be incumbent on the clinical characteristics of individual patients. Thus, although immunotherapy has the advantages of lower toxic side effects and long-lasting efficacy, its application in bladder cancer still faces challenges, such as the lack of predictive biomarkers and the effects of pelvic lymph node dissection. Further research is needed to explore these issues in order to improve the efficacy of immunotherapy for bladder cancer.

How Do Molecular Classifications Affect the Neoadjuvant Treatment of Muscle-Invasive Urothelial Carcinoma?

Despite the significant improvements in the field of oncological treatments in recent decades, and the advent of targeted therapies and immunotherapy, urothelial carcinoma of the bladder remains a highly heterogeneous and difficult-to-treat neoplasm with a poor prognosis. In this context, owing to the new methods of genomic sequencing, numerous studies have analyzed the genetic features of muscle-invasive bladder cancer, providing a consensus set of molecular classes, to identify malignancies that may respond better to specific treatments (standard chemotherapy, immunotherapy, target therapy, local-regional treatment, or combinations) and improve the survival. The aim of the current review is to provide an overview of the current status of the molecular landscape of muscle-invasive bladder cancer, focusing our attention on therapeutic and prognostic implications in order to select the most effective and tailored therapeutic regimen for the individual patient.

The assessment of pathological response to neoadjuvant chemotherapy in muscle-invasive bladder cancer patients with DCE-MRI and DWI: a systematic review and meta-analysis

OBJECTIVE

The purpose of this meta-analysis was to determine the value of dynamic contrast-enhanced-MRI (DCE-MRI) and diffusion-weighted imaging (DWI) in evaluating the pathological response of muscle invasive bladder cancer (MIBC) to neoadjuvant chemotherapy (NAC), and further indirectly compare the diagnostic performance of DCE-MRI and DWI.

METHODS

Literatures associated to DCE-MRI and DWI in the evaluation of pathological response of MIBC to NAC were searched from PubMed, Cochrane Library, web of science, and EMBASE databases. The quality assessment of diagnostic accuracy studies 2 tool was used to assess the quality of studies. Pooled sensitivity (SE), specificity (SP), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the area under the receiver operating characteristic curves (AUC) with their 95% confidence intervals (CIs) were calculated to evaluate the diagnostic performance of DCE-MRI and DWI in predicting the pathological response to NAC in patients with MIBC.

RESULTS

There were 11 studies involved, 6 of which only underwent DCE- MRI examination, 4 of which only underwent DWI examination, and 1 of which underwent both DCE- MRI and DWI examination. The pooled SE, SP, PLR, NLR, DOR of DCE-MRI were 0.88 (95% CI: 0.78-0.93), 0.88 (95% CI: 0.67-0.96), 7.4 (95% CI: 2.3-24.2), 0.14 (95% CI: 0.07-0.27), and 53 (95% CI: 10-288), respectively. The pooled SE, SP, PLR, NLR, DOR of DWI were 0.83 (95% CI: 0.75-0.88), 0.88 (95% CI: 0.81-0.93), 7.1 (95% CI: 4.3-11.7), 0.20 (95% CI: 0.14-0.28), and 36 (95% CI:18-73), respectively. The AUCs of SROC curve for DCE-MRI and DWI were 0.93 (95% CI: 0.91-0.95) and 0.92 (95% CI: 0.89-0.94), respectively. There were no significant differences between DWI and DCE-MRI for SE, SP, and AUC.

CONCLUSION

This meta-analysis demonstrated high diagnostic performance of both DCE-MRI and DWI in predicting the pathological response to NAC in MIBC. DWI might be a potential substitute for DCE-MRI, with no significant difference in diagnostic performance between the two. However, caution should be taken when applying our results, as our results were based on indirect comparison.

ADVANCES IN KNOWLEDGE

No previous studies have comprehensively analysed the value of DCE-MRI and DWI in evaluating the pathological response to NAC in MIBC. According to the current study, both DCE-MRI and DWI yielded high diagnostic performance, with the AUCs of 0.93 and 0.92, respectively. Indirect comparison no significant difference in the diagnostic performanceof DCE-MRI and DWI.

Artificial Intelligence in Digital Pathology for Bladder Cancer: Hype or Hope? A Systematic Review

Bladder cancer (BC) diagnosis and prediction of prognosis are hindered by subjective pathological evaluation, which may cause misdiagnosis and under-/over-treatment. Computational pathology (CPATH) can identify clinical outcome predictors, offering an objective approach to improve prognosis. However, a systematic review of CPATH in BC literature is lacking. Therefore, we present a comprehensive overview of studies that used CPATH in BC, analyzing 33 out of 2285 identified studies. Most studies analyzed regions of interest to distinguish normal versus tumor tissue and identify tumor grade/stage and tissue types (e.g., urothelium, stroma, and muscle). The cell's nuclear area, shape irregularity, and roundness were the most promising markers to predict recurrence and survival based on selected regions of interest, with >80% accuracy. CPATH identified molecular subtypes by detecting features, e.g., papillary structures, hyperchromatic, and pleomorphic nuclei. Combining clinicopathological and image-derived features improved recurrence and survival prediction. However, due to the lack of outcome interpretability and independent test datasets, robustness and clinical applicability could not be ensured. The current literature demonstrates that CPATH holds the potential to improve BC diagnosis and prediction of prognosis. However, more robust, interpretable, accurate models and larger datasets-representative of clinical scenarios-are needed to address artificial intelligence's reliability, robustness, and black box challenge.

Predictive and Prognostic Role of the Neutrophil-to-Lymphocyte Ratio in Muscle Invasive Bladder Cancer Treated With Neoadjuvant Chemotherapy and Radical Cystectomy

INTRODUCTION

There is a persistent lack of validated biomarkers that identify patients most likely to benefit from neoadjuvant chemotherapy (NAC) in urothelial carcinoma of the bladder (UCB). Therefore, the purpose of this study was to investigate the predictive and prognostic impact of the pretreatment neutrophil-to-lymphocyte ratio (NLR) in UCB patients treated with NAC and radical cystectomy (RC).

