Urodrill - a novel MRI-guided endoscopic biopsy technique to sample and molecularly classify muscle-invasive bladder cancer without fractionating the specimen during transurethral resection.

The current diagnostic pathway for patients with muscle-invasive bladder cancer (MIBC), which involves with computed tomography urography, cystoscopy, and transurethral resection of the bladder (TURB) to histologically confirm MIBC, delays definitive treatment. The Vesical Imaging-Reporting and Data System (VI-RADS) has been suggested for MIBC identification using magnetic resonance imaging (MRI), but a recent randomized trial reported misclassification in one-third of patients. We investigated a new endoscopic biopsy device (Urodrill) for histological confirmation of MIBC and assessment of molecular subtype by gene expression in patients with VI-RADS 4 and 5 lesions on MRI. In ten patients, Urodrill biopsies were guided by MR images to the muscle-invasive portion of the tumor via a flexible cystoscope under general anesthesia. During the same session, conventional TURB was subsequently performed. A Urodrill sample was successfully obtained in nine of ten patients. MIBC was verified in six of nine patients, and seven of nine samples contained detrusor muscle. In seven of eight patients for whom a Urodrill biopsy sample was subjected to RNA sequencing, single-sample molecular classification according to the Lund taxonomy was feasible. No complications related to the biopsy device occurred. A randomized trial comparing this new diagnostic pathway for patients with VI-RADS 4 and 5 lesions and the current standard (TURB) is warranted. Patient summary: We report on a novel biopsy device for patients with muscle-invasive bladder cancer that facilitates histology analysis and molecular characterization of tumor samples.

Tumor Biomarkers for Bacillus Calmette-Guérin Response: What We Get Is Not What We Want.

Studies to date on biomarkers predictive of response to bacillus Calmette-Guérin (BCG) treatment for non-muscle-invasive bladder cancer have only identified markers with prognostic potential. There is an urgent need for larger study cohorts and for control arms comprising BCG-untreated patients to identify biomarkers with true ability to predict BCG response in classifying this patient population.

The Lund taxonomy for bladder cancer classification - from gene expression clustering to cancer cell molecular phenotypes, and back again.

Treatment of bladder cancer patients depends on precise diagnosis. Molecular subtyping by gene expression profiling may contribute substantially to subclassification of bladder cancer. Several classification systems have been proposed. Most of these base their classification on whole biopsy features, and molecular subtypes are therefore often defined by a combination of features from the cancer cells as well as infiltrating noncancer cells. This makes the link to what is seen at the cancer cell level unclear. The aim of the Lund taxonomy (LundTax) has been to align gene expression-level classification with immunohistochemical classification to identify cancer cell phenotypes independent of infiltration and proliferation. A systematic approach was used in which gene expression clusters were validated and adjusted by immunohistochemistry using markers expressed only by the cancer cells. This review provides a rationale for defining molecular subtypes and a step-by-step description of the development of the LundTax with motivations for each modification and extension. As the cancer cell phenotype defined by gene expression profiling corresponds with the immunohistochemistry of cancer cells, the LundTax represents a harmonization of the gene expression and immunohistochemical levels. Furthermore, the classification system is independent of pathological stage and is, thus, applicable to all urothelial carcinomas. A unified classification system relevant for both the molecular biologist and pathologist will facilitate systematization of current treatment practices, as well as the development of new treatments. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

UROSCAN and UROSCANSEQ: a large-scale multicenter effort towards translation of molecular bladder cancer subtypes into clinical practice - from biobank to RNA-sequencing in real time.

