Abstract
CONCLUSIONS
A single-patient classifier was developed that identifies patients with histologic urothelial cancer harboring a NE transcriptomic profile. These tumors represent a high-risk subgroup of MIBC, which may require different treatment.
RESULTS
In the training cohort (PTC), hierarchical clustering using an 84-gene panel showed a cluster of 8 patients (4.6%) with highly heterogeneous expression of NE markers in the absence of basal or luminal marker expression. NE-like tumors were identified in 1% to 6.6% of cases in validation cohorts. Patients with NE-like tumors had significantly worse 1-year progression-free survival (65% NE-like vs. 82% overall; P = 0.046) and, after adjusting for clinical and pathologic factors, had a 6.4-fold increased risk of all-cause mortality (P = 0.001). IHC confirmed the neuronal character of these tumors.
EXPERIMENTAL DESIGN
Transcriptome-wide expression profiles were generated for MIBC collected from 7 institutions and clinical-use of Decipher Bladder. Using unsupervised clustering, we generated a clustering solution on a prospective training cohort (PTC; n = 175), developed single-sample classifiers to predict NE tumors, and evaluated the resultant models on a testing radical cystectomy (RC) cohort (n = 225). A random forest model was finalized and applied to 5 validation cohorts (n = 1302). Uni- and multivariable survival analyses were used to characterize clinical outcomes.
PURPOSE
Neuroendocrine (NE) bladder carcinoma is a rare and aggressive variant. Molecular subtyping studies have found that 5% to 15% of muscle-invasive bladder cancer (MIBC) have transcriptomic patterns consistent with NE bladder cancer in the absence of NE histology. The clinical implications of this NE-like subtype have not been explored in depth.