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Background Early metastasis is a hallmark of small cell lung cancer (SCLC). However, the mechanisms and resulting patterns of SCLC dissemination are unclear. Our aim was thus to investigate the organ specificity and timing of blood‐borne metastases in a comprehensive large cohort of SCLC patients. Methods In this retrospective non‐interventional cross‐sectional study of 1009 Caucasian SCLC patients, we investigated the correlation between the distinct locations of the primary tumor and metastatic sites. Results The onset of bone (p, In this study, our aim was to examine the organ specificity and timing of blood‐borne metastases in a comprehensive large cohort of Caucasian SCLC patients (n =1009). We report here that the onset of bone, brain, and pericardial metastases are late events, whereas adrenal gland and liver metastases occur earlier during tumor progression. We also show that several metastatic sites, such as bone and liver, and brain and adrenal gland intend to co‐metastasize preferentially. Of note, however, no significant associations were observed with regards to the timing and organ preference of distant metastases when comparing central and peripheral primary tumors.

Small cell lung cancer (SCLC; accounting for approximately 13%–15% of all lung cancers) is an exceptionally lethal malignancy characterized by rapid doubling time and high propensity to metastasize. In contrast to the increasingly personalized therapies in other types of lung cancer, SCLC is still regarded as a homogeneous disease and the prognosis of SCLC patients remains poor. Recently, however, substantial progress has been made in our understanding of SCLC biology. Advances in genomics and development of new preclinical models have facilitated insights into the intratumoral heterogeneity and specific genetic alterations of this disease. This worldwide resurgence of studies on SCLC has ultimately led to the development of novel subtype-specific classifications primarily based on the neuroendocrine features and distinct molecular profiles of SCLC. Importantly, these biologically distinct subtypes might define unique therapeutic vulnerabilities. Herein, we summarize the current knowledge on the molecular profiles of SCLC subtypes with a focus on their potential clinical implications., Graphical Abstract, Small cell lung cancer is still regarded as a homogeneous disease associated with poor prognosis. Recent analysis, however, has led to the development of novel subtype-specific classifications primarily based on the neuroendocrine features and molecular profiles. The better understanding of these biologically distinct subtypes might help to define unique therapeutic vulnerabilities.

Well-characterized archival formalin-fixed paraffin-embedded (FFPE) tissues are of much value for prospective biomarker discovery studies, and protocols that offer high throughput and good reproducibility are essential in proteomics. Therefore, we implemented efficient paraffin removal and protein extraction from FFPE tissues followed by an optimized two-enzyme digestion using suspension trapping (S-Trap). The protocol was then combined with TMTpro 16plex labeling and applied to lung adenocarcinoma patient samples. In total, 9585 proteins were identified, and proteins related to the clinical outcome were detected. Because acetylation is known to play a major role in cancer development, a fast on-trap acetylation protocol was developed for studying endogenous lysine acetylation, which allows identification and localization of the lysine acetylation together with quantitative comparison between samples. We demonstrated that FFPE tissues are equivalent to frozen tissues to study the degree of acetylation between patients. In summary, we present a reproducible sample preparation workflow optimized for FFPE tissues that resolves known proteomic-related challenges. We demonstrate compatibility of the S-Trap with isobaric labeling and for the first time, we prove that it is feasible to study endogenous lysine acetylation stoichiometry in FFPE tissues, contributing to better utility of the existing global tissue archives. The MS proteomic data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the data set identifiers PXD020157, PXD021986, and PXD021964.

