Evidence against Stable Protein S-Nitrosylation as a Widespread Mechanism of Post-translational Regulation.

S-nitrosation, commonly referred to as S-nitrosylation, is widely regarded as a ubiquitous, stable post-translational modification that directly regulates many proteins. Such a widespread role would appear to be incompatible with the inherent lability of the S-nitroso bond, especially its propensity to rapidly react with thiols to generate disulfide bonds. As anticipated, we observed robust and widespread protein S-nitrosation after exposing cells to nitrosocysteine or lipopolysaccharide. Proteins detected using the ascorbate-dependent biotin switch method are typically interpreted to be directly regulated by S-nitrosation. However, these S-nitrosated proteins are shown to predominantly comprise transient intermediates leading to disulfide bond formation. These disulfides are likely to be the dominant end effectors resulting from elevations in nitrosating cellular nitric oxide species. We propose that S-nitrosation primarily serves as a transient intermediate leading to disulfide formation. Overall, we conclude that the current widely held perception that stable S-nitrosation directly regulates the function of many proteins is significantly incorrect.

Improved early detection of ovarian cancer using longitudinal multimarker models.

BACKGROUND: Ovarian cancer has a poor survival rate due to late diagnosis and improved methods are needed for its early detection. Our primary objective was to identify and incorporate additional biomarkers into longitudinal models to improve on the performance of CA125 as a first-line screening test for ovarian cancer. METHODS: This case-control study nested within UKCTOCS used 490 serial serum samples from 49 women later diagnosed with ovarian cancer and 31 control women who were cancer-free. Proteomics-based biomarker discovery was carried out using pooled samples and selected candidates, including those from the literature, assayed in all serial samples. Multimarker longitudinal models were derived and tested against CA125 for early detection of ovarian cancer. RESULTS: The best performing models, incorporating CA125, HE4, CHI3L1, PEBP4 and/or AGR2, provided 85.7% sensitivity at 95.4% specificity up to 1 year before diagnosis, significantly improving on CA125 alone. For Type II cases (mostly high-grade serous), models achieved 95.5% sensitivity at 95.4% specificity. Predictive values were elevated earlier than CA125, showing the potential of models to improve lead time. CONCLUSIONS: We have identified candidate biomarkers and tested longitudinal multimarker models that significantly improve on CA125 for early detection of ovarian cancer. These models now warrant independent validation.

Small extracellular vesicles secreted from human amniotic fluid mesenchymal stromal cells possess cardioprotective and promigratory potential.

Mesenchymal stromal cells (MSCs) exhibit antiapoptotic and proangiogenic functions in models of myocardial infarction which may be mediated by secreted small extracellular vesicles (sEVs). However, MSCs have frequently been harvested from aged or diseased patients, while the isolated sEVs often contain high levels of impurities. Here, we studied the cardioprotective and proangiogenic activities of size-exclusion chromatography-purified sEVs secreted from human foetal amniotic fluid stem cells (SS-hAFSCs), possessing superior functional potential to that of adult MSCs. We demonstrated for the first time that highly pure (up to 1.7 × 1010 particles/µg protein) and thoroughly characterised SS-hAFSC sEVs protect rat hearts from ischaemia-reperfusion injury in vivo when administered intravenously prior to reperfusion (38 ± 9% infarct size reduction, p < 0.05). SS-hAFSC sEVs did not protect isolated primary cardiomyocytes in models of simulated ischaemia-reperfusion injury in vitro, indicative of indirect cardioprotective effects. SS-hAFSC sEVs were not proangiogenic in vitro, although they markedly stimulated endothelial cell migration. Additionally, sEVs were entirely responsible for the promigratory effects of the medium conditioned by SS-hAFSC. Mechanistically, sEV-induced chemotaxis involved phosphatidylinositol 3-kinase (PI3K) signalling, as its pharmacological inhibition in treated endothelial cells reduced migration by 54 ± 7% (p < 0.001). Together, these data indicate that SS-hAFSC sEVs have multifactorial beneficial effects in a myocardial infarction setting.

