Minimally invasive biopsy-based diagnostics in support of precision cancer medicine.

Precision cancer medicine (PCM) to support the treatment of solid tumors requires minimally invasive diagnostics. Here, we describe the development of fine-needle aspiration biopsy-based (FNA) molecular cytology which will be increasingly important in diagnostics and adaptive treatment. We provide support for FNA-based molecular cytology having a significant potential to replace core needle biopsy (CNB) as a patient-friendly potent technique for tumor sampling for various tumor types. This is not only because CNB is a more traumatic procedure and may be associated with more complications compared to FNA-based sampling, but also due to the recently developed molecular methods used with FNA. Recent studies show that image-guided FNA in combination with ultrasensitive molecular methods also offers opportunities for characterization of the tumor microenvironment which can aid therapeutic decisions. Here we provide arguments for an increased implementation of molecular FNA-based sampling as a patient-friendly diagnostic method, which may, due to its repeatability, facilitate regular sampling that is needed during different treatment lines, to provide tumor information, supporting treatment decisions, shortening lead times in healthcare, and benefit healthcare economics.

Multiplex protein analysis and ensemble machine learning methods of fine needle aspirates from prostate cancer patients reveal potential diagnostic signatures associated with tumour grade.

BACKGROUND: Improved molecular diagnosis is needed in prostate cancer (PC). Fine needle aspiration (FNA) is a minimally invasive biopsy technique, less traumatic compared to core needle biopsy, and could be useful for diagnosis of PC. Molecular biomarkers (BMs) in FNA-samples can be assessed for prediction, eg of immunotherapy efficacy before treatment as well as at treatment decision time points during disease progression. METHODS: In the present pilot study, the expression levels of 151 BM proteins were analysed by proximity extension assay in FNA-samples from 16 patients, including benign prostate lesions (n = 3) and cancers (n = 13). An ensemble data analysis strategy was applied using several machine learning models. RESULTS: Twelve potentially predictive BM proteins correlating with International Society of Urological Pathology grade groups were identified, among them vimentin, tissue factor pathway inhibitor 2, and integrin beta-5. The validity of the results was supported by network analysis that showed functional associations between most of the identified putative BMs. We also showed that multiple immune checkpoint targets can be assessed (eg PD-L1, CD137, and Galectin-9), which may support the selection of immunotherapy in advanced PC. Results are promising but need further validation in a larger cohort. CONCLUSIONS: Our pilot study represents a "proof of concept" and shows that multiplex profiling of potential diagnostic and predictive BM proteins is feasible on tumour material obtained by FNA sampling of prostate cancer. Moreover, our results demonstrate that an ensemble data analysis strategy may facilitate the identification of BM signatures in pilot studies when the patient cohort is limited.

Plasma RNA profiling unveils transcriptional signatures associated with resistance to osimertinib in EGFR T790M positive non-small cell lung cancer patients.

Background: Targeted therapy with tyrosine kinases inhibitors (TKIs) against epidermal growth factor receptor (EGFR) is part of routine clinical practice for EGFR mutant advanced non-small cell lung cancer (NSCLC) patients. These patients eventually develop resistance, frequently accompanied by a gatekeeper mutation, T790M. Osimertinib is a third-generation EGFR TKI displaying potency to the T790M resistance mutation. Here we aimed to analyze if exosomal RNAs, isolated from longitudinally sampled plasma of osimertinib-treated EGFR T790M NSCLC patients, could provide biomarkers of acquired resistance to osimertinib. Methods: Plasma was collected at baseline and progression of disease from 20 patients treated with osimertinib in the multicenter phase II study TKI in Relapsed EGFR-mutated non-small cell lung cancer patients (TREM). Plasma was centrifuged at 16,000 g followed by exosomal RNA extraction using Qiagen exoRNeasy kit. RNA was subjected to transcriptomics analysis with Clariom D. Results: Transcriptome profiling revealed differential expression [log2(fold-change) >0.25, false discovery rate (FDR) P<0.15, and P(interaction) >0.05] of 128 transcripts. We applied network enrichment analysis (NEA) at the pathway level in a large collection of functional gene sets. This overall enrichment analysis revealed alterations in pathways related to EGFR and PI3K as well as to syndecan and glypican pathways (NEA FDR <3×10-10). When applied to the 40 individual, sample-specific gene sets, the NEA detected 16 immune-related gene sets (FDR <0.25, P(interaction) >0.05 and NEA z-score exceeding 3 in at least one sample). Conclusions: Our study demonstrates a potential usability of plasma-derived exosomal RNAs to characterize molecular phenotypes of emerging osimertinib resistance. Furthermore, it highlights the involvement of multiple RNA species in shaping the transcriptome landscape of osimertinib-refractory NSCLC patients.

