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Additional method details, tables and figures to support text in the manuscript. Figure S.1 Protein yield from LCM of regions of interest. Figure S.2 Variations on data analysis in the Perseus software. Figure S.3 Incidence of Biochemical Recurrence in Sample Cohort for Immunohistochemistry. Figure S.4 Expression of significant proteins in 'normal' patient biopsy tissue. Table S1.1 Significantly changing proteins between G3 epithelia and stroma. Table S1.2 Significantly changing proteins between G4 epithelia and stroma. Table S.1.3 Significantly changing proteins between G3 and G4 epithelia Table S1.4 Significantly changing proteins between G3 and G4 Stroma

Full list of proteins identified from LC-MS/MS analysis of all tumour regions of interest

Prostate cancer is the second most common cancer in men worldwide. Gleason grading is an important predictor of prostate cancer outcomes and is influential in determining patient treatment options. Clinical decisions based on a Gleason score of 7 are difficult as the prognosis for individuals diagnosed with Gleason 4+3 cancer is much worse than for those diagnosed with Gleason 3+4 cancer. Laser capture microdissection (LCM) is a highly precise method to isolate specific cell populations or discrete microregions from tissues. This report undertook a detailed molecular characterization of the tumor microenvironment in prostate cancer to define the proteome in the epithelial and stromal regions from tumor foci of Gleason grades 3 and 4. Tissue regions of interest were isolated from several Gleason 3+3 and Gleason 4+4 tumors using telepathology to leverage specialized pathology expertise to support LCM. Over 2,000 proteins were identified following liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis of all regions of interest. Statistical analysis revealed significant differences in protein expression (>100 proteins) between Gleason 3 and Gleason 4 regions—in both stromal and epithelial compartments. A subset of these proteins has had prior strong association with prostate cancer, thereby providing evidence for the authenticity of the approach. Finally, validation of these proteins by immunohistochemistry has been obtained using an independent cohort of prostate cancer tumor specimens.Implications: This unbiased strategy provides a strong foundation for the development of biomarker protein panels with significant diagnostic and prognostic potential. Mol Cancer Res; 15(3); 281–93. ©2017 AACR.

SARS-CoV-2 infection in children results in a wide range of clinical outcomes. Paediatric Multisystem Inflammatory syndrome temporally associated with COVID-19(PIMS-TS) occurs weeks after a SARS-CoV-2 infection, and results in severe illness. This protocol describes a study to fully characterize the circulating proteome of children who have PIMS-TS, the proteome of healthy children who have previously been infected with SARS-CoV-2 and the proteome of febrile children with a confirmed invasive infection. Orthogonal proteomic techniques will be utilized to provide a deep proteomic characterization.

Heart failure (HF) screening strategies require biomarkers to predict disease manifestation to aid HF surveillance and management programmes. The aim of this study was to validate a previous proteomics discovery programme that identified Tetranectin as a potential HF biomarker candidate based on expression level changes in asymptomatic patients at future risk for HF development. The initial study consisted of 132 patients, comprising of HF (n = 40), no-HF controls (n = 60), and cardiac surgery patients (n = 32). Serum samples were quantified for circulating levels of Tetranectin and a panel of circulating fibro-inflammatory markers. Cardiac tissue served as a resource to investigate the relationship between cardiac Tetranectin levels and fibrosis and inflammation within the myocardium. An independent cohort of 224 patients with or without HF was used to validate serum Tetranectin levels. Results show that circulating Tetranectin levels are significantly reduced in HF patients (p

BackgroundDuring the first wave of the SARS- CoV-2 pandemic in England, children accounted for just 1% of confirmed infections, had a milder clinical course and had much lower mortality than adults, a pattern similar to other international settings. The proportion of children in the UK infected with SARS-CoV-2 was unknown, with children less likely to attend symptomatic testing and issues with the sensitivity of real time reverse transcription PCR of oral/nasal swabs.ObjectivesTo measure the seroprevalence of SARS-CoV-2 antibodies in children of healthcare workers in the UK and to characterise the antibody response to SARS-CoV-2 infection and longitudinal antibody kinetics of SARS-CoV-2 infection.MethodsMulticentre observational prospective cohort study designed to determine seroprevalence of antibodies to SARS-CoV-2 in healthy children and report on symptoms experienced. Children of healthcare workers were recruited from five UK centres and underwent phlebotomy at three time points, beginning 16 April. There were follow up plasma/serum collections at two and six months after the original collection. Serum and/or plasma were tested for SARS-CoV-2 antibodies.Results1042 potential participants were screened for inclusion, with 35 excluded. Of the 1002 included 15 were excluded from analysis due to unsuccessful phlebotomy. Of the 992 included participants at the first time point, 68 had positive SARS-CoV-2 antibody tests, giving a seroprevalence of 6.9% (95% CI 5.4% to 8.6% n=992). Belfast had a significantly lower seroprevalence than all other sites at 0.9% (95% CI 0.2% to 3.3%, n=215, p

