Genomic Identification Of Significant Targets In Cancer Research Articles

TGF-β signaling-related signature for predicting prognosis and therapeutic response in lower-grade glioma.

Low-grade glioma (LGG) is a tumor that includes World Health Organization (WHO) grade II and III glioma, the treatment of which consistently results in relapse and drug resistance. Transforming growth factor-beta (TGF-β) is a multifunctional cytokine that regulates various cellular processes, which is found to be abnormal in tumors and promotes glioma development and progression. In this study, we aimed to systematically evaluate the importance of the genes associated with TGF-β in LGG and discover the role of these genes in the prognosis and treatment response of LGG. We used the "Bioconductor Limma" and "consensusClusterplus" R packages to screen differential and prognostic TGF-β-related genes. The R package "GSVA" was used to estimate the infiltration of immune cells and metabolism signature. The drug sensitivity for each TGF-β subtype was assessed by the R package "pRRophetic". The Genomic Identification of Significant Targets in Cancer (GISTIC) algorithm was used to assess the copy number variation (CNV). The onco-print tool of the "complexheatmap package" was employed to visualize the somatic mutation and copy number alteration (CNA) among TGF clusters. We reported three subtypes (A, B, and C) of LGG according to the classification of TGF-β-related genes, where subtype A showed the best prognosis. Subtype B was highly enriched in immune cells. Somatic variations were observed to be diverse in all of the three TGF-β subtypes. Furthermore, another three genes (SHA, AC062021.1, and SNCG) related to TGF-β were identified, which can be a superior predictor of prognosis with a risk score. LGG can be divided into three subtypes based on TGF-β signaling-related genes with distinct immune infiltration, metabolism, somatic variations, and prognosis.

The extended concurrent genes signature for disease-free survival in breast cancer

Previously we had identified concurrent genes, which highlighted the interplay between copy number variation (CNV) and differential gene expression (GE) for Han Chinese breast cancers. The merit of the approach is to discovery biomarkers not identifiable by conventional GE only data, for which phenotype-correlation or gene variability is the criteria of gene selection. Thirty-one comparative genomic hybridization (CGH) and 83GE microarrays were performed, with 29 breast cancers assayed from both platforms. Potential targets were revealed by Genomic Identification of Significant Targets in Cancer (GISTIC) from CGH arrays. Concurrent genes and genes with significant GISTIC scores were used to derive the extended concurrent genes signature, which was consensus from leading edge analysis across all studies and a supervised partial least square (PLS) regression predictive model of disease-free survival was constructed. There were 1584 concurrent genes from 29 samples with both CGH and GE microarrays. Enriched concurrent genes sets for disease-free survival were identified independently from 83GE arrays and another one with Han Chinese origin as well as three studies of Western origin. For five studies with disease-free survival follow up, prognostic discrepancy was observed between predicted high-risk and low-risk group patients. We concluded that through parallel analyses of CGH and GE microarrays, the proposed extended concurrent gene expression signature can identify biomarkers with prognostic values.

Bioinformatic Analysis Reveals GSG2 as a Potential Target for Breast Cancer Therapy.

ObjectiveTo explore the potential role of GSG2 in breast cancer progression.MethodsThe mRNA expression, DNA copy number and clinical data used in this study were obtained from the TCGA data portal. The copy number variations (CNVs) thresholds were determined according to the set of discrete copy number calls provided by Genomic Identification of Significant Targets in Cancer (GISTIC).ResultsThe mRNA expression level of GSG2 in 112 breast cancer tissues was much higher than that in adjacent normal tissues. GSG2 was significantly upregulated in stage II compared with stage I, and there was no differential expression of GSG2 between tumors with or without metastasis. Heterozygous deletion occupied 57.1% of CNVs for GSG2 gene in breast cancer samples. Patients with higher GSG2 expression tended to suffer from poorer prognosis.ConclusionOur profiling analysis indicated the overexpression of GSG2 might play an important role in breast cancer development, suggesting that GSG2 could be a new target for breast cancer treatment, making GSG2 inhibitors becoming potential drugs for breast cancer therapy.

Comprehensive Molecular Profiling of Idiopathic Erythrocytosis By Genetic Ancestry

