Somatic Copy Number Aberrations Research Articles

Abstract 781: Modeling the impact of somatic alterations across human cancers

Abstract Large-scale cancer genomics projects like The Cancer Genome Atlas have generated a comprehensive catalog of somatic mutations and copy number aberrations across many tumor types, but the role of most frequently altered genes remains obscure. To better model the impact of these alterations, we developed a novel computational strategy for exploiting parallel phosphoproteomics and mRNA sequencing data for large tumor sets by linking dysregulation of upstream signaling pathways with altered transcriptional response through the transcriptional circuitry. Our modeling allows us to interpret the impact of somatic alterations in terms of functional outcomes such as altered signaling and transcription factor (TF) activity. We used this novel machine learning strategy to train phosphoprotein-TF interaction models across 12 human cancers for which large reverse-phase protein array and RNA-seq data sets are available through TCGA. First, we used this approach to identify shared and cancer-specific roles of TF/signaling regulators across cancer types. Then we performed a statistical analysis to associate frequent somatic aberrations with alterations in inferred TF and signaling protein activities. From our analysis, we gained many novel insights into cancer biology. We identified both known (e.g FOXO1 for breast cancer) and novel TF regulators of cancer (e.g. ELK1 for head and neck cancer). Many of these identified TF regulators were significantly associated with survival outcome in bladder urothelial, renal cell clear and endometrial carcinoma. Next we performed a comprehensive cross-cancer analysis and identified relationships between somatic alterations and downstream transcriptional effects and signaling pathway activation. We observed that specific molecular aberrations have different functional consequences in different cancer types. For example, PIK3CA mutations are associated with altered activities of a diverse set of TFs across cancers that are involved in cell cycle, apoptosis, metabolism and MAPK/ERK signaling. Notably, in cell line models, we validated some of the altered TFs predicted by our model. We showed that PIK3CA mutation leads to ELK1 activation in breast and head and neck cancer models. We further found that different set of TFs are associated with a specific mutation in different cancers due to the different background of genomic aberrations in each cancer. For example, KRAS mutations are associated with a distinct set of TFs depending of cancer-specific co-mutation profiles (e.g. co-mutations of KRAS and TP53 in lung adenocarcinoma and co-mutations of KRAS and APC in colorectal cancer). Our analysis revealed both known and novel interactions of frequently altered genes with signaling pathways and transcriptional programs in a pan-cancer context. Patterns of co-alterations across cancers may provide new insights relevant to targeted therapy and may be crucial to optimizing combination therapies. Citation Format: Hatice U. Osmanbeyoglu, Eneda Toska, José Baselga, Christina Leslie. Modeling the impact of somatic alterations across human cancers. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 781.

Abstract 156: Integrated exome and transcriptome sequencing of primary lung cancers and paired distant metastases

Abstract Background: The precise molecular mechanisms underlying metastasis of nonsmall cell lung cancers (NSCLC) are largely unknown. Two recent studies comparing genomic landscapes of primary NSCLC tumors and paired brain metastases suggested branched evolution, where all metastatic and primary tumors shared a common ancestor yet continued to evolve independently. The integrated genomic and transcriptomic profiles of primary NSCLC and metastases have not been studied in any details. Methods: We performed whole exome sequencing (WES) and RNA sequencing (RNA-seq) of surgically resected primary tumors and paired distant metastases from 7 patients with NSCLC. Results: Totally, 6,945 somatic mutations, including 1,702 non-silent (stop-gain, stop-loss, frameshift, splicing site and nonsynonymous) mutations were identified by WES. Metastases trended to have larger mutation burdens compared to paired primary tumors, although the difference was not statistically different (average 595 mutations per tumor in primary tumors versus 852 mutations per tumor in metastases, respectively, p = 0.54). On average, 51% of all mutations (24% to 93%) were shared between primary tumors and metastases. We identified 14 canonical cancer gene mutations in this cohort of patients, defined as mutations that lead to amino acid changes identical to those found previously in cancer genes or disrupting mutations in tumor suppressor genes, all of which were shared between primary tumors and paired distant metastases. In addition, metastases resembled paired primary NSCLC tumors closely in regard to somatic copy number aberration profiles and mutation signatures. Pathway analysis from RNA-seq data demonstrated that 25 of the 35 signal transduction pathways that were significantly down regulated in metastases relative to primary NSCLC tumors were related to immune activation. Validation study with a larger patient cohort is in progress. Conclusions: Although branched evolution is a common phenomenon during metastasis of NSCLC, majority of canonical cancer gene mutations are probably early molecular events likely acquired before metastasis initiates. Mutation mechanism may be determined early during carcinogenesis and preserved during cancer evolution even at the metastatic sites. Immune suppression may be one characteristic feature of cancer cells of metastatic capacity. Citation Format: Jianjun Zhang, Chia-Chin Wu, Jianhua Zhang, Junya Fujimoto, Xingzhi Song, Xizeng Mao, Huadong Sun, Sahil Seth, Rebecca Thornton, Marcus Coyle, Latasha Little, Curtis Gumbs, Carmen Behrens, Chi-Wan Chow, Erik Sulman, Ganesh Rao, Stephen Swisher, Ignacio Wistuba, John Heymach, Andrew Futreal, Daniel Gomez. Integrated exome and transcriptome sequencing of primary lung cancers and paired distant metastases. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 156.

