Hereditary predisposition and causative environmental exposures have long been recognized in human malignancies. In most instances, cancer cases occur sporadically, suggesting that environmental influences are critical in determining cancer risk. To test the influence of genetic polymorphisms on breast cancer risk, we have measured 98 single nucleotide polymorphisms (SNPs) distributed over 45 genes of potential relevance to breast cancer etiology in 174 patients and have compared these with matched normal controls. Using machine learning techniques such as support vector machines (SVMs), decision trees, and naïve Bayes, we identified a subset of three SNPs as key discriminators between breast cancer and controls. The SVMs performed maximally among predictive models, achieving 69% predictive power in distinguishing between the two groups, compared with a 50% baseline predictive power obtained from the data after repeated random permutation of class labels (individuals with cancer or controls). However, the simpler naïve Bayes model as well as the decision tree model performed quite similarly to the SVM. The three SNP sites most useful in this model were (a) the ؉4536T/C site of the aldosterone synthase gene CYP11B2 at amino acid residue 386 Val/Ala (T/C) (rs4541); (b) the ؉4328C/G site of the aryl hydrocarbon hydroxylase CYP1B1 at amino acid residue 293 Leu/Val (C/G) (rs5292); and (c) the ؉4449C/T site of the transcription factor BCL6 at amino acid 387 Asp/Asp (rs1056932). No single SNP site on its own could achieve more than 60% in predictive accuracy. We have shown that multiple SNP sites from different genes over distant parts of the genome are better at identifying breast cancer patients than any one SNP alone. As high-throughput technology for SNPs improves and as more SNPs are identified, it is likely that much higher predictive accuracy will be achieved and a useful clinical tool developed.
Capillary Sodium dodlecyl sulfate (SDS)-DALT an (abbreviation for Dalton) electrophoresis was applied to analysis of proteins in single HT29 human colon adenocarcinoma cells. A vacuum pulse was employed to introduce a single cell into the coated capillary. Once the cell was lysed, proteins were denatured with SDS, fluorescantly labeled with 3-(2-furoyl)-quinoline-2-carboxaldehyde (FQ), and then separated by using 8% pullulan as the sieving matrix. This method offers a few advantages for single-cell protein analysis. First, it provides reproducible separation of single-cell proteins according to their size. Based on comparison with the migration time of standard proteins, most components from a single HT29 cancer cell have molecular masses within the range of 10-100 kDa. Second, as a one-dimensional separation method, it gives fairly good resolution for proteins. Typically, around 30 protein components of a single HT29 cell were resolved, indicating that this method has similar peak capacity to SDS-polyacrylamide gel electrophoresis (PAGE). Third, this method shows high detection sensitivity and wide dynamic range, which is important because of the wide range of protein expression in living systems. Detection limits for standard proteins ranged from 10(-10) to 10(-11) M. Finally, this method provides much higher speed than classical gel electrophoresis methods, and it provides automated anlysis of cellular proteins at the single-cell level; the separation is complete in 30 min and the entire analysis takes approximately 45 min.
Capillary sodium dodecyl sulfate (SDS)-DALT electrophoresis (SDS-DALT-CE) refers to CE separation of proteins based on their size; DALT is the abbreviation for Dalton, the unit used to describe molecular weight. In this work, seven proteins from 18 to 116 kDa were denatured by SDS, labeled by 3-(2-furoyl) quinoline-2-carboxaldehyde, separated by SDS-DALT-CE in polyethylene oxide sieving matrix, and detected by laser-induced fluorescence (LIF) in a sheath flow cuvette. This method was combined with detergent differential fractionation, which is a protein fractionation method using a series of detergent-containing buffers to sequentially extract protein fractions from cells, to analyze the proteins in HT29 human colon adenocarcinoma cells. In addition, on-column labeling was demonstrated for protein analysis by SDS-DALT-CE with LIF, and applied to analysis of proteins in a single HT29 cancer cell. Most proteins had molecular masses from 10 to 120 kDa. Similar protein profiles were obtained for single cells and protein extract of a large cell population.
We report a compact, two-dimensional direct-reading fluorescence spectrograph and demonstrate its application to DNA sequencing by capillary array electrophoresis. The detection cuvette is based on sheath flow, wherein the capillaries terminate in a two-dimensional array in a fluid-filled chamber that is pressurized with buffer. A thin metal plate is located downstream from the capillaries. This barrier plate has an array of holes that precisely matches the location of the capillaries. Buffer flows through the holes, drawing analyte from the capillaries in a well-defined array of thin filaments. Fluorescence is excited in the upper chamber with an elliptically shaped laser beam. The bottom chamber is sealed with a glass window and drained from the side. Fluorescence is detected by imaging the illuminated sample streams through the holes in the barrier plate. A prism is used to disperse fluorescence from each sample across a CCD camera so that the emission spectrum is monitored simultaneously from each capillary. The instrument is demonstrated in a 32-capillary configuration but can be scaled to several thousand capillaries.
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