Project description:Bladder cancer, one of the most prevalent malignancies worldwide, remains hard to classify due to a staggering molecular complexity. Despite a plethora of diagnostic tools and therapies, it is hard to outline the key steps leading up to the transition from high-risk non–muscle-invasive bladder cancer (NMIBC) to muscle-invasive bladder cancer (MIBC). Carcinogen-induced murine models can recapitulate urothelial carcinogenesis and natural anti-tumor immunity. Herein, we have developed and profiled a novel model of progressive NMIBC based on 10 weeks of OH-BBN exposure in hepatocyte growth factor/cyclin dependent kinase 4 (R24C) (Hgf-Cdk4R24C) mice. The profiling of the model was performed by histology grading, single cell transcriptomic and proteomic analysis, while the derivation of a tumorigenic cell line was validated and used to assess in vivo anti-tumor effects in response to immunotherapy. Established NMIBC was present in females at 10 weeks post OH-BBN exposure while neoplasia was not as advanced in male mice, however all mice progressed to MIBC. Single cell RNA sequencing analysis revealed an intratumoral heterogeneity also described in the human disease trajectory. Moreover, although immune activation biomarkers were elevated in urine during carcinogen exposure, anti-programmed cell death protein 1 (anti-PD1) monotherapy did not prevent tumor progression. Furthermore, anti-PD1 immunotherapy did not control the growth of subcutaneous tumors formed by the newly derived urothelial cancer cell line. However, treatment with CpG-oligodeoxynucleotides (ODN) significantly decreased tumor volume, but only in females. In conclusion, the molecular map of this novel preclinical model of bladder cancer provides an opportunity to further investigate pharmacological therapies ahead with regards to both targeted drugs and immunotherapies to improve the strategies of how we should tackle the heterogeneous tumor microenvironment in urothelial bladder cancer to improve responses rates in the clinic.

Project description:Even though urothelial cancer (UC) is the fourth common tumor type among males, progress in treatment development has been deficient. Pathological assessment provides the urologists with only a broad classification, complicated by frequent disagreement among pathologist and the co-existence of different grading systems. Consequently, there is a great need for an objective, reproducible and biologically relevant classification system to make treatment more efficient. In the present investigation we present a molecular taxonomy for UC stratification based on integrated genomics. We used gene expression profiles from 308 UC to define seven molecular subtypes using step-by-step partitions and a bootstrap approach. Results were validated in three independent and publically available data sets. The subtypes differ significantly with respect to expression of cell cycle genes, of receptor tyrosine kinases particularity FGFR3, ERBB2 (HER2), and EGFR, of an FGFR3 associated gene expression signature, of cytokaratins, and of cell adhesion genes. The subtypes also differ significantly with respect to FGFR3, PIK3CA, and TP53 mutations. The expression of key proteins was validated by IHC on TMA. A further inspection indicated that the subtypes could be reduced to four major types of UC; Urobasal/D-driven, Genomically unstable/E-driven, Evolved urobasal, and Basal/SCC like, with characteristic and highly divergent molecular phenotypes. We show that the molecular subtypes cut across pathological classification and that tumors classified as one subtype maintain their characteristic molecular phenotype irrespective of pathological stage and grade. Available data from the Drugbank database and the Cochrane central registry of controlled trials indicate that susceptibility to specific drugs is more likely to be associated with the molecular stratification than with pathological classification. The presented molecular taxonomy stratifies UC into subtypes with distinct molecular phenotypes and biological properties. We anticipate that the molecular taxonomy will be a useful tool in future clinical investigations. Total RNA from fresh-frozen resection samples of 308 urothelial carcinomas was hybridized to the Illumina HumanHT-12 V3.0 expression beadchip arrays (Illumina Inc) at the SCIBLU Genomics Centre at Lund University Sweden (http://www.lth.se/sciblu). Supplementary files: GSE32894_non-normalized_308UCsamples.txt file = Raw intensity values for 308 UC (urothelial tumor) samples subjected only to background correction. GSE32894_reps_normals_preprocess*.txt files = Descriptive details and non-normalized data for technical replicates and normal samples that were used only in the preprocessing of the data. This dataset partly overlaps with Series GSE32549. Names of the overlapping sample names are the same, but the title of each sample is unique to the hybridization.

