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. Our findings indicate the principal cell lineage marker L1CAM and intercalated cell lineage marker LINC01187 to be expressed mutually exclusively in a unique checkered pattern in BHD-associated HOTs, and these 2 lineage markers collectively capture the 2 distinct tumor epithelial populations seen to co-exist morphologically in HOTs. We further confirmed that the unique checkered expression pattern of L1CAM and LINC01187 distinguished HOT from chRCC, renal oncocytoma, and other major and rare renal cell carcinoma subtypes. We also characterized the histopathologic features and immunophenotypic features of oncocytosis in the background kidney of patients with BHD, as well as the intertumor and intratumor heterogeneity seen within HOT. We suggest that L1CAM and LINC01187 can serve as stand-alone diagnostic markers or as a panel for the diagnosis of HOT. These lineage markers will inform future studies on the evolution and interaction between the 2 transcriptionally distinct tumor epithelial populations in such tumors.

Characterization of protein S-(2-succino)-cysteine (2SC) succination as a biomarker for fumarate hydratase-deficient renal cell carcinoma.

Fumarate hydratase (FH)-deficient renal cell carcinoma (RCC) is an aggressive, rare genetic disease affecting the kidney and other organ systems. We constructed a specialized multi-institutional cohort of 20 primary FH-deficient RCC cases with aims of characterizing a new commercially available antibody, S-(2-succino)-cysteine (2SC). Herein, we present our findings on the biomarker characterization and performance of 2SC expression by immunohistochemistry (IHC) in FH-deficient RCC and other common and rare RCC subtypes. Morphological assessment revealed characteristic cytomorphologic features and a majority (55%) of FH-deficient RCC had mixed architectural growth patterns. We observed predominantly diffuse and strong cytoplasmic staining with limited nuclear positivity for 2SC staining on IHC. Receiver operating characteristic curves (ROC) for 2SC identified the threshold IHC score (cutoff) as 90, with the sensitivity and specificity being 100% and 91%, respectively. The findings of the present study along with the prior evidence in literature encourage utilization of 2SC as a positive marker along with the loss of FH expression by anti-FH IHC staining as a negative marker, in clinical and/or pathologic scenarios when considering FH-deficient RCC in the differential diagnosis. FH-/2SC+ may serve as a comprehensive IHC panel in identifying such cases and excluding morphologically similar entities.

Characterization of Intercalated Cell Markers KIT and LINC01187 in Chromophobe Renal Cell Carcinoma and Other Renal Neoplasms.

Introduction. 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. Methods. In our recent next-generation sequencing based study, we nominated a lineage-specific novel biomarker LINC01187 (long intergenic non-protein coding RNA 1187) which was found to be enriched in chromophobe RCC. Like KIT (cluster of differentiation 117; CD117), a clinically utilized chromophobe RCC related biomarker, LINC01187 is expressed in intercalated cells of the nephron. In this follow-up study, we performed KIT immunohistochemistry and LINC01187 RNA in situ hybridization (RNA-ISH) on a cohort of chromophobe RCC and other renal neoplasms, characterized the expression patterns, and quantified the expression signals of the two biomarkers in both primary and metastatic settings. Results. LINC01187, in comparison to KIT, exhibits stronger and more uniform expression within tumors while maintaining temporal and spatial consistency. LINC01187 also is devoid of intra-tumoral heterogeneous expression pattern, a phenomenon commonly noted with KIT. Conclusions. LINC01187 expression can augment the currently utilized KIT assay and help facilitate easy microscopic analyses in routine surgical pathology practice.

Deciphering intratumor heterogeneity in clear cell renal cell carcinoma utilizing clinicopathologic and molecular platforms.