BACKGROUND: Bladder cancer is molecularly one of the most heterogenous malignancies characterized by equally heterogenous clinical outcomes. Standard morphological assessment with pathology and added immunohistochemical analyses is unable to fully address the heterogeneity, but up to now treatment decisions have been made based on such information only. Bladder cancer molecular subtypes will likely provide means for a more personalized bladder cancer care. METHODS: To facilitate further development of bladder cancer molecular subtypes and clinical translation, the UROSCAN-biobank was initiated in 2013 to achieve systematic biobanking of preoperative blood and fresh frozen tumor tissue in a population-based setting. In a second phase, we established in 2018 a parallel logistic pipeline for molecular profiling by RNA-sequencing, to develop and validate clinical implementation of molecular subtyping and actionable molecular target identification in real-time. RESULTS: Until June 2021, 1825 individuals were included in the UROSCAN-biobank, of which 1650 (90%) had primary bladder cancer, 127 (7%) recurrent tumors, and 48 (3%) unknown tumor status. In 159 patients, multiple tumors were sampled, and metachronous tumors were collected in 83 patients. Between 2016 and 2020 the UROSCAN-biobanking included 1122/2999 (37%) of all primary bladder cancer patients in the Southern Healthcare Region. Until June 2021, the corresponding numbers subjected to RNA-sequencing and molecular subtyping was 605 (UROSCANSEQ), of which 52 (9%) samples were not sequenced due to inadequate RNA-quality (n = 47) or technical failure/lost sample (n = 5). CONCLUSIONS: The UROSCAN-biobanking and UROSCANSEQ-infrastructure for molecular subtyping by real-time RNA-sequencing represents, to our knowledge, the largest effort of evaluating population-wide molecular classification of bladder cancer.

Predictive value of molecular subtypes and APOBEC3G for adjuvant chemotherapy in urothelial bladder cancer.

OBJECTIVE: Although targeted approaches have become available in second- and third-line settings, platinum-based chemotherapy remains the standard first-line treatment for advanced muscle-invasive bladder cancer (MIBC). Therefore, the prediction of platinum resistance is of utmost clinical importance. METHODS: In this study, we established a routine compatible method for the molecular classification of MIBC samples according to various classification systems and applied this method to evaluate the impact of subtypes on survival after adjuvant chemotherapy. This retrospective study included 191 patients with advanced MIBC (pT≥3 or pN+) who underwent radical cystectomy, with or without adjuvant chemotherapy. A 48-gene panel and classifier rule set were established to determine molecular subtypes according to TCGA, MDA, LundTax, and Consensus classifications. Additionally, 12 single platinum-predictive candidate genes were assessed. The results were correlated with patients' clinicopathological and follow-up data and were validated using independent data sets. RESULTS: Our final evaluation of 159 patients demonstrated better survival in the luminal groups for those who received chemotherapy compared with those who did not. In contrast, no such differences were observed in basal subtypes. The use of chemotherapy was associated with better survival in patients with high APOBEC3G expression (p < 0.002). This association was confirmed using an independent data set of patients who received neoadjuvant platinum therapy. CONCLUSIONS: The proposed method robustly replicates the most commonly used transcriptome-based subtype classifications from paraffin-embedded tissue samples. The luminal, but not basal, molecular subtypes had the greatest benefit from adjuvant platinum therapy. We identified and validated APOBEC3G as a novel predictive marker for platinum-treated patients.

The Urothelial Transcriptomic Response to Interferon Gamma: Implications for Bladder Cancer Prognosis and Immunotherapy.

Interferon gamma (IFNγ) is central to the inflammatory immune response, such as that entrained by BCG immunotherapy for bladder cancer. However, immune-mediated tumour cell killing is subject to modulation by immunoinhibitory "checkpoint" receptors such as PD-L1. We investigated the effects of IFNγ on barrier-forming in vitro-differentiated normal human urothelium using mRNA-sequencing, and showed canonical upregulation of MHC class I/II and de novo expression of the T cell tropic CXCL9-11 chemokines. Normal urothelium constitutively expressed immunoinhibitory B7 family member VSIR (VISTA), while CD274 (PD-L1) expression was induced/upregulated by IFNγ. We generated a urothelial IFNγ response gene signature. When applied to the unsupervised clustering of non-muscle-invasive bladder cancers, the IFNγ-signature predicted longer recurrence-free survival. In muscle-invasive cancers, the IFNγ-signature split the basal/squamous consensus subtype, with significantly worse overall survival when weak or absent. This study offers novel insights into strategies to enhance immunotherapy via the IFNγ and VISTA/PD-L1 nexus.