PATIENTS AND METHODS

We conducted a retrospective analysis of an international-multicenter database comprising 404 UCB patients staged cT2-4N0-3M0. The cohort was split into low and high NLR using an optimal cutoff value determined by maximizing Youden's index. Logistic and Cox regression analyses were performed with respect to several clinical endpoints. The discriminative ability of the models and the additive discriminative value of NLR was assessed by calculating the area under receiver operating characteristics curves, C-index, and decision curve analysis (DCA).

RESULTS

A total of 169 patients (41.8%) had a high NLR, which was associated with a decreased probability of complete response (CR, OR: 0.24 [95% CI, 0.13-0.42], P < .001) and/or partial response (PR, OR: 0.33 [95% CI, 0.21-0.49], P < .001). Adding the NLR to predictive reference models significantly improved their accuracy for the prediction of both CR and PR. A high NLR was associated with poor survival outcomes in the pretreatment setting, however, it didn't meaningfully change the C-index based on the model.

CONCLUSION

We confirmed that an elevated NLR is an independent and clinically significant predictor of response to NAC and adverse pathological features in UCB treated with NAC plus RC. The accuracy of this biomarker in the age of immunotherapy warrants further evaluation.

Impact of nephroureterectomy on postoperative renal function in upper tract urothelial carcinoma: A multicenter retrospective study

OBJECTIVE

To assess the impact of radical nephroureterectomy on postoperative renal function in patients with upper tract urothelial carcinoma (UTUC).

METHODS

We retrospectively evaluated 645 patients with UTUC treated with radical nephroureterectomy between January 2000 and May 2022. The primary outcome was the rate of postoperative estimated glomerular filtration rate (eGFR) ≥60 mL/min/1.73 m2 . Secondary outcomes included the rate of eGFR decline, identification of factors related to eGFR decline, and the impact of comorbidities (diabetes or cardiovascular disease) on postoperative eGFR at 1 year.

RESULTS

The median preoperative and postoperative eGFR levels were 55.6 and 43.3 mL/min/1.73 m2 , respectively. The rate of patients with preoperative and postoperative eGFR ≥60 mL/min/1.73 m2 was 40.9% and 9.0%, respectively. The median decline in eGFR after surgery was 25.1%. The presence of preoperative unilateral hydronephrosis and eGFR <60 mL/min/1.73 m2 was significantly associated with a low decline of postoperative eGFR and poor survival. The impact of the presence of comorbidities on postoperative eGFR at 1 year was significant (p < 0.001).

CONCLUSION

Impaired renal function is prevalent in patients with UTUC. The rate of patients with postoperative eGFR ≥60 mL/min/1.73 m2 was 9.0%. The presence of preoperative renal impairment was significantly related to a low decline in postoperative eGFR and poor survival. The presence of comorbidities had a significant effect on eGFR decline 1 year after radical nephroureterectomy.

The Present and Future of Artificial Intelligence in Urological Cancer

Artificial intelligence has drawn more and more attention for both research and application in the field of medicine. It has considerable potential for urological cancer detection, therapy, and prognosis prediction due to its ability to choose features in data to complete a particular task autonomously. Although the clinical application of AI is still immature and faces drawbacks such as insufficient data and a lack of prospective clinical trials, AI will play an essential role in individualization and the whole management of cancers as research progresses. In this review, we summarize the applications and studies of AI in major urological cancers, including tumor diagnosis, treatment, and prognosis prediction. Moreover, we discuss the current challenges and future applications of AI.

Predicting Lymph Node Metastasis Status from Primary Muscle-Invasive Bladder Cancer Histology Slides Using Deep Learning: A Retrospective Multicenter Study

BACKGROUND

Accurate prediction of lymph node metastasis (LNM) status in patients with muscle-invasive bladder cancer (MIBC) before radical cystectomy can guide the use of neoadjuvant chemotherapy and the extent of pelvic lymph node dissection. We aimed to develop and validate a weakly-supervised deep learning model to predict LNM status from digitized histopathological slides in MIBC.

METHODS

We trained a multiple instance learning model with an attention mechanism (namely SBLNP) from a cohort of 323 patients in the TCGA cohort. In parallel, we collected corresponding clinical information to construct a logistic regression model. Subsequently, the score predicted by the SBLNP was incorporated into the logistic regression model. In total, 417 WSIs from 139 patients in the RHWU cohort and 230 WSIs from 78 patients in the PHHC cohort were used as independent external validation sets.

RESULTS

In the TCGA cohort, the SBLNP achieved an AUROC of 0.811 (95% confidence interval [CI], 0.771-0.855), the clinical classifier achieved an AUROC of 0.697 (95% CI, 0.661-0.728) and the combined classifier yielded an improvement to 0.864 (95% CI, 0.827-0.906). Encouragingly, the SBLNP still maintained high performance in the RHWU cohort and PHHC cohort, with an AUROC of 0.762 (95% CI, 0.725-0.801) and 0.746 (95% CI, 0.687-0.799), respectively. Moreover, the interpretability of SBLNP identified stroma with lymphocytic inflammation as a key feature of predicting LNM presence.

CONCLUSIONS

Our proposed weakly-supervised deep learning model can predict the LNM status of MIBC patients from routine WSIs, demonstrating decent generalization performance and holding promise for clinical implementation.

Alternative splicing in bladder cancer: potential strategies for cancer diagnosis, prognosis, and treatment

Bladder cancer is the most common malignancy of the urinary tract worldwide. The therapeutic options to tackle this disease comprise surgery, intravesical or systemic chemotherapy, and immunotherapy. Unfortunately, a wide number of patients ultimately become resistant to these treatments and develop aggressive metastatic disease, presenting a poor prognosis. Therefore, the identification of novel therapeutic approaches to tackle this devastating pathology is urgently needed. However, a significant limitation is that the progression and drug response of bladder cancer is strongly associated with its intrinsic molecular heterogeneity. In this sense, RNA splicing is recently gaining importance as a critical hallmark of cancer since can have a significant clinical value. In fact, a profound dysregulation of the splicing process has been reported in bladder cancer, especially in the expression of certain key splicing variants and circular RNAs with a potential clinical value as diagnostic/prognostic biomarkers or therapeutic targets in this pathology. Indeed, some authors have already evidenced a profound antitumor effect by targeting some splicing factors (e.g., PTBP1), mRNA splicing variants (e.g., PKM2, HYAL4-v1), and circular RNAs (e.g., circITCH, circMYLK), which illustrates new possibilities to significantly improve the management of this pathology. This review represents the first detailed overview of the splicing process and its alterations in bladder cancer, and highlights opportunities for the development of novel diagnostic/prognostic biomarkers and their clinical potential for the treatment of this devastating cancer type. This article is categorized under: RNA Processing > Splicing Regulation/Alternative Splicing RNA in Disease and Development > RNA in Disease.