Introduction: Idiopathic erythrocytosis (IE) is characterized by a persistently elevated hemoglobin, equivocal erythropoietin (EPO) levels, absence of janus kinase 2 (JAK2) mutations suggestive of polycythemia vera (PV) and no secondary cause. One study used a targeted 21 gene next-generation sequencing panel and identified novel variants in known erythrocytosis-related genes as well as novel genes associated with the oxygen-sensing pathway. However, expanded sequencing of blood and matched tissue samples in a large ethnically diverse group of IE patients has not been performed. Methods: All patients signed informed consent to participate in an observational study approved by the Institutional Review Board; they provide blood and buccal mucosa samples at study entry and at 24-month follow-up. Patients were enrolled if JAK2 testing and a complete work up for secondary causes was negative. They were required to have hemoglobin levels greater than 16 g/dL on two occasions or greater than 15 g/dL if undergoing phlebotomy. Our initial sequencing of 20 IE patients was performed utilizing high resolution whole-exome sequencing of circulating blood samples (disease) at a mean coverage of 390x and matched normal (buccal) samples at mean coverage of 300x. To stratify samples by genetic ancestry, we performed a population stratification principle component analysis (PCA) and STRUCTURE using Ancestry Informative Markers derived from 1K Genome Phase1_v3 Exome database. The primary in-silico analysis was performed on the baseline samples from treatment-naïve patients. The whole-exome data was generated in accordance to GATK's best practices with same filters applied as described by Exome Aggregation Consortium. The additional downstream in-silico paired analysis was performed using MutSig2.0 (Mutation Significance) algorithm to determine significant mutations and GISTIC (The Genomic Identification of Significant Targets in Cancer) to identify the significant copy number events, IPA (Ingenuity Pathway Analysis) to determine pathways along with other computational . Results: Median age at baseline was 52 years (range 35-71). Six patients (30%) were female and 14 (70%) were male. Median values and ranges for laboratory parameters at baseline were as follows: WBC 6.6 x 109/L (5-9.7), Hgb 17 g/dL (15.5-19.8), Plt 218 x 109/L (86-374), and EPO level 9.8 IU/L (2-14.3). Three patients had a personal history of malignancy, including 2 with lymphoma. Two patients had a family history of myeloid malignancy (chronic myeloid leukemia and PV). Our ancestry analysis of initial 20 patients with IE identified 6 patients with high European percent ancestry (EUR), 1 patient with high Asian percent ancestry (EAS) and 13 patients with high percent Ad Mixed ancestry (AMR). In our cohort, 60% (12/20) of patients had been also diagnosed with a liver disorder (11 with fatty liver, 1 with cirrhosis) that was not significantly different across populations. We identified, on average, 42 non-silent somatic mutations (not present in the buccal samples) in whole blood across our cohort with no statistical difference (p=0.671) in mutation burden between ancestry groups or between patients with and without liver disease. Age, gender, and ethnicity were not associated with mutation burden. Utilizing MutSig algorithm, we identified a novel candidate gene, CHAF1A, with high mutation prevalence of 30% in patients with IE. Further analysis of mutation landscape identified somatic nonsilent mutations in 25 known oncogenes which were present in at least 10% of patients. Our mutation signatures in IE identified a significant association with failure of double stranded DNA repair. Only one patient had a mutation in TET2. Further analysis of copy number indicated copy number loss in genes such as SETD3 and GSH associated with chromatin assembly which may suggest alterations in chromatin assembly and changes in the epigenome. Our analysis also identified a high number of 9p and 13q gains in patients with IE. Conclusion: In this study, we utilized high-resolution next generation sequencing in association with comprehensive clinical annotation to determine potential molecular drivers of IE in a multi-ethnic population. We identified somatic mutations in a subset of patients which may represent clonal hematopoiesis. Long term follow up of outcomes in this cohort may clarify the significance of these mutations in the pathogenesis of IE. Disclosures No relevant conflicts of interest to declare.

Comparable Genomic Copy Number Aberrations Differ across Astrocytoma Malignancy Grades.

A collection of intracranial astrocytomas of different malignancy grades was analyzed for copy number aberrations (CNA) in order to identify regions that are driving cancer pathogenesis. Astrocytomas were analyzed by Array Comparative Genomic Hybridization (aCGH) and bioinformatics utilizing a Bioconductor package, Genomic Identification of Significant Targets in Cancer (GISTIC) 2.0.23 and DAVID software. Altogether, 1438 CNA were found of which losses prevailed. On our total sample, significant deletions affected 14 chromosomal regions, out of which deletions at 17p13.2, 9p21.3, 13q12.11, 22q12.3 remained significant even at 0.05 q-value. When divided into malignancy groups, the regions identified as significantly deleted in high grades were: 9p21.3; 17p13.2; 10q24.2; 14q21.3; 1p36.11 and 13q12.11, while amplified were: 3q28; 12q13.3 and 21q22.3. Low grades comprised significant deletions at 3p14.3; 11p15.4; 15q15.1; 16q22.1; 20q11.22 and 22q12.3 indicating their involvement in early stages of tumorigenesis. Significantly enriched pathways were: PI3K-Akt, Cytokine-cytokine receptor, the nucleotide-binding oligomerization domain (NOD)–like receptor, Jak-STAT, retinoic acid-inducible gene (RIG)-I-like receptor and Toll-like receptor pathways. HPV and herpex simplex infection and inflammation pathways were also represented. The present study brings new data to astrocytoma research amplifying the wide spectrum of changes that could help us identify the regions critical for tumorigenesis.

Childhood supratentorial ependymomas with YAP1-MAMLD1 fusion: an entity with characteristic clinical, radiological, cytogenetic and histopathological features.