The Lund Molecular Taxonomy Applied to Non-Muscle-Invasive Urothelial Carcinoma.

The precise classification of tumors into relevant molecular subtypes will facilitate both future research and optimal treatment. Here, the Lund Taxonomy system for molecular classification of urothelial carcinoma was applied to two large and independent cohorts of non-muscle-invasive tumors. Of 752 tumors classified, close to 100% were of the luminal subtypes, 95% urothelial-like (Uro; UroA, UroB, or UroC) and 5% genomically unstable. The obtained subtype structure organized the tumors into groups with specific and coherent gene mutation, genomic, and clinical profiles. The intrasubtype variability in the largest group of tumors, UroA, was caused by infiltration and proliferation, not considered as cancer cell type-defining properties. Within the UroA subtype, a HOXB/late cell-cycle gene expression polarity was found, strongly associated with FGFR3, STAG2, and TP53 mutations, as well as with chromosome 9 losses. Kaplan-Meier analyses identified the genomically unstable subtype as a progression high-risk group, also valid in the subgroup of T1 tumors. Almost all progression events occurred within 12 months in this subtype. Also, a general progression gene signature was derived that identifies high- and low-risk tumors. All findings were demonstrated in two independent cohorts. The Lund Taxonomy system is applicable to both non-muscle- and muscle-invasive tumors and may be a useful biological framework for translational studies.

Immunohistochemistry subtyping of urothelial carcinoma is feasible in the daily practice.

The preferred treatment of choice in muscle-invasive bladder cancer (MIBC) is usually transurethral resection followed by cystectomy, with neoadjuvant chemotherapy being a second option. As the treatment is associated with relevant side effects, a great effort is being made to improve the selection of patients, with molecular subtyping being one of the main strategies. Our aim was to develop an immunohistochemical algorithm for subtyping MIBCs. After a literature review, we have developed a simple algorithm to subtype MIBCs based on their morphology and three common antibodies: GATA3, CK5/6, and p16. We applied it to 113 muscle-invasive carcinomas. The positivity threshold for GATA3 and CK5/6 was 20% with at least moderate intensity, while p16 was 70% with moderate to intense nuclear and cytoplasmic staining. Cases GATA3 + CK5/6 - were considered luminal, while cases GATA3 - CK5/6 + were classified as nonluminal/basal squamous. Luminal p16 + cases were labeled as genomically unstable and luminal p16 - as Uro-like. Cases GATA3 + CK5/6 + with a predominantly basal pattern were labeled luminal, while diffuse cases were labeled nonluminal/basal squamous. All GATA3-CK5/6 - cases were considered nonluminal and were divided into mesenchymal-like or neuroendocrine, depending on the morphology. We were able to classify the 113 cases as: 82 (72.57%) were luminal, being 47 Uro-like (41.59%) and 35 (30.97%) genomically unstable; 31 (27.43%) were nonluminal, being 24 basal/squamous (21.24%), two (1.76%) mesenchymal-like, and five (4.42%) neuroendocrine like. We have achieved a feasible and cost-effective algorithm to subtype MIBCs from morphological features and the use of three common antibodies. Further studies in external cohorts are necessary to validate these results.

Patient-Derived Bladder Cancer Organoid Models in Tumor Biology and Drug Testing: A Systematic Review.

Bladder cancer is a common and highly heterogeneous malignancy with a relatively poor outcome. Patient-derived tumor organoid cultures have emerged as a preclinical model with improved biomimicity. However, the impact of the different methods being used in the composition and dynamics of the models remains unknown. This study aims to systematically review the literature regarding patient-derived organoid models for normal and cancer tissue of the bladder, and their current and potential future applications for tumor biology studies and drug testing. A PRISMA-compliant systematic review of the PubMED, Embase, Web of Sciences, and Scopus databases was performed. The results were analyzed based on the methodologies, comparison with primary tumors, functional analysis, and chemotherapy and immunotherapy testing. The literature search identified 536 articles, 24 of which met the inclusion criteria. Bladder cancer organoid models have been increasingly used for tumor biology studies and drug screening. Despite the heterogeneity between methods, organoids and primary tissues showed high genetic and phenotypic concordance. Organoid sensitivity to chemotherapy matched the response in patient-derived xenograft (PDX) models and predicted response based on clinical and mutation data. Advances in bioengineering technology, such as microfluidic devices, bioprinters, and imaging, are likely to further standardize and expand the use of organoids.

