DNA Copy Number Data Research Articles

Deciphering Folate Receptor alphaGene Expression and mRNA Signatures in Ovarian Cancer: Implications for Precision Therapies.

Antibody-drug conjugates targeting folate receptor alpha (FRα) are a promising treatment for platinum-resistant ovarian cancer (OC) with high FRα expression. Challenges persist in accurately assessing FRα expression levels. Our study aimed to better elucidate FRα gene expression and identify mRNA signatures in OC. We pooled OC gene expression data from 16 public datasets, encompassing 1832 OC and 30 normal ovarian tissues. Additional data included DNA copy number and methylation data from TCGA and protein data from 363 cancer cell lines from the Broad Institute Cancer Cell Line Encyclopedia. FOLR1 mRNA expression was significantly correlated with protein expression in pan-cancer cell lines and ovarian cancer cell lines. FOLR1 expression was higher in OC samples than in normal ovarian tissues (OR = 3.88, p = 6.97 × 10-12). Patients with high FOLR1 expression were more likely to be diagnosed with serous histology, FIGO stage III-IV, and high-grade tumors; however, nearly similar percentages of patients with low FOLR1 expression were also diagnosed with these features. FOLR1 mRNA expression was not correlated with platinum sensitivity or complete surgery, nor with prognosis. However, we identified a 187-gene signature associated with high FOLR1 expression that was significantly associated with improved survival (HR = 0.71, p = 1.18 × 10-6), independently from clinicopathological features. We identified a gene expression signature correlated to high FRα expression and OC prognosis, which may be used to refine therapeutic strategies targeting FRα in OC. These findings warrant validation in larger cohorts.

Abstract 4307: Integrative molecular subtypes of acute myeloid leukemia

Abstract Introduction: Acute Myeloid Leukemia (AML) is a heterogenous disease characterized by distinct clinical course and prognosis based on genomics, epigenomics or transcriptomics profile. However, the multi-omics profiles have not been systematically integrated to define the integrative molecular subtypes of AML. There is a great clinical interest to identify the patterns across multi-omics profiles that could be used for prognosis and guiding targeted therapy in AML. Methods: To identify integrative molecular subtypes (iSubtypes) of AML, we performed an integrative clustering (iCluster) analysis of the AML multi-omics data (n=160) generated by The Cancer Genome Atlas (TCGA), which consisted of somatic mutation, DNA copy number, DNA methylation and RNA-seq gene expression data for 160 AML samples. We identified the multi-omics signatures that drove the molecular classification of AML. Based on the methylation and gene expression signatures, we derived a gene panel for classification of AML and verified the prognostic power of the gene panel using three independent AML datasets (n=1382). Results: We identified four iSubtypes of AML that featured distinct multi-omics signatures. At the DNA level, the iSubtype 1 was characterized by chromosomal abnormalities and high-frequency mutation of TP53 (30%) and RUNX1 (27%); the iSubtype 2 was characterized by chromosomal abnormalities and high-frequency mutation of CEBPA (20%) and FLT3 (26%); while the iSubtypes 3 and 4 were characterized by chromosomal normality and high-frequency mutation of FLT3 (34%, 41%), NPM1 (37%, 57%) and DNMT3A (20%, 41%). At the epigenomics level, the iSubtypes 1, 3 and 4 were characterized by hypomethylation of subtype driver genes, while the iSubtypes 2 was characterized by hypermethylation of subtype driver genes. At the transcriptomics level, the 4 iSubtypes were distinguished by differentially expressed genes involved in immune process, regulation of immune process, angiogenesis, leukocyte cell activation and migration, wound healing and cell structure organization, etc. The iSubtypes 1 and 4 had the worse overall survival (OS), while the iSubtype 3 had the best and the iSubtype 2 had the middle OS. Based on the subtype-driving methylation and transcription signatures, we derived a 571-gene panel for classification of AML. Using 3 independent AML transcriptomics datasets, we demonstrated that the excellent power of the gene panel in classifying AML into 4 gene expression subtypes with similar survival outcomes. Conclusions: iSubtypes of AML are jointly determined by multi-omics profiles. The subtype-driving methylation and transcription signature have excellent power in classifying AML into clinically relevant subtypes. This integrative analysis provides insights into the biological processes underling AML. Citation Format: Qianxing (Quincy) Mo, Seongseok Yun, David A. Sallman, Nicole Vincelette, Guang Peng, Ling Zhang, Jeffrey E. Lancet, Eric Padron. Integrative molecular subtypes of acute myeloid leukemia. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4307.