Association between the cervicovaginal microbiome, BRCA1 mutation status, and risk of ovarian cancer: a case-control study.

BACKGROUND: Various factors-including age, family history, inflammation, reproductive factors, and tubal ligation-modulate the risk of ovarian cancer. In this study, our aim was to establish whether women with, or at risk of developing, ovarian cancer have an imbalanced cervicovaginal microbiome. METHODS: We did a case-control study in two sets of women aged 18-87 years in the Czech Republic, Germany, Italy, Norway, and the UK. The ovarian cancer set comprised women with epithelial ovarian cancer and controls (both healthy controls and those diagnosed with benign gynaecological conditions). The BRCA set comprised women with a BRCA1 mutation but without ovarian cancer and controls who were wild type for BRCA1 and BRCA2 (both healthy controls and those with benign gynaecological conditions). Cervicovaginal samples were gathered from all participants with the ThinPrep system and then underwent 16S rRNA gene sequencing. For each sample, we calculated the proportion of lactobacilli species (ie, Lactobacillus crispatus, Lactobacillus iners, Lactobacillus gasseri, and Lactobacillus jensenii), which are essential for the generation of a protective low vaginal pH, in the cervicovaginal microbiota. We grouped samples into those in which lactobacilli accounted for at least 50% of the species present (community type L) and those in which lactobacilli accounted for less than 50% of the species present (community type O). We assessed the adjusted association between BRCA1 status and ovarian cancer status and cervicovaginal microbiota community type, using a logistic regression model with a bias reduction method. FINDINGS: Participants were recruited between Jan 2, 2016, and July 21, 2018. The ovarian cancer set (n=360) comprised 176 women with epithelial ovarian cancer, 115 healthy controls and 69 controls with benign gynaecological conditions. The BRCA set (n=220) included 109 women with BRCA1 mutations, 97 healthy controls wild type for BRCA1 and BRCA2 and 14 controls with a benign gynaecological condition wild type for BRCA1 and BRCA2. On the basis of two-dimensional density plots, receiver-operating characteristic curve analysis, and age thresholds used previously, we divided the cohort into those younger than 50 years and those aged 50 years or older. In the ovarian cancer set, women aged 50 years or older had a higher prevalence of community type O microbiota (81 [61%] of 133 ovarian cancer cases and 84 [59%] of 142 healthy controls) than those younger than 50 years (23 [53%] of 43 cases and 12 [29%] of 42 controls). In the ovarian cancer set, women younger than 50 years with ovarian cancer had a significantly higher prevalence of community type O microbiota than did age-matched controls under a logistic regression model with bias correction (odds ratio [OR] 2·80 [95% CI 1·17-6·94]; p=0·020). In the BRCA set, women with BRCA1 mutations younger than 50 years were also more likely to have community type O microbiota than age-matched controls (OR 2·79 [95% CI 1·25-6·68]; p=0·012), after adjustment for pregnancy (ever). This risk was increased further if more than one first-degree family member was affected by any cancer (OR 5·26 [95% CI 1·83-15·30]; p=0·0022). In both sets, we noted that the younger the participants, the stronger the association between community type O microbiota and ovarian cancer or BRCA1 mutation status (eg, OR for community type O for cases aged <40 years in the ovarian cancer set 7·00 [95% CI 1·27-51·44], p=0·025; OR for community type O for BRCA1 mutation carriers aged <35 years in the BRCA set 4·40 [1·14-24·36], p=0·031). INTERPRETATION: The presence of ovarian cancer, or factors known to affect risk for the disease (ie, age and BRCA1 germline mutations), were significantly associated with having a community type O cervicovaginal microbiota. Whether re-instatement of a community type L microbiome by using, for example, vaginal suppositories containing live lactobacilli, would alter the microbiomial composition higher up in the female genital tract and in the fallopian tubes (the site of origin of high-grade serous ovarian cancer), and whether such changes could translate into a reduced incidence of ovarian cancer, needs to be investigated. FUNDING: EU Horizon 2020 Research and Innovation Programme, EU Horizon 2020 European Research Council Programme, and The Eve Appeal.

