Lumican is overexpressed in lung adenocarcinoma pleural effusions.

Adenocarcinoma (AdC) is the most common lung cancer subtype and is often associated with pleural effusion (PE). Its poor prognosis is attributable to diagnostic delay and lack of effective treatments and there is a pressing need in discovering new biomarkers for early diagnosis or targeted therapies. To date, little is known about lung AdC proteome. We investigated protein expression of lung AdC in PE using the isobaric Tags for Relative and Absolute Quantification (iTRAQ) approach to identify possible novel diagnostic/prognostic biomarkers. This provided the identification of 109 of lung AdC-related proteins. We further analyzed lumican, one of the overexpressed proteins, in 88 resected lung AdCs and in 23 malignant PE cell-blocks (13 lung AdCs and 10 non-lung cancers) using immunohistochemistry. In AdC surgical samples, lumican expression was low in cancer cells, whereas it was strong and diffuse in the stroma surrounding the tumor. However, lumican expression was not associated with tumor grade, stage, and vascular/pleural invasion. None of the lung cancer cell-blocks showed lumican immunoreaction, whereas those of all the other tumors were strongly positive. Finally, immunoblotting analysis showed lumican expression in both cell lysate and conditioned medium of a fibroblast culture but not in those of A549 lung cancer cell line. PE is a valid source of information for proteomic analysis without many of the restrictions of plasma. The high lumican levels characterizing AdC PEs are probably due to its release by the fibroblasts surrounding the tumor. Despite the role of lumican in lung AdC is still elusive, it could be of diagnostic value

A Timely shift from shotgun to targeted proteomics and how it can be groundbreaking for cancer research

Funding The present work was funded by FUB/UnB, CNPq, FAP-DF, CAPES, and FINEP.Peer reviewedPublisher PD

Identification of Stage-Specific Breast Markers using Quantitative Proteomics

YesMatched healthy and diseased tissues from breast cancer patients were analyzed by quantitative proteomics. By comparing proteomic profiles of fibroadenoma (benign tumors, three patients), DCIS (noninvasive cancer, three patients), and invasive ductal carcinoma (four patients), we identified protein alterations that correlated with breast cancer progression. Three 8-plex iTRAQ experiments generated an average of 826 protein identifications, of which 402 were common. After excluding those originating from blood, 59 proteins were significantly changed in tumor compared with normal tissues, with the majority associated with invasive carcinomas. Bioinformatics analysis identified relationships between proteins in this subset including roles in redox regulation, lipid transport, protein folding, and proteasomal degradation, with a substantial number increased in expression due to Myc oncogene activation. Three target proteins, cofilin-1 and p23 (increased in invasive carcinoma) and membrane copper amine oxidase 3 (decreased in invasive carcinoma), were subjected to further validation. All three were observed in phenotype-specific breast cancer cell lines, normal (nontransformed) breast cell lines, and primary breast epithelial cells by Western blotting, but only cofilin-1 and p23 were detected by multiple reaction monitoring mass spectrometry analysis. All three proteins were detected by both analytical approaches in matched tissue biopsies emulating the response observed with proteomics analysis. Tissue microarray analysis (361 patients) indicated cofilin-1 staining positively correlating with tumor grade and p23 staining with ER positive status; both therefore merit further investigation as potential biomarkers.Cyprus Research Promotion Foundation, Yorkshire Cancer Researc

Mass spectrometry-based cancer biomarker discovery

The aim of the projects in this thesis was to identify biomarkers for clear cell renal cell carcinomas (ccRCC) and head and neck/oral squamous cell carcinoma (HNOSCC), using quantitative or qualitative proteomics. Comparative analysis of cancerous and normal tissue homogenates, or secretome analysis of cancer cell cultures using liquid chromatography - mass spectrometry (LC-MS) and immunoassay techniques, allowed the identification of different types of biomarkers: diagnostic or prognostic, biofluid- or tissue-based. Chapter 1 of this thesis provides general information on cancer and cancer biomarker discovery. Chapter 2 gives a brief introduction to the techniques used in this work and theories behind them. Chapters 3 - 5 are papers that resulted from the cancer biomarker discovery research performed here, and Chapter 6 contains the conclusions, the author's comments and the final remarks. The papers on the identification of biomarkers for different diseases, to which the author of this thesis contributed, are listed in the Appendix

