A comprehensive characterization of genome-wide copy number aberrations in colorectal cancer reveals novel oncogenes and patterns of alterations

To develop a comprehensive overview of copy number aberrations (CNAs) in stage-II/III colorectal cancer (CRC), we characterized 302 tumors from the PETACC-3 clinical trial. Microsatellite-stable (MSS) samples (n = 269) had 66 minimal common CNA regions, with frequent gains on 20 q (72.5%), 7 (41.8%), 8 q (33.1%) and 13 q (51.0%) and losses on 18 (58.6%), 4 q (26%) and 21 q (21.6%). MSS tumors have significantly more CNAs than microsatellite-instable (MSI) tumors: within the MSI tumors a novel deletion of the tumor suppressor WWOX at 16 q23.1 was identified (p<0.01). Focal aberrations identified by the GISTIC method confirmed amplifications of oncogenes including EGFR, ERBB2, CCND1, MET, and MYC, and deletions of tumor suppressors including TP53, APC, and SMAD4, and gene expression was highly concordant with copy number aberration for these genes. Novel amplicons included putative oncogenes such as WNK1 and HNF4A, which also showed high concordance between copy number and expression. Survival analysis associated a specific patient segment featured by chromosome 20 q gains to an improved overall survival, which might be due to higher expression of genes such as EEF1B2 and PTK6. The CNA clustering also grouped tumors characterized by a poor prognosis BRAF-mutant-like signature derived from mRNA data from this cohort. We further revealed non-random correlation between CNAs among unlinked loci, including positive correlation between 20 q gain and 8 q gain, and 20 q gain and chromosome 18 loss, consistent with co-selection of these CNAs. These results reinforce the non-random nature of somatic CNAs in stage-II/III CRC and highlight loci and genes that may play an important role in driving the development and outcome of this disease.     

RSF1 and Not Cyclin D1 Gene Amplification May Predict Lack of Benefit from Adjuvant Tamoxifen in High-Risk Pre-Menopausal Women in the MA.12 Randomized Clinical Trial

Most women with estrogen receptor expressing breast cancers receiving anti-estrogens such as tamoxifen may not need or benefit from them. Besides the estrogen receptor, there are no predictive biomarkers to help select breast cancer patients for tamoxifen treatment. CCND1 (cyclin D1) gene amplification is a putative candidate tamoxifen predictive biomarker. The RSF1 (remodeling and spacing factor 1) gene is frequently co-amplified with CCND1 on chromosome 11q. We validated the predictive value of these biomarkers in the MA.12 randomized study of adjuvant tamoxifen vs. placebo in high-risk premenopausal early breast cancer. Premenopausal women with node-positive/high-risk node-negative early breast cancer received standard adjuvant chemotherapy and then were randomized to tamoxifen (20 mg/day) or placebo for 5 yrs. Overall survival (OS) and relapse-free survival (RFS) were evaluated. Fluorescent in-situ hybridization was performed on a tissue microarray of 495 breast tumors (74% of patients) to measure CCND1 and RSF1 copy number. A multivariate Cox model to obtain hazard ratios (HR) adjusting for clinico-pathologic factors was used to assess the effect of these biomarkers on Os and RFS. 672 women were followed for a median of 8.4 years. We were able to measure the DNA copy number of CCND1 in 442 patients and RSF1 in 413 patients. CCND1 gene amplification was observed in 8.7% and RSF1 in 6.8% of these patients, preferentially in estrogen receptor-positive breast cancers. No statistically significant interaction with treatment was observed for either CCND1 or RSF1 amplification, although patients with high RSF1 copy number did not show benefit from adjuvant tamoxifen (HR = 1.11, interaction p = 0.09). Unlike CCND1 amplification, RSF1 amplification may predict for outcome in high-risk premenopausal breast cancer patients treated with adjuvant tamoxifen.     

Common Genomic Aberrations in Mouse and Human Breast Cancers with Concurrent P53 Deficiency and Activated PTEN-PI3K-AKT Pathway

Simultaneous P53 loss and activation of the PTEN-restricted PI3K-AKT pathway frequently occur in aggressive breast cancers. P53 loss causes genome instability, while PTEN loss and/or activating mutations of PIK3CA and AKT promote cancer cell proliferation that also increases incidences of genomic aberrations. However, the genomic alterations associated with P53 loss and activated PTEN-PI3K-AKT signaling in breast cancer have not been defined. Spatiotemporally controlled breast cancer models with inactivation of both P53 and Pten in adult mice have not been established for studying genomic alterations. Herein, we deleted both floxed Pten and Tp53 genes in the mammary gland epithelial cells in adult mice using a RCAS virus-mediated Cre-expressing system. These mice developed small tumors in 21 weeks, and poorly differentiated larger tumors in 26 weeks. In these tumors, we identified 360 genes mutated by nonsynonymous point mutations and small insertions and deletions (NSPMs/InDels), 435 genes altered by copy number amplifications (CNAs), and 450 genes inactivated by copy number deletions (CNDs). Importantly, 22.2%, 75.9% and 27.3% of these genes were also altered in human breast tumors with P53 and PTEN losses or P53 loss and activated PI3K-AKT signaling by NSPMs/InDels, CNAs and CNDs, respectively. Therefore, inactivation of P53 and Pten in adult mice causes rapid-growing breast tumors, and these tumors recapitulate a significant number of genetic aberrations in human breast tumors with inactivated P53 and activated PTEN-PI3K-AKT signaling. Further characterization of these commonly altered genes in breast cancer should help to identify novel cancer-driving genes and molecular targets for developing therapeutics.     