Discovery of non-invasive biomarkers for the diagnosis of endometriosis.

BACKGROUND: Endometriosis is a common gynaecological disorder affecting 5-10% of women of reproductive age who often experience chronic pelvic pain and infertility. Definitive diagnosis is through laparoscopy, exposing patients to potentially serious complications, and is often delayed. Non-invasive biomarkers are urgently required to accelerate diagnosis and for triaging potential patients for surgery. METHODS: This retrospective case control biomarker discovery and validation study used quantitative 2D-difference gel electrophoresis and tandem mass tagging-liquid chromatography-tandem mass spectrometry for protein expression profiling of eutopic and ectopic endometrial tissue samples collected from 28 cases of endometriosis and 18 control patients undergoing surgery for investigation of chronic pelvic pain without endometriosis or prophylactic surgery. Samples were further sub-grouped by menstrual cycle phase. Selected differentially expressed candidate markers (LUM, CPM, TNC, TPM2 and PAEP) were verified by ELISA in a set of 87 serum samples collected from the same and additional women. Previously reported biomarkers (CA125, sICAM1, FST, VEGF, MCP1, MIF and IL1R2) were also validated and diagnostic performance of markers and combinations established. RESULTS: Cycle phase and endometriosis-associated proteomic changes were identified in eutopic tissue from over 1400 identified gene products, yielding potential biomarker candidates. Bioinformatics analysis revealed enrichment of adhesion/extracellular matrix proteins and progesterone signalling. The best single marker for discriminating endometriosis from controls remained CA125 (AUC = 0.63), with the best cross-validated multimarker models improving the AUC to 0.71-0.81, depending upon menstrual cycle phase and control group. CONCLUSIONS: We have identified menstrual cycle- and endometriosis-associated protein changes linked to various cellular processes that are potential biomarkers and that provide insight into the biology of endometriosis. Our data indicate that the markers tested, whilst not useful alone, have improved diagnostic accuracy when used in combination and demonstrate menstrual cycle specificity. Tissue heterogeneity and blood contamination is likely to have hindered biomarker discovery, whilst a small sample size precludes accurate determination of performance by cycle phase. Independent validation of these biomarker panels in a larger cohort is however warranted, and if successful, they may have clinical utility in triaging patients for surgery.

Effects of ErbB2 Overexpression on the Proteome and ErbB Ligand-specific Phosphosignaling in Mammary Luminal Epithelial Cells.

Most breast cancers arise from luminal epithelial cells, and 25-30% of these tumors overexpress the ErbB2/HER2 receptor that correlates with disease progression and poor prognosis. The mechanisms of ErbB2 signaling and the effects of its overexpression are not fully understood. Herein, stable isotope labeling by amino acids in cell culture (SILAC), expression profiling, and phosphopeptide enrichment of a relevant, non-transformed, and immortalized human mammary luminal epithelial cell model were used to profile ErbB2-dependent differences in protein expression and phosphorylation events triggered via EGF receptor (EGF treatment) and ErbB3 (HRG1ß treatment) in the context of ErbB2 overexpression. Bioinformatics analysis was used to infer changes in cellular processes and signaling events. We demonstrate the complexity of the responses to oncogene expression and growth factor signaling, and we identify protein changes relevant to ErbB2-dependent altered cellular phenotype, in particular cell cycle progression and hyper-proliferation, reduced adhesion, and enhanced motility. Moreover, we define a novel mechanism by which ErbB signaling suppresses basal interferon signaling that would promote the survival and proliferation of mammary luminal epithelial cells. Numerous novel sites of growth factor-regulated phosphorylation were identified that were enhanced by ErbB2 overexpression, and we putatively link these to altered cell behavior and also highlight the importance of performing parallel protein expression profiling alongside phosphoproteomic analysis.

Surfactant Protein-D Is Essential for Immunity to Helminth Infection.

