Background: Recent and independent muscle-invasive bladder cancer (MIBC) molecular classifications identified the basal / squamous-like (BASQ) tumours as an intrinsic and robust subtype, with a poor outcome and possible chemosensitivity to cisplatin based regimen, making mandatory the development of a diagnostic tool for their identification in routine samples. Our study aimed to evaluate the diagnostic accuracy of a Nanostring classifier for tumor subtype prediction on FPPE specimens. Methods: Two series of MIBC were used (CIT n = 51 & Stransky n = 22) for which BASQ tumours were identified previously using Affymetrix transcriptome data obtained from frozen samples (Rebouissou, Science Trans Med 2014). 29 genes were selected to predict the basal subtype, RNA expression of matched frozen and FFPE samples was studied using Nanostring technology. To define the classifiers for Affymetrix, frozen and FFPE Nanostring expression matrix on CIT samples the centroid of each cluster was calculated using the expression of 29 genes. Internal validation used leave-one-out cross-validation to train and test the prediction accuracy of the new classifier. For external validation, the CIT samples were used as training set and the Stransky samples as validation set. Predictive accuracy expressed as percentage of correctly classified samples is provided. Results: Correlations between Affymetrix, frozen and FFPE Nanostring data set were checked for gene expression and samples. Using CIT samples as train and test set, the predictive accuracy for BASQ tumour identification was for Affymetrix, frozen Nanostring and FFPE Nanostring classifiers, 90.20% [78.59%; 96.74%], 88.24% [76.13%; 95.56%] and 92.16% [81.12%; 97.82%], respectively. Using training on CIT samples and test on Stransky samples, this predictive accuracy was 90.91% [70.84%; 98.88%] both for Affymetrix, frozen Nanostring and FFPE Nanostring classifiers. Conclusions: The 29 gene expression Nanostring codeset was able to identify reliably basal / squamous like tumours on FFPE samples from MIBC in comparison with the gold standard approach based on transcriptomic profile, appearing as a promising diagnostic tool.