Identification of vascular breast tumor markers by laser capture microdissection and label-free LC-MS

Blood vessels in tumors frequently show abnormal characteristics, such as tortuous morphology or leakiness, but very little is known about protein expression in tumor vessels. In this study, we have used laser capture microdissection (LCM) to isolate microvessels from clinical samples of invasive ductal carcinoma (IDC), the most common form of malignant breast cancer, and from patient-matched adjacent nonmalignant tissue. This approach eliminates many of the problems associated with the heterogeneity of clinical tumor tissues by controlling for differences in protein expression between both individual patients and different cell types. Proteins from the microvessels were trypsinized and the resulting peptides were quantified by a label-free nanoLC-MS method. A total of 86 proteins were identified that are overexpressed in tumor vessels relative to vessels isolated from the adjacent nonmalignant tissue. These proteins include well-known breast tumor markers such as Periostin and Tenascin C but also proteins with lesser-known or emerging roles in breast cancer and tumor angiogenesis (i.e., Serpin H1, Clic-1, and Transgelin 2). We also identified 40 proteins that were relatively under-expressed in IDC tumor vessels, including several components of the basement membrane whose lower expression could be responsible for weakening tumor vessels. Lastly, we show that a subset of 29 proteins, derived from our list of differentially expressed proteins, is able to predict survival in three publicly available clinical breast cancer microarray data sets, which suggests that this subset of proteins likely plays a functional role in cancer progression and outcome.     

Proteome analysis of hepatocellular carcinoma by laser capture microdissection

Hepatocellular carcinoma (HCC) is one of the most frequent visceral neoplasia worldwide and is a multifactorial and multistage pathogenesis that finally leads to the deregulation of cell homeostasis. Laser capture microdissection (LCM) may allow a more ready identification of differences in protein expression in selected cell types or areas of tissue, and microscopic regions as small as 3-5 microm in diameter can be sampled. Here we applied the LCM to the proteomic study of hepatitis B-related HCC and surrounding non-tumor tissues. Proteome alterations were observed using 2-DE and ESI-MS/MS, and alterations in the proteome were examined. Twenty protein spots were selected, of which 11 proteins were significantly altered in the HCC compared with the surrounding non-tumor tissues. Of the proteins that were selected, peroxiredoxin 2, apolipoprotein A-I precursor, 3-hydroxyacyl-CoA dehydrogenase type II, and 14.5-kDa translational inhibitor protein appear to be novel candidates as useful hepatitis B-related HCC markers. This study indicates that LCM is a useful technological method in the proteomic study of cancer tissue. The proteins revealed in this experiment can be used in the future for studies pertaining to hepatocarcinogenesis, or as diagnostic markers and therapeutic targets for HCC associated with hepatitis B virus infection.     

Proteomic analysis of high-grade dysplastic cervical cells obtained from ThinPrep slides using laser capture microdissection and mass spectrometry

The purpose of this discovery phase study was to identify candidate protein biomarkers for high-grade dysplastic cervical cells using mass spectrometry. Laser Capture Microdissection (LCM) was utilized to isolate high-grade dysplastic and normal cells from ThinPrep slides prepared from cervical cytological specimens. Following cell capture, samples were solubilized and proteins separated by gel electrophoresis in preparation for enzymatic digestion and liquid chromatography mass spectrometry analysis (LC-MS). Processed samples were subsequently analyzed using a linear ion trap coupled with a Fourier transform mass spectrometer (LTQ-FT MS). It was determined that both PreservCyt Solution and ThinPrep Pap Stain (Cytyc Corporation) were compatible with the sample processing and LC-MS analysis. In total, from 9 normal and 9 abnormal cervical cytological specimens, more than 1000 unique proteins were identified with high confidence, based on approximately 12,000 captured cells per specimen. Quantitative protein differences between HSIL (High-Grade Squamous Intraepithelial Lesion) and NILM (Negative for Intraepithelial Lesions or Malignancy) samples were determined by comparing the intensities of the representative (label-free) peptide ions. More than 200 proteins were found to exhibit a 3-fold difference in protein level. Interestingly, significant up-regulation of nuclear and mitochondrial proteins in HSIL specimens was noted. In several cases, the increased protein abundance observed in high-grade cells, as determined by quantitative LC-MS, was validated by immunocytochemical methods using ThinPrep cervical specimens. With the study of additional clinical specimens, the differential abundance of proteins in high-grade dysplastic cells versus morphologically normal cervical cells may lead to validated novel biomarkers for cervical disease.     

