Abstract 4919: Multiplexed EGFR signaling pathway analysis in FFPE tissue using quantitative mass spectrometry
Bibliographic record
Abstract
Abstract The epidermal growth factor receptor (EGFR) is a drug target for both small molecule and antibody therapeutics and has been approved in non small-cell lung carcinoma (NSCLC) and colorectal carcinoma (CRC) among other indications. These drugs block receptor signaling though blockade of the tyrosine kinase domain, or through inhibition of ligand binding. Current genomic tests measure receptor amplification, RNA levels, the mutation status of receptor or pathway molecules (EGFR or kRAS mutations) but no current assay can directly assess the activation state of the EGFR or its downstream signaling pathway components. Indeed, the EGFR mutation positive NSCLC tumors (thought to be constitutively active) show a high response rate to TKI therapy, but the many non responders (50% or more) demonstrate the limitation of genomic analysis. Since activation of EGFR is necessary for the response to these targeted agents, it is critical to measure what levels of receptor activation and downstream signaling determines tumor responsiveness to EGFR targeted therapies in these patients. For this reason, we have developed a panel of new diagnostic assays which measure the activation of the EGFR and key downstream signaling proteins through quantitation of the phosphorylation state of these proteins. These assays are based on the Liquid Tissue®-SRM technology platform. This approach enables relative and absolute quantification of proteins and their phosphorylation status directly in formalin fixed paraffin embedded (FFPE) tissue. We preclinically validated the multiplexed Liquid Tissue® phospho-SRM assay on formalin fixed EGF stimulated A431 cells. We followed up these in vitro studies with phospho-SRM analysis of FFPE NSCLC xenograft explants where extensive independent histopathologic and molecular characterization had been performed, allowing us to benchmark our phospho-SRM analysis with standard diagnostic analyses. We have now extended these quantitation studies by measuring the expression of EGFR and phospho-EGFR in FFPE tissues obtained from relevant human clinical trial cohorts – Gefitinib treated NSCLC and Cetuximab treated CRC. It is hoped that we will be able to correlate EGFR expression, activation and signaling in these tumors with responsiveness to EGFR targeted therapy, and to validate this assay for use as a companion diagnostic to guide therapy in both NSCLC and CRC. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4919. doi:10.1158/1538-7445.AM2011-4919
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".