scholarly journals An Integrative Genomics Approach for Associating GWAS Information with Triple-Negative Breast Cancer

2013 ◽  
Vol 12 ◽  
pp. CIN.S10413 ◽  
Author(s):  
Chindo Hicks ◽  
Ranjit Kumar ◽  
Antonio Pannuti ◽  
Kandis Backus ◽  
Alexandra Brown ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Gene Expression Data ◽  
Triple Negative Breast Cancer ◽  
Genetic Variants ◽  
Triple Negative ◽  
Genome Wide Association Studies ◽  
Expression Data ◽  
Integrative Genomics ◽  
Increased Risk

Genome-wide association studies (GWAS) have identified genetic variants associated with an increased risk of developing breast cancer. However, the association of genetic variants and their associated genes with the most aggressive subset of breast cancer, the triple-negative breast cancer (TNBC), remains a central puzzle in molecular epidemiology. The objective of this study was to determine whether genes containing single nucleotide polymorphisms (SNPs) associated with an increased risk of developing breast cancer are connected to and could stratify different subtypes of TNBC. Additionally, we sought to identify molecular pathways and networks involved in TNBC. We performed integrative genomics analysis, combining information from GWAS studies involving over 400,000 cases and over 400,000 controls, with gene expression data derived from 124 breast cancer patients classified as TNBC (at the time of diagnosis) and 142 cancer-free controls. Analysis of GWAS reports produced 500 SNPs mapped to 188 genes. We identified a signature of 159 functionally related SNP-containing genes which were significantly ( P < 10−5) associated with and stratified TNBC. Additionally, we identified 97 genes which were functionally related to, and had similar patterns of expression profiles, SNP-containing genes. Network modeling and pathway prediction revealed multi-gene pathways including p53, NFkB, BRCA, apoptosis, DNA repair, DNA mismatch, and excision repair pathways enriched for SNPs mapped to genes significantly associated with TNBC. The results provide convincing evidence that integrating GWAS information with gene expression data provides a unified and powerful approach for biomarker discovery in TNBC.

scholarly journals An Integrative Genomics Approach to Biomarker Discovery in Breast Cancer

2011 ◽  
Vol 10 ◽  
pp. CIN.S6837 ◽  
Author(s):  
Chindo Hicks ◽  
Rozana Asfour ◽  
Antonio Pannuti ◽  
Lucio Miele
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Gene Expression Data ◽  
Genetic Variants ◽  
Association Studies ◽  
Biological Pathways ◽  
Genome Wide Association Studies ◽  
Expression Data ◽  
Integrative Genomics ◽  
Novel Genes

Genome-wide association studies (GWAS) have successfully identified genetic variants associated with risk for breast cancer. However, the molecular mechanisms through which the identified variants confer risk or influence phenotypic expression remains poorly understood. Here, we present a novel integrative genomics approach that combines GWAS information with gene expression data to assess the combined contribution of multiple genetic variants acting within genes and putative biological pathways, and to identify novel genes and biological pathways that could not be identified using traditional GWAS. The results show that genes containing SNPs associated with risk for breast cancer are functionally related and interact with each other in biological pathways relevant to breast cancer. Additionally, we identified novel genes that are co-expressed and interact with genes containing SNPs associated with breast cancer. Integrative analysis combining GWAS information with gene expression data provides functional bridges between GWAS findings and biological pathways involved in breast cancer.

scholarly journals Integrative Genomic Analysis for the Discovery of Biomarkers in Prostate Cancer

2014 ◽  
Vol 9 ◽  
pp. BMI.S13729 ◽  
Author(s):  
Chindo Hicks ◽  
Tejaswi Koganti ◽  
Shankar Giri ◽  
Memory Tekere ◽  
Ritika Ramani ◽  
...  
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Gene Expression Data ◽  
Genetic Variants ◽  
Association Studies ◽  
Biological Pathways ◽  
Great Success ◽  
Genome Wide Association Studies ◽  
Expression Data ◽  
Increased Risk

Genome-wide association studies (GWAS) have achieved great success in identifying single nucleotide polymorphisms (SNPs, herein called genetic variants) and genes associated with risk of developing prostate cancer. However, GWAS do not typically link the genetic variants to the disease state or inform the broader context in which the genetic variants operate. Here, we present a novel integrative genomics approach that combines GWAS information with gene expression data to infer the causal association between gene expression and the disease and to identify the network states and biological pathways enriched for genetic variants. We identified gene regulatory networks and biological pathways enriched for genetic variants, including the prostate cancer, IGF-1, JAK2, androgen, and prolactin signaling pathways. The integration of GWAS information with gene expression data provides insights about the broader context in which genetic variants associated with an increased risk of developing prostate cancer operate.

scholarly journals Unraveling the Genomic-Epigenomic Interaction Landscape in Triple Negative and Non-Triple Negative Breast Cancer