A novel method to identify and characterize personalized functional driver lncRNAs in cancer samples

Cancer is a highly heterogeneous disease, and different individuals of the same cancer type can display different therapeutic effects and prognosis. Genetic variation of long non-coding RNA is the key factor driving tumor development, and plays an important role in genetic and biological heterogeneity. Therefore, it is of great significance to identify lncRNA as a driving factor in the non-coding region and explain its function in tumors for revealing the pathogenesis of cancer. In this study, we developed an integrated method to identify Personalized Functional Driver lncRNAs (PFD-lncRNAs) by integrating the DNA copy number data, gene expression data, and the biological subpathways information. Then, we applied the method to identify 2695 PFD-lncRNAs in 5334 samples across 19 cancer types. We performed an analysis of the association between PFD-lncRNAs and drug sensitivity, which provides medication guidance in disease therapy and drug discovery in the individual. Our research is of great significance for elucidating the biological roles of lncRNA genetic variation in cancer, revealing the related mechanism of cancer, and providing novel insights for individualized medicine.

Whole genome copy number analyses reveal a highly aberrant genome in TP53 mutant lung adenocarcinoma tumors

BackgroundGenetic alterations are common in non-small cell lung cancer (NSCLC), and DNA mutations and translocations are targets for therapy. Copy number aberrations occur frequently in NSCLC tumors and may influence gene expression and further alter signaling pathways. In this study we aimed to characterize the genomic architecture of NSCLC tumors and to identify genomic differences between tumors stratified by histology and mutation status. Furthermore, we sought to integrate DNA copy number data with mRNA expression to find genes with expression putatively regulated by copy number aberrations and the oncogenic pathways associated with these affected genes.MethodsCopy number data were obtained from 190 resected early-stage NSCLC tumors and gene expression data were available from 113 of the adenocarcinomas. Clinical and histopathological data were known, and EGFR-, KRAS- and TP53 mutation status was determined. Allele-specific copy number profiles were calculated using ASCAT, and regional copy number aberration were subsequently obtained and analyzed jointly with the gene expression data.ResultsThe NSCLC tumors tissue displayed overall complex DNA copy number profiles with numerous recurrent aberrations. Despite histological differences, tissue samples from squamous cell carcinomas and adenocarcinomas had remarkably similar copy number patterns. The TP53-mutated lung adenocarcinomas displayed a highly aberrant genome, with significantly altered copy number profiles including gains, losses and focal complex events. The EGFR-mutant lung adenocarcinomas had specific arm-wise aberrations particularly at chromosome7p and 9q. A large number of genes displayed correlation between copy number and expression level, and the PI(3)K-mTOR pathway was highly enriched for such genes.ConclusionsThe genomic architecture in NSCLC tumors is complex, and particularly TP53-mutated lung adenocarcinomas displayed highly aberrant copy number profiles. We suggest to always include TP53-mutation status when studying copy number aberrations in NSCLC tumors. Copy number may further impact gene expression and alter cellular signaling pathways.

Integrative analysis of prognostic long non-coding RNAs with copy number variation in bladder cancer.

