Identification of candidate pathogenic synonymous variants in familial breast cancer
(2024) BINP52 20232Degree Projects in Bioinformatics
- Abstract
- Breast cancer is the most prevalent type of cancer and is the leading cause of cancer-related mortality among women. Although there have been significant advances in early screening and diagnostic strategies, the global incidence and mortality of breast cancer are expected to continue to increase. While there are many risk factors involved in the onset of the disease, family history is considered to be one of the most important, and estimates show that about 15-20% of all breast cancer cases are familial. Despite significant efforts to map the genetic landscape of familial breast cancer, over half of the estimated hereditary risk for the disease remains unexplained, highlighting the need for novel approaches. In recent years, synonymous... (More)
- Breast cancer is the most prevalent type of cancer and is the leading cause of cancer-related mortality among women. Although there have been significant advances in early screening and diagnostic strategies, the global incidence and mortality of breast cancer are expected to continue to increase. While there are many risk factors involved in the onset of the disease, family history is considered to be one of the most important, and estimates show that about 15-20% of all breast cancer cases are familial. Despite significant efforts to map the genetic landscape of familial breast cancer, over half of the estimated hereditary risk for the disease remains unexplained, highlighting the need for novel approaches. In recent years, synonymous variants, previously considered to be “silent”, have been implicated in many human diseases and their potential for functionality has been recognized. However, many genetic studies in familial breast cancer still disregard synonymous variants, focusing on variants with direct consequences on the amino acid sequences of the encoded proteins. In this study, we present an updated and optimized variant annotation pipeline capable of annotating variants with features relevant for the identification of potentially functional synonymous variants. We report our analysis of synonymous variants in several established and potential cancer susceptibility genes from two large cohorts of women with breast cancer and discuss candidate synonymous variants with potential for functionality. Our results provide an insight into the complex nature of predicting the functional impact of synonymous variants and highlight the need for further efforts in the development of strategies for synonymous variant effect prediction. (Less)
- Popular Abstract
- Understanding the role of not-so-silent variants in familial breast cancer
Breast cancer is the leading cause of cancer-related deaths for women globally. While the majority of breast cancer cases are from patients without any family history of the disease, approximately 1 in 5 cases are from patients with a history of breast cancer in first- or second-degree family members, also known as familial breast cancer. Despite significant effort in trying to understand the genetic background for familial breast cancer, estimates show that up to half of the hereditary risk in breast cancer remains unexplained. Identifying the mutations responsible for the increased risk of breast cancer is paramount in developing effective screening and... (More) - Understanding the role of not-so-silent variants in familial breast cancer
Breast cancer is the leading cause of cancer-related deaths for women globally. While the majority of breast cancer cases are from patients without any family history of the disease, approximately 1 in 5 cases are from patients with a history of breast cancer in first- or second-degree family members, also known as familial breast cancer. Despite significant effort in trying to understand the genetic background for familial breast cancer, estimates show that up to half of the hereditary risk in breast cancer remains unexplained. Identifying the mutations responsible for the increased risk of breast cancer is paramount in developing effective screening and diagnostic strategies against the disease. Our project focuses on the understanding of the largely unexplored role of synonymous, or “silent” mutations in familial breast cancer.
Synonymous variants are mutations in our DNA that do not actually change the amino acid sequences of the encoded proteins. As such, they are usually considered to be “silent” and without any deletarious effect. That is why they are often ignored in genetic research for many human diseases, including breast cancer. However, several studies have shown that synonymous variants may actually have a functional effect through various mechanisms that influence different aspects of gene expression – the process by which proteins are made using our DNA as templates.
The focus of this project was to update and optimize a bioinformatics tool developed by the group to annotate different features of synonymous variants and to identify potentially disease-causing synonymous variants that could be of interest for further experimental studies. We have optimized the tool to improve its performance and reduce the amount of time it takes to analyze large numbers of variants and created a ranking system based on the annotated features to prioritize synonymous variants with more interesting features. We have also performed analyses to determine whether specific variants are statistically associated with breast cancer, and combined our results to select candidate variants to study further in the lab.
Our results illustrate the complex nature of predicting the functionality of synonymous variants and highlight the need for many more studies to fully understand the unexplored role of synonymous variants in familial breast cancer and other human diseases.
Master’s Degree Project in Bioinformatics 60 credits 2024
Department of Biology, Lund University
Advisor: Helena Persson
Divison of Oncology, Department of Clinical Sciences, Lund, Faculty of Medicine, Lund University (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9155639
- author
- Han, Euisuk
- supervisor
- organization
- course
- BINP52 20232
- year
- 2024
- type
- H2 - Master's Degree (Two Years)
- subject
- language
- English
- id
- 9155639
- date added to LUP
- 2024-05-30 13:56:41
- date last changed
- 2024-05-30 13:56:41
@misc{9155639,
abstract = {{Breast cancer is the most prevalent type of cancer and is the leading cause of cancer-related mortality among women. Although there have been significant advances in early screening and diagnostic strategies, the global incidence and mortality of breast cancer are expected to continue to increase. While there are many risk factors involved in the onset of the disease, family history is considered to be one of the most important, and estimates show that about 15-20% of all breast cancer cases are familial. Despite significant efforts to map the genetic landscape of familial breast cancer, over half of the estimated hereditary risk for the disease remains unexplained, highlighting the need for novel approaches. In recent years, synonymous variants, previously considered to be “silent”, have been implicated in many human diseases and their potential for functionality has been recognized. However, many genetic studies in familial breast cancer still disregard synonymous variants, focusing on variants with direct consequences on the amino acid sequences of the encoded proteins. In this study, we present an updated and optimized variant annotation pipeline capable of annotating variants with features relevant for the identification of potentially functional synonymous variants. We report our analysis of synonymous variants in several established and potential cancer susceptibility genes from two large cohorts of women with breast cancer and discuss candidate synonymous variants with potential for functionality. Our results provide an insight into the complex nature of predicting the functional impact of synonymous variants and highlight the need for further efforts in the development of strategies for synonymous variant effect prediction.}},
author = {{Han, Euisuk}},
language = {{eng}},
note = {{Student Paper}},
title = {{Identification of candidate pathogenic synonymous variants in familial breast cancer}},
year = {{2024}},
}