Jason P. Sinnwell

Utility of ALK-1 protein expression and ALK rearrangements in distinguishing inflammatory myofibroblastic tumor from malignant spindle cell lesions of the urinary bladder

Inflammatory myofibroblastic tumor of the urinary bladder is an unusual spindle cell neoplasm that displays cytologic atypia, infiltrative growth and mitotic activity mimicking malignant tumors, such as leiomyosarcoma, rhabdomyosarcoma and sarcomatoid carcinoma. The objective of this study was to determine if anaplastic lymphoma kinase (ALK-1) protein expression detected by immunohistochemistry and ALK rearrangements detected by fluorescence in situ hybridization (FISH) were useful in distinguishing inflammatory myofibroblastic tumor from malignant spindle cell tumors of the urinary bladder. In inflammatory myofibroblastic tumor, ALK-1 expression was identified in 13 of 21 cases (62%) and ALK rearrangements in 14 of 21 cases (67%). All cases of inflammatory myofibroblastic tumor demonstrating ALK-1 expression, carried ALK rearrangements. One case negative for ALK-1 expression exhibited ALK rearrangement. ALK rearrangements were more common in women (P=0.0032). Leiomyosarcoma, sarcomatoid carcinoma, embryonal rhabdomyosarcoma and reactive myofibroblastic proliferations were negative for ALK-1 protein and ALK rearrangements. Immunohistochemistry using markers of muscle, epithelial, neural, and follicular dendritic cell differentiation showed overlap between inflammatory myofibroblastic tumor with and without ALK gene rearrangements, and between inflammatory myofibroblastic tumor and spindle cell malignancies. However, coexpression of cytokeratin and muscle-specific antigens was unique to inflammatory myofibroblastic tumor, observed in approximately half the tumors. This study indicates that detection of ALK protein and ALK gene rearrangements are useful in distinguishing inflammatory myofibroblastic tumor from spindle cell malignancies in the urinary bladder. Additionally, our findings suggest that ALK rearrangement is the primary mechanism for ALK activation and that inflammatory myofibroblastic tumor likely represents a heterogeneous group of spindle cell proliferations with the majority associated with ALK translocations, and the remaining associated with other etiologies.

Multiple Genetic Variant Association Testing by Collapsing and Kernel Methods With Pedigree or Population Structured Data

Searching for rare genetic variants associated with complex diseases can be facilitated by enriching for diseased carriers of rare variants by sampling cases from pedigrees enriched for disease, possibly with related or unrelated controls. This strategy, however, complicates analyses because of shared genetic ancestry, as well as linkage disequilibrium among genetic markers. To overcome these problems, we developed broad classes of “burden” statistics and kernel statistics, extending commonly used methods for unrelated case‐control data to allow for known pedigree relationships, for autosomes and the X chromosome. Furthermore, by replacing pedigree‐based genetic correlation matrices with estimates of genetic relationships based on large‐scale genomic data, our methods can be used to account for population‐structured data. By simulations, we show that the type I error rates of our developed methods are near the asymptotic nominal levels, allowing rapid computation of P‐values. Our simulations also show that a linear weighted kernel statistic is generally more powerful than a weighted “burden” statistic. Because the proposed statistics are rapid to compute, they can be readily used for large‐scale screening of the association of genomic sequence data with disease status.

The kinship2 R Package for Pedigree Data

Background: The kinship2 package is restructured from the previous kinship package. Existing features are now enhanced and new features added for handling pedigree objects. Methods: Pedigree plotting features have been updated to display features on complex pedigrees while adhering to pedigree plotting standards. Kinship matrices can now be calculated for the X chromosome. Other methods have been added to subset and trim pedigrees while maintaining the pedigree structure. Conclusion: We make the kinship2 package available for R on the Contributed R Archives Network (CRAN), where data management is built-in and other packages can use the pedigree object.

Using the gene ontology to scan multilevel gene sets for associations in genome wide association studies

Gene‐set analyses have been widely used in gene expression studies, and some of the developed methods have been extended to genome wide association studies (GWAS). Yet, complications due to linkage disequilibrium (LD) among single nucleotide polymorphisms (SNPs), and variable numbers of SNPs per gene and genes per gene‐set, have plagued current approaches, often leading to ad hoc “fixes.” To overcome some of the current limitations, we developed a general approach to scan GWAS SNP data for both gene‐level and gene‐set analyses, building on score statistics for generalized linear models, and taking advantage of the directed acyclic graph structure of the gene ontology when creating gene‐sets. However, other types of gene‐set structures can be used, such as the popular Kyoto Encyclopedia of Genes and Genomes (KEGG). Our approach combines SNPs into genes, and genes into gene‐sets, but assures that positive and negative effects of genes on a trait do not cancel. To control for multiple testing of many gene‐sets, we use an efficient computational strategy that accounts for LD and provides accurate step‐down adjusted P‐values for each gene‐set. Application of our methods to two different GWAS provide guidance on the potential strengths and weaknesses of our proposed gene‐set analyses.

