A genomic algorithm for the molecular classification of common renal cortical neoplasms: development and validation

Development of a Single Molecule Counting Assay to Differentiate Chromophobe Renal Cancer and Oncocytoma in Clinics

Malignant chromophobe renal cancer (chRCC) and benign oncocytoma (RO) are two renal tumor types difficult to differentiate using histology and immunohistochemistry-based methods because of their similarity in appearance. We previously developed a transcriptomics-based classification pipeline with "Chromophobe-Oncocytoma Gene Signature" (COGS) on a single-molecule counting platform. Renal cancer patients (n = 32, chRCC = 17, RO = 15) were recruited from Augusta University Medical Center (AUMC). Formalin-fixed paraffin-embedded (FFPE) blocks from their excised tumors were collected. We created a custom single-molecule counting code set for COGS to assay RNA from FFPE blocks. Utilizing hematoxylin-eosin stain, pathologists were able to correctly classify these tumor types (91.8%). Our unsupervised learning with UMAP (Uniform manifold approximation and projection, accuracy = 0.97) and hierarchical clustering (accuracy = 1.0) identified two clusters congruent with their histology. We next developed and compared four supervised models (random forest, support vector machine, generalized linear model with L2 regularization, and supervised UMAP). Supervised UMAP has shown to classify all the cases correctly (sensitivity = 1, specificity = 1, accuracy = 1) followed by random forest models (sensitivity = 0.84, specificity = 1, accuracy = 1). This pipeline can be used as a clinical tool by pathologists to differentiate chRCC from RO.

Comprehensive study of 9 novel cases of TFEB-amplified renal cell carcinoma: an aggressive tumor with frequent PDL1 expression

BACKGROUND & OBJECTIVES

First described in 2014, renal cell carcinoma (RCC) with TFEB amplification (6p21) is a rare molecular subgroup whose diagnosis is challenging. The prognosis and therapeutic implications remain unclear.

METHODS

We report here the clinical, histological, immunohistochemical and genetic features of 9 novel cases. The pathological and immunohistochemical features were centrally reviewed by expert uropathologists. Fluorescence in situ hybridization (FISH) confirmed the diagnosis and comparative genomic hybridization (CGH) was performed to determine quantitative genomic alterations. We also performed an exhaustive review of the literature and compiled our data.

RESULTS

TFEB-amplified RCC were locally advanced with initial lymph node involvement in one case and liver metastasis in another case. They were high-grade eosinophilic tumors with papillary/pseudopapillary architecture, frequent positivity for melanocytic markers and frequent PDL1 expression. FISH demonstrated high-level TFEB amplification in 6 cases. One case showed concomitant TFEB translocation. CGH analysis identified complex alterations with frequent losses of 1p, 2q, 3p, 6p, and frequent 6p and 8q gains. VEGFA co-amplification was identified in all cases with a lower level than TFEB. The prognosis was poor with five patients having lymph node or distant metastases.

CONCLUSION

TFEB-amplified RCC is a rare molecular subgroup with variable morphology whose diagnosis is confirmed by FISH analysis. The complex alterations identified by CGH are consistent with an aggressive clinical behavior. The co-amplification of VEGFA and the expression of PDL1 could suggest a potential benefit from antiangiogenics and targeted immunotherapy in combination for these aggressive tumors.

Assessing Genomic Copy Number Alterations as Best Practice for Renal Cell Neoplasia: An Evidence-Based Review from the Cancer Genomics Consortium Workgroup

Renal cell neoplasia are heterogeneous with diverse histology, genetic alterations, and clinical behavior that are diagnosed mostly on morphologic features. The Renal Cell Neoplasia Workgroup of the Cancer Genomics Consortium systematically evaluated peer-reviewed literature on genomic studies of renal cell carcinoma (RCC), including clear cell RCC, papillary RCC, chromophobe RCC, and the translocation RCC involving TFE3, TFEB and MITF rearrangements, as well as benign oncocytoma, which together comprise about 95% of all renal cell neoplasia. The Workgroup curated recurrent copy number alterations (CNAs), copy-neutral loss-of-heterozygosity (cnLOH), rearrangements, and mutations, found in each subtype and assigned clinical relevance according to established criteria. In clear cell RCC, loss of 3p has a disease-initiating role and most likely also in progression with mutations detected in VHL and other genes mapped to this arm, and loss of 9p and/or 14q has well-substantiated prognostic utility. Gain of chromosomes 7 and 17 are hallmark CNAs of papillary RCC, but patterns of other CNAs as detected by chromosomal microarray analysis (CMA) afford sub-classification into Type 1 and 2 with prognostic value, and for further sub-stratification of Type 2. Inherent chromosome loss in chromophobe RCC as detected by CMA is useful for distinguishing the eosinophilic variant from benign oncocytoma which in contrast exhibits few CNAs or rearranged CCND1, but share mitochondrial DNA mutations. In morphologically atypical RCCs, rearrangement of TFE3 and TFEB should be considered in the differential diagnosis, portending an aggressive RCC subtype. Overall, this evidence-based review provides a validated role for assessment of CNAs in renal cell neoplasia in the clinical setting to assist in renal cell neoplasm diagnosis and sub-classification within subtypes that is integral to the management of patients, from small incidentally found renal masses to larger surgically resected specimens, and simultaneously identify the presence of key alterations portending outcome in malignant RCC subtypes.

Clinical Utility of Chromosome Genomic Array Testing for Unclassified and Advanced-Stage Renal Cell Carcinomas

Context.—

Cytogenomic analysis provides a useful adjunct to traditional pathology in the categorization of renal cell carcinomas (RCCs), particularly in morphologically ambiguous cases, but it has disadvantages, including cost.