Cancers ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1559
Author(s):  
Jiande Wu ◽  
Tarun Karthik Kumar Mamidi ◽  
Lu Zhang ◽  
Chindo Hicks
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Signaling Pathways ◽  
Somatic Mutation ◽  
Gene Expression Data ◽  
Triple Negative Breast Cancer ◽  
Somatic Mutations ◽  
Triple Negative ◽  
Expression Data ◽  
Gene Expression Signatures

Background: The recent surge of next generation sequencing of breast cancer genomes has enabled development of comprehensive catalogues of somatic mutations and expanded the molecular classification of subtypes of breast cancer. However, somatic mutations and gene expression data have not been leveraged and integrated with epigenomic data to unravel the genomic-epigenomic interaction landscape of triple negative breast cancer (TNBC) and non-triple negative breast cancer (non-TNBC). Methods: We performed integrative data analysis combining somatic mutation, epigenomic and gene expression data from The Cancer Genome Atlas (TCGA) to unravel the possible oncogenic interactions between genomic and epigenomic variation in TNBC and non-TNBC. We hypothesized that within breast cancers, there are differences in somatic mutation, DNA methylation and gene expression signatures between TNBC and non-TNBC. We further hypothesized that genomic and epigenomic alterations affect gene regulatory networks and signaling pathways driving the two types of breast cancer. Results: The investigation revealed somatic mutated, epigenomic and gene expression signatures unique to TNBC and non-TNBC and signatures distinguishing the two types of breast cancer. In addition, the investigation revealed molecular networks and signaling pathways enriched for somatic mutations and epigenomic changes unique to each type of breast cancer. The most significant pathways for TNBC were: retinal biosynthesis, BAG2, LXR/RXR, EIF2 and P2Y purigenic receptor signaling pathways. The most significant pathways for non-TNBC were: UVB-induced MAPK, PCP, Apelin endothelial, Endoplasmatic reticulum stress and mechanisms of viral exit from host signaling Pathways. Conclusion: The investigation revealed integrated genomic, epigenomic and gene expression signatures and signing pathways unique to TNBC and non-TNBC, and a gene signature distinguishing the two types of breast cancer. The study demonstrates that integrative analysis of multi-omics data is a powerful approach for unravelling the genomic-epigenomic interaction landscape in TNBC and non-TNBC.

scholarly journals Evaluation of Gene Expression Data From Cybrids and Tumours Highlights Elevated NDRG1-Driven Proliferation in Triple-Negative Breast Cancer

2020 ◽  
Vol 14 ◽  
pp. 117822342093444
Author(s):  
Akanksha Mishra ◽  
Maria Bonello ◽  
Adam Byron ◽  
Simon P Langdon ◽  
Andrew H Sims
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Gene Expression Data ◽  
Triple Negative Breast Cancer ◽  
Breast Cancer Cells ◽  
Triple Negative ◽  
Donor Cell ◽  
Expression Data ◽  
Donor Cells

Background: Triple-negative breast cancer is an aggressive type of breast cancer with high risk of recurrence. It is still poorly understood and lacks any targeted therapy, which makes it difficult to treat. Thus, it is important to understand the underlying mechanisms and pathways that are dysregulated in triple-negative breast cancer. Methods: To investigate the role of mitochondria in triple-negative breast cancer progression, we analysed previously reported gene expression data from triple-negative breast cancer cybrids with SUM-159 as the nuclear donor cell and SUM-159 or A1N4 (c-SUM-159, c-A1N4) as the mitochondrial donor cells and with 143B as the nuclear donor cell and MCF-10A or MDA-MB-231 (c-MCF-10A, c-MDA-MB-231) as the mitochondrial donor cells. The role of potential biomarkers in cell proliferation and migration was examined in SUM-159 and MDA-MB-231 cells using sulforhodamine B and wound healing assays. Results: Rank product analysis of cybrid gene expression data identified 149 genes which were significantly up-regulated in the cybrids with mitochondria from the cancer cell line. Analysis of previously reported breast tumour gene expression datasets confirmed 9 of the 149 genes were amplified, up-regulated, or down-regulated in more than 10% of the patients. The genes included NDRG1, PVT1, and EXT1, which are co-located in cytoband 8q24, which is frequently amplified in breast cancer. NDRG1 showed the largest down-regulation in the cybrids with benign mitochondria and was associated with poor prognosis in a breast cancer clinical dataset. Knockdown of NDRG1 expression significantly decreased proliferation of SUM-159 triple-negative breast cancer cells. Conclusions: These results indicate that mitochondria-regulated nuclear gene expression helps breast cancer cells survive and proliferate, consistent with previous work focusing on an Src gene signature which is mitochondria regulated and drives malignancy in breast cancer cybrids. This is the first study to show that mitochondria in triple-negative breast cancer mediate significant up-regulation of a number of genes, and silencing of NDRG1 leads to significant reduction in proliferation.

scholarly journals Deconvolution of the Genomic and Epigenomic Interaction Landscape of Triple-Negative Breast Cancer