Copy number variations (CNVs), which can affect the role of long non-coding RNAs (lncRNAs), are important genetic changes seen in some malignant tumors. We analyzed lncRNAs with CNV to explore the relationship between lncRNAs and prognosis in bladder cancer (BLCA). Messenger RNA (mRNA) expression levels, DNA methylation, and DNA copy number data of 408 BLCA patients were subjected to integrative bioinformatics analysis. Cluster analysis was performed to obtain different subtypes and differently expressed lncRNAs and coding genes. Weighted gene co-expression network analysis (WGCNA) was performed to identify the co-expression gene and lncRNA modules. CNV-associated lncRNA data and their influence on cancer prognosis were assessed with Kaplan-Meier survival curve. Multi-omics integration analysis revealed five prognostic lncRNAs with CNV, namely NR2F1-AS1, LINC01138, THUMPD3-AS1, LOC101928489,and TMEM147-AS1,and a risk-score signature related to overall survival in BLCA was identified. Moreover, validated results in another independent Gene Expression Omnibus (GEO) dataset, GSE31684, were consistent with these results. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that the mitogen-activated protein kinase (MAPK) signaling pathway, focal adhesion pathway, and Janus kinase-signal transducers and activators of transcription (JAK-STAT) signaling pathway were enriched in a high-risk score pattern, suggesting that imbalance in these pathways is closely related to tumor development. We revealed the prognosis-related lncRNAs by analyzing the expression profiles of lncRNAs and CNVs, which can be used as prognostic biomarkers for BLCA.

Development and validation of prognostic markers in sarcomas base on a multi-omics analysis

BackgroundIn sarcomas, the DNA copy number and DNA methylation exhibit genomic aberrations. Transcriptome imbalances play a driving role in the heterogeneous progression of sarcomas. However, it is still unclear whether abnormalities of DNA copy numbers are systematically related to epigenetic DNA methylation, thus, a comprehensive analysis of sarcoma occurrence and development from the perspective of epigenetic and genomics is required.MethodsRNASeq, copy number variation (CNV), methylation data, clinical follow-up information were obtained from The Cancer Genome Atlas (TCGA) and GEO database. The association between methylation and CNV was analyzed to further identify methylation-related genes (MET-Gs) and CNV abnormality-related genes (CNV-Gs). Subsequently DNA copy number, methylation, and gene expression data associated with the MET-Gs and CNV-Gs were integrated to determine molecular subtypes and clinical and molecular characteristics of molecular subtypes. Finally, key biomarkers were determined and validated in independent validation sets.ResultsA total of 5354 CNV-Gs and 4042 MET-Gs were screened and showed a high degree of consistency. Four molecular subtypes (iC1, iC2, iC3, and iC4) with different prognostic significances were identified by multiomics cluster analysis, specifically, iC2 had the worst prognosis and iC4 indicated an immune-enhancing state. Three potential prognostic markers (ENO1, ACVRL1 and APBB1IP) were determined after comparing the molecular characteristics of the four molecular subtypes. The expression of ENO1 gene was significantly correlated with CNV, and was noticeably higher in iC2 subtype with the worst prognosis than any other subtypes. The expressions of ACVRL1 and APBB1IP were negatively correlated with methylation, and were high-expressed in the iC4 subtype with the most favorable prognosis. In addition, the number of silent/nonsilent mutations and neoantigens in iC2 subtype were significantly more than those in iC1/iC3/iC4 subtype, and the same trend was also observed in CNV Gain/Loss.ConclusionThe current comprehensive analysis of genomic and epigenomic regulation provides new insights into multilayered pathobiology of sarcomas. Four molecular subtypes and three prognostic markers developed in this study improve the current understanding of the molecular mechanisms underlying sarcoma.

Integrated Analysis of the Gene Expression Profiling and Copy Number Aberration of the Ovarian Cancer

Objective: DNA copy number alterations and difference expression are frequently observed in ovarian cancer. The purpose of this way was to pinpoint gene expression change that was associated with alterations in DNA copy number and could therefore enlighten some potential oncogenes and stability genes with functional roles in cancers, and investigated the bioinformatics significance for those correlated genes. Method: We obtained the DNA copy number and mRNA expression data from the Cancer Genomic Atlas and identified the most statistically significant copy number alteration regions using the GISTIC. Then identified the significance genes between the tumor samples within the copy number alteration regions and analyzed the correlation using a binary matrix. The selected genes were subjected to bioinformatics analysis using GSEA tool. Results: GISTIC analysis results showed there were 45 significance copy number amplification regions in the ovarian cancer, SAM and Fisher’s exact test found there have 40 genes can affect the expression level, which located in the amplification regions. That means we obtained 40 genes which have a correlation between copy number amplification and drastic up- and down-expression, which p-value ere overlapped with the several published studies which were focused on the gene study of tumorigenesis. Conclusion: The use of statistics and bioinformatics to analyze the microarray data can found an interaction network involved. The combination of the copy number data and expression has provided a short list of candidate genes that are consistent with tumor driving roles. These would offer new ideas for early diagnosis and treat target of ovarian cancer.

