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

Proteomic analysis of the urothelial cancer landscape

Urothelial bladder cancer (UC) has a wide tumor biological spectrum with challenging prognostic stratification and relevant therapy-associated morbidity. Most molecular classifications relate only indirectly to the therapeutically relevant protein level. We improve the pre-analytics of clinical samples for proteome analyses and characterize a cohort of 434 samples with 242 tumors and 192 paired normal mucosae covering the full range of UC. We evaluate sample-wise tumor specificity and rank biomarkers by target relevance. We identify robust proteomic subtypes with prognostic information independent from histopathological groups. In silico drug prediction suggests efficacy of several compounds hitherto not in clinical use. Both in silico and in vitro data indicate predictive value of the proteomic clusters for these drugs. We underline that proteomics is relevant for personalized oncology and provide abundance and tumor specificity data for a large part of the UC proteome ( www.cancerproteins.org ).

Molecular Subtypes of Bladder Cancer: Component Signatures and Potential Value in Clinical Decision-making

Bladder cancer may be classified into "molecular subtypes" based on gene expression. These are associated with treatment response and patient outcomes. The gene expression signatures that define these subtypes are diverse, including signatures of epithelial differentiation, stromal involvement, cell cycle activity, and immune cell infiltration. Multiple different systems are described. While earlier studies considered molecular subtypes to be intrinsic properties of cancer, recent data have shown molecular subtypes change as tumors progress and evolve, and often differ between histologically distinct regions of a tumor. The data also indicate that some signatures that define molecular subtypes may be treated as independent continuous variables, rather than categorical subtypes, and these individual signatures may be more clinically informative. This review describes molecular subtypes of urothelial carcinoma, including histologic subtypes and tumors with divergent differentiation, and explores potential future uses in patient management.

International Society of Urological Pathology Consensus Conference on Current Issues in Bladder Cancer. Working Group 4: Molecular Subtypes of Bladder Cancer-Principles of Classification and Emerging Clinical Utility

Molecular subtyping has been a major focus of bladder cancer research over the past decade. Despite many promising associations with clinical outcomes and treatment response, its clinical impact has yet to be defined. As part of the 2022 International Society of Urological Pathology Conference on Bladder Cancer, we reviewed the current state of the science for bladder cancer molecular subtyping. Our review included several different subtyping systems. We derived the following 7 principles, which summarize progress and challenges of molecular subtyping: (1) bladder cancer has 3 major molecular subtypes: luminal, basal-squamous, and neuroendocrine; (2) signatures of the tumor microenvironment differ greatly among bladder cancers, particularly among luminal tumors; (3) luminal bladder cancers are biologically diverse, and much of this diversity results from differences in features unrelated to the tumor microenvironment, such as FGFR3 signaling and RB1 inactivation; (4) molecular subtype of bladder cancer associates with tumor stage and histomorphology; (5) many subtyping systems include idiosyncrasies, such as subtypes recognized by no other system; (6) there are broad fuzzy borders between molecular subtypes, and cases that fall on these fuzzy borders are often classified differently by different subtyping systems; and (7) when there are histomorphologically distinct regions within a single tumor, the molecular subtypes of these regions are often discordant. We reviewed several use cases for molecular subtyping, highlighting their promise as clinical biomarkers. Finally, we conclude that data are currently insufficient to support the routine use of molecular subtyping to guide bladder cancer management, an opinion shared with the majority of conference attendees. We also conclude that molecular subtype should not be considered an "intrinsic" property of a tumor but should instead be considered the result of a specific laboratory test, performed using a specific testing platform and classification algorithm, validated for a specific clinical application.

Feasibility and Impact of Immunohistochemistry-based Molecular Subtyping for Muscle-invasive Bladder Cancer in Patients Treated with Radiation-based Therapy

Background

Distinct molecular subtypes of muscle-invasive bladder cancer (MIBC) have been identified via gene expression profiling.

Objective

We investigated the feasibility of a simple immunohistochemistry (IHC)-based Lund subtyping method and the association of MIBC subtypes with oncological outcomes for patients after bladder-preserving radiation-based therapy.

Design setting and participants

Transurethral resected tumor tissues from 104 patients treated with radiation-based therapy were sampled on tissue microarray blocks.

Outcome measurements and statistical analysis

The expression of KRT5, GATA3, and p16 proteins was scored via digital image analysis. Hierarchical clustering was used to classify tumors as the basal subtype or one of two luminal subtypes: genomically unstable (GU) or urothelial-like (URO). Subtypes were evaluated for association with complete response (CR), recurrence-free survival (RFS), and overall survival (OS).

Results and limitations

The median OS was 43 mo (95% confidence interval 19-77) and median follow-up was 55 mo (interquartile range 39-75). Age and clinical stage had a significant impact on OS (p < 0.05). IHC-based subtype classification was feasible in most patients (89%). The subtype was basal in 23.6%, GU in 14.0%, URO in 31.2%, and unclassified in 31.2% of patients. No significant differences in CR, RFS, or OS were observed between the molecular subtypes. Limitations include the retrospective design and relatively small sample size.

Conclusions

IHC-based molecular MIBC subtyping using a three-antibody algorithm is feasible in most patients treated with radiation-based therapy. MIBC subtype was not associated with response or survival. Further prospective studies are warranted to confirm the lack of association between molecular subtype and survival in patients treated with trimodal therapy.

