Sparse canonical correlation to identify breast cancer related genes regulated by copy number aberrations

Background: Copy number aberrations (CNA) have proved to be of clinical and therapeutic significance for many diseases including breast cancer, since they drive numerous key underlying biological processes, by regulating molecular phenotypes like gene expression and others. To comprehensively assess the effect of CNAs, it is not sufficient to only identify significant CNA-gene expression pairs, but also to identify the overall gene networks and regulatory structures that are influenced by CNAs, subsequently producing change in outcomes. Methods: In this article, we adopt a two-step analysis approach to identify CNA regulated genes whose expression levels affect breast cancer related outcomes: (1) we identify gene modules that are regulated by CNAs through sparse canonical correlation analysis (sCCA) which selects a set of closely located CNAs that regulates the expression levels of selected genes. (2) then, we use a using generalized linear model, to identify which genes within the gene modules are associated with breast cancer related outcomes. Results: Analyzing clinical and genomic data on 1904 breast cancer patients from the METABRIC study, we found 14 gene modules to be regulated by groups of proximally located CNA sites. The identification of gene modules was further validated using independent data on individuals in a study of breast invasive carcinoma from The Cancer Genome Atlas (TCGA). Association analysis on 7 different breast cancer related outcomes identified several novel and interpretable regulatory associations which highlights how CNA can impact key biological pathways and process in context of breast cancer. Through downstream analysis of two example outcomes: estrogen receptor status and overall survival, we show that the identified genes were enriched in relevant biological pathways and the key advantage of our method is that we additionally identify the CNA that regulate these genes. Due to the availability of multiple types of outcomes, we further meta-analyzed the results to identify genes that had potentially associations with multiple outcomes. Conclusions: Overall we present a generalizable analysis approach to identify genes associated to different outcomes that are regulated by sets of CNA and can further be used to combine results across various types of outcomes. The results show that our method can identify novel and interpretable associations, by providing mechanistic insights on how the effects of CNA are cascaded via gene expression to impact breast cancer and related outcomes.

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Claudin-low-like mouse mammary tumors show distinct transcriptomic patterns uncoupled from genomic drivers

10.1101/557298 ◽

2019 ◽

Author(s):

Christian Fougner ◽

Helga Bergholtz ◽

Raoul Kuiper ◽

Jens Henrik Norum ◽

Therese Sørlie

Keyword(s):

Breast Cancer ◽

Gene Expression ◽

Copy Number ◽

Breast Cancer Subtype ◽

Mammary Tumors ◽

Breast Cancers ◽

Copy Number Aberrations ◽

Induced Tumors ◽

Cancer Subtype ◽

Mouse Mammary Tumors

AbstractClaudin-low breast cancer is a molecular subtype associated with poor prognosis and without targeted treatment options. The claudin-low subtype is defined by certain biological characteristics, some of which may be clinically actionable, such as high immunogenicity. In mice, the medroxyprogesterone acetate (MPA) and 7,12-dimethylbenzanthracene (DMBA) induced mammary tumor model yields a heterogeneous set of tumors, a subset of which display claudin-low features. Neither the genomic characteristics of MPA/DMBA-induced claudin-low tumors, nor those of human claudin-low breast tumors, have been thoroughly explored.The transcriptomic characteristics and subtypes of MPA/DMBA-induced mouse mammary tumors were determined using gene expression microarrays. Somatic mutations and copy number aberrations in MPA/DMBA-induced tumors were identified from whole exome sequencing data. A publicly available dataset was queried to explore the genomic characteristics of human claudin-low breast cancer and to validate findings in the murine tumors.Half of MPA/DMBA-induced tumors showed a claudin-low-like subtype. All tumors carried mutations in known driver genes. While the specific genes carrying mutations varied between tumors, there was a consistent mutational signature with an overweight of T>A transversions in TG dinucleotides. Most tumors carried copy number aberrations with a potential oncogenic driver effect. Overall, several genomic events were observed recurrently, however none accurately delineated claudin-low-like tumors. Human claudin-low breast cancers carried a distinct set of genomic characteristics, in particular a relatively low burden of mutations and copy number aberrations. The gene expression characteristics of claudin-low-like MPA/DMBA-induced tumors accurately reflected those of human claudin-low tumors, including epithelial-mesenchymal transition phenotype, high level of immune activation and low degree of differentiation. There was an elevated expression of the immunosuppressive genes PTGS2 (encoding COX-2) and CD274 (encoding PD-L1) in human and murine claudin-low tumors. Our findings show that the claudin-low breast cancer subtype is not demarcated by specific genomic aberrations, but carries potentially targetable characteristics warranting further research.Author SummaryBreast cancer is comprised of several distinct disease subtypes with different etiologies, prognoses and therapeutic targets. The claudin-low breast cancer subtype is relatively poorly understood, and no specific treatment exists targeting its unique characteristics. Animal models accurately representing human disease counterparts are vital for developing novel therapeutics, but for the claudin-low breast cancer subtype, no such uniform model exists. Here, we show that exposing mice to the carcinogen DMBA and the hormone MPA causes a diverse range of mammary tumors to grow, and half of these have a gene expression pattern similar to that seen in human claudin-low breast cancer. These tumors have numerous changes in their DNA, with clear differences between each tumor, however no specific DNA aberrations clearly demarcate the claudin-low subtype. We also analyzed human breast cancers and show that human claudin-low tumors have several clear patterns in their DNA aberrations, but no specific features accurately distinguish claudin-low from non-claudin-low breast cancer. Finally, we show that both human and murine claudin-low tumors express high levels of genes associated with suppression of immune response. In sum, we highlight claudin-low breast cancer as a clinically relevant subtype with a complex etiology, and with potential unexploited therapeutic targets.

