msproteomics sitereport: reporting DIA-MS phosphoproteomics experiments at site level with ease.

SUMMARY: Identification and quantification of phosphorylation sites are essential for biological interpretation of a phosphoproteomics experiment. For data independent acquisition mass spectrometry-based (DIA-MS) phosphoproteomics, extracting a site-level report from the output of current processing software is not straightforward as multiple peptides might contribute to a single site, multiple phosphorylation sites can occur on the same peptides, and protein isoforms complicate site specification. Currently only limited support is available from a commercial software package via a platform-specific solution with a rather simple site quantification method. Here we present sitereport, a software tool implemented in an extendable Python package called msproteomics to report phosphosites and phosphopeptides from a DIA-MS phosphoproteomics experiment with a proven quantification method called MaxLFQ. We demonstrate the use of sitereport for downstream data analysis at site level, allowing benchmarking different DIA-MS processing software tools. AVAILABILITY AND IMPLEMENTATION: sitereport is available as a command line tool in the Python package msproteomics, released under the Apache License 2.0 and available from the Python Package Index (PyPI) at https://pypi.org/project/msproteomics and GitHub at https://github.com/tvpham/msproteomics. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Secretome processing for proteomics: A methods comparison.

The cancer cell secretome comprises a treasure-trove for biomarkers since it reflects cross-talk between tumor cells and their surrounding environment with high detectability in biofluids. In this study, we evaluated six secretome sample processing workflows coupled to single-shot mass spectrometry: (1) Protein concentration by ultrafiltration with a molecular weight cut-off (MWCO) filter and sample preparation through in-gel digestion (IGD); (2) Acetone protein precipitation coupled to IGD; (3) MWCO filter-based protein concentration followed by to in-solution digestion (ISD); (4) Acetone protein precipitation coupled to ISD; (5) Direct ISD; (6) Secretome lyophilization and ISD. To this end, we assessed workflow triplicates in terms of total number of protein identifications, unique identifications, reproducibility of protein identification and quantification and detectability of small proteins with important functions in cancer biology such as cytokines, chemokines, and growth factors. Our findings revealed that acetone protein precipitation coupled to ISD outperformed the other methods in terms of the number of identified proteins (2246) and method reproducibility (correlation coefficient between replicates (r = 0.94, CV = 19%). Overall, especially small proteins such as those from the classes mentioned above were better identified using ISD workflows. Concluding, herein we report that secretome protein precipitation coupled to ISD is the method of choice for high-throughput secretome proteomics via single shot nanoLC-MS/MS.

Phosphoproteomic Analysis of FLCN Inactivation Highlights Differential Kinase Pathways and Regulatory TFEB Phosphoserines.

In Birt-Hogg-Dubé (BHD) syndrome, germline loss-of-function mutations in the Folliculin (FLCN) gene lead to an increased risk of renal cancer. To address how FLCN inactivation affects cellular kinase signaling pathways, we analyzed comprehensive phosphoproteomic profiles of FLCNPOS and FLCNNEG human renal tubular epithelial cells (RPTEC/TERT1). In total, 15,744 phosphorylated peptides were identified from 4329 phosphorylated proteins. INKA analysis revealed that FLCN loss alters the activity of numerous kinases, including tyrosine kinases EGFR, MET, and the Ephrin receptor subfamily (EPHA2 and EPHB1), as well their downstream targets MAPK1/3. Validation experiments in the BHD renal tumor cell line UOK257 confirmed that FLCN loss contributes to enhanced MAPK1/3 and downstream RPS6K1/3 signaling. The clinically available MAPK inhibitor Ulixertinib showed enhanced toxicity in FLCNNEG cells. Interestingly, FLCN inactivation induced the phosphorylation of PIK3CD (Tyr524) without altering the phosphorylation of canonical Akt1/Akt2/mTOR/EIF4EBP1 phosphosites. Also, we identified that FLCN inactivation resulted in dephosphorylation of TFEB Ser109, Ser114, and Ser122, which may be linked to increased oxidative stress levels in FLCNNEG cells. Together, our study highlights differential phosphorylation of specific kinases and substrates in FLCNNEG renal cells. This provides insight into BHD-associated renal tumorigenesis and may point to several novel candidates for targeted therapies.

