HLA-G gene polymorphisms as predictors of survival in colorectal cancer: A unified machine learning approach for cancer detection

Outlet Title

Journal of King Saud University - Science

Authors

Youssef Harrath, Dakota State UniversityFollow
Marwa Hasni, LR-OASIS, National Engineering School of Tunis, University of Tunis El Manar, Tunis, Tunisia
Sabrine Dhouioui, Laboratory Microorganisms and Active Biomolecules, Sciences Faculty of Tunis, University of Tunis El Manar, Tunis, Tunisia
Nadia Boujelbene, Department of Pathology, Salah Azaiez Institute, Faculty of Medicine of Tunis, University of Tunis El Manar, Tunis, Tunisia
Abdel Halim Harrath, Department of Zoology, College of Science, King Saud University, Riyadh, Saudi ArabiaFollow
Mohamed Ayadi, Department of Surgical Oncology, Salah Azaiez Institute, Faculty of Medicine of Tunis, University of Tunis El Manar, Tunis, Tunisia
Ines Zemni, Department of Surgical Oncology, Salah Azaiez Institute, Faculty of Medicine of Tunis, University of Tunis El Manar, Tunis, Tunisia
Safa Bhar Layeb, LR-OASIS, National Engineering School of Tunis, University of Tunis El Manar, Tunis, TunisiaFollow
Ines Zidi, Laboratory Microorganisms and Active Biomolecules, Sciences Faculty of Tunis, University of Tunis El Manar, Tunis, TunisiaFollow

Document Type

Article

Publication Date

Fall 12-9-2024

Abstract

Objectives

Human Leukocyte Antigen (HLA-G) is a potent molecule involved in immune-tolerance. Here, we investigated the contribution of HLA-G gene polymorphisms (14 bp Ins/Del and +3142C/G) for accurate prediction of colorectal cancer (CRC) overall survival (OS) status. Our study presents a comprehensive investigation of the prognostic value of HLA-G genotypes and haplotypes in predicting OS status in 266 Tunisian patients with CRC.

Methods

We used a machine learning (ML)-based framework described below: (1) A dimensionality reduction approach was used to examine evidence of an association between HLA-G genotypes and OS status. (2) Decision-tree ML models were used to explore the performance of the HLA-G genotype as a relevant contributing feature to accurately predict OS status.

Results

HLA-G polymorphisms were highly predictive of OS status when a random forest classifier was used. The HLA-G 14 bp Ins/Del polymorphism outperformed the HLA-G + 3142C/G polymorphism as a predictor of OS. The Del/Del genotype was associated with worse OS and the G/G genotype was associated with favorable OS. The InsC haplotype predicted a favorable prognosis, and the DelG haplotype predicted a worse OS. The combined prediction demonstrated, with 100 % precision and high accuracy, that Del/Del genotype associated with key clinical features, can efficiently predict worse OS. The results were evaluated through an external validation process to ensure their reliability.

Recommended Citation

Marwa Hasni, Sabrine Dhouioui, Nadia Boujelbene, Youssef Harrath, Abdel Halim Harrath, Mohamed Ali Ayadi, Ines Zemni, Safa Bhar Layeb, and Ines Zidi. "HLA-G gene polymorphisms as predictors of survival in colorectal cancer: A unified machine learning approach." Journal of King Saud University-Science (2024): 103564.