Perioperative systemic therapy in muscle invasive bladder cancer: Current standard method, biomarkers and emerging strategies

Bladder cancer ranks as the 10th most common cancer type globally, and muscle-invasive disease accounts for approximately 25% of newly diagnosed bladder cancers. Despite definitive treatment, 50% of patients with muscle-invasive bladder cancer (MIBC) develop metastasis within 2 years, leading to death. Perioperative systemic therapy is generally recommended to control local relapse or distant metastasis after surgical resection for patients with MIBC. Cisplatin-based neoadjuvant chemotherapy followed by radical cystectomy is the current standard treatment to improve oncologic control and survival outcomes. Adjuvant chemotherapy is recommended for patients with pathological T3-4 or positive lymph nodes after radical cystectomy if no neoadjuvant chemotherapy was given. Nonetheless, perioperative systemic therapy is not applied widely because of its toxicity, and less than 25% of patients receive cisplatin-based neoadjuvant chemotherapy. Therefore, the development of predictive biomarkers for neoadjuvant chemotherapy efficacy and alternative effective regimens for cisplatin-ineligible patients are important. Furthermore, recently, novel anticancer agents such as immune checkpoint inhibitors and antibody-drug conjugates have proven survival benefits in the metastatic setting, thereby expanding their therapeutic applications to the perioperative setting for non-metastatic MIBC. Herein, we discuss the current status and future perspectives of perioperative systemic strategies for MIBC.

Circulating Tumor Cells Predict Response of Neoadjuvant Chemotherapy in Patients with Bladder Cancer: A Preliminary Study

This study aimed to explore the existence of circulating tumor cells (CTCs) in patients with muscle-invasive bladder cancer (MIBC) and their predictive potential for response to neoadjuvant chemotherapy (NAC). From 33 blood samples of MIBC patients, CTCs were isolated by cell surface markers and enriched by the IsoFlux™ device, followed by morphological and immunofluorescent identification. CTCs were detected at baseline in all samples. Immunofluorescence confirmed the tumor origin. MIBC patients were stratified by NAC response into the disease control (DC) and progressive disease (PD) groups. In the DC group, the number of CTCs decreased significantly after four courses of NAC (p < 0.0001). CTC counts in 7.5 mL after four NAC cycles were highly correlated with postoperative pathological T stage (p < 0.0001). Our study demonstrated that CTCs might represent a valuable predictive marker for NAC response in MIBC. CTC detection in MIBC patients could allow early arrangement of radical cystectomy for NAC non-responders to prevent disease progression while receiving the NAC courses.

Approaches to Clinical Complete Response after Neoadjuvant Chemotherapy in Muscle-Invasive Bladder Cancer: Possibilities and Limitations

In the surgical oncology field, the change from a past radical surgery to an organ preserving surgery is a big trend. In muscle-invasive bladder cancer treatment, neoadjuvant chemotherapy (NAC) followed by radical cystectomy (RC) is the standard of care for muscle-invasive bladder cancer (MIBC) patients eligible for cisplatin. There is a growing interest in bladder preserving strategies after NAC because good oncologic outcome has been reported for pathologic complete response (pCR) patients after NAC, and many studies have continued to discuss whether bladder preservation treatment is possible for these patients. However, in actual clinical practice, decision-making should be determined according to clinical staging and there is a gap that cannot be ignored between clinical complete response (cCR) and pCR. Currently, there is a lack in a uniform approach to post-NAC restaging of MIBC and a standardized cCR definition. In this review, we clarify the gap between cCR and pCR at the current situation and focus on emerging strategies in bladder preservation in selected patients with MIBC who achieve cCR following NAC.

Urothelial Carcinoma: Update on Staging and Reporting, and Pathologic Changes Following Neoadjuvant Chemotherapies

Staging and reporting of cancers of the urinary tract have undergone major changes in the past decade to meet the needs for improved patient management. Substantial progress has been made. There, however, remain issues that require further clarity, including the substaging of pT1 tumors, grading and reporting of tumors with grade heterogeneity, and following NAC. Multi-institutional collaborative studies with prospective data will further inform the accurate diagnosis, staging, and reporting of these tumors, and in conjunction with genomic data will ultimately contribute to precision and personalized patient management.

Quantitative Assessment of Tumor-Infiltrating Lymphocytes Using Machine Learning Predicts Survival in Muscle-Invasive Bladder Cancer

(1) Purpose: Although assessment of tumor-infiltrating lymphocytes (TILs) has been acknowledged to have important predictive prognostic value in muscle-invasive bladder cancer (MIBC), it is limited by inter- and intra-observer variability, hampering widespread clinical application. We aimed to evaluate the prognostic value of quantitative TILs score based on a machine learning (ML) algorithm to identify MIBC patients who might benefit from immunotherapy or the de-escalation of therapy. (2) Methods: We constructed an artificial neural network classifier for tumor cells, lymphocytes, stromal cells, and “ignore” cells from hematoxylin-and-eosin-stained slide images using the QuPath open source software. We defined four unique TILs variables based on ML to analyze TILs measurements. Pathological slide images from 133 MIBC patients were retrospectively collected as the discovery set to determine the optimal association of ML-read TILs variables with patient survival outcomes. For validation, we evaluated an independent external validation set consisting of 247 MIBC patients. (3) Results: We found that all four TILs variables had significant prognostic associations with survival outcomes in MIBC patients (p < 0.001 for all comparisons), with higher TILs score being associated with better prognosis. Univariate and multivariate Cox regression analyses demonstrated that electronic TILs (eTILs) variables were independently associated with overall survival after adjustment for clinicopathological factors including age, sex, and pathological stage (p < 0.001 for all analyses). Results analyzed in different subgroups showed that the eTILs variable was a strong prognostic factor that was not redundant with pre-existing clinicopathological features (p < 0.05 for all analyses). (4) Conclusion: ML-driven cell classifier-defined TILs variables were robust and independent prognostic factors in two independent cohorts of MIBC patients. eTILs have the potential to identify a subset of high-risk stage II or stage III-IV MIBC patients who might benefit from adjuvant immunotherapy.

