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Abstract LB-177: Quantification of cell signaling proteins by immuno-MALDI

2018· article· en· W2887119137 on OpenAlexaff
Robert Popp, René P. Zahedi, André LeBlanc, Yassene Mohammed, Adriana Aguilar‐Mahecha, Oliver Pötz, Mark Basik, Gerald Batist, Christoph H. Borchers

Bibliographic record

VenueCancer Research · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMolecular Biology Techniques and Applications
Canadian institutionsMcGill UniversityJewish General HospitalUniversity of Victoria
Fundersnot available
KeywordsPhosphopeptideLysis bufferPhosphorylationChemistryAlkaline phosphataseProtein kinase BLysisTrypsinMolecular biologyAKT1PI3K/AKT/mTOR pathwayBiochemistryBiologySignal transductionEnzyme

Abstract

fetched live from OpenAlex

Abstract Introduction. To improve cancer patient stratification and overcome the drawbacks of currently used approaches to assess signaling pathway proteins, we set out to develop immuno-matrix assisted laser ionization/desorption (iMALDI) assays combined with a phosphatase-based phosphopeptide quantitation (PPQ) approach to measure PI3K/AKT/mTOR pathway activity. Specifically, we targeted the C-terminal tryptic peptides of AKT1 and AKT2 due to their involvement in full kinase activation. Methods. Following trypsin digestion of cell lysate, stable isotope-labeled standard (SIS) peptides are added. After splitting the solution, one aliquot is treated with phosphatase. Bead-coupled antibodies enrich the non-phosphorylated target peptides, which are washed and spotted onto a MALDI plate, and acidic MALDI matrix elutes the peptides. The resulting light/heavy ratios of both aliquots allow the calculation of protein expression levels and peptide phosphorylation stoichiometry. Results. The iMALDI assays were validated for linear range and accuracy, as well as interference screening, requiring only ~50 µg of total cell or tissue lysate protein to quantify both AKT1 and AKT2 expression levels and phosphorylation stoichiometry. CVs of technical replicates were found to consistently be below 10%. We were able to quantify AKT1 and AKT2 from various cell lines and fresh frozen tumor samples, including SW480 and HCT116 colon cancer cell lines, MDA-MB-231 breast cancer cells, and colon cancer and breast cancer tumor lysates. Further, a direct comparison of matched fresh frozen and formalin-fixed paraffin-embedded (FFPE) tissues showed that the expression levels and phosphorylation stoichiometry quantified differ depending on the tissue preservation method, and that phosphorylation stoichiometries above 30% occur in only a small subset of samples. A direct comparison of four pairs of normal and adjacent tumor tissues showed elevated AKT1 phosphorylation stoichiometry of ~40% in a colorectal cancer liver metastasis, and significantly elevated AKT1 (3.6-fold) and AKT2 (2.2-fold) expression levels in a surgical breast tumor sample. Future directions. In a next step, patient-derived mouse xenograft tissue samples, collected after specific drug treatment, will be analyzed, and the AKT results will be correlated to genomic data to answer the hypothesis whether the AKT expression levels and phosphorylation stoichiometries correlate with response to treatment. Citation Format: Robert Popp, René P. Zahedi, André LeBlanc, Yassene Mohammed, Adriana Aguilar-Mahecha, Oliver Pötz, Mark Basik, Gerald Batist, Christoph H. Borchers. Quantification of cell signaling proteins by immuno-MALDI [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr LB-177.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.003

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.047
GPT teacher head0.399
Teacher spread0.352 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2018
Admission routes1
Has abstractyes

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