Clear cell renal cell carcinoma (CCRCC) is a common renal malignancy known for its lethality and chromosome 3p aberrancies associated with loss of VHL. It has been shown that additional prognostic molecular markers exist in other transcriptional modifiers such as BAP1 and SETD2. Molecular heterogeneity has been described between primary and metastatic sites as well as genetic diversity in spatial tumor analysis; however, morphologic and proteogenomic heterogeneity information is lacking. We assessed 77 nephrectomy specimens with a diagnosis of CCRCC for morphologic architectural patterns including nodular growth patterns and variations in WHO/ISUP grade. Evaluation of highly heterogeneous areas with immunohistochemical (IHC) staining for BAP1, UCHL1, SETD2, and CAIX was performed and correlated with morphologic and histology data. Ultimately, high variability in the morphologic and histological findings matched the complexity of the IHC findings. Alterations in expression of CAIX and UCHL1 correlated with alterations in transcriptional regulators BAP1 and SETD2 within the tumor. High-grade morphology, such as eosinophilia, were areas enriched for alteration of biomarker expression. This highly complex data set of morphologic and biomarker characteristics highlights the heterogeneity of morphology amongst high-grade CCRCC tumors.

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. DESIGN: Setting, and Participants: Whole slide images from 392 in-house and TCGA cases were employed and annotated using QuPath. Image patches of 224 × 224 pixel were exported at 10 ×, 20 ×, and 40 × for input into a deep learning model based on MobileNetV2 convolutional neural network architecture pre-trained on ImageNet. A separate model was trained for each magnification. Training and test datasets consisted of 261 cases and 131 cases, respectively. The output of the model included a prediction of ERG-positive (ERG rearranged) or ERG-negative (ERG not rearranged) status for each input patch. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Various accuracy measurements including area under the curve (AUC) of the receiver operating characteristic (ROC) curves were used to evaluate the deep learning model. RESULTS AND LIMITATIONS: All models showed similar ROC curves with AUC results ranging between 0.82 and 0.85. The sensitivity and specificity of these models were 75.0% and 83.1% (20 × model), respectively. CONCLUSIONS: A deep learning-based model can successfully predict ERG rearrangement status in the majority of prostatic adenocarcinomas utilizing only H&E-stained digital slides. Such an artificial intelligence-based model can eliminate the need for using extra tumor tissue to perform ancillary studies in order to assess for ERG gene rearrangement in prostatic adenocarcinoma.

TRIM63 is a sensitive and specific biomarker for MiT family aberration-associated renal cell carcinoma.

Microphthalmia-associated transcription factor (MiT) family aberration-associated renal cell carcinoma (MiTF-RCC) is a subtype of renal cell carcinoma harboring recurrent chromosomal rearrangements involving TFE3 or TFEB genes. MiTF-RCC is morphologically diverse, can histologically resemble common RCC subtypes like clear cell RCC and papillary RCC, and often poses a diagnostic challenge in genitourinary clinical and pathology practice. To characterize the MiTF-RCC at the molecular level and identify biomarker signatures associated with MiTF-RCC, we analyzed RNAseq data from MiTF-RCC, other RCC subtypes and benign kidney. Upon identifying TRIM63 as a cancer-specific biomarker in MiTF-RCC, we evaluated its expression independently by RNA in situ hybridization (RNA-ISH) in whole tissue sections from 177 RCC cases. We specifically included 31 cytogenetically confirmed MiTF-RCC cases and 70 RCC cases suspicious for MiTF-RCC in terms of clinical and morphological features, to evaluate and compare TRIM63 RNA-ISH results with the results from TFE3/TFEB fluorescence in situ hybridization (FISH), which is the current clinical standard. We confirmed that TRIM63 mRNA was highly expressed in all classes of MiTF-RCC compared to other renal tumor categories, where it was mostly absent to low. While the TRIM63 RNA-ISH and TFE3/TFEB FISH results were largely concordant, importantly, TRIM63 RNA-ISH was strongly positive in TFE3 FISH false-negative cases with RBM10-TFE3 inversion. In conclusion, TRIM63 can serve as a diagnostic marker to distinguish MiTF-RCC from other renal tumor subtypes with overlapping morphology. We suggest a combination of TFE3/TFEB FISH and TRIM63 RNA-ISH assays to improve the accuracy and efficiency of MiTF-RCC diagnosis. Accurate diagnosis of MiTF-RCC and other RCC subtypes would enable effective targeted therapy and avoid poor therapeutic response due to tumor misclassification.