Diffusion-weighted MRI to determine response and long-term clinical outcomes in muscle-invasive bladder cancer following neoadjuvant chemotherapy

Objective

This study aims to determine local treatment response and long-term survival outcomes in patients with localised muscle-invasive bladder cancer (MIBC) patients receiving neoadjuvant chemotherapy (NAC) using diffusion-weighted MRI (DWI) and apparent diffusion coefficient (ADC) analysis.

Methods

Patients with T2-T4aN0-3M0 bladder cancer suitable for NAC were recruited prospectively. DWI was performed prior to NAC and was repeated following NAC completion. Conventional response assessment was performed with cystoscopy and tumour site biopsy. Response was dichotomised into response (

Results

Forty-eight patients (96 DWI) were evaluated. NAC response was associated with significant increase in mean ΔADC and %ΔADC compared to poor response (ΔADCall 0.32×10-3 versus 0.11×10-3 mm2/s; p=0.009, and %ΔADCall 21.70% versus 8.23%; p=0.013). Highest specificity predicting response was seen at 75th percentile ADC (AUC, 0.8; p=0.01). Sensitivity, specificity, positive predictive power, and negative predictive power of %ΔADCb100 75th percentile was 73.7%, 90.0%, 96.6%, and 52.9%, respectively. %ΔADCb100 75th percentile >15.5% was associated with significant improvement in OS (HR, 0.40; 95% CI, 0.19-0.86; p=0.0179), bCSS (HR, 0.26; 95% CI, 0.08-0.82; p=0.0214), PFS (HR, 0.16; 95% CI, 0.05-0.48; p=0.0012), and time to cystectomy (HR, 0.19; 95% CI, 0.07-0.47; p=0.0004).

Conclusions

Quantitative ADC analysis can successfully identify NAC response and improved long-term clinical outcomes. Multi-centre validation to assess reproducibility and repeatability is required before testing within clinical trials to inform MIBC treatment decision making.

Advances in knowledge

We successfully demonstrated that measured change in DWI can successfully identify NAC response and improved long-term survival outcomes.

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Key Words

• MRI
• diffusion weighted magnetic resonance imaging (DWI)
• imaging biomakers
• muscle invasive bladder cancer (MIBC)
• neoadjuavant chemotherapy

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MESH Headings Collapse

Grants

• 28724 Cancer Research UK

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Affiliation(s)

Shaista Hafeez Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom Urology Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom Department of Radiotherapy, The Royal Marsden NHS Foundation Trust, London, United Kingdom
Mu Koh Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom Department of Diagnostic Radiology, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
Kelly Jones Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom Urology Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
Amir El Ghzal Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom Urology Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
James D’Arcy Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
Pardeep Kumar Urology Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
Vincent Khoo Urology Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom Department of Radiotherapy, The Royal Marsden NHS Foundation Trust, London, United Kingdom
Susan Lalondrelle Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom Department of Radiotherapy, The Royal Marsden NHS Foundation Trust, London, United Kingdom
Fiona McDonald Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom Department of Radiotherapy, The Royal Marsden NHS Foundation Trust, London, United Kingdom
Alan Thompson Urology Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
Erica Scurr Department of Diagnostic Radiology, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
Aslam Sohaib Department of Diagnostic Radiology, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
Robert Anthony Huddart Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom Urology Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom Department of Radiotherapy, The Royal Marsden NHS Foundation Trust, London, United Kingdom

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Systems Drug Design for Muscle Invasive Bladder Cancer and Advanced Bladder Cancer by Genome-Wide Microarray Data and Deep Learning Method with Drug Design Specifications

Bladder cancer is the 10th most common cancer worldwide. Due to the lack of understanding of the oncogenic mechanisms between muscle-invasive bladder cancer (MIBC) and advanced bladder cancer (ABC) and the limitations of current treatments, novel therapeutic approaches are urgently needed. In this study, we utilized the systems biology method via genome-wide microarray data to explore the oncogenic mechanisms of MIBC and ABC to identify their respective drug targets for systems drug discovery. First, we constructed the candidate genome-wide genetic and epigenetic networks (GWGEN) through big data mining. Second, we applied the system identification and system order detection method to delete false positives in candidate GWGENs to obtain the real GWGENs of MIBC and ABC from their genome-wide microarray data. Third, we extracted the core GWGENs from the real GWGENs by selecting the significant proteins, genes and epigenetics via the principal network projection (PNP) method. Finally, we obtained the core signaling pathways from the corresponding core GWGEN through the annotations of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway to investigate the carcinogenic mechanisms of MIBC and ABC. Based on the carcinogenic mechanisms, we selected the significant drug targets NFKB1, LEF1 and MYC for MIBC, and LEF1, MYC, NOTCH1 and FOXO1 for ABC. To design molecular drug combinations for MIBC and ABC, we employed a deep neural network (DNN)-based drug-target interaction (DTI) model with drug specifications. The DNN-based DTI model was trained by drug-target interaction databases to predict the candidate drugs for MIBC and ABC, respectively. Subsequently, the drug design specifications based on regulation ability, sensitivity and toxicity were employed as filter criteria for screening the potential drug combinations of Embelin and Obatoclax for MIBC, and Obatoclax, Entinostat and Imiquimod for ABC from their candidate drugs. In conclusion, we not only investigated the oncogenic mechanisms of MIBC and ABC, but also provided promising therapeutic options for MIBC and ABC, respectively.

A novel signature to predict the neoadjuvant chemotherapy response of bladder carcinoma: Results from a territory multicenter real-world study

Background: Although neoadjuvant chemotherapy (NAC) has become the standard treatment option for muscle invasive bladder carcinoma (MIBC), its application is still limited because of the lack of biomarkers for NAC prediction.

Methods: We conducted a territory multicenter real-world study to summarize NAC practice in China and its associated clinicopathologic variables with NAC response. Then, we developed and validated a robust gene-based signature for accurate NAC prediction using weighted correlation network analysis (WGCNA), the least absolute shrinkage and selector operation (LASSO) algorithm, a multivariable binary logistic regression model, and immunohistochemistry (IHC).

