A. Rose Brannon

Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT): A Hybridization Capture-Based Next-Generation Sequencing Clinical Assay for Solid Tumor Molecular Oncology

The identification of specific genetic alterations as key oncogenic drivers and the development of targeted therapies are together transforming clinical oncology and creating a pressing need for increased breadth and throughput of clinical genotyping. Next-generation sequencing assays allow the efficient and unbiased detection of clinically actionable mutations. To enable precision oncology in patients with solid tumors, we developed Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT), a hybridization capture-based next-generation sequencing assay for targeted deep sequencing of all exons and selected introns of 341 key cancer genes in formalin-fixed, paraffin-embedded tumors. Barcoded libraries from patient-matched tumor and normal samples were captured, sequenced, and subjected to a custom analysis pipeline to identify somatic mutations. Sensitivity, specificity, reproducibility of MSK-IMPACT were assessed through extensive analytical validation. We tested 284 tumor samples with previously known point mutations and insertions/deletions in 47 exons of 19 cancer genes. All known variants were accurately detected, and there was high reproducibility of inter- and intrarun replicates. The detection limit for low-frequency variants was approximately 2% for hotspot mutations and 5% for nonhotspot mutations. Copy number alterations and structural rearrangements were also reliably detected. MSK-IMPACT profiles oncogenic DNA alterations in clinical solid tumor samples with high accuracy and sensitivity. Paired analysis of tumors and patient-matched normal samples enables unambiguous detection of somatic mutations to guide treatment decisions.

Molecular Stratification of Clear Cell Renal Cell Carcinoma by Consensus Clustering Reveals Distinct Subtypes and Survival Patterns

Clear cell renal cell carcinoma (ccRCC) is the predominant RCC subtype, but even within this classification, the natural history is heterogeneous and difficult to predict. A sophisticated understanding of the molecular features most discriminatory for the underlying tumor heterogeneity should be predicated on identifiable and biologically meaningful patterns of gene expression. Gene expression microarray data were analyzed using software that implements iterative unsupervised consensus clustering algorithms to identify the optimal molecular subclasses, without clinical or other classifying information. ConsensusCluster analysis identified two distinct subtypes of ccRCC within the training set, designated clear cell type A (ccA) and B (ccB). Based on the core tumors, or most well-defined arrays, in each subtype, logical analysis of data (LAD) defined a small, highly predictive gene set that could then be used to classify additional tumors individually. The subclasses were corroborated in a validation data set of 177 tumors and analyzed for clinical outcome. Based on individual tumor assignment, tumors designated ccA have markedly improved disease-specific survival compared to ccB (median survival of 8.6 vs 2.0 years, P = 0.002). Analyzed by both univariate and multivariate analysis, the classification schema was independently associated with survival. Using patterns of gene expression based on a defined gene set, ccRCC was classified into two robust subclasses based on inherent molecular features that ultimately correspond to marked differences in clinical outcome. This classification schema thus provides a molecular stratification applicable to individual tumors that has implications to influence treatment decisions, define biological mechanisms involved in ccRCC tumor progression, and direct future drug discovery.

Tumor Genetic Analyses of Patients with Metastatic Renal Cell Carcinoma and Extended Benefit from mTOR Inhibitor Therapy

Purpose: Rapalogs are allosteric mTOR inhibitors and approved agents for advanced kidney cancer. Reports of clonal heterogeneity in this disease challenge the concept of targeted monotherapy, yet a small subset of patients derives extended benefit. Our aim was to analyze such outliers and explore the genomic background of extreme rapalog sensitivity in the context of intratumor heterogeneity. Experimental Design: We analyzed archived tumor tissue of 5 patients with renal cell carcinoma, who previously achieved durable disease control with rapalogs (median duration, 28 months). DNA was extracted from spatially separate areas of primary tumors and metastases. Custom target capture and ultradeep sequencing was used to identify alterations across 230 target genes. Whole-exome sequence analysis was added to investigate genes beyond this original target list. Results: Five long-term responders contributed 14 specimens to explore clonal heterogeneity. Genomic alterations with activating effect on mTOR signaling were detected in 11 of 14 specimens, offering plausible explanation for exceptional treatment response through alterations in two genes (TSC1 and MTOR). In two subjects, distinct yet functionally convergent alterations activated the mTOR pathway in spatially separate sites. In 1 patient, concurrent genomic events occurred in two separate pathway components across different tumor regions. Conclusions: Analysis of outlier cases can facilitate identification of potential biomarkers for targeted agents, and we implicate two genes as candidates for further study in this class of drugs. The previously reported phenomenon of clonal convergence can occur within a targetable pathway which might have implications for biomarker development beyond this disease and this class of agents. Clin Cancer Res; 20(7); 1955–64. ©2014 AACR.