Cancer therapeutics-related cardiac dysfunction (CTRCD) has emerged as a major cause of morbidity and mortality in cancer survivors. Effective clinical management of CTRCD is impeded by a lack of sensitive diagnostic and prognostic strategies. Circulating molecular markers could potentially address this need as they are often indicative of cardiac stress before cardiac damage can be detected clinically. A growing understanding of the underlying physiological mechanisms for CTRCD has inspired research efforts to identify novel pathophysiologically relevant biomarkers that may also guide development of cardio-protective therapeutic approaches. The purpose of this review is to evaluate current circulating biomarkers of cardiac stress and their potential role in diagnosis and management of CTRCD. We also discuss some emerging avenues for CTRCD-focused biomarker investigations.

Following the introduction of routine Prostate Specific Antigen (PSA) screening in the early 1990′s, Prostate Cancer (PCa) is often detected at an early stage. There are also a growing number of treatment options available and so the associated mortality rate is generally low. However, PCa is an extremely complex and heterogenous disease and many patients suffer disease recurrence following initial therapy. Disease recurrence commonly results in metastasis and metastatic PCa has an average survival rate of just 3–5 years. A significant problem in the clinical management of PCa is being able to differentiate between patients who will respond to standard therapies and those who may benefit from more aggressive intervention at an earlier stage. It is also acknowledged that for many men the disease is not life threatenting. Hence, there is a growing desire to identify patients who can be spared the significant side effects associated with PCa treatment until such time (if ever) their disease progresses to the point where treatment is required. To these important clinical needs, current biomarkers and clinical methods for patient stratification and personlised treatment are insufficient. This review provides a comprehensive overview of the complexities of PCa pathology and disease management. In this context it is possible to review current biomarkers and proteomic technologies that will support development of biomarker-driven decision tools to meet current important clinical needs. With such an in-depth understanding of disease pathology, the development of novel clinical biomarkers can proceed in an efficient and effective manner, such that they have a better chance of improving patient outcomes.

Introduction Cardiac arrhythmia is strongly linked with heart failure (HF) and a primary cause of stroke. The condition affects around 37,000 people in Northern Ireland although it is estimated that many thousands more remain undiagnosed. It is important to be able to diagnose cardiac arrhythmia early, so that appropriate interventions can be made to reduce risk of subsequent stroke or HF. Currently, diagnosis and management of cardiac arrhythmia is reliant on assessment of clinical risk factors, however, routine monitoring of circulating biomarkers would significantly improve accuracy for prediction of arrhythmia and associated adverse events. The aim of this study was to (i) identify protein biomarkers, which can predict cardiac arrhythmia and (ii) identify protein biomarkers that are predictive of HF in patients with arrhythmia. Methods Multiple Reaction Monitoring mass spectrometry-based assays were developed for measurement of a selection of candidate protein biomarkers of cardiovascular injury. Assays were developed using nanoflow reverse phase C18 chromatographic ChipCube based separation, coupled to an Agilent 6460 triple quadrupole mass spectrometer. Optimised MRM assays were applied, in a sample blinded manner, for analysis of a cohort of 410 serum samples. This included 112 patients with cardiac arrhythmia as well as matched controls without cardiac arrhythmia. Results MRM assays were established for measurement of 25 proteins. Individually, a number of the biomarker proteins show significant differential expression between patients with and without cardiac arrhythmia. An 11-protein biomarker model was identified, which was comparable to BNP in prediction of HF within the cardiac arrhythmia subset of patients (Protein panel AUC = 0.856 vs BNP AUC = 0.838). Combination of the 11 proteins with BNP notably enhanced the predictive capacity of BNP (AUC = 0.898). Conclusions/Implications Through this study, assays have been developed for robust, multiplexed measurement of 25 cardiovascular disease-associated proteins in patient serum samples. A number of proteins were identified, which show significant expression changes in association with cardiac arrhythmia and will be further explored. Importantly, a statistical model revealed a panel of 11 proteins, which can predict HF in patients with cardiac arrhythmia, with comparable accuracy to BNP. This panel will need to be further validated in independent patient cohorts.