Ependymoma with YAP1‐MAMLD1 fusion is a rare, recently described supratentorial neoplasm of childhood, with few cases published so far. We report on 15 pediatric patients with ependymomas carrying YAP1‐MAMLD1 fusions, with their characteristic histopathology, immunophenotype and molecular/cytogenetic, radiological and clinical features. The YAP1‐MAMLD1 fusion was documented by RT‐PCR/Sanger sequencing, and tumor genomes were studied by molecular inversion probe (MIP) analysis. Significant copy number alterations were identified by GISTIC (Genomic Identification of Significant Targets in Cancer) analysis. All cases showed similar histopathological features including areas of high cellularity, presence of perivascular pseudo‐rosettes, small to medium‐sized nuclei with characteristic granular chromatin and strikingly abundant cells with dot‐like cytoplasmic expression of epithelial membrane antigen. Eleven cases presented features of anaplasia, corresponding to WHO grade III. MRI showed large supratentorial multinodular tumors with cystic components, heterogeneous contrast enhancement, located in the ventricular or periventricular region. One of two variants of YAP1‐MAMLD1 fusions was detected in all cases. The MIP genome profiles showed balanced profiles, with focal alterations of the YAP1 locus at 11q22.1–11q21.2 (7/14), MAMLD1 locus (Xp28) (10/14) and losses of chromosome arm 22q (5/14). Most patients were female (13/15) and younger than 3 years at diagnosis (12/15; median age, 8.2 months). Apart from one patient who died during surgery, all patients are alive without evidence of disease progression after receiving different treatment protocols, three without postoperative further treatment (median follow‐up, 4.84 years). In this to date, largest series of ependymomas with YAP1‐MAMLD1 fusions we show that they harbor characteristic histopathological, cytogenetic and imaging features, occur mostly in young girls under 3 years and are associated with good outcome. Therefore, this genetically defined neoplasm should be considered a distinct disease entity. The diagnosis should be confirmed by demonstration of the specific fusion. Further studies on large collaborative series are warranted to confirm our findings.

Amplification of 1q32.1 Refines the Molecular Classification of Endometrial Carcinoma.

Purpose: Molecular classification of endometrial cancer identified distinct molecular subgroups. However, the largest subset of endometrial cancers remains poorly characterized and is referred to as the "nonspecific molecular profile" (NSMP) subgroup. Here, we aimed at refining the classification of this subgroup by profiling somatic copy-number aberrations (SCNAs).Experimental Design: SCNAs were analyzed in 141 endometrial cancers using whole-genome SNP arrays and pooled with 361 endometrial cancers from The Cancer Genome Atlas. Genomic Identification of Significant Targets in Cancer (GISTIC) identified statistically enriched SCNAs and penalized Cox regression assessed survival effects. The prognostic significance of relevant SCNAs was validated using multiplex ligation-dependent probe amplification in 840 endometrial cancers from the PORTEC-1/2 trials. Copy-number status of genes was correlated with gene expression to identify potential cancer drivers. One plausible oncogene was validated in vitro using antisense oligonucleotide-based strategy.Results: SCNAs affecting chromosome 1q32.1 significantly correlated with worse relapse-free survival (RFS) in the NSMP subgroup (HR, 2.12; 95% CI, 1.26-3.59; P = 0.005). This effect was replicated in NSMP endometrial cancers from PORTEC-1/2 (HR, 2.34; 95% CI, 1.17-4.70; P = 0.017). A new molecular classification including the 1q32.1 amplification improved risk prediction of recurrence. MDM4 gene expression strongly correlated with 1q32.1 amplification. Silencing MDM4 inhibited cell growth in cell lines carrying 1q32.1 amplification, but not in those without MDM4 amplification. Vice versa, increasing MDM4 expression in nonamplified cell lines stimulated cell proliferation.Conclusions: 1q32.1 amplification was identified as a prognostic marker for poorly characterized NSMP endometrial cancers, refining the molecular classification of this subgroup. We functionally validated MDM4 as a potential oncogenic driver in the 1q32.1 region. Clin Cancer Res; 23(23); 7232-41. ©2017 AACR.

Functionally-focused algorithmic analysis of high resolution microarray-CGH genomic landscapes demonstrates comparable genomic copy number aberrations in MSI and MSS sporadic colorectal cancer.

Array-based comparative genomic hybridization (aCGH) emerged as a powerful technology for studying copy number variations at higher resolution in many cancers including colorectal cancer. However, the lack of standardized systematic protocols including bioinformatic algorithms to obtain and analyze genomic data resulted in significant variation in the reported copy number aberration (CNA) data. Here, we present genomic aCGH data obtained using highly stringent and functionally relevant statistical algorithms from 116 well-defined microsatellites instable (MSI) and microsatellite stable (MSS) colorectal cancers. We utilized aCGH to characterize genomic CNAs in 116 well-defined sets of colorectal cancer (CRC) cases. We further applied the significance testing for aberrant copy number (STAC) and Genomic Identification of Significant Targets in Cancer (GISTIC) algorithms to identify functionally relevant (nonrandom) chromosomal aberrations in the analyzed colorectal cancer samples. Our results produced high resolution genomic landscapes of both, MSI and MSS sporadic CRC. We found that CNAs in MSI and MSS CRCs are heterogeneous in nature but may be divided into 3 distinct genomic patterns. Moreover, we show that although CNAs in MSI and MSS CRCs differ with respect to their size, number and chromosomal distribution, the functional copy number aberrations obtained from MSI and MSS CRCs were in fact comparable but not identical. These unifying CNAs were verified by MLPA tumor-loss gene panel, which spans 15 different chromosomal locations and contains 50 probes for at least 20 tumor suppressor genes. Consistently, deletion/amplification in these frequently cancer altered genes were identical in MSS and MSI CRCs. Our results suggest that MSI and MSS copy number aberrations driving CRC may be functionally comparable.