Abstract 121: Analysis and comparison of somatic copy number alterations in gastric cardia adenocarcinoma and gastric non-cardia adenocarcinoma

Abstract Gastric adenocarcinoma is one of the most common cancer type worldwide. Anatomically it may raise from the cardia or non-cardia part of the stomach and previous studies have shown differential susceptibilities loci and prognosis between gastric cardia adenocarcinoma (GCA) and gastric non-cardia adenocarcinoma (GNCA). To better understand the genomic alterations that drive gastric adenocarcinoma and to investigate the differences of genetic aberration between GCA and GNCA, we analyzed somatic copy-number aberrations in 205 gastric adenocarcinomas resected samples, including 114 GCAs and 91 GNCAs using Illumina Human OmniZhongHua BeadChips. We identified 49 significantly recurrent focal alterations in gastric adenocarcinoma. In addition to those previously reported in stomach cancer, several novel focal changes were also observed, including gain of 11p11.2, 6q23.3, 12p11.1, 5p15.33 and loss of 8p11.22, 9p22.2, 18q22.1, 15q21.2, 17q23.3. A few known or potential oncogenes such as TERT, MYB, and IRS2, were included in the focal amplified regions that were not reported in gastric cancer before. Also, a few potential tumor suppressors were seen in these focal loss regions, including DOK6, BRIP1 and NDST4. Especially, HDC, a gene involved in gastric acid secretory, was harbored in the newly identified focal loss region, 15q21.2. Three focal changes, loss of 20p12.1 (containing MACROD2), 6q26 (containing PARK2), and gain of 11p11.2 (containing CRY2), were identified to correlate to the post-surgery overall survival, which may deserve to be further investigated as the potential prognosis markers. Comparison of somatic copy number alternation patterns revealed that in chromosome arm level, 16p and 5q had distinct copy number status between GCA and GNCA samples. The frequencies of three novel focal changes were significantly different between GCA and GNCA. Furthermore, KRAS amplification, a well characterized gastric adenocarcinoma prognosis marker was associated with worse clinical outcome in GNCA, but not in GCA. Taken together, these results provided novel candidate oncogenes or tumor suppressors for gastric adenocarcinoma and different features in structural alterations between GCA and GNCA, which potentially inform novel opportunities for targeted therapeutic interventions. Citation Format: Manjiao Liu, Zhen Liu, Jian Bai, Hong Cai, Yang Ke, Changqing Zeng. Analysis and comparison of somatic copy number alterations in gastric cardia adenocarcinoma and gastric non-cardia adenocarcinoma. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 121.

Cells Comprising the Prostate Cancer Microenvironment Lack Recurrent Clonal Somatic Genomic Aberrations.

Prostate cancer-associated stroma (CAS) plays an active role in malignant transformation, tumor progression, and metastasis. Molecular analyses of CAS have demonstrated significant changes in gene expression; however, conflicting evidence exists on whether genomic alterations in benign cells comprising the tumor microenvironment (TME) underlie gene expression changes and oncogenic phenotypes. This study evaluates the nuclear and mitochondrial DNA integrity of prostate carcinoma cells, CAS, matched benign epithelium and benign epithelium-associated stroma by whole-genome copy-number analyses, targeted sequencing of TP53, and FISH. Array comparative genomic hybridization (aCGH) of CAS revealed a copy-neutral diploid genome with only rare and small somatic copy-number aberrations (SCNA). In contrast, several expected recurrent SCNAs were evident in the adjacent prostate carcinoma cells, including gains at 3q, 7p, and 8q, and losses at 8p and 10q. No somatic TP53 mutations were observed in CAS. Mitochondrial DNA (mtDNA) extracted from carcinoma cells and stroma identified 23 somatic mtDNA mutations in neoplastic epithelial cells, but only one mutation in stroma. Finally, genomic analyses identified no SCNAs, LOH, or copy-neutral LOH in cultured cancer-associated fibroblasts, which are known to promote prostate cancer progression in vivo The gene expression changes observed in prostate cancer-adjacent stroma and the attendant contribution of the stroma to the development and progression of prostate cancer are not due to frequent or recurrent genomic alterations in the TME.

Abstract 45: Detection of focal somatic copy number variants in whole genome, whole exome, and targeted next-generation sequencing data of tumor/normal pairs

Abstract We describe the development and validation of an analysis pipeline for detection of focal somatic copy number aberrations from next-generation sequencing (NGS) data. In the clinical setting, tumor samples may be derived from historical tissue or from recently collected fresh frozen biopsies. DNA extracted from samples preserved as formalin-fixed, paraffin-embedded (FFPE) tissue are often highly degraded. We describe challenges inherent to sequencing different tissue sources and algorithmic approaches for optimizing detection of focal alterations in these samples with a high degree of accuracy. The first area of optimization takes into account clonal or fragment coverage based on user-defined intervals by accounting for coverage between paired-end reads. Normalized log2 fold-changes between tumor and normal samples are then calculated and a smoothing window is applied. In addition, we utilize tumor allele frequencies of known heterozygous germline SNPs identified within the normal to both evaluate potential false positives and correct biases. Lastly, a segmentation algorithm (circular binary segmentation as implemented in DNAcopy package1) is applied to summarize the individual log2 fold-changes into intervals with a constant copy number state. The results from the segmentation algorithm are then annotated and reformatted into the VCF format. We have analytically optimized and validated our algorithm across a series of samples with known alterations for implementation on both clinical and research samples. 1. Seshan VE and Olshen A. DNAcopy: DNA copy number data analysis. R package version 1.40.0. Citation Format: Jessica Aldrich, Jonathan J. Keats, Winnie S. Liang, John D. Carpten, David W. Craig. Detection of focal somatic copy number variants in whole genome, whole exome, and targeted next-generation sequencing data of tumor/normal pairs. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Integrating Clinical Genomics and Cancer Therapy; Jun 13-16, 2015; Salt Lake City, UT. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(1_Suppl):Abstract nr 45.

Unbiased Detection of Somatic Copy Number Aberrations in cfDNA of Lung Cancer Cases and High-Risk Controls with Low Coverage Whole Genome Sequencing.