CellMiner Cross-Database (CellMinerCDB) version 1.2: Exploration of patient-derived cancer cell line pharmacogenomics

CellMiner Cross-Database (CellMinerCDB, discover.nci.nih.gov/cellminercdb) allows integration and analysis of molecular and pharmacological data within and across cancer cell line datasets from the National Cancer Institute (NCI), Broad Institute, Sanger/MGH and MD Anderson Cancer Center (MDACC). We present CellMinerCDB 1.2 with updates to datasets from NCI-60, Broad Cancer Cell Line Encyclopedia and Sanger/MGH, and the addition of new datasets, including NCI-ALMANAC drug combination, MDACC Cell Line Project proteomic, NCI-SCLC DNA copy number and methylation data, and Broad methylation, genetic dependency and metabolomic datasets. CellMinerCDB (v1.2) includes several improvements over the previously published version: (i) new and updated datasets; (ii) support for pattern comparisons and multivariate analyses across data sources; (iii) updated annotations with drug mechanism of action information and biologically relevant multigene signatures; (iv) analysis speedups via caching; (v) a new dataset download feature; (vi) improved visualization of subsets of multiple tissue types; (vii) breakdown of univariate associations by tissue type; and (viii) enhanced help information. The curation and common annotations (e.g. tissues of origin and identifiers) provided here across pharmacogenomic datasets increase the utility of the individual datasets to address multiple researcher question types, including data reproducibility, biomarker discovery and multivariate analysis of drug activity.

Molecular correlates of sensitivity to PARP inhibition beyond homologous recombination deficiency in pre-clinical models of colorectal cancer point to wild-type TP53 activity.

BackgroundPARP inhibitors are active in various tumour types beyond BRCA-mutant cancers, but their activity and molecular correlates in colorectal cancer (CRC) are not well studied.MethodsMutations and genome-wide mutational patterns associated with homologous recombination deficiency (HRD) were investigated in 255 primary CRCs with whole-exome sequencing and/or DNA copy number data. Efficacy of five PARP inhibitors and their molecular correlates were evaluated in 93 CRC cell lines partly annotated with mutational-, DNA copy number-, and/or gene expression profiles. Post-treatment gene expression profiling and specific protein expression analyses were performed in two pairs of PARP inhibitor sensitive and resistant cell lines.FindingsA subset of microsatellite stable (MSS) CRCs had truncating mutations in homologous recombination-related genes, but these were not associated with genomic signatures of HRD. Eight CRC cell lines (9%) were sensitive to PARP inhibition, but sensitivity was not predicted by HRD-related genomic and transcriptomic signatures. In contrast, drug sensitivity in MSS cell lines was strongly associated with TP53 wild-type status (odds ratio 15.7, p = 0.023) and TP53-related expression signatures. Increased downstream TP53 activity was among the primary response mechanisms, and TP53 inhibition antagonized the effect of PARP inhibitors. Wild-type TP53-mediated suppression of RAD51 was identified as a possible mechanism of action for sensitivity to PARP inhibition.InterpretationPARP inhibitors are active in a subset of CRC cell lines and preserved TP53 function may increase the likelihood of response.

Multi-omics integrative analysis and survival risk model construction of non-small cell lung cancer based on The Cancer Genome Atlas datasets.