VRK1 Regulates Sensitivity to Oxidative Stress by Altering Histone Epigenetic Modifications and the Nuclear Phosphoproteome in Tumor Cells.

The chromatin organization and its dynamic remodeling determine its accessibility and sensitivity to DNA damage oxidative stress, the main source of endogenous DNA damage. We studied the role of the VRK1 chromatin kinase in the response to oxidative stress. which alters the nuclear pattern of histone epigenetic modifications and phosphoproteome pathways. The early effect of oxidative stress on chromatin was studied by determining the levels of 8-oxoG lesions and the alteration of the epigenetic modification of histones. Oxidative stress caused an accumulation of 8-oxoG DNA lesions that were increased by VRK1 depletion, causing a significant accumulation of DNA strand breaks detected by labeling free 3'-DNA ends. In addition, oxidative stress altered the pattern of chromatin epigenetic marks and the nuclear phosphoproteome pathways that were impaired by VRK1 depletion. Oxidative stress induced the acetylation of H4K16ac and H3K9 and the loss of H3K4me3. The depletion of VRK1 altered all these modifications induced by oxidative stress and resulted in losses of H4K16ac and H3K9ac and increases in the H3K9me3 and H3K4me3 levels. All these changes were induced by the oxidative stress in the epigenetic pattern of histones and impaired by VRK1 depletion, indicating that VRK1 plays a major role in the functional reorganization of chromatin in the response to oxidative stress. The analysis of the nuclear phosphoproteome in response to oxidative stress detected an enrichment of the phosphorylated proteins associated with the chromosome organization and chromatin remodeling pathways, which were significantly decreased by VRK1 depletion. VRK1 depletion alters the histone epigenetic pattern and nuclear phosphoproteome pathways in response to oxidative stress. The enzymes performing post-translational epigenetic modifications are potential targets in synthetic lethality strategies for cancer therapies.

A transformer architecture for retention time prediction in liquid chromatography mass spectrometry-based proteomics.

Accurate retention time (RT) prediction is important for spectral library-based analysis in data-independent acquisition mass spectrometry-based proteomics. The deep learning approach has demonstrated superior performance over traditional machine learning methods for this purpose. The transformer architecture is a recent development in deep learning that delivers state-of-the-art performance in many fields such as natural language processing, computer vision, and biology. We assess the performance of the transformer architecture for RT prediction using datasets from five deep learning models Prosit, DeepDIA, AutoRT, DeepPhospho, and AlphaPeptDeep. The experimental results on holdout datasets and independent datasets exhibit state-of-the-art performance of the transformer architecture. The software and evaluation datasets are publicly available for future development in the field.

Atrial epicardial adipose tissue abundantly secretes myeloperoxidase and activates atrial fibroblasts in patients with atrial fibrillation.