Immunohistochemical Assays for Bladder Cancer Molecular Subtyping: Optimizing Parsimony and Performance of Lund Taxonomy Classifiers.

Transcriptomic and proteomic profiling classify bladder cancers into luminal and basal molecular subtypes, with controversial prognostic and predictive associations. The complexity of published subtyping algorithms is a major impediment to understanding their biology and validating or refuting their clinical use. Here, we optimize and validate compact algorithms based on the Lund taxonomy, which separates luminal subtypes into urothelial-like (Uro) and genomically unstable (GU). We characterized immunohistochemical expression data from two muscle-invasive bladder cancer cohorts (n=193, n=76) and developed efficient decision tree subtyping models using 4-fold cross-validation. We demonstrated that a published algorithm using routine assays (GATA3, KRT5, p16) classified basal/luminal subtypes and basal/Uro/GU subtypes with 86%-95% and 67%-86% accuracies, respectively. KRT14 and RB1 are less frequently used in pathology practice but achieved the simplest, most accurate models for basal/luminal and basal/Uro/GU discrimination, with 93%-96% and 85%-86% accuracies, respectively. More complex models with up to eight antibodies performed no better than simpler two- or three-antibody models. We conclude that simple immunohistochemistry classifiers can accurately identify luminal (Uro, GU) and basal subtypes and are appealing options for clinical implementation.

Molecular Subtypes as a Basis for Stratified Use of Neoadjuvant Chemotherapy for Muscle-Invasive Bladder Cancer-A Narrative Review.

There are no established biomarkers to guide patient selection for neoadjuvant chemotherapy prior to radical cystectomy for muscle-invasive bladder cancer. Recent studies suggest that molecular subtype classification holds promise for predicting chemotherapy response and/or survival benefit in this setting. Here, we summarize and discuss the scientific literature examining transcriptomic or panel-based molecular subtyping applied to neoadjuvant chemotherapy-treated patient cohorts. We find that there is not sufficient evidence to conclude that the basal subtype of muscle-invasive bladder cancer responds well to chemotherapy, since only a minority of studies support this conclusion. More evidence indicates that luminal-like subtypes may have the most improved outcomes after neoadjuvant chemotherapy. There are also conflicting data concerning the association between biopsy stromal content and response. Subtypes indicative of high stromal infiltration responded well in some studies and poorly in others. Uncertainties when interpreting the current literature include a lack of reporting both response and survival outcomes and the inherent risk of bias in retrospective study designs. Taken together, available studies suggest a role for molecular subtyping in stratifying patients for receiving neoadjuvant chemotherapy. The precise classification system that best captures such a predictive effect, and the exact subtypes for which other treatment options are more beneficial remains to be established, preferably in prospective studies.

Molecular pathology of the non-luminal Ba/Sq-like and Sc/NE-like classes of urothelial tumours: An integrated immunohistochemical analysis.