Molecular profiling using low coverage whole genome sequencing of cell free DNA (cfDNA) represents a non-targeted approach to identify multiple somatic copy number alterations (SCNA) across different lung cancer subtypes. We aim to establish that SCNA can be detected in cfDNA of lung cancer cases.Standard protocols were followed to process matched cfDNA, formalin-fixed paraffin embedded (FFPE) tumour and lymphocyte DNA. Copy number profiles for cfDNA or FFPE DNA were normalised to profiles from matched lymphocyte DNA with the software CNAnorm. Technical sensitivity was determined by spiking different proportions of FFPE tumour DNA into cfDNA from controls.The median genome coverage was 0.26X (range 0.05X-0.97X). For two advanced stage cases there was a positive correlation between copy number ratio profiles of matched cfDNA and FFPE DNA (r = 0.62, p < 0.0001 and r = 0.75, p < 0.0001). There was no correlation for four advanced and two early stage cases. There were low magnitude copy number aberrations detected in high-risk controls (N = 5). We detected spiked FFPE DNA derived SCNAs with a tumour fraction as low as 10 % of cfDNA.Our preliminary results demonstrate non-invasive detection of tumour-derived copy number alterations in advanced lung cancer cases with low coverage whole genome sequencing. Clinical characteristics and treatment may influence whether SCNA are detected in cfDNA.

Establishment and Characterization of a Patient-Derived Model of ALK-Positive Anaplastic Large Cell Lymphoma

Background: Anaplastic large cell lymphoma (ALCL) is an uncommon, aggressive CD30-positive T-cell lymphoma exhibiting or lacking chromosomal translocation involving the Anaplastic Lymphoma Kinase (ALK) gene and expression of ALK protein. ALK positive ALCL (ALK+-ALCL) typically has an improved prognosis compared with ALK-negative; however, patients often respond favorably to standard chemotherapy and CD30-directed immunoconjugates only to progress and are left with few treatment options. To help identify additional treatment options, we collected tumor tissue and established, characterized and evaluated in vivo an ALK+-ALCL patient-derived xenograft (PDX) model from a thirty one year old Caucasian female with relapsed ALCL following initial therapy with a pediatric S-phase specific regimen.Methods: The ST2698 ALK+-ALCL model was established in CB17 SCID mice using tissue collected from a lymph node tumor biopsy. Clinical tissue, patient blood and the PDX model were subjected to WGS sequencing using an augmented and content-enhanced exome. The augmented exome is optimized to detect major cancer mutations by enhancing coverage over known sequencing gaps and GC-rich regions across >1300 cancer and 200 miRNA genes. We also performed whole-transcriptome sequencing on the PDX model. All data were analyzed using a cancer bioinformatics pipeline optimized for high accuracy detection of small variants and indels, somatic copy-number aberrations, gene expression and fusions. Drug sensitivity studies were performed evaluating sensitivity of the model to patient's current clinical treatment and relevant targeted therapies; study endpoints included tumor volume and time from treatment initiation with tumor growth inhibition, delay and regression reported at study completion.Results: Exome analysis identified several variants which were confirmed by transcriptome data. Efficacy studies confirmed model sensitivity to the patient's current clinical course (CHOP). In addition, ST2698 was found moderately sensitive to the IMiD lenalidomide (T/C=47%). However, treatment with the ALK-inhibitors crizotinib or ceritinib resulted in tumor regressions including durable complete responses in some mice.Conclusion: We have established and characterized a patient-derived ALK+-ALCL xenograft model using DNA and RNA-based analysis. In addition we evaluated the model in vivo and confirmed sensitivity to the patient's current clinical course and identified two ALK inhibitors as active, including reported complete tumor regressions. DisclosuresRasco:Celgene: Research Funding; Asana BioSciences, LLC: Research Funding. Tolcher:Asana BioSciences, LLC: Consultancy, Research Funding; AbbVie: Consultancy; ArQule: Consultancy; Bayer: Consultancy; BioMed Valley Discoveries: Research Funding; Janssen R&D: Consultancy.

Abstract A18: Establishment and characterization of serial patient derived xenograft models representing erlotinib sensitive/resistant non-small cell lung cancer

Abstract Background: A subset of non-small cell lung cancer (NSCLC) is driven by mutations or deletions in the epithelial growth factor receptor (EGFR). Several targeted therapies including gefitinib and erlotinib are initially effective towards EGFR-mutant NSCLC; however, resistance to therapy often occurs during the course of treatment. To better understand the mechanisms for resistance to targeted therapies in EGFR-mutant NSCLC we collected tissue from a patient prior to and following response and progression to erlotinib and established xenografts for preclinical drug screening. Clinical and PDX tissue were characterized and compared using DNA and RNA analysis and the models compared in vivo for sensitivity to erlotinib and other therapies. Methods: The NSCLC adenocarcinoma PDX models were established in CB17 SCID mice using tissue collected from a lung biopsy (ST551) or ascites (ST551C). Clinical tissue, patient blood and the PDX model were subjected to WGS sequencing using an augmented and content-enhanced exome. The augmented exome is optimized to detect major cancer mutations by enhancing coverage over known sequencing gaps and GC-rich regions across &amp;gt;1300 cancer and 200 miRNA genes. We also performed whole-transcriptome sequencing on the PDX model. All data were analyzed using a cancer bioinformatics pipeline optimized for high accuracy detection of small variants and indels, somatic copy-number aberrations, gene expression and fusions. Drug sensitivity studies were performed evaluating sensitivity of the model to patient's current clinical treatment and relevant targeted therapies; study endpoints included tumor volume and time from treatment initiation with tumor growth inhibition, delay and regression reported at study completion. In erlotinib efficacy studies the therapy was administered daily via oral gavage at 35 mg/kg for sixty days. Results: Genomic analysis identified several variants which were confirmed by transcriptome data including the previously identified EGFR deletion as well as an MGMT deletion. Efficacy studies reported activity of erlotinib towards the ST551 model with a tumor growth inhibition of 112% including tumor regressions during treatment. However erlotinib was found less activity towards the ST551C model with a tumor growth inhibition of 55% and no tumor regressions. Conclusion: We have established a pair of PDX models from the same patient representing erlotinib sensitive and resistant NSCLC and have characterized the model using comparative genomic analysis and in in vivo efficacy testing. These models can be utilized to better understand mechanisms of resistance to EGFR-targeted therapies and represent unique tools in developing novel therapies to EGFR resistance. Citation Format: Michael J. J. Wick, Elena Helman, Teresa L. Vaught, Monica Farley, Lizette Gamez, Alyssa Moriarty, Scott Ulmer, Anthony W. Tolcher, Drew W. Rasco, Michael Clark, Amita Patnaik, Kyriakos P. Papadopoulos. Establishment and characterization of serial patient derived xenograft models representing erlotinib sensitive/resistant non-small cell lung cancer. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr A18.