Robust MS quantification method for phospho-peptides using 18O/16O labeling

Background  

Quantitative measurements of specific protein phosphorylation sites, as presented here, can be used to investigate signal transduction pathways, which is an important aspect of cell dynamics. The presented method quantitatively compares peptide abundances from experiments using ¹⁸O/¹⁶O labeling starting from elaborated MS spectra. It was originally developed to study signaling cascades activated by amyloid-β treatment of neurons used as a cellular model system with relevance to Alzheimer's disease, but is generally applicable.     

Proteomic analysis of advanced colorectal cancer by laser capture microdissection and two-dimensional difference gel electrophoresis

The emergence of laser capture microdissection (LCM) and two-dimensional difference gel electrophoresis (2D-DIGE) has been shown to greatly improve the accuracy and sensitivity of global protein expression analysis. However, their combined use in profiling tumour proteome has rarely been reported. In this study, we applied these techniques to profile the protein expression changes of the late stage colorectal cancer (CRC) and its liver metastases. The study revealed that both the primary and secondary tumours showed a distinct protein expression profile compared to normal tissues, but were indistinguishable from each other. Differential analysis between the primary tumour and patient-matched normal colon mucosa identified a total of 71 proteins to be altered in CRC. Over 40% of these proteins have been previously reported as CRC-related proteins, validating the accuracy of the current analysis. We have also identified many previously unknown changes including overexpression of ACY1, HSC70, HnRNP I, HnRNP A3, SET, ANP32A and TUFM in CRC, which have been further verified by western blotting and immunohistochemistry. This study demonstrated that LCM in combination with 2D-DIGE is a powerful tool to analyse the proteome of tumour tissues and may lead to the identification of potential novel protein markers and therapeutic targets for cancer.     

Quantitative proteomics using 16O/18O labeling and linear ion trap mass spectrometry

Quantitative proteomics using stable isotopic 16O/18O labeling has emerged as a very powerful tool, since it has a number of advantages over other methods, including the simplicity of chemistry, the constant mass tag at the C termini and its general applicability. However, due to the small mass difference between labeled and unlabeled peptide species, this approach has usually been restricted to high-resolution mass spectrometers. In this study we explored whether the high-resolution scanning mode, together with the extremely high scanning speed of the linear IT allows the 16O/18O-labeling method to be used for accurate, large-scale quantitative analysis of proteomes. A protocol, including digestion, desalting, labeling, MS and quantitative analysis was developed and tested using protein standards and whole proteome extracts. Using this method we were able to identify and quantify 140 proteins from only 10 mug of a proteome extract from mesenchymal stem cells. Relative expression changes larger than twofold can be identified with this method at the 95% confidence level. Our results demonstrate that accurate quantitative analysis using 16O/18O labeling can be performed in the practice using linear IT MS, without compromising large-scale peptide identification efficiency.     