Profiling of extracellular vesicles of metastatic urothelial cancer patients to discover protein signatures related to treatment outcome.

The prognosis of metastatic urothelial carcinoma (mUC) patients is poor, and early prediction of systemic therapy response would be valuable to improve outcome. In this exploratory study, we investigated protein profiles in sequential plasma-isolated extracellular vesicles (EVs) from a subset of mUC patients treated within a Phase I trial with vinflunine combined with sorafenib. The isolated EVs were of exosome size and expressed exosome markers CD9, TSG101 and SYND-1. We found, no association between EVs/ml plasma at baseline and progression-free survival (PFS). Protein profiling of EVs, using an antibody-based 92-plex Proximity Extension Assay on the Oncology II® platform, revealed a heterogeneous protein expression pattern. Qlucore bioinformatic analyses put forward a protein signature comprising of SYND-1, TNFSF13, FGF-BP1, TFPI-2, GZMH, ABL1 and ERBB3 to be putatively associated with PFS. Similarly, a protein signature from EVs that related to best treatment response was found, which included FR-alpha, TLR 3, TRAIL and FASLG. Several of the markers in the PFS or best treatment response signatures were also identified by a machine learning classification algorithm. In conclusion, protein profiling of EVs isolated from plasma of mUC patients shows a potential to identify protein signatures that may associate with PFS and/or treatment response.

Multiplex immune protein profiling of fine-needle aspirates from patients with non-small-cell lung cancer reveals signatures associated with PD-L1 expression and tumor stage.

Biomarker signatures identified through minimally invasive procedures already at diagnosis of non-small-cell lung cancer (NSCLC) could help to guide treatment with immune checkpoint inhibitors (ICI). Here, we performed multiplex profiling of immune-related proteins in fine-needle aspirate (FNA) samples of thoracic lesions from patients with NSCLC to assess PD-L1 expression and identify related protein signatures. Transthoracic FNA samples from 14 patients were subjected to multiplex antibody-based profiling by proximity extension assay (PEA). PEA profiling employed protein panels relevant to immune and tumor signaling and was followed by Qlucore® Omics Explorer analysis. All lesions analyzed were NSCLC adenocarcinomas, and PEA profiles could be used to monitor 163 proteins in all but one sample. Multiple key immune signaling components (including CD73, granzyme A, and chemokines CCL3 and CCL23) were identified and expression of several of these proteins (e.g., CCL3 and CCL23) correlated to PD-L1 expression. We also found EphA2, a marker previously linked to inferior NSCLC prognosis, to correlate to PD-L1 expression. Our identified protein signatures related to stage included, among others, CXCL10 and IL12RB1. We conclude that transthoracic FNA allows for extensive immune and tumor protein profiling with assessment of putative biomarkers of important for ICI treatment selection in NSCLC.

Super-resolution microscopy can identify specific protein distribution patterns in platelets incubated with cancer cells.

Protein contents in platelets are frequently changed upon tumor development and metastasis. However, how cancer cells can influence protein-selective redistribution and release within platelets, thereby promoting tumor development, remains largely elusive. With fluorescence-based super-resolution stimulated emission depletion (STED) imaging we reveal how specific proteins, implicated in tumor progression and metastasis, re-distribute within platelets, when subject to soluble activators (thrombin, adenosine diphosphate and thromboxane A2), and when incubated with cancer (MCF-7, MDA-MB-231, EFO21) or non-cancer cells (184A1, MCF10A). Upon cancer cell incubation, the cell-adhesion protein P-selectin was found to re-distribute into circular nano-structures, consistent with accumulation into the membrane of protein-storing alpha-granules within the platelets. These changes were to a significantly lesser extent, if at all, found in platelets incubated with normal cells, or in platelets subject to soluble platelet activators. From these patterns, we developed a classification procedure, whereby platelets exposed to cancer cells, to non-cancer cells, soluble activators, as well as non-activated platelets all could be identified in an automatic, objective manner. We demonstrate that STED imaging, in contrast to electron and confocal microscopy, has the necessary spatial resolution and labelling efficiency to identify protein distribution patterns in platelets and can resolve how they specifically change upon different activations. Combined with image analyses of specific protein distribution patterns within the platelets, STED imaging can thus have a role in future platelet-based cancer diagnostics and therapeutic monitoring. The presented approach can also bring further clarity into fundamental mechanisms for cancer cell-platelet interactions, and into non-contact cell-to-cell interactions in general.