Focal chromosomal copy number aberrations in cancer—Needles in a genome haystack

The extent of focal chromosomal copy number aberrations (CNAs) in cancer has been uncovered through technical innovations, and this discovery has been critical for the identification of new cancer driver genes in genomics projects such as TCGA and ICGC. Unlike constitutive copy number variations (CNVs), focal CNAs are the result of many selection events during the evolution of cancer genomes. Therefore, it is possible that a single gene in a focal CNA gives the tumor a selective growth advantage. This concept has been instrumental in the discovery of new cancer driver genes. However, focal CNAs lack a consensus definition; therefore, we propose one based on pragmatic considerations. We also describe different strategies to identify focal CNAs and procedures to distinguish them from large CNAs and CNVs.     

Network modeling of the transcriptional effects of copy number aberrations in glioblastoma

DNA copy number aberrations (CNAs) are a hallmark of cancer genomes. However, little is known about how such changes affect global gene expression. We develop a modeling framework, EPoC (Endogenous Perturbation analysis of Cancer), to (1) detect disease‐driving CNAs and their effect on target mRNA expression, and to (2) stratify cancer patients into long‐ and short‐term survivors. Our method constructs causal network models of gene expression by combining genome‐wide DNA‐ and RNA‐level data. Prognostic scores are obtained from a singular value decomposition of the networks. By applying EPoC to glioblastoma data from The Cancer Genome Atlas consortium, we demonstrate that the resulting network models contain known disease‐relevant hub genes, reveal interesting candidate hubs, and uncover predictors of patient survival. Targeted validations in four glioblastoma cell lines support selected predictions, and implicate the p53‐interacting protein Necdin in suppressing glioblastoma cell growth. We conclude that large‐scale network modeling of the effects of CNAs on gene expression may provide insights into the biology of human cancer. Free software in MATLAB and R is provided.     

Leukemogenesis as a new approach to investigate the correlation between up regulated gene 4/upregulator of cell proliferation (URG4/URGCP) and signal transduction genes in leukemia

The aim of the study is to the determine the profiles of cell cycle genes and a new candidate oncogene of URG4/URGCP which play role in leukemia, establishing the association between the early prognosis of cancer and the quantitation of genetic changes, and bringing a molecular approach to definite diagnosis. In this study, 36 newly diagnosed patients’ with ALL-AML in the range of 0–18 years and six control group patients’ bone marrow samples were included. Total RNA was isolated from samples and then complementary DNA synthesis was performed. The obtained cDNAs have been installed 96 well plates after prepared appropriate mixtures and assessed with LightCycler^® 480 Real-Time PCR quantitatively. CHEK1, URG4/URGCP, CCNG1, CCNC, CDC16, KRAS, CDKN2D genes in the T-ALL group; CCND2, ATM, CDK8, CHEK1, TP53, CHEK2, CCNG2, CDK4, CDKN2A, E2F4, CCNC, KRAS genes in the precursor B-ALL group and CCND2, CDK6 genes in the AML group have shown significant increase in mRNA expression level. In the featured role of acute leukemia the regulating signaling pathways of leukemogenesis partially defined, although identification of new genetic markers in acute leukemia subgroups, will allow the development of early diagnostic and new treatment protocols.     

Impact on disease development, genomic location and biological function of copy number alterations in non-small cell lung cancer

