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Molecular classification of urothelial carcinoma: global mRNA classification versus tumour-cell phenotype classification.

ABSTRACT: Global mRNA expression analysis is efficient for phenotypic profiling of tumours, and has been used to define molecular subtypes for almost every major tumour type. A key limitation is that most tumours are communities of both tumour and non-tumour cells. This problem is particularly pertinent for analysis of advanced invasive tumours, which are known to induce major changes and responses in both the tumour and the surrounding tissue. To identify bladder cancer tumour-cell phenotypes and compare classification by tumour-cell phenotype with classification by global gene expression analysis, we analysed 307 advanced bladder cancers (cystectomized) both by genome gene expression analysis and by immunohistochemistry with antibodies for 28 proteins. According to systematic analysis of gene and protein expression data, focusing on key molecular processes, we describe five tumour-cell phenotypes of advanced urothelial carcinoma: urothelial-like, genomically unstable, basal/SCC-like, mesenchymal-like, and small-cell/neuroendocrine-like. We provide molecular pathological definitions for each subtype. Tumours expressing urothelial differentiation factors show inconsistent and abnormal protein expression of terminal differentiation markers, suggesting pseudo-differentiation. Cancers with different tumour-cell phenotypes may co-cluster (converge), and cases with identical tumour-cell phenotypes may cluster apart (diverge), in global mRNA analyses. This divergence/convergence suggests that broad global commonalities related to the invasive process may exist between muscle-invasive tumours regardless of specific tumour-cell phenotype. Hence, there is a systematic disagreement in subtype classification determined by global mRNA profiling and by immunohistochemical profiling at the tumour-cell level. We suggest that a combination of molecular pathology (tumour-cell phenotype) and global mRNA profiling (context) is required for adequate subtype classification of muscle-invasive bladder cancer. © 2017 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

SUBMITTER: Sjodahl G

PROVIDER: S-EPMC5413843 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Molecular classification of urothelial carcinoma: global mRNA classification versus tumour-cell phenotype classification.

Sjödahl Gottfrid G Eriksson Pontus P Liedberg Fredrik F Höglund Mattias M

The Journal of pathology 20170328 1

Global mRNA expression analysis is efficient for phenotypic profiling of tumours, and has been used to define molecular subtypes for almost every major tumour type. A key limitation is that most tumours are communities of both tumour and non-tumour cells. This problem is particularly pertinent for analysis of advanced invasive tumours, which are known to induce major changes and responses in both the tumour and the surrounding tissue. To identify bladder cancer tumour-cell phenotypes and compare ...[more]

PMID: 28195647

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Project description:BackgroundLiver zonation is a unique phenomenon in which the liver exhibits distinct functions among hepatocytes along the radial axis of the lobule. This phenomenon can cause the sectionalized initiation of several liver diseases, including hepatocellular carcinoma (HCC). However, few studies have explored the zonation features of HCC.MethodsFour single-cell RNA sequencing datasets were used to identify hepatocyte-specific zonation markers. Integrative analysis was then performed with a training RNA-seq cohort (616 HCC samples) and an external validating microarray cohort (285 HCC samples) from the International Cancer Genome Consortium, The Cancer Genome Atlas, Gene Expression Omnibus, and EMBL's European Bioinformatics Institute for clustering using non-negative matrix factorization consensus clustering based on zonation genes. Afterward, we evaluated the prognostic value, clinical characteristics, transcriptome and mutation features, immune infiltration, and immunotherapy response of the HCC subclasses.ResultsA total of 94 human hepatocyte-specific zonation markers (39 central markers and 55 portal markers) were identified for the first time. Subsequently, three subgroups of HCC, namely Cluster1, Cluster2, and Cluster3 were identified. Cluster1 exhibited a non-zonational-like signature with the worst prognosis. Cluster2 was intensively associated with a central-like signature and exhibited low immune infiltration and sensitivity toward immune blockade therapy. Cluster3 was intensively correlated with a portal-like signature with the best prognosis. Finally, we identified candidate therapeutic targets and agents for Cluster1 HCC samples.ConclusionThe current study established a novel HCC classification based on liver zonation signature. By classifying HCC into three clusters with non-zonational-like (Cluster1), central-like (Cluster2), and portal-like (Cluster3) features, this study provided new perspectives on the heterogeneity of HCC and shed new light on delivering precision medicine for HCC patients.

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.

Dataset Information

Molecular classification of urothelial carcinoma: global mRNA classification versus tumour-cell phenotype classification.

Publications

Molecular classification of urothelial carcinoma: global mRNA classification versus tumour-cell phenotype classification.

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