Background: Patients with chronic kidney disease (CKD) have poor outcomes following myocardial infarction (MI). We performed an untargeted examination of 175 biomarkers to identify those with the strongest association with CKD and to examine the association of those biomarkers with long-term outcomes. Methods: A total of 175 different biomarkers from MI patients enrolled in the Swedish Web-System for Enhancement and Development of Evidence-Based Care in Heart Disease Evaluated According to Recommended Therapies (SWEDEHEART) registry were analysed either by a multiple reaction monitoring mass spectrometry assay or by a multiplex assay (proximity extension assay). Random forests statistical models were used to assess the predictor importance of biomarkers, CKD and outcomes. Results: A total of 1098 MI patients with a median estimated glomerular filtration rate of 85 mL min−1/1.73 m2 were followed for a median of 3.2 years. The random forests analyses, without and with adjustment for differences in demography, comorbidities and severity of disease, identified six biomarkers (adrenomedullin, TNF receptor-1, adipocyte fatty acid-binding protein-4, TNF-related apoptosis-inducing ligand receptor 2, growth differentiation factor-15 and TNF receptor-2) to be strongly associated with CKD. All six biomarkers were also amongst the 15 strongest predictors for death, and four of them were amongst the strongest predictors of subsequent MI and heart failure hospitalization. Conclusion: In patients with MI, a proteomic approach could identify six biomarkers that best predicted CKD. These biomarkers were also amongst the most important predictors of long-term outcomes. Thus, these biomarkers indicate underlying mechanisms that may contribute to the poor prognosis seen in patients with MI and CKD. (Less)

In the advanced stages, malignant melanoma (MM) has a very poor prognosis. Due to tremendous efforts in cancer research over the last 10 years, and the introduction of novel therapies such as targeted therapies and immunomodulators, the rather dark horizon of the median survival has dramatically changed from under 1 year to several years. With the advent of proteomics, deep-mining studies can reach low-abundant expression levels. The complexity of the proteome, however, still surpasses the dynamic range capabilities of current analytical techniques. Consequently, many predicted protein products with potential biological functions have not yet been verified in experimental proteomic data. This category of ‘missing proteins’ (MP) is comprised of all proteins that have been predicted but are currently unverified. As part of the initiative launched in 2016 in the USA, the European Cancer Moonshot Center has performed numerous deep proteomics analyses on samples from MM patients. In this study, nine MPs were clearly identified by mass spectrometry in MM metastases. Some MPs significantly correlated with proteins that possess identical PFAM structural domains; and other MPs were significantly associated with cancer-related proteins. This is the first study to our knowledge, where unknown and novel proteins have been annotated in metastatic melanoma tumour tissue.

Summary The hippocampus is important for memory formation and is severely affected in the brain with Alzheimer disease (AD). Our understanding of early pathogenic processes occurring in hippocampi in AD is limited due to tissue unavailability. Here, we report a chemical approach to rapidly generate free-floating hippocampal spheroids (HSs), from human induced pluripotent stem cells. When used to model AD, both APP and atypical PS1 variant HSs displayed increased Aβ42/Aβ40 peptide ratios and decreased synaptic protein levels, which are common features of AD. However, the two variants differed in tau hyperphosphorylation, protein aggregation, and protein network alterations. NeuroD1-mediated gene therapy in HSs-derived progenitors resulted in modulation of expression of numerous genes, including those involved in synaptic transmission. Thus, HSs can be harnessed to unravel the mechanisms underlying early pathogenic changes in the hippocampi of AD patients, and provide a robust platform for the development of therapeutic strategies targeting early stage AD., Graphical Abstract, Highlights • Rapid generation of hippocampal spheroids (HSs) from hiPSCs using defined chemical agents • hiPSC-derived HSs can be utilized as a source of hippocampal neurons • hiPSC-derived HSs can be used to model Alzheimer disease • hiPSC-derived HSs can be used to develop innovative therapeutic solutions, In this article, Roybon and colleagues developed a protocol to efficiently and rapidly generate hippocampus neurons from human induced pluripotent stem cells, which they used to model Alzheimer disease and develop a gene therapy approach to modulate the expression of genes involved in synaptic transmission.

