Richard Finney

Genetic Alterations Activating Kinase and Cytokine Receptor Signaling in High-Risk Acute Lymphoblastic Leukemia

Genomic profiling has identified a subtype of high-risk B-progenitor acute lymphoblastic leukemia (B-ALL) with alteration of IKZF1, a gene expression profile similar to BCR-ABL1-positive ALL and poor outcome (Ph-like ALL). The genetic alterations that activate kinase signaling in Ph-like ALL are poorly understood. We performed transcriptome and whole genome sequencing on 15 cases of Ph-like ALL and identified rearrangements involving ABL1, JAK2, PDGFRB, CRLF2, and EPOR, activating mutations of IL7R and FLT3, and deletion of SH2B3, which encodes the JAK2-negative regulator LNK. Importantly, several of these alterations induce transformation that is attenuated with tyrosine kinase inhibitors, suggesting the treatment outcome of these patients may be improved with targeted therapy.

Metastasis Predictive Signature Profiles Pre-exist in Normal Tissues

Previous studies from our laboratory have demonstrated that metastatic propensity is significantly influenced by the genetic background upon which tumors arise. We have also established that human gene expression profiles predictive of metastasis are not only present in mouse tumors with both high and low metastatic capacity, but also correlate with genetic background. These results suggest that human metastasis-predictive gene expression signatures may be significantly driven by genetic background, rather than acquired somatic mutations. To test this hypothesis, gene expression profiling was performed on inbred mouse strains with significantly different metastatic efficiencies. Analysis of previously described human metastasis signature gene expression patterns in normal tissues permitted accurate categorization of high or low metastatic mouse genotypes. Furthermore, prospective identification of animals at high risk of metastasis was achieved by using mass spectrometry to characterize salivary peptide polymorphisms in a genetically heterogeneous population. These results strongly support the role of constitutional genetic variation in modulation of metastatic efficiency and suggest that predictive signature profiles could be developed from normal tissues in humans. The ability to identify those individuals at high risk of disseminated disease at the time of clinical manifestation of a primary cancer could have a significant impact on cancer management.

Genetic variations at loci involved in the immune response are risk factors for hepatocellular carcinoma.

Primary liver cancer is the third most common cause of cancer‐related death worldwide, with a rising incidence in Western countries. Little is known about the genetic etiology of this disease. To identify genetic factors associated with hepatocellular carcinoma (HCC) and liver cirrhosis (LC), we conducted a comprehensive, genome‐wide variation analysis in a population of unrelated Asian individuals. Copy number variation (CNV) and single nucleotide polymorphisms (SNPs) were assayed in peripheral blood with the high‐density Affymetrix SNP6.0 microarray platform. We used a two‐stage discovery and replication design to control for overfitting and to validate observed results. We identified a strong association with CNV at the T‐cell receptor gamma and alpha loci (P < 1 × 10−15) in HCC cases when contrasted with controls. This variation appears to be somatic in origin, reflecting differences between T‐cell receptor processing in lymphocytes from individuals with liver disease and healthy individuals that is not attributable to chronic hepatitis virus infection. Analysis of constitutional variation identified three susceptibility loci including the class II MHC complex, whose protein products present antigen to T‐cell receptors and mediate immune surveillance. Statistical analysis of biologic networks identified variation in the “antigen presentation and processing” pathway as being highly significantly associated with HCC (P = 1 × 10−11). SNP analysis identified two variants whose allele frequencies differ significantly between HCC and LC. One of these (P = 1.74 × 10−12) lies in the PTEN homolog TPTE2. Conclusion: Combined analysis of CNV, individual SNPs, and pathways suggest that HCC susceptibility is mediated by germline factors affecting the immune response and differences in T‐cell receptor processing. (HEPATOLOGY 2010)

Discovery Analysis of TCGA Data Reveals Association between Germline Genotype and Survival in Ovarian Cancer Patients