Results: In total, we collected 69 consecutive MIBC patients treated with NAC from four clinical centers. The application of NAC in the real world was relatively safe, with only two grade Ⅳ and seven grade Ⅲ AEs and no treatment-related deaths being reported. Among these patients, 16 patients gave up surgery after NAC, leaving 53 patients for further analysis. We divided them into pathological response and non-response groups and found that there were more patients with a higher grade and stage in the non-response group. Patients with a pathological response could benefit from a significant overall survival (OS) improvement. In addition, univariate and multivariate logistic analyses indicated that tumor grade and clinical T stage were both independent factors for predicting NAC response. Importantly, we developed and validated a five-gene-based risk score for extremely high predictive accuracy for NAC response.

Conclusion: NAC was relatively safe and could significantly improve OS for MIBC patients in the real-world practice. Our five-gene-based risk score could guide personalized therapy and promote the application of NAC.

Neoadjuvant therapy for muscle-invasive bladder cancer: Current clinical scenario, future perspectives, and unsolved questions

Cisplatin-based neoadjuvant chemotherapy (NAC) followed by radical cystectomy is the standard treatment for patients with muscle-invasive bladder cancer (MIBC). However, the implementation of NAC is lower than desirable mainly due to its limited impact on overall survival, patients' comorbidities and the lack of predictive biomarkers to select those patients most likely to benefit from NAC. In the last decade, improved molecular MIBC characterisation, the identification of potential predictive and prognostic biomarkers as well as the incorporation of new effective therapies with a better toxicity profile, such as immunotherapy, has changed the treatment paradigm for MIBC. Therefore, the main goal for the near future is to introduce these clinical and translational advances into routine clinical practice to personalise treatment for each patient and increase the opportunity to implement bladder preservation strategies. The present review focuses on the current status of NAC in MIBC, unsolved questions and future therapeutic approaches.

A Necroptosis-Related lncRNA to Develop a Signature to Predict the Outcome, Immune Landscape, and Chemotherapeutic Responses in Bladder Urothelial Carcinoma

Objective

Many studies have drawn their attention to the immunotherapy of bladder urothelial carcinoma in terms of immunologic mechanisms of human body. These include immunogenicity of the tumor cells and involvement of long non-coding RNA (lncRNA). We constructed a necroptosis-related long noncoding RNA (nrlncRNA) risk factor model to predict BLCA outcomes and calculate correlations with chemosensitivity and immune infiltration.

Methods

Transcriptomic data from BLCA specimens were accessed from The Cancer Genome Atlas, and nrlncRNAs were identified by performing co-expression analysis. Univariate analysis was performed to identify differentially expressed nrlncRNA pairs. We constructed least absolute contraction and selector operation regression models and drew receiver operating characteristic curves for 1-, 3-, and 5-year survival rates. Akaike information criterion (AIC) values for survival over 1 year were determined as cutoff values in high- and low-risk subgroups. We reassessed the differences between subgroups in terms of survival, clinicopathological characteristics, chemotherapy efficacy, tumor-infiltrating immune cells, and markers of immunosuppression.

Results

We identified a total of 260 necroptosis-related lncRNA pairs, of which we incorporated 13 into the prognostic model. Areas under the curve of 1-, 3-, and 5- year survival time were 0.763, 0.836, and 0.842, respectively. We confirmed the excellent predictive performance of the risk model. Based on AIC values, we confirmed that the high-risk group was susceptible to unfavorable outcomes. The risk scores correlated with survival were age, clinical stage, grade, and tumor node metastases. The risk model was an independent predictor and demonstrated higher predictive power. The risk model can also be utilized to determine immune cell infiltration status, expression levels of immune checkpoint genes, and the sensitivity to cisplatin, doxorubicin, and methotrexate.

Conclusion

We constructed a novel necroptosis-related signature that predicts BLCA outcomes and performs satisfactorily in the immune landscape and chemotherapeutic responses.

Muscle-invasive bladder cancer: pretreatment prediction of response to neoadjuvant chemotherapy with diffusion-weighted MR imaging

PURPOSE

To investigate the usefulness of diffusion-weighted MR imaging with ADC value and histogram analysis of ADC in the prediction of response to neoadjuvant chemotherapy (NAC) in patients with muscle-invasive bladder cancer (MIBC).

METHODS

Fifty-eight consecutive patients with clinical T2-4aN0M0 MIBC who underwent MRI before and after NAC were enrolled in the prospective study. The evaluation of response to NAC was based on the pathologic T (pT) stage after surgery. Patients with non-muscle-invasive residual cancer (pTa, pTis, pT1) were defined as responders, while those with muscle-invasive residual cancer (≥ pT2) were defined as non-responders. The ADC value measured from a single-section region of interest and ADC histogram parameters derived from whole-tumor volume of interest in responder and non-responder were compared using the Mann-Whitney U test or independent samples t test. ROC curve analysis was used to evaluate the diagnostic performance of ADC value and ADC histogram parameters in predicting the response to NAC.

RESULTS

The pretreatment ADC value of responders ([1.33 (± 0.21)] × 10^-3mm²/s) was significantly higher than that of non-responders ([1.09 (± 0.08)] × 10^-3mm²/s) (P < .001). Most of the pretreatment ADC histogram parameters (Mean, 10th, 25th, 50th, 75th, and 90th percentiles) of responders were significantly higher than that of non-responders (P < .001). The AUC was highest for the pretreatment ADC value (0.88; 95% confidence interval: 0.77, 0.95; P < .001).

CONCLUSION

Diffusion-weighted MR imaging with ADC value and histogram analysis of ADC are useful to predict NAC response in patients with MIBC.

