No abstract

Variants in the APOE gene region may explain ethnic differences in the association of Alzheimer’s disease (AD) with ε4. Ethnic differences in allele frequencies for three APOE region SNPs (single nucleotide polymorphisms) were identified and tested for association in 19,398 East Asians (EastA), including Koreans and Japanese, 15,836 European ancestry (EuroA) individuals, and 4985 African Americans, and with brain imaging measures of cortical atrophy in sub-samples of Koreans and EuroAs. Among ε4/ε4 individuals, AD risk increased substantially in a dose-dependent manner with the number of APOE promoter SNP rs405509 T alleles in EastAs (TT: OR (odds ratio) = 27.02, p = 8.80 × 10−94; GT: OR = 15.87, p = 2.62 × 10−9) and EuroAs (TT: OR = 18.13, p = 2.69 × 10−108; GT: OR = 12.63, p = 3.44 × 10−64), and rs405509-T homozygotes had a younger onset and more severe cortical atrophy than those with G-allele. Functional experiments using APOE promoter fragments demonstrated that TT lowered APOE expression in human brain and serum. The modifying effect of rs405509 genotype explained much of the ethnic variability in the AD/ε4 association, and increasing APOE expression might lower AD risk among ε4 homozygotes.

BackgroundMatrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) has been demonstrated to be useful for molecular profiling of common solid tumors. Using recently developed MALDI matrices for lipid profiling, we evaluated whether direct tissue MALDI MS analysis on proteins and lipids may classify human breast cancer samples according to the intrinsic subtype.MethodsThirty-four pairs of frozen, resected breast cancer and adjacent normal tissue samples were analyzed using histology-directed, MALDI MS analysis. Sinapinic acid and 2,5-dihydroxybenzoic acid/α-cyano-4-hydroxycinnamic acid were manually deposited on areas of each tissue section enriched in epithelial cells to identify lipid profiles, and mass spectra were acquired using a MALDI-time of flight instrument.ResultsProtein and lipid profiles distinguish cancer from adjacent normal tissue samples with the median prediction accuracy of 94.1%. Luminal, HER2+, and triple-negative tumors demonstrated different protein and lipid profiles, as evidenced by permutation P values less than 0.01 for 0.632+ bootstrap cross-validated misclassification rates with all classifiers tested. Discriminatory proteins and lipids were useful for classifying tumors according to the intrinsic subtype with median prediction accuracies of 80.0-81.3% in random test sets.ConclusionsProtein and lipid profiles accurately distinguish tumor from adjacent normal tissue and classify breast cancers according to the intrinsic subtype.

This study was undertaken to evaluate protein and lipid profiles of ovarian cancer tissue samples. Twenty-three frozen ovarian cancer samples and 6 adjacent normal samples were analyzed using histology-directed, matrix-assisted laser desorption/ionization mass spectrometry. Sinapinic acid and 2, 5-dihydroxybenzoic acid/α-cyano-4-hydroxycinnamic acid were manually deposited on areas of each tissue section enriched in epithelial cells to identify protein and lipid profiles respectively, and mass spectra were acquired using a matrix-assisted laser desorption/ionization-time of flight instrument. Protein and lipid profiles classify 11 cancer and 3 adjacent normal samples in 100 random test sets with 92.9% median accuracy. Phosphatidylcholines {32:3} [M + Na] (m/z = 750.66), {34:1} [M + K] (m/z = 798.60), and {36:2} [M + K] (m/z = 824.56) were found to be increased in ovarian cancer. Interestingly, breast cancer-associated changes in lipid and protein profiles were also found in ovarian cancer. Thus, protein and lipid profiles accurately distinguish ovarian cancer from adjacent normal tissue samples. Common cancer-associated alterations in lipid and protein profiles were identified between ovarian and breast cancers.