Asia-Pacific Journal of Oncology Nursing

PERSPECTIVE
Year
: 2021  |  Volume : 8  |  Issue : 2  |  Page : 112--114

Topological Data Analysis: A New Method to Identify Genetic Alterations in Cancer


Jie Yu1, Xinzhong Chang2 
1 Foreign Languages College, Tianjin Normal University, Tianjin, China
2 Department of Breast Surgery, Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China

Correspondence Address:
MD Xinzhong Chang
Department of Breast Surgery, Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060
China

Cancer is the largest health problem worldwide. A number of targeted therapies are currently employed for the treatment of different cancers. Determining the molecular mechanisms that are necessary for cancer development and progression is the most critical step in targeted therapies. Currently, many studies have identified a large number of frequently mutated cancer-associated genes using recurrence-based methods. However, only the cancer-associated mutations with a mutation frequency >15% can be identified by these methods. In other words, they cannot be used to identify driver genes that have low mutation frequency but play a major role in tumorigenesis and development. Thus, there is an urgent need for a method for identifying cancer-associated genes that are not based on recurrence. In a study, recently published in Nature Communications, research team led by Prof. Raúl Rabadán from the Columbia University successfully devised a novel topological data analysis approach to identify low-prevalence cancer-associated gene mutations using expression data from multiple cancers.


How to cite this article:
Yu J, Chang X. Topological Data Analysis: A New Method to Identify Genetic Alterations in Cancer.Asia Pac J Oncol Nurs 2021;8:112-114


How to cite this URL:
Yu J, Chang X. Topological Data Analysis: A New Method to Identify Genetic Alterations in Cancer. Asia Pac J Oncol Nurs [serial online] 2021 [cited 2021 Mar 8 ];8:112-114
Available from: https://www.apjon.org/article.asp?issn=2347-5625;year=2021;volume=8;issue=2;spage=112;epage=114;aulast=Yu;type=0