The urinary metabolic profile of diethylene glycol methyl ether and triethylene glycol methyl ether in Sprague-Dawley rats and the role of the metabolite methoxyacetic acid in their toxicity.

Ethylene glycol ethers are a well-known series of solvents and hydraulic fluids derived from the reaction of ethylene oxide and monoalcohols. Use of methanol as the alcohol results in a series of mono, di and triethylene glycol methyl ethers. The first in the series, monoethylene glycol methyl ether (EGME or 2-methoxyethanol) is well characterised and metabolises in vivo to methoxyacetic acid (MAA), a known reproductive toxicant.

Proteomic characterization of microdissected breast tissue environment provides a protein-level overview of malignant transformation.

Both healthy and cancerous breast tissue is heterogeneous, which is a bottleneck for proteomics-based biomarker analysis, as it obscures the cellular origin of a measured protein. We therefore aimed at obtaining a protein-level interpretation of malignant transformation through global proteome analysis of a variety of laser capture microdissected cells originating from benign and malignant breast tissues. We compared proteomic differences between these tissues, both from cells of epithelial origin and the stromal environment, and performed string analysis.

The advantage of laser-capture microdissection over whole tissue analysis in proteomic profiling studies.

Laser-capture microdissection (LCM) offers a reliable cell population enrichment tool and has been successfully coupled to MS analysis. Despite this, most proteomic studies employ whole tissue lysate (WTL) analysis in the discovery of disease biomarkers and in profiling analyses. Furthermore, the influence of tissue heterogeneity in WTL analysis, nor its impact in biomarker discovery studies have been completely elucidated.

Targeted MS Assay Predicting Tamoxifen Resistance in Estrogen-Receptor-Positive Breast Cancer Tissues and Sera.

We recently reported on the development of a 4-protein-based classifier (PDCD4, CGN, G3BP2, and OCIAD1) capable of predicting outcome to tamoxifen treatment in recurrent, estrogen-receptor-positive breast cancer based on high-resolution MS data. A precise and high-throughput assay to measure these proteins in a multiplexed, targeted fashion would be favorable to measure large numbers of patient samples to move these findings toward a clinical setting. By coupling immunoprecipitation to multiple reaction monitoring (MRM) MS and stable isotope dilution, we developed a high-precision assay to measure the 4-protein signature in 38 primary breast cancer whole tissue lysates (WTLs).

Global proteomic characterization of microdissected estrogen receptor positive breast tumors.

We here describe two proteomic datasets deposited in ProteomeXchange via PRIDE partner repository [1] with dataset identifiers PXD000484 (defined as "training") and PXD000485 (defined as "test") that have been used for the development of a tamoxifen outcome predictive signature [2]. Both datasets comprised 56 fresh frozen estrogen receptor (ER) positive primary breast tumor specimens derived from patients who received tamoxifen as first line therapy for recurrent disease. Patient groups were defined based on time to progression (TTP) after start of tamoxifen therapy (6 months cutoff): 32 good and 24 poor treatment outcome patients were comprised in the training set, respectively.

4-protein signature predicting tamoxifen treatment outcome in recurrent breast cancer.

Estrogen receptor (ER) positive tumors represent the majority of breast malignancies, and are effectively treated with hormonal therapies, such as tamoxifen. However, in the recurrent disease resistance to tamoxifen therapy is common and a major cause of death. In recent years, in-depth proteome analyses have enabled identification of clinically useful biomarkers, particularly, when heterogeneity in complex tumor tissue was reduced using laser capture microdissection (LCM).

Shotgun proteomics on tissue specimens extracted with Acid guanidinium-thiocyanate-phenol-chloroform.

Protein-containing organic fractions of acid guanidinium thiocyanate-phenol-chloroform-extracted tissues are an interesting source of proteins as this method is widely used for RNA extraction for gene expression analysis. However, due to difficulties in redissolving pelleted proteins from the organic phase, protein analysis has only been limitedly reported. Current shotgun mass spectrometry-based methods, however, require minute amounts of sample, and methods have been developed that allow SDS to be removed from an extraction buffer prior to protein digestion.

Integrative analysis of genomics and proteomics data on clinical breast cancer tissue specimens extracted with acid guanidinium thiocyanate-phenol-chloroform.

Acid guanidinium thiocyanate, phenol, and chloroform extraction (AGPC) is a commonly used procedure to extract RNA from fresh frozen tissues and cell lines. In addition, DNA and proteins can be recovered, which makes AGPC an attractive source for integrative analysis on tissues of which little material is available, such as clinical specimens. Despite this potential, AGPC has only scarcely been used for proteomic analysis, mainly due to difficulties in extracting proteins.

Comparative proteome analysis revealing an 11-protein signature for aggressive triple-negative breast cancer.

Background: Clinical outcome of patients with triple-negative breast cancer (TNBC) is highly variable. This study aims to identify and validate a prognostic protein signature for TNBC patients to reduce unnecessary adjuvant systemic therapy.

Methods: Frozen primary tumors were collected from 126 lymph node-negative and adjuvant therapy-naive TNBC patients.

Optimized nLC-MS workflow for laser capture microdissected breast cancer tissue.

Reliable sample preparation is of utmost importance for comparative proteome analysis, particularly when investigating minute amounts of clinical specimens, such as laser capture microdissected tumor tissue. In this study, we present an optimized nanoLC-MS workflow specifically for the analysis of laser capture microdissected breast cancer tissue. Analytical performance of different laser capture microdissection (LCM) functions available on the PALM system, time dependent trypsin digestion efficiency, effect of sample preparation and digestion time on peptide modification, semi-tryptic peptides and missed cleavages were evaluated.

Laser capture microdissection applications in breast cancer proteomics.

Breast cancer tissues are characterized by cellular heterogeneity, representing a mixture of, e.g., healthy epithelial ducts, invasive or in situ tumor cells, surrounding stroma, infiltrating immune cells, blood vessels, and capillaries.