Objective.—

To define the clinical scenarios in which this technology has direct clinical applications.

Design.—

DNA was isolated from paraffin-embedded tissue from 40 selected cases of RCC. Chromosome genomic array testing was performed using the OncoScan.

Results.—

Of 23 cases of unclassified renal tumors, 19 (83%) were reclassified with incorporation of cytogenetic and histologic features, including 10 as clear cell RCC, 2 as collecting duct carcinoma, 2 as papillary RCC, and 1 as novel TFEB-amplified tumor lacking TFEB translocation. Of 5 tumors with “hybrid” oncocytic features, 3 were reclassified as an eosinophilic variant of chromophobe RCC and 1 as oncocytoma. Appropriate staging in 2 patients was determined by identifying distinct, nonshared cytogenetic profiles. Of 11 cases of metastatic clear cell RCC, 7 (63%) had cytogenetic features associated with a poor prognosis.

Conclusions.—

We identified 5 scenarios in which chromosome genomic array testing has direct clinical utility: (1) to investigate unclassified RCCs, (2) to understand tumors with “hybrid” features and “collision” tumors, (3) to determine appropriate staging in questions of bilateral tumors and/or metastases, (4) to identify chromosomal aberrations in metastatic clear cell RCCs associated with a worse prognosis, and (5) to identify new entities. This has practical value in our institution, where a molecular profile diagnostically separating morphologically difficult to classify clear cell, papillary, chromophobe, and unclassified RCC influences treatment recommendations and clinical trial eligibility.

Fluorescent In Situ Hybridization in Surgical Pathology Practice

There have been rapid and significant advances in diagnostic and predictive molecular techniques in recent years with profound impact on patient care. In situ hybridization (ISH) studies have become well entrenched in surgical pathology practice and their role in the evaluation of HER2 in breast carcinoma and their diagnostic utility in soft tissue pathology are well known. Fluorescent ISH is being increasingly used in other sites such as the head and neck and the gynecologic tract. Like most tests in surgical pathology, ISH studies require good quality tissue, correlation with clinical and histopathologic findings, and adherence to guidelines for optimal assay performance and interpretation. Although ISH studies are largely performed in tertiary centers, the tissue is often processed by a variety of laboratories and the referring pathologists are required to discuss the need, relevance, and significance of these tests and the results with their clinical colleagues. Here we review the predictive and diagnostic utility of fluorescent ISH studies in a variety of organ systems, the preanalytical factors that may affect the results, and the pitfalls in the interpretation that all practicing surgical pathologists should be aware of.

An enhanced deterministic K-Means clustering algorithm for cancer subtype prediction from gene expression data

BACKGROUND

Clustering algorithms with steps involving randomness usually give different results on different executions for the same dataset. This non-deterministic nature of algorithms such as the K-Means clustering algorithm limits their applicability in areas such as cancer subtype prediction using gene expression data. It is hard to sensibly compare the results of such algorithms with those of other algorithms. The non-deterministic nature of K-Means is due to its random selection of data points as initial centroids.

METHOD

We propose an improved, density based version of K-Means, which involves a novel and systematic method for selecting initial centroids. The key idea of the algorithm is to select data points which belong to dense regions and which are adequately separated in feature space as the initial centroids.

RESULTS

We compared the proposed algorithm to a set of eleven widely used single clustering algorithms and a prominent ensemble clustering algorithm which is being used for cancer data classification, based on the performances on a set of datasets comprising ten cancer gene expression datasets. The proposed algorithm has shown better overall performance than the others.

CONCLUSION

There is a pressing need in the Biomedical domain for simple, easy-to-use and more accurate Machine Learning tools for cancer subtype prediction. The proposed algorithm is simple, easy-to-use and gives stable results. Moreover, it provides comparatively better predictions of cancer subtypes from gene expression data.

Renal Cell Tumors: Understanding Their Molecular Pathological Epidemiology and the 2016 WHO Classification

Accumulating evidence suggests that renal cell tumors represent a group of histologically and molecularly heterogeneous diseases, even within the same histological subtype. In accordance with the increased understanding of the morphological, immunohistochemical, molecular, and epidemiological characteristics of renal cell tumors, the World Health Organization (WHO) classification of renal cell tumors has been modified. This review provides perspectives on both new and current subtypes of renal cell tumors, as well as on the emerging/provisional renal cell carcinomas in the new 2016 WHO classification, which focuses on features of their molecular pathological epidemiology. The WHO classification will require additional revisions to enable the classification of renal cell tumors as clinically meaningful subtypes and provide a better understanding of the unique characteristics of renal cell tumors.

Translocation Renal Cell Carcinoma: An Update on Clinicopathological and Molecular Features

Microphthalmia-associated transcription (MiT) family translocation renal cell carcinoma (tRCC) comprises Xp11 tRCC and t(6;11) RCC. Due to the presence of fusion genes, Xp11 tRCC and t(6;11) RCC are also known as TFE3- and TFEB-rearranged RCC, respectively. TFE3 and TFEB belong to the MiT family, which regulates melanocyte and osteoclast differentiation, and TFE3- and TFEB-rearranged RCC show characteristic clinicopathological and immunohistochemical features. Recent studies identified the fusion partner-dependent clinicopathological and immunohistochemical features in TFE3-rearranged RCC. Furthermore, RCC with chromosome 6p amplification, including TFEB, was identified as a unique subtype of RCC, along with ALK-rearranged RCC. This review summarizes these recent advancements in our tRCC-related knowledge.