Critical Analysis of Genome-Wide Association Studies: Triple Negative Breast Cancer Quae Exempli Causa

Abstract

Genome-wide association studies (GWAS) are useful in assessing and analyzing either differences or variations in DNA sequences across the human genome to detect genetic risk factors of diseases prevalent within a target population under study. The ultimate goal of GWAS is to predict either disease risk or disease progression by identifying genetic risk factors. These risk factors will define the biological basis of disease susceptibility for the purposes of developing innovative, preventative, and therapeutic strategies. As single nucleotide polymorphisms (SNPs) are often used in GWAS, their relevance for triple negative breast cancer (TNBC) will be assessed in this review. Furthermore, as there are different levels and patterns of linkage disequilibrium (LD) present within different human subpopulations, a plausible strategy to evaluate known SNPs associated with incidence of breast cancer in ethnically different patient cohorts will be presented and discussed. Additionally, a description of GWAS for TNBC will be presented, involving various identified SNPs correlated with miRNA sites to determine their efficacies on either prognosis or progression of TNBC in patients. Although GWAS have identified multiple common breast cancer susceptibility variants that individually would result in minor risks, it is their combined effects that would likely result in major risks. Thus, one approach to quantify synergistic effects of such common variants is to utilize polygenic risk scores. Therefore, studies utilizing predictive risk scores (PRSs) based on known breast cancer susceptibility SNPs will be evaluated. Such PRSs are potentially useful in improving stratification for screening, particularly when combining family history, other risk factors, and risk prediction models. In conclusion, although interpretation of the results from GWAS remains a challenge, the use of SNPs associated with TNBC may elucidate and better contextualize these studies.

Keywords: CNVs; GWAS; SNPs; TNBC; breast cancer; linkage disequilibrium; predictive risk scores; structural variants.

Figure 1

A technical flow chart for genome-wide association studies (GWAS). Abbreviation: QC, quality control.

Figure 2

Frequencies of each type of functional consequence caused by single nucleotide polymorphisms (SNPs) associated with TNBC. Abbreviations: SNPs, single nucleotide polymorphisms; TNBC, triple negative breast cancer; UTR, untranslated region.

Figure 3

Schematic representation of SNPs associated with triple negative breast cancer obtained from the EMBL-EBI GWAS catalogue. Abbreviation: SNPs- single nucleotide polymorphism, EMBL-EBI, The European Bioinformatics Institute.

Figure 4

Correlations of the two most studied SNPs associated with triple negative breast cancer and other nearby SNPs identified following analysis of the GWAS catalogue. Abbreviations: SNPs, single nucleotide polymorphisms; GWAS, Genome-wide association studies.

Figure 5

Locations of TNBC-related SNPs distributed across all somatic human chromosomes. In red color, SNPs related to TNBC risk, and in violet color, SNPs associated with different outcomes of TNBC (taken from Table S1). Abbreviations: A, adenine; C, cytosine; T, thymine; G, guanine.

Figure 6

Divergent bar graphs illustrating significant differences among subpopulation frequencies noted in TNBC-related SNPs. Abbreviations: A, adenine, C, cytosine; G, guanine; T, thymine.