BackgroundStudies based on molecular testing of oral/nasal swabs underestimate SARS-CoV-2 infection due to issues with test sensitivity and timing of testing. The objective of this study was to report the presence of SARS-CoV-2 antibodies, consistent with previous infection, and to report the symptomatology of infection in children.DesignThis multicentre observational cohort study, conducted between 16th April – 3rd July 2020 at 5 UK sites, aimed to recruit 900 children aged 2 to 15 years of age. Participants provided blood samples for SARS-CoV-2 antibody testing and data were gathered regarding unwell contacts and symptoms.Results1007 participants were enrolled, and 992 were included in the final analysis. The median age of participants was 10·1 years. There were 68 (6.9%) participants with positive SARS-CoV-2 antibody tests indicative of previous SARS-CoV-2 infection. Of these, 34/68 (50%) reported no symptoms. The presence of antibodies and the mean antibody titre was not influenced by age. Following multivariate analysis 4 independent variables were identified as significantly associated with SARS-CoV-2 infection. These were: known infected household contact; fatigue; gastrointestinal symptoms; and changes in sense of smell or taste.DiscussionIn this study children demonstrated similar antibody titres in response to SARS-CoV-2 irrespective of age. The symptoms of SARS-CoV-2 infection in children were subtle but of those reported, fatigue, gastrointestinal symptoms and changes in sense of smell or taste were most strongly associated with antibody positivity.RegistrationThis study was registered at https://www.clinicaltrials.gov (trial registration: NCT04347408) on the 15/04/2020.

Background Studies based on molecular testing of oral/nasal swabs underestimate SARS-CoV-2 infection due to issues with test sensitivity, test timing and selection bias. The objective of this study was to report the presence of SARS-CoV-2 antibodies, consistent with previous infection. Design This multicentre observational cohort study, conducted between 16 April to 3 July 2020 at 5 UK sites, recruited children of healthcare workers, aged 2–15 years. Participants provided blood samples for SARS-CoV-2 antibody testing and data were gathered regarding unwell contacts and symptoms. Results 1007 participants were enrolled, and 992 were included in the final analysis. The median age of participants was 10·1 years. There were 68 (6.9%) participants with positive SARS-CoV-2 antibody tests indicative of previous SARS-CoV-2 infection. Of these, 34/68 (50%) reported no symptoms prior to testing. The presence of antibodies and the mean antibody titre was not influenced by age. Following multivariable analysis four independent variables were identified as significantly associated with SARS-CoV-2 seropositivity: known infected household contact OR=10.9 (95% CI 6.1 to 19.6); fatigue OR=16.8 (95% CI 5.5 to 51.9); gastrointestinal symptoms OR=6.6 (95% CI 3.0 to 13.8); and changes in sense of smell or taste OR=10.0 (95% CI 2.4 to 11.4). Discussion Children demonstrated similar antibody titres in response to SARS-CoV-2 irrespective of age. Fatigue, gastrointestinal symptoms and changes in sense of smell or taste were the symptoms most strongly associated with SARS-CoV-2 antibody positivity. Trial registration number NCT0434740., What proportion of children have antibodies against SARS CoV2 after the first wave of infetion in the UK? This study of healthy children of healthcare workers finds a similar proportion are antibody positive as adults (6%). Half of the positive children had no prior COVID symptoms fever, cough and vomiting/ diarrhoea occurred in most of the symptomatic children.

Background Advances in cancer therapy have significantly improved long term survival rates of those with breast cancer. Concurrently, chemotherapy-induced cardiac dysfunction is receiving increased attention in breast cancer survivors. Reduced left ventricular systolic function related to cancer therapies has recently been designated cancer therapeutics-related cardiac dysfunction (CTRCD). The addition of Trastuzumab to Epirubicin treatment has been shown to slow progression of disease, reduce mortality and extend duration of survival in patients with HER2+ Breast Cancer. However, both drugs have off target cardiotoxic effects. Currently echocardiography is the standard diagnostic test for detecting left ventricular systolic dysfunction in patients receiving these agents, but often becomes abnormal only when significant irreversible cardiac damage has occurred. There is an emerging need for blood-based biomarkers to aid in diagnosing subclinical cardiac dysfunction and to stratify those at risk prior to therapy. Methods AC16 cardiomyocytes were treated with Epirubicin (26ug/ml) and Trastuzumab (150ug/ml), both together and in monotherapy, over 10hr and 26hr studies. Cell viability was assessed via MTT cell viability assay. Protein and gene expression of Troponin I and BNP were assessed via western blot analysis and RT-PCR. Western blot analysis and fluorescent microscopy staining of oxidative stress markers was also carried out to investigate potential mechanisms of cardiac damage. Results Morphological changes occurred in all cells treated over 26hrs, particularly with combined treatment. Cell viability decreased significantly compared to control in the combined treatment group over 26hrs (p 0.0126*). Troponin I expression also increased significantly in the combined treatment group compared to monotreatment with Epirubicin for the same timepoint (p 0.015). BNP levels significantly increased in cells treated with a combination of Epirubicin and Trastuzumab compared to Trastuzumab alone (p=0.023). Conclusion Combined treatment with Epirubicin and Trastuzumab produces significantly more cell damage than monotreatment with either therapy. Troponin I and BNP are biomarkers that should be explored as a diagnostic tool for prediction of subclinical CTRCD.