A systematic comparison of copy number alterations in four types of female cancer.

BackgroundDetection and localization of genomic alterations and breakpoints are crucial in cancer research. The purpose of this study was to investigate, in a methodological and biological perspective, different female, hormone-dependent cancers to identify common and diverse DNA aberrations, genes, and pathways.MethodsIn this work, we analyzed tissue samples from patients with breast (n = 112), ovarian (n = 74), endometrial (n = 84), or cervical (n = 76) cancer. To identify genomic aberrations, the Circular Binary Segmentation (CBS) and Piecewise Constant Fitting (PCF) algorithms were used and segmentation thresholds optimized. The Genomic Identification of Significant Targets in Cancer (GISTIC) algorithm was applied to the segmented data to identify significantly altered regions and the associated genes were analyzed by Ingenuity Pathway Analysis (IPA) to detect over-represented pathways and functions within the identified gene sets.Results and DiscussionAnalyses of high-resolution copy number alterations in four different female cancer types are presented. For appropriately adjusted segmentation parameters the two segmentation algorithms CBS and PCF performed similarly. We identified one region at 8q24.3 with focal aberrations that was altered at significant frequency across all four cancer types. Considering both, broad regions and focal peaks, three additional regions with gains at significant frequency were revealed at 1p21.1, 8p22, and 13q21.33, respectively. Several of these events involve known cancer-related genes, like PPP2R2A, PSCA, PTP4A3, and PTK2. In the female reproductive system (ovarian, endometrial, and cervix [OEC]), we discovered three common events: copy number gains at 5p15.33 and 15q11.2, further a copy number loss at 8p21.2. Interestingly, as many as 75% of the aberrations (75% amplifications and 86% deletions) identified by GISTIC were specific for just one cancer type and represented distinct molecular pathways.ConclusionsOur results disclose that some prominent copy number changes are shared in the four examined female, hormone-dependent cancer whereas others are definitive to specific cancer types.Electronic supplementary materialThe online version of this article (doi:10.1186/s12885-016-2899-4) contains supplementary material, which is available to authorized users.

In-Depth Molecular Profiling of Multiple Myeloma in African Americans

Introduction: Multiple Myeloma (MM) is a complex malignancy of plasma cells well-described hyperdyploidy, and immunoglobulin gene rearrangements. To promote rapid advances in the field, Multiple Myeloma Research Foundation (MMRF) initiative is an intensive and comprehensive longitudinal study (CoMMpass) designed to create a rich discovery ecosystem to through in-depth clinical and molecular profiling to understand the molecular perturbations of the disease in the context of therapy. The large study population empowered us to stratify mutational landscapes among different ethnicities to influence on broader disparities in tumor dynamics.Methods: Clinical data, tumor/normal sample collection, and mutational landscape analysis described in this abstract are derived from MMRF CoMMpass IA7 release that is composed of self-identified 93 African American (AA) and 377 European American (EA). The post-processing and primary analysis was done on baseline samples only. Whole exome sequencing was analyzed for the detection of somatic events. Secondary analysis was performed using MutSigCV (Mutation Significance) algorithm and GISTIC (The Genomic Identification of Significant Targets in Cancer) to determine the significance of coding mutations and copy number events.Results: Our preliminary comparison analysis of CoMMpass IA7 data demonstrated that overall there was no statistical difference (p=0.5973) in nonsilent mutation burden between the two stratified groups, AA (μ=63.9 mutations/patient) vs EA (μ=73.7 mutations/patient). However, we have observed several notable differences. The most notable population difference (p<0.0001) was TP53 mutation occurrence, which was more common in EA 5.6% (21/377) compared AA 2.1% (2/93).Furthermore, MutSig analysis also revealed a novel candidate PTCHD3 (p = 7.07E-06, q = 3.33E-02) with 6% occurrence in AA compared to only 0.04% in EA. Furthermore, we looked at mutation occurrence difference of at least 5 fold between the two stratified populations. We have identified several additional genes that have higher mutation frequencies in tumors from AA patients including: ANKRD26, BCL7A, BRWD3. Interestingly, majority is implicated in epigenetic regulatory mechanisms.Moreover, despite the complex karyotype in MM translocations, our analysis demonstrated a lower frequency of 14q32 translocations in tumors from AA patients (10%) compared to tumors from EA patients (37%). These data would independently validate our previously reported differences in 14q32 breakpoints between these two populations.Conclusion: Data from this comprehensive diverse multi-institutional longitudinal study has afforded us the opportunity to study population differences among MM patients in an unprecedented way. Taking advantage of high quality, high-resolution whole exome and whole-genome data has allowed us to identify potential differences in the genomic and molecular landscape of MM from AA and EA patients. These data may help us further understand the incidence and outcomes among patients from these populations. As CoMMpass continues to mature these datasets will be retested that may result in some of these preliminary reported events to either level off, or increase in power. DisclosuresMulligan:Millennium Pharmaceuticals, Inc., Cambridge, MA, USA, a wholly owned subsidiary of Takeda Pharmaceutical Company Limited: Employment. Lonial:Janssen: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Millennium: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Onyx: Consultancy, Research Funding. Keats:Translational Genomic Research Institute: Employment.