Quantitative proteomic analysis of mouse embryonic fibroblasts and induced pluripotent stem cells using 16O/18O labeling

Induced pluripotent stem cells (iPSC) hold great promise for regenerative medicine as well as for investigations into the pathogenesis and treatment of various diseases. Understanding of key intracellular signaling pathways and protein targets that control development of iPSC from somatic cells is essential for designing new approaches to improve reprogramming efficiency. Here, we report the development and application of an integrated quantitative proteomics platform for investigating differences in protein expressions between mouse embryonic fibroblasts (MEF) and MEF-derived iPSC. This platform consists of 16O/18O labeling, multidimensional peptide separation coupled with tandem mass spectrometry, and data analysis with UNiquant software. With this platform, a total of 2481 proteins were identified and quantified from the 16O/18O-labeled MEF-iPSC proteome mixtures with a false discovery rate of 0.01. Among them, 218 proteins were significantly upregulated, while 247 proteins were significantly downregulated in iPSC compared to MEF. Many nuclear proteins, including Hdac1, Dnmt1, Pcna, Ccnd1, Smarcc1, and subunits in DNA replication and RNA polymerase II complex, were found to be enhanced in iPSC. Protein network analysis revealed that Pcna functions as a hub orchestrating complicated mechanisms including DNA replication, epigenetic inheritance (Dnmt1), and chromatin remodeling (Smarcc1) to reprogram MEF and maintain stemness of iPSC.     

Quantitative proteome analysis of human plasma following in vivo lipopolysaccharide administration using 16O/18O labeling and the accurate mass and time tag approach

Identification of novel diagnostic or therapeutic biomarkers from human blood plasma would benefit significantly from quantitative measurements of the proteome constituents over a range of physiological conditions. Herein we describe an initial demonstration of proteome-wide quantitative analysis of human plasma. The approach utilizes postdigestion trypsin-catalyzed 16O/18O peptide labeling, two-dimensional LC-FTICR mass spectrometry, and the accurate mass and time (AMT) tag strategy to identify and quantify peptides/proteins from complex samples. A peptide accurate mass and LC elution time AMT tag data base was initially generated using MS/MS following extensive multidimensional LC separations to provide the basis for subsequent peptide identifications. The AMT tag data base contains >8,000 putative identified peptides, providing 938 confident plasma protein identifications. The quantitative approach was applied without depletion of high abundance proteins for comparative analyses of plasma samples from an individual prior to and 9 h after lipopolysaccharide (LPS) administration. Accurate quantification of changes in protein abundance was demonstrated by both 1:1 labeling of control plasma and the comparison between the plasma samples following LPS administration. A total of 429 distinct plasma proteins were quantified from the comparative analyses, and the protein abundances for 25 proteins, including several known inflammatory response mediators, were observed to change significantly following LPS administration.     

Proteomic analysis of infiltrating ductal carcinoma tissues by coupled 2-D DIGE/MS/MS analysis

There is a growing interest in protein expression profiling aiming to identify novel diagnostic markers in breast cancer. Proteomic approaches such as two-dimensional differential gel electrophoresis coupled with tandem mass spectrometry analysis (2-D DIGE/MS/MS) have been used successfully for the identification of candidate biomarkers for screening, diagnosis, prognosis and monitoring of treatment response in various types of cancer. Identifying previously unknown proteins of potential clinical relevance will ultimately help in reaching effective ways to manage the disease. We analyzed breast cancer tissues from five tumor and five normal tissue samples from ten breast cancer subjects with infiltrating ductal carcinoma (IDC) by 2-D DIGE using two types of immobilized pH gradient (IPG) strips: pH 3-10 and pH 4-7. From all the spots detected, differentially expressed (p < 0.05 and ratio > 2) were 50 spots. Of these, 39 proteins were successfully identified by MS, representing 29 different proteins. Ten proteins were overexpressed in the tumor samples. The 2-D DIGE/MS/MS analysis revealed an increase in the expression levels in tumor samples of several proteins not previously associated with breast cancer, such as: macrophage-capping protein (CAPG), phosphomannomutase 2 (PMM2), ATPase ASN1, methylthioribose-1-phosphate isomerase (MRI1), peptidyl-prolyl cis-trans isomerase FKBP4, cellular retinoic acid-binding protein 2 (CRABP2), lamin B1 and keratin, type II cytoskeletal 8 (KRT8). Ingenuity Pathway Analysis (IPA) revealed highly significant (p = 10(-26)) interactions between the identified proteins and their association with cancer. These proteins are involved in many diverse pathways and have established roles in cellular metabolism. It remains the goal of future work to test the suitability of the identified proteins in samples of larger and independent patient groups.     