Cancers ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 1692 ◽  
Author(s):  
Jiande Wu ◽  
Tarun Karthik Kumar Mamidi ◽  
Lu Zhang ◽  
Chindo Hicks
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Signaling Pathways ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Molecular Networks ◽  
Genome Wide Association Studies ◽  
Integrative Genomics ◽  
Gene Expression Variation ◽  
Expression Variation

Triple-negative breast cancer (TNBC) is the most aggressive form of breast cancer. Emerging evidenced suggests that both genetics and epigenetic factors play a role in the pathogenesis of TNBC. However, oncogenic interactions and cooperation between genomic and epigenomic variation have not been characterized. The objective of this study was to deconvolute the genomic and epigenomic interaction landscape in TNBC using an integrative genomics approach, which integrates information on germline, somatic, epigenomic and gene expression variation. We hypothesized that TNBC originates from a complex interplay between genomic (both germline and somatic variation) and epigenomic variation. We further hypothesized that these complex arrays of interacting genomic and epigenomic factors affect entire molecular networks and signaling pathways which, in turn, drive TNBC. We addressed these hypotheses using germline variation from genome-wide association studies and somatic, epigenomic and gene expression variation from The Cancer Genome Atlas (TCGA). The investigation revealed signatures of functionally related genes containing germline, somatic and epigenetic variations. DNA methylation had an effect on gene expression. Network and pathway analysis revealed molecule networks and signaling pathways enriched for germline, somatic and epigenomic variation, among them: Role of BRCA1 in DNA Damage Response, Hereditary Breast Cancer Signaling, Molecular Mechanisms of Cancer, Estrogen-Dependent Breast Cancer, p53, MYC Mediated Apoptosis, and PTEN Signaling pathways. The investigation revealed that integrative genomics is a powerful approach for deconvoluting the genomic-epigenomic interaction landscape in TNBC. Further studies are needed to understand the biological mechanisms underlying oncogenic interactions between genomic and epigenomic factors in TNBC.

scholarly journals A Review of the Hereditary Component of Triple Negative Breast Cancer: High- and Moderate-Penetrance Breast Cancer Genes, Low-Penetrance Loci, and the Role of Nontraditional Genetic Elements

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Darrell L. Ellsworth ◽  
Clesson E. Turner ◽  
Rachel E. Ellsworth
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Large Scale ◽  
Triple Negative ◽  
Association Studies ◽  
African Ancestry ◽  
Genome Wide Association Studies ◽  
Genetic Elements ◽  
Genome Wide ◽  
Increased Risk

Triple negative breast cancer (TNBC), representing 10-15% of breast tumors diagnosed each year, is a clinically defined subtype of breast cancer associated with poor prognosis. The higher incidence of TNBC in certain populations such as young women and/or women of African ancestry and a unique pathological phenotype shared between TNBC and BRCA1-deficient tumors suggest that TNBC may be inherited through germline mutations. In this article, we describe genes and genetic elements, beyond BRCA1 and BRCA2, which have been associated with increased risk of TNBC. Multigene panel testing has identified high- and moderate-penetrance cancer predisposition genes associated with increased risk for TNBC. Development of large-scale genome-wide SNP assays coupled with genome-wide association studies (GWAS) has led to the discovery of low-penetrance TNBC-associated loci. Next-generation sequencing has identified variants in noncoding RNAs, viral integration sites, and genes in underexplored regions of the human genome that may contribute to the genetic underpinnings of TNBC. Advances in our understanding of the genetics of TNBC are driving improvements in risk assessment and patient management.

scholarly journals Novel Integrative Genomics Approach for Associating GWAS Information with Intrinsic Subtypes of Breast Cancer

2013 ◽  
Vol 12 ◽  
pp. CIN.S11452 ◽  
Author(s):  
Chindo Hicks ◽  
Tejaswi Koganti ◽  
Alexandra S. Brown ◽  
Jesus Monico ◽  
Kandis Backus ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Genetic Variants ◽  
Association Studies ◽  
Great Success ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Integrative Genomics ◽  
Intrinsic Subtypes ◽  
Increased Risk ◽  
Distinct Disease

Genome-wide association studies (GWAS) have achieved great success in identifying common variants associated with increased risk of developing breast cancer. However, GWAS do not typically provide information about the broader context in which genetic variants operate in different subtypes of breast cancer. The objective of this study was to determine whether genes containing single nucleotide polymorphisms (SNPs, herein called genetic variants) are associated with different subtypes of breast cancer. Additionally, we sought to identify gene regulator networks and biological pathways enriched for these genetic variants. Using supervised analysis, we identified 201 genes that were significantly associated with the six intrinsic subtypes of breast cancer. The results demonstrate that integrative genomics analysis is a powerful approach for linking GWAS information to distinct disease states and provide insights about the broader context in which genetic variants operate in different subtypes of breast cancer.

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