Lung cancer is a major cause of cancer-associated mortality worldwide. However, the association between multi-omics data and survival in lung cancer is not fully understood. The present study investigated the performance of the methylation survival risk model in multi-platform integrative molecular subtypes and aimed to identify copy number (CN) variations and mutations that are associated with survival risk. The present study analyzed 439 lung adenocarcinoma cases based on DNA methylation, RNA, microRNA (miRNA), DNA copy number and mutations from The Cancer Genome Atlas datasets. First, six cancer subtypes were identified using integrating DNA methylation, RNA, miRNA and DNA copy number data. The least absolute shrinkage and selection operator (LASSO) regression algorithm was used to extract methylation sites of survival model and calculate the methylation-based survival risk indices for all patients. Survival for patients in the high-risk group was significantly lower compared with that for patients in the low-risk group (P<0.05). The present study also assessed methylation-based survival risks of the six subtypes and analyzed the association between survival risk and non-silent mutation rate, number of segments, fraction of segments altered, aneuploidy score, number of segments with loss of heterozygosity (LOH), fraction of segments with LOH and homologous repair deficiency. Finally, the specific copy number regions and mutant genes associated with the different subtypes were identified (P<0.01). Chromosome regions 17q24.3 and 11p15.5 were identified as those with the most survival risk-associated copy number variation regions, while a total of 29 mutant genes were significantly associated with survival (P<0.01).

Identification of a minimal region of loss on chromosome 6q27 associated with poor survival of high-risk neuroblastoma patients

ABSTRACTPatients with high-risk neuroblastoma (HR-NB) often initially respond to therapy, but afterward they become resistant and disease recurred. Unfortunately, it does not exist one or more specific chromosome defects associated with relapse or refractory NB. Recently, genomic evidence from primary tumors indicated that the distal region of chromosome 6q is loss in HR-NB patients with fatal outcome. We identified a minimal common region of loss of chromosome 6q27 spanning an area of 2.09 Mb by high-resolution DNA copy number data of a small cohort of HR-NB samples carrying 6q loss. This region of loss harbored five genes T, SFT2D1, RPS6KA2, FGFR1OP, and UNC93A. We found that low SFT2D1, RPS6KA2, and FGFR1OP gene expression predicted poor outcome in HR-NB patients using public R2 Platform. Further functional studies will be essential to confirm the presumed tumor suppressor gene(s) located within 6q27 region. These results suggest that SFT2D1, RPS6KA2, and FGFR1OP genes may be responsible for poor prognosis of HR-NB tumors with 6q27 loss, and their haploinsufficiency may be crucial in accelerating tumor progression.

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

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

Essential genes shape cancer genomes through linear limitation of homozygous deletions

The landscape of somatic acquired deletions in cancer cells is shaped by positive and negative selection. Recurrent deletions typically target tumor suppressor, leading to positive selection. Simultaneously, loss of a nearby essential gene can lead to negative selection, and introduce latent vulnerabilities specific to cancer cells. Here we show that, under basic assumptions on positive and negative selection, deletion limitation gives rise to a statistical pattern where the frequency of homozygous deletions decreases approximately linearly between the deletion target gene and the nearest essential genes. Using DNA copy number data from 9,744 human cancer specimens, we demonstrate that linear deletion limitation exists and exposes deletion-limiting genes for seven known deletion targets (CDKN2A, RB1, PTEN, MAP2K4, NF1, SMAD4, and LINC00290). Downstream analysis of pooled CRISPR/Cas9 data provide further evidence of essentiality. Our results provide further insight into how the deletion landscape is shaped and identify potentially targetable vulnerabilities.

Abstract 1647: Integrative subtype analysis of muscle-invasive bladder cancer reveals subtypes that have different overall survival and respond differently to neoadjuvant chemotherapy