Protein profiling of fine-needle aspirates reveals subtype-associated immune signatures and involvement of chemokines in breast cancer.

There are increasing demands for informative cancer biomarkers, accessible via minimally invasive procedures, both for initial diagnostics and for follow-up of personalized cancer therapy, including immunotherapy. Fine-needle aspiration (FNA) biopsy provides ready access to relevant tissue samples; however, the minute amounts of sample require sensitive multiplex molecular analysis to be of clinical biomarker utility. We have applied proximity extension assays (PEA) to analyze 167 proteins in FNA samples from patients with breast cancer (BC; n = 25) and benign lesions (n = 32). We demonstrate that the FNA BC samples could be divided into two main clusters, characterized by differences in expression levels of the estrogen receptor (ER) and the proliferation marker Ki67. This clustering corresponded to some extent to established BC subtypes. Our analysis also revealed several proteins whose expression levels differed between BC and benign lesions (e.g., CA9, GZMB, IL-6, VEGFA, CXCL11, PDL1, and PCD1), as well as several chemokines correlating with ER and Ki67 status (e.g., CCL4, CCL8, CCL20, CXCL8, CXCL9, and CXCL17). Finally, we also identified three signatures that could predict Ki67 status, ER status, and tumor grade, respectively, based on a small subset of proteins, which was dominated by chemokines. To our knowledge, expression profiles of CCL13 in benign lesions and BC have not previously been described but were shown herein to correlate with proliferation (P = 0.00095), suggesting a role in advanced BC. Given the broad functional range of the proteins analyzed, immune-related proteins were overrepresented among the observed alterations. Our pilot study supports the emerging role of chemokines in BC progression. Due to the minimally traumatic sampling and clinically important molecular information for therapeutic decisions, this methodology is promising for future immunoscoring and monitoring of treatment efficacy in BC.

A fine-needle aspiration-based protein signature discriminates benign from malignant breast lesions.

There are increasing demands for informative cancer biomarkers, accessible via minimally invasive procedures, both for initial diagnostics and to follow-up personalized cancer therapy. Fine-needle aspiration (FNA) biopsy provides ready access to relevant tissues; however, the minute sample amounts require sensitive multiplex molecular analysis to achieve clinical utility. We have applied proximity extension assays (PEA) and NanoString (NS) technology for analyses of proteins and of RNA, respectively, in FNA samples. Using samples from patients with breast cancer (BC, n = 25) or benign lesions (n = 33), we demonstrate that these FNA-based molecular analyses (a) can offer high sensitivity and reproducibility, (b) may provide correct diagnosis in shorter time and at a lower cost than current practice, (c) correlate with results from routine analysis (i.e., benchmarking against immunohistochemistry tests for ER, PR, HER2, and Ki67), and (d) may also help identify new markers related to immunotherapy. A specific 11-protein signature, including FGF binding protein 1, decorin, and furin, distinguished all cancer patient samples from all benign lesions in our main cohort and in smaller replication cohort. Due to the minimally traumatic sampling and rich molecular information, this combined proteomics and transcriptomic methodology is promising for diagnostics and evaluation of treatment efficacy in BC.

Protein Expression in Tonsillar and Base of Tongue Cancer and in Relation to Human Papillomavirus (HPV) and Clinical Outcome.

Human papillomavirus (HPV) is a major etiological factor for tonsillar and the base of tongue cancer (TSCC/BOTSCC). HPV-positive and HPV-negative TSCC/BOTSCC present major differences in mutations, mRNA expression and clinical outcome. Earlier protein studies on TSCC/BOTSCC have mainly analyzed individual proteins. Here, the aim was to compare a larger set of cancer and immune related proteins in HPV-positive and HPV-negative TSCC/BOTSCC in relation to normal tissue, presence of HPV, and clinical outcome. Fresh frozen tissue from 42 HPV-positive and 17 HPV-negative TSCC/BOTSCC, and corresponding normal samples, were analyzed for expression of 167 proteins using two Olink multiplex immunoassays. Major differences in protein expression between TSCC/BOTSCC and normal tissue were identified, especially in chemo- and cytokines. Moreover, 34 proteins, mainly immunoregulatory proteins and chemokines, were differently expressed in HPV-positive vs HPV-negative TSCC/BOTSCC. Several proteins were potentially related to clinical outcome for HPV-positive or HPV-negative tumors. For HPV-positive tumors, these were mostly related to angiogenesis and hypoxia. Correlation with clinical outcome of one of these, VEGFA, was validated by immunohistochemistry. Differences in immune related proteins between HPV-positive and HPV-negative TSCC/BOTSCC reflect the stronger activity of the immune defense in the former. Angiogenesis related proteins might serve as potential targets for therapy in HPV-positive TSCC/BOTSCC.