Brief introduction Almost half of all deaths in Europe are attributable to by Cardiovascular Disease (CVD). There is a critical unmet need for better biomarkers so that CVD can be diagnosed at an earlier stage and with greater accuracy. Mass spectrometry-based multiple reaction monitoring (MRM) allows for rapid, targeted measurement of multiple protein biomarkers via detection of ‘proteotypic’ peptide fragments. Such assays can be developed in blood samples, which is desirable for minimally-invasive, routine monitoring of cardiovascular health. The purpose of this study was to design a robust MRM-based assay for the simultaneous detection and measurement of a panel of 36 proteins, including 19 known and 17 novel protein biomarkers of CVD, in blood. The overall aim was to evaluate the potential clinical utility of this biomarker panel for prediction of heart failure in a cohort of 500 patients. Explanation of basic methods Proteotypic peptides for each of the 36 candidate biomarker proteins were identified using Skyline and Spectrum Mill PeptideSelector software. MRM assays were developed using nanoflow reverse phase C18 chromatographic ChipCube based separation, coupled to a 6460 triple quadrupole mass spectrometer. Patient samples and synthetic peptides were used to obtain reference MS/MS spectra for building high quality MRM assays. For initial verification of the candidate protein biomarker panel, the MRM assay was applied, in a sample blinded manner, to a cohort of 500 serum samples from patients with heart failure and age-matched non-heart failure controls with CVD risk-factors. Results MRM assays were established for 35 peptides, corresponding to 9 of the known candidate biomarker proteins and all 16 of the novel biomarkers (Table 1). Individually, a number of the biomarker proteins show differential expression between heart failure with preserved and reduced ejection fraction (Table 2). Combined measurement of all biomarker proteins was found to have greater predictive capacity for heart failure than the current gold standard of B-type natriuretic peptide (BNP) alone. A statistical mode found that the biomarker panel, combined with BNP was capable of correctly predicting heart failure in blinded patient samples with accuracy of 82.19% AUC of 0.89 (Figure 1). Conclusions/Implications Through this study, assays have been developed for robust, multiplexed measurement of 26 CVD biomarker proteins in patient serum samples. Here it was observed that measurement of the full panel of CVD protein biomarkers offers more accurate prediction of heart failure than measurement of BNP alone. This panel will need to be further validated in independent patient cohorts. Conflict of interest None

Prostate cancer is the second most common cancer in men worldwide. Gleason grading is an important predictor of prostate cancer outcomes and is influential in determining patient treatment options. Clinical decisions based on a Gleason score of 7 are difficult as the prognosis for individuals diagnosed with Gleason 4+3 cancer is much worse than for those diagnosed with Gleason 3+4 cancer. Laser capture microdissection (LCM) is a highly precise method to isolate specific cell populations or discrete microregions from tissues. This report undertook a detailed molecular characterization of the tumor microenvironment in prostate cancer to define the proteome in the epithelial and stromal regions from tumor foci of Gleason grades 3 and 4. Tissue regions of interest were isolated from several Gleason 3+3 and Gleason 4+4 tumors using telepathology to leverage specialized pathology expertise to support LCM. Over 2,000 proteins were identified following liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis of all regions of interest. Statistical analysis revealed significant differences in protein expression (>100 proteins) between Gleason 3 and Gleason 4 regions—in both stromal and epithelial compartments. A subset of these proteins has had prior strong association with prostate cancer, thereby providing evidence for the authenticity of the approach. Finally, validation of these proteins by immunohistochemistry has been obtained using an independent cohort of prostate cancer tumor specimens. Implications: This unbiased strategy provides a strong foundation for the development of biomarker protein panels with significant diagnostic and prognostic potential. Mol Cancer Res; 15(3); 281–93. ©2017 AACR.