Genome wide DNA copy number analysis in cholangiocarcinoma using high resolution molecular inversion probe single nucleotide polymorphism assay

In order to study molecular similarities and differences of intrahepatic (IH-CCA) and extrahepatic (EH-CCA) cholangiocarcinoma, 24 FFPE tumor samples (13 IH-CCA, 11 EH-CCA) were analyzed for whole genome copy number variations (CNVs) using a new high-density Molecular Inversion Probe Single Nucleotide Polymorphism (MIP SNP) assay.Common in both tumor subtypes the most frequent losses were detected on chromosome 1p, 3p, 6q and 9 while gains were mostly seen in 1q, 8q as well as complete chromosome 17 and 20. Applying the statistical GISTIC (Genomic Identification of Significant Targets in Cancer) tool we identified potential novel candidate tumor suppressor- (DBC1, FHIT, PPP2R2A) and oncogenes (LYN, FGF19, GRB7, PTPN1) within these regions of chromosomal instability.Next to common aberrations in IH-CCA and EH-CCA, we additionally found significant differences in copy number variations on chromosome 3 and 14. Moreover, due to the fact that mutations in the Isocitrate dehydrogenase (IDH-1 and IDH-2) genes are more frequent in our IH-CCA than in our EH-CCA samples, we suggest that the tumor subtypes have a different molecular profile.In conclusion, new possible target genes within regions of high significant copy number aberrations were detected using a high-density Molecular Inversion Probe Single Nucleotide Polymorphism (MIP SNP) assay, which opens a future perspective of fast routine copy number and marker gene identification for gene targeted therapy.

Abstract 1102: Integrated genomic analysis of clear-cell ovarian cancer identifies PRKCI as a therapeutic target

Abstract Clear-cell ovarian cancer (CCOC) is the third most common subtype of ovarian cancer. CCOC is more resistant to standard chemotherapy and has a poorer prognosis than serous and endometrioid histotypes. Through a comprehensive genomic approach, genes that are responsible for the aggressive behavior of CCOC were identified and their mechanism explored. Genome-wide DNA copy number alterations were measured in 13 CCOC cell lines using high-resolution oligonucleotide array comparative genomic hybridization (Agilent 105k Human Genome CGH Microarray). Genomic identification of significant targets in cancer (GISTIC) analysis identified 16 amplicons containing 391 genes. Integrating whole genome expression data from human CCOC tumor specimens and normal ovarian surface epithelium specimen revealed 45 amplified genes showed mRNA overexpression in CCOC tumor specimens. Among the 45 genes, protein kinase C iota (PRKCI) was amplified in 9/13 CCOC cell lines and was overexpressed (6.7 fold) in CCOC tumor specimens. Cell proliferation, migration/invasion and tumorigenicity were suppressed by knockdown of PRKCI in PRKCI-overexpressing cells (KOC-7c and OVISE) and were enhanced by overexpression of PRKCI in cells with low endogenous levels of PRKCI (ES2 and TOV21G). Targeted inhibition of PRKCI with sodium aurothiomalate (ATM) suppressed cell growth, cell migration/invasion and tumorigenicity in CCOC cells. Western blot analysis revealed that PRKCI oncogenic function was mediated through MEK/ERK and PI3K/Akt signaling pathways. Thus, PKRCI can be considered as a potential novel CCOC-specific target; not only it inhibits malignant behavior of CCOC cells, but also induces the two major molecular pathways regulating cisplatin resistance. The results from the present study indicate that our comprehensive genomic analysis of CCOC allows identification of therapeutic targets responsible for the aggressive behavior specific of this ovarian cancer histotype and thus improve its therapeutic outcome. Citation Format: Tsun Yee Tsang, Gayatry Mohapatra, Hiroaki Itamochi, Samuel C. Mok, Michael J. Birrer. Integrated genomic analysis of clear-cell ovarian cancer identifies PRKCI as a therapeutic target. [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 1102. doi:10.1158/1538-7445.AM2015-1102

Abstract 4873: Epicopy: Measuring DNA copy number variation using high-density methylation microarrays