Abstract LB-C04: Modeling the impact of somatic alterations across human cancers

Abstract Modeling the impact of somatic alterations across human cancers Hatice U. Osmanbeyoglu1, Christina S. Leslie1,* 1Computational Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY Abstract Large-scale cancer genomics projects like The Cancer Genome Atlas have generated a comprehensive catalog of somatic mutations and copy number aberrations across many tumor types, but the role of some frequently altered genes remains obscure. To better model the impact of these alterations, we developed a computational strategy for exploiting parallel phosphoproteomics and mRNA sequencing data for large tumor sets to link dysregulation of upstream signaling pathways with altered transcriptional response through the transcriptional circuitry. Our modeling allows us to interpret the impact of mutations and copy number events in terms of altered signaling and transcription factor (TF) activity. We used a novel machine learning strategy to train phosphoprotein-TF interaction models across 10 human cancers for which large reverse-phase protein array and RNA-seq data sets are available through TCGA. We then applied a novel algorithmic approach to extract networks of signaling proteins and TFs whose inferred activities are correlated across tumors and whose dysregulation is associated with specific somatically altered genes. Our analysis revealed both known and novel interactions of frequently altered genes with signaling pathways and transcriptional programs in a pan-cancer context. Moreover, our algorithmic approach provides a general strategy for modeling the impact of recurrent mutations and copy number alterations on signaling pathways and transcriptional programs through pan-cancer analysis. Citation Format: Hatice U. Osmanbeyoglu, Christina Leslie. Modeling the impact of somatic alterations across human cancers. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr LB-C04.

Abstract A2-39: Augmented targeted NGS in cancer diagnostics: Comparing gene panels and whole exome sequencing for accurate detection of driver mutations

Abstract With the advent of next-generation sequencing techniques, tumor mutations that guide therapeutic decisions can be identified on a large scale. The ability to accurately detect these mutations is often impaired by obstacles such as sequencing coverage gaps, small sample amount, low cellularity, and tumor heterogeneity. Two methods commonly used to interrogate the genomic profile of a tumor are: i) cancer gene panels, where a small number of genes (in the range of ~5-500, depending on the specific panel design) is assessed, and ii) cancer exome sequencing, where most human genes are evaluated. Additionally, tumor RNA can be studied to elucidate gene fusions and expression features that may impact treatment. Depending on the goals of the investigator, both methods have certain advantages and disadvantages. Differences between these assays must be clearly understood in order for cancer researchers to make the best decision to achieve their objective. We developed a set of unique sequencing assays to augment and improve detection of major cancer mutations by enhancing coverage over known sequencing gaps and GC-rich regions. We utilize these protocols to create an accuracy and content enhanced whole-exome (ACE Exome) as well as an extended, augmented cancer gene panel (ACE Extended Cancer Panel), targeting over 1,300 cancer genes and 200 miRNA genes at very high depth. We compared these ACE assays to standard exome and gene panels currently available. We then compared the ACE panel to the ACE exome using a set of well-characterized cancer cell lines, cell line mixtures with known genomic perturbations, and primary tumor and matched normal pairs involved in drug resistance. We also performed whole-transcriptome and targeted RNA sequencing as companion assays to the DNA exome and panel, respectively. All data were analyzed using a cancer bioinformatics pipeline optimized for detection of low-representation small variants and indels, as well as somatic copy-number aberrations, gene expression and fusions. The ACE assays were able to detect somatic variants with higher accuracy than standard assays across regions targeted by both. For example, a low-representation BRAF mutation detected by standard exome was confirmed as a false positive using the ACE exome due to 90 times more coverage over that region. Between the ACE assays, we found that 88% of somatic variants identified through ACE exome were also identified with our comprehensive panel within regions targeted by both. Conversely, more than half of the somatic variants discovered in the ACE panel were missed in the ACE exome due to insufficient read depth. For instance, the panel detected two EGFR variants known to be present at 1% that were missed in the ACE exome. About 20 times more somatic variants across some ~18,000 genes were detected in whole-exome that are not targeted on the augmented gene panel. These genes have not yet been associated with cancer in current literature, but may be of potential interest for discovery research. Copy number profiles, although more comprehensive in the exome, were recapitulated using the panel, despite large distances between panel targets. Finally, the integration of RNA analysis to the DNA panel was able to detect expression and fusion patterns. In particular, we detected a DNA mutation associated with resistance in a post-treatment specimen, but accompanying RNA data proved this mutant unexpressed and thereby unlikely to be the driver of resistance. For NGS-based cancer analysis to effectively guide clinical decisions and research, accuracy across all relevant cancer genes is of paramount importance. An enhanced exome may offer a solution for researchers interested in novel cancer associations who desire broad, even coverage. A comprehensive, high-depth panel targeting a large set of genes associated with cancer, accompanied by RNA analysis, may accomplish research goals across a wide range of translational cancer research. Citation Format: Elena Helman, Michael James Clark, Sean Boyle, Richard Chen, Shujun Luo, Christian Haudenschild, Jason Harris, Gabor Bartha, Deanna Church, John West. Augmented targeted NGS in cancer diagnostics: Comparing gene panels and whole exome sequencing for accurate detection of driver mutations. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr A2-39.