An immune-related lncRNA model for predicting prognosis, immune landscape and chemotherapeutic response in bladder cancer

Long noncoding RNAs (lncRNAs) participate in cancer immunity. We characterized the clinical significance of an immune-related lncRNA model and evaluated its association with immune infiltrations and chemosensitivity in bladder cancer. Transcriptome data of bladder cancer specimens were employed from The Cancer Genome Atlas. Dysregulated immune-related lncRNAs were screened via Pearson correlation and differential expression analyses, followed by recognition of lncRNA pairs. Then, a LASSO regression model was constructed, and receiver operator characteristic curves of one-, three- and five-year survival were established. Akaike information criterion (AIC) value of one-year survival was determined as the cutoff of high- and low-risk subgroups. The differences in survival, clinical features, immune cell infiltrations and chemosensitivity were compared between subgroups. Totally, 90 immune-related lncRNA pairs were identified, 15 of which were screened for constructing the prognostic model. The area under the curves of one-, three- and five-year survival were 0.806, 0.825 and 0.828, confirming the favorable predictive performance of this model. According to the AIC value, we clustered patients into high- and low-risk subgroups. High-risk score indicated unfavorable outcomes. The risk model was related to survival status, age, stage and TNM. Compared with conventional clinicopathological characteristics, the risk model displayed higher predictive efficacy and served as an independent predictor. Also, it could well characterize immune cell infiltration landscape and predict immune checkpoint expression and sensitivity to cisplatin and methotrexate. Collectively, the model conducted by paring immune-related lncRNAs regardless of expressions exhibits a favorable efficacy in predicting prognosis, immune landscape and chemotherapeutic response in bladder cancer.

Impact of preoperative systemic immune-inflammation Index on oncologic outcomes in bladder cancer patients treated with radical cystectomy

PURPOSE

To investigate the predictive and prognostic value of the preoperative systemic immune-inflammation index (SII) in patients undergoing radical cystectomy (RC) for clinically non-metastatic urothelial cancer of the bladder (UCB).

METHODS

Overall, 4,335 patients were included, and the cohort was stratified in two groups according to SII using an optimal cut-off determined by the Youden index. Uni- and multivariable logistic and Cox regression analyses were performed, and the discriminatory ability by adding SII to a reference model based on available clinicopathologic variables was assessed by area under receiver operating characteristics curves (AUC) and concordance-indices. The additional clinical net-benefit was assessed using decision curve analysis (DCA).

RESULTS

High SII was observed in 1879 (43%) patients. On multivariable preoperative logistic regression, high SII was associated with lymph node involvement (LNI; P = 0.004), pT3/4 disease (P <0.001), and non-organ confined disease (NOCD; P <0.001) with improvement of AUCs for predicting LNI (P = 0.01) and pT3/4 disease (P = 0.01). On multivariable Cox regression including preoperative available clinicopathologic values, high SII was associated with recurrence-free survival (P = 0.028), cancer-specific survival (P = 0.005), and overall survival (P = 0.006), without improvement of concordance-indices. On DCAs, the inclusion of SII did not meaningfully improve the net-benefit for clinical decision-making in all models.

CONCLUSION

High preoperative SII is independently associated with pathologic features of aggressive disease and worse survival outcomes. However, it did not improve the discriminatory margin of a prediction model beyond established clinicopathologic features and failed to add clinical benefit for decision making. The implementation of SII as a part of a panel of biomarkers in future studies might improve decision-making.

Predictive models of response to neoadjuvant chemotherapy in muscle-invasive bladder cancer using nuclear morphology and tissue architecture

Characterizing likelihood of response to neoadjuvant chemotherapy (NAC) in muscle-invasive bladder cancer (MIBC) is an important yet unmet challenge. In this study, a machine-learning framework is developed using imaging of biopsy pathology specimens to generate models of likelihood of NAC response. Developed using cross-validation (evaluable N = 66) and an independent validation cohort (evaluable N = 56), our models achieve promising results (65%-73% accuracy). Interestingly, one model-using features derived from hematoxylin and eosin (H&E)-stained tissues in conjunction with clinico-demographic features-is able to stratify the cohort into likely responders in cross-validation and the validation cohort (response rate of 65% for predicted responder compared with the 41% baseline response rate in the validation cohort). The results suggest that computational approaches applied to routine pathology specimens of MIBC can capture differences between responders and non-responders to NAC and should therefore be considered in the future design of precision oncology for MIBC.

Histological Variants of Urothelial Carcinoma Predict No Response to Neoadjuvant Chemotherapy

BACKGROUND

Platinum-based neoadjuvant chemotherapy (NAC) in muscle-invasive urothelial bladder cancer (MIBC) has been adopted as a standard of care related to better survival outcomes. However, there is a considerable number of patients who do not respond, experiencing toxicity and delay in the surgical treatment. Our aim is to find biomarkers of response that could be easily adopted in the clinical practice.

METHODS

Between January 2009 and July 2016, 52 patients with MIBC were submitted to radical cystectomy after NAC. A tissue microarray containing 25 cases, who met the inclusion criteria was built for immunohistochemical analysis of Cytokeratins 5/6, 7, and 20, GATA3, Her2, EGFR, p63, p53, Carbonic-anhydrase IX (CAIX), MLH1, MSH2, MSH6, and PMS2. The surgery was performed in a mean time of 58.7 (± 21) days after the end of the NAC. Fisher's exact test was used to analyze the relationship between response (≤pT1) and histopathological and immunohistochemical results and Kaplan-Meier curves were designed for survival analysis.

RESULTS

Ten (40.0%) patients presented response to NAC. Histological variants of the urothelial carcinoma characterized by squamous, sarcomatous/rhabdoid, plasmacytoid, and micropapillary was present in 36.0% and none responded to NAC (P = .002). CAIX was expressed by 53.3% and none responded to NAC (P= .005). Lymph-node metastasis, divergent differentiation, and expression of cytokeratin 5/6 were related to short cancer specific survival.

CONCLUSION

Histological variants and CAIX immune-expression are biomarkers of nonresponse to NAC of MIBC, and might be easily used in the clinical practice to select patients to be submitted to surgery upfront.

[French ccAFU guidelines - update 2020-2022: bladder cancer]

OBJECTIVE

- To update French guidelines for the management of bladder cancer specifically non-muscle invasive (NMIBC) and muscle-invasive bladder cancers (MIBC).

METHODS

- A Medline search was achieved between 2018 and 2020, notably regarding diagnosis, options of treatment and follow-up of bladder cancer, to evaluate different references with levels of evidence.

