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Computing Skin Cutaneous Melanoma Outcome From the HLA-Alleles and Clinical Characteristics
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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7113398/ https://www.ncbi.nlm.nih.gov/pubmed/32273881 http://dx.doi.org/10.3389/fgene.2020.00221 |
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author | Dhall, Anjali Patiyal, Sumeet Kaur, Harpreet Bhalla, Sherry Arora, Chakit Raghava, Gajendra P. S. |
author_facet | Dhall, Anjali Patiyal, Sumeet Kaur, Harpreet Bhalla, Sherry Arora, Chakit Raghava, Gajendra P. S. |
author_sort | Dhall, Anjali |
collection | PubMed |
description | 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-B(∗)55 (HR = 0.15, 95% CI 0.034–0.67), HLA-A(∗)01 (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-B(∗)50 (HR = 2.76, 95% CI 1.284–5.941), HLA-DRB1(∗)12 (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, p-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/). |
format | Online Article Text |
id | pubmed-7113398 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-71133982020-04-09 Computing Skin Cutaneous Melanoma Outcome From the HLA-Alleles and Clinical Characteristics Dhall, Anjali Patiyal, Sumeet Kaur, Harpreet Bhalla, Sherry Arora, Chakit Raghava, Gajendra P. S. Front Genet Genetics 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-B(∗)55 (HR = 0.15, 95% CI 0.034–0.67), HLA-A(∗)01 (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-B(∗)50 (HR = 2.76, 95% CI 1.284–5.941), HLA-DRB1(∗)12 (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, p-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/). Frontiers Media S.A. 2020-03-26 /pmc/articles/PMC7113398/ /pubmed/32273881 http://dx.doi.org/10.3389/fgene.2020.00221 Text en Copyright © 2020 Dhall, Patiyal, Kaur, Bhalla, Arora and Raghava. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Dhall, Anjali Patiyal, Sumeet Kaur, Harpreet Bhalla, Sherry Arora, Chakit Raghava, Gajendra P. S. Computing Skin Cutaneous Melanoma Outcome From the HLA-Alleles and Clinical Characteristics |
title | Computing Skin Cutaneous Melanoma Outcome From the HLA-Alleles and Clinical Characteristics |
title_full | Computing Skin Cutaneous Melanoma Outcome From the HLA-Alleles and Clinical Characteristics |
title_fullStr | Computing Skin Cutaneous Melanoma Outcome From the HLA-Alleles and Clinical Characteristics |
title_full_unstemmed | Computing Skin Cutaneous Melanoma Outcome From the HLA-Alleles and Clinical Characteristics |
title_short | Computing Skin Cutaneous Melanoma Outcome From the HLA-Alleles and Clinical Characteristics |
title_sort | computing skin cutaneous melanoma outcome from the hla-alleles and clinical characteristics |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7113398/ https://www.ncbi.nlm.nih.gov/pubmed/32273881 http://dx.doi.org/10.3389/fgene.2020.00221 |
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