Several groups have during past years produced molecular classification schemes for bladder cancer. Even though no consensus on how to define a subtype exists, one approach has been to base definitions on how tumours cluster according to their mRNA expression profiles. In many cases, obtained profiles, and thus class defining features, are affected by signals from non-tumour cells within the biopsy. To overcome this issue, we combined gene expression analyses with analyses of the actual tumour cells by extensive immunohistochemistry (IHC). By this approach we were able to define tumour cell phenotypes i.e., subtypes defined by features of the tumour cells only, and adjust mRNA-based algorithms accordingly. In the present investigation we address the non-luminal Basal/Squamous-like (Ba/Sq) and Small cell/Neuroendocrine-like (Sc/NE) categories of tumours defined by mRNA-based classification. We make use of IHC data for 15 proteins, all known to be instrumental for defining molecular subtypes of urothelial carcinoma. We show that the UroB type of tumours, frequently grouped together with Ba/Sq, are different from the Ba/Sq entity at several essential features and is a derivative of Urothelial-like tumours (Uro). We show that the Sc/NE tumours are similar to but represents extreme versions of Genomically Unstable (GU) tumours. We apply clustering to 423 cases representing all subtypes using IHC data for 14 proteins and show that the obtained grouping conforms well with the mRNA-based classification. This work describes in detail the molecular pathology of non-luminal RNA-based bladder cancer subtypes and highlight similarities/dissimilarities suggestive of origin.

Complete metabolic response with [18 F]fluorodeoxyglucose-positron emission tomography/computed tomography predicts survival following induction chemotherapy and radical cystectomy in clinically lymph node positive bladder cancer.

OBJECTIVE: To determine whether repeated [18 F]fluorodeoxyglucose-positron emission tomography/computed tomography (FDG-PET-CT) scans can predict increased cancer-specific survival (CSS) after induction chemotherapy followed by radical cystectomy (RC). PATIENTS AND METHODS: Between 2007 and 2018, 86 patients with clinically lymph node (LN)-positive bladder cancer (T1-T4, N1-N3, M0-M1a) were included and underwent a repeated FDG-PET-CT during cisplatin-based induction chemotherapy. The 71 patients that had a response to chemotherapy underwent RC. Response to chemotherapy was evaluated in LNs through repeated FDG-PET-CT and stratified as partial response or complete response using three different methods: maximum standardised uptake value (SUVmax ), adapted Deauville criteria, and total lesion glycolysis (TLG). Progression-free survival (PFS) and CSS were analysed for all three methods by Cox regression analysis. RESULTS: After a median follow-up of 40 months, 15 of the 71 patients who underwent RC had died from bladder cancer. Using SUVmax and the adapted Deauville criteria, multivariable Cox regression analyses adjusting for age, clinical tumour stage and LN stage showed that complete response was associated with increased PFS (hazard ratio [HR] 3.42, 95% confidence interval [CI] 1.20-9.77) and CSS (HR 3.30, 95% CI 1.02-10.65). Using TLG, a complete response was also associated with increased PFS (HR 5.17, 95% CI 1.90-14.04) and CSS (HR 6.32, 95% CI 2.06-19.41). CONCLUSIONS: Complete metabolic response with FDG-PET-CT predicts survival after induction chemotherapy followed by RC in patients with LN-positive bladder cancer and comprises a novel tool in evaluating response to chemotherapy before surgery. This strategy has the potential to tailor treatment in individual patients by identifying significant response to chemotherapy, which motivates the administration of a full course of induction chemotherapy with a higher threshold for suspending treatment due to toxicity and side-effects.

Diagnostic and prognostic implications of a three-antibody molecular subtyping algorithm for non-muscle invasive bladder cancer.

