Abstract

Background: The cause of leukemia, the most common type of cancer, remains unknown. Genetic studies have reported more than a thousand of genes as being linked to the disease.Methods: A total of 1,093 leukemia candidate genes, identified from leukemia-gene relations data extracted from the ResNet 11 Mammalian database and supported by 6,524 references were evaluated. Four network metrics were used to evaluate individual gene potential relevance to leukemia. Gene-set enrichment, sub-network enrichment, and network-connectivity analyses were conducted on gene attributes. An expression dataset of 71 leukemia patients, and 76 healthy controls, was employed for validationResults: A total of 952 out of 1,093 genes were enriched in 100 pathways (p < 3.3e-20), demonstrating strong gene-gene interaction. A network metrics analysis revealed 5 genes (TP53, CTNNB1, AKT1, TNF, and RARA), as measured by both functional diversity and replication frequency, as the top leukemia candidates. Validation, using expression data, showed that the 1,093 genes, as a whole, and the top genes, as identified by the proposed metrics, were efficient in distinguishing leukemia patients from controls (maximum classification ratio = 95.3 % with permutation p-value = 0.0054).Conclusion: The genetic causes of leukemia are linked to a genetic network composed of a large number of genes. This network, together with the network metrics provided in this study, could provide a basis for further molecular studies in the field.

Highlights

  • Leukemia is a group of cancers, usually originating in bone marrow, which result in great numbers of abnormal white blood cells

  • More than a thousand genes related to leukemia, many of which suggested as potential biomarkers for the disease, such as FLT3, WT1, TET2, and KRAS, have been reported . [3,4,5] Several genes, such as IL2 and CSF3, have been studied in clinical trials . [6, 7] Many articles have reported genetic changes, and gene quantitative changes, in leukemia [8, 9]

  • The study workflow was as follows: 1) acquisition of a leukemia-gene relation dataset and identification of leukemia candidate genes; 2) enrichment analysis of the identified genes to study their pathogenic significance to leukemia; 3) network metrics analysis to identify genes having specific significance; 4) network connectivity analysis (NCA) to test functional associations between the reported genes; and, 5) validation using an independent gene expression data set

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Summary

Introduction

Leukemia is a group of cancers, usually originating in bone marrow, which result in great numbers of abnormal white blood cells. It is the most common type of childhood cancer, even though approximately 90 % of all leukemia cases are in adults [1]. [6, 7] Many articles have reported genetic changes, and gene quantitative changes, in leukemia [8, 9]. Both increased, and decreased, gene expression levels/activities have been observed [1012]. The cause of leukemia, the most common type of cancer, remains unknown. Genetic studies have reported more than a thousand of genes as being linked to the disease

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