Abstract A1-30: Integrated genomic analysis identified sequential molecular aberrations in stepwise progression from early to classical hepatocellular carcinomas

Abstract Early hepatocellular carcinoma (HCC) is defined as a very well differentiated liver cancer with the presence of stromal invasion to the remaining Glisson's triad within the tumor (carcinoma in situ), which consists of small hepatocytes with little cellular atypia but with structural atypia. Different from classical HCC, early HCC is macroscopically characterized by indistinct margins and clinically detected as hypovascular lesion by imaging modalities. When such small-sized precursor lesions reach 1.5 to 2.0 cm in diameter, less differentiated cancerous tissues arise within the tumor and develop, finally replacing the very well differentiated HCC. Thus, early HCC originates from chronic liver disease and develops into classical HCC in stepwise manner. To identify sequential genetic alterations in stepwise hepatocarcinogenesis, transcriptome and whole-exome sequences were performed on 47 early and 105 classical HCCs, and molecular aberrations containing somatic mutations, gene expression, fusion events, and copy number aberrations were compared between two groups. In addition, integrating the molecular alterations from different methods, we distinguished genetic driver aberrations from by-chance changes that are not relevant to cancer genome and elucidated recurrent pathways responsible for initiation and progression in stepwise hepatocarcinogenesis. Expression profile of early HCC was different from that of classical HCC, and chromosomal aberrations, somatic mutations, and gene fusion events were significantly frequent in classical HCC. By exome sequencing, mutation of CTNNB1, CSMD3, AXIN1, COL11A1, TSC2, and ATM were often observed in both groups, while those of TP53, ARID2 and ALPK2 were significantly frequent in classical HCC. Integrated analysis showed that distinct expression profile in early HCC would define it as another molecular entity from classical HCC due to its different mutation pattern. Prevalence of somatic mutations of CTNNB1 and p53/RB pathway genes were common, while those of ARID2 and AKT/PI3K pathway genes were significantly frequent in classical HCC. Unexpectedly, WNT target genes were up-regulated only in classical HCC with CTNNB1 mutation, and even down-regulated in those with AXIN1 mutation. Similarly, cell cycle genes related with p53/RB pathway were up-regulated only in classical HCC. Taken together, despite of frequent mutations in CTNNB1 and TP53 in early HCC, additional mutational events such as SWI/SNF complexes and AKT/PI3K pathway will be required for transcriptional activation of downstream targets in HCC progression. Furthermore, TERT is the most frequently up-regulated in early HCC by various mechanisms: recurrent gene fusion including 3 prime portion of TERT such as SLC12A7-TERT (8.5%), focal gain of 5p15.33 (19.1% vs 12.3%), hepatitis B virus integration (2.1% vs 3.8%), and TERT promoter mutation (63.8% vs 59.0%). Despite of driver genes mutation, their pathways are not aberrantly activated and therefore, early HCC is a precursor in accordance with clinical characteristics different from classical HCC. Citation Format: Yutaka Midorikawa, Shogo Yamamoto, Kenji Tatsuno, Hiroki Ueda, Shingo Tsuji, Genta Nagae, Tadatoshi Takayama, Hiroyuki Aburatani. Integrated genomic analysis identified sequential molecular aberrations in stepwise progression from early to classical hepatocellular carcinomas. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr A1-30.

Genomic profiling of CHEK2*1100delC-mutated breast carcinomas.

BackgroundCHEK2*1100delC is a moderate-risk breast cancer susceptibility allele with a high prevalence in the Netherlands. We performed copy number and gene expression profiling to investigate whether CHEK2*1100delC breast cancers harbor characteristic genomic aberrations, as seen for BRCA1 mutated breast cancers.MethodsWe performed high-resolution SNP array and gene expression profiling of 120 familial breast carcinomas selected from a larger cohort of 155 familial breast tumors, including BRCA1, BRCA2, and CHEK2 mutant tumors. Gene expression analyses based on a mRNA immune signature was used to identify samples with relative low amounts of tumor infiltrating lymphocytes (TILs), which were previously found to disturb tumor copy number and LOH (loss of heterozygosity) profiling. We specifically compared the genomic and gene expression profiles of CHEK2*1100delC breast cancers (n = 14) with BRCAX (familial non-BRCA1/BRCA2/CHEK2*1100delC mutated) breast cancers (n = 34) of the luminal intrinsic subtypes for which both SNP-array and gene expression data is available.ResultsHigh amounts of TILs were found in a relatively small number of luminal breast cancers as compared to breast cancers of the basal-like subtype. As expected, these samples mostly have very few copy number aberrations and no detectable regions of LOH. By unsupervised hierarchical clustering of copy number data we observed a great degree of heterogeneity amongst the CHEK2*1100delC breast cancers, comparable to the BRCAX breast cancers. Furthermore, copy number aberrations were mostly seen at low frequencies in both the CHEK2*1100delC and BRCAX group of breast cancers. However, supervised class comparison identified copy number loss of chromosomal arm 1p to be associated with CHEK2*1100delC status.ConclusionsIn conclusion, in contrast to basal-like BRCA1 mutated breast cancers, no apparent specific somatic copy number aberration (CNA) profile for CHEK2*1100delC breast cancers was found. With the possible exception of copy number loss of chromosomal arm 1p in a subset of tumors, which might be involved in CHEK2 tumorigenesis. This difference in CNAs profiles might be explained by the need for BRCA1-deficient tumor cells to acquire survival factors, by for example specific copy number aberrations, to expand. Such factors may not be needed for breast tumors with a defect in a non-essential gene such as CHEK2.Electronic supplementary materialThe online version of this article (doi:10.1186/s12885-015-1880-y) contains supplementary material, which is available to authorized users.

