Segmentation of genomic and transcriptomic microarrays data reveals major correlation between DNA copy number aberrations and gene–loci expression

High prevalence of APOA1/C3/A4/A5 alterations in luminal breast cancers among young women in East Asia

In East Asia, the breast cancer incidence rate among women aged <50 years has rapidly increased. Emerging tumors are distinctly characterized by a high prevalence of estrogen receptor (ER)-positive/human epidermal growth factor receptor (HER2)-negative cancer. In the present study, we identified unique genetic alterations in these emerging tumors. We analyzed gene copy number variations (CNVs) in breast tumors from 120 Taiwanese patients, and obtained public datasets of CNV and gene expression (GE). The data regarding CNV and GE were separately compared between East Asian and Western patients, and the overlapping genes identified in the comparisons were explored to identify the gene-gene interaction networks. In the age <50 years/ER + /HER2- subgroup, tumors of East Asian patients exhibited a higher frequency of copy number loss in APOA1/C3/A4/A5, a lipid-metabolizing gene cluster (33 vs. 10%, P < .001) and lower APOA1/C3/A4/A5 expressions than tumors of Western patients. These copy number loss related- and GE-related results were validated in another Taiwanese cohort and in two GE datasets, respectively. The copy number loss was significantly associated with poor survival among Western patients, but not among East Asian patients. Lower APOA1, APOC3, and APOA5 expressions were associated with higher ESTIMATE immune scores, indicating an abundance of tumor-infiltrating immune cells. In conclusion, APOA1/C3/A4/A5 copy number loss was more prevalent in luminal breast tumors among East Asian women aged <50 years, and its immunomodulatory effect on the tumor microenvironment possibly plays various roles in the tumor biology of East Asian patients.

Utility of gene expression studies in relation to radiation exposure and clinical outcomes: thyroid cancer in the Ukrainian-American cohort and late health effects in a MAYAK worker cohort

PURPOSE

We herein report on changes in gene expression after radiation exposure to iodine-131 from the Chernobyl accident in the Ukrainian-American thyroid cohort and to external gamma ray or internal plutonium exposure in the Mayak Production Association radiation workers.

MATERIALS AND METHODS

Taking advantage of access to tissue samples from the thyroid cancer cases in the Ukrainian-American cohort, our group tried to identify candidate genes to discriminate spontaneously occurring thyroid cancers from thyroid cancers caused by radiation exposure. We also examined gene expression changes in normal and cancerous thyroid tissue in relation to iodine-131 dose separately. Gene expression changes in the peripheral blood of radiation exposed Mayak workers were examined to elucidate the dose-to-gene and gene-to-health (e.g. cardiovascular disease) relationships.

CONCLUSIONS

Results of both projects are discussed under the aspect of dose-response relationships (dose-to-gene) and clinical outcome relationships (gene-to-effect) in light of how mechanistic data can be translated into actionable knowledge for radiation protection or clinical purposes.

The landscape of genomic copy number alterations in colorectal cancer and their consequences on gene expression levels and disease outcome

Aneuploidy, the unbalanced state of the chromosome content, represents a hallmark of most solid tumors, including colorectal cancer. Such aneuploidies result in tumor specific genomic imbalances, which emerge in premalignant precursor lesions. Moreover, increasing levels of chromosomal instability have been observed in adenocarcinomas and are maintained in distant metastases. A number of studies have systematically integrated copy number alterations with gene expression changes in primary carcinomas, cell lines, and experimental models of aneuploidy. In fact, chromosomal aneuploidies target a number of genes conferring a selective advantage for the metabolism of the cancer cell. Copy number alterations not only have a positive correlation with expression changes of the majority of genes on the altered genomic segment, but also have effects on the transcriptional levels of genes genome-wide. Finally, copy number alterations have been associated with disease outcome; nevertheless, the translational applicability in clinical practice requires further studies. Here, we (i) review the spectrum of genetic alterations that lead to colorectal cancer, (ii) describe the most frequent copy number alterations at different stages of colorectal carcinogenesis, (iii) exemplify their positive correlation with gene expression levels, and (iv) discuss copy number alterations that are potentially involved in disease outcome of individual patients.