Pulmonary epithelial cell responses can enhance type 2 immunity and contribute to control of nematode infections. An important epithelial product is the collectin Surfactant Protein D (SP-D). We found that SP-D concentrations increased in the lung following Nippostrongylus brasiliensis infection; this increase was dependent on key components of the type 2 immune response. We carried out loss and gain of function studies of SP-D to establish if SP-D was required for optimal immunity to the parasite. N. brasiliensis infection of SP-D-/- mice resulted in profound impairment of host innate immunity and ability to resolve infection. Raising pulmonary SP-D levels prior to infection enhanced parasite expulsion and type 2 immune responses, including increased numbers of IL-13 producing type 2 innate lymphoid cells (ILC2), elevated expression of markers of alternative activation by alveolar macrophages (alvM) and increased production of the type 2 cytokines IL-4 and IL-13. Adoptive transfer of alvM from SP-D-treated parasite infected mice into naïve recipients enhanced immunity to N. brasiliensis. Protection was associated with selective binding by the SP-D carbohydrate recognition domain (CRD) to L4 parasites to enhance their killing by alvM. These findings are the first demonstration that the collectin SP-D is an essential component of host innate immunity to helminths.

Testing breast cancer serum biomarkers for early detection and prognosis in pre-diagnosis samples.

BACKGROUND: Breast cancer is a leading cause of morbidity and mortality worldwide. Although mammography screening is available, there is an ongoing interest in improved early detection and prognosis. Herein, we have analysed a combination of serological biomarkers in a case-control cohort of sera taken before diagnosis. METHODS: This nested case-control study within the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) used serum samples from 239 women who subsequently developed breast cancer and 239 matched cancer-free controls. Sera were screened by ELISA for 9 candidate markers. Univariate and multivariate analyses were performed to examine associations with clinico-pathological features and between case controls in different time groups before diagnosis. RESULTS: Significant associations with clinico-pathological features related to prognosis were found for several candidates (CA15-3, HSP90A and PAI-1). However, there were no consistent differences between cases and controls for any candidate in the lead up to diagnosis. Whilst combination models outperformed single markers, there was no increase in performance towards diagnosis. CONCLUSIONS: This study using unique pre-diagnosis samples shows that CA15-3, HSP90A and PAI-1 have potential as early prognostic markers and warrant further investigation. However, none of the candidates or combinations would be useful for screening.

EVERREST prospective study: a 6-year prospective study to define the clinical and biological characteristics of pregnancies affected by severe early onset fetal growth restriction.

BACKGROUND: Fetal growth restriction (FGR) is a serious obstetric condition for which there is currently no treatment. The EVERREST Prospective Study has been designed to characterise the natural history of pregnancies affected by severe early onset FGR and establish a well phenotyped bio-bank. The findings will provide up-to-date information for clinicians and patients and inform the design and conduct of the EVERREST Clinical Trial: a phase I/IIa trial to assess the safety and efficacy of maternal vascular endothelial growth factor (VEGF) gene therapy in severe early onset FGR. Data and samples from the EVERREST Prospective Study will be used to identify ultrasound and/or biochemical markers of prognosis in pregnancies with an estimated fetal weight (EFW) <3rd centile between 20+0 and 26+6 weeks of gestation. METHODS: This is a 6 year European multicentre prospective cohort study, recruiting women with a singleton pregnancy where the EFW is <3rd centile for gestational age and <600 g at 20+0 to 26+6 weeks of gestation. Detailed data are collected on: maternal history; antenatal, peripartum, and postnatal maternal complications; health economic impact; psychological impact; neonatal condition, progress and complications; and infant growth and neurodevelopment to 2 years of corrected age in surviving infants. Standardised longitudinal ultrasound measurements are performed, including: fetal biometry; uterine artery, umbilical artery, middle cerebral artery, and ductus venosus Doppler velocimetry; and uterine artery and umbilical vein volume blood flow. Samples of maternal blood and urine, amniotic fluid (if amniocentesis performed), placenta, umbilical cord blood, and placental bed (if caesarean delivery performed) are collected for bio-banking. An initial analysis of maternal blood samples at enrolment is planned to identify biochemical markers that are predictors for fetal or neonatal death. DISCUSSION: The findings of the EVERREST Prospective Study will support the development of a novel therapy for severe early onset FGR by describing in detail the natural history of the disease and by identifying women whose pregnancies have the poorest outcomes, in whom a therapy might be most advantageous. The findings will also enable better counselling of couples with affected pregnancies, and provide a valuable resource for future research into the causes of FGR. TRIAL REGISTRATION: NCT02097667 registered 31st October 2013.

