Proteomic analysis of formalin-fixed paraffin-embedded (FFPE) tissue would enable retrospective biomarker investigations of this vast archive of pathologically characterized clinical samples that exist worldwide. These FFPE tissues are, however, refractory to proteomic investigations utilizing many state of the art methodologies largely due to the high level of covalently cross-linked proteins arising from formalin fixation. A novel tissue microdissection technique has been developed and combined with a method to extract soluble peptides directly from FFPE tissue for mass spectral analysis of prostate cancer (PCa) and benign prostate hyperplasia (BPH). Hundreds of proteins from PCa and BPH tissue were identified, including several known PCa markers such as prostate-specific antigen, prostatic acid phosphatase, and macrophage inhibitory cytokine-1. Quantitative proteomic profiling utilizing stable isotope labeling confirmed similar expression levels of prostate-specific antigen and prostatic acid phosphatase in BPH and PCa cells, whereas the expression of macrophage inhibitory cytokine-1 was found to be greater in PCa as compared with BPH cells.

Identification and quantitation of candidate biomarker proteins in large numbers of individual tissues is required to validate specific proteins, or panels of proteins, for clinical use as diagnostic, prognostic, toxicological, or therapeutic markers. Mass spectrometry (MS) provides an exciting analytical methodology for this purpose. Liquid Tissue MS protein preparation allows researchers to utilize the vast, already existing, collections of formalin-fixed paraffin-embedded (FFPE) tissues for the procurement of peptides and the analysis across a variety of MS platforms.

BackgroundOverexpression of Met tyrosine kinase receptor is associated with poor prognosis. Overexpression, and particularly MET amplification, are predictive of response to Met-specific therapy in preclinical models. Immunohistochemistry (IHC) of formalin-fixed paraffin-embedded (FFPE) tissues is currently used to select for ‘high Met’ expressing tumors for Met inhibitor trials. IHC suffers from antibody non-specificity, lack of quantitative resolution, and, when quantifying multiple proteins, inefficient use of scarce tissue.MethodsAfter describing the development of the Liquid-Tissue-Selected Reaction Monitoring-mass spectrometry (LT-SRM-MS) Met assay, we evaluated the expression level of Met in 130 FFPE gastroesophageal cancer (GEC) tissues. We assessed the correlation of SRM Met expression to IHC and mean MET gene copy number (GCN)/nucleus or MET/CEP7 ratio by fluorescence in situ hybridization (FISH).ResultsProteomic mapping of recombinant Met identified 418TEFTTALQR426 as the optimal SRM peptide. Limits of detection (LOD) and quantitation (LOQ) for this peptide were 150 and 200 amol/µg tumor protein, respectively. The assay demonstrated excellent precision and temporal stability of measurements in serial sections analyzed one year apart. Expression levels of 130 GEC tissues ranged (<150 amol/µg to 4669.5 amol/µg. High correlation was observed between SRM Met expression and both MET GCN and MET/CEP7 ratio as determined by FISH (n = 30; R2 = 0.898). IHC did not correlate well with SRM (n = 44; R2 = 0.537) nor FISH GCN (n = 31; R2 = 0.509). A Met SRM level of ≥1500 amol/µg was 100% sensitive (95% CI 0.69–1) and 100% specific (95% CI 0.92–1) for MET amplification.ConclusionsThe Met SRM assay measured the absolute Met levels in clinical tissues with high precision. Compared to IHC, SRM provided a quantitative and linear measurement of Met expression, reliably distinguishing between non-amplified and amplified MET tumors. These results demonstrate a novel clinical tool for efficient tumor expression profiling, potentially leading to better informed therapeutic decisions for patients with GEC.