Identification of cancer prognosis-associated lncRNAs based on the miRNA-TF co-regulatory motifs and dosage sensitivity

By integrating dosage sensitivity and motif regulation data, we established a framework and identified a total of 33 cancer prognosis-associated lncRNAs.

MVisAGe Identifies Concordant and Discordant Genomic Alterations of Driver Genes in Squamous Tumors

Integrated analyses of multiple genomic datatypes are now common in cancer profiling studies. Such data present opportunities for numerous computational experiments, yet analytic pipelines are limited. Tools such as the cBioPortal and Regulome Explorer, although useful, are not easy to access programmatically or to implement locally. Here, we introduce the MVisAGe R package, which allows users to quantify gene-level associations between two genomic datatypes to investigate the effect of genomic alterations (e.g., DNA copy number changes on gene expression). Visualizing Pearson/Spearman correlation coefficients according to the genomic positions of the underlying genes provides a powerful yet novel tool for conducting exploratory analyses. We demonstrate its utility by analyzing three publicly available cancer datasets. Our approach highlights canonical oncogenes in chr11q13 that displayed the strongest associations between expression and copy number, including CCND1 and CTTN, genes not identified by copy number analysis in the primary reports. We demonstrate highly concordant usage of shared oncogenes on chr3q, yet strikingly diverse oncogene usage on chr11q as a function of HPV infection status. Regions of chr19 that display remarkable associations between methylation and gene expression were identified, as were previously unreported miRNA-gene expression associations that may contribute to the epithelial-to-mesenchymal transition.Significance: This study presents an important bioinformatics tool that will enable integrated analyses of multiple genomic datatypes. Cancer Res; 78(12); 3375-85. ©2018 AACR.

Copy number variation and disease resistance in plants

Plant genome diversity varies from single nucleotide polymorphisms to large-scale deletions, insertions, duplications, or re-arrangements. These re-arrangements of sequences resulting from duplication, gains or losses of DNA segments are termed copy number variations (CNVs). During the last decade, numerous studies have emphasized the importance of CNVs as a factor affecting human phenotype; in particular, CNVs have been associated with risks for several severe diseases. In plants, the exploration of the extent and role of CNVs in resistance against pathogens and pests is just beginning. Since CNVs are likely to be associated with disease resistance in plants, an understanding of the distribution of CNVs could assist in the identification of novel plant disease-resistance genes. In this paper, we review existing information about CNVs; their importance, role and function, as well as their association with disease resistance in plants.

Integrating genetics and epigenetics in breast cancer: biological insights, experimental, computational methods and therapeutic potential

BACKGROUND

Development of human cancer can proceed through the accumulation of different genetic changes affecting the structure and function of the genome. Combined analyses of molecular data at multiple levels, such as DNA copy-number alteration, mRNA and miRNA expression, can clarify biological functions and pathways deregulated in cancer. The integrative methods that are used to investigate these data involve different fields, including biology, bioinformatics, and statistics.

RESULTS

These methodologies are presented in this review, and their implementation in breast cancer is discussed with a focus on integration strategies. We report current applications, recent studies and interesting results leading to the identification of candidate biomarkers for diagnosis, prognosis, and therapy in breast cancer by using both individual and combined analyses.

CONCLUSION

This review presents a state of art of the role of different technologies in breast cancer based on the integration of genetics and epigenetics, and shares some issues related to the new opportunities and challenges offered by the application of such integrative approaches.

