Passenger Alterations Research Articles

Somatic Molecular Heterogeneity in Bilateral Macronodular Adrenocortical Disease (BMAD) Differs Among the Pathological Subgroups.

Bilateral macronodular adrenocortical disease (BMAD) is an uncommon cause of Cushing's syndrome leading to bilateral macronodules. Isolated BMAD has been classified into three molecular groups: patients with ARMC5 alteration, KDM1A alteration, and patients without known genetic cause. The aim of this study was to identify by NGS, in a cohort of 26 patients with BMAD, the somatic alterations acquired in different nodules after macrodissection from patients with germline ARMC5 or KDM1A alterations and to analyze potential somatic alterations in a panel of five other genes involved in adrenal pathology (GNAS, PDE8B, PDE11A, PRKAR1A, and PRKACA). Twenty-three patients (7 ARMC5, 3 KDM1A, and 13 BMAD with unknown genetic cause) were analyzable. Somatic ARMC5 or KDM1A events were exclusively observed in patients with germline ARMC5 and KDM1A alterations, respectively. Six out of 7 ARMC5 patients have a high heterogeneity in identified somatic events, whereas one ARMC5 and all KDM1A patients show a loss of heterozygosity (LOH) in all nodules. Except for passenger alterations of GNAS, no genetic alteration susceptible to causing the disease was detected in the BMAD with unknown genetic cause. Our study reinforces our knowledge of the somatic genetic heterogeneity of ARMC5 and the somatic homogeneity of KDM1A. It reveals the absence of purely somatic events in these two genes and provides a new tool for detecting KDM1A alterations by FISH 1p36/1q25.

A pan-cancer landscape of pathogenic somatic copy number variations

ObjectiveCopy number variations (CNVs) play crucial roles in physiological and pathological processes, including cancer. However, the functional implications of somatic CNVs in tumor progression and evolution remain unclear. This study focuses on identifying CNV alterations with high pathogenic potential that drive and sustain tumorigenesis, distinguishing them from passenger alterations that accumulate during tumor growth. Our goal is to explore the variability of CNVs across different tumor types and infer their impact on tumor cell functions. MethodsStarting from 7352 copy number profiles across 33 different cancer types, we infer the pathogenicity of each CNV and perform both intra- and inter-tumor analyses to predict the functional impact of different genomic patterns. We evaluate the actionability of genes belonging to altered regions and we correlate the presence of pathogenic regions with genome instability patterns and patients’ survival. ResultsOur analysis uncovered large heterogeneity among different tumors suggesting in many cases distinct genetic drivers of tumorigenesis. Recurrent genomic alterations frequently coincide with dysfunctional homologous recombination pathways and negative regulation of the immune system. In certain tumors, the number of pathogenic CNVs emerged as a prognostic biomarker, highlighting their significance in cancer progression. ConclusionThis study contributes to elucidate the functional impact of pathogenic CNVs in tumor progression and sheds light on their potential as prognostic markers in specific cancer types.

NTRK fusions in osteosarcoma are rare and non-functional events.

Neurotrophic tyrosine receptor kinase (NTRK) fusions are promising molecular targets that have been described in a broad range of malignant tumours. Fusions commonly lead to the expression of chimeric proteins with constitutive tyrosine kinase activation that drives tumorigenesis. Despite a low prevalence among most solid tumours (<1%), the first encouraging results with pan‐NTRK tyrosine kinase inhibitors (TKIs) such as larotrectinib or entrectinib stimulated the search for eligible patients. Here, we report the first three cases of osteosarcoma harbouring NTRK fusions, among 113 patients sequenced. It is also the first report on NTRK fusions within a tumour type characterised by highly rearranged genomes and abundant passenger mutations. Whereas the presence of NTRK gene fusions in many tumours is considered to be one of the main driver events for tumour progression, the three chimeric transcripts described here appear non‐functional and likely represent randomly occurring passenger alterations. Particularly in tumours with complex karyotypes, it may therefore be advisable to specifically investigate the fusion transcripts for functional impact before considering targeted treatment approaches using pan‐NTRK TKIs.