Comparative sequencing analysis reveals high genomic concordance between matched primary and metastatic colorectal cancer lesions

BackgroundColorectal cancer is the second leading cause of cancer death in the United States, with over 50,000 deaths estimated in 2014. Molecular profiling for somatic mutations that predict absence of response to anti-EGFR therapy has become standard practice in the treatment of metastatic colorectal cancer; however, the quantity and type of tissue available for testing is frequently limited. Further, the degree to which the primary tumor is a faithful representation of metastatic disease has been questioned. As next-generation sequencing technology becomes more widely available for clinical use and additional molecularly targeted agents are considered as treatment options in colorectal cancer, it is important to characterize the extent of tumor heterogeneity between primary and metastatic tumors.ResultsWe performed deep coverage, targeted next-generation sequencing of 230 key cancer-associated genes for 69 matched primary and metastatic tumors and normal tissue. Mutation profiles were 100% concordant for KRAS, NRAS, and BRAF, and were highly concordant for recurrent alterations in colorectal cancer. Additionally, whole genome sequencing of four patient trios did not reveal any additional site-specific targetable alterations.ConclusionsColorectal cancer primary tumors and metastases exhibit high genomic concordance. As current clinical practices in colorectal cancer revolve around KRAS, NRAS, and BRAF mutation status, diagnostic sequencing of either primary or metastatic tissue as available is acceptable for most patients. Additionally, consistency between targeted sequencing and whole genome sequencing results suggests that targeted sequencing may be a suitable strategy for clinical diagnostic applications.

An Integrated Metabolic Atlas of Clear Cell Renal Cell Carcinoma

Dysregulated metabolism is a hallmark of cancer, manifested through alterations in metabolites. We performed metabolomic profiling on 138 matched clear cell renal cell carcinoma (ccRCC)/normal tissue pairs and found that ccRCC is characterized by broad shifts in central carbon metabolism, one-carbon metabolism, and antioxidant response. Tumor progression and metastasis were associated with metabolite increases in glutathione and cysteine/methionine metabolism pathways. We develop an analytic pipeline and visualization tool (metabolograms) to bridge the gap between TCGA transcriptomic profiling and our metabolomic data, which enables us to assemble an integrated pathway-level metabolic atlas and to demonstrate discordance between transcriptome and metabolome. Lastly, expression profiling was performed on a high-glutathione cluster, which corresponds to a poor-survival subgroup in the ccRCC TCGA cohort.

Variation in chromatin accessibility in human kidney cancer links H3K36 methyltransferase loss with widespread RNA processing defects.

Comprehensive sequencing of human cancers has identified recurrent mutations in genes encoding chromatin regulatory proteins. For clear cell renal cell carcinoma (ccRCC), three of the five commonly mutated genes encode the chromatin regulators PBRM1, SETD2, and BAP1. How these mutations alter the chromatin landscape and transcriptional program in ccRCC or other cancers is not understood. Here, we identified alterations in chromatin organization and transcript profiles associated with mutations in chromatin regulators in a large cohort of primary human kidney tumors. By associating variation in chromatin organization with mutations in SETD2, which encodes the enzyme responsible for H3K36 trimethylation, we found that changes in chromatin accessibility occurred primarily within actively transcribed genes. This increase in chromatin accessibility was linked with widespread alterations in RNA processing, including intron retention and aberrant splicing, affecting ∼25% of all expressed genes. Furthermore, decreased nucleosome occupancy proximal to misspliced exons was observed in tumors lacking H3K36me3. These results directly link mutations in SETD2 to chromatin accessibility changes and RNA processing defects in cancer. Detecting the functional consequences of specific mutations in chromatin regulatory proteins in primary human samples could ultimately inform the therapeutic application of an emerging class of chromatin-targeted compounds.