Spatiotemporal Heterogeneity Characterizes the Genetic Landscape of Pheochromocytoma and Defines Early Events in Tumorigenesis.

Pheochromocytoma and paraganglioma (PPGL) patients display heterogeneity in the clinical presentation and underlying genetic cause. The degree of inter- and intratumor genetic heterogeneity has not yet been defined. In PPGLs from 94 patients, we analyzed LOH, copy-number variations, and mutation status of SDHA, SDHB, SDHC, SDHD, SDHAF2, VHL, EPAS1, NF1, RET, TMEM127, MAX, and HRAS using high-density SNP array and targeted deep sequencing, respectively. Genetic heterogeneity was determined through (i) bioinformatics analysis of individual samples that estimated absolute purity and ploidy from SNP array data and (ii) comparison of paired tumor samples that allowed reconstruction of phylogenetic trees. Mutations were found in 61% of the tumors and correlated with specific patterns of somatic copy-number aberrations (SCNA) and degree of nontumoral cell admixture. Intratumor genetic heterogeneity was observed in 74 of 136 samples using absolute bioinformatics estimations and in 22 of 24 patients by comparison of paired samples. In addition, a low genetic concordance was observed between paired primary tumors and distant metastases. This allowed for reconstructing the life history of individual tumors, identifying somatic mutations as well as copy-number loss of 3p and 11p (VHL subgroup), 1p (Cluster 2), and 17q (NF1 subgroup) as early events in PPGL tumorigenesis. Genomic landscapes of PPGL are specific to mutation subtype and characterized by genetic heterogeneity both within and between tumor lesions of the same patient.

A novel framework for analyzing somatic copy number aberrations and tumor subclones for paired heterogeneous tumor samples.

Application of the Next generation sequencing (NGS) technology has demonstrated that most tumor samples exhibit intra-tumor heterogeneity. Here we proposed SAPPH (Somatic Aberrations Prediction for Paired Heterogeneous tumor samples), as a new method for estimating tumor somatic copy number aberrations as well as inferring tumor subclone proportions from heterogeneous tumor sequencing data. This method is based on CBS and local proportion clustering strategy. When SAPPH is applied on simulated tumor samples, the agreement between the results analyzed by SAPPH and the sequencing signals suggests that SAPPH can find the solution to best fit the signal distributions. We benchmark the performance of SAPPH and show that it outperforms existing method in estimating tumor copy number aberrations.

Whole-Genome Sequencing of Growth Hormone (GH)-Secreting Pituitary Adenomas.

The somatic landscape of pituitary adenomas is largely unknown. Identification of somatic alterations aims at better understanding of tumor pathology. The objective of the study was a genome-wide characterization of somatic single-nucleotide variants, structural variants, and copy-number aberrations in somatotropinomas. Whole-genome sequencing and single-nucleotide polymorphism array analyses were performed on 12 fresh-frozen somatotropinomas and their corresponding blood samples. All the coding somatic variants were confirmed by Sanger sequencing. Studied tumors were somatotropinomas. Apart from one AIP mutation-positive patient, all cases were mutation negative for the established germline mutations associated with pituitary adenomas. There were no interventions. Somatic variants were identified with an established computational pipeline and filtered against germline data. Somatic copy number alteration analyses were performed using segmentation-based approaches. A genome-wide analysis revealed on average 129 somatic single-nucleotide variants per tumor. Further analysis of coding regions showed on average 2.3 single-nucleotide variants per tumor. The only recurrent somatic events were the oncogenic GNAS mutation (p.Arg201Cys) and shared chromosome losses (chromosomes 1, 6, 13, 14, 15, 16, 18, 22). Analysis of somatic structural variants revealed one tumor with a complex chromosomal rearrangement. Somatotropinomas showed a low number of somatic genetic alterations. Whereas no novel recurrently mutated genes could be identified, the somatic landscape has potential to affect the Ca(2+) and ATP pathways known to be involved in the pituitary tumorigenesis. Further studies, eg, methylome and transcriptome analyses, are needed to investigate possible interplay between the recurrent chromosome losses and epigenetic factors.

Selection and evolution in the genomic landscape of copy number alterations in ductal carcinoma in situ (DCIS) and its progression to invasive carcinoma of ductal/no special type: a meta-analysis.