317P - Novel fusion genes identified from matched primary and recurrent breast cancers by RNA-sequencing

BackgroundBreast cancers display substantial inter/intra-tumor heterogeneity. While numerous fusion genes have been identified, most are found to be subclonal, passenger alterations. To discover fusion genes which drive tumor progression and metastasis, we performed RNA-sequencing of matched primary and metastatic breast cancer samples. MethodsRNA-sequencing was performed from sixteen patients matched primary-recurrent tumor tissue and RNA-sequencing data was successfully achieved from sixteen primary tumors and eight recurrent tumors. DeFuse program was used to identify fusion transcripts (FT). ResultsAmong the sixteen patients, six were hormone receptor positive, three were HER2 positive and seven were triple negative tumors. Three cases displayed loco-regional recurrence only and other patients had distant metastases. Overall, 516 fusion transcripts were identified. Mean numbers of fusions in primary and recurred tumors were 28 and 14.6 FTs per sample. Numbers of fusions were greater in two cases with BRCA1 pathogenic germline mutations while no significant differences were observed across subtypes. Novel inter-chromosomal fusion transcript, BCL2-ESR1, CSMD1-ESR1 and HPGDS-ESR1 were found in one hormone receptor positive patient’s metastasis and/or primary tumor. All fusions resulted in preservation of the DNA-binding domain and ligand-binding domain (exon4-10) of the ESR1 gene, with high ESR1 FPKM expression value. Fusions of ERBB2-, MALAT1- and CDK6- genes were found. Among the identified FTs, three cases harbored a previously reported recurrent fusion transcript EEF1DP3-FRY. ConclusionsRNA sequencing revealed numerous fusion transcripts. Among them we found novel fusions including ESR1 fusions which need further validation and functional annotation to confirm their role in tumor progression and metastasis. Legal entity responsible for the studyThe authors. FundingAsan Medical Center. DisclosureAll authors have declared no conflicts of interest.

Non-Clear Cell Renal Cell Carcinomas: From Shadow to Light.

Non-clear cell renal cell carcinomas (RCCs) account for up to 25% of kidney cancers and encompass distinct diseases with distinct pathologic features, different molecular alterations, and various patterns of response to systemic therapies. Recent advances in molecular biology and large collaborative efforts helped to better define the oncogenic mechanisms at play in papillary, chromophobe, collecting duct, medullary, translocation, and sarcomatoid RCCs. Papillary RCCs are divided into several subsets of tumors characterized by distinct gene expression profiles, chromatin remodeling genes, cell cycle changes, and alterations of the MET pathway. Chromophobe RCC genomic analysis revealed mostly metabolic pathway alterations with mitochondrial dysfunctions. Translocation RCCs are characterized by MITF fusions and wide genomic reprogramming. Collecting duct carcinomas are distinct entities from upper tract urothelial carcinomas associated with high T-cell infiltration and metabolic alterations. Medullary RCCs present alterations of the INI1 gene and rhabdoid features at pathologic analysis. Finally, sarcomatoid RCCs represent sarcomatoid differentiation for any subsets of RCCs with specific alterations associated with mesenchymal dedifferentiation. From the standpoint of systemic therapy, more than a decade of using VEGF and mTOR inhibitors showed that they generally had limited efficacy in non-clear cell RCCs compared with clear cell RCCs. MET inhibitors are actively being developed for papillary RCC with a specific focus on MET-driven tumors. Other strategies under investigation include CDK4/6 inhibitors in tumors with cell cycle alterations and EZH2 inhibitors in RCCs with INI1 loss. The emergence of immune checkpoint inhibitors and combination strategies enlarges the spectrum of investigational treatments. Better understanding of driver and passenger alterations and better patient stratification along with dedicated clinical networks will be key to improving the management of these rare tumors.

The Damaging Effect of Passenger Mutations on Cancer Progression.

Genomic instability and high mutation rates cause cancer to acquire numerous mutations and chromosomal alterations during its somatic evolution; most are termed passengers because they do not confer cancer phenotypes. Evolutionary simulations and cancer genomic studies suggest that mildly deleterious passengers accumulate and can collectively slow cancer progression. Clinical data also suggest an association between passenger load and response to therapeutics, yet no causal link between the effects of passengers and cancer progression has been established. To assess this, we introduced increasing passenger loads into human cell lines and immunocompromised mouse models. We found that passengers dramatically reduced proliferative fitness (∼3% per Mb), slowed tumor growth, and reduced metastatic progression. We developed new genomic measures of damaging passenger load that can accurately predict the fitness costs of passengers in cell lines and in human breast cancers. We conclude that genomic instability and an elevated load of DNA alterations in cancer is a double-edged sword: it accelerates the accumulation of adaptive drivers, but incurs a harmful passenger load that can outweigh driver benefit. The effects of passenger alterations on cancer fitness were unrelated to enhanced immunity, as our tests were performed either in cell culture or in immunocompromised animals. Our findings refute traditional paradigms of passengers as neutral events, suggesting that passenger load reduces the fitness of cancer cells and slows or prevents progression of both primary and metastatic disease. The antitumor effects of chemotherapies can in part be due to the induction of genomic instability and increased passenger load. Cancer Res; 77(18); 4763-72. ©2017 AACR.