Lung cancer, of which more than 80% is non-small cell, is the leading cause of cancer-related death in the United States. Copy number alterations (CNAs) in lung cancer have been shown to be positionally clustered in certain genomic regions. However, it remains unclear whether genes with copy number changes are functionally clustered. Using a dense single nucleotide polymorphism array, we performed genome-wide copy number analyses of a large collection of non-small cell lung tumors (n = 301). We proposed a formal statistical test for CNAs between different groups (e.g., non-involved lung vs. tumors, early vs. late stage tumors). We also customized the gene set enrichment analysis (GSEA) algorithm to investigate the overrepresentation of genes with CNAs in predefined biological pathways and gene sets (i.e., functional clustering). We found that CNAs events increase substantially from germline, early stage to late stage tumor. In addition to genomic position, CNAs tend to occur away from the gene locations, especially in germline, non-involved tissue and early stage tumors. Such tendency decreases from germline to early stage and then to late stage tumors, suggesting a relaxation of selection during tumor progression. Furthermore, genes with CNAs in non-small cell lung tumors were enriched in certain gene sets and biological pathways that play crucial roles in oncogenesis and cancer progression, demonstrating the functional aspect of CNAs in the context of biological pathways that were overlooked previously. We conclude that CNAs increase with disease progression and CNAs are both positionally and functionally clustered. The potential functional capabilities acquired via CNAs may be sufficient for normal cells to transform into malignant cells.     

Lack of Genomic Heterogeneity at High-Resolution aCGH between Primary Breast Cancers and Their Paired Lymph Node Metastases

Lymph-node metastasis (LNM) predict high recurrence rates in breast cancer patients. Systemic treatment aims to eliminate (micro)metastatic cells. However decisions regarding systemic treatment depend largely on clinical and molecular characteristics of primary tumours. It remains, however, unclear to what extent metastases resemble the cognate primary breast tumours, especially on a genomic level, and as such will be eradicated by the systemic therapy chosen. In this study we used high-resolution aCGH to investigate DNA copy number differences between primary breast cancers and their paired LNMs. To date, no recurrent LNM-specific genomic aberrations have been identified using array comparative genomic hybridization (aCGH) analysis. In our study we employ a high-resolution platform and we stratify on different breast cancer subtypes, both aspects that might have underpowered previously performed studies.To test the possibility that genomic instability in triple-negative breast cancers (TNBCs) might cause increased random and potentially also recurrent copy number aberrations (CNAs) in their LNMs, we studied 10 primary TNBC–LNM pairs and 10 ER-positive (ER+) pairs and verified our findings adding additionally 5 TNBC-LNM and 22 ER+-LNM pairs. We found that all LNMs clustered nearest to their matched tumour except for two cases, of which one was due to the presence of two distinct histological components in one tumour. We found no significantly altered CNAs between tumour and their LNMs in the entire group or in the subgroups. Within the TNBC subgroup, no absolute increase in CNAs was found in the LNMs compared to their primary tumours, suggesting that increased genomic instability does not lead to more CNAs in LNMs. Our findings suggest a high clonal relationship between primary breast tumours and its LNMs, at least prior to treatment, and support the use of primary tumour characteristics to guide adjuvant systemic chemotherapy in breast cancer patients.     

Identification of cancer genes using a statistical framework for multiexperiment analysis of nondiscretized array CGH data

Tumor formation is in part driven by DNA copy number alterations (CNAs), which can be measured using microarray-based Comparative Genomic Hybridization (aCGH). Multiexperiment analysis of aCGH data from tumors allows discovery of recurrent CNAs that are potentially causal to cancer development. Until now, multiexperiment aCGH data analysis has been dependent on discretization of measurement data to a gain, loss or no-change state. Valuable biological information is lost when a heterogeneous system such as a solid tumor is reduced to these states. We have developed a new approach which inputs nondiscretized aCGH data to identify regions that are significantly aberrant across an entire tumor set. Our method is based on kernel regression and accounts for the strength of a probe's signal, its local genomic environment and the signal distribution across multiple tumors. In an analysis of 89 human breast tumors, our method showed enrichment for known cancer genes in the detected regions and identified aberrations that are strongly associated with breast cancer subtypes and clinical parameters. Furthermore, we identified 18 recurrent aberrant regions in a new dataset of 19 p53-deficient mouse mammary tumors. These regions, combined with gene expression microarray data, point to known cancer genes and novel candidate cancer genes.     

Micro-Scale Genomic DNA Copy Number Aberrations as Another Means of Mutagenesis in Breast Cancer

Introduction

In breast cancer, the basal-like subtype has high levels of genomic instability relative to other breast cancer subtypes with many basal-like-specific regions of aberration. There is evidence that this genomic instability extends to smaller scale genomic aberrations, as shown by a previously described micro-deletion event in the PTEN gene in the Basal-like SUM149 breast cancer cell line.

Methods

We sought to identify if small regions of genomic DNA copy number changes exist by using a high density, gene-centric Comparative Genomic Hybridizations (CGH) array on cell lines and primary tumors. A custom tiling array for CGH (244,000 probes, 200 bp tiling resolution) was created to identify small regions of genomic change, which was focused on previously identified basal-like-specific, and general cancer genes. Tumor genomic DNA from 94 patients and 2 breast cancer cell lines was labeled and hybridized to these arrays. Aberrations were called using SWITCHdna and the smallest 25% of SWITCHdna-defined genomic segments were called micro-aberrations (<64 contiguous probes, ∼ 15 kb).