Intrinsic molecular subtypes may explain marked variation between bladder cancer patients in prognosis and response to therapy. Complex testing algorithms and little attention to more prevalent, early-stage (non-muscle invasive) bladder cancers (NMIBCs) have hindered implementation of subtyping in clinical practice. Here, using a three-antibody immunohistochemistry (IHC) algorithm, we identify the diagnostic and prognostic associations of well-validated proteomic features of basal and luminal subtypes in NMIBC. By IHC, we divided 481 NMIBCs into basal (GATA3- /KRT5+ ) and luminal (GATA3+ /KRT5 variable) subtypes. We further divided the luminal subtype into URO (p16 low), URO-KRT5+ (KRT5+ ), and genomically unstable (GU) (p16 high) subtypes. Expression thresholds were confirmed using unsupervised hierarchical clustering. Subtypes were correlated with pathology and outcomes. All NMIBC cases clustered into the basal/squamous (basal) or one of the three luminal (URO, URO-KRT5+ , and GU) subtypes. Although uncommon in this NMIBC cohort, basal tumors (3%, n = 16) had dramatically higher grade (100%, n = 16, odds ratio [OR] = 13, relative risk = 3.25) and stage, and rapid progression to muscle invasion (median progression-free survival = 35.4 months, p = 0.0001). URO, the most common subtype (46%, n = 220), showed rapid recurrence (median recurrence-free survival [RFS] = 11.5 months, p = 0.039) compared to its GU counterpart (29%, n = 137, median RFS = 16.9 months), even in patients who received intravesical immunotherapy (p = 0.049). URO-KRT5+ tumors (22%, n = 108) were typically low grade (66%, n = 71, OR = 3.7) and recurred slowly (median RFS = 38.7 months). Therefore, a simple immunohistochemical algorithm can identify clinically relevant molecular subtypes of NMIBC. In routine clinical practice, this three-antibody algorithm may help clarify diagnostic dilemmas and optimize surveillance and treatment strategies for patients.

A quantitative polymerase chain reaction based method for molecular subtype classification of urinary bladder cancer-Stromal gene expressions show higher prognostic values than intrinsic tumor genes.

Transcriptome-based molecular subtypes of muscle-invasive bladder cancer (MIBC) have been shown to be both prognostic and predictive, but are not used in routine clinical practice. We aimed to develop a feasible, reverse transcription quantitative polymerase chain reaction (RT-qPCR)-based method for molecular subtyping. First, we defined a 68-gene set covering tumor intrinsic (luminal, basal, squamous, neuronal, epithelial-to-mesenchymal, in situ carcinoma) and stromal (immune, extracellular matrix, p53-like) signatures. Then, classifier methods with this 68-gene panel were developed in silico and validated on public data sets with available subtype class information (MD Anderson [MDA], The Cancer Genome Atlas [TCGA], Lund, Consensus). Finally, expression of the selected 68 genes was determined in 104 frozen tissue samples of our MIBC cohort by RT-qPCR using the TaqMan Array Card platform and samples were classified by our newly developed classifiers. The prognostic value of each subtype classification system and molecular signature scores were assessed. We found that the reduced marker set combined with the developed classifiers were able to reproduce the TCGA II, MDA, Lund and Consensus subtype classification systems with an overlap of 79%, 76%, 69% and 64%, respectively. Importantly, we could successfully classify 96% (100/104) of our MIBC samples by using RT-qPCR. Neuronal and luminal subtypes and low stromal gene expressions were associated with poor survival. In conclusion, we developed a robust and feasible method for the molecular subtyping according to the TCGA II, MDA, Lund and Consensus classifications. Our results suggest that stromal signatures have a superior prognostic value compared to tumor intrinsic signatures and therefore underline the importance of tumor-stroma interaction during the progression of MIBC.

A comparison of rule-based and centroid single-sample multiclass predictors for transcriptomic classification.

MOTIVATION: Gene expression-based multiclass prediction, such as tumor subtyping, is a non-trivial bioinformatic problem. Most classifier methods operate by comparing expression levels relative to other samples. Methods that base predictions on the expression pattern within a sample have been proposed as an alternative. As these methods are invariant to the cohort composition and can be applied to a sample in isolation, they can collectively be termed single sample predictors (SSP). Such predictors could potentially be used for preprocessing-free classification of new samples and be built to function across different expression platforms where proper batch and dataset normalization is challenging. Here, we evaluate the behavior of several multiclass SSPs based on binary gene-pair rules (k-Top Scoring Pairs, Absolute Intrinsic Molecular Subtyping and a new Random Forest approach) and compare them to centroids built with centered or raw expression values, with the criteria that an optimal predictor should have high accuracy, overcome differences in tumor purity, be robust across expression platforms and provide an informative prediction output score. RESULTS: We found that gene-pair-based SSPs showed excellent performance on many expression-based classification tasks. The three methods differed in prediction score output, handling of tied scores and behavior in low purity samples. The k-Top Scoring Pairs and Random Forest approach both achieved high classification accuracy while providing an informative prediction score. Although gene-pair-based SSPs have been touted as being cross-platform compatible (through training on mixed platform data), out-of-the-box compatibility with a new dataset remains a potential issue that warrants cohort-to-cohort verification. AVAILABILITY AND IMPLEMENTATION: Our R package 'multiclassPairs' (https://cran.r-project.org/package=multiclassPairs) (https://doi.org/10.1093/bioinformatics/btab088) is freely available and enables easy training, prediction, and visualization using the gene-pair rule-based Random Forest SSP method and provides additional multiclass functionalities to the switchBox k-Top-Scoring Pairs package. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Different Responses to Neoadjuvant Chemotherapy in Urothelial Carcinoma Molecular Subtypes.

