Genomics and Epidemiological Analysis of Melanoma Laterality

  • Fan W
Citations of this article
Mendeley users who have this article in their library.


Skin cancer is the most commonly diagnosed cancer in the United States and melanoma is considered the deadliest form of skin cancer. Although the environmental causes of melanomas are known, the molecular mechanisms involved are still being researched. Melanomas present more often on the left side of the body, but explanations for this laterality are conflicting and largely focused on epidemiological factors. In this thesis, both epidemiological and genetic factors affecting melanoma laterality are analyzed to explore how tumor laterality and patterning may arise in general. The Surveillance, Epidemiology, and End Results (SEER) and The Cancer Genome Atlas (TCGA) databases were used to analyze clinical cases of melanoma. Data analysis was conducted by calculating a laterality ratio of asymmetric melanomas and comparing how these ratios differ in epidemiological and genetic variables. A machine learning algorithm was also applied to predict which variables or groups of variables may determine laterality. Results showed that, as established, melanomas tend to exhibit left-sided laterality, but epidemiological factors alone are not good indicators of where tumors present. Genomics analysis revealed several genes and targets of interest. Genes involved in cell adhesion were consistently significant, but there was no conclusive evidence that a specific gene or set of genes causes left-sided patterning. Although results did not reveal specific genetic targets as determinants of melanoma laterality, they prove that the methods used can be tools for analyzing tumor laterality in general and can help in predicting what variables are important in molecular mechanisms indicating laterality.




Fan, W. Z. (2018). Genomics and Epidemiological Analysis of Melanoma Laterality. ProQuest Dissertations and Theses (p. 50). Retrieved from

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free