Abstract Introduction: Muscle-invasive bladder cancer (MIBC) is a heterogeneous disease driven by accumulative alterations on DNA, epigenomics, genomics and protein expression levels. There is a clinical need to classify MIBC samples into molecular subtypes and to identify driver molecular alterations that could be targeted by precision medicine. Methods: We performed an integrative clustering analysis of 388 TCGA MIBC samples. Each of the samples has somatic mutation, DNA copy number, methylation and gene expression data. We used Bayesian iClusterPlus method to identify integrative MIBC subtypes and subtype-specific genes and genomic features. Pathways and gene sets altered in the subtypes were identified by gene set and gene functional term enrichment analyses. To investigate the prognostic power of the subtype-specific gene expression signature, we compiled 5 more publicly available MIBC data sets and classified the samples into different subtypes using 1-nearest neighbor method. Subtype-specific overall survival was estimated by Kaplan-Meier method. Log-rank test and Cox model were used to compare the subtype-specific survival functions. Results: We identified two integrative MIBC subtypes with distinct genomic landscapes. The top driver mutated genes included TP53, KDM6A, FGFR3, ELF3, RB1 and PIK3C2A. DNA regions containing MTAP, CDKN2A/2B, and several INFA genes were the driver altered regions. The integrative subtypes had similar gene expression pattern as the basal and differentiated subtypes reported by Mo et al., 2018 (JNCI 110(5):448-459), where a group of basal and differentiated markers were differentially expressed between the two subtypes. For this reason, we named them as basal and differentiated integrative subtypes. The basal subtypes were characterized by up-regulation of immune signaling pathways including CTLA-4, cytokine and inflammatory, NKT and JAK_STAT signaling pathways. A significant amount of the driver genes had negative correlation between methylation and gene expression. Furthermore, the subtype-specific gene expression signature was prognostic. For chemotherapy-naïve patients, the basal subtype was associated with worse overall survival. However, for patients undergone neoadjuvant chemotherapy, the basal subtype of patients had a better overall survival. Conclusion: We identified basal and differentiated integrative subtypes of MIBC, which were characterized by distinct alterations on the DNA, epigenomics and gene expression levels. The two subtypes were associated with differentially altered pathways such as immune signaling pathways and responded differently to neoadjuvant chemotherapy. This integrative analysis has provided us a comprehensive picture of MIBC biology and revealed targetable molecular pathways for future precision therapeutics. Citation Format: QIANXING MO, Roger Li, Keith Chan. Integrative subtype analysis of muscle-invasive bladder cancer reveals subtypes that have different overall survival and respond differently to neoadjuvant chemotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1647.

MOSClip: multi-omic and survival pathway analysis for the identification of survival associated gene and modules.

Survival analyses of gene expression data has been a useful and widely used approach in clinical applications. But, in complex diseases, such as cancer, the identification of survival-associated cell processes - rather than single genes - provides more informative results because the efficacy of survival prediction increases when multiple prognostic features are combined to enlarge the possibility of having druggable targets. Moreover, genome-wide screening in molecular medicine has rapidly grown, providing not only gene expression but also multi-omic measurements such as DNA mutations, methylation, expression, and copy number data. In cancer, virtually all these aberrations can contribute in synergy to pathological processes, and their measurements can improve a patient’s outcome and help in diagnosis and treatment decisions. Here, we present MOSClip, an R package implementing a new topological pathway analysis tool able to integrate multi-omic data and look for survival-associated gene modules. MOSClip tests the survival association of dimensionality-reduced multi-omic data using multivariate models, providing graphical devices for management, browsing and interpretation of results. Using simulated data we evaluated MOSClip performance in terms of false positives and false negatives in different settings, while the TCGA ovarian cancer dataset is used as a case study to highlight MOSClip’s potential.

Abstract P2-03-03: BRG1-SOX4 mediates a novel and essential signaling network that activates PI3K/Akt signaling in TNBC