BACKGROUND: For muscle-invasive bladder cancer (MIBC), no tissue biomarkers are available for clinical use to predict response to neoadjuvant chemotherapy. OBJECTIVE: To investigate how molecular subtypes impact pathological response and survival in patients receiving preoperative cisplatin-based chemotherapy. DESIGN, SETTING, AND PARTICIPANTS: Classification of a retrospective cohort of 149 patients was performed by tumor transcriptomic profiling and immunostaining. A cohort treated with radical cystectomy alone and public data sets were used for comparison and external validation. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Complete pathological response in the cystectomy specimen (ypT0N0) and survival were compared in predefined molecular subtypes. Differential gene expression and chemotherapy response were explored beyond molecular subtypes. RESULTS AND LIMITATIONS: Patients with genomically unstable (GU) and urothelial-like (Uro) tumors had higher proportions of complete pathological response (16/31 [52%] and 17/54 [31%]), versus five out of 24 (21%) with the basal/squamous (Ba/Sq) subtype following neoadjuvant chemotherapy and radical cystectomy. Molecular subtype was independently associated with improved survival for patients with GU tumors (hazard ratio [HR] 0.29, 95% confidence interval [CI]: 0.11-0.79) and UroC tumors (HR 0.37, 95% CI: 0.14-0.94) compared with Ba/Sq tumors, adjusting for clinical stage. In addition, expression of the gene coding for osteopontin (SPP1) showed a subtype-dependent effect on chemotherapy response. CONCLUSIONS: Urothelial cancer of the luminal-like (GU and Uro) subtypes is more responsive to cisplatin-based neoadjuvant chemotherapy. A second-generation of subtype-specific biomarkers, for example, SPP1, may be a way forward to develop a more precision-based treatment approach for neoadjuvant chemotherapy in MIBC. PATIENT SUMMARY: This study shows that tumor classification by gene expression profiling and molecular subtyping can identify patients who are more likely to benefit from chemotherapy before radical cystectomy for muscle-invasive bladder cancer. Together with other markers for response, molecular subtypes could have a role in selective administration of such chemotherapy.

An integrated multi-omics analysis identifies prognostic molecular subtypes of non-muscle-invasive bladder cancer.

The molecular landscape in non-muscle-invasive bladder cancer (NMIBC) is characterized by large biological heterogeneity with variable clinical outcomes. Here, we perform an integrative multi-omics analysis of patients diagnosed with NMIBC (n = 834). Transcriptomic analysis identifies four classes (1, 2a, 2b and 3) reflecting tumor biology and disease aggressiveness. Both transcriptome-based subtyping and the level of chromosomal instability provide independent prognostic value beyond established prognostic clinicopathological parameters. High chromosomal instability, p53-pathway disruption and APOBEC-related mutations are significantly associated with transcriptomic class 2a and poor outcome. RNA-derived immune cell infiltration is associated with chromosomally unstable tumors and enriched in class 2b. Spatial proteomics analysis confirms the higher infiltration of class 2b tumors and demonstrates an association between higher immune cell infiltration and lower recurrence rates. Finally, the independent prognostic value of the transcriptomic classes is documented in 1228 validation samples using a single sample classification tool. The classifier provides a framework for biomarker discovery and for optimizing treatment and surveillance in next-generation clinical trials.