Proteomic analysis of prolactinoma cells by immuno-laser capture microdissection combined with online two-dimensional nano-scale liquid chromatography/mass spectrometry

Background  

Pituitary adenomas, the third most common intracranial tumor, comprise nearly 16.7% of intracranial neoplasm and 25%-44% of pituitary adenomas are prolactinomas. Prolactinoma represents a complex heterogeneous mixture of cells including prolactin (PRL), endothelial cells, fibroblasts, and other stromal cells, making it difficult to dissect the molecular and cellular mechanisms of prolactin cells in pituitary tumorigenesis through high-throughout-omics analysis. Our newly developed immuno-laser capture microdissection (LCM) method would permit rapid and reliable procurement of prolactin cells from this heterogeneous tissue. Thus, prolactin cell specific molecular events involved in pituitary tumorigenesis and cell signaling can be approached by proteomic analysis.     

Identificating cathepsin D as a biomarker for differentiation and prognosis of nasopharyngeal carcinoma by laser capture microdissection and proteomic analysis

In this study, we applied laser capture microdissection and a proteomic approach to identify novel nasopharyngeal carcinoma (NPC) biomarkers. Proteins from pooled microdissected NPC and normal nasopharyngeal epithelial tissues (NNET) were separated by two-dimensional gel electrophoresis, and differential proteins were identified by mass spectrometry. Expression of the differential protein cathepsin D in the above two tissues as well as four NPC cell lines was determined by Western blotting. Next, siRNA was used to inhibit the expression of cathepsin D in highly metastatic NPC cell line 5-8F to examine whether it associates with NPC metastasis. Immunohistochemistry was also performed to detect the expression of cathepsin D in 72 cases of primary NPC, 28 cases of NNET, and 20 cases of cervical lymph node metastases, and the correlation of its expression level with clinicopathologic features and clinical outcomes were evaluated. Thirty-six differential proteins between the NPC and NNET were identified. The expression level of cathepsin D in the two types of tissues was confirmed by Western blotting and related to differentiation degree and metastatic potential of the NPC cell lines. Down-regulated cathepsin D expression by siRNA significantly decreased in vitro invasive ability of 5-8F cells. Significant cathepsin D down-regulation was observed in NPC versus NNET, whereas significant cathepsin D up-regulation was observed in lymph node metastasis versus primary NPC. In addition, cathepsin D down-regulation was significantly correlated with poor histological differentiation, whereas cathepsin D up-regulation was significantly correlated with advanced clinical stage, recurrence, and lymph node and distant metastasis. Furthermore, survival curves showed that patients with cathepsin D up-regulation had a poor prognosis. Multivariate analysis confirmed that cathepsin D expression was an independent prognostic indicator. The data suggest that cathepsin D is a potential biomarker for the differentiation and prognosis of NPC, and its dysregulation might play an important role in the pathogenesis of NPC.     

Gene expression in the tuberculous granuloma: analysis by laser capture microdissection and real-time PCR

We have assessed the kinetics of host gene expression in granulomas of mice infected with virulent Mycobacterium tuberculosis, using an approach that incorporates the laser capture microdissection (LCM) and real-time PCR technology in conjunction with a newly derived mathematical equation. The results have provided evidence indicating that conventional use of whole infected lungs to study granuloma-specific gene expression can yield data that may not genuinely reflect intralesional events. Significantly, the expression of nine host genes known to regulate the inflammatory response to M. tuberculosis, as determined by real-time PCR analysis of microdissected granuloma-derived cDNAs, was downregulated (up to 27-fold) at around the time when the rapid growth phase of the bacilli in the lungs of infected mice ends. This downregulation was masked when whole infected lungs were used for the studies. The data suggest that the host immune system can adjust and respond to, or can be modulated by specific physiological states of the tubercle bacillus in vivo. The LCM/real-time PCR-based system described in this study can be applied to safely and accurately evaluate gene expression in any lesions that can be microscopically visualized, including those contained in biohazardous tissues.     

