Quantitative extracellular matrix proteomics to study mammary and liver tissue microenvironments

Abstract

Normal epithelium exists within a dynamic extracellular matrix (ECM) that is tuned to regulate tissue specific epithelial cell function. As such, ECM contributes to tissue homeostasis, differentiation, and disease, including cancer. Though it is now recognized that the functional unit of normal and transformed epithelium is the epithelial cell and its adjacent ECM, we lack a basic understanding of tissue-specific ECM composition and abundance, as well as how physiologic changes in ECM impact cancer risk and outcomes. While traditional proteomic techniques have advanced to robustly identify ECM proteins within tissues, methods to determine absolute abundance have lagged. Here, with a focus on tissues relevant to breast cancer, we utilize mass spectrometry methods optimized for absolute quantitative ECM analysis. Employing an extensive protein extraction and digestion method, combined with stable isotope labeled Quantitative conCATamer (QconCAT) peptides that serve as internal standards for absolute quantification of protein, we quantify 98 ECM, ECM-associated, and cellular proteins in a single analytical run. In rodent models, we applied this approach to the primary site of breast cancer, the normal mammary gland, as well as a common and particularly deadly site of breast cancer metastasis, the liver. We find that mammary gland and liver have distinct ECM abundance and relative composition. Further, we show mammary gland ECM abundance and relative compositions differ across the reproductive cycle, with the most dramatic changes occurring during the pro-tumorigenic window of weaning-induced involution. Combined, this work suggests ECM candidates for investigation of breast cancer progression and metastasis, particularly in postpartum breast cancers that are characterized by high metastatic rates. Finally, we suggest that with use of absolute quantitative ECM proteomics to characterize tissues of interest, it will be possible to reconstruct more relevant in vitro models to investigate tumor-ECM dynamics at higher resolution.

Keywords: Breast cancer; Extracellular matrix; Liver; Liver metastasis; Mammary gland; Mass spectrometry proteomics.

Figure 1. Quantitative QconCAT ECM proteomics pipeline

A) Experimental pipeline for quantitative ECM proteomics. Tissues are sequentially extracted to obtain cellular, soluble ECM (sECM), and insoluble ECM (iECM) fractions. QconCATs are spiked into fractions and samples are then proteolytically digested (full list of Quantitative conCATamers in Supplementary Table 1). B) Table of a subset of the 98 ECM/ECM-associated proteins represented in the Quantitative conCATamers (QconCAT) used to determine absolute concentration of proteins by mass spectrometry proteomics; the first three amino acids of the peptide represented are identified in italics (top). Representative chromatographic elution profile of equal molar concentration of conCATamer peptides detected by LC-SRM mass spectrometry demonstrates peptide-specific spectral profiles (bottom). For labeled peaks, darker shading indicates ¹²C₆ peptide (endogenous) and lighter shading indicates ¹³C₆ peptide (QconCAT), which is spiked in at known, equimolar concentrations. Integrated peak areas are used for ratio metric determination of endogenous peptide levels, a surrogate for protein concentration (bottom). C) Percent of proteins identified within the cellular, sECM, and iECM fractions of rat mammary gland (left) and liver (right) according to the DAVID gene ontology functional group classification. D) Percent of collagen I identified in cellular, sECM, and iECM fractions of rat mammary gland (left) and liver (right). E) Ratio of collagen alpha-1(I) to collagen alpha-2(I) for peptide spectral matches vs. QconCAT based quantification in rat mammary gland and liver.

Figure 2. QconCAT based ECM proteomics reveals unique mammary gland and liver ECM profiles

A) QconCAT based ECM proteomics of nulliparous rat mammary gland and liver tissues displayed as total abundance of proteins (nmol/gram of tissue) grouped by DAVID gene ontology functional classifications; n=5 rats/group for mammary gland and n=6 rats for liver analyses. B) Representative H&E stained rat mammary gland (MG; left) and liver (right) showing tissue specific differences in stromal-epithelial cell composition; scale bar=60 μm (arrow=MG epithelium; liver H&E shows epithelium throughout the tissue). C) Nanomolar concentration of total ECM per gram of tissue from QconCAT proteomics in the mammary gland and liver. D) Abundance of ECM and ECM-associated proteins based on DAVID gene ontology functional groups with cytoskeletal and cellular protein groups excluded. E) Twenty most abundant ECM proteins in the rat MG (left) and liver (right) as detected by QconCAT proteomics. Tabular results in Supplementary Tables 2 & 3. F) Nanomolar concentration of fibrillar collagen in MG and liver from QconCAT proteomic analysis (top left) and collagen trichrome staining quantification in MG and liver (top right). Representative trichrome stained images (blue stain) of rat MG (bottom left) and liver (bottom right); scale bar=250 μm, inset scale bar=60 μm. *=p-value<0.0001, Student’s T-test. G) Twenty most abundant ECM proteins, excluding collagen I, in the rat MG (left) and liver (right) as detected by QconCAT proteomics, tabular results shown in Supplementary Tables 2 & 3.

Figure 3. Quantitative ECM proteomics reveals dynamic and cyclical mammary gland ECM remodeling across the reproductive cycle

Principle component analysis of quantitative ECM proteomics performed on rat mammary glands across the reproductive cycle (Nullip=nulliparous; Preg=pregnancy days 18–21; Lac=lactation day 10; InvD2-InvD10=involution days 2, 4, 6, 8, and 10; Reg=regressed, 4 weeks post-weaning); n=5 rats/grp. Data shows that ECM composition in the mammary gland changes in phase with the reproductive cycle in a stepwise, cyclical fashion.

Figure 4. Quantitative ECM proteomics unravels the unique composition and abundance of ECM proteins across the reproductive cycle

A) QconCAT based ECM proteomics of rat MG tissues across the reproductive cycle, with identified cellular protein groups removed; n=5 rats/grp. B) Twenty most abundant ECM proteins in Nullip, InvD2, InvD6, and Reg stage rat MG; tabular results highlighted in Supplementary Table 2. C) Twenty most abundant ECM proteins in Nullip, InvD2, InvD6, and Reg stage rat MG, with collagen I removed from the analysis. Tabular results in Supplementary Table 2. D) Select tumor suppressive (lumican) and tumor-promotional (collagen VI, thrombospondin 1, galectin-3, tenascin-C) ECM protein levels, as well as collagen XII from individual rats, as determined by QconCAT based ECM proteomics of Nullip, InvD2, InvD6, and Reg stages, n=5 rats/grp; *=p-value<0.05, **=p-value<0.01, ***=p-value<0.001, ****=p-value<0.0001, One-way ANOVA.