BACKGROUND: Epicardial adipose tissue (EAT) secretome induces fibrosis. Fibrosis, primarily extracellular matrix (ECM) produced by fibroblasts, creates a substrate for atrial fibrillation (AF). Whether the EAT secretome from patients with AF activates human atrial fibroblasts and through which components, remains unexplored. RESEARCH AIMS: (a) To investigate if the EAT secretome from patients with versus without AF increases ECM production in atrial fibroblasts. (b) To identify profibrotic proteins and processes in the EAT secretome and EAT from patients with, who will develop (future onset), and without AF. METHODS: Atrial EAT was obtainded during thoracoscopic ablation (AF, n = 20), or open-heart surgery (future onset and non-AF, n = 35). ECM gene expression of human atrial fibroblasts exposed to the EAT secretome and the proteomes of EAT secretome and EAT were assessed in patients with and without AF. Myeloperoxidase and neutrophil extracellular traps (NETs) were assessed immunohistochemically in patients with paroxysmal, persistent, future onset, and those who remain free of AF (non-AF). RESULTS: The expression of COL1A1 and FN1 in fibroblasts exposed to secretome from patients with AF was 3.7 and 4.7 times higher than in patients without AF (p < 0.05). Myeloperoxidase was the most increased protein in the EAT secretome and EAT from patients with versus without AF (FC 18.07 and 21.57, p < 0.005), as was the gene-set neutrophil degranulation. Immunohistochemically, myeloperoxidase was highest in persistent (FC 13.3, p < 0.0001) and increased in future onset AF (FC 2.4, p = 0.02) versus non-AF. Myeloperoxidase aggregated subepicardially and around fibrofatty infiltrates. NETs were increased in patients with persistent versus non-AF (p = 0.03). CONCLUSION: In AF, the EAT secretome induces ECM gene expression in atrial fibroblasts and contains abundant myeloperoxidase. EAT myeloperoxidase was increased prior to AF onset, and both myeloperoxidase and NETs were highest in persistent AF, highlighting the role of EAT neutrophils in the pathophysiology of AF.

Inferring kinase activity from phosphoproteomic data: Tool comparison and recent applications.

Aberrant cellular signaling pathways are a hallmark of cancer and other diseases. One of the most important signaling mechanisms involves protein phosphorylation/dephosphorylation. Protein phosphorylation is catalyzed by protein kinases, and over 530 protein kinases have been identified in the human genome. Aberrant kinase activity is one of the drivers of tumorigenesis and cancer progression and results in altered phosphorylation abundance of downstream substrates. Upstream kinase activity can be inferred from the global collection of phosphorylated substrates. Mass spectrometry-based phosphoproteomic experiments nowadays routinely allow identification and quantitation of >10k phosphosites per biological sample. This substrate phosphorylation footprint can be used to infer upstream kinase activities using tools like Kinase Substrate Enrichment Analysis (KSEA), Posttranslational Modification Substrate Enrichment Analysis (PTM-SEA), and Integrative Inferred Kinase Activity Analysis (INKA). Since the topic of kinase activity inference is very active with many new approaches reported in the past 3 years, we would like to give an overview of the field. In this review, an inventory of kinase activity inference tools, their underlying algorithms, statistical frameworks, kinase-substrate databases, and user-friendliness is presented. The most widely-used tools are compared in-depth. Subsequently, recent applications of the tools are described focusing on clinical tissues and hematological samples. Two main application areas for kinase activity inference tools can be discerned. (1) Maximal biological insights can be obtained from large data sets with group comparisons using multiple complementary tools (e.g., PTM-SEA and KSEA or INKA). (2) In the oncology context where personalized treatment requires analysis of single samples, INKA for example, has emerged as tool that can prioritize actionable kinases for targeted inhibition.

Candidate biomarkers for treatment benefit from sunitinib in patients with advanced renal cell carcinoma using mass spectrometry-based (phospho)proteomics.

The tyrosine kinase inhibitor sunitinib is an effective first-line treatment for patients with advanced renal cell carcinoma (RCC). Hypothesizing that a functional read-out by mass spectrometry-based (phospho, p-)proteomics will identify predictive biomarkers for treatment outcome of sunitinib, tumor tissues of 26 RCC patients were analyzed. Eight patients had primary resistant (RES) and 18 sensitive (SENS) RCC. A 78 phosphosite signature (p < 0.05, fold-change > 2) was identified; 22 p-sites were upregulated in RES (unique in RES: BCAR3, NOP58, EIF4A2, GDI1) and 56 in SENS (35 unique). EIF4A1/EIF4A2 were differentially expressed in RES at the (p-)proteome and, in an independent cohort, transcriptome level. Inferred kinase activity of MAPK3 (p = 0.026) and EGFR (p = 0.045) as determined by INKA was higher in SENS. Posttranslational modifications signature enrichment analysis showed that different p-site-centric signatures were enriched (p < 0.05), of which FGF1 and prolactin pathways in RES and, in SENS, vanadate and thrombin treatment pathways, were most significant. In conclusion, the RCC (phospho)proteome revealed differential p-sites and kinase activities associated with sunitinib resistance and sensitivity. Independent validation is warranted to develop an assay for upfront identification of patients who are intrinsically resistant to sunitinib.