Accurate qualitative and quantitative proteomic analysis of clinical hepatocellular carcinoma using laser capture microdissection coupled with isotope-coded affinity tag and two-dimensional liquid chromatography mass spectrometry

Laser capture microdissection (LCM) is a powerful tool that enables the isolation of specific cell types from tissue sections, overcoming the problem of tissue heterogeneity and contamination. This study combined the LCM with isotope-coded affinity tag (ICAT) technology and two-dimensional liquid chromatography to investigate the qualitative and quantitative proteomes of hepatocellular carcinoma (HCC). The effects of three different histochemical stains on tissue sections have been compared, and toluidine blue stain was proved as the most suitable stain for LCM followed by proteomic analysis. The solubilized proteins from microdissected HCC and non-HCC hepatocytes were qualitatively and quantitatively analyzed with two-dimensional liquid chromatography tandem mass spectrometry (2D-LC-MS/MS) alone or coupled with cleavable ICAT labeling technology. A total of 644 proteins were qualitative identified, and 261 proteins were unambiguously quantitated. These results show that the clinical proteomic method using LCM coupled with ICAT and 2D-LC-MS/MS can carry out not only large-scale but also accurate qualitative and quantitative analysis.     

Application of laser capture microdissection combined with two-dimensional electrophoresis for the discovery of differentially regulated proteins in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is the most lethal of all the common malignancies and markers for early detection or targets for treatment of this disease are urgently required. The disease is characterised by a strong stromal response, with cancer cells usually representing a relatively small proportion of the cells in the tumor mass. We therefore performed laser capture microdissection (LCM) to enrich for both normal and malignant pancreatic ductal epithelial cells. Proteins extracted from these cells were then separated by two-dimensional gel electrophoresis (2-DE). The limited amounts of protein in the LCM procured samples necessitated the detection of 2-DE resolved proteins by silver staining. Consequently, loading equivalent amounts of protein onto gels was essential. However, we found that conventional means of measuring total protein in the samples were not sufficiently accurate. We therefore adopted a strategy in which the samples were first separated by one-dimensional sodium dodecyl sulphate-polyacrylamide gel electrophoresis, stained with silver stain and subjected to densitometry. Evaluation of the staining intensity was then used to normalise the samples. We found that the protein profiles from undissected normal pancreas and LCM-acquired non-malignant ductal epithelial cells from the same tissue block were different, underpinning the value of LCM in our analysis. The comparisons of protein profiles from nonmalignant and malignant ductal epithelial cells revealed nine protein spots that were consistently differentially regulated. Five of these proteins showed increased expression in tumor cells while four showed diminished expression in these cells. One of the proteins displaying enhanced expression in tumor cells was identified as the calcium-binding protein, S100A6. To determine the incidence of S100A6 overexpression in pancreatic cancer, we carried out immunohistochemical analysis on sections from a pancreas cancer tissue array containing 174 duplicate normal and malignant pancreatic tissue samples, from 46 pancreas cancer patients. Normal pancreatic ductal epithelia were either devoid of detectable S100A6 or showed weak expression only. Moderately or poorly differentiated tumors, by contrast, showed a higher incidence and a higher level of S100A6 expression. These observations indicate that the combination of LCM with 2-DE provides an effective strategy to discover proteins that are differentially expressed in PDAC.     