CCND1 rearrangements and cyclin D1 overexpression in renal oncocytomas: frequency, clinicopathologic features, and utility in differentiation from chromophobe renal cell carcinoma

SUMMARY Renal oncocytoma is a benign tumor occurring singly or as multiple synchronous lesions. The histologic features of renal oncocytoma may overlap with those of chromophobe renal cell carcinoma. Chromosomal translocations involving the CCND1 locus at 11q13 and overexpression of cyclin D1 occur in a subset of renal oncocytomas. We evaluated a series of 63 renal oncocytomas and 36 chromophobe renal cell carcinomas and assessed the clinical features, cyclin D1 overexpression by immunohistochemistry, and alterations of the CCND1 gene by fluorescence in situ hybridization. All 36 chromophobe renal cell carcinomas were negative for cyclin D1 overexpression and alterations of CCND1. Of the 63 renal oncocytomas, 21 (33%) showed cyclin D1 overexpression. Of 21 renal oncocytomas with cyclin D1 overexpression, a CCND1 rearrangement was detected in 12 (57%). A CCND1 rearrangement was also identified in 1 (2%) of the 42 renal oncocytomas without cyclin D1 overexpression. Of 42 renal oncocytomas without cyclin D1 overexpression, 16 (38%) were from patients with multiple renal oncocytomas at nephrectomy. Of 21 renal oncocytomas with cyclin D1 overexpression, only 1 (5%) patient had multiple renal oncocytomas (P = .006). Of the 25 patients whose original tumor showed no cyclin D1 overexpression, 8 (32%) developed a subsequent renal oncocytoma. None of 15 patients whose original tumor showed cyclin D1 overexpression had a subsequent renal oncocytoma (P = .016). The findings of this study suggest that renal oncocytomas lacking cyclin D1 overexpression may be associated with the development of multiple renal oncocytomas and that these patients are more likely to develop subsequent renal oncocytomas suggesting the need for more frequent clinical for these patients and little need for follow-up in patients with renal oncocytomas overexpressing cyclin D1. The data also show that cyclin D1 overexpression and CCND1 rearrangements by fluorescence in situ hybridization are absent in chromophobe renal cell carcinoma, suggesting that these are useful when differentiating between renal oncocytoma and chromophobe renal cell carcinoma.

Identification of genes and haplotypes that predict rheumatoid arthritis using random forests

Random forest (RF) analysis of genetic data does not require specification of the mode of inheritance, and provides measures of variable importance that incorporate interaction effects. In this paper we describe RF-based approaches for assessment of gene and haplotype importance, and apply these approaches to a subset of the North American Rheumatoid Arthritis Consortium case-control data provided by Genetic Analysis Workshop 16. The RF analyses of 37 genes identified many of the same genes as logistic regression, but also suggested importance of certain single-nucleotide polymorphism and genes that were not ranked highly by logistic regression. A new permutation method did not reveal strong evidence of gene-gene interaction effects in these data. Although RFs are a promising approach for genetic data analysis, extensions beyond simple single-nucleotide polymorphism analyses and modifications to improve computational feasibility are needed.

Determining the frequency of pathogenic germline variants from exome sequencing in patients with castrate-resistant prostate cancer

Objectives To determine the frequency of pathogenic inherited mutations in 157 select genes from patients with metastatic castrate-resistant prostate cancer (mCRPC). Design Observational. Setting Multisite US-based cohort. Participants Seventy-one adult male patients with histological confirmation of prostate cancer, and had progressive disease while on androgen deprivation therapy. Results Twelve patients (17.4%) showed evidence of carrying pathogenic or likely pathogenic germline variants in the ATM, ATR, BRCA2, FANCL, MSR1, MUTYH, RB1, TSHR and WRN genes. All but one patient opted in to receive clinically actionable results at the time of study initiation. We also found that pathogenic germline BRCA2 variants appear to be enriched in mCRPC compared to familial prostate cancers. Conclusions Pathogenic variants in cancer-susceptibility genes are frequently observed in patients with mCRPC. A substantial proportion of patients with mCRPC or their family members would derive clinical utility from mutation screening. Trial registration number NCT01953640; Results.

Isochromosome 12p and polysomy 12 in primary central nervous system germ cell tumors: frequency and association with clinicopathologic features.