Proteome Profiling of Breast Tumors by Gel Electrophoresis and Nanoscale Electrospray Ionization Mass Spectrometry

We have conducted proteome-wide analysis of fresh surgery specimens derived from breast cancer patients, using an approach that integrates size-based intact protein fractionation, nanoscale liquid separation of peptides, electrospray ion trap mass spectrometry, and bioinformatics. Through this approach, we have acquired a large amount of peptide fragmentation spectra from size-resolved fractions of the proteomes of several breast tumors, tissue peripheral to the tumor, and samples from patients undergoing noncancer surgery. Label-free quantitation was used to generate protein abundance maps for each proteome and perform comparative analyses. The mass spectrometry data revealed distinct qualitative and quantitative patterns distinguishing the tumors from healthy tissue as well as differences between metastatic and non-metastatic human breast cancers including many established and potential novel candidate protein biomarkers. Selected proteins were evaluated by Western blotting using tumors grouped according to histological grade, size, and receptor expression but differing in nodal status. Immunohistochemical analysis of a wide panel of breast tumors was conducted to assess expression in different types of breast cancers and the cellular distribution of the candidate proteins. These experiments provided further insights and an independent validation of the data obtained by mass spectrometry and revealed the potential of this approach for establishing multimodal markers for early metastasis, therapy outcomes, prognosis, and diagnosis in the future. © 2008 American Chemical Society

Tear fluid biomarkers in ocular and systemic disease: potential use for predictive, preventive and personalised medicine

In the field of predictive, preventive and personalised medicine, researchers are keen to identify novel and reliable ways to predict and diagnose disease, as well as to monitor patient response to therapeutic agents. In the last decade alone, the sensitivity of profiling technologies has undergone huge improvements in detection sensitivity, thus allowing quantification of minute samples, for example body fluids that were previously difficult to assay. As a consequence, there has been a huge increase in tear fluid investigation, predominantly in the field of ocular surface disease. As tears are a more accessible and less complex body fluid (than serum or plasma) and sampling is much less invasive, research is starting to focus on how disease processes affect the proteomic, lipidomic and metabolomic composition of the tear film. By determining compositional changes to tear profiles, crucial pathways in disease progression may be identified, allowing for more predictive and personalised therapy of the individual. This article will provide an overview of the various putative tear fluid biomarkers that have been identified to date, ranging from ocular surface disease and retinopathies to cancer and multiple sclerosis. Putative tear fluid biomarkers of ocular disorders, as well as the more recent field of systemic disease biomarkers, will be shown

Finding Needles in Haystacks: The Use of Quantitative Proteomics for the Early Detection of Colorectal Cancer

Colorectal cancer (CRC) is a common and treatable disease if diagnosed early. Current population screening programs are suboptimal, and consequently, there is a need for the development of new methodologies for early diagnosis of CRC. In the past 10 years, unprecedented technological advancements in the field of mass spectrometry (MS)-based proteomics have progressively increased the sophistication and utility of these investigations, leading to the draft mapping of the human proteome. These exciting studies have shaped our mechanistic understanding of the human genome and begun to provide us with a suite of novel biomarkers to predict the onset, progression and severity of many debilitating diseases. Thus, sophisticated MS workflows coupled with revolutionary protein quantification techniques hold promise for the field of MS-based plasma proteomics, particularly valuable in the context of early stage identification of curable CRC. However, within the last 40 years, no new plasma protein biomarkers of CRC have been translated into clinical practice. Here. we discuss the application of proteomic technologies within the field of CRC, highlighting contemporary MS-based plasma proteomic strategies that could be exploited to deliver on the promise of a panel of sensitive and specific plasma-based biomarkers with which to non-invasively detect early stage CRC

A caspase-3 'death-switch' in colorectal cancer cells for induced and synchronous tumor apoptosis in vitro and in vivo facilitates the development of minimally invasive cell death biomarkers