Evidence of Altered Glycosylation of Serum Proteins Prior to Pancreatic Cancer Diagnosis.

Biomarkers for the early detection of pancreatic cancer are urgently needed. The aim of this pilot study was to evaluate changes in serum N-glycoproteins and their glycosylation status prior to clinical presentation of pancreatic cancer that may be potential biomarkers. Prediagnosis serum samples pooled according to five time-to-diagnosis groups and a non-cancer control pool were digested with trypsin, labelled with mass tags, and subjected to titanium dioxide capture, deglycosylation, and 2D-LC-MS/MS profiling. Unbound peptides were profiled in parallel. Across the sample groups, 703 proteins were quantified and 426 putative sites of N-glycosylation were identified with evidence of several novel sites. Altered proteins with biomarker potential were predominantly abundant inflammatory response, coagulation, and immune-related proteins. Whilst glycopeptide profiles largely paralleled those of their parent proteins, there was evidence of altered N-glycosylation site occupancy or sialic acid content prior to diagnosis for some proteins, most notably of immunoglobulin gamma chains. α-1-Antitrypsin was tested as a biomarker, but found not to complement carbohydrate antigen 19-9 (CA19-9) in early detection of cancer. In conclusion, we provide preliminary evidence of altered glycosylation of several serum proteins prior to pancreatic cancer diagnosis, warranting further investigation of these proteins as early biomarkers. These changes may be largely driven by inflammatory processes that occur in response to tumour formation and progression.

Advances in mass spectrometry-based cancer research and analysis: from cancer proteomics to clinical diagnostics.

INTRODUCTION: The last 20 years have seen significant improvements in the analytical capabilities of biological mass spectrometry (MS). Studies using advanced MS have resulted in new insights into cell biology and the etiology of diseases as well as its use in clinical applications. AREAS COVERED: This review discusses recent developments in MS-based technologies and their cancer-related applications with a focus on proteomics. It also discusses the issues around translating the research findings to the clinic and provides an outline of where the field is moving. Expert commentary: Proteomics has been problematic to adapt for the clinical setting. However, MS-based techniques continue to demonstrate potential in novel clinical uses beyond classical cancer proteomics.

Identification of novel candidate biomarkers of epithelial ovarian cancer by profiling the secretomes of three-dimensional genetic models of ovarian carcinogenesis.

Epithelial ovarian cancer (EOC) is still considered the most lethal gynecological malignancy and improved early detection of ovarian cancer is crucial to improving patient prognoses. To address this need, we tested whether candidate EOC biomarkers can be identified using three-dimensional (3D) in vitro models. We quantified changes in the abundance of secreted proteins in a 3D genetic model of early-stage EOC, generated by expressing CMYC and KRAS(G) (12) (V) in TERT-immortalized normal ovarian epithelial cells. Cellular proteins were labeled in live cells using stable isotopic amino acid analogues, and secreted proteins identified and quantified using liquid chromatography-tandem mass spectrometry. Thirty-seven and 55 proteins were differentially expressed by CMYC and CMYC+KRAS(G) (12) (V) expressing cells respectively (p < 0.05; >2-fold). We evaluated expression of the top candidate biomarkers in ∼210 primary EOCs: CHI3L1 and FKBP4 are both expressed by >96% of primary EOCs, and FASN and API5 are expressed by 86 and 75% of cases. High expression of CHI3L1 and FKBP4 was associated with worse patient survival (p = 0.042 and p = 0.002, respectively). Expression of LGALS3BP was positively associated with recurrence (p = 0.0001) and suboptimal debulking (p = 0.018) suggesting that these proteins may be novel prognostic biomarkers. Furthermore, within early stage tumours (I/II), high expression of API5, CHI3L1 and FASN was associated with high tumour grade (p = 3 × 10(-4) , p = 0.016, p = 0.010, respectively). We show in vitro cell biology models of early-stage cancer development can be used to identify novel candidate biomarkers for disease, and report the identification of proteins that represent novel potential candidate diagnostic and prognostic biomarkers for this highly lethal disease.