OC-033 Nine-Gene Signature Implicated in the Early Development of Hepatitis C Virus (HCV) Related Hepatocellular Carcinoma (HCC)

Introduction HCV remains the commonest cause of HCC related deaths in the west. Dysplastic nodules (DN) harbour highly relevant genomic information based on its strong potential to progress to HCC. Copy number alterations (CNA) have not been previously studied in a large cohort of HCV related DN. In this study we used next generation sequencing (NGS) to identify potential drivers of oncogenesis in a cohort of HCV related DNs and HCCs. Methods We performed low coverage next generation DNA sequencing of 116 HCCs and 49 DNs from 63 HCV infected patients to investigate their CNA profiles. Patients with a mixed aetiology of liver disease were excluded. Significant copy number gain and loss peaks were identified using GISTIC 2.0. To identify driver from passenger alterations, we stratified the peaks according to their amplitude and frequency within included samples. We also identified peaks that were inclusive of genes causally implicated in cancer, highly associated with cancer or involved in major cell signalling pathways. We further analysed the HCC-related peaks and correlated each of them to patient and tumour clinical features. This correlation was corrected for false discovery rate (FDR) using the Benjamini-Hochberg procedure. Results We identified 86 and 79 significant CNA peaks in HCC and DN respectively. The peaks were further stratified as described above which lead to recognition of a 9 gene signature highly implicated in early HCV related HCC. This included losses of ROCK1, CARS, SBDS, DUX4 and gains of NCOA2, MYC, TPO, YWHAZ and MCM4. Our data confirmed the alteration of 51 other genes in HCC but not DN. This included gains of CCND1, NFKB1/2, MUC1, FGF2/4/19 and CKS1B and losses of CDKN2A/B, KRAS, PTEN, RB1, NOTCH1, CCNA2, BMPR1B which have previously been implicated in hepatocarcinogenesis. Out of 86 HCC-related peaks, 16/86 had significant associations with clinical features after correction for FDR. Six of the above 16 peaks overlapped with 6 out of the 9 gene signature we previously identified. Genomic features strongly correlated with tumour differentiation, number of tumours per liver and overall survival. No association was found between HCV genotype or PCR quantity. Conclusion Analysis of DNA copy number profiles of a large number of HCV related DN and HCC using NGS revealed a signature of 9 genes likely to be implicated as drivers in the early development of this cancer. Our study generates a valid hypothesis and further studies are needed to confirm causality. Disclosure of Interest W. Fateen: None Declared, H. Wood: None Declared, S. Berri Employee of: Illumina, H. Thygesen: None Declared, J. Wyatt: None Declared, M. El- Meteini: None Declared, C. Millson: None Declared, P. Quirke: None Declared

Abstract B25: A novel in vivo gain-of-function screen for metastasis drivers in non-small cell lung cancers