Abstract Background: Cancers exploit changes in both genomic copy number and DNA methylation to promote growth and escape tumor-suppressor pathways. Under the 2-hit hypothesis, a single gene is likely to be altered by multiple mechanisms at the same time and integrated analysis can sharpen the focus on the most likely drivers. Requiring larger amounts of input material and imposing additional costs may limit multiplatform analysis, especially in studies using archival tissues with long clinical follow-up information where the nucleic acids are degraded and yields are generally lower than are obtained from fresh tissues. Taking advantage of similarities between methylation arrays and SNP arrays, we developed Epicopy, a robust computational method to identify DNA copy number variation (CNV) using high-density Illumina Human Methylation 450K methylation microarrays, thereby delivering two complementary genetic and epigenetic profiles from a single chip. Methods: Epicopy was developed using data from thyroid carcinoma samples arrayed by The Cancer Genome Atlas (TCGA) and subsequently validated on breast and lung small cell carcinoma TCGA datasets. Using Epicopy, we identified circumstances where CNV information can be reliably measured by methylation microarrays. Results: Using TCGA SNP microarrays as the gold standard to assess the performance of methylation derived CNV data from the thyroid, breast, and lung small cell carcinoma datasets, we showed that Epicopy is able to detect CNVs identified by SNP arrays at a sensitivity of 0.69 and specificity of 0.90. Frequently occurring CNVs identified using Genomic Identification of Significant Targets in Cancer (GISTIC), were identified with even higher accuracy. Conclusion: Epicopy provides a robust method to obtain both copy number and methylation information from a single methylation microarray experiment and will add value to methylation microarrays at no additional cost to the user. Tools to highlight regions of high sensitivity and specificity will also be provided to help users decide on the feasibility of using Epicopy to identify CNVs in regions of interest. Epicopy is implemented in the R statistical language and will be made available as a freestanding package as part of the Bioconductor bioinformatics software project. Citation Format: Soonweng Cho, Hyun-seok Kim, Leslie M. Cope, Christopher B. Umbricht. Epicopy: Measuring DNA copy number variation using high-density methylation microarrays. [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 4873. doi:10.1158/1538-7445.AM2015-4873

Integrated exon level expression analysis of driver genes explain their role in colorectal cancer.

Integrated analysis of genomic and transcriptomic level changes holds promise for a better understanding of colorectal cancer (CRC) biology. There is a pertinent need to explain the functional effect of genome level changes by integrating the information at the transcript level. Using high resolution cytogenetics array, we had earlier identified driver genes by ‘Genomic Identification of Significant Targets In Cancer (GISTIC)’ analysis of paired tumour-normal samples from colorectal cancer patients. In this study, we analyze these driver genes at three levels using exon array data – gene, exon and network. Gene level analysis revealed a small subset to experience differential expression. These results were reinforced by carrying out separate differential expression analyses (SAM and LIMMA). ATP8B1 was found to be the novel gene associated with CRC that shows changes at cytogenetic, gene and exon levels. Splice index of 29 exons corresponding to 13 genes was found to be significantly altered in tumour samples. Driver genes were used to construct regulatory networks for tumour and normal groups. There were rearrangements in transcription factor genes suggesting the presence of regulatory switching. The regulatory pattern of AHR gene was found to have the most significant alteration. Our results integrate data with focus on driver genes resulting in highly enriched novel molecules that need further studies to establish their role in CRC.

Abstract 3412: Distinct copy number alterations in genomes of oral cavity squamous cell carcinomas

Abstract Oral cavity squamous cell carcinoma (OSCC) is one of the most common cancers in Taiwan and worldwide. Despite recent progress in the diagnosis and therapeutic modalities for OSCC, the 5-year survival rate has not been improved in recent two decades. In order to provide some clues for clinical management of OSCC, 72 advanced-stage OSCCs were analyzed using two microarray platforms (26 cases with Affymetrix 500K and 46 cases with Affymetrix SNP 6.0). Genomic copy number was derived from calculating the intensity ratio between the OSCC and a set of normal DNAs from HapMap project. Segmented copy numbers for each tumor were inferred with the hidden markov model using the Partek GS software and circular binary segmentation using GenePattern pipeline. Genomic Identification of Significant Targets in Cancer (GISTIC) analysis was used to identify significant copy number alterations (CNAs) using a Q-value cutoff of 0.25. With this approach, 41 (2 gain and 39 loss) and 32 (4 gain and 28 loss) significant regions were distinguished from 500K and SNP 6.0 platform, respectively. Among them, 12 (2 gains (7p11.2 and 11q13.3) and 10 losses (2q23.3-q24.2, 3p14.2-p12.1, 4q35.2, 7q33-q34, 9p21.3, 11q22.3-q24.3, 16q23.1, 18q11.2-q22.3, 21q21.1 and 21q22.3)) CNAs were identical in these two platforms. Two gain regions contained the well known oncogene EGFR (7p11.2) and CCND1 (11q13.3) and 10 deletion regions resides several known cancer suppressor genes such as FHIT (3p14.2-p12.1), FAT1 (4q35.1), CDKN2A (9p21.3) and ATM (11q22.3-q24.3). Among them, gain of 11q13.3 was correlated significantly with lymph node metastasis and loss of 4q35.2 was significantly associated with lymph node extracapsular spread (LNECS) and poor disease-free survival. Copy number gains of EGFR and CCND1 were further confirmed by fluorescence in situ hybridization and TaqMan CN assay (Hs01818912_cn and Hs02353610_cn), respectively. We found that the concordance rate was 74.63% for EGFR and 77.78% for CCND1. To further explore the clinical value of copy number gains of EGFR and CCND1 in OSCC, 257 OSCC cases were analyzed. Preliminary results indicated that gains of CCND1 were significantly associated with tumor differentiation, lymph node metastasis and LNECS; while amplification of EGFR gene was significantly associated with tumor stage and lymph node metastasis but not LNECS. Furthermore, gains of CCND1 were significantly associated with poor disease-free and overall survival. On the other hand, amplification of EGFR was not associated with either disease-free or overall survival. Taken together, we have revealed the significant CNAs of OSCCs in Taiwan and confirmed the amplification of two important genes (CCND1 and EGFR) in 257 OSCCs. Thus, current genome-wide CNAs analysis provides clues for future characterization of important oncogenes and tumor suppressor genes associated with the behaviors of the disease. Citation Format: Huei-Tzu Chien, Shiang-Fu Huang, I-How Chen, Chun-Ta Liao, Hung-Ming Wang, Sou-De Cheng, Ling-Ling Hsieh. Distinct copy number alterations in genomes of oral cavity squamous cell carcinomas. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3412. doi:10.1158/1538-7445.AM2014-3412

