Dhall, Anjali and Patiyal, Sumeet and Kaur, Harpreet and Bhalla, Sherry and Arora, Chakit and Raghava, G.P.S. (2020) Computing Skin Cutaneous Melanoma Outcome From the HLA-Alleles and Clinical Characteristics. Frontiers in genetics, 11. p. 221. ISSN 1664-8021
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Human leukocyte antigen (HLA) are essential components of the immune system that stimulate immune cells to provide protection and defense against cancer. Thousands of HLA alleles have been reported in the literature, but only a specific set of HLA alleles are present in an individual. The capability of the immune system to recognize cancer-associated mutations depends on the presence of a particular set of alleles, which elicit an immune response to fight against cancer. Therefore, the occurrence of specific HLA alleles affects the survival outcome of cancer patients. In the current study, prediction models were developed, using 401 cutaneous melanoma patients, to predict the overall survival (OS) of patients using their clinical data and HLA alleles. We observed that the presence of certain favorable superalleles like HLA-B55 (HR = 0.15, 95% CI 0.034-0.67), HLA-A01 (HR = 0.5, 95% CI 0.3-0.8), is responsible for the improved OS. In contrast, the presence of certain unfavorable superalleles such as HLA-B50 (HR = 2.76, 95% CI 1.284-5.941), HLA-DRB112 (HR = 3.44, 95% CI 1.64-7.2) is responsible for the poor survival. We developed prediction models using key 14 HLA superalleles, demographic, and clinical characteristics for predicting high-risk cutaneous melanoma patients and achieved HR = 4.52 (95% CI 3.088-6.609, -value = 8.01E-15). Eventually, we also provide a web-based service to the community for predicting the risk status in cutaneous melanoma patients (https://webs.iiitd.edu.in/raghava/skcmhrp/).
| Item Type: | Article |
|---|---|
| Additional Information: | Copyright of this article belongs to Frontiers Media. |
| Uncontrolled Keywords: | HLA; Hazard ratio; cutaneous melanoma; machine learning; prognosis; regression; superalleles; survival analysis |
| Subjects: | Q Science > QR Microbiology |
| Depositing User: | Dr. K.P.S.Sengar |
| Date Deposited: | 27 Apr 2020 11:46 |
| Last Modified: | 27 Apr 2020 11:46 |
| URI: | http://crdd.osdd.net/open/id/eprint/2563 |
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