Functional proteomic analysis of long-term growth factor stimulation and receptor tyrosine kinase coactivation in Swiss 3T3 fibroblasts.

In Swiss 3T3 fibroblasts, long-term stimulation with PDGF, but not insulin-like growth factor 1 (IGF-1) or EGF, results in the establishment of an elongated migratory phenotype, characterized by the formation of retractile dendritic protrusions and absence of actin stress fibers and focal adhesion complexes. To identify receptor tyrosine kinase-specific reorganization of the Swiss 3T3 proteome during phenotypic differentiation, we compared changes in the pattern of protein synthesis and phosphorylation during long-term exposure to PDGF, IGF-1, EGF, and their combinations using 2DE-based proteomics after (35)S- and (33)P-metabolic labeling. One hundred and five differentially regulated proteins were identified by mass spectrometry and some of these extensively validated. PDGF stimulation produced the highest overall rate of protein synthesis at any given time and induced the most sustained phospho-signaling. Simultaneous activation with two or three of the growth factors revealed both synergistic and antagonistic effects on protein synthesis and expression levels with PDGF showing dominance over both IGF-1 and EGF in generating distinct proteome compositions. Using signaling pathway inhibitors, PI3K was identified as an early site for signal diversification, with sustained activity of the PI3K/AKT pathway critical for regulating late protein synthesis and phosphorylation of target proteins and required for maintaining the PDGF-dependent motile phenotype. Several proteins were identified with novel PI3K/Akt-dependent synthesis and phosphorylations including eEF2, PRS7, RACK-1, acidic calponin, NAP1L1, Hsp73, and fascin. The data also reveal induction/suppression of key F-actin and actomyosin regulators and chaperonins that enable PDGFR to direct the assembly of a motile cytoskeleton, despite simultaneous antagonistic signaling activities. Together, the study demonstrates that long-term exposure to different growth factors results in receptor tyrosine kinase-specific regulation of relatively small subproteomes, and implies that the strength and longevity of receptor tyrosine kinase-specific signals are critical in defining the composition and functional activity of the resulting proteome.

Identification of potential serum peptide biomarkers of biliary tract cancer using MALDI MS profiling.

BACKGROUND: The aim of this discovery study was the identification of peptide serum biomarkers for detecting biliary tract cancer (BTC) using samples from healthy volunteers and benign cases of biliary disease as control groups. This work was based on the hypothesis that cancer-specific exopeptidases exist and that their activities in serum can generate cancer-predictive peptide fragments from circulating proteins during coagulation. METHODS: This case control study used a semi-automated platform incorporating polypeptide extraction linked to matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) to profile 92 patient serum samples. Predictive models were generated to test a validation serum set from BTC cases and healthy volunteers. RESULTS: Several peptide peaks were found that could significantly differentiate BTC patients from healthy controls and benign biliary disease. A predictive model resulted in a sensitivity of 100% and a specificity of 93.8% in detecting BTC in the validation set, whilst another model gave a sensitivity of 79.5% and a specificity of 83.9% in discriminating BTC from benign biliary disease samples in the training set. Discriminatory peaks were identified by tandem MS as fragments of abundant clotting proteins. CONCLUSIONS: Serum MALDI MS peptide signatures can accurately discriminate patients with BTC from healthy volunteers.

Serum biomarker-based early detection of pancreatic ductal adenocarcinomas with ensemble learning.