Epigenetic Modification of the von Willebrand Factor Promoter Drives Platelet Aggregation on the Pulmonary Endothelium in Chronic Thromboembolic Pulmonary Hypertension.

Rationale: von Willebrand factor (vWF) mediates platelet adhesion during thrombosis. While chronic thromboembolic pulmonary hypertension (CTEPH) is associated with increased plasma levels of vWF, the role of this protein in CTEPH has remained enigmatic. Objectives: To identify the role of vWF in CTEPH. Methods: CTEPH-specific patient plasma and pulmonary endarterectomy material from patients with CTEPH were used to study the relationship between inflammation, vWF expression, and pulmonary thrombosis. Cell culture findings were validated in human tissue, and proteomics and chromatin immunoprecipitation were used to investigate the underlying mechanism of CTEPH. Measurements and Main Results: vWF is increased in plasma and the pulmonary endothelium of CTEPH patients. In vitro, the increase in vWF gene expression and the higher release of vWF protein upon endothelial activation resulted in elevated platelet adhesion to CTEPH endothelium. Proteomic analysis revealed that nuclear factor (NF)-κB2 was significantly increased in CTEPH. We demonstrate reduced histone tri-methylation and increased histone acetylation of the vWF promoter in CTEPH endothelium, facilitating binding of NF-κB2 to the vWF promoter and driving vWF transcription. Genetic interference of NFκB2 normalized the high vWF RNA expression levels and reversed the prothrombotic phenotype observed in CTEPH-pulmonary artery endothelial cells. Conclusions: Epigenetic regulation of the vWF promoter contributes to the creation of a local environment that favors in situ thrombosis in the pulmonary arteries. It reveals a direct molecular link between inflammatory pathways and platelet adhesion in the pulmonary vascular wall, emphasizing a possible role of in situ thrombosis in the development or progression of CTEPH.

C1q is increased in cerebrospinal fluid-derived extracellular vesicles in Alzheimer's disease: A multi-cohort proteomics and immuno-assay validation study.

INTRODUCTION: Extracellular vesicles (EVs) may propagate and modulate Alzheimer's disease (AD) pathology. We aimed to comprehensively characterize the proteome of cerebrospinal fluid (CSF) EVs to identify proteins and pathways altered in AD. METHODS: CSF EVs were isolated by ultracentrifugation (Cohort 1) or Vn96 peptide (Cohort 2) from non-neurodegenerative controls (n = 15, 16) and AD patients (n = 22, 20, respectively). EVs were subjected to untargeted quantitative mass spectrometry-based proteomics. Results were validated by enzyme-linked immunosorbent assay (ELISA) in Cohorts 3 and 4, consisting of controls (n = 16, n = 43, (Cohort3, Cohort4)), and patients with AD (n = 24, n = 100). RESULTS: We found > 30 differentially expressed proteins in AD CSF EVs involved in immune-regulation. Increase of C1q levels in AD compared to non-demented controls was validated by ELISA (∼ 1.5 fold, p (Cohort 3) = 0.03, p (Cohort 4) = 0.005). DISCUSSION: EVs may be utilized as a potential biomarker and may play a so far unprecedented role in immune-regulation in AD.

Cancer cells copy migratory behavior and exchange signaling networks via extracellular vesicles.