Project description:Even though urothelial cancer (UC) is the fourth common tumor type among males, progress in treatment development has been deficient. Pathological assessment provides the urologists with only a broad classification, complicated by frequent disagreement among pathologist and the co-existence of different grading systems. Consequently, there is a great need for an objective, reproducible and biologically relevant classification system to make treatment more efficient. In the present investigation we present a molecular taxonomy for UC stratification based on integrated genomics. We used gene expression profiles from 308 UC to define seven molecular subtypes using step-by-step partitions and a bootstrap approach. Results were validated in three independent and publically available data sets. The subtypes differ significantly with respect to expression of cell cycle genes, of receptor tyrosine kinases particularity FGFR3, ERBB2 (HER2), and EGFR, of an FGFR3 associated gene expression signature, of cytokaratins, and of cell adhesion genes. The subtypes also differ significantly with respect to FGFR3, PIK3CA, and TP53 mutations. The expression of key proteins was validated by IHC on TMA. A further inspection indicated that the subtypes could be reduced to four major types of UC; Urobasal/D-driven, Genomically unstable/E-driven, Evolved urobasal, and Basal/SCC like, with characteristic and highly divergent molecular phenotypes. We show that the molecular subtypes cut across pathological classification and that tumors classified as one subtype maintain their characteristic molecular phenotype irrespective of pathological stage and grade. Available data from the Drugbank database and the Cochrane central registry of controlled trials indicate that susceptibility to specific drugs is more likely to be associated with the molecular stratification than with pathological classification. The presented molecular taxonomy stratifies UC into subtypes with distinct molecular phenotypes and biological properties. We anticipate that the molecular taxonomy will be a useful tool in future clinical investigations.

Project description:When making treatment decisions, oncologists often stratify breast cancers into a low-risk group (ER+, low grade); an intermediate-risk group (ER+, high grade); and a high-risk group that includes Her2+ and triple-negative (ER-/PR-/Her2-) tumors. None of the currently available gene signatures correlates to this clinical classification. We aimed to develop a test that is practical for the oncologists, that offers both molecular characterization of BCs, and improved prediction of prognosis and treatment response. We investigated the molecular basis of such clinical practice by grouping Her2+ and triple-negative breast cancers together during clustering analyses on the genome-wide gene expression profiles of our training cohort, mostly derived from fine needle aspiration biopsies (FNABs) of 149 consecutive evaluable Breast cancers. The analyses consistently divided these tumors into a three-cluster pattern, similar to clinical risk-stratification groups, that was reproducible in published microarray databases (n=2487) annotated with clinical outcomes. The clinicopathologic parameters of each of these three molecular groups were also similar to clinical classification. The low-risk group had good outcomes and benefited from endocrine therapy. Both intermediate- and high-risk groups had poor outcomes and were resistant to endocrine therapy. The latter demonstrated the highest rate of complete pathological response to neoadjuvant chemotherapy; the highest activities in MYC, E2F1, Ras, β-Catenin and IFN-γ pathways; and poor prognosis predicted by 14 independent prognostic signatures. Based on a multivariate analysis, this new gene signature, termed ClinicoMolecular Triad Classification, predicted recurrence and treatment response better than all pathologic parameters and other prognostic signatures. 149 invasive breast cancers from the 172 specimens contained 161 tumors were used in this study. Expression data of the 11 tumors with replicate was separately combined before analysis.

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Simplified Molecular Classification of Urothelial Carcinoma via Multi-Omic Profiling: Implications for Precision Therapy

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