Abstract Metastatic lung cancer is the leading cause of cancer related mortality in the world. Insights on specific genetic causes are limited and novel approaches are necessary to elucidate specific genes that drive lung cancer progression and metastasis. Extensive genomic and transcriptomic profiling of human lung cancers by consortia like ‘The Cancer Genome Atlas’ (TCGA) and the ‘International Cancer Genome Consortium’ (ICGC) has revealed a complex genetic landscape marked by abundant aberrations. In addition to acquiring mutations or amplification of well documented drivers like Kras, p53 or EGFR, lung cancers also demonstrate an enrichment of hundreds of low frequency gene aberrations which are a mix of key driver mutations and nascent passenger alterations caused by progressive genomic instability that could have definite role in cancer progression and metastasis. Our goal was to establish a robust screening platform to selectively identify these functionally critical “driver” genes in lung cancers. To identify a prioritized list of potential candidates we performed a multi-level cross-species comparison of our published high confidence transcriptome data from genetically-engineered mouse models of lung cancers and human lung cancer genomic data from TCGA, focusing on elevated gene expression and/or gene amplification. We identified an enriched list of 225 putative driver genes in lung cancers which were used to construct a lentiviral based cDNA expression library with unique molecular barcoding of individual cDNAs. Using a non-metastatic syngeneic mouse lung cancer model we generated individually transduced stable over-expressing lines for each of the 225 genes. These candidate lines were then entered into parallel in vitro and in vivo screens. In vitro testing includes cell invasion assays in a 96-well format, with positive hits defined as those scoring above 3x standard deviations relative to the control cells expressing mCherry. Positive hits were revalidated using standard 24-well invasion assays and also studied for growth phenotypes in 3D cultures. To selectively identify genes with functional role in metastasis, we performed a unique in vivo positive selection screen to test individual and combinatorial effects of lung cancer driver aberrations. For this we used pools of 20 cDNA expressing lines transplanted into syngeneic mice and observed for primary tumor growth and occurrence of metastases in lungs and other organs. Metastatic lesions and primary tumors were collected and genomic DNA from these was used to identify the unique individual barcodes by NGS barcode enrichment analysis. Metastatic drivers were identified by the relative enrichment of the unique barcode sequences for all the respective pool cDNAs in the metastatic tissue. We have identified both known (e.g. MYC) and several novel (e.g. THRA, TMEM106B, GNAS) potential oncogenic and metastatic drivers from the pooled screen which are currently being revalidated for their individual in vivo metastatic potencies. We are performing gain-of-function/loss-of-function studies for the identified driver genes to determine the pathways which they regulate. We are also analyzing the clinical relevance of these genes based upon their expression pattern and prognostic utility across TCGA and other public datasets, along with in-house patient samples and tissue microarrays of resected and biopsy specimens. Our unique high through-put approach will significantly advance the field of cancer target discovery by identifying new drug targets and biomarkers, essential for novel effective treatment options for lung cancer patients. Citation Format: Samrat T. Kundu, Caitlin Grzeskowiak, Chad J. Creighton, Kenneth L. Scott, Don L. Gibbons. A novel in vivo gain-of-function screen for metastasis drivers in non-small cell lung cancers. [abstract]. In: Proceedings of the AACR Special Conference on Tumor Metastasis; 2015 Nov 30-Dec 3; Austin, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(7 Suppl):Abstract nr B25.

New role for ZFX in oncogenesis

New role for ZFX in oncogenesis

Abstract 3415: Genetic analysis of multifocal glioblastoma multiforme foci points to their monoclonal evolution and highlights early and late events in their development

Abstract Glioblastoma (GBM) is the most common and malignant type of brain tumor in adults with an average survival time of less than a year. A hallmark of GBM is its infiltrating growth hampering successful surgical treatment and precluding curative therapy. Multifocal GBMs - multiple synchronous lesions in the same patient - represent approximately 8-10% of all gliomas and generally have a poor prognosis. There are two theories as to the nature of these multifocal GBMs: they could either have originated from one main GBM or they can be independent tumors. Genetic studies of multifocal GBMs are very rare and such studies could elucidate the nature of these tumors. We have analyzed eleven tumor foci of six patients with multifocal GBMs using array comparative genome hybridization (aCGH), spectral karyotyping (SKY), and Sanger sequencing of PTEN, TP53, and IDH1/2. Array CGH analysis of ten of the tumors revealed multiple genetic aberrations. The most frequent were gain of chromosome 7 (9/10), amplification of EGFR (10/10), loss of chromosome 10 (10/10), and partial loss of chromosome 9 (7/10). SKY analysis identified multiple translocations including complex rearrangements. None of the tumors carried a mutation in IDH1/2 and they were genetically similar to primary GBMs although they exhibited unique characteristics; e.g. all carried an EGFR amplification, indicating that it is important for the multifocal phenotype. Tumor foci derived from the same patient always shared identical aberrations, proving monoclonal origin of these tumors but also exhibited additional aberrations, which were specific for each focus and therefore must have occurred later in tumor development. Moreover, our results show that events important for gliomagenesis could occur at different time points in tumor evolution: for example, the region involved in the EGFR amplification was different in both foci from three patients and identical in two foci from one patient. The same can be said of point mutations in TP53 and PTEN; TP53 mutations were identical in the different foci from one patient and different in another patient while PTEN mutations were different in the foci from two patients and similar in those of one. Interestingly, in each patient one focus always contained more aberrations than the other, highlighting the possibility that one derived from the other; this would further support the hypothesis that multifocal GBMs are of monoclonal origin and then develop independently of each other by clonal evolution. Taken together, multifocal GBM provide an excellent model for investigating tumor progression and invasion and might help to distinguish between driver and passenger alterations in GBM. Acknowledgements: This work was partially supported by a grant (MeDDrive program) of the Medizinische Fakultät Carl Gustav Carus, Technische Universität Dresden. Citation Format: Khalil Abou-El-Ardat, Dietmar Krex, Michael Seifert, Kerstin Becker, Morten Hillmer, Sophie Eisenreich, Arleta Käßner-Frensel, Petra Freitag, Eva-Maria Gerlach, Karl Hackmann, Andreas Rump, Gabriele Schackert, Evelin Schröck, Barbara Klink. Genetic analysis of multifocal glioblastoma multiforme foci points to their monoclonal evolution and highlights early and late events in their development. [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 3415. doi:10.1158/1538-7445.AM2014-3415

