Expression of L1 Cell Adhesion Molecule, a Nephronal Principal Cell Marker, in Nephrogenic Adenoma.

Nephrogenic adenoma (NA) is a benign, reactive lesion seen predominantly in the urinary bladder and often associated with antecedent inflammation, instrumentation, or an operative history. Its histopathologic diversity can create diagnostic dilemmas and pathologists use morphologic evaluation along with available immunohistochemical (IHC) markers to navigate these challenges. IHC assays currently do not designate or specify NA's potential putative cell of origin.

Hybrid Oncocytic Tumors (HOTs) in Birt-Hogg-Dubé Syndrome Patients-A Tale of Two Cities: Sequencing Analysis Reveals Dual Lineage Markers Capturing the 2 Cellular Populations of HOT.

Birt-Hogg-Dubé (BHD) syndrome is associated with an increased risk of multifocal renal tumors, including hybrid oncocytic tumor (HOT) and chromophobe renal cell carcinoma (chRCC). HOT exhibits heterogenous histologic features overlapping with chRCC and benign renal oncocytoma, posing challenges in diagnosis of HOT and renal tumor entities resembling HOT. In this study, we performed integrative analysis of bulk and single-cell RNA sequencing data from renal tumors and normal kidney tissues, and nominated candidate biomarkers of HOT, L1CAM, and LINC01187 , which are also lineage-specific markers labeling the principal cell and intercalated cell lineages of the distal nephron, respectively.

Characterization of Intercalated Cell Markers KIT and in Chromophobe Renal Cell Carcinoma and Other Renal Neoplasms.

Chromophobe renal cell carcinoma (chromophobe RCC) is the third major subcategory of renal tumors after clear cell RCC and papillary RCC, accounting for approximately 5% of all RCC subtypes. Other oncocytic neoplasms seen commonly in surgical pathology practice include the eosinophilic variant of chromophobe RCC, renal oncocytoma, and low-grade oncocytic unclassified RCC. In our recent next-generation sequencing based study, we nominated a lineage-specific novel biomarker (long intergenic non-protein coding RNA 1187) which was found to be enriched in chromophobe RCC.

Leveraging artificial intelligence to predict ERG gene fusion status in prostate cancer.

Background: TMPRSS2-ERG gene rearrangement, the most common E26 transformation specific (ETS) gene fusion within prostate cancer, is known to contribute to the pathogenesis of this disease and carries diagnostic annotations for prostate cancer patients clinically. The ERG rearrangement status in prostatic adenocarcinoma currently cannot be reliably identified from histologic features on H&E-stained slides alone and hence requires ancillary studies such as immunohistochemistry (IHC), fluorescent in situ hybridization (FISH) or next generation sequencing (NGS) for identification.

Methods: OBJECTIVE: We accordingly sought to develop a deep learning-based algorithm to identify ERG rearrangement status in prostatic adenocarcinoma based on digitized slides of H&E morphology alone.