// Claire Tonry 1 , John Armstrong 2 and Stephen R. Pennington 1 1 Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin, Co. Dublin 2 St. Luke’s Hospital, Rathgar, Dublin, Co. Dublin Correspondence to: Claire Tonry, email: // Keywords : prostate cancer; tumour microenvironment; biomarkers; proteomics; mass spectrometry Received : June 13, 2016 Accepted : October 19, 2016 Published : January 12, 2017 Abstract In the developed world, prostate cancer is the most common cancer diagnosis in men. Although prostate cancer initially presents as a non life-threatening disease, 90% of patients will develop castration resistant prostate cancer (CRPC), which preludes distant metastasis and is largely accountable for prostate cancer associated deaths. This is because as yet, there are no viable molecular therapeutic targets for effective treatment of CRPC. It is now widely accepted that cancer cells can alter their metabolic profile during the course of tumourgenesis and metastasis such that they are able to survive in oxygen and nutrient-poor environments. This work was aimed towards gaining greater mechanistic understanding of how such ‘stresses’ in the tumour microenvironment impact on both androgen sensitive (LNCaP) and androgen independent (LNCaP-abl and LNCaP-abl-Hof) prostate cancer cell lines. Here we have applied technically robust and reproducible label-free liquid chromatography mass spectrometry analysis for comprehensive proteomic profiling of prostate cancer cell lines under nutrient deficient (low glucose) conditions. This led to the identification of approximately 4,000 proteins - one of the largest protein datasets for prostate cancer cell lines established to date. The biological and clinical significance of proteins showing a significant change in expression as result of low glucose conditions was established. Novel, intuitive workflows were subsequently implemented to ensure the verification of selected proteins of interest in a robust, reproducible and high throughput manner. Overall, these data suggest that this strategy supports identification of protein biomarkers of prostate cancer progression and potential therapeutic targets for CRPC.

When compared with hormonal therapy alone, treatment with combined hormone and radiation therapy (CHRT) gives improved disease-specific survival outcomes for patients with prostate cancer; however, a significant number of CHRT patients still succumb to recurrent disease. The purpose of this study was to use longitudinal patient samples obtained as part of an ongoing noninterventional clinical trial (ICORG06-15) to identify and evaluate a potential serum protein signature of disease recurrence. Label-free LC-MS/MS based protein discovery was undertaken on depleted serum samples from CHRT patients who showed evidence of disease recurrence (n = 3) and time-matched patient controls (n = 3). A total of 104 proteins showed a significant change between these two groups. Multiple reaction monitoring (MRM) assays were designed for a subset of these proteins as part of a panel of putative prostate cancer biomarkers (41 proteins) for evaluation in longitudinal serum samples. These data revealed significant interpatient variability in individual protein expression between time of diagnosis, disease recurrence, and beyond and serve to highlight the importance of longitudinal patient samples for evaluating the use of candidate protein biomarkers in disease monitoring.

Introduction The need for biomarkers to identify cardiac dysfunction in patients with diabetes (DM) is becoming increasingly pressing due to the global rise in disease prevalence and reducing healthcare resources to detect and manage these complications. With the risk of heart failure being 2–5 fold greater in those with diabetes, early identification of cardiac dysfunction may facilitate more timely management and reduce or delay future heart failure development. The aim of this ongoing study is to identify serum protein and micro RNA (miRNA) biomarker signatures that can be used to diagnose asymptomatic left ventricular diastolic dysfunction (LVDD) in diabetic patients. Methods The biomarker discovery cohort consisted of a selected subset of 200 patients from within the STOP-HF population. Four pooled age- and gender-matched groups of 50 patients were analysed, with and without DM and with and without asymptomatic LVDD. LVDD was defined on echocardiography as left atrial volume index ≥34 ml/m2 and E’ Results The proteomics and miRNA discovery analysis identified over 70 potential biomarkers that were differentially expressed in patients with both diabetes and LVDD compared with the other three discovery groups. GO-Term enrichment analysis revealed a significant involvement of processes relating to inflammation, including Humoral immune response, Complement activation, and Acute inflammatory responses (q-values: 1.00 E-30, 1.00 E-30, 1.00 E-30 respectively). Conclusion Verification and validation of the diagnostic potential of these novel protein and miRNA biomarkers candidates may support future strategies for the early identification and monitoring of LVDD in diabetic populations. Furthermore, functional analysis and identification of disease relevance of these biomarkers could highlight new therapeutic targets, including novel anti-inflammatory approaches.