Abstract Background: Triple negative (TNBC) breast cancer, which is largely synonymous with the basal-like molecular subtype, is an aggressive malignancy that accounts for nearly 1 in 4 breast cancer related deaths and disproportionately affects younger women and women of African American decent. Given the lack of drug-able targets expressed by TNBC tumors, few therapeutic options exist beyond currently utilized cytotoxic therapies, and the overall prognosis for these patients remains poor. While TNBC tumors are characterized by high PI3K signaling, clinical trials targeting this pathway have had limited success. Therefore, identifying mechanisms driving key oncogenic pathways, including PI3K, is paramount to understanding the transformation process and enabling the development of rational, personalized therapeutic regimens. Methods: We utilized a PI3K gene expression signature as a conceptual framework to analyze genome-wide mRNA expression and DNA copy number data from human breast tumors to identify genetic drivers of PI3K/Akt signaling. Kinome profiling was used to identify changes in the drug-able kinome regulated by these genes and in vitro studies were used to delineate mechanisms by which identified genes mediate oncogenic PI3K signaling in TNBC. Results: Integrative proteogenomic analyses of orthogonal genome-wide data from ˜3,000 human tumors from the TCGA and METABRIC studies identified amplification and overexpression of the oncogenic transcription factor SOX4 as well as the SWI/SNF ATPase BRG1 in tumors with high PI3K activity. These alterations were predominantly expressed in TNBC or basal-like breast tumors. Chromatin immunoprecipitation followed by DNA sequencing (ChIPseq) as well as shRNA-based studies confirmed that BRG1 regulates SOX4 expression in TNBC cell lines. Analyses of data from a genome-wide RNA interference (RNAi) screen in 27 breast cancer cell lines further indicated that SOX4 is essential in cell lines with high PI3K activity and this was confirmed by colony formation and cell proliferation assays. Importantly, in vitro analyses confirmed that both BRG1 and SOX4 regulate Akt phosphorylation and down-stream signaling. Profiling of the drug-able kinome in SOX4 depleted cell lines compared to control cells using Multiplexed kinase Inhibitor Beads couple with quantitative Mass Spectrometry (MIB/MS) identified 21 drug-able kinases regulated by SOX4 activity including TGFBR2 which has been previously shown to regulate PI3K activity. RNA sequencing (RNAseq) and RT-PCR analyses confirmed that SOX4 mediates TGFBR2 mRNA levels and co-immunoprecipitation experiments in conjunction with ChIP assays demonstrated that BRG1 and SOX4 form a complex at the TGFBR2 promoter and enhancer region to regulate TGFBR2 expression. Conclusions: In this study, we demonstrated that BRG1-SOX4 constitutes a novel and essential signaling pathway which promotes PI3K/Akt activity through TGFβ signaling in TNBC/basal-like breast cancer and leads to activation of additional, drug-able kinases. Given the essentiality of BRG1 and SOX4, our data suggest that targeting this interaction and/or the down-stream components of this pathway may represent a novel therapeutic strategy in TNBC. Citation Format: Gatza ML, Angus SP, Khella CA, Tong K, Verzi M, Mehta GA. BRG1-SOX4 mediates a novel and essential signaling network that activates PI3K/Akt signaling in TNBC [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P2-03-03.

CNVScope: Visually Exploring Copy Number Aberrations in Cancer Genomes.

Motivation:DNA copy number (CN) data are a fast-growing source of information used in basic and translational cancer research. Most CN segmentation data are presented without regard to the relationship between chromosomal regions. We offer both a toolkit to help scientists without programming experience visually explore the CN interactome and a package that constructs CN interactomes from publicly available data sets.Results:The CNVScope visualization, based on a publicly available neuroblastoma CN data set, clearly displays a distinct CN interaction in the region of the MYCN, a canonical frequent amplicon target in this cancer. Exploration of the data rapidly identified cis and trans events, including a strong anticorrelation between 11q loss and17q gain with the region of 11q loss bounded by the cell cycle regulator CCND1.Availability:The shiny application is readily available for use at http://cnvscope.nci.nih.gov/, and the package can be downloaded from CRAN (https://cran.r-project.org/package=CNVScope), where help pages and vignettes are located. A newer version is available on the GitHub site (https://github.com/jamesdalg/CNVScope/), which features an animated tutorial. The CNVScope package can be locally installed using instructions on the GitHub site for Windows and Macintosh systems. This CN analysis package also runs on a linux high-performance computing cluster, with options for multinode and multiprocessor analysis of CN variant data. The shiny application can be started using a single command (which will automatically install the public data package).

Functional genomics identifies AMPD2 as a new prognostic marker for undifferentiated pleomorphic sarcoma.