BackgroundAnalysis of key therapeutic targets such as epidermal growth factor receptor (EGFR) in clinical tissue samples is typically done by immunohistochemistry (IHC) and is only subjectively quantitative through a narrow dynamic range. The development of a standardized, highly-sensitive, linear, and quantitative assay for EGFR for use in patient tumor tissue carries high potential for identifying those patients most likely to benefit from EGFR-targeted therapies.MethodsA mass spectrometry-based Selected Reaction Monitoring (SRM) assay for the EGFR protein (EGFR-SRM) was developed utilizing the Liquid Tissue®-SRM technology platform. Tissue culture cells (n = 4) were analyzed by enzyme-linked immunosorbent assay (ELISA) to establish quantitative EGFR levels. Matching formalin fixed cultures were analyzed by the EGFR-SRM assay and benchmarked against immunoassay of the non-fixed cultured cells. Xenograft human tumor tissue (n = 10) of non-small cell lung cancer (NSCLC) origin and NSCLC patient tumor tissue samples (n = 23) were microdissected and the EGFR-SRM assay performed on Liquid Tissue lysates prepared from microdissected tissue. Quantitative curves and linear regression curves for correlation between immunoassay and SRM methodology were developed in Excel.ResultsThe assay was developed for quantitation of a single EGFR tryptic peptide for use in FFPE patient tissue with absolute specificity to uniquely distinguish EGFR from all other proteins including the receptor tyrosine kinases, IGF-1R, cMet, Her2, Her3, and Her4. The assay was analytically validated against a collection of tissue culture cell lines where SRM analysis of the formalin fixed cells accurately reflects EGFR protein levels in matching non-formalin fixed cultures as established by ELISA sandwich immunoassay (R2 = 0.9991). The SRM assay was applied to a collection of FFPE NSCLC xenograft tumors where SRM data range from 305amol/μg to 12,860amol/μg and are consistent with EGFR protein levels in these tumors as previously-reported by western blot and SRM analysis of the matched frozen tissue. In addition, the SRM assay was applied to a collection of histologically-characterized FFPE NSCLC patient tumor tissue where EGFR levels were quantitated from not detected (ND) to 670amol/μg.ConclusionsThis report describes and evaluates the performance of a robust and reproducible SRM assay designed for measuring EGFR directly in FFPE patient tumor tissue with accuracy at extremely low (attomolar) levels. This assay can be used as part of a complementary or companion diagnostic strategy to support novel therapies currently under development and demonstrates the potential to identify candidates for EGFR-inhibitor therapy, predict treatment outcome, and reveal mechanisms of therapeutic resistance.

One of the critical gaps in the clinical diagnostic space is the lack of quantitative proteomic methods for use on formalin-fixed, paraffin-embedded (FFPE) tissue. Herein, we describe the development of a quantitative, multiplexed, mass spectrometry-based selected reaction monitoring (SRM) assay for four therapeutically important targets: epidermal growth factor receptor, human EGF receptor (HER)-2, HER3, and insulin-like growth factor-1 receptor. These assays were developed using the Liquid Tissue-SRM technology platform, in which FFPE tumor tissues were microdissected, completely solubilized, and then subjected to multiplexed quantitation by SRM mass spectrometry. The assays were preclinically validated by comparing Liquid Tissue-SRM quantitation of FFPE cell lines with enzyme-linked immunosorbent assay/electrochemiluminescence quantitation of fresh cells (R(2) > 0.95). Clinical performance was assessed on two cohorts of breast cancer tissue: one cohort of 10 samples with a wide range of HER2 expression and a second cohort of 19 HER2 IHC 3+ tissues. These clinical data demonstrate the feasibility of quantitative, multiplexed clinical analysis of proteomic markers in FFPE tissue. Our findings represent a significant advancement in cancer tissue analysis because multiplexed, quantitative analysis of protein targets in FFPE tumor tissue can be tailored to specific oncological indications to provide the following: i) complementary support for anatomical pathological diagnoses, ii) patient stratification to optimize treatment outcomes and identify drug resistance, and iii) support for the clinical development of novel therapies.