Ductal carcinoma in situ (DCIS) is a pre-invasive malignancy detected with an increasing frequency through screening mammography. One of the primary aims of therapy is to prevent local recurrence, as in situ or as invasive carcinoma, the latter arising in half of the recurrent cases. Reliable biomarkers predictive of its association with recurrence, particularly as invasive disease, are however lacking. In this study, we perform a meta-analysis of 26 studies which report somatic copy number aberrations (SCNAs) in 288 cases of 'pure' DCIS and 328 of DCIS associated with invasive carcinoma, along with additional unmatched cases of 145 invasive carcinoma of ductal/no special type (IDC) and 50 of atypical ductal hyperplasia (ADH). SCNA frequencies across the genome were calculated at cytoband resolution (UCSC genome build 19) to maximally utilize the available information in published literature. Fisher's exact test was used to identify significant differences in the gain-loss distribution in each cytoband in different group comparisons. We found synchronous DCIS to be at a more advanced stage of genetic aberrations than pure DCIS and was very similar to IDC. Differences in gains and losses in each disease process (i.e. invasive or in situ) at each cytoband were used to infer evidence of selection and conservation for each cytoband and to define an evolutionary conservation scale (ECS) as a tool to identify and distinguish driver SCNA from the passenger SCNA. Using ECS, we have identified aberrations that show evidence of selection from the early stages of neoplasia (i.e. in ADH and pure DCIS) and persist in IDC; we postulate these to be driver aberrations and that their presence may predict progression to invasive disease.

Abstract 4868: CODEX: a normalization and copy number variation detection method for whole-exome sequencing

Abstract Background: High throughput sequencing of DNA coding regions has become a common way of assaying genomic variation in the study of cancer. Copy number aberration (CNA) is an important type of genomic change, but detecting and characterizing CNA from whole-exome sequencing (WES) is challenging due to the high level of biases and artifacts. Methods: We propose CODEX, a normalization and CNA calling procedure for WES data. The Poisson latent factor model in CODEX includes terms that specifically remove biases due to GC content, exon capture and amplification efficiency, and latent systemic artifacts. CODEX also includes a Poisson likelihood-based recursive segmentation procedure that explicitly models the count-based WES data. CODEX can be used to detect both germline and somatic CNAs in cancer samples with or without matched normal. Results: Compared to existing approaches, CODEX is shown to be more effective in removing the biases in WES, and attains better sensitivity and specificity in detecting copy number aberrations by in silico spike-in studies. We further evaluate performance on 222 neuroblastoma samples with matched normal from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) Project. We carry out systematic genome-wide analysis and detailed characterization of both germline and somatic copy number events. With a focus on a well-studied rare somatic CNV within the ATRX gene, we show that the cross-sample normalization procedure of CODEX is more effective in removing noise than the standard pipeline of normalizing the tumor against the matched normal, and that the segmentation procedure performs well in detecting CNVs with recurrent complex nested structures. For detecting germline mutations, CODEX is compared to existing methods on a population analysis of HapMap samples from the 1000 Genomes Project, and shown to be perform well on three microarray-based validation data sets. Conclusions: The cross-sample normalization procedure of CODEX, when applied to the matrix of tumor and normal samples, is more effective in reducing noise than normalizing each tumor to its matched normal. The somatic deletions in the ATRX region have a nested structure, which CODEX was able to recover. Through multiple types of validation, CODEX is shown to be applicable to a wide range of study designs for copy number estimation using WES data. Citation Format: Yuchao Jiang, Derek A. Oldridge, Sharon J. Diskin, Nancy R. Zhang. CODEX: a normalization and copy number variation detection method for whole-exome sequencing. [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 4868. doi:10.1158/1538-7445.AM2015-4868

Abstract 1457: Genomic characterization of a PDX model of T-DM1-resistant HER2+ invasive ductal carcinoma using augmented exome sequencing

Abstract HER2 amplification/overexpression occurs in 20-30% of breast cancers and is associated with poor prognosis and increased metastatic potential. Patients with HER2+ breast cancers who have progressed on trastuzumab and lapatinib are often prescribed the antibody-drug conjugate, do-trastuzumab emtansine (T-DM1). Results from the TH3RESA and EMILIA studies showed that T-DM1 increased progression-free and overall survival compared to standard therapy and suggested it be considered as standard of care. Despite these favorable efficacy results, most patients treated with T-DM1 eventually progress, but the mechanisms of resistance are not understood. Acquired resistance to T-DM1 has been shown in-vitro, but has not been examined in an in-vivo system. An FNA from a metastatic lung lesion was used to establish a human PDX model from a patient with metastatic HER2+ invasive ductal carcinoma. This model was found resistant to T-DM1 administered weekly at 3 m/k and every three weeks at 10 m/k. We performed whole-exome sequencing on both the metastatic tissue and the PDX model using a content-enhanced exome technology we developed. Our augmented exome is optimized to detect major cancer mutations by enhancing coverage over known sequencing gaps and GC-rich regions across &amp;gt;1300 cancer and 200 miRNA genes. We also performed whole-transcriptome sequencing on the PDX model. All data were analyzed using a cancer bioinformatics pipeline optimized for high-accuracy detection of small variants and indels, somatic copy-number aberrations, gene expression and fusions. We comprehensively profiled the exomes of a metastatic HER2+ ductal carcinoma resistant to T-DM1 treatment and a PDX model derived from it. We found that the PDX model was highly consistent with the neoplastic tissue, with respect to both somatic variants and copy-number alterations, establishing it as an accurate representation of a patient-derived T-DM1-resistant tumor. We verified only 0.27% contamination by mouse DNA in the PDX model. Specifically, we confirmed the continued amplification of HER2 as well as CCNE1 and MYC. Loss-of-heterozygosity of TP53 was coupled with a clonal damaging point mutation. Of note, we found a non-synonymous mutation in HER2, suggesting possible involvement in resistance mechanisms. Transcriptome data confirmed mutation expression in the RNA and gene expression changes of amplified/deleted genes. We present the first preclinical model of a human xenograft derived from a HER2+ metastatic breast cancer with acquired T-DM1 resistance. T-DM1 is effective in treating advanced HER2+ breast cancer in patients who have progressed on standard therapies, but this efficacy is short-lived. Here, we used whole-exome and transcriptome sequencing to characterize the genomic profile of tumors that have become resistant to T-DM1 and present a patient-derived model to reveal insights into acquired T-DM1 resistance mechanisms. Citation Format: Elena Helman, Michael J. Wick, Michael J. Clark, Lizette Gamez, Sean Boyle, Kyriakos P. Papadopoulos, Shujun Luo, Anthony W. Tolcher, Parin Sripakdeevong, Mirian Karbelashvili, Deanna Church, Richard Chen, John West. Genomic characterization of a PDX model of T-DM1-resistant HER2+ invasive ductal carcinoma using augmented exome sequencing. [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 1457. doi:10.1158/1538-7445.AM2015-1457

