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.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7461549PMC
http://dx.doi.org/10.3390/ijms21165835DOI Listing

Publication Analysis

Top Keywords

breast cancer
20
risk factors
16
genome-wide association
8
association studies
8
triple negative
8
negative breast
8
risk
8
genetic risk
8
factors risk
8
tnbc will
8

Similar Publications

GradeDiff-IM: An Ensembles Model-based Grade Classification of Breast Cancer.

Biomed Phys Eng Express

January 2025

School of Engineering and Computing, University of the West of Scotland, University of the West of Scotland - Paisley Campus, Paisley PA1 2BE, UK, City, Paisley, PA1 2BE, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND.

Cancer grade classification is a challenging task identified from the cell structure of healthy and abnormal tissues. The partitioner learns about the malignant cell through the grading and plans the treatment strategy accordingly. A major portion of researchers used DL models for grade classification.

View Article and Find Full Text PDF

Background: Bangladesh and West Bengal, India, are 2 densely populated South Asian neighboring regions with many socioeconomic and cultural similarities. In dealing with breast cancer (BC)-related issues, statistics show that people from these regions are having similar problems and fates. According to the Global Cancer Statistics 2020 and 2012 reports, for BC (particularly female BC), the age-standardized incidence rate is approximately 22 to 25 per 100,000 people, and the age-standardized mortality rate is approximately 11 to 13 per 100,000 for these areas.

View Article and Find Full Text PDF

Purpose: Breast cancer ranks as the most prevalent cancer in women, characterized by heightened fatty acid synthesis and glycolytic activity. Fatty acid synthase (FASN) is prominently expressed in breast cancer cells, regulating fatty acid synthesis, thereby enhancing tumor growth and migration, and leading to radioresistance. This study aims to investigate how FASN inhibition affects cell proliferation, migration, and radioresistance in breast cancer, as well as the mechanisms involved.

View Article and Find Full Text PDF

Triple negative breast cancers often contain higher numbers of tumour-infiltrating lymphocytes compared with other breast cancer subtypes, with their number correlating with prolonged survival. Since little is known about tumour-infiltrating lymphocyte trafficking in triple negative breast cancers, we investigated the relationship between tumour-infiltrating lymphocytes and the vascular compartment to better understand the immune tumour microenvironment in this aggressive cancer type. We aimed to identify mechanisms and signaling pathways responsible for immune cell trafficking in triple negative breast cancers, specifically of basal type, that could potentially be manipulated to change such tumours from immune "cold" to "hot" thereby increasing the likelihood of successful immunotherapy in this challenging patient population.

View Article and Find Full Text PDF

This study presents a novel approach to modeling breast cancer dynamics, one of the most significant health threats to women worldwide. Utilizing a piecewise mathematical framework, we incorporate both deterministic and stochastic elements of cancer progression. The model is divided into three distinct phases: (1) initial growth, characterized by a constant-order Caputo proportional operator (CPC), (2) intermediate growth, modeled by a variable-order CPC, and (3) advanced stages, capturing stochastic fluctuations in cancer cell populations using a stochastic operator.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!