5 research outputs found

    Mutational analysis of selected high-grade malignancies in a premenopausal gynecologic cancer population: a potential for targeted therapies?

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    Abstract Background In 2017, there will be 107,000 cases of gynecologic cancer diagnosed in the US with an overall survival of around 70%-most occurring in post-menopausal individuals. In this study, we have examined a younger (≤ 40 years of age) subpopulation of these women with high grade/ high stage gynecologic malignancies, attempting to identify unique genetic abnormalities or combinations thereof through tissue block specimens. This information was then analyzed in light of known target therapies to see if genetic analysis in this setting would yield significant therapeutic advantage. Methods We retrospectively evaluated patients with high grade/high stage gynecologic cancers (≤ 40 years of age), examined the presence and status of 400 oncogenes and tumors suppressor genes from Formalin-fixed, Paraffin-embedded (FFPE) tissue and functionally classified mutations by SIFT and Polyphen. Results Twenty women were identified and stratified into positive and negative outcomes. No demographic, clinicopathologic or treatment factors were significant between these groups. Of the 400 genes evaluated, twelve mutations were significant between the groups, six with targeted therapies. Mutations associated with negative outcomes within histologies/locations were evaluated: ERBB3 in epithelial (ovarian), ALK/GPR124/KMT2D in neuroendocrine (ovarian/endometrial), ROS1/EGFR, ROS1/ERBB3/KMT2D/NIRK1 and GPR124 in sarcoma. All negative outcomes were void of mutations in APC/ABL2. A predictive model for negative outcomes in our cohort was developed from these data: AKAP9-/MBD1-/APC-/ABL2- with a mutation load of > 20.5. Conclusions Unique multi-gene and mutational outcome correlations were identified in our cohort. Resulting complex mutational profiles in distinctly aggressive gynecologic cancers suggested potential for novel therapeutic treatment. Future larger scale studies will be needed to correlate the genotypic and phenotypic features identified here

    Genome-wide association study identifies loci influencing concentrations of liver enzymes in plasma.

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    Concentrations of liver enzymes in plasma are widely used as indicators of liver disease. We carried out a genome-wide association study in 61,089 individuals, identifying 42 loci associated with concentrations of liver enzymes in plasma, of which 32 are new associations (P = 10(-8) to P = 10(-190)). We used functional genomic approaches including metabonomic profiling and gene expression analyses to identify probable candidate genes at these regions. We identified 69 candidate genes, including genes involved in biliary transport (ATP8B1 and ABCB11), glucose, carbohydrate and lipid metabolism (FADS1, FADS2, GCKR, JMJD1C, HNF1A, MLXIPL, PNPLA3, PPP1R3B, SLC2A2 and TRIB1), glycoprotein biosynthesis and cell surface glycobiology (ABO, ASGR1, FUT2, GPLD1 and ST3GAL4), inflammation and immunity (CD276, CDH6, GCKR, HNF1A, HPR, ITGA1, RORA and STAT4) and glutathione metabolism (GSTT1, GSTT2 and GGT), as well as several genes of uncertain or unknown function (including ABHD12, EFHD1, EFNA1, EPHA2, MICAL3 and ZNF827). Our results provide new insight into genetic mechanisms and pathways influencing markers of liver function
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