RESULTS

- Diagnosis of NMIBC (Ta, T1, CIS) is based on a complete deep resection of the tumor. The use of fluorescence and a second-look indication are essential to improve initial diagnosis. Risks of both recurrence and progression can be estimated using the EORTC score. A stratification of patients into low, intermediate and high risk groups is pivotal for recommending adjuvant treatment: instillation of chemotherapy (immediate post-operative, standard schedule) or intravesical BCG (standard schedule and maintenance). Cystectomy is recommended in BCG-refractory patients. Extension evaluation of MIBC is based on contrast-enhanced pelvic-abdominal and thoracic CT-scan. Multiparametric MRI can be an alternative. Cystectomy associated with extended lymph nodes dissection is considered the gold standard for non-metastatic MIBC. It should be preceded by cisplatin-based neoadjuvant chemotherapy in eligible patients. An orthotopic bladder substitution should be proposed to both male and female patients with no contraindication and in cases of negative frozen urethral samples; otherwise transileal ureterostomy is recommended as urinary diversion. All patients should be included in an Early Recovery After Surgery (ERAS) protocol. For metastatic MIBC, first-line chemotherapy using platin is recommended (GC or MVAC), when performans status (PS <1) and renal function (creatinine clearance >60 mL/min) allow it (only in 50% of cases). In second line treatment, immunotherapy with pembrolizumab demonstrated a significant improvement in overall survival.

CONCLUSION

- These updated French guidelines will contribute to increase the level of urological care for the diagnosis and treatment of patients diagnosed with NMIBC and MIBC.

Impact of the preoperative modified glasgow prognostic score on disease outcome after radical cystectomy for urothelial carcinoma of the bladder

BACKGROUND

To investigate the predictive and prognostic value of the preoperative modified Glasgow Prognostic Score (mGPS) in patients with urothelial carcinoma of the bladder (UCB) treated with radical cystectomy (RC).

METHODS

We conducted a retrospective analysis of an established multicenter database consisting of 4,335 patients who were treated with RC +/- adjuvant chemotherapy for UCB between 1979 and 2012. The mGPS of each patient was calculated on the basis of preoperative serum C-reactive protein and albumin. Uni- and multivariable logistic and Cox regression analyses were performed. The discriminatory ability of the models was assessed by calculating the area under receiver operating characteristics curves (AUC) and concordance-indices (C-Index). The additional clinical net-benefit was assessed using the decision curve analysis (DCA).

RESULTS

A mGPS of 0, 1, and 2 was observed in 3,158 (72.8%), 1,020 (23.5%), and 157 (3.6%) patients, respectively. On multivariable logistic regression analyses, mGPS of 1 or 2 were associated with an increased risk of pT3/4 disease at RC (OR 1.25, p=0.004 and OR 2.58, p<0.001, respectively) and/or lymph node metastasis (OR 1.7, p<0.001 and OR 3.9, p<0.001, respectively). Addition of the mGPS to a predictive model based on preoperatively available variables improved its accuracy for prediction of lymph node metastasis (change of AUC +3.7%, p<0.001). On multivariable Cox regression analyses, mGPS of 1 or 2 remained associated with worse recurrence-free survival (HR 1.14, p=0.03 and HR 1.89 p<0.001, respectively), cancer-specific survival (HR 1.16, p=0.032 and HR 2.1, p<0.001, respectively) and overall survival (HR 1.5, p=0.007 and HR 1.92 p<0.001, respectively) compared to mGPS of 0. The additional discriminatory ability of the mGPS for prognosis of survival outcomes in separate models that included either established pre- or postoperative variables did not improve the C-Index by a prognostically relevant degree (change of C-Index <2% for all models). On DCA, the inclusion of the mGPS did not meaningfully improve the net-benefit for clinical decision-making regarding survival outcomes.

CONCLUSIONS

We confirmed that an elevated mGPS is an independent risk factor for non-organ confined disease and poor survival outcomes in patients with UCB undergoing RC. However, the mGPS showed little value in improving the discriminatory ability of predictive and prognostic models that relied on either pre- or postoperative clinicopathological variables. The discriminatory ability of this biomarker in the age of immunotherapy warrants further evaluation.

A panel of systemic inflammatory response biomarkers for outcome prediction in patients treated with radical cystectomy for urothelial carcinoma

Objectives

To determine the predictive and prognostic value of a panel of systemic inflammatory response (SIR) biomarkers relative to established clinicopathological variables in order to improve patient selection and facilitate more efficient delivery of peri‐operative systemic therapy.

Materials and Methods

The preoperative serum levels of a panel of SIR biomarkers, including albumin–globulin ratio, neutrophil–lymphocyte ratio, De Ritis ratio, monocyte–lymphocyte ratio and modified Glasgow prognostic score were assessed in 4199 patients treated with radical cystectomy for clinically non‐metastatic urothelial carcinoma of the bladder. Patients were randomly divided into a training and a testing cohort. A machine‐learning‐based variable selection approach (least absolute shrinkage and selection operator regression) was used for the fitting of several multivariable predictive and prognostic models. The outcomes of interest included prediction of upstaging to carcinoma invading bladder muscle (MIBC), lymph node involvement, pT3/4 disease, cancer‐specific survival (CSS) and recurrence‐free survival (RFS). The discriminatory ability of each model was either quantified by area under the receiver‐operating curves or by the C‐index. After validation and calibration of each model, a nomogram was created and decision‐curve analysis was used to evaluate the clinical net benefit.

Results

For all outcome variables, at least one SIR biomarker was selected by the machine‐learning process to be of high discriminative power during the fitting of the models. In the testing cohort, model performance evaluation for preoperative prediction of lymph node metastasis, ≥pT3 disease and upstaging to MIBC showed a 200‐fold bootstrap‐corrected area under the curve of 67.3%, 73% and 65.8%, respectively. For postoperative prognosis of CSS and RFS, a 200‐fold bootstrap corrected C‐index of 73.3% and 72.2%, respectively, was found. However, even the most predictive combinations of SIR biomarkers only marginally increased the discriminative ability of the respective model in comparison to established clinicopathological variables.

Conclusion

While our machine‐learning approach for fitting of the models with the highest discriminative ability incorporated several previously validated SIR biomarkers, these failed to improve the discriminative ability of the models to a clinically meaningful degree. While the prognostic and predictive value of such cheap and readily available biomarkers warrants further evaluation in the age of immunotherapy, additional novel biomarkers are still needed to improve risk stratification.

