Molecular Subtypes Are Associated With Clinical Benefit in Cisplatin-Treated Metastatic Urothelial Cancer Patients.

PURPOSE: Cisplatin-based combination chemotherapy (CHT) is standard of care in metastatic urothelial cancer (mUC); however, no predictive molecular biomarkers are available for clinical use. The aim of this study was to investigate the impact of molecular subtypes in relation to treatment response and survival in patients with mUC treated with first-line CHT. PATIENTS AND METHODS: Molecular subtype classification according to the Lund Taxonomy (LundTax) was performed by tumor transcriptomic profiling and immunostaining in a retrospective cohort. Molecular subtypes were investigated in relation to the primary end point overall response rate (ORR) and secondary end points progression-free survival (PFS) and overall survival (OS). Differential gene expression and association to treatment response were explored. RESULTS: Ninety-five patients with mUC were classified into urothelial-like (Uro, 43%), genomically unstable (GU, 26%), basal squamous-like (Ba/Sq, 20%), mesenchymal-like (Mes-like, 8%), and small cell neuroendocrine-like (Sc/NE, 3%) subtypes. Patients with Mes-like tumors had lower ORR (14%) compared with Uro (70%), GU (77%), Ba/Sq (75%), and Sc/NE (67%; odds ratio, 0.06 [95% CI, 0.01 to 0.54], P = .012). Furthermore, patients with Mes-like tumors had significantly shorter PFS (hazard ratio [HR], 5.18 [95% CI, 2.28 to 11.76], P < .001) and OS (HR, 3.19 [95% CI, 1.45 to 7.03], P = .004). Patients with Uro and GU showed the longest survival. In responders, an enrichment of downregulated stromal- and immune-related genes was seen. Downregulation of interferon-induced transmembrane protein 2 was associated with increased ORR and improved OS. CONCLUSION: This study identifies different CHT responses by LundTax molecular subtypes in patients with mUC, where the Mes-like subtype was associated with lower response rate and shorter survival.

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.

Restoring tumor immunogenicity with dendritic cell reprogramming.

Decreased antigen presentation contributes to the ability of cancer cells to evade the immune system. We used the minimal gene regulatory network of type 1 conventional dendritic cells (cDC1) to reprogram cancer cells into professional antigen-presenting cells (tumor-APCs). Enforced expression of the transcription factors PU.1, IRF8, and BATF3 (PIB) was sufficient to induce the cDC1 phenotype in 36 cell lines derived from human and mouse hematological and solid tumors. Within 9 days of reprogramming, tumor-APCs acquired transcriptional and epigenetic programs associated with cDC1 cells. Reprogramming restored the expression of antigen presentation complexes and costimulatory molecules on the surfaces of tumor cells, allowing the presentation of endogenous tumor antigens on MHC-I and facilitating targeted killing by CD8+ T cells. Functionally, tumor-APCs engulfed and processed proteins and dead cells, secreted inflammatory cytokines, and cross-presented antigens to naïve CD8+ T cells. Human primary tumor cells could also be reprogrammed to increase their capability to present antigen and to activate patient-specific tumor-infiltrating lymphocytes. In addition to acquiring improved antigen presentation, tumor-APCs had impaired tumorigenicity in vitro and in vivo. Injection of in vitro generated melanoma-derived tumor-APCs into subcutaneous melanoma tumors delayed tumor growth and increased survival in mice. Antitumor immunity elicited by tumor-APCs was synergistic with immune checkpoint inhibitors. Our approach serves as a platform for the development of immunotherapies that endow cancer cells with the capability to process and present endogenous tumor antigens.

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.

What is a Bladder Cancer Molecular Subtype?

BACKGROUND: Several molecular classification systems for bladder cancer have been proposed, but due to differences on how to define molecular subtypes, controversies and misunderstandings have arisen. OBJECTIVE: To discuss different aspects of the molecular classification of bladder cancer and to point to the consequences of using different conceptual approaches. To question some underlying assumptions when defining molecular subtypes. METHODS: To critically reflect on some of the principles and methods used when defining molecular subtypes. RESULTS: Depending on underlying assumptions and aims for the definitions of subtypes, different types of molecular subtypes will be arrived at. CONCLUSION: The underlying assumptions and their consequences must be better clarified when defining molecular subtypes.

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.

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.

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.

Analysis of fusion transcripts indicates widespread deregulation of snoRNAs and their host genes in breast cancer.

Genomic rearrangements in cancer can join the sequences of two separate genes. Studies of such gene fusion events have mainly focused on identification of fusion proteins from the chimeric transcripts. We have previously investigated how fusions instead can affect the expression of intronic microRNA (miRNA) genes that are encoded within fusion gene partners. Here, we extend our analysis to small nucleolar RNAs (snoRNAs) that also are embedded within protein-coding or noncoding host genes. We found that snoRNA hosts are selectively enriched in fusion transcripts, like miRNA host genes, and that this enrichment is associated with all snoRNA classes. These structural changes may have functional consequences for the cell; proteins involved in the protein translation machinery are overrepresented among snoRNA host genes, a gene architecture assumed to be needed for closely coordinated expression of snoRNAs and host proteins. Our data indicate that this structure is frequently disrupted in cancer. We furthermore observed that snoRNA genes involved in fusions tend to associate with stronger promoters than the natural host, suggesting a mechanism that selects for snoRNA overexpression. In summary, we highlight a previously unexplored frequent structural change in cancer that affects important components of cellular physiology.