Platelet protein biomarker panel for ovarian cancer diagnosis.

BACKGROUND: Platelets support cancer growth and spread making platelet proteins candidates in the search for biomarkers. METHODS: Two-dimensional (2D) gel electrophoresis, Partial Least Squares Discriminant Analysis (PLS-DA), Western blot, DigiWest. RESULTS: PLS-DA of platelet protein expression in 2D gels suggested differences between the International Federation of Gynaecology and Obstetrics (FIGO) stages III-IV of ovarian cancer, compared to benign adnexal lesions with a sensitivity of 96% and a specificity of 88%. A PLS-DA-based model correctly predicted 7 out of 8 cases of FIGO stages I-II of ovarian cancer after verification by western blot. Receiver-operator curve (ROC) analysis indicated a sensitivity of 83% and specificity of 76% at cut-off >0.5 (area under the curve (AUC) = 0.831, p < 0.0001) for detecting these cases. Validation on an independent set of samples by DigiWest with PLS-DA differentiated benign adnexal lesions and ovarian cancer, FIGO stages III-IV, with a sensitivity of 70% and a specificity of 83%. CONCLUSION: We identified a group of platelet protein biomarker candidates that can quantify the differential expression between ovarian cancer cases as compared to benign adnexal lesions.

Protein levels of clusterin and glutathione synthetase in platelets allow for early detection of colorectal cancer.

Colorectal cancer (CRC) is one of the most frequent malignancies in the Western world. Early tumor detection and intervention are important determinants on CRC patient survival. During early tumor proliferation, dissemination and angiogenesis, platelets store and segregate proteins actively and selectively. Hence, the platelet proteome is a potential source of biomarkers denoting early malignancy. By comparing protein profiles of platelets between healthy volunteers (n = 12) and patients with early- (n = 7) and late-stage (n = 5) CRCs using multiplex fluorescence two-dimensional gel electrophoresis (2D-DIGE), we aimed at identifying differentially regulated proteins within platelets. By inter-group comparisons, 94 differentially expressed protein spots were detected (p < 0.05) between healthy controls and patients with early- and late-stage CRCs and revealed distinct separations between all three groups in principal component analyses. 54 proteins of interest were identified by mass spectrometry and resulted in high-ranked Ingenuity Pathway Analysis networks associated with Cellular function and maintenance, Cellular assembly and organization, Developmental disorder and Organismal injury and abnormalities (p < 0.0001 to p = 0.0495). Target proteins were validated by multiplex fluorescence-based Western blot analyses using an additional, independent cohort of platelet protein samples [healthy controls (n = 15), early-stage CRCs (n = 15), late-stage CRCs (n = 15)]. Two proteins-clusterin and glutathione synthetase (GSH-S)-featured high impact and were subsequently validated in this independent clinical cohort distinguishing healthy controls from patients with early- and late-stage CRCs. Thus, the potential of clusterin and GSH-S as platelet biomarkers for early detection of CRC could improve existing screening modalities in clinical application and should be confirmed in a prospective multicenter trial.

Core-needle biopsy of breast cancer is associated with a higher rate of distant metastases 5 to 15 years after diagnosis than FNA biopsy.