Recent data showed that cancer cells from different tumor subtypes with distinct metastatic potential influence each other's metastatic behavior by exchanging biomolecules through extracellular vesicles (EVs). However, it is debated how small amounts of cargo can mediate this effect, especially in tumors where all cells are from one subtype, and only subtle molecular differences drive metastatic heterogeneity. To study this, we have characterized the content of EVs shed in vivo by two clones of melanoma (B16) tumors with distinct metastatic potential. Using the Cre-LoxP system and intravital microscopy, we show that cells from these distinct clones phenocopy their migratory behavior through EV exchange. By tandem mass spectrometry and RNA sequencing, we show that EVs shed by these clones into the tumor microenvironment contain thousands of different proteins and RNAs, and many of these biomolecules are from interconnected signaling networks involved in cellular processes such as migration. Thus, EVs contain numerous proteins and RNAs and act on recipient cells by invoking a multi-faceted biological response including cell migration.

Secreted protein markers in oral squamous cell carcinoma (OSCC).

BACKGROUND: Oral squamous cell carcinoma (OSCC) is a main cause of oral cancer mortality and morbidity in central south Asia. To improve the clinical outcome of OSCC patients, detection markers are needed, which are preferably non-invasive and thus independent of a tissue biopsy. METHODS: In the present study, we aimed to identify robust candidate protein biomarkers for non-invasive OSCC diagnosis. To this end, we measured the global protein profiles of OSCC tissue lysates to matched normal adjacent mucosa samples (n = 14) and the secretomes of nine HNSCC cell lines using LC-MS/MS-based proteomics. RESULTS: A total of 5123 tissue proteins were identified, of which 205 were robustly up- regulated (p-value < 0.01, fold change > + 2) in OSCC-tissues compared to normal adjacent tissues. The biological process "Secretion" was highly enriched in this set of proteins. Other upregulated biological pathways included "Unfolded Protein Response", "Spliceosomal complex assembly", "Protein localization to endosome" and "Interferon Gamma Response". Transcription factor analysis implicated Creb3L1, ESRRA, YY, ELF2, STAT1 and XBP as potential regulators. Of the 205 upregulated tissue proteins, 132 were identified in the cancer cell line secretomes, underscoring their potential use as non-invasive biofluid markers. To further prioritize our candidate markers for non-invasive OSCC detection, we integrated our data with public biofluid datasets including OSCC saliva, yielding 25 candidate markers for further study. CONCLUSIONS: We identified several key proteins and processes that are associated with OSCC tissues, underscoring the importance of altered secretion. Cancer-associated OSCC secretome proteins present in saliva have potential to be used as novel non-invasive biomarkers for the diagnosis of OSCC.

Phosphotyrosine-based Phosphoproteomics for Target Identification and Drug Response Prediction in AML Cell Lines.

Acute myeloid leukemia (AML) is a clonal disorder arising from hematopoietic myeloid progenitors. Aberrantly activated tyrosine kinases (TK) are involved in leukemogenesis and are associated with poor treatment outcome. Kinase inhibitor (KI) treatment has shown promise in improving patient outcome in AML. However, inhibitor selection for patients is suboptimal.In a preclinical effort to address KI selection, we analyzed a panel of 16 AML cell lines using phosphotyrosine (pY) enrichment-based, label-free phosphoproteomics. The Integrative Inferred Kinase Activity (INKA) algorithm was used to identify hyperphosphorylated, active kinases as candidates for KI treatment, and efficacy of selected KIs was tested.Heterogeneous signaling was observed with between 241 and 2764 phosphopeptides detected per cell line. Of 4853 identified phosphopeptides with 4229 phosphosites, 4459 phosphopeptides (4430 pY) were linked to 3605 class I sites (3525 pY). INKA analysis in single cell lines successfully pinpointed driver kinases (PDGFRA, JAK2, KIT and FLT3) corresponding with activating mutations present in these cell lines. Furthermore, potential receptor tyrosine kinase (RTK) drivers, undetected by standard molecular analyses, were identified in four cell lines (FGFR1 in KG-1 and KG-1a, PDGFRA in Kasumi-3, and FLT3 in MM6). These cell lines proved highly sensitive to specific KIs. Six AML cell lines without a clear RTK driver showed evidence of MAPK1/3 activation, indicative of the presence of activating upstream RAS mutations. Importantly, FLT3 phosphorylation was demonstrated in two clinical AML samples with a FLT3 internal tandem duplication (ITD) mutation.Our data show the potential of pY-phosphoproteomics and INKA analysis to provide insight in AML TK signaling and identify hyperactive kinases as potential targets for treatment in AML cell lines. These results warrant future investigation of clinical samples to further our understanding of TK phosphorylation in relation to clinical response in the individual patient.