Results

Our data showed that primary tumor breast cancer genomes frequently contained many small-scale copy number gains and losses, termed micro-aberrations, most of which are undetectable using typical-density genome-wide aCGH arrays. The basal-like subtype exhibited the highest incidence of these events. These micro-aberrations sometimes altered expression of the involved gene. We confirmed the presence of the PTEN micro-amplification in SUM149 and by mRNA-seq showed that this resulted in loss of expression of all exons downstream of this event. Micro-aberrations disproportionately affected the 5′ regions of the affected genes, including the promoter region, and high frequency of micro-aberrations was associated with poor survival.

Conclusion

Using a high-probe-density, gene-centric aCGH microarray, we present evidence of small-scale genomic aberrations that can contribute to gene inactivation. These events may contribute to tumor formation through mechanisms not detected using conventional DNA copy number analyses.     

Irrelevance of CHEK2 variants to diagnosis of breast/ovarian cancer predisposition in Polish cohort

CHEK2 gen encodes cell cycle checkpoint kinase 2 that participates in the DNA repair pathway, cell cycle regulation and apoptosis. Mutations in CHEK2 gene may result in kinase inactivation or reduce both catalytic activity and capability of binding other proteins. Some studies indicate that alterations in CHEK2 gene confers increase the risk of breast cancer and some other malignancies, while the results of other studies are inconclusive. Thus the significance of CHEK2 mutations in aetiology of breast cancer is still debatable. The aim of our study was to evaluate the relationship between the breast/ovarian cancer and CHEK2 variants by: i) the analysis of the frequency of selected CHEK2 variants in breast and ovarian cancer patients compared to the controls; ii) evaluation of relationships between the certain CHEK2 variants and clinico-histopathological and pedigree data. The study was performed on 284 breast cancer patients, 113 ovarian cancer patients and 287 healthy women. We revealed the presence of 430T > C, del5395 and IVS2 + 1G > A variants but not 1100delC in individuals from both study and control groups. We did not observe significant differences between cancer patients and controls neither in regard to the frequency nor to the type of CHEK2 variants. We discussed the potential application of CHEK2 variants in the evaluation of breast and ovarian cancer predisposition.     

Comparative Oncogenomics Implicates the Neurofibromin 1 Gene (NF1) as a Breast Cancer Driver

Identifying genomic alterations driving breast cancer is complicated by tumor diversity and genetic heterogeneity. Relevant mouse models are powerful for untangling this problem because such heterogeneity can be controlled. Inbred Chaos3 mice exhibit high levels of genomic instability leading to mammary tumors that have tumor gene expression profiles closely resembling mature human mammary luminal cell signatures. We genomically characterized mammary adenocarcinomas from these mice to identify cancer-causing genomic events that overlap common alterations in human breast cancer. Chaos3 tumors underwent recurrent copy number alterations (CNAs), particularly deletion of the RAS inhibitor Neurofibromin 1 (Nf1) in nearly all cases. These overlap with human CNAs including NF1, which is deleted or mutated in 27.7% of all breast carcinomas. Chaos3 mammary tumor cells exhibit RAS hyperactivation and increased sensitivity to RAS pathway inhibitors. These results indicate that spontaneous NF1 loss can drive breast cancer. This should be informative for treatment of the significant fraction of patients whose tumors bear NF1 mutations.     

High frequency of common DNA copy number abnormalities detected by bacterial artificial chromosome array comparative genomic hybridization in 24 breast cancer cell lines

Breast cancer is a widespread disease in Japan and across the world. Breast cancer cells, as well as most other types of cancer cells, have diverse chromosomal aberrations. Clarifying the character of these chromosomal aberrations should contribute to the development of more suitable therapies, along with the predictions of metastasis and prognosis. Twenty-four breast cancer cell lines were analyzed by bacterial artificial chromosome (BAC) array comparative genomic hybridization (CGH). The array slide contained duplicate spots of 4030 BAC clone DNAs covering the entire human genome with 1 Mbp resolution. In all 24 breast cancer cell lines, frequent and significant amplifications as well as deletions were detected by BAC array CGH. Common DNA copy number gains, detected in 60% (above 15 cell lines) of the 24 breast cancer cell lines were found in 76 BAC clones, located at 1q, 5p, 8q, 9p, 16p, 17q, and 20q. Moreover, common DNA copy number loss was detected in 136 BAC clones, located at 1q, 2q, 3p, 4p, 6q, 8p, 9p, 11p, 13q, 17p, 18q, 19p, Xp, and Xq. The DNA copy number abnormalities found included abnormality of the well-known oncogene cMYC (8q24.21); however, most of them were not reported to relate to breast cancer. BAC array CGH has great potential to detect DNA copy number abnormalities, and has revealed that breast cancer cell lines have substantial heterogeneity.