An integrated approach to reveal miRNAs' impacts on the functional consequence of copy number alterations in cancer

Copy number alteration (CNA) is known to induce gene expression changes mainly through dosage effect, and therefore affect the initiation and progression of tumor. However, tumor samples exhibit heterogeneity in gene dosage sensitivity due to the complicated mechanisms of transcriptional regulation. Currently, no high-throughput method has been available for identifying the regulatory factors affecting the functional consequences of CNA, and determining their effects on cancer. In view of the important regulatory role of miRNA, we investigated the influence of miRNAs on the dosage sensitivities of genes within the CNA regions. By integrating copy number, mRNA expression, miRNA expression profiles of three kinds of cancer, we observed a tendency for high dosage-sensitivity genes to be more targeted by miRNAs in cancer, and identified the miRNAs regulating the dosage sensitivity of amplified/deleted target genes. The results show that miRNAs can modulate oncogenic biological functions by regulating the genes within the CNA regions, and thus play a role as a trigger or balancer in cancer, affecting cancer processes, even survival. This work provided a framework for analyzing the regulation of dosage effect, which will shed a light on understanding the oncogenic and tumor suppressive mechanisms of CNA. Besides, new cancer-related miRNAs were identified.

Consequences of Aneuploidy in Cancer: Transcriptome and Beyond

Cancer cells differ from normal healthy cells in multiple aspects ranging from altered cellular signaling through metabolic changes to aberrant chromosome content, so called aneuploidy. The large-scale changes in copy numbers of chromosomes or large chromosomal regions due to aneuploidy alter significantly the gene expression, as several hundreds of genes are gained or lost. Comparison of quantitative genome, transcriptome and proteome data enables dissection of the molecular causes that underlie the gene expression changes observed in cancer cells and provides a new perspective on the molecular consequences of aneuploidy. Here, we will map to what degree aneuploidy affects the expression of genes located on the affected chromosomes. We will also address the effects of aneuploidy on global gene expression in cancer cells as well as whether and how it may contribute to the physiology of cancer cells.

Integrated DNA Copy Number and Gene Expression Regulatory Network Analysis of Non-small Cell Lung Cancer Metastasis

Integrative analysis of multi-level molecular profiles can distinguish interactions that cannot be revealed based on one kind of data in the analysis of cancer susceptibility and metastasis. DNA copy number variations (CNVs) are common in cancer cells, and their role in cell behaviors and relationship to gene expression (GE) is poorly understood. An integrative analysis of CNV and genome-wide mRNA expression can discover copy number alterations and their possible regulatory effects on GE. This study presents a novel framework to identify important genes and construct potential regulatory networks based on these genes. Using this approach, DNA copy number aberrations and their effects on GE in lung cancer progression were revealed. Specifically, this approach contains the following steps: (1) select a pool of candidate driver genes, which have significant CNV in lung cancer patient tumors or have a significant association with the clinical outcome at the transcriptional level; (2) rank important driver genes in lung cancer patients with good prognosis and poor prognosis, respectively, and use top-ranked driver genes to construct regulatory networks with the COpy Number and EXpression In Cancer (CONEXIC) method; (3) identify experimentally confirmed molecular interactions in the constructed regulatory networks using Ingenuity Pathway Analysis (IPA); and (4) visualize the refined regulatory networks with the software package Genatomy. The constructed CNV/mRNA regulatory networks provide important insights into potential CNV-regulated transcriptional mechanisms in lung cancer metastasis.

A meta-analysis of multiple matched copy number and transcriptomics data sets for inferring gene regulatory relationships

Inferring gene regulatory relationships from observational data is challenging. Manipulation and intervention is often required to unravel causal relationships unambiguously. However, gene copy number changes, as they frequently occur in cancer cells, might be considered natural manipulation experiments on gene expression. An increasing number of data sets on matched array comparative genomic hybridisation and transcriptomics experiments from a variety of cancer pathologies are becoming publicly available. Here we explore the potential of a meta-analysis of thirty such data sets. The aim of our analysis was to assess the potential of in silico inference of trans-acting gene regulatory relationships from this type of data. We found sufficient correlation signal in the data to infer gene regulatory relationships, with interesting similarities between data sets. A number of genes had highly correlated copy number and expression changes in many of the data sets and we present predicted potential trans-acted regulatory relationships for each of these genes. The study also investigates to what extent heterogeneity between cell types and between pathologies determines the number of statistically significant predictions available from a meta-analysis of experiments.