BACKGROUND Ovarian cancer remains a significant public health burden, with the highest mortality rate of all the gynecological cancers. This is attributable to the late stage at which the majority of ovarian cancers are diagnosed, coupled with the low and variable response of advanced tumors to standard chemotherapies. To date, clinically useful predictors of treatment response remain lacking. Identifying the genetic determinants of ovarian cancer survival and treatment response is crucial to the development of prognostic biomarkers and personalized therapies that may improve outcomes for the late-stage patients who comprise the majority of cases. METHODS To identify constitutional genetic variations contributing to ovarian cancer mortality, we systematically investigated associations between germline polymorphisms and ovarian cancer survival using data from The Cancer Genome Atlas Project (TCGA). Using stage-stratified Cox proportional hazards regression, we examined >650,000 SNP loci for association with survival. We additionally examined whether the association of significant SNPs with survival was modified by somatic alterations. RESULTS Germline polymorphisms at rs4934282 (AGAP11/C10orf116) and rs1857623 (DNAH14) were associated with stage-adjusted survival (p= 1.12e-07 and 1.80e-07, FDR q= 1.2e-04 and 2.4e-04, respectively). A third SNP, rs4869 (C10orf116), was additionally identified as significant in the exome sequencing data; it is in near-perfect LD with rs4934282. The associations with survival remained significant when somatic alterations. CONCLUSIONS Discovery analysis of TCGA data reveals germline genetic variations that may play a role in ovarian cancer survival even among late-stage cases. The significant loci are located near genes previously reported as having a possible relationship to platinum and taxol response. Because the variant alleles at the significant loci are common (frequencies for rs4934282 A/C alleles = 0.54/0.46, respectively; rs1857623 A/G alleles = 0.55/0.45, respectively) and germline variants can be assayed noninvasively, our findings provide potential targets for further exploration as prognostic biomarkers and individualized therapies.

Alview: Portable Software for Viewing Sequence Reads in BAM Formatted Files

The name Alview is a contraction of the term Alignment Viewer. Alview is a compiled to native architecture software tool for visualizing the alignment of sequencing data. Inputs are files of short-read sequences aligned to a reference genome in the SAM/BAM format and files containing reference genome data. Outputs are visualizations of these aligned short reads. Alview is written in portable C with optional graphical user interface (GUI) code written in C, C++, and Objective-C. The application can run in three different ways: as a web server, as a command line tool, or as a native, GUI program. Alview is compatible with Microsoft Windows, Linux, and Apple OS X. It is available as a web demo at https://cgwb.nci.nih.gov/cgi-bin/alview. The source code and Windows/Mac/Linux executables are available via https://github.com/NCIP/alview.

Chromatic: WebAssembly-Based Cancer Genome Viewer:

Chromatic is a novel web-browser tool that enables researchers to visually inspect genomic variations identified through next-generation sequencing of cancer data sets to determine whether such calls are, in fact, valid. It is the first cancer bioinformatics tool developed using WebAssembly technology, which comprises a portable, low-level byte code format that provides for the rapid execution of programs within supported web browsers. It has been designed expressly for ease of use by scientists without extensive expertise in bioinformatics.

Transcriptional Alterations in Hereditary and Sporadic Nonfunctioning Pancreatic Neuroendocrine Tumors According to Genotype.

Nonfunctioning pancreatic neuroendocrine tumors (NFPanNETs) may be sporadic or inherited because of germline mutations associated with von Hippel‐Lindau disease (VHL) or multiple endocrine neoplasia type 1 (MEN1). The clinical behavior of NFPanNETs is difficult to predict, even in tumors of the same stage and grade. The authors analyzed genotype‐specific patterns of transcriptional messenger RNA (mRNA) levels of NFPanNETs to understand the molecular features that determine PanNET phenotype.

Abstract 63: Alview (ALignment VIEWer): A software tool to visualize next generation sequencing (NGS) data

Proceedings: AACR 106th Annual Meeting 2015; April 18-22, 2015; Philadelphia, PA Widespread use of NGS has led to the increasing sizes of high throughput sequencing data of various types from different platforms. Review of alignment data by experienced genomics researchers is an important quality control element in this process. Key to this activity is visual inspection of the sequencing data in order to eliminate false positives and document the likelihood of true positives. Furthermore, such manual, or visual, examination of data must occur at extremely rapid speeds. Alview (for “ALignment VIEWer”) is a compiled to native architecture software tool for visualizing the alignment of sequencing data. The inputs data are in the SAM/BAM format short read sequences that are aligned to a reference genome sequence. Outputs are images’ representing these short reads aligned to the reference genome. Alview is written in portable C with optional Graphical User Interface (GUI) code written in C,C++ or Objective C. Alview can be compiled to run in three different ways: (1) as a webserver, (2) as a command line tool, or (3) Alview is executable as a native graphical user interface. Alview is compatible with Microsoft Windows, Linux, and Apple OS X. Our new tool saves time and addresses specific regions of interest (for example, regions containing known or novel mutations or SNPS) and peruses these regions in the manner of a “slideshow”, enabling the scanning of a large number of samples in a short time Citation Format: Daoud Meerzaman, Richard Finney, Qing-Rong Chen, Cu Nguyen, Chih Hao Hsu, Barbra Dunn. Alview (ALignment VIEWer): A software tool to visualize next generation sequencing (NGS) data. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 63. doi:10.1158/1538-7445.AM2015-63