Gene/Protein Disease Symptom Drug Enzyme Compound
Pivot Concepts:   Target Concepts:
Query: UMLS:C0023473 (chronic myeloid leukemia)
 18,916 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Little is known about inherited factors associated with the risk of developing chronic myelogenous leukemia (CML). We used a dedicated DNA chip containing 16 561 single nucleotide polymorphisms (SNPs) covering 1 916 candidate genes to analyze 437 CML patients and 1 144 healthy control individuals. Single SNP association analysis identified 139 SNPs that passed multiple comparisons (1% false discovery rate). The HDAC9, AVEN, SEMA3C, IKBKB, GSTA3, RIPK1 and FGF2 genes were each represented by three SNPs, the PSM family by four SNPs and the SLC15A1 gene by six. Haplotype analysis showed that certain combinations of rare alleles of these genes increased the risk of developing CML by more than two or three-fold. A classification tree model identified five SNPs belonging to the genes PSMB10, TNFRSF10D, PSMB2, PPARD and CYP26B1, which were associated with CML predisposition. A CML-risk-allele score was created using these five SNPs. This score was accurate for discriminating CML status (AUC: 0.61, 95%CI: 0.58-0.64). Interestingly, the score was associated with age at diagnosis and the average number of risk alleles was significantly higher in younger patients. The risk-allele score showed the same distribution in the general population (HapMap CEU samples) as in our control individuals and was associated with differential gene expression patterns of two genes (VAPA and TDRKH). In conclusion, we describe haplotypes and a genetic score that are significantly associated with a predisposition to develop CML. The SNPs identified will also serve to drive fundamental research on the putative role of these genes in CML development.
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PMID:Genetic polymorphisms associated with increased risk of developing chronic myelogenous leukemia. 2647 55

The aim of the present study was to evaluate the potential network of arsenic trioxide (ATO) target genes in pancreatic cancer. The DrugBank, STITCH, cBioPortal, Kaplan-Meier plotter and Oncomine websites were used to analyze the association of ATO and its target genes with pancreatic cancer. Initially, 19 ATO target genes were identified, along with their associated protein-protein interaction networks and Kyoto Encyclopedia of Genes and Genomes pathways. ATO was found to be associated with multiple types of cancer, and the most common solid cancer was pancreatic cancer. A total of 6 ATO target genes (namely AKT1, CCND1, CDKN2A, IKBKB, MAPK1 and MAPK3) were found to be associated with pancreatic cancer. Next, the mutation information of the 6 ATO target genes in pancreatic cancer was collected. A total of 20 ATO interacting genes were identified, which were mainly involved in hepatitis B, prostate cancer, pathways in cancer, glioma and chronic myeloid leukemia. Finally, the genes CCND1 and MAPK1 were detected to be prognostic factors in patients with pancreatic cancer. In conclusion, bioinformatics analysis may help elucidate the molecular mechanisms underlying the involvement of ATO in pancreatic cancer, enabling more effective treatment of this disease.
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PMID:Evaluation of the target genes of arsenic trioxide in pancreatic cancer by bioinformatics analysis. 3161 27