Hereditary leiomyomatosis and renal cell carcinoma syndrome-associated renal cancer: recognition of the syndrome by pathologic features and the utility of detecting aberrant succination by immunohistochemistry.

Hereditary leiomyomatosis and renal cell carcinoma (HLRCC) syndrome is an autosomal dominant disorder in which germline mutations of fumarate hydratase (FH) gene confer an increased risk of cutaneous and uterine leiomyomas and renal cancer. HLRCC-associated renal cancer is highly aggressive and frequently presents as a solitary mass. We reviewed the clinicopathologic features of 9 patients with renal tumors presenting as sporadic cases but who were later proven to have FH germline mutations. Histologically, all tumors showed mixed architectural patterns, with papillary as the dominant pattern in only 3 cases. Besides papillary, tubular, tubulopapillary, solid, and cystic elements, 6 of 9 tumors contained collecting duct carcinoma–like areas with infiltrating tubules, nests, or individual cells surrounded by desmoplastic stroma. Prominent tubulocystic carcinoma–like component and sarcomatoid differentiation were identified. Although all tumors exhibited the proposed hallmark of HLRCC (large eosinophilic nucleolus surrounded by a clear halo), this feature was often not uniformly present throughout the tumor. Prior studies have shown that a high level of fumarate accumulated in HLRCC tumor cells causes aberrant succination of cellular proteins by forming a stable chemical modification, S-(2-succino)-cysteine (2SC), which can be detected by immunohistochemistry. We thus explored the utility of detecting 2SC by immunohistochemistry in the differential diagnosis of HLRCC tumors and other high-grade renal tumors and investigated the correlation between 2SC staining and FH molecular alterations. All confirmed HLRCC tumors demonstrated diffuse and strong nuclear and cytoplasmic 2SC staining, whereas all clear cell (184/184, 100%), most high-grade unclassified (93/97, 96%), and the large majority of “type 2” papillary (35/45, 78%) renal cell carcinoma cases showed no 2SC immunoreactivity. A subset of papillary (22%) and rare unclassified (4%) tumors showed patchy or diffuse cytoplasmic staining without nuclear labeling, unlike the pattern seen with confirmed HLRCC tumors. Sequencing revealed no germline or somatic FH alterations in 14 tumors that either exhibited only cytoplasmic 2SC staining (n=5) or were negative for 2SC (n=9), despite their HLRCC-like morphologic features. Our results emphasize the pivotal role of pathologic examination in the diagnosis of HLRCC patients and indicate immunohistochemical detection of 2SC as a useful ancillary tool in the differentiation of HLRCC renal tumors from other high-grade renal cell carcinomas.

ClearCode34: A Prognostic Risk Predictor for Localized Clear Cell Renal Cell Carcinoma

BACKGROUND Gene expression signatures have proven to be useful tools in many cancers to identify distinct subtypes of disease based on molecular features that drive pathogenesis, and to aid in predicting clinical outcomes. However, there are no current signatures for kidney cancer that are applicable in a clinical setting. OBJECTIVE To generate a signature biomarker for the clear cell renal cell carcinoma (ccRCC) good risk (ccA) and poor risk (ccB) subtype classification that could be readily applied to clinical samples to develop an integrated model for biologically defined risk stratification. DESIGN, SETTING, AND PARTICIPANTS A set of 72 ccRCC sample standards was used to develop a 34-gene classifier (ClearCode34) for assigning ccRCC tumors to subtypes. The classifier was applied to RNA-sequencing data from 380 nonmetastatic ccRCC samples from the Cancer Genome Atlas (TCGA), and to 157 formalin-fixed clinical samples collected at the University of North Carolina. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Kaplan-Meier analyses were performed on the individual cohorts to calculate recurrence-free survival (RFS), cancer-specific survival (CSS), and overall survival (OS). Training and test sets were randomly selected from the combined cohorts to assemble a risk prediction model for disease recurrence. RESULTS AND LIMITATIONS The subtypes were significantly associated with RFS (p<0.01), CSS (p<0.01), and OS (p<0.01). Hazard ratios for subtype classification were similar to those of stage and grade in association with recurrence risk, and remained significant in multivariate analyses. An integrated molecular/clinical model for RFS to assign patients to risk groups was able to accurately predict CSS above established, clinical risk-prediction algorithms. CONCLUSIONS The ClearCode34-based model provides prognostic stratification that improves upon established algorithms to assess risk for recurrence and death for nonmetastatic ccRCC patients. PATIENT SUMMARY We developed a 34-gene subtype predictor to classify clear cell renal cell carcinoma tumors according to ccA or ccB subtypes and built a subtype-inclusive model to analyze patient survival outcomes.