Using passenger mutations to estimate the timing of driver mutations and identify mutator alterations

BackgroundRecent developments in high-throughput genomic technologies make it possible to have a comprehensive view of genomic alterations in tumors on a whole genome scale. Only a small number of somatic alterations detected in tumor genomes are driver alterations which drive tumorigenesis. Most of the somatic alterations are passengers that are neutral to tumor cell selection. Although most research efforts are focused on analyzing driver alterations, the passenger alterations also provide valuable information about the history of tumor development.ResultsIn this paper, we develop a method for estimating the age of the tumor lineage and the timing of the driver alterations based on the number of passenger alterations. This method also identifies mutator genes which increase genomic instability when they are altered and provides estimates of the increased rate of alterations caused by each mutator gene. We applied this method to copy number data and DNA sequencing data for ovarian and lung tumors. We identified well known mutators such as TP53, PRKDC, BRCA1/2 as well as new mutator candidates PPP2R2A and the chromosomal region 22q13.33. We found that most mutator genes alter early during tumorigenesis and were able to estimate the age of individual tumor lineage in cell generations.ConclusionsThis is the first computational method to identify mutator genes and to take into account the increase of the alteration rate by mutator genes, providing more accurate estimates of the tumor age and the timing of driver alterations.

Next-Generation Sequencing Reveals High Concordance of Recurrent Somatic Alterations Between Primary Tumor and Metastases From Patients With Non–Small-Cell Lung Cancer

Characterization of the genomic changes that drive an individual patient's disease is critical in management of many cancers. In patients with non-small-cell lung cancer (NSCLC), obtaining tumor samples of sufficient size for genomic profiling on recurrence is often challenging. We undertook this study to compare genomic alterations identified in archived primary tumors from patients with NSCLC with those identified in metachronous or synchronous metastases. Primary and matched metastatic tumor pairs from 15 patients were analyzed by using a targeted next-generation sequencing assay in a Clinical Laboratory Improvement Amendments laboratory. Genomic libraries were captured for 3,230 exons in 182 cancer-related genes plus 37 introns from 14 genes often rearranged in cancer and sequenced to high coverage. Among 30 tumors, 311 genomic alterations were identified of which 63 were known recurrent (32 in primary tumor, 31 in metastasis) and 248 were nonrecurrent (likely passenger). TP53 mutations were the most frequently observed recurrent alterations (12 patients). Tumors harbored two or more (maximum four) recurrent alterations in 10 patients. Comparative analysis of recurrent alterations between primary tumor and matched metastasis revealed a concordance rate of 94% compared with 63% for likely passenger alterations. This high concordance suggests that for the purposes of genomic profiling, use of archived primary tumor can identify the key recurrent somatic alterations present in matched NSCLC metastases and may provide much of the relevant genomic information required to guide treatment on recurrence.

Abstract 1610: Serial treatment-transplant xenograft model of Bevacizumab-resistance reveals temporal induction of markers associated with disease progression.