BACKGROUND: The literature offers discordant results regarding whether diagnostic biopsy is associated with the dissemination of cancer cells, resulting in local and/or distant metastasis. The long-term outcomes of patients with breast cancer were compared between those who were diagnosed using either fine-needle aspiration biopsy (FNAB) or core-needle biopsy (CNB) during 2 decades: the 1970s and 1990s. METHODS: In the 1970s, the only diagnostic needle biopsy method used for breast cancer in Sweden was FNAB. CNB was introduced 1989 and became established in Stockholm Gotland County in the early 1990s. The authors compared the clinical outcomes of patients diagnosed using FNAB from 1971 to 1976 (n = 354) versus those of patients diagnosed using CNB from 1991 to 1995 (n = 1729). Adjusting for differences in various treatment modalities, mammography screening, tumor size, DNA ploidy, and patient age between the 2 decades, 2 strictly matched samples representing FNAB (n = 181) and CNB (n = 203) were selected for a 15-year follow-up study. RESULTS: In a comparison of the rates of distant metastasis in the strictly matched patient groups from the FNAB and CNB cohorts, significantly higher rates of late-appearing (5-15 years after diagnosis) distant metastasis were observed among the patients who were diagnosed on CNB compared with those who were diagnosed on FNAB. No significant difference in local metastasis was observed between the 2 groups. CONCLUSIONS: At 5 to 15 years after diagnosis of the primary tumor, CNB-diagnosed patients had significantly higher rates of distant metastases than FNAB-diagnosed patients. Cancer Cytopathol 2017;125:748-56. © 2017 American Cancer Society.

Artemin-GFRα3 interactions partially contribute to acute inflammatory hypersensitivity.

The expression of artemin (ARTN), a glial cell line-derived neurotrophic factor (GDNF) family ligand, increases in pre-clinical models of nociception and recent evidence suggests this growth factor may play a causative role in inflammatory pain mechanisms. The aim of this study was to demonstrate functional inhibition of ARTN with monoclonal antibodies and to determine whether ARTN neutralisation could reverse inflammatory pain in mice. We show that monoclonal antibodies with high affinity to ARTN, completely inhibit ARTN-induced Ret and ERK activation in a human neuroblastoma cell line, and block capsaicin-induced CGRP secretion from primary rat DRG cultures. In addition, administration of anti-ARTN antibodies to mice provides a transient, partial reversal (41%) of FCA-induced mechanical hypersensitivity. Anti-ARTN antibodies had no effect on hypersensitivity in response to partial nerve ligation in mice. These data suggest that ARTN-GFRα3 interactions partially mediate early stage nociceptive signalling following an inflammatory insult.

Multivariate meta-analysis of proteomics data from human prostate and colon tumours.

BACKGROUND: There is a vast need to find clinically applicable protein biomarkers as support in cancer diagnosis and tumour classification. In proteomics research, a number of methods can be used to obtain systemic information on protein and pathway level on cells and tissues. One fundamental tool in analysing protein expression has been two-dimensional gel electrophoresis (2DE). Several cancer 2DE studies have reported partially redundant lists of differently expressed proteins. To be able to further extract valuable information from existing 2DE data, the power of a multivariate meta-analysis will be evaluated in this work. RESULTS: We here demonstrate a multivariate meta-analysis of 2DE proteomics data from human prostate and colon tumours. We developed a bioinformatic workflow for identifying common patterns over two tumour types. This included dealing with pre-processing of data and handling of missing values followed by the development of a multivariate Partial Least Squares (PLS) model for prediction and variable selection. The variable selection was based on the variables performance in the PLS model in combination with stability in the validation. The PLS model development and variable selection was rigorously evaluated using a double cross-validation scheme. The most stable variables from a bootstrap validation gave a mean prediction success of 93% when predicting left out test sets on models discriminating between normal and tumour tissue, common for the two tumour types. The analysis conducted in this study identified 14 proteins with a common trend between the tumour types prostate and colon, i.e. the same expression profile between normal and tumour samples. CONCLUSIONS: The workflow for meta-analysis developed in this study enabled the finding of a common protein profile for two malign tumour types, which was not possible to identify when analysing the data sets separately.

Implementation of a protein profiling platform developed as an academic-pharmaceutical industry collaborative effort.

As much attention has devoted to the proteome research during the last few years, biomarker discovery has become an increasingly hot area, potentially enabling the development of new assays for diagnosis and prognosis of severe diseases. This is the field of research interest where efforts originating from both academic and industrial groups should jointly work on solutions. In this paper, we would like to demonstrate the fruitful combination of both research domains where the scientific crossroads sprout fresh ideas from the basic research domain and how these are refined and tethered to industrial standards. We will present an approach that is based on novel microfluidic devices, utilizing their benefits in processing small-volume samples. Our biomarker discovery strategy, built around this platform, involves optimized samples processing (based on SPE and sample enrichment) and fast MALDI-MS readout. The identification of novel biomarkers at low-abundance level has been achieved by the utilization of a miniaturized sample handling platform, which offers clean-up and enrichment of proteins in one step. Complete automation has been realized in the form of a unique robotic instrumentation that is able to extract and transfer 96 samples onto standard MALDI target plates with high throughput. The developed platform was operated with a 60 sample turnaround per hour allowing sensitivities in femtomol regions of medium- and low-abundant target proteins from clinical studies on samples of multiple sclerosis and gastroesophageal reflux disease. Several proteins have been identified as new biomarkers from cerebrospinal fluid and esophagus epithelial cells.