Synthetic Lethality in ATM-Deficient RAD50-Mutant Tumors Underlies Outlier Response to Cancer Therapy

UNLABELLED Metastatic solid tumors are almost invariably fatal. Patients with disseminated small-cell cancers have a particularly unfavorable prognosis, with most succumbing to their disease within two years. Here, we report on the genetic and functional analysis of an outlier curative response of a patient with metastatic small-cell cancer to combined checkpoint kinase 1 (CHK1) inhibition and DNA-damaging chemotherapy. Whole-genome sequencing revealed a clonal hemizygous mutation in the Mre11 complex gene RAD50 that attenuated ATM signaling which in the context of CHK1 inhibition contributed, via synthetic lethality, to extreme sensitivity to irinotecan. As Mre11 mutations occur in a diversity of human tumors, the results suggest a tumor-specific combination therapy strategy in which checkpoint inhibition in combination with DNA-damaging chemotherapy is synthetically lethal in tumor cells but not normal cells with somatic mutations that impair Mre11 complex function. SIGNIFICANCE Strategies to effect deep and lasting responses to cancer therapy in patients with metastatic disease have remained difficult to attain, especially in early-phase clinical trials. Here, we present an in-depth genomic and functional genetic analysis identifying RAD50 hypomorphism as a contributing factor to a curative response to systemic combination therapy in a patient with recurrent, metastatic small-cell cancer.

Meta-analysis of Clear Cell Renal Cell Carcinoma Gene Expression Defines a Variant Subgroup and Identifies Gender Influences on Tumor Biology

BACKGROUND Clear cell renal cell carcinoma (ccRCC) displays molecular and histologic heterogeneity. Previously described subsets of this disease, ccA and ccB, were defined based on multigene expression profiles, but it is unclear whether these subgroupings reflect the full spectrum of disease or how these molecular subtypes relate to histologic descriptions or gender. OBJECTIVE Determine whether additional subtypes of ccRCC exist and whether these subtypes are related to von Hippel-Lindau (VHL) inactivation, hypoxia-inducible factor (HIF) 1 and 2 expression, tumor histology, or gender. DESIGN, SETTING, AND PARTICIPANTS Six large, publicly available ccRCC gene expression databases were identified that cumulatively provided data for 480 tumors for meta-analysis via meta-array compilation. MEASUREMENTS Unsupervised consensus clustering was performed on the meta-arrays. Tumors were examined for the relationship of multigene-defined consensus subtypes and expression signatures of VHL mutation and HIF status, tumor histology, and gender. RESULTS AND LIMITATIONS Two dominant subsets of ccRCC were observed. However, a minor third cluster was revealed that correlated strongly with a wild type (WT) VHL expression profile and indications of variant histologies. When variant histologies were removed, ccA tumors naturally divided by gender. This technique is limited by the potential for persistent batch effect, tumor sampling bias, and restrictions of annotated information. CONCLUSIONS The ccA and ccB subsets of ccRCC are robust in meta-analysis among histologically conventional ccRCC tumors. A third group of tumors was identified that may represent a new variant of ccRCC. Within definitively clear cell tumors, gender may delineate tumors in such a way that it could have implications regarding current treatments and future drug development.