Computational Analysis of Phosphoproteomics Data in Multi-Omics Cancer Studies.

Multiple types of molecular data for the same set of clinical samples are increasingly available and may be analyzed jointly in an integrative analysis to maximize comprehensive biological insight. This analysis is important as separate analyses of individual omics data types usually do not fully explain disease phenotypes. An increasing number of studies have now been focusing on multi-omics data integration, yet not many studies have included phosphoproteomics data, an important layer for understanding signaling pathways. Multi-omics integration methods with phosphoproteomics data are reviewed in the context of cancer research as well as multi-omics methods papers that would be promising to apply to phosphoproteomics data. Analysis of individual data types is still the major approach even in large cohort proteogenomics studies. Hence, a section is dedicated on possible integrative methods for multi-omics and phosphoproteomics data. In summary, this review provides the readers with both currently used integrative methods previously applied to phosphoproteomics and multi-omics data integration and other algorithms for multi-omics data integration promising for future application to phosphoproteomics data.

iq: an R package to estimate relative protein abundances from ion quantification in DIA-MS-based proteomics.

SUMMARY: We present an R package called iq to enable accurate protein quantification for label-free data-independent acquisition (DIA) mass spectrometry-based proteomics, a recently developed global approach with superior quantitative consistency. We implement the popular maximal peptide ratio extraction module of the MaxLFQ algorithm, so far only applicable to data-dependent acquisition mode using the software suite MaxQuant. Moreover, our implementation shows, for each protein separately, the validity of quantification over all samples. Hence, iq exports a state-of-the-art protein quantification algorithm to the emerging DIA mode in an open-source implementation. AVAILABILITY AND IMPLEMENTATION: The open-source R package is available on CRAN, https://github.com/tvpham/iq/releases and oncoproteomics.nl/iq. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Time dependent effect of cold ischemia on the phosphoproteome and protein kinase activity in fresh-frozen colorectal cancer tissue obtained from patients.

BACKGROUND: Based on their potential to analyze aberrant cellular signaling in relation to biological function, kinase activity profiling in tumor biopsies by peptide microarrays and mass spectrometry-based phosphoproteomics may guide selection of protein kinase inhibitors in patients with cancer. Variable tissue handling procedures in clinical practice may influence protein phosphorylation status and kinase activity and therewith may hamper biomarker discovery. Here, the effect of cold ischemia time (CIT) on the stability of kinase activity and protein phosphorylation status in fresh-frozen clinical tissue samples was studied using peptide microarrays and mass spectrometry-based phosphoproteomics. METHODS: Biopsies of colorectal cancer resection specimens from five patients were collected and snap frozen immediately after surgery and at 6 additional time points between 0 and 180 min of CIT. Kinase activity profiling was performed for all samples using a peptide microarray. MS-based global phosphoproteomics was performed in tumors from 3 patients at 4 time points. Statistical and cluster analyses were performed to analyze changes in kinase activity and phosphoproteome resulting from CIT. RESULTS: Unsupervised cluster analysis of kinase activity and phosphoproteome data revealed that samples from the same patients cluster together. Continuous ANOVA analysis of all 7 time points for 5 patient samples resulted in 4 peptides out of 210 (2%) with significantly (p < 0.01 and fold change > 2) altered signal intensity in time. In 4 out of 5 patients tumor kinase activity was stable with CIT. MS-based phosphoproteomics resulted in the detection of 10,488 different phosphopeptides with on average 6044 phosphopeptides per tumor sample. 2715 phosphopeptides were detected in all samples at time point 0, of which 90 (3.3%) phosphopeptides showed significant changes in intensity with CIT (p < 0.01). Only two phosphopeptides were significantly changed in all time points, including one peptide (PKP3) with a fold change > 2. CONCLUSIONS: The vast majority of the phosphoproteome as well as the activity of protein kinases in colorectal cancer resection tissue is stable up to 180 min of CIT and reflects tumor characteristics. However, specific changes in kinase activity with increasing CIT were observed. Therefore, stringent tissue collection procedures are advised to minimize changes in kinase activity during CIT.