Biological samples of human and animal origin are utilized in research for many purposes and in a variety of scientific fields, including mass spectrometry-based proteomics. Various types of samples, including organs, tissues, cells, body fluids such as blood, plasma, cerebrospinal fluid, saliva and semen, can be collected from humans or animals and processed for proteomics analysis. Depending on the physiological state and sample origin, collected samples are used in research and diagnostics for different purposes. In mass spectrometry-based proteomics, body fluids and tissues are commonly used in discovery experiments to search for specific protein markers that can distinguish physiological from pathophysiological states, which in turn offer new diagnosis strategies and help developing new drugs to prevent disease more efficiently. Cell lines in combination with technologies such as Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) have broader application and are used frequently to investigate the mechanism of a disease or to investigate for the mechanism of a drug function. All of these are important components for defining the mechanisms of disease, discovering new pharmaceutical treatments and finally testing side effects of newly discovered drugs.

Biological samples of human and animal origin are utilized in research for many purposes and in a variety of scientific fields, including mass spectrometry-based proteomics. Various types of samples, including organs, tissues, cells, body fluids such as blood, plasma, cerebrospinal fluid, saliva and semen, can be collected from humans or animals and processed for proteomics analysis. Depending on the physiological state and sample origin, collected samples are used in research and diagnostics for different purposes. In mass spectrometry-based proteomics, body fluids and tissues are commonly used in discovery experiments to search for specific protein markers that can distinguish physiological from pathophysiological states, which in turn offer new diagnosis strategies and help developing new drugs to prevent disease more efficiently. Cell lines in combination with technologies such as Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) have broader application and are used frequently to investigate the mechanism of a disease or to investigate for the mechanism of a drug function. All of these are important components for defining the mechanisms of disease, discovering new pharmaceutical treatments and finally testing side effects of newly discovered drugs.

Prostate Cancer (PCa) is the second most commonly diagnosed cancer in men worldwide. Although increased expression of prostate-specific antigen (PSA) is an effective indicator for the recurrence of PCa, its intended use as a screening marker for PCa is of considerable controversy. Recent research efforts in the field of PCa biomarkers have focused on the identification of tissue and fluid-based biomarkers that would be better able to stratify those individuals diagnosed with PCa who (i) might best receive no treatment (active surveillance of the disease); (ii) would benefit from existing treatments; or (iii) those who are likely to succumb to disease recurrence and/or have aggressive disease. The growing demand for better prostate cancer biomarkers has coincided with the development of improved discovery and evaluation technologies for multiplexed measurement of proteins in bio-fluids and tissues. This review aims to (i) provide an overview of these technologies as well as describe some of the candidate PCa protein biomarkers that have been discovered using them; (ii) address some of the general limitations in the clinical evaluation and validation of protein biomarkers; and (iii) make recommendations for strategies that could be adopted to improve the successful development of protein biomarkers to deliver improvements in personalized PCa patient decision making.

Graphical abstract, Highlights ⿢ A systematic workflow for unbiased label-free LC⿿MS/MS analysis of laser capture microdissected material is presented. ⿢ This LCM proteomics workflow was applied to fresh frozen tissue sections from prostate cancer patients. ⿢ Expert annotation of regions of tumor for dissection from the sections of heterogenous tissue was undertaken by telepathology. ⿢ Requirements for sample loading to support reproducible semi-quantitative analysis of protein expression were determined. ⿢ To support tumor characterisation the LCM proteomics workflow was used to identify approximately 2000 proteins from tumor regions acquired from patient tissue sections., Laser capture microdissection (LCM) allows microscopic procurement of specific cell types from tissue sections. Here, we present an optimized workflow for coupling LCM to LC⿿MS/MS including: sectioning of tissue, a standard LCM workflow, protein digestion and advanced LC⿿MS/MS. Soluble proteins extracted from benign epithelial cells, their associated stroma, tumor epithelial cells and their associated stromal cells from a single patient tissue sample were digested and profiled using advanced LC⿿MS/MS. The correlation between technical replicates was R2 = 0.99 with a mean % CV of 9.55% ± 8.73. The correlation between sample replicates was R2 = 0.97 with a mean % CV of 13.83% ± 10.17. This represents a robust, systematic approach for profiling of the tumor microenvironment using LCM coupled to label-free LC⿿MS/MS.