Abstract 1400: Extended concurrent gene signatures of ER, HER2 and disease-free survival in breast cancers

Abstract Our recent work had identified concurrent gene signatures which highlighted the interplay between copy number variation (CNV) and differential gene expression (GE) for Han Chinese breast cancers. The merit of the approach is the discovery of biomarkers not readily identified by conventional GE only data, for which phenotype-correlation or gene variability is the criteria of gene selection. A total of 31 array CGH and 83 GE arrays (29 samples with data from both platforms) were performed. Potential targets of cancer therapy were revealed by Genomic Identification of Significant Targets in Cancer (GISTIC) from 31 array CGH. We used these concurrent genes as well as genes with significant GISTIC scores to derive signatures associated with clinical ER, HER2 status, and disease-free survival. The most common gain regions were 1q21.2 and 17q12-q21.1 while the most common lost region was 22q11.23. In subgroup analysis, recurrent gains for ER positive cancers were 8p23.1, and 8p11.23-11.21. For HER2 overexpressing tumors, recurrent gain was 17q12-21.1 and recurrent losses were 8p11.22, 8p12, and 8p23.1. We identified 1,584 concurrent genes from 29 samples assayed for both array CGH and GE microarrays, and enriched concurrent gene sets for ER, HER2 and disease-free survival were identified independently from our 83 GE arrays (GSE48391) and two series with Han Chinese origin (GSE5460 and GSE20685) as well as three studies of Western countries (GSE7390, GSE2034 and GSE3494). Signature genes were consensus genes from leading edge analysis across all studies, and we used supervised partial least square (PLS) regression to derived predictive model of clinical ER, HER2 and disease-free survival with each signature gene further weighted by the coefficient of concurrence as an additive tuning parameter. The predictive accuracy was 92.3% for ER and 84.6% for HER2 in 208 Han Chinese breast cancers and was 87.3% for ER in 735 breast cancers in Western countries. For five studies with disease-free survival data (no survival data for GSE5460), prognostic discrepancy was observed in four studies except GSE3493 between high-risk and low-risk patients predicted with the concurrent signature. We conclude that parallel analysis of CGH and microarray data, in conjunction with known gene expression patterns, can be used to identify biomarkers with prognostic values in breast cancer. Citation Format: Chi-Cheng Huang, Shih-Hsin Tu, Ching-Shui Huang, Heng-Hui Lien, Liang-Chuan Lai, Eric Y. Chuang. Extended concurrent gene signatures of ER, HER2 and disease-free survival in breast cancers. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1400. doi:10.1158/1538-7445.AM2014-1400

Genome‐wide analysis of esophageal adenocarcinoma yields specific copy number aberrations that correlate with prognosis

The incidence of esophageal adenocarcinoma (EAC) has been increasing rapidly for the past 3 decades in Western (Caucasian) populations. Curative treatment is based around esophagectomy, which has a major impact on quality of life. For those suitable for treatment with curative intent, 5-year survival is ∼30%. More accurate prognostic tools are therefore needed, and copy number aberrations (CNAs) may offer the ability to act as prospective biomarkers in this regard. We performed a genome-wide examination of CNAs in 54 samples of EAC using single-nucleotide polymorphism (SNP) arrays. Our aims were to describe frequent regions of CNA, to define driver CNAs, and to identify CNAs that correlated with survival. Regions of frequent amplification included oncogenes such as EGFR, MYC, KLF12, and ERBB2, while frequently deleted regions included tumor suppressor genes such as CDKN2A/B, PTPRD, FHIT, and SMAD4. The genomic identification of significant targets in cancer (GISTIC) algorithm identified 24 regions of gain and 28 regions of loss that were likely to contain driver changes. We discovered 61 genes in five regions that, when stratified by CNA type (gain or loss), correlated with a statistically significant difference in survival. Pathway analysis of the genes residing in both the GISTIC and prognostic regions showed they were significantly enriched for cancer-related networks. Finally, we discovered that copy-neutral loss of heterozygosity is a frequent mechanism of CNA in genes currently targetable by chemotherapy, potentially leading to under-reporting of cases suitable for such treatment.