Proteomics in prostate cancer research.

The incidence of early prostate cancer (PCa) among middle-aged men has increased rapidly. For many of these men, curatively intended treatment does more harm than good. Established prognostic factors are tumor stage and grade. As a result of earlier detection a majority of patients now have nonpalpable tumors (T1c) of intermediate grade (Gleason score 6). Prostate specific antigen in serum in such cases is generally at a low level and not a reliable predictor of prognosis. Altogether there is an urgent need for adjunctive prognostic indicators. In the search for relevant tumor markers for improved patient selection an exploration of the proteome (the human proteins) could be fruitful. This paper critically reviews the use of 2-dimensional gel electrophoresis (2-DE) for proteome research. Additional steps such as image analysis and mass spectrometry are described. Techniques based on non-2-DE platforms: surface-enhanced laser desorption/ionization (SELDI), isotope coded affinity tags (ICAT) and array-based technologies are also summarized. Although labor-intensive and time-consuming, 2-DE is presently the most powerful method for analysis of cellular protein phenotype and may potentially reveal gene regulations that cannot be detected on a genetic level.

Correlation of protein expression, Gleason score and DNA ploidy in prostate cancer.

The prognosis of prostate cancer correlates with tumor differentiation. Gleason score and DNA ploidy are two prognostic factors that correlate with prognosis. We analyzed differences in protein expression in prostate cancer of high and low aggressiveness according to these measures. From 35 prostatectomy specimens, 29 cancer samples and 10 benign samples were harvested by scraping cells from cut surfaces. DNA ploidy was assessed by image cytometry. Protein preparations from cell suspensions were examined by 2-DE. Protein spots that differed quantitatively between sample groups were identified by MS fingerprinting of tryptic fragments and MS/MS sequence analysis. We found 39 protein spots with expression levels that were raised or lowered in correlation with Gleason score and/or DNA ploidy pattern (31 overexpressed in high-malignant cancer, 8 underexpressed). Of these, 30 were identified by MS. Among overexpressed proteins were heat-shock, structural and membrane proteins and enzymes involved in gene silencing, protein synthesis/degradation, mitochondrial protein import (metaxin 2), detoxification (GST-pi) and energy metabolism. Stroma-associated proteins were generally underexpressed. The protein expression of prostate cancer correlates with tumor differentiation. Potential prognostic markers may be found among proteins that are differentially expressed and the clinical value of these should be validated.

Frozen tissue biobanks. Tissue handling, cryopreservation, extraction, and use for proteomic analysis.

The potential and the limitations of protein analysis of tissue samples are surveyed. The complexity, concentration range and dynamics of the human proteome are reviewed, as is the effect of handling and cryopreservation. Protein extraction, solubilization, resolution and detection are discussed, in relation to the properties of the human proteome.

Evaluation of two sample preparation methods for prostate proteome analysis.

For laboratory techniques that require well-preserved proteins, such as 2-DE, fresh tissue must be harvested and processed as fast as possible to avoid proteolytic degradation. We describe a modified method for harvesting tissue from radical prostatectomy specimens for proteome analysis and compare it with the standard technique. Cells were scraped from cut surfaces of 11 prostate specimens. A fraction of the material was smeared on a glass slide and Giemsa stained for morphological control. The sample was collected in a medium with protease inhibitors, and the protein material was prepared for 2-DE. Filtering and Percoll centrifugation were omitted. Sample locations were noted on a specimen map. From the same area, a tissue block was harvested for comparison. The block was processed with the conventional technique including mechanical disintegration, filtering and Percoll centrifugation. Quality measures of 2-DE were similar with both methods. With the scrape sampling technique, control smears showed abundant epithelial cells and a cleaner background and processing was faster than with tissue block sampling. For proteomic analysis, the scrape sample technique has several advantages over the tissue block method.