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Penalized differential pathway analysis of integrative oncogenomics studies

Statistical Applications in Genetics and Molecular Biology ◽

10.1515/sagmb-2013-0020 ◽

2014 ◽

Vol 13 (2) ◽

Cited By ~ 1

Author(s):

Wessel N. van Wieringen ◽

Mark A. van de Wiel

Keyword(s):

Gene Expression ◽

Cancer Patients ◽

Copy Number ◽

Model Parameters ◽

Integrative Genomics ◽

Dna Copy Number ◽

Expression Levels ◽

Copy Number Aberrations ◽

Dna Copy Number Aberrations ◽

Gene Expression Levels

AbstractThrough integration of genomic data from multiple sources, we may obtain a more accurate and complete picture of the molecular mechanisms underlying tumorigenesis. We discuss the integration of DNA copy number and mRNA gene expression data from an observational integrative genomics study involving cancer patients. The two molecular levels involved are linked through the central dogma of molecular biology. DNA copy number aberrations abound in the cancer cell. Here we investigate how these aberrations affect gene expression levels within a pathway using observational integrative genomics data of cancer patients. In particular, we aim to identify differential edges between regulatory networks of two groups involving these molecular levels. Motivated by the rate equations, the regulatory mechanism between DNA copy number aberrations and gene expression levels within a pathway is modeled by a simultaneous-equations model, for the one- and two-group case. The latter facilitates the identification of differential interactions between the two groups. Model parameters are estimated by penalized least squares using the lasso (

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The BIRC Family Genes Expression in Patients with Triple Negative Breast Cancer

International Journal of Molecular Sciences ◽

10.3390/ijms22041820 ◽

2021 ◽

Vol 22 (4) ◽

pp. 1820

Author(s):

Anna Makuch-Kocka ◽

Janusz Kocki ◽

Anna Brzozowska ◽

Jacek Bogucki ◽

Przemysław Kołodziej ◽

...

Keyword(s):

Breast Cancer ◽

Gene Expression ◽

Clinical Data ◽

Triple Negative Breast Cancer ◽

Triple Negative ◽

Lymphatic Vessels ◽

The Cancer Genome Atlas ◽

Expression Level ◽

Cancer Tissue ◽

Expression Levels

The BIRC (baculoviral IAP repeat-containing; BIRC) family genes encode for Inhibitor of Apoptosis (IAP) proteins. The dysregulation of the expression levels of the genes in question in cancer tissue as compared to normal tissue suggests that the apoptosis process in cancer cells was disturbed, which may be associated with the development and chemoresistance of triple negative breast cancer (TNBC). In our study, we determined the expression level of eight genes from the BIRC family using the Real-Time PCR method in patients with TNBC and compared the obtained results with clinical data. Additionally, using bioinformatics tools (Ualcan and The Breast Cancer Gene-Expression Miner v4.5 (bc-GenExMiner v4.5)), we compared our data with the data in the Cancer Genome Atlas (TCGA) database. We observed diverse expression pattern among the studied genes in breast cancer tissue. Comparing the expression level of the studied genes with the clinical data, we found that in patients diagnosed with breast cancer under the age of 50, the expression levels of all studied genes were higher compared to patients diagnosed after the age of 50. We observed that in patients with invasion of neoplastic cells into lymphatic vessels and fat tissue, the expression levels of BIRC family genes were lower compared to patients in whom these features were not noted. Statistically significant differences in gene expression were also noted in patients classified into three groups depending on the basis of the Scarff-Bloom and Richardson (SBR) Grading System.

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