Citations

Abstract High BAALC expression levels are associated with poor outcome in cytogenetically normal acute myeloid leukemia (CN-AML) patients. Recently, miR-3151 was discovered in intron 1 of BAALC. To evaluate the prognostic significance of miR-3151 expression levels and to gain insight into the biologic and prognostic interplay between miR-3151 and its host, miR-3151 and BAALC expression were measured in pretreatment blood of 179 CN-AML patients. Gene-expression profiling and miRNA-expression profiling were performed using microarrays. High miR-3151 expression was associated with shorter disease-free and overall survival, whereas high BAALC expression predicted failure of complete remission and shorter overall survival. Patients exhibiting high expression of both miR-3151 and BAALC had worse outcome than patients expressing low levels of either gene or both genes. In gene-expression profiling, high miR-3151 expressers showed down-regulation of genes involved in transcriptional regulation, posttranslational modification, and cancer pathways. Two genes, FBXL20 and USP40, were validated as direct miR-3151 targets. The results of the present study show that high expression of miR-3151 is an independent prognosticator for poor outcome in CN-AML and affects different outcome end points than its host gene, BAALC. The combination of both markers identified a patient subset with the poorest outcome. This interplay between an intronic miR and its host may have important biologic implications.

Overexpression of the brain and acute leukemia, cytoplasmic ( BAALC ) gene is implicated in myeloid leukemogenesis and associated with poor outcome in both acute myeloid leukemia (AML) and acute lymphoblastic leukemia patients. Additionally, high BAALC expression occurs in glioblastoma, melanoma, and childhood gastrointestinal stroma tumors, suggesting an oncogenic role for BAALC . However, the mechanisms underlying the deregulated expression are unknown. We hypothesized that a common heritable genetic feature located in cis might account for overexpression of BAALC in an allele-specific manner. By sequencing the genomic region of BAALC we identified nine informative single nucleotide polymorphisms (SNPs) and tested them for a possible association with BAALC expression levels. We show that BAALC overexpression occurs in the presence of the T allele of SNP rs62527607[GT], which creates a binding site for the activating RUNX1 transcription factor in the BAALC promoter region. The mechanism is demonstrated experimentally in vitro using luciferase reporter assays and electrophoretic mobility shift assay (EMSA) analysis. The association of high BAALC expression with the T allele and its correlations with RUNX1 expresser status are shown in vivo in a test set ( n = 253) and validation set ( n = 105) of samples from cytogenetically normal AML patients from different populations. Thus, we identify a heritable genomic feature predisposing to overexpression of an oncogene, thereby possibly leading to enhanced AML leukemogenesis. Our findings further suggest that genomic variants might become useful tools in the practice of personalized medicine.

Abstract Background: Genome-wide association studies (GWAS) for epithelial ovarian cancer (EOC), the most lethal gynecologic malignancy, have identified novel susceptibility loci. GWAS for survival after EOC have had more limited success. The association of each single-nucleotide polymorphism (SNP) individually may not be well suited to detect small effects of multiple SNPs, such as those operating within the same biologic pathway. Gene set analysis (GSA) overcomes this limitation by assessing overall evidence for association of a phenotype with all measured variation in a set of genes. Methods: To determine gene sets associated with EOC overall survival, we conducted GSA using data from two large GWAS (N cases = 2,813, N deaths = 1,116), with a novel Principal Component-Gamma GSA method. Analysis was completed for all cases and then separately for high-grade serous histologic subtype. Results: Analysis of the high-grade serous subjects resulted in 43 gene sets with P < 0.005 (1.7%); of these, 21 gene sets had P < 0.10 in both GWAS, including intracellular signaling pathway (P = 7.3 × 10−5) and macrolide binding (P = 6.2 × 10−4) gene sets. The top gene sets in analysis of all cases were meiotic mismatch repair (P = 6.3 × 10−4) and macrolide binding (P = 1.0 × 10−3). Of 18 gene sets with P < 0.005 (0.7%), eight had P < 0.10 in both GWAS. Conclusion: This research detected novel gene sets associated with EOC survival. Impact: Novel gene sets associated with EOC survival might lead to new insights and avenues for development of novel therapies for EOC and pharmacogenomic studies. Cancer Epidemiol Biomarkers Prev; 21(3); 529–36. ©2012 AACR.

To gain insight into the genomic basis of diffuse large B-cell lymphoma (DLBCL), we performed massively parallel whole-exome sequencing of 55 primary tumor samples from patients with DLBCL and matched normal tissue. We identified recurrent mutations in genes that are well known to be functionally relevant in DLBCL, including MYD88 , CARD11 , EZH2 , and CREBBP . We also identified somatic mutations in genes for which a functional role in DLBCL has not been previously suspected. These genes include MEF2B , MLL2 , BTG1 , GNA13 , ACTB , P2RY8 , PCLO , and TNFRSF14 . Further, we show that BCL2 mutations commonly occur in patients with BCL2 / IgH rearrangements as a result of somatic hypermutation normally occurring at the IgH locus. The BCL2 point mutations are primarily synonymous, and likely caused by activation-induced cytidine deaminase–mediated somatic hypermutation, as shown by comprehensive analysis of enrichment of mutations in WRCY target motifs. Those nonsynonymous mutations that are observed tend to be found outside of the functionally important BH domains of the protein, suggesting that strong negative selection against BCL2 loss-of-function mutations is at play. Last, by using an algorithm designed to identify likely functionally relevant but infrequent mutations, we identify KRAS , BRAF , and NOTCH1 as likely drivers of DLBCL pathogenesis in some patients. Our data provide an unbiased view of the landscape of mutations in DLBCL, and this in turn may point toward new therapeutic strategies for the disease.