Iodine-131 dose-dependent gene expression: alterations in both normal and tumour thyroid tissues of post-Chernobyl thyroid cancers

BACKGROUND

A strong, consistent association between childhood irradiation and subsequent thyroid cancer provides an excellent model for studying radiation carcinogenesis.

METHODS

We evaluated gene expression in 63 paired RNA specimens from frozen normal and tumour thyroid tissues with individual iodine-131 (I-131) doses (0.008-8.6 Gy, no unirradiated controls) received from Chernobyl fallout during childhood (Ukrainian-American cohort). Approximately half of these randomly selected samples (32 tumour/normal tissue RNA specimens) were hybridised on 64 whole-genome microarrays (Agilent, 4 × 44 K). Associations between I-131 dose and gene expression were assessed separately in normal and tumour tissues using Kruskal-Wallis and linear trend tests. Of 155 genes significantly associated with I-131 after Bonferroni correction and with ≥2-fold increase per dose category, we selected 95 genes. On the remaining 31 RNA samples these genes were used for validation purposes using qRT-PCR.

RESULTS

Expression of eight genes (ABCC3, C1orf9, C6orf62, FGFR1OP2, HEY2, NDOR1, STAT3, and UCP3) in normal tissue and six genes (ANKRD46, CD47, HNRNPH1, NDOR1, SCEL, and SERPINA1) in tumour tissue was significantly associated with I-131. PANTHER/DAVID pathway analyses demonstrated significant over-representation of genes coding for nucleic acid binding in normal and tumour tissues, and for p53, EGF, and FGF signalling pathways in tumour tissue.

CONCLUSION

The multistep process of radiation carcinogenesis begins in histologically normal thyroid tissue and may involve dose-dependent gene expression changes.

Combined analysis of genome-wide expression and copy number profiles to identify key altered genomic regions in cancer

BACKGROUND

Analysis of DNA copy number alterations and gene expression changes in human samples have been used to find potential target genes in complex diseases. Recent studies have combined these two types of data using different strategies, but focusing on finding gene-based relationships. However, it has been proposed that these data can be used to identify key genomic regions, which may enclose causal genes under the assumption that disease-associated gene expression changes are caused by genomic alterations.

Cancer vulnerabilities unveiled by genomic loss

Due to genome instability, most cancers exhibit loss of regions containing tumor suppressor genes and collateral loss of other genes. To identify cancer-specific vulnerabilities that are the result of copy number losses, we performed integrated analyses of genome-wide copy number and RNAi profiles and identified 56 genes for which gene suppression specifically inhibited the proliferation of cells harboring partial copy number loss of that gene. These CYCLOPS (copy number alterations yielding cancer liabilities owing to partial loss) genes are enriched for spliceosome, proteasome, and ribosome components. One CYCLOPS gene, PSMC2, encodes an essential member of the 19S proteasome. Normal cells express excess PSMC2, which resides in a complex with PSMC1, PSMD2, and PSMD5 and acts as a reservoir protecting cells from PSMC2 suppression. Cells harboring partial PSMC2 copy number loss lack this complex and die after PSMC2 suppression. These observations define a distinct class of cancer-specific liabilities resulting from genome instability.

Iodine-131 dose dependent gene expression in thyroid cancers and corresponding normal tissues following the Chernobyl accident