Proteins in stool as biomarkers for non-invasive detection of colorectal adenomas with high risk of progression.

Screening to detect colorectal cancer (CRC) in an early or premalignant state is an effective method to reduce CRC mortality rates. Current stool-based screening tests, e.g. fecal immunochemical test (FIT), have a suboptimal sensitivity for colorectal adenomas and difficulty distinguishing adenomas at high risk of progressing to cancer from those at lower risk. We aimed to identify stool protein biomarker panels that can be used for the early detection of high-risk adenomas and CRC. Proteomics data (LC-MS/MS) were collected on stool samples from adenoma (n = 71) and CRC patients (n = 81) as well as controls (n = 129). Colorectal adenoma tissue samples were characterized by low-coverage whole-genome sequencing to determine their risk of progression based on specific DNA copy number changes. Proteomics data were used for logistic regression modeling to establish protein biomarker panels. In total, 15 of the adenomas (15.8%) were defined as high risk of progressing to cancer. A protein panel, consisting of haptoglobin (Hp), LAMP1, SYNE2, and ANXA6, was identified for the detection of high-risk adenomas (sensitivity of 53% at specificity of 95%). Two panels, one consisting of Hp and LRG1 and one of Hp, LRG1, RBP4, and FN1, were identified for high-risk adenomas and CRCs detection (sensitivity of 66% and 62%, respectively, at specificity of 95%). Validation of Hp as a biomarker for high-risk adenomas and CRCs was performed using an antibody-based assay in FIT samples from a subset of individuals from the discovery series (n = 158) and an independent validation series (n = 795). Hp protein was significantly more abundant in high-risk adenoma FIT samples compared to controls in the discovery (p = 0.036) and the validation series (p = 9e-5). We conclude that Hp, LAMP1, SYNE2, LRG1, RBP4, FN1, and ANXA6 may be of value as stool biomarkers for early detection of high-risk adenomas and CRCs. © 2019 Authors. Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Human Testis Phosphoproteome Reveals Kinases as Potential Targets in Spermatogenesis and Testicular Cancer.

Spermatogenesis is a complex cell differentiation process that includes marked genetic, cellular, functional and structural changes. It requires tight regulation, because disturbances in any of the spermatogenic processes would lead to fertility deficiencies as well as disorders in offspring. To increase our knowledge of signal transduction during sperm development, we carried out a large-scale identification of the phosphorylation events that occur in the human male gonad. Metal oxide affinity chromatography using TiO2 combined with LC-MS/MS was conducted to profile the phosphoproteome of adult human testes with full spermatogenesis. A total of 8187 phosphopeptides derived from 2661 proteins were identified, resulting in the most complete report of human testicular phosphoproteins to date. Phosphorylation events were enriched in proteins functionally related to spermatogenesis, as well as to highly active processes in the male gonad, such as transcriptional and translational regulation, cytoskeleton organization, DNA packaging, cell cycle and apoptosis. Moreover, 174 phosphorylated kinases were identified. The most active human protein kinases in the testis were predicted both by the number of phosphopeptide spectra identified and the phosphorylation status of the kinase activation loop. The potential function of cyclin-dependent kinase 12 (CDK12) and p21-activated kinase 4 (PAK4) has been explored by in silico, protein-protein interaction analysis, immunodetection in testicular tissue, and a functional assay in a human embryonal carcinoma cell line. The colocalization of CDK12 with Golgi markers suggests a potential crucial role of this protein kinase during sperm formation. PAK4 has been found expressed in human spermatogonia, and a role in embryonal carcinoma cell response to apoptosis has been observed. Together, our protein discovery analysis confirms that phosphoregulation by protein kinases is highly active in sperm differentiation and opens a window to detailed characterization and validation of potential targets for the development of drugs modulating male fertility and tumor behavior.