Genome‐wide analysis of DNA copy number alterations and loss of heterozygosity in intracranial germ cell tumors

Intracranial germ cell tumors (GCTs) are rare and heterogeneous with very little is known about their pathogenesis and underlying genetic abnormalities. In order to identify candidate genes and pathways which are involved in the pathogenesis of these tumors, we have profiled 62 intracranial GCTs for DNA copy number alterations (CNAs) and loss of heterozygosity (LOH) by using single nucleotide polymorphism (SNP) array and quantitative real time PCR (qPCR). Initially 27 cases of tumor tissues with matched blood samples were fully analyzed by SNP microarray and qPCR. Statistical analysis using the genomic identification of significant targets in cancer (GISTIC) tool identified 10 regions of significant copy number gain and 11 regions of significant copy number loss. While overall pattern of genomic aberration was similar between germinoma and nongerminomatous germ cell tumors (NGGCTs), a few subtype-specific peak regions were identified. Analysis by SNP array and qPCR was replicated using an independent cohort of 35 cases. Frequent aberrations of CCND2 (12p13) and RB1 (13q14) suggest that Cyclin/CDK-RB-E2F pathway might play a critical role in the pathogenesis of intracranial GCTs. Frequent gain of PRDM14 (8q13) implies that transcriptional regulation of primordial germ cell specification might be an important factor in the development of this tumor.

Integrative analysis of copy number alteration and gene expression profiling in ovarian clear cell adenocarcinoma

Ovarian clear cell adenocarcinoma (Ov-CCA) is a distinctive subtype of ovarian epithelial carcinoma. In this study, we performed array comparative genomic hybridization (aCGH) and paired gene expression microarray of 19 fresh-frozen samples and conducted integrative analysis. For the copy number alterations, significantly amplified regions (false discovery rate [FDR] q <0.05) were 1q21.3 and 8q24.3, and significantly deleted regions were 3p21.31, 4q12, 5q13.2, 5q23.2, 5q31.1, 7p22.1, 7q11.23, 8p12, 9p22.1, 11p15.1, 12p13.31, 15q11.2, 15q21.2, 18p11.31, and 22q11.21 using the Genomic Identification of Significant Targets in Cancer (GISTIC) analysis. Integrative analysis revealed 94 genes demonstrating frequent copy number alterations (>25% of samples) that correlated with gene expression (FDR <0.05). These genes were mainly located on 8p11.21, 8p21.2-p21.3, 8q22.1, 8q24.3, 17q23.2-q23.3, 19p13.3, and 19p13.11. Among the regions, 8q24.3 was found to contain the most genes (30 of 94 genes) including PTK2. The 8q24.3 region was indicated as the most significant region, as supported by copy number, GISTIC, and integrative analysis. Pathway analysis using differentially expressed genes on 8q24.3 revealed several major nodes, including PTK2. In conclusion, we identified a set of 94 candidate genes with frequent copy number alterations that correlated with gene expression. Specific chromosomal alterations, such as the 8q24.3 gain containing PTK2, could be a therapeutic target in a subset of Ov-CCAs.

Genetic markers associated with early cancer‐specific mortality following prostatectomy

This study sought to identify novel effectors and markers of localized but potentially life-threatening prostate cancer (PCa), by evaluating chromosomal copy number alterations (CNAs) in tumors from patients who underwent prostatectomy and correlating these with clinicopathologic features and outcome. CNAs in tumor DNA samples from 125 patients in the discovery cohort who underwent prostatectomy were assayed with high-resolution Affymetrix 6.0 single-nucleotide polymorphism microarrays and then analyzed using the Genomic Identification of Significant Targets in Cancer (GISTIC) algorithm. The assays revealed 20 significant regions of CNAs, 4 of them novel, and identified the target genes of 4 of the alterations. By univariate analysis, 7 CNAs were significantly associated with early PCa-specific mortality. These included gains of chromosomal regions that contain the genes MYC, ADAR, or TPD52 and losses of sequences that incorporate SERPINB5, USP10, PTEN, or TP53. On multivariate analysis, only the CNAs of PTEN (phosphatase and tensin homolog) and MYC (v-myc myelocytomatosis viral oncogene homolog) contributed additional prognostic information independent of that provided by pathologic stage, Gleason score, and initial prostate-specific antigen level. Patients whose tumors had alterations of both genes had a markedly elevated risk of PCa-specific mortality (odds ratio = 53; 95% CI = 6.92-405, P = 1 × 10(-4)). Analyses of 333 tumors from 3 additional distinct patient cohorts confirmed the relationship between CNAs of PTEN and MYC and lethal PCa. This study identified new CNAs and genes that likely contribute to the pathogenesis of localized PCa and suggests that patients whose tumors have acquired CNAs of PTEN, MYC, or both have an increased risk of early PCa-specific mortality.