A quantitative analysis of Arabidopsis plasma membrane using trypsin-catalyzed (18)O labeling

Typical mass spectrometry-based protein lists from purified fractions are confounded by the absence of tools for evaluating contaminants. In this report, we compare the results of a standard survey experiment using an ion trap mass spectrometer with those obtained using dual isotope labeling and a Q-TOF mass spectrometer to quantify the degree of enrichment of proteins in purified subcellular fractions of Arabidopsis plasma membrane. Incorporation of a stable isotope, either H(2)(18)O or H(2)(16)O, during trypsinization allowed relative quantification of the degree of enrichment of proteins within membranes after phase partitioning with polyethylene glycol/dextran mixtures. The ratios allowed the quantification of 174 membrane-associated proteins with 70 showing plasma membrane enrichment equal to or greater than ATP-dependent proton pumps, canonical plasma membrane proteins. Enriched proteins included several hallmark plasma membrane proteins, such as H(+)-ATPases, aquaporins, receptor-like kinases, and various transporters, as well as a number of proteins with unknown functions. Most importantly, a comparison of the datasets from a sequencing "survey" analysis using the ion trap mass spectrometer with that from the quantitative dual isotope labeling ratio method indicates that as many as one-fourth of the putative survey identifications are biological contaminants rather than bona fide plasma membrane proteins.     

Proteomic analysis of human ventricular cerebrospinal fluid from neurologically normal, elderly subjects using two-dimensional LC-MS/MS

A two-dimensional liquid chromatography separation scheme coupled to tandem mass spectrometry (2-D LC-MS/MS) was utilized to profile the proteome of human CSF. Ventricular CSF samples acquired post-mortem from 10 cognitively normal elderly subjects (mean +/- SEM Braak stage = 1.7 +/- 0.2) were analyzed to determine their protein composition. Raw CSF samples were subjected to an immunobased processing method to remove highly abundant albumin and immunoglobulin (Ig), allowing better detection of lower-abundance proteins. Samples were subjected to trypsin proteolysis followed by C18 solid-phase extraction. Tryptic CSF peptides were separated using a 2-D LC column, in which both strong cation exchange (SCX) and C18 phases were packed into a single capillary. MS/MS spectra of CSF peptides were searched against a human sub-database of the NBCI nonredundant database using the SEQUEST algorithm. Search results were further filtered using DTAselect, and individual samples were compared to one another using Contrast. Using this method, we were able to unambiguously identify 249 CSF proteins from 10 subjects. Of these proteins, 38% were unique to individual subjects, whereas only 6% were common to all 10 subjects. These results suggest considerable subject-to-subject variability in the CSF proteome.     

Tracing the Sources of Exported Nitrate in the Turkey Lakes Watershed Using 15N/14N and 18O/16O isotopic ratios

Nitrate produced by bacterially mediated nitrification in soils is isotopically distinct from atmospheric nitrate in precipitation. ¹⁵N/¹⁴N and ¹⁸O/¹⁶O isotopic ratios of nitrate can therefore be used to distinguish between these two sources of nitrate in surface waters and groundwaters. Two forested catchments in the Turkey Lakes Watershed (TLW) near Sault Ste. Marie, Ontario, Canada were studied to determine the relative contributions of atmospheric and microbial nitrate to nitrate export. The TLW is reasonably undisturbed and receives a moderate amount of inorganic nitrogen bulk deposition (8.7 kg N · ha⁻¹· yr⁻¹) yet it exhibits unusually low inorganic nitrogen retention (average = 65% of deposition). The measured isotopic ratios for nitrate in precipitation ranged from +35 to +59‰ (VSMOW) for δ¹⁸O and −4 to +0.8‰ (AIR) for δ¹⁵N. Nitrate produced from nitrification at the TLW is expected to have an average isotope value of approximately −1.0‰ for δ¹⁸O and a value of about 0 to +6‰ for δ¹⁵N, thus, the isotopic separation between atmospheric and soil sources of nitrate is substantial. Nitrate produced by nitrification of ammonium appears to be the dominant source of the nitrate exported in both catchments, even during the snowmelt period. These whole catchment results are consistent with the results of small but intensive plot scale studies that have shown that the majority of the nitrate leached from these catchments is microbial in origin. The isotopic composition of stream nitrate provides information about N-cycling in the forested upland and riparian zones on a whole catchment basis. Received 5 October 1999; accepted 18 August 2000     