Patient summary

For patients with invasive bladder cancer treated with radiation-based therapy, we classified tumors into different subtypes using just three molecular stains. This method is cheaper and more widely available than the usual approach. However, we did not find an association between different cancer subtypes and survival.

Quantitative nuclear grading: an objective, artificial intelligence-facilitated foundation for grading noninvasive papillary urothelial carcinoma

In non-muscle invasive bladder cancer, grade drives important treatment and management decisions. However, grading is complex, qualitative, and has considerable inter-and intra-observer variability. Previous literature showed that nuclear features quantitatively differ between bladder cancer grades, but these studies were limited in size and scope. Here, we measure morphometric features relevant to grading criteria and build simplified classification models that objectively distinguish between grades of non-invasive papillary urothelial carcinoma (NPUC). We analyzed 516 low-grade and 125 high-grade 1.0 mm diameter image samples from a cohort of 371 NPUC cases. All images underwent WHO/ISUP 2004 consensus pathologist grading at our institution that was subsequently validated by expert genitourinary pathologists from two additional institutions. Automated software segmented tissue regions and measured nuclear features of size, shape, and mitotic rate for millions of nuclei. We then analyzed differences between grades and constructed classification models which had accuracies up to 88% and areas under the curve as high as 0.94. Variation in the nuclear area was the best univariate discriminator and was prioritized, along with the mitotic index, in the top-performing classifiers. Adding shape-related variables improved accuracy further. These findings indicate that nuclear morphometry and automated mitotic figure counts can be used to objectively differentiate between grades of NPUC. Future efforts will adapt the workflow to whole slides and tune grading thresholds to best reflect time to recurrence and progression. Defining these essential quantitative elements of grading has the potential to revolutionize pathologic assessment and provide a starting point from which to improve the prognostic utility of grade.

Progression-associated molecular changes in basal/squamous and sarcomatoid bladder carcinogenesis

The aggressive basal/squamous (Ba/Sq) bladder cancer (BLCA) subtype is often diagnosed at the muscle-invasive stage and can progress to the sarcomatoid variant. Identification of molecular changes occurring during progression from non-muscle-invasive BLCA (NMIBC) to Ba/Sq muscle-invasive BLCA (MIBC) is thus challenging in human disease. We used the N-butyl-N-(4-hydroxybutyl)-nitrosamine (BBN) mouse model of Ba/Sq MIBC to study longitudinally the molecular changes leading to the Ba/Sq phenotype and to the sarcomatoid variant using IHC and microdissection followed by RNA-seq at all stages of progression. A shift to the Ba/Sq phenotype started in early progression stages. Pathway analysis of gene clusters with coordinated expression changes revealed Shh signaling loss and a shift from fatty acid metabolism to glycolysis. An upregulated cluster, appearing early in carcinogenesis, showed relevance to human disease, identifying NMIBC patients at risk of progression. Similar to the human counterpart, sarcomatoid BBN tumors displayed a Ba/Sq phenotype and epithelial-mesenchymal transition (EMT) features. An EGFR/FGFR1 signaling switch occurred with sarcomatoid dedifferentiation and correlated with EMT. BLCA cell lines with high EMT were the most sensitive to FGFR1 knockout and resistant to EGFR knockout. Taken together, these findings provide insights into the underlying biology of Ba/Sq BLCA progression and sarcomatoid dedifferentiation with potential clinical implications. © 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.

Are We Ready to Implement Molecular Subtyping of Bladder Cancer in Clinical Practice? Part 2: Subtypes and Divergent Differentiation

Following several attempts to achieve a molecular stratification of bladder cancer (BC) over the last decade, a "consensus" classification has been recently developed to provide a common base for the molecular classification of bladder cancer (BC), encompassing a six-cluster scheme with distinct prognostic and predictive characteristics. In order to implement molecular subtyping (MS) as a risk stratification tool in routine practice, immunohistochemistry (IHC) has been explored as a readily accessible, relatively inexpensive, standardized surrogate method, achieving promising results in different clinical settings. The second part of this review deals with the pathological and clinical features of the molecular clusters, both in conventional and divergent urothelial carcinoma, with a focus on the role of IHC-based subtyping.

Are We Ready to Implement Molecular Subtyping of Bladder Cancer in Clinical Practice? Part 1: General Issues and Marker Expression

Bladder cancer (BC) is a heterogeneous disease with highly variable clinical and pathological features, and resulting in different outcomes. Such heterogeneity ensues from distinct pathogenetic mechanisms and may consistently affect treatment responses in single patients. Thus, over the last few years, several groups have developed molecular classification schemes for BC, mainly based on their mRNA expression profiles. A “consensus” classification has recently been proposed to combine the published systems, agreeing on a six-cluster scheme with distinct prognostic and predictive features. In order to implement molecular subtyping as a risk-stratification tool in routine practice, immunohistochemistry (IHC) has been explored as a readily accessible, relatively inexpensive, standardized surrogate method, achieving promising results in different clinical settings. The first part of this review deals with the steps resulting in the development of a molecular subtyping of BC, its prognostic and predictive implications, and the main features of immunohistochemical markers used as surrogates to stratify BC into pre-defined molecular clusters.

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.