BACKGROUND: Earlier detection of pancreatic ductal adenocarcinoma (PDAC) is key to improving patient outcomes, as it is mostly detected at advanced stages which are associated with poor survival. Developing non-invasive blood tests for early detection would be an important breakthrough. METHODS: The primary objective of the work presented here is to use a dataset that is prospectively collected, to quantify a set of cancer-associated proteins and construct multi-marker models with the capacity to predict PDAC years before diagnosis. The data used is part of a nested case-control study within the UK Collaborative Trial of Ovarian Cancer Screening and is comprised of 218 samples, collected from a total of 143 post-menopausal women who were diagnosed with pancreatic cancer within 70 months after sample collection, and 249 matched non-cancer controls. We develop a stacked ensemble modelling technique to achieve robustness in predictions and, therefore, improve performance in newly collected datasets. RESULTS: Here we show that with ensemble learning we can predict PDAC status with an AUC of 0.91 (95% CI 0.75-1.0), sensitivity of 92% (95% CI 0.54-1.0) at 90% specificity, up to 1 year prior to diagnosis, and at an AUC of 0.85 (95% CI 0.74-0.93) up to 2 years prior to diagnosis (sensitivity of 61%, 95% CI 0.17-0.83, at 90% specificity). CONCLUSIONS: The ensemble modelling strategy explored here outperforms considerably biomarker combinations cited in the literature. Further developments in the selection of classifiers balancing performance and heterogeneity should further enhance the predictive capacity of the method.

Pancreatic cancers are most frequently detected at an advanced stage. This limits treatment options and contributes to the dismal survival rates currently recorded. The development of new tests that could improve detection of early-stage disease is fundamental to improve outcomes. Here, we use advanced data analysis techniques to devise an early detection test for pancreatic cancer. We use data on markers in the blood from people enrolled on a screening trial. Our test correctly identifies as positive for pancreatic cancer 91% of the time up to 1 year prior to diagnosis, and 78% of the time up to 2 years prior to diagnosis. These results surpass previously reported tests and should encourage further evaluation of the test in different populations, to see whether it should be adopted in the clinic.

Quantitative profiling of serum samples using TMT protein labelling, fractionation and LC-MS/MS.

Blood-borne biomarkers are urgently required for the early detection, accurate diagnosis and prognosis of disease. Additionally, improved methods of profiling serum and plasma proteins for biomarker discovery efforts are needed. Herein, we report a quantitative method based on amino-group labelling of serum proteins (rather than peptides) with isobaric tandem mass tags (TMT) and incorporating immune-based depletion, gel-based and strong anion exchange separation of proteins prior to differential endoproteinase treatment and liquid chromatography tandem mass spectrometry. We report a generally higher level of quantitative coverage of the serum proteome compared to other peptide-based isobaric tagging approaches and show the potential of the method by applying it to a set of unique samples that pre-date the diagnosis of pancreatic cancer.

Blood levels of adiponectin and IL-1Ra distinguish type 3c from type 2 diabetes: Implications for earlier pancreatic cancer detection in new-onset diabetes.

BACKGROUND: Screening for pancreatic ductal adenocarcinoma (PDAC) in populations at high risk is recommended. Individuals with new-onset type 2 diabetes mellitus (NOD) are the largest high-risk group for PDAC. To facilitate screening, we sought biomarkers capable of stratifying NOD subjects into those with type 2 diabetes mellitus (T2DM) and those with the less prevalent PDAC-related diabetes (PDAC-DM), a form of type 3c DM commonly misdiagnosed as T2DM. METHODS: Using mass spectrometry- and immunoassay-based methodologies in a multi-stage analysis of independent sample sets (n=443 samples), blood levels of 264 proteins were considered using Ingenuity Pathway Analysis, literature review and targeted training and validation. FINDINGS: Of 30 candidate biomarkers evaluated in up to four independent patient sets, 12 showed statistically significant differences in levels between PDAC-DM and T2DM. The combination of adiponectin and interleukin-1 receptor antagonist (IL-1Ra) showed strong diagnostic potential, (AUC of 0.91; 95% CI: 0.84-0.99) for the distinction of T3cDM from T2DM. INTERPRETATION: Adiponectin and IL-1Ra warrant further consideration for use in screening for PDAC in individuals newly-diagnosed with T2DM. FUNDING: North West Cancer Research, UK, Cancer Research UK, Pancreatic Cancer Action, UK.

