Functional annotation of breast cancer risk loci: current progress and future directions

Abstract

Genome-wide association studies coupled with large-scale replication and fine-scale mapping studies have identified more than 150 genomic regions that are associated with breast cancer risk. Here, we review efforts to translate these findings into a greater understanding of disease mechanism. Our review comes in the context of a recently published fine-scale mapping analysis of these regions, which reported 352 independent signals and a total of 13,367 credible causal variants. The vast majority of credible causal variants map to noncoding DNA, implicating regulation of gene expression as the mechanism by which functional variants influence risk. Accordingly, we review methods for defining candidate-regulatory sequences, methods for identifying putative target genes and methods for linking candidate-regulatory sequences to putative target genes. We provide a summary of available data resources and identify gaps in these resources. We conclude that while much work has been done, there is still much to do. There are, however, grounds for optimism; combining statistical data from fine-scale mapping with functional data that are more representative of the normal “at risk” breast, generated using new technologies, should lead to a greater understanding of the mechanisms that influence an individual woman’s risk of breast cancer.

RETRACTED: Prediction of Breast cancer using integrated machine learning-fuzzy and dimension reduction techniques

“…It is crucial to understand that both women with and without a known genetic component to BC belong to the group of women who are at a high risk of getting the disease. Initial precaution is very much essential to avoid unwanted deaths due to this disease [25,26]. Several different and novel techniques, including the FIS, genetic neuro-fuzzy, and FDSS, were used after 2004, as shown in Fig.…”

Genetic Factors in the Screening and Imaging for Breast Cancer

“…Polymorphism is a variant that is common and thought to be a “normal” variation. Single nucleotide polymorphisms are substitutions in single bases in the DNA sequence, which are estimated to occur in 1/100–1/1000 base pairs [ 17 ]. These variations account for human genetic variation.…”

Coding roles of long non-coding RNAs in breast cancer: Emerging molecular diagnostic biomarkers and potential therapeutic targets with special reference to chemotherapy resistance

“…Among all epigenetic controls, emerging evidence suggests that lncRNAs can play a crucial role in all types of human cancers, including glioma , liver , lung (Chen et al, 2020c), pancreatic (Lv and Huang, 2019), ovarian (Oncul et al, 2020), pancreatic (Pandya et al, 2020), liver and breast cancer (Koboldt et al, 2012;Kagohara et al, 2018;Kansara et al, 2020;Ghafouri-Fard et al, 2021;Romualdo Cardoso et al, 2022) etc. LncRNAs are one class among different non-coding RNA species uncovered and accounted for ~80% of the total mammalian genome (Esteller, 2008;Kagohara et al, 2018) (Figure 1).…”