Germ cell tumors arising within the central nervous system are rare neoplasms that typically occur along midline structures in children and young adults. Although isochromosome 12p is established as a frequent chromosomal abnormality in testicular germ cell tumors, studies examining isochromosome 12p in primary central nervous system germ cell tumors are limited. Herein, we studied 24 primary central nervous system germ cell tumors from 23 patients using fluorescence in situ hybridization to determine the frequency of isochromosome 12p in these neoplasms. Of the 24 primary central nervous system germ cell tumors, fluorescence in situ hybridization detected isochromosome 12p in 6 (25%) tumors, whereas 11 (46%) tumors showed polysomy (multiple copies) of chromosome 12. One case with isochromosome 12p also showed increased 12p independent of isochromosome 12p formation. The remaining 7 tumors yielded a normal result by fluorescence in situ hybridization. Clinical follow-up of this patient cohort indicated 8 patients (32%) developed a recurrence, although no association was demonstrated between the presence or absence of chromosomal 12 abnormalities and tumor relapse. We confirm that isochromosome 12p is less frequent in primary central nervous system germ cell tumors relative to testicular germ cell tumors, and although our numbers are limited, the presence or absence of isochromosome 12p does not appear to impact tumor recurrence. Similarly, although polysomy 12 was identified in nearly half of our central nervous system germ cell tumors, no prognostic significance was attributed to this abnormality. These results suggest that fluorescence in situ hybridization studies for isochromosome 12p or polysomy 12 may have limited use in the evaluation of these rare neoplasms.

Tumor Sequencing and Patient-Derived Xenografts in the Neoadjuvant Treatment of Breast Cancer

Background: Breast cancer patients with residual disease after neoadjuvant chemotherapy (NAC) have increased recurrence risk. Molecular characterization, knowledge of NAC response, and simultaneous generation of patient-derived xenografts (PDXs) may accelerate drug development. However, the feasibility of this approach is unknown. Methods: We conducted a prospective study of 140 breast cancer patients treated with NAC and performed tumor and germline sequencing and generated patient-derived xenografts (PDXs) using core needle biopsies. Chemotherapy response was assessed at surgery. Results: Recurrent “targetable” alterations were not enriched in patients without pathologic complete response (pCR); however, upregulation of steroid receptor signaling and lower pCR rates (16.7%, 1/6) were observed in triple-negative breast cancer (TNBC) patients with luminal androgen receptor (LAR) vs basal subtypes (60.0%, 21/35). Within TNBC, TP53 mutation frequency (75.6%, 31/41) did not differ comparing basal (74.3%, 26/35) and LAR (83.3%, 5/6); however, TP53 stop-gain mutations were more common in basal (22.9%, 8/35) vs LAR (0.0%, 0/6), which was confirmed in The Cancer Genome Atlas and British Columbia data sets. In luminal B tumors, Ki-67 responses were observed in tumors that harbored mutations conferring endocrine resistance (p53, AKT, and IKBKE). PDX take rate (27.4%, 31/113) varied according to tumor subtype, and in a patient with progression on NAC, sequencing data informed drug selection (olaparib) with in vivo antitumor activity observed in the primary and resistant (postchemotherapy) PDXs. Conclusions: In this study, we demonstrate the feasibility of tumor sequencing and PDX generation in the NAC setting. “Targetable” alterations were not enriched in chemotherapy-resistant tumors; however, prioritization of drug testing based on sequence data may accelerate drug development.

Statistical Methods for Testing Genetic Pleiotropy

Genetic pleiotropy is when a single gene influences more than one trait. Detecting pleiotropy and understanding its causes can improve the biological understanding of a gene in multiple ways, yet current multivariate methods to evaluate pleiotropy test the null hypothesis that none of the traits are associated with a variant; departures from the null could be driven by just one associated trait. A formal test of pleiotropy should assume a null hypothesis that one or no traits are associated with a genetic variant. For the special case of two traits, one can construct this null hypothesis based on the intersection-union (IU) test, which rejects the null hypothesis only if the null hypotheses of no association for both traits are rejected. To allow for more than two traits, we developed a new likelihood-ratio test for pleiotropy. We then extended the testing framework to a sequential approach to test the null hypothesis that k+1 traits are associated, given that the null of k traits are associated was rejected. This provides a formal testing framework to determine the number of traits associated with a genetic variant, while accounting for correlations among the traits. By simulations, we illustrate the type I error rate and power of our new methods; describe how they are influenced by sample size, the number of traits, and the trait correlations; and apply the new methods to multivariate immune phenotypes in response to smallpox vaccination. Our new approach provides a quantitative assessment of pleiotropy, enhancing current analytic practice.