HCPT-peptide prodrug with tumor microenvironment -responsive morphology transformable characteristic for boosted bladder tumor chemotherapy

As a common method for postoperative adjuvant treatments of bladder tumor, chemotherapy encounters low tumor targeting, short tumor retention time and bad bioavailability in clinical applications, which result in unsatisfactory high chemotherapeutical doses, frequent administration and subsequent severe side effects. Herein, we innovatively introduced the enzyme-assisted assembly to construct a bladder tumor-specific transformable peptide prodrug (i.e. HCPT-FF-GFLG-EEYSA). The prodrug targeted bladder tumor through the specific binding capacity of YSA to EphA2 and underwent on-demand structural transformation intracellularly from micelles to fibrils catalyzed by cathepsin B (CtsB), of which EphA2 and CtsB are overexpressed on the outer membrane and in cytoplasm of bladder tumor cells, respectively. Comparing with hydroxycamptothecin (HCPT), the prodrug can prolong the drug retention time and release the active drug in a sustained manner, which in turn decrease the administration frequencies of chemotherapeutics and reduce the side toxicities, etc. This strategy provides an alternative for bladder tumor chemotherapeutics and shows great potential to inhibit the relapse of postoperative tumors.

The impact of histological variants on outcomes after open radical cystectomy for muscle-invasive urothelial bladder cancer: results from a single tertiary referral centre

OBJECTIVES

To evaluate the impact of histological variants on oncological outcomes of patients with muscle-invasive bladder cancer treated with open radical cystectomy and furthermore to determine any association between survival and each histotype of bladder cancer.

MATERIALS AND METHODS

Data from 525 consecutive patients with muscle-invasive bladder cancer treated with radical cystectomy between January 2008 and May 2019 were collected retrospectively. The Kaplan-Meier curves and multivariable analysis addressed the role of histological variants in recurrence, cancer-specific and overall mortality between all subgroups.

RESULTS

Of 525 patients, 131 (25.0%) showed a histological variant at radical cystectomy. With a median follow-up of 31 months, 209 (39.8%) recurrences, 184 (35.0%) cancer-related deaths and 260 (49.5%) overall deaths were reported. The presence of histological variant was associated with advanced tumour stage, the presence of concomitant carcinoma in situ, lymph node metastasis, lymphovascular invasion and positive surgical margins compared to pure urothelial bladder cancer (all p values < .008) and resulted as an independent risk factor for cancer-specific mortality (p = 0.001). Patients with a histological variant were at significantly higher risk for recurrence, cancer-specific mortality and overall mortality (all p values ≤ .001). Micropapillary, sarcomatoid or small cell differentiation was associated with reduced survival.

CONCLUSION

The presence of histological variants at radical cystectomy seems to be weakly associated with reduced survival compared to pure urothelial bladder cancer paired for pathologic stage. The association of histological variants with advanced and biologically aggressive tumours suggests the need for attention on the overall management of these patients, in particular for micropapillary, sarcomatoid and small cell differentiation.

European Association of Urology Guidelines on Muscle-invasive and Metastatic Bladder Cancer: Summary of the 2020 Guidelines

CONTEXT

This overview presents the updated European Association of Urology (EAU) guidelines for muscle-invasive and metastatic bladder cancer (MMIBC).

OBJECTIVE

To provide practical evidence-based recommendations and consensus statements on the clinical management of MMIBC with a focus on diagnosis and treatment.

EVIDENCE ACQUISITION

A broad and comprehensive scoping exercise covering all areas of the MMIBC guideline has been performed annually since its 2017 publication (based on the 2016 guideline). Databases covered by the search included Medline, EMBASE, and the Cochrane Libraries, resulting in yearly guideline updates. A level of evidence and a grade of recommendation were assigned. Additionally, the results of a collaborative multistakeholder consensus project on advanced bladder cancer (BC) have been incorporated in the 2020 guidelines, addressing those areas where it is unlikely that prospective comparative studies will be conducted.

EVIDENCE SYNTHESIS

Variant histologies are increasingly reported in invasive BC and are relevant for treatment and prognosis. Staging is preferably done with (enhanced) computerised tomography scanning. Treatment decisions are still largely based on clinical factors. Radical cystectomy (RC) with lymph node dissection remains the recommended treatment in highest-risk non-muscle-invasive and muscle-invasive nonmetastatic BC, preceded by cisplatin-based neoadjuvant chemotherapy (NAC) for invasive tumours in "fit" patients. Selected men and women benefit from sexuality sparing RC, although this is not recommended as standard therapy. Open and robotic RC show comparable outcomes, provided the procedure is performed in experienced centres. For open RC 10, the minimum selected case load is 10 procedures per year. If bladder preservation is considered, chemoradiation is an alternative in well-selected patients without carcinoma in situ and after maximal resection. Adjuvant chemotherapy should be considered if no NAC was given. Perioperative immunotherapy can be offered in clinical trial setting. For fit metastatic patients, cisplatin-based chemotherapy remains the first choice. In cisplatin-ineligible patients, immunotherapy in Programmed Death Ligand 1 (PD-L1)-positive patients or carboplatin in PD-L1-negative patients is recommended. For second-line treatment in metastatic disease, pembrolizumab is recommended. Postchemotherapy surgery may prolong survival in responders. Quality of life should be monitored in all phases of treatment and follow-up. The extended version of the guidelines is available at the EAU website: https://uroweb.org/guideline/bladder-cancer-muscle-invasive-and-metastatic/.

CONCLUSIONS

This summary of the 2020 EAU MMIBC guideline provides updated information on the diagnosis and treatment of MMIBC for incorporation into clinical practice.

PATIENT SUMMARY

The European Association of Urology Muscle-invasive and Metastatic Bladder Cancer (MMIBC) Panel has released an updated version of their guideline, which contains information on histology, staging, prognostic factors, and treatment of MMIBC. The recommendations are based on the current literature (until the end of 2019), with emphasis on high-level data from randomised clinical trials and meta-analyses and on the findings of an international consensus meeting. Surgical removal of the bladder and bladder preservation are discussed, as well as the use of chemotherapy and immunotherapy in localised and metastatic disease.