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.

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.

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.

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.

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.

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.

multiclassPairs: an R package to train multiclass pair-based classifier.

MOTIVATION: k-Top Scoring Pairs (kTSP) algorithms utilize in-sample gene expression feature pair rules for class prediction, and have demonstrated excellent performance and robustness. The available packages and tools primarily focus on binary prediction (i.e. two classes). However, many real-world classification problems e.g. tumor subtype prediction, are multiclass tasks. RESULTS: Here, we present multiclassPairs, an R package to train pair-based single sample classifiers for multiclass problems. multiclassPairs offers two main methods to build multiclass prediction models, either using a one-versus-rest kTSP scheme or through a novel pair-based Random Forest approach. The package also provides options for dealing with class imbalances, multiplatform training, missing features in test data and visualization of training and test results. AVAILABILITY AND IMPLEMENTATION: 'multiclassPairs' package is available on CRAN servers and GitHub: https://github.com/NourMarzouka/multiclassPairs. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Stage-stratified molecular profiling of non-muscle-invasive bladder cancer enhances biological, clinical, and therapeutic insight.

Understanding the molecular determinants that underpin the clinical heterogeneity of non-muscle-invasive bladder cancer (NMIBC) is essential for prognostication and therapy development. Stage T1 disease in particular presents a high risk of progression and requires improved understanding. We present a detailed multi-omics study containing gene expression, copy number, and mutational profiles that show relationships to immune infiltration, disease recurrence, and progression to muscle invasion. We compare expression and genomic subtypes derived from all NMIBCs with those derived from the individual disease stages Ta and T1. We show that sufficient molecular heterogeneity exists within the separate stages to allow subclassification and that this is more clinically meaningful for stage T1 disease than that derived from all NMIBCs. This provides improved biological understanding and identifies subtypes of T1 tumors that may benefit from chemo- or immunotherapy.

Recurring urothelial carcinomas show genomic rearrangements incompatible with a direct relationship.

We used the fact that patients with non-muscle invasive bladder tumors show local recurrences and multiple tumors to study re-initiation of tumor growth from the same urothelium. By extensive genomic analyses we show that tumors from the same patient are clonal. We show that gross genomic chromosomal aberrations may be detected in one tumor, only to be undetected in a recurrent tumor. By analyses of incompatible changes i.e., genomic alterations that cannot be reversed, we show that almost all tumors from a single patient may show such changes, thus the tumors cannot have originated from each other. As recurring tumors share both genomic alterations and driver gene mutations, these must have been present in the urothelium in periods with no tumor growth. We present a model that includes a growing and evolving field of urothelial cells that occasionally, and locally, produce bursts of cellular growth leading to overt tumors.

Molecular changes during progression from nonmuscle invasive to advanced urothelial carcinoma.

Molecular changes occurring during invasion and clinical progression of cancer are difficult to study longitudinally in patient-derived material. A unique feature of urothelial bladder cancer (UBC) is that patients frequently develop multiple nonmuscle invasive tumors, some of which may eventually progress to invade the muscle of the bladder wall. Here, we use a cohort of 73 patients that experienced a total of 357 UBC diagnoses to study the stability or change in detected molecular alterations during cancer progression. The tumors were subtyped by gene expression profiling and analyzed for hotspot mutations in FGFR3, PIK3CA and TERT, the most frequent early driver mutations in this tumor type. TP53 alterations, frequent in advanced UBC, were inferred from p53 staining pattern, and potential genomic alterations were inferred by gene expression patterns at regions harboring frequent copy number alterations. We show that early driver mutations were largely preserved in UBC recurrences. Changes in FGFR3, PIK3CA or TERT mutation status were not linked to changes in molecular subtype and aggressive behavior. Instead, changes into a more aggressive molecular subtype seem to be associated with p53 alterations. We analyze changes in gene expression from primary tumors, to recurrences and progression tumors, and identify two modes of progression: Patients for whom progression is preceded by or coincides with a radical subtype shift, and patients who progress without any systematic molecular changes. For the latter group of patients, progression may be either stochastic or depending on factors already present at primary tumor initiation.

A Consensus Molecular Classification of Muscle-invasive Bladder Cancer.

BACKGROUND: Muscle-invasive bladder cancer (MIBC) is a molecularly diverse disease with heterogeneous clinical outcomes. Several molecular classifications have been proposed, but the diversity of their subtype sets impedes their clinical application. OBJECTIVE: To achieve an international consensus on MIBC molecular subtypes that reconciles the published classification schemes. DESIGN, SETTING, AND PARTICIPANTS: We used 1750 MIBC transcriptomic profiles from 16 published datasets and two additional cohorts. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: We performed a network-based analysis of six independent MIBC classification systems to identify a consensus set of molecular classes. Association with survival was assessed using multivariable Cox models. RESULTS AND LIMITATIONS: We report the results of an international effort to reach a consensus on MIBC molecular subtypes. We identified a consensus set of six molecular classes: luminal papillary (24%), luminal nonspecified (8%), luminal unstable (15%), stroma-rich (15%), basal/squamous (35%), and neuroendocrine-like (3%). These consensus classes differ regarding underlying oncogenic mechanisms, infiltration by immune and stromal cells, and histological and clinical characteristics, including outcomes. We provide a single-sample classifier that assigns a consensus class label to a tumor sample's transcriptome. Limitations of the work are retrospective clinical data collection and a lack of complete information regarding patient treatment. CONCLUSIONS: This consensus system offers a robust framework that will enable testing and validation of predictive biomarkers in future prospective clinical trials. PATIENT SUMMARY: Bladder cancers are heterogeneous at the molecular level, and scientists have proposed several classifications into sets of molecular classes. While these classifications may be useful to stratify patients for prognosis or response to treatment, a consensus classification would facilitate the clinical use of molecular classes. Conducted by multidisciplinary expert teams in the field, this study proposes such a consensus and provides a tool for applying the consensus classification in the clinical setting.