Abstract INTRODUCTION: Acquired resistance threatens the potential of anti-angiogenic therapy. Xenograft models of acquired anti-angiogenic therapy resistance are lacking and often fail to reflect changes human tumors acquire during prolonged serial treatment with anti-angiogenic therapy because of the significantly shorter lifespan of tumor-bearing mice. To create a xenograft model of bevacizumab-resistant GBM allowing temporal definition of changes during resistance to VEGF blockade, we created a model whereby serially passaged xenografts were continually exposed to bevacizumab versus IgG control antibody over 5 generations in vivo. METHODS: We treated 5 subcutaneous U87 glioma cell line-derived xenografts with bevacizumab or IgG, explanted the least responsive xenograft and reimplanted it subcutaneously, then repeated this pattern of treatment followed by explantation and reimplantation of the least responsive xenograft for 4 more generations, generating 5 generations of U87-IgG and U87-BevR xenografts. Western blot assessed temporal changes. RESULTS: Subcutaneous fifth generation U87-BevR were unresponsive to bevacizumab versus IgG (P=0.8). Bevacizumab caused U87-IgG to regress (P&amp;lt;0.05) while U87BevR grew exponentially during bevacizumab treatment (P=0.6). Intracranial U87-BevR xenografts were bevacizumab unresponsive (P=0.1), while intracranial U87-IgG xenografts responded to bevacizumab (P=0.006). Intracranial U87-BevR xenografts also exhibited further discontinuous invasion, higher percent of invading tumor cells 10 μm from a vessel, and more invasive islands (P&amp;lt;0.05). U87-BevR xenografts expressed 9-fold more c-Met protein than U87-IgG xenografts after one generation, an effect sustained through all 5 generations. U87-BevR exhibited 6-fold more phosphorylated c-Met, a change not occurring until the fifth generation. U87-BevR exhibited 9-fold more phosphorylated STAT3 and 8-fold more VEGFR2 than U87-IgG through all 5 generations. U87-BevR exhibited 5-8-fold more alpha5beta1 integrin than U87-IgG cells, a disparity peaking during the third generation before resolving during generations 4-5. CONCLUSIONS: Our novel model of acquired anti-angiogenic therapy resistance showed that acquired resistance increases parenchymal and perivascular invasion with some changes (increased c-Met, VEGFR2, and phosphorylated STAT3) occurring early and lasting throughout resistance, while other changes like alpha5beta1 integrin upregulation peaked later and decreased over time. The ability of this model to replicate prolonged anti-angiogenic therapy duration seen in patients should generate a molecular profile of anti-angiogenic therapy resistance, and should define which resistance-associated changes are driver versus passenger alterations. Citation Format: Arman Jahangiri, Michael De Lay, W. Shawn Carbonell, Liane Miller, Manish K. Aghi. Serial treatment-transplant xenograft model of Bevacizumab-resistance reveals temporal induction of markers associated with disease progression. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1610. doi:10.1158/1538-7445.AM2013-1610

Integrative functional genomics identifies RINT1 as a novel GBM oncogene

Large-scale cancer genomics efforts are identifying hundreds of somatic genomic alterations in glioblastoma (GBM). Distinguishing between active driver and neutral passenger alterations requires functional assessment of each gene; therefore, integrating biological weight of evidence with statistical significance for each genomic alteration will enable better prioritization for downstream studies. Here, we demonstrate the feasibility and potential of in vitro functional genomic screens to rapidly and systematically prioritize high-probability candidate genes for in vivo validation. Integration of low-complexity gain- and loss-of-function screens designed on the basis of genomic data identified 6 candidate GBM oncogenes, and RINT1 was validated as a novel GBM oncogene based on its ability to confer tumorigenicity to primary nontransformed murine astrocytes in vivo. Cancer genomics-guided low-complexity genomic screens can quickly provide a functional filter to prioritize high-value targets for further downstream mechanistic and translational studies.

Histotype-specific copy-number alterations in ovarian cancer

BackgroundEpithelial ovarian cancer is characterized by multiple genomic alterations; most are passenger alterations which do not confer tumor growth. Like many cancers, it is a heterogeneous disease and can be broadly categorized into 4 main histotypes of clear cell, endometrioid, mucinous, and serous. To date, histotype-specific copy number alterations have been difficult to elucidate. The difficulty lies in having sufficient sample size in each histotype for statistical analyses.MethodsTo dissect the heterogeneity of ovarian cancer and identify histotype-specific alterations, we used an in silico hypothesis-driven approach on multiple datasets of epithelial ovarian cancer.ResultsIn concordance with previous studies on global copy number alterations landscape, the study showed similar alterations. However, when the landscape was de-convoluted into histotypes, distinct alterations were observed. We report here significant histotype-specific copy number alterations in ovarian cancer and showed that there is genomic diversity amongst the histotypes. 76 cancer genes were found to be significantly altered with several as potential copy number drivers, including ERBB2 in mucinous, and TPM3 in endometrioid histotypes. ERBB2 was found to have preferential alterations, where it was amplified in mucinous (28.6%) but deleted in serous tumors (15.1%). Validation of ERBB2 expression showed significant correlation with microarray data (p=0.007). There also appeared to be reciprocal relationship between KRAS mutation and copy number alterations. In mucinous tumors where KRAS mutation is common, the gene was not significantly altered. However, KRAS was significantly amplified in serous tumors where mutations are rare in high grade tumors.ConclusionsThe study demonstrates that the copy number landscape is specific to the histotypes and identification of these alterations can pave the way for targeted drug therapy specific to the histotypes.