AgNOR analysis of atypical ductal hyperplasia and intraductal carcinoma of the breast

OBJECTIVE: To determine the diagnostic and prognostic value of argyrophilic nucleolar organizer regions (AgNORs) in atypical ductal hyperplasia (ADH), ductal carcinoma in situ (DCIS) and microinvasive ductal carcinoma (MDCA) of the breast. STUDY DESIGN: Image analysis of histologic sections from biopsies of 46 breast ADH and DCIS and 18 cases of MDCA. Determination of morphometric features of cell nuclei and nucleolar organizer regions by using AMBA software system. Data were compared with the estrogen receptor/progesterone receptor (ER/PR) content as well as with the growth fraction, determined immunohistochemically. RESULTS: AgNOR number and total AgNOR area increased from ADH to DCIS. The highest values were recorded in cases of DCIS with microinvasion. Differences between ADH and intraductal or microinvasive ductal carcinoma were statistically significant. Within the group of intraductal carcinomas, the lowest values were measured in the solid type and highest values in the comedo type. A correlation was found between AgNOR features and growth fraction but not between these features and ER/PR status. CONCLUSION: Selected AgNOR features are relevant for differentiation between ADH and DCIS as well as between low and high grade DCIS and microinvasive ductal carcinoma. Therefore, objective and reproducible data obtained by AgNOR analysis may allow better evaluation of the prognostic significance of these lesions.     

High-throughput proteomic analysis of human infiltrating ductal carcinoma of the breast

Large-scale proteomics will play a critical role in the rapid display, identification and validation of new protein targets, and elucidation of the underlying molecular events that are associated with disease development, progression and severity. However, because the proteome of most organisms are significantly more complex than the genome, the comprehensive analysis of protein expression changes will require an analytical effort beyond the capacity of standard laboratory equipment. We describe the first high-throughput proteomic analysis of human breast infiltrating ductal carcinoma (IDCA) using OCT (optimal cutting temperature) embedded biopsies, two-dimensional difference gel electrophoresis (2-D DIGE) technology and a fully automated spot handling workstation. Total proteins from four breast IDCAs (Stage I, IIA, IIB and IIIA) were individually compared to protein from non-neoplastic tissue obtained from a female donor with no personal or family history of breast cancer. We detected differences in protein abundance that ranged from 14.8% in stage I IDCA versus normal, to 30.6% in stage IIB IDCA versus normal. A total of 524 proteins that showed > or = three-fold difference in abundance between IDCA and normal tissue were picked, processed and identified by mass spectrometry. Out of the proteins picked, approximately 80% were unambiguously assigned identities by matrix-assisted laser desorbtion/ionization-time of flight mass spectrometry or liquid chromatography-tandem mass spectrometry in the first pass. Bioinformatics tools were also used to mine databases to determine if the identified proteins are involved in important pathways and/or interact with other proteins. Gelsolin, vinculin, lumican, alpha-1-antitrypsin, heat shock protein-60, cytokeratin-18, transferrin, enolase-1 and beta-actin, showed differential abundance between IDCA and normal tissue, but the trend was not consistent in all samples. Out of the proteins with database hits, only heat shock protein-70 (more abundant) and peroxiredoxin-2 (less abundant) displayed the same trend in all the IDCAs examined. This preliminary study demonstrates quantitative and qualitative differences in protein abundance between breast IDCAs and reveals 2-D DIGE portraits that may be a reflection of the histological and pathological status of breast IDCA.