Soft-tissue sarcomas are rare, heterogeneous, and often aggressive mesenchymal cancers. Many of them are associated with poor outcome, partially because biomarkers that can identify high-risk patients are lacking. Studies on sarcomas are often limited by small sample-sizes rendering the identification of biomarkers difficult when focusing on individual cohorts. However, the increasing number of publicly available 'omics' data opens inroads to overcome this obstacle. Here, we combine transcriptome analyses, immunohistochemistry, and functional assays to show that high adenosine monophosphate deaminase 2 (AMPD2) is a robust prognostic biomarker for worse outcome in undifferentiated pleomorphic sarcoma (UPS). Gene expression and survival data for UPS from two independent studies were subjected to survival association-testing. Genes, whose high expression was significantly correlated with worse outcome in both cohorts, were considered as biomarker candidates. The best candidate, AMPD2, was validated in a tissue microarray. Analysis of DNA copy-number data and matched transcriptomes indicated that high AMPD2 expression is significantly correlated with gains at the AMPD2 locus. Gene set enrichment analyses of AMPD2 co-expressed genes in both transcriptome datasets suggested that AMPD2-high UPS are enriched in tumorigenic signatures. Consistently, knockdown of AMPD2 by RNA interference in an UPS cell line inhibited proliferation in vitro and tumorigenicity in vivo. Collectively, we provide evidence that AMPD2 may serve as a biomarker for outcome prediction in UPS. Our study exemplifies how the integration of 'omics' data, immunohistochemistry, and functional experiments can identify novel biomarkers even in a rare sarcoma, which may serve as a blueprint for biomarker identification for other rare cancers.

Abstract LB-378: Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing

Abstract Chromothripsis is a newly discovered mutational phenomenon involving massive, clustered genomic rearrangements that occurs in cancer and other diseases. Recent studies in cancer suggest that chromothripsis may be far more common than initially inferred from low resolution DNA copy number data. Here, we analyze the patterns of chromothripsis across 2,658 tumors spanning 39 cancer types using whole-genome sequencing data. We find that chromothripsis events are pervasive across cancers, with a frequency of &amp;gt;50% in several cancer types. Whereas canonical chromothripsis profiles display oscillations between two copy number states, a considerable fraction of the events involves multiple chromosomes as well as additional structural alterations. In addition to non-homologous end-joining, we detect signatures of replicative processes and templated insertions. Chromothripsis contributes to oncogene amplification as well as to inactivation of genes such as mismatch-repair related genes. These findings show that chromothripsis is a major process driving genome evolution in human cancer. Citation Format: Isidro Cortés-Ciriano, June-Koo Lee, Ruibin Xi, Dhawal Jain, Youngsook L. Jung, Lixing Yang, Dmitry Gordenin, Leszek J. Klimczak, Cheng-Zhong Zhang, David S. Pellman, Peter J. Park. Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr LB-378.

Genome-wide multi-omics profiling of the 8p11-p12 amplicon in breast carcinoma.

Genomic instability contributes to the neoplastic phenotype by deregulating key cancer-related genes, which in turn can have a detrimental effect on patient outcome. DNA amplification of the 8p11-p12 genomic region has clinical and biological implications in multiple malignancies, including breast carcinoma where the amplicon has been associated with tumor progression and poor prognosis. However, oncogenes driving increased cancer-related death and recurrent genetic features associated with the 8p11-p12 amplicon remain to be identified. In this study, DNA copy number and transcriptome profiling data for 229 primary invasive breast carcinomas (corresponding to 185 patients) were evaluated in conjunction with clinicopathological features to identify putative oncogenes in 8p11-p12 amplified samples. Illumina paired-end whole transcriptome sequencing and whole-genome SNP genotyping were subsequently performed on 23 samples showing high-level regional 8p11-p12 amplification to characterize recurrent genetic variants (SNPs and indels), expressed gene fusions, gene expression profiles and allelic imbalances. We now show previously undescribed chromothripsis-like patterns spanning the 8p11-p12 genomic region and allele-specific DNA amplification events. In addition, recurrent amplification-specific genetic features were identified, including genetic variants in the HIST1H1E and UQCRHL genes and fusion transcripts containing MALAT1 non-coding RNA, which is known to be a prognostic indicator for breast cancer and stimulated by estrogen. In summary, these findings highlight novel candidate targets for improved treatment of 8p11-p12 amplified breast carcinomas.