Abstract 3958: Multi-Reg: An integrative parallel approach to uncover drivers of cancer

Abstract Tumor samples harbor a vast number of genomic alterations of various kinds, and it is difficult to distinguish driver alterations that contribute to oncogenesis from passenger alterations. Most computational methods identify driver genes by focusing on the most frequent copy number alterations. Previous work in our lab has led to the development of CONEXIC, a Bayesian algorithm that identifies candidate driver genes in cancer and links them to gene expression signatures they govern by integrating copy number and gene expression (Akavia et al, Cell, 2010). This algorithm was applied to data from melanoma cell lines, where it correctly identified known drivers, such as MITF and KLF6, and connected them to their known targets. In addition, it predicted novel tumor dependencies not previously implicated in melanoma, which were validated experimentally. Drivers may act concurrently, where not only the strongest one is important. For example, either PTEN deletion or AKT activation can lead to a similar expression signature and phenotype. Therefore, we developed a new algorithm, based on the same principles as CONEXIC, with multiple improvements. The new algorithm - Multi-Reg - is capable of detecting multiple candidate regulators that can all act in parallel to regulate an expression signature, and is also capable of integrating mutations in addition to copy number and gene expression data. We applied Multi-Reg to glioblastoma data from The Cancer Genome Atlas (TCGA). This data includes copy number, gene expression and mutations for hundreds of primary tumor samples. Multi-Reg has identified putative drivers that were missed by CONEXIC, such as the known genes PDGFRA and NF1, in addition to EGFR &amp; ERB2 (identified by CONEXIC). Additionally, since Multi-Reg candidate drivers act in parallel, we can group them by shared targets. For example, EGFR &amp; ERRB2 induce the same genes, which represent the Mesenchymal subtype of glibolastoma. These same genes are repressed by PDGFRA &amp; NF1. This matches the known behavior of glioblastoma subtypes, where EGFR &amp; PDGFRA characterize the Mesenchymal and Proneural subtypes, respectively. Thus, our results correctly identify known drivers of glioblastoma. Additionally, Multi-Reg results identified RHPN2 as a novel oncogenic factor controlling a gene expression signature related to adhesion. Validation has shown that while RHPN2 has no effect on cell proliferation it induces invasiveness in glioblastoma cell lines. This shows that Multi-Reg cannot only discover drivers, but can link them to the oncogenic phenomena they controls, and suggest the appropriate biological validation for it. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 3958. doi:1538-7445.AM2012-3958

Abstract A26: Multi-Reg: An integrative parallel approach to uncover drivers of cancer

Abstract Tumor samples harbor a vast number of genomic alterations of various kinds, and it is not easy to distinguish driver alterations that contribute to oncogenesis from passenger alterations. Most computational methods attempt to identify driver alternations by focusing on the most frequent alterations. Previous work in our lab has led to the development of CONEXIC, a Bayesian framework for integrating copy number and gene expression to identify candidate driver genes in cancer and to link them to gene expression signatures they regulate (Akavia et al, Cell, 2010). This framework was applied to data from melanoma cell lines, where it correctly identified known drivers (MITF) and connected them to their known targets. In addition, it predicted novel tumor dependencies not previously implicated in melanoma, which were confirmed experimentally. In general, current algorithms identify only one driver (the strongest) controlling a gene expression signature. However, drivers may act in parallel, where not only the strongest one is important. For example, either PTEN deletion or AKT activation can lead to a similar expression signature and phenotype. Therefore, we developed a new algorithm, based on the same principles as CONEXIC with multiple improvements. The new algorithm (called Multi-Reg) is capable of detecting multiple candidate regulators that can all act in parallel to regulate an expression signature. This algorithm can integrate mutations in addition to copy number and expression. Finally, we have designed Multi-Reg to be easier and quicker to run and more robust. We applied Multi-Reg to glioblastoma data from The Cancer Genome Atlas (TCGA). This data includes copy number, gene expression and mutations for hundreds of primary tumor samples. We found 84 candidate regulators that were missed by CONEXIC, but discovered by Multi-Reg. Because of Multi-Reg's ability to search for genes working in parallel, it identified FGFR3, PDGFRA and NF1, in addition to EGFR &amp; MET (identified by CONEXIC), as important candidate drivers. Additionally, Multi-Reg results identified RHPN2 as a novel oncogenic factor controlling a gene expression signature related to invasion and migration. Validation has shown that RHPN2 has limited effect on cell proliferation but induces invasiveness in glioblastoma cell lines. Our results correctly identify known drivers of glioblastoma progression, including oncogenes such as EGFR, MET, CEBPB and tumor suppressors such as p16 and NF1. Multi-Reg also has the capability to identify more regulators than CONEXIC, and has correctly linked RHPN2 to the oncogenic phenomena it controls. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the Second AACR International Conference on Frontiers in Basic Cancer Research; 2011 Sep 14-18; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2011;71(18 Suppl):Abstract nr A26.

