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Quantification of Membrane and Membrane- Bound Proteins in Normal and Malignant Breast Cancer Cells Isolated from the Same Patient with Primary Breast Carcinoma Liang, Zhao et. Al, 2006 Presented by: Richard Pelikan October 27, 2006 BioInf 2032
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Motivation How do you affect cells?
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Motivation How do you affect cells? Target the cell membrane
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Motivation How do you affect cells? Target the cell membrane What do you target? Here goes nothin’!
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Objective SILAC = Stable Isotope Labeling with Amino acids in cell Culture Determine if SILAC can effectively determine changes in the protein expression levels on cell membranes Determine if these measurements are related to disease
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Outline Introduction to Proteomics Experiments Results Discussion
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Outline Introduction to Proteomics Experiments Results Discussion
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Introduction to Proteomics Proteomics: The study of proteins How do proteins interact? What effect can we have on proteins? How are proteins related to states of health? More difficult than genomics Differences between cells, organisms, etc.
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Introduction to Proteomics Which proteins can we monitor to measure health? Biomarkers: biological entities which shows information How do you find biomarkers? Develop multiple protein assays Use high-throughput protein measurement systems
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Mass Spectrometry (MS) Zap proteins with lasers, generating a unique signature for the protein mixture
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Mass Spectrometry (MS) Zap proteins with lasers, generating a unique signature for the protein mixture 1) Collect biofluids
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Mass Spectrometry (MS) Zap proteins with lasers, generating a unique signature for the protein mixture 1) Collect biofluids2) Zap with lasers
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Mass Spectrometry (MS) Zap proteins with lasers, generating a unique signature for the protein mixture 1) Collect biofluids2) Zap with lasers3) Analyze data
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Mass Spectrometry (MS) Heavy molecules move slower Amount Mass / Charge
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Mass Spectrometry (MS) Heavy molecules move slower 7 Daltons 16 Daltons (I’m tall for my weight!) Amount Mass / Charge
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Mass Spectrometry (MS) Heavy molecules move slower Amount Mass / Charge
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Mass Spectrometry (MS) Heavy molecules move slower Amount Mass / Charge
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Mass Spectrometry (MS) Heavy molecules move slower Amount Mass / Charge
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Mass Spectrometry (MS) Heavy molecules move slower Amount Mass / Charge
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Mass Spectrometry (MS) Heavy molecules move slower Amount Mass / Charge 7
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Mass Spectrometry (MS) Heavy molecules move slower Amount Mass / Charge Amount Mass / Charge 7
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Mass Spectrometry (MS) Heavy molecules move slower Amount Mass / Charge Amount Mass / Charge 716
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Mass Spectrometry (MS) There is a tradeoff between the simplicity of data production and quality of data (In general) you don’t know which peak corresponds to which protein There are ways to control which proteins you expect to see
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Example of protein control
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Introduction Quantities of proteins can be measured using MS technology It is necessary to have control over what you see in the data to be able to identify proteins Verification is still important!
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Outline Introduction to Proteomics Experiments Results Discussion
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Experiments Biofluid: Cells taken from a 74-year old patient with breast cancer Some cells are healthy, some are from the tumor itself Technology: MS instrumentation is relatively standard Details are only for performing replication of results
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Experiments – Protein Control Normal cellsTumor cells + Light tag solution+ Heavy tag solution Cells produce tagged proteins m/z Mass spectra of the mixture shows uneven proportions of light and heavy proteins
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Experiments – measuring ratios A protein is broken down into peptides by trypsin digestion Each peptide generates a light-heavy pair The ratio of each pair is averaged to achieve the assumed ratio of the parent protein
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Figure 2 – Peptide Ratios
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Experiments Force cells to produce proteins with differently weighted tags Measure the differences in amounts of proteins with light or heavy tags Identify and study which proteins are differentially expressed
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Outline Introduction to Proteomics Experiments Results Discussion
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Results 997 proteins identified through the SILAC technique 830 of which are actually membrane proteins Only 35 were found to be “differentially expressed” Many of these are reported in literature as cancer biomarkers Immunohistochemistry seems to reflect the results seen in the MS data
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Results - Immunohistochemistry Staining seems to reflect regulation observed in MS data (for this individual) NormalCancer Normal
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Outline Introduction to Proteomics Experiments Results Discussion
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SILAC seems to be effective for characterizing changes in the membrane proteome Didn’t detect one of the most prominent membrane tumor markers
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Discussion Issues exist with this approach How can it be high-throughput? To what degree is the differential expression ratio significant to disease? Why the reliance on biopsy material? Suggestions Do a classification study Explain their independent tests better
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Thank you!! Forget proteomics, look forward to:
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