Effects of Cancer Presence and Therapy on the Platelet Proteome.

Platelets are involved in tumor angiogenesis and cancer progression. Previous studies indicated that cancer could affect platelet content. In the current study, we investigated whether cancer-associated proteins can be discerned in the platelets of cancer patients, and whether antitumor treatment may affect the platelet proteome. Platelets were isolated from nine patients with different cancer types and ten healthy volunteers. From three patients, platelets were isolated before and after the start of antitumor treatment. Mass spectrometry-based proteomics of gel-fractionated platelet proteins were used to compare patients versus controls and before and after treatment initiation. A total of 4059 proteins were detected, of which 50 were significantly more abundant in patients, and 36 more in healthy volunteers. Eight of these proteins overlapped with our previous cancer platelet proteomics study. From these data, we selected potential biomarkers of cancer including six upregulated proteins (RNF213, CTSG, PGLYRP1, RPL8, S100A8, S100A9) and two downregulated proteins (GPX1, TNS1). Antitumor treatment resulted in increased levels of 432 proteins and decreased levels of 189 proteins. In conclusion, the platelet proteome may be affected in cancer patients and platelets are a potential source of cancer biomarkers. In addition, we found in a small group of patients that anticancer treatment significantly changes the platelet proteome.

Combined Expression of Plasma Thrombospondin-2 and CA19-9 for Diagnosis of Pancreatic Cancer and Distal Cholangiocarcinoma: A Proteome Approach.

BACKGROUND: Minimally invasive diagnostic biomarkers for patients with pancreatic ductal adenocarcinoma (PDAC) and distal cholangiocarcinoma (dCCA) are warranted to facilitate accurate diagnosis. This study identified diagnostic plasma proteins based on proteomics of tumor secretome. MATERIALS AND METHODS: Secretome of tumor and normal tissue was collected after resection of PDAC and dCCA. Differentially expressed proteins were measured by mass spectrometry. Selected candidate biomarkers and carbohydrate antigen 19-9 (CA19-9) were validated by enzyme-linked immunosorbent assay in plasma from patients with PDAC (n = 82), dCCA (n = 29), benign disease (BD; n = 30), and healthy donors (HDs; n = 50). Areas under the curve (AUCs) of receiver operator characteristic curves were calculated to determine the discriminative power. RESULTS: In tumor secretome, 696 discriminatory proteins were identified, including 21 candidate biomarkers. Thrombospondin-2 (THBS2) emerged as promising biomarker. Abundance of THBS2 in plasma from patients with cancer was significantly higher compared to HDs (p < .001, AUC = 0.844). Combined expression of THBS2 and CA19-9 yielded the optimal discriminatory capacity (AUC = 0.952), similarly for early- and late-stage disease (AUC = 0.971 and AUC = 0.911). Remarkably, this combination demonstrated a power similar to CA19-9 to discriminate cancer from BD (AUC = 0.764), and THBS2 provided an additive value in patients with high expression levels of bilirubin. CONCLUSION: Our proteome approach identified a promising set of candidate biomarkers. The combined plasma expression of THBS2/CA19-9 is able to accurately distinguish patients with PDAC or dCCA from HD and BD. IMPLICATIONS FOR PRACTICE: The combined plasma expression of thrombospondin-2 and carbohydrate antigen 19-9 is able to accurately diagnose patients with pancreatic cancer and distal cholangiocarcinoma. This will facilitate minimally invasive diagnosis for these patients by distinguishing them from healthy individuals and benign diseases.