Novel anticancer drugs targeting key apoptosis regulators have been developed and are undergoing clinical trials. Pharmacodynamic biomarkers to define the optimum dose of drug that provokes tumor apoptosis are in demand; acquisition of longitudinal tumor biopsies is a significant challenge and minimally invasive biomarkers are required. Considering this, we have developed and validated a preclinical 'death-switch' model for the discovery of secreted biomarkers of tumour apoptosis using in vitro proteomics and in vivo evaluation of the novel imaging probe [ 18 F]ML-10 for non-invasive detection of apoptosis using positron emission tomography (PET). The 'death-switch' is a constitutively active mutant caspase-3 that is robustly induced by doxycycline to drive synchronous apoptosis in human colorectal cancer cells in vitro or grown as tumor xenografts. Deathswitch induction caused caspase-dependent apoptosis between 3 and 24 hours in vitro and regression of 'death-switched' xenografts occurred within 24 h correlating with the percentage of apoptotic cells in tumor and levels of an established cell death biomarker (cleaved cytokeratin-18) in the blood. We sought to define secreted biomarkers of tumor apoptosis from cultured cells using Discovery Isobaric Tag proteomics, which may provide candidates to validate in blood. Early after caspase-3 activation, levels of normally secreted proteins were decreased (e.g. Gelsolin and Midkine) and proteins including CD44 and High Mobility Group protein B1 (HMGB1) that were released into cell culture media in vitro were also identified in the bloodstream of mice bearing death-switched tumors. We also exemplify the utility of the death-switch model for the validation of apoptotic imaging probes using [ 18 F]ML-10, a PET tracer currently in clinical trials. Results showed increased tracer uptake of [ 18 F]ML-10 in tumours undergoing apoptosis, compared with matched tumour controls imaged in the same animal. Overall, the death-switch model represents a robust and versatile tool for the discovery and validation of apoptosis biomarkers. © 2013 Macmillan Publishers Limited. All rights reserved

Pinpointing new urinary biomarkers for bladder cancer detection and stage differentiation by label-free quantitative mass spectrometry

Bladder cancer is the fourth most common neoplasia in more developed countries and the seventh worldwide, in the male gender. On cost per patient, it is also one of the most expensive malignancies at patient level, because current diagnostics, follow-up, and treatment are not cost-effective. Cystoscopy, the regular method to diagnose bladder cancer, is invasive, causes pain and it has a low sensibility. Furthermore, it is used to monitor recurrent urothelial carcinomas, contributing significantly to rise bladder cancer costs. Therefore, new non-invasive and more reliable methods of diagnosis and prognosis are needed. Genetic mutations in bladder tumour cells, as well as tumour response from neighbouring cells and from the immune system, implicate protein expression and activation different from healthy people, therefore originating new features in the urine proteome. As urine is in direct contact with these tumour and urothelial cells, it is expected that changes in the bladder are reflected in the urine content. Therefore, the urinary proteome is an excellent biopsy for finding protein biomarkers of diagnosis and prognosis. This work has the primary goal of finding a urine-based panel of biomarkers of diagnosis and staging for bladder cancer. The Hospital São José provided urine samples from patients who had Bladder Cancer as follows: (i) non-muscle invasive stages Ta and T1, and (ii) muscle invasive T2-T4 (T2+) and (iii) from other patients used as controls. So far, five groups were formed as indicated next: (a) bladder cancer-Ta; (b) T1; (c) T2+ (d) volunteers with no urothelial conditions and (e) volunteers presenting lower urinary tract symptoms. The methodology selected to find the biomarkers was free-label quantification of peptides by High-Resolution Mass Spectrometry. To this end, the urine proteome was first separated and then digested using the Filter Aided Sample Preparation -FASP- method. The pools of peptides obtained were used to identify and quantify the proteins present in the urine samples. Then, using bioinformatics, data was interpreted, and two biomarker panels were obtained. The first panel consists of 35 proteins to diagnostic bladder cancer. The second panel consists of 76 proteins to stage bladder cancer