A quantitative polymerase chain reaction based method for molecular subtype classification of urinary bladder cancer—Stromal gene expressions show higher prognostic values than intrinsic tumor genes

Transcriptome-based molecular subtypes of muscle-invasive bladder cancer (MIBC) have been shown to be both prognostic and predictive, but are not used in routine clinical practice. We aimed to develop a feasible, reverse transcription quantitative polymerase chain reaction (RT-qPCR)-based method for molecular subtyping. First, we defined a 68-gene set covering tumor intrinsic (luminal, basal, squamous, neuronal, epithelial-to-mesenchymal, in situ carcinoma) and stromal (immune, extracellular matrix, p53-like) signatures. Then, classifier methods with this 68-gene panel were developed in silico and validated on public data sets with available subtype class information (MD Anderson [MDA], The Cancer Genome Atlas [TCGA], Lund, Consensus). Finally, expression of the selected 68 genes was determined in 104 frozen tissue samples of our MIBC cohort by RT-qPCR using the TaqMan Array Card platform and samples were classified by our newly developed classifiers. The prognostic value of each subtype classification system and molecular signature scores were assessed. We found that the reduced marker set combined with the developed classifiers were able to reproduce the TCGA II, MDA, Lund and Consensus subtype classification systems with an overlap of 79%, 76%, 69% and 64%, respectively. Importantly, we could successfully classify 96% (100/104) of our MIBC samples by using RT-qPCR. Neuronal and luminal subtypes and low stromal gene expressions were associated with poor survival. In conclusion, we developed a robust and feasible method for the molecular subtyping according to the TCGA II, MDA, Lund and Consensus classifications. Our results suggest that stromal signatures have a superior prognostic value compared to tumor intrinsic signatures and therefore underline the importance of tumor-stroma interaction during the progression of MIBC