The strong and consistent relationship between irradiation at a young age and subsequent thyroid cancer provides an excellent model for studying radiation carcinogenesis in humans. We thus evaluated differential gene expression in thyroid tissue in relation to iodine-131 (I-131) doses received from the Chernobyl accident. Sixty three of 104 papillary thyroid cancers diagnosed between 1998 and 2008 in the Ukrainian-American cohort with individual I-131 thyroid dose estimates had paired RNA specimens from fresh frozen tumor (T) and normal (N) tissue provided by the Chernobyl Tissue Bank and satisfied quality control criteria. We first hybridized 32 randomly allocated RNA specimen pairs (T/N) on 64 whole genome microarrays (Agilent, 4×44 K). Associations of differential gene expression (log₂(T/N)) with dose were assessed using Kruskall-Wallis and trend tests in linear mixed regression models. While none of the genes withstood correction for the false discovery rate, we selected 75 genes with a priori evidence or P kruskall/P trend <0.0005 for validation by qRT-PCR on the remaining 31 RNA specimen pairs (T/N). The qRT-PCR data were analyzed using linear mixed regression models that included radiation dose as a categorical or ordinal variable. Eleven of 75 qRT-PCR assayed genes (ACVR2A, AJAP1, CA12, CDK12, FAM38A, GALNT7, LMO3, MTA1, SLC19A1, SLC43A3, ZNF493) were confirmed to have a statistically significant differential dose-expression relationship. Our study is among the first to provide direct human data on long term differential gene expression in relation to individual I-131 doses and to identify a set of genes potentially important in radiation carcinogenesis.

Cancer gene prioritization by integrative analysis of mRNA expression and DNA copy number data: a comparative review

A variety of genome-wide profiling techniques are available to investigate complementary aspects of genome structure and function. Integrative analysis of heterogeneous data sources can reveal higher level interactions that cannot be detected based on individual observations. A standard integration task in cancer studies is to identify altered genomic regions that induce changes in the expression of the associated genes based on joint analysis of genome-wide gene expression and copy number profiling measurements. In this review, we highlight common approaches to genomic data integration and provide a transparent benchmarking procedure to quantitatively compare method performances in cancer gene prioritization. Algorithms, data sets and benchmarking results are available at http://intcomp.r-forge.r-project.org.

The consequences of chromosomal aneuploidy on the transcriptome of cancer cells

Chromosomal aneuploidies are a defining feature of carcinomas, i.e., tumors of epithelial origin. Such aneuploidies result in tumor specific genomic copy number alterations. The patterns of genomic imbalances are tumor specific, and to a certain extent specific for defined stages of tumor development. Genomic imbalances occur already in premalignant precursor lesions, i.e., before the transition to invasive disease, and their distribution is maintained in metastases, and in cell lines derived from primary tumors. These observations are consistent with the interpretation that tumor specific genomic imbalances are drivers of malignant transformation. Naturally, this precipitates the question of how such imbalances influence the expression of resident genes. A number of laboratories have systematically integrated copy number alterations with gene expression changes in primary tumors and metastases, cell lines, and experimental models of aneuploidy to address the question as to whether genomic imbalances deregulate the expression of one or few key genes, or rather affect the cancer transcriptome more globally. The majority of these studies showed that gene expression levels follow genomic copy number. Therefore, gross genomic copy number changes, including aneuploidies of entire chromosome arms and chromosomes, result in a massive deregulation of the transcriptome of cancer cells. This article is part of a Special Issue entitled: Chromatin in time and space.

Integrative analyses for omics data: a Bayesian mixture model to assess the concordance of ChIP-chip and ChIP-seq measurements

The analysis of different variations in genomics, transcriptomics, epigenomics, and proteomics has increased considerably in recent years. This is especially due to the success of microarray and, more recently, sequencing technology. Apart from understanding mechanisms of disease pathogenesis on a molecular basis, for example in cancer research, the challenge of analyzing such different data types in an integrated way has become increasingly important also for the validation of new sequencing technologies with maximum resolution. For this purpose, a methodological framework for their comparison with microarray techniques in the context of smallest sample sizes, which result from the high costs of experiments, is proposed in this contribution. Based on an adaptation of the externally centered correlation coefficient ( Schäfer et al. 2009 ), it is demonstrated how a Bayesian mixture model can be applied to compare and classify measurements of histone acetylation that stem from chromatin immunoprecipitation combined with either microarray (ChIP-chip) or sequencing techniques (ChIP-seq) for the identification of DNA fragments. Here, the murine hematopoietic cell line 32D, which was transduced with the oncogene BCR-ABL, the hallmark of chronic myeloid leukemia, was characterized. Cells were compared to mock-transduced cells as control. Activation or inhibition of other genes by histone modifications induced by the oncogene is considered critical in such a context for the understanding of the disease.