Abstract CT136: Final biomarker analysis of the phase I study of the selective BRAF V600 inhibitor encorafenib (LGX818) combined with cetuximab with or without the α-specific PI3K inhibitor alpelisib (BYL719) in patients with advanced BRAF-mutant colorectal cancer

Abstract Background: Although BRAF V600-mutated (BRAFm) colorectal carcinoma (CRC) does not generally respond to BRAF inhibitors, results of preclinical studies suggest strong synergistic activity between a BRAF inhibitor and an EGFR inhibitor or a PI3K inhibitor. The aims of this study were to establish safety and preliminary activity of combination therapy with encorafenib (ENC), a highly selective BRAF V600 inhibitor, the EGFR monoclonal antibody cetuximab (CTX), ± the α-specific PI3K inhibitor alpelisib (ALP) in patients (pts) with BRAFm CRC; and assess the potential clinical significance of biomarkers and microsatellite instability (MSI) status by genomic analysis of tumor samples. Methods: In this phase I study, the maximum tolerated dose/recommended phase II dose (RP2D) was determined and safety, tolerability, and anti-tumor activity of ENC + CTX ± ALP were evaluated, in pts with advanced BRAFm/KRAS wild-type CRC. Archival or fresh screening tumor samples were analyzed for somatic mutations and copy number aberrations to evaluate potential correlation with response. Results: Fifty-four pts were enrolled in the dose-escalation phase; 26 in the dual arm (ENC + CTX) and 28 in the triple arm (ENC + ALP + CTX). RP2D for each treatment arm was established as 200 mg ENC QD + CTX weekly (dual arm) + 300 mg ALP once daily (triple arm). The most common grade 3/4 treatment-related adverse events were fatigue and hypophosphatemia in the dual arm (8% each), and nausea and hypophosphatemia in the triple arm (4% each). Hyperglycemia was observed in one patient (3.8%) in the dual arm and 8 patients (29%) in the triple arm. Overall response rates (≥ partial response [PR]) for the dual and triple arms were 23% (1 CR, 4 PR, and 1 unconfirmed (u) PR) and 32% (4 PR and 5 uPR), respectively. Median progression-free survival was 3.7 and 4.3 months, respectively. Biomarker analysis was performed on 21 tumor samples. Several genetic alterations occurred with similar frequency between patient samples and the FoundationOne database (PIK3CA, TP53, APC). Specifically, the PIK3CA mutation and PTEN alterations were found in 24% and 38% of patient samples, respectively; however, these alterations did not appear to be correlated with response. Non-MSI-high status was associated with a lower PFS for the dual arm (2.8 vs 3.7 months), but not the triple arm (4.4 vs 4.3 months). Updated biomarker analyses, including MSI status, will be presented. Conclusions: These results indicate that both ENC + CTX and ENC + CTX + ALP are well tolerated with promising antitumor activity in pts with advanced BRAFm CRC who failed at least one prior therapy. Additional biomarker analyses will help to clarify the clinical significance of genetic alterations, particularly with MSI status and the PI3K pathway. Enrollment in the phase II portion of the study is ongoing. Citation Format: Jan H. M. Schellens, Robin van Geel, Johanna C. Bendell, Anna Spreafico, Martin Schuler, Takayuki Yoshino, Jean-Pierre Delord, Yasuhide Yamada, Martijn P. Lolkema, Jason E. Faris, Ferry A. L. M. Eskens, Sunil Sharma, Rona Yaeger, Heinz-Josef Lenz, Zev A. Wainberg, Emin Avsar, Arkendu Chatterjee, Savina Jaeger, Tim Demuth, Josep Tabernero. Final biomarker analysis of the phase I study of the selective BRAF V600 inhibitor encorafenib (LGX818) combined with cetuximab with or without the α-specific PI3K inhibitor alpelisib (BYL719) in patients with advanced BRAF-mutant colorectal cancer. [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 CT136. doi:10.1158/1538-7445.AM2015-CT136

Relatively Small Contribution of Methylation and Genomic Copy Number Aberration to the Aberrant Expression of Inflammation-Related Genes in HBV-Related Hepatocellular Carcinoma.

BackgroundIt is well known that chronic inflammation plays a pivotal role in the development of hepatitis B virus (HBV) related hepatocellular carcinoma (HCC). However, the causes behind aberrant expression of inflammation-related genes occurred in HCC remain unclear.MethodsWe performed array-based analyses to comprehensively investigate the contributions of DNA methylation and somatic copy number aberration (SCNA) to the aberrant expression of 1,027 inflammation-related genes in 30 HCCs and paired non-tumor tissues. The results were validated in public datasets and an additional sample set of 47 paired HCCs and non-tumor tissues.ResultsWe identified 252 differentially expressed, 125 aberrantly methylated and 287 copy number changed inflammation-related genes. Despite reasonable statistical power, among them, only 11 genes and 56 genes whose aberrant expression was associated with DNA methylation or SCNA, respectively. DNA methylation and SCNA together contributed to less than 30% aberrant expression of inflammation-related genes.ConclusionThese results suggest that molecular mechanisms other than DNA methylation and SCNA might play major role in the regulation of aberrant expression of inflammation-related gene in HBV-related HCCs.