Penalized regression elucidates aberration hotspots mediating subtype-specific transcriptional responses in breast cancer

Copy number alterations (CNAs) associated with cancer are known to contribute to genomic instability and gene deregulation. Integrating CNAs with gene expression helps to elucidate the mechanisms by which CNAs act and to identify the transcriptional downstream targets of CNAs. Such analyses can help to sort functional driver events from the many accompanying passenger alterations. However, the way CNAs affect gene expression can vary in different cellular contexts, for example between different subtypes of the same cancer. Thus, it is important to develop computational approaches capable of inferring differential connectivity of regulatory networks in different cellular contexts. We propose a statistical deregulation model that integrates copy number and expression data of different disease subtypes to jointly model common and differential regulatory relationships. Our model not only identifies CNAs driving gene expression changes, but at the same time also predicts differences in regulation that distinguish one cancer subtype from the other. We implement our model in a penalized regression framework and demonstrate in a simulation study the feasibility and accuracy of our approach. Subsequently, we show that this model can identify both known and novel aspects of cross-talk between the ER and NOTCH pathways in ER-negative-specific deregulations, when compared with ER-positive breast cancer. This flexible model can be applied on other modalities such as methylation or microRNA and expression to disentangle cancer signaling pathways. The Bioconductor-compliant R package DANCE is available from www.markowetzlab.org/software/ yinyin.yuan@cancer.org.uk; florian.markowetz@cancer.org.uk.

Genetic changes including gene copy number alterations and their relation to prognosis in childhood acute myeloid leukemia

We studied a series of 68 subjects diagnosed with childhood acute myeloid leukemia (AML) using conventional cytogenetics and fluorescence in situ hybridization (FISH), polymerase chain reaction (PCR) to analyze mutations in FLT3 and NPM1 genes, and/or array comparative genomic hybridization (CGH). Cytogenetic/FISH abnormalities were observed in 71% of subjects, FLT3-ITD mutations in 15%, and NPM1 mutations in 13%. The array CGH alterations (average 3.6 per case) were observed in 96% of the tested subjects. The most frequent alterations were gains of 8q24.3 and 11p15.5-p15.4 in 16% of the samples. Six genes (AKT1, RUNX1, LTB, SDC1, RUNX1T1, and JAK2) from the imbalanced regions have been reported to be involved in AML, whereas other 30 cancer genes, not previously reported in an AML context, were identified as imbalanced. They probably correspond to non passenger alterations that cooperate with the recurrent translocations. The clinical data and genetic changes were tested to find out the possible association with prognosis. Genomic instability (four or more genomic imbalances) was correlated with poor patient outcome (p = 0.029).

Integrative approach for prioritizing cancer genes in sporadic colon cancer

The current multistep carcinogenesis models of colon cancer do not fully capture the genetic heterogeneity of the disease, which is additionally complicated by the presence of passenger and driver genetic alterations. The aim of this study was to select in the context of this significant heterogeneity additional genes functionally related to colon cancer development. High-throughput copy number and gene expression data of 36 microsatellite stable sporadic colon cancers resected from patients of a single institution characterized for mutations in APC, KRAS, TP53 and loss of 18q were analyzed. Genes whose expression correlated with the underlying copy number pattern were selected, and their association with the above listed mutations and overall survival was evaluated. Gain of 20q was strongly associated with TP53 mutation, and overall survival with alterations on 7p, 8p, 13q, 18q, and 20q. An association with 18q loss and gain of 8q24 was also observed. New candidate genes with a potential role in colon cancer are PLCG1 on 20q, DBC1 on 8q21, and NDGR1 on 8p24. In addition, an unexpected pattern of loss and mutability was found in the region upstream of the KRAS gene. By integrating copy number alterations with gene expression and mutations in colon cancer associated genes, we have developed a strategy that identifies previously known molecular features and additional players in the molecular landscape of colon cancer.