Moffitt researchers reported the discovery of a new 19 gene expression signature that appears to have value in improving the accuracy of urothelial cancer diagnosis at the USCAP 2018 meeting in Vancouver.
The correct diagnosis of urothelial cancer, especially when metastatic can be very challenging for the surgical pathologist Urothelial carcinoma (UC) can mimic a poorly squamous cell carcinoma (SCC) and it may be difficult to distinguish the two especially in metastatic sites.
Metastatic cancer imaged with PET scan
It is important to distinguish the two cancers for proper patient management. These two cancers have an overlapping immunohistochemical profile (both positive for CK5/6, CK7, p63 and p40). GATA3 although relatively specific for UC, can also be expressed in SCC.
It is important to distinguish urothelial carcinoma from other epithelial cancers to ensure proper diagnosis and patient managment
Gene expression analysis is a powerful method that can measure the expression level of thousands of mRNA messages simultaneously in a tissue biopsy specimen. Analysis of data from this technique, when coupled with bioinformatics analysis can produce powerful classification algorithms which could be used in a CLIA laboratory to improve the accuracy of current diagnostic approaches.
Affymetrix chips for rapid gene expression
The Moffitt researchers analyzed 161 UC, 38 head and neck cases, and 268 lung cancer SCC cases from Moffitts Total Cancer Care (TCC) database to create the initial algorithm. The data was collected on the a specially modified HuRSTA chip containing 60607 probe sets covering 26356 genes. An algorithm was developed from the 19 top most differentially expressed genes using principal component analysis (PCA). The PCA model performed at above 98% sensitivity and specificity correctly identifying the histological origin of the specimens on self validation.
PCA analysis separating tumor types using 19 gene signature
The signature was further validated on publicly available external datasets at GEO datasets, with 96 cases of H&N SCC from GSE31056, 18 lung SCCs from GSE10245 and 93 UC from GSE31684, total of 207 cases.This signature correctly identified 112 of the 114 publicly available SCCs with gene data (96 H&N and 16 lung) as SCC and all of 93 publicly available UCs with gene data as UC
The identification of a gene classification algorithm will enable improved classification of these challenging lesions, particularly in the metastatic setting.
The Moffitt investigators will continue to evaluate this new signature and propose to develop it into a routine diagnostic assay. In addition, deeper understanding of the molecular basis of urothelial cancer and how it differs at the molecular level potentially opens new approaches to therapy.
An assay like this could be far superior than classical IHC as the complexity of gene expression will give multiple insights into not only tissue of orign but also other aspects of the cancer biology such as immune status.
Understanding the molecular basis of urothelial cancer will provide insights into novel treatment opportunity
The work was supported by the Moffitt Morsani Molecular Laboratories
Presented at the 2018 USCAP meeting in Vancouver Canada