Identification of Interconnected Markers for T-Cell Acute Lymphoblastic Leukemia

T-cell acute lymphoblastic leukemia (T-ALL) is a complex disease, resulting from proliferation of differentially arrested immature T cells. The molecular mechanisms and the genes involved in the generation of T-ALL remain largely undefined. In this study, we propose a set of genes to differentiate individuals with T-ALL from the nonleukemia/healthy ones and genes that are not differential themselves but interconnected with highly differentially expressed ones. We provide new suggestions for pathways involved in the cause of T-ALL and show that network-based classification techniques produce fewer genes with more meaningful and successful results than expression-based approaches. We have identified 19 significant subnetworks, containing 102 genes. The classification/prediction accuracies of subnetworks are considerably high, as high as 98%. Subnetworks contain 6 nondifferentially expressed genes, which could potentially participate in pathogenesis of T-ALL. Although these genes are not differential, they may serve as biomarkers if their loss/gain of function contributes to generation of T-ALL via SNPs. We conclude that transcription factors, zinc-ion-binding proteins, and tyrosine kinases are the important protein families to trigger T-ALL. These potential disease-causing genes in our subnetworks may serve as biomarkers, alternative to the traditional ones used for the diagnosis of T-ALL, and help understand the pathogenesis of the disease

Identification of Interconnected Markers for T-Cell Acute Lymphoblastic Leukemia

T-cell acute lymphoblastic leukemia (T-ALL) is a complex disease, resulting from proliferation of differentially arrested immature T cells. The molecular mechanisms and the genes involved in the generation of T-ALL remain largely undefined. In this study, we propose a set of genes to differentiate individuals with T-ALL from the nonleukemia/healthy ones and genes that are not differential themselves but interconnected with highly differentially expressed ones. We provide new suggestions for pathways involved in the cause of T-ALL and show that network-based classification techniques produce fewer genes with more meaningful and successful results than expression-based approaches. We have identified 19 significant subnetworks, containing 102 genes. The classification/prediction accuracies of subnetworks are considerably high, as high as 98%. Subnetworks contain 6 nondifferentially expressed genes, which could potentially participate in pathogenesis of T-ALL. Although these genes are not differential, they may serve as biomarkers if their loss/gain of function contributes to generation of T-ALL via SNPs. We conclude that transcription factors, zinc-ion-binding proteins, and tyrosine kinases are the important protein families to trigger T-ALL. These potential disease-causing genes in our subnetworks may serve as biomarkers, alternative to the traditional ones used for the diagnosis of T-ALL, and help understand the pathogenesis of the disease

A novel pathogenic frameshift variant of CD3E gene in two T-B+ NK+ SCID patients from Turkey.

Severe combined immunodeficiency (SCID) is the most severe form of primary immunodeficiency, which is characterized by the dysfunction and/or absence of T lymphocytes. Early diagnosis of SCID is crucial for overall survival, and if it remains untreated, SCID is often fatal. Next-generation sequencing (NGS) has become a rapid, high-throughput technology, and has already been proven to be beneficial in medical diagnostics. In this study, a targeted NGS panel was developed to identify the genetic variations of SCID by using SmartChip-TE technology, and a novel pathogenic frameshift variant was found in the CD3E gene. Sanger sequencing has confirmed the segregation of the variant among patients. We found a novel deletion in the CD3E gene (NM000733.3:p.L58Hfs*9) in two T-B+ NK+ patients. The variant was not found in the databases of dbSNP, ExAC, and 1000G. One sibling in family I was homozygous and the rest of the family members were heterozygous for this variant. T cell receptor excision circle (TREC) and kappa-deleting recombination excision circle (KREC) analyses were performed for T and B cell maturation. TRECs were not detected in both patients and the KREC copy numbers were similar to the other family members. In addition, heterozygous family members showed decreased TREC levels when compared with the wild-type sibling, indicating that carrying this variant in one allele does not cause immunodeficiency, but does effect T cell proliferation. Here, we report a novel pathogenic frameshift variant in CD3E gene by using targeted NGS panel

HighTUBB2Aexpression in childhood T-ALL is correlated with the clinical outcome

Introduction Microtubules are polymers that perform functions such as mitosis, intracellular transport, cell morphology, and ciliary and flagellar motility. Since microtubules are taking active part in cell division, they are among direct targets of several antimitotic drugs. Methods Expression levels of tubulin isotypes were analyzed in microarray data of childhood diagnostic T-ALL samples (n = 31) and healthy thymocytes (n = 7). Findings were validated with qPCR in separate T-ALL cohort (n = 48), and clinical correlation analyses were performed.TUBB2A's effects were tested with siRNA-mediated knockdown in MOLT4 cell line, and apoptosis assay was carried out at 24, 48, and 72 hours time points. Results In microarray data,TUBB2Awas found to be the only differentially expressed tubulin isotype (adj.Pvalue = .01), which was validated by qPCR (P = .02). Samples representing differentiation stages of T cell showed an increasing trend ofTUBB2Atoward mature T-cell stage.TUBB2Aexpression was significantly higher in high-risk group patients (P = .026) and in a group with WBC counts >100 (x10(9)cells/L) (P = .029). HighTUBB2Awas also found to be a predictor of shorter OS (P = .029) and RFS (P = .042). Conclusion Aberrant expression of TUBB isotypes can affect the balance of microtubules or microtubule-associated proteins, which might lead to drug resistance/relapse. Contribution of cytoskeleton proteins to drug resistance needs further investigation, and understanding aberrant expression and mode of action of microtubules will improve therapy strategies