Background
Currently, the treatment regimen of bladder cancer depends on the stage and grade. Yet, patients with similar histopathological characteristics may have distinct prognosis. Luminal/basal subtyping had proved to be a satisfactory subtyping method. Here we intended to evaluate immunohistochemistry, a more clinically-practical method, in luminal/basal classification and further risk-stratification.
Conclusions
Molecular subtyping into luminal/basal subtype and risk stratification method using a 2-marker method by immunohistochemistry can be an economical, clinically practical method to predict patient prognosis and could help to develop treatment strategy and follow-up schedule in clinical practice.
Methods
Patients diagnosed with urothelial carcinoma of the bladder in Changhai Hospital were retrospectively recruited and corresponding formalin-fixed paraffin embedded blocks were acquired. Tissue microarrays (TMAs) of these patients were established followed by immunohistochemical (IHC) staining of 14 markers. Patients were classified into luminal or basal subtype according to CK5/6, CK14, CK20 and GATA3 expression. Further subtyping of luminal and basal tumors was performed according to the expression of other markers.
Results
A total of 236 patients were included: 163 and 73 patients were assigned to training and validation cohorts, respectively. Patients with basal tumor were related with poorer prognosis compared to those with luminal tumor (P=0.025 and 0.008 in training and validation cohorts, respectively). We further revealed luminal muscle invasive bladder cancer (MIBC) patients could be further categorized into subgroups with different risks. Cytoplasmic YAP1 and CCNB1 were selected as classifier, patients with low expression of cytoplasmic YAP1 or CCNB1 were independent risk factor for poorer prognosis (hazard ratio =2.19, P=0.04). Conclusions: Molecular subtyping into luminal/basal subtype and risk stratification method using a 2-marker method by immunohistochemistry can be an economical, clinically practical method to predict patient prognosis and could help to develop treatment strategy and follow-up schedule in clinical practice.