IMAC/TiO(2) enrich for peptide modifications other than phosphorylation: implications for chromatographic choice and database searching in phosphoproteomics.

Protein regulation by reversible phosphorylation is fundamental in nature, and large-scale phosphoproteomic analyses are becoming routine in proteomics laboratories. These analyses utilise phosphopeptide separation and enrichment techniques linked to LC-MS/MS. Herein, we report that IMAC and TiO(2) also enrich for non-phosphorylated modified peptides such as acetylated, deamidated and carbamylated peptides. Urea and digestion conditions commonly used in phosphoproteomic workflows are the likely sources of the induced modifications (deamidation and carbamylation) and can easily modify phosphopeptides. Including these variable modifications in database searches increased the total number of identified phosphopeptides by 15%. We also show that strong cation exchange fractionation provides poor resolution of phosphopeptides and actually enriches these alternatively modified peptides. By switching to reverse-phase chromatography, we show a significant improvement in the number of identified phosphopeptides. We recommend that the users of phosphopeptide enrichment strategies avoid using urea as a denaturant and that careful consideration is given to chromatographic conditions and the types of variable modifications used in database searches. Thus, the capacity of IMAC and TiO(2) to enrich phosphopeptides bearing modifications other than phosphorylation is a previously unappreciated property of these chromatographies with practical implications for the field of phosphoproteomics.

Major role of epidermal growth factor receptor and Src kinases in promoting oxidative stress-dependent loss of adhesion and apoptosis in epithelial cells.

A growing body of evidence suggests that reactive oxygen species are critical components of cell signaling pathways, in particular regulating protein phosphorylation events. Here, we show that oxidative stress in response to hydrogen peroxide treatment of human epithelial cells induces robust tyrosine phosphorylation on multiple proteins. Using an anti-phosphotyrosine purification and liquid chromatography-tandem mass spectrometry approach, we have identified many of these H(2)O(2)-induced tyrosine-phosphorylated proteins. Importantly, we show that epidermal growth factor receptor (EGFR) and Src are the primary upstream kinases mediating these events through their redox activation. The finding that many of the identified proteins have functions in cell adhesion, cell-cell junctions, and the actin cytoskeleton prompted us to examine stress-induced changes in adhesion. Immunofluorescence analysis showed that H(2)O(2) alters cell adhesion structures and the actin cytoskeleton causing loss of adhesion and apoptosis. Remarkably, these cellular changes could be attenuated by inhibition of EGFR and Src, identifying these kinases as targets to block oxidative damage. In summary, our data demonstrate that EGFR and Src together play a central role in oxidative stress-induced phosphorylation, which in turn results in loss of adhesion, morphological changes, and cell damage in epithelial cells. These data also provide a general model for redox signaling in other cell systems.

Lectin microarray profiling of metastatic breast cancers.

Altered protein glycosylation compared with the disease-free state is a universal feature of cancer cells. It has long been established that distinct glycan structures are associated with specific forms of cancer, but far less is known about the complete array of glycans associated with certain tumors. The cancer glycome has great potential as a source of biomarkers, but progress in this field has been hindered by a lack of available techniques for the elucidation of disease-associated glycosylation. In the present study, lectin microarrays consisting of 45 lectins with different binding preferences covering N- and O-linked glycans were coupled with evanescent-field activated fluorescent detection in the glycomic analysis of primary breast tumors and the serum and urine of patients with metastatic breast cancer. A single 50 µm section of a primary breast tumor or <1 µL of breast cancer patient serum or urine was sufficient to detect glycosylation alterations associated with metastatic breast cancer, as inferred from lectin-binding patterns. The high-throughput, sensitive and relatively simple nature of the simultaneous analysis of N- and O-linked glycosylation following minimal sample preparation and without the need for protein deglycosylation makes the lectin microarray analysis described a valuable tool for discovery phase glycomic profiling.