Aims There is a paucity of studies comprehensively comparing the prognostic value of larger arrays of biomarkers indicative of different pathobiological axes in acute myocardial infarction (MI). Methods and results In this explorative investigation, we simultaneously analysed 175 circulating biomarkers reflecting different inflammatory traits, coagulation activity, endothelial dysfunction, atherogenesis, myocardial dysfunction and damage, apoptosis, kidney function, glucose-, and lipid metabolism. Measurements were performed in samples from 1099 MI patients (SWEDEHEART registry) applying two newer multimarker panels [Proximity Extension Assay (Olink Bioscience), Multiple Reaction Monitoring mass spectrometry]. The prognostic value of biomarkers regarding all-cause mortality, recurrent MI, and heart failure hospitalizations (median follow-up ≤6.6 years) was studied using Lasso analysis, a penalized logistic regression model that considers all biomarkers simultaneously while minimizing the risk for spurious findings. Tumour necrosis factor-related apoptosis-inducing ligand receptor 2 (TRAIL-R2), ovarian cancer-related tumour marker CA 125 (CA-125), and fibroblast growth factor 23 (FGF-23) consistently predicted all-cause mortality in crude and age/sex-adjusted analyses. Growth-differentiation factor 15 (GDF-15) was strongly predictive in the crude model. TRAIL-R2 and B-type natriuretic peptide (BNP) consistently predicted heart failure hospitalizations. No biomarker predicted recurrent MI. The prognostic value of all biomarkers was abrogated following additional adjustment for clinical variables owing to our rigorous statistical approach. Conclusion Apart from biomarkers with established prognostic value (i.e. BNP and to some extent GDF-15), several ‘novel’ biomarkers (i.e. TRAIL-R2, CA-125, FGF-23) emerged as risk predictors in patients with MI. Our data warrant further investigation regarding the utility of these biomarkers for clinical decision-making in acute MI.

Melanoma of the skin is the sixth most common type of cancer in Europe and accounts for 3.4% of all diagnosed cancers. More alarming is the degree of recurrence that occurs with approximately 20% of patients lethally relapsing following treatment. Malignant melanoma is a highly aggressive skin cancer and metastases rapidly extend to the regional lymph nodes (stage 3) and to distal organs (stage 4). Targeted oncotherapy is one of the standard treatment for progressive stage 4 melanoma, and BRAF inhibitors (e.g. vemurafenib, dabrafenib) combined with MEK inhibitor (e.g. trametinib) can effectively counter BRAFV600E-mutated melanomas. Compared to conventional chemotherapy, targeted BRAFV600E inhibition achieves a significantly higher response rate. After a period of cancer control, however, most responsive patients develop resistance to the therapy and lethal progression. The many underlying factors potentially causing resistance to BRAF inhibitors have been extensively studied. Nevertheless, the remaining unsolved clinical questions necessitate alternative research approaches to address the molecular mechanisms underlying metastatic and treatment-resistant melanoma. In broader terms, proteomics can address clinical questions far beyond the reach of genomics, by measuring, i.e. the relative abundance of protein products, post-translational modifications (PTMs), protein localisation, turnover, protein interactions and protein function. More specifically, proteomic analysis of body fluids and tissues in a given medical and clinical setting can aid in the identification of cancer biomarkers and novel therapeutic targets. Achieving this goal requires the development of a robust and reproducible clinical proteomic platform that encompasses automated biobanking of patient samples, tissue sectioning and histological examination, efficient protein extraction, enzymatic digestion, mass spectrometry-based quantitative protein analysis by label-free or labelling technologies and/or enrichment of peptides with specific PTMs. By combining data from, e.g. phosphoproteomics and acetylomics, the protein expression profiles of different melanoma stages can provide a solid framework for understanding the biology and progression of the disease. When complemented by proteogenomics, customised protein sequence databases generated from patient-specific genomic and transcriptomic data aid in interpreting clinical proteomic biomarker data to provide a deeper and more comprehensive molecular characterisation of cellular functions underlying disease progression. In parallel to a streamlined, patient-centric, clinical proteomic pipeline, mass spectrometry-based imaging can aid in interrogating the spatial distribution of drugs and drug metabolites within tissues at single-cell resolution. These developments are an important advancement in studying drug action and efficacy in vivo and will aid in the development of more effective and safer strategies for the treatment of melanoma. A collaborative effort of gargantuan proportions between academia and healthcare professionals has led to the initiation, establishment and development of a cutting-edge cancer research centre with a specialisation in melanoma and lung cancer. The primary research focus of the European Cancer Moonshot Lund Center is to understand the impact that drugs have on cancer at an individualised and personalised level. Simultaneously, the centre increases awareness of the relentless battle against cancer and attracts global interest in the exceptional research performed at the centre.

The tryptophan to kynurenine ratio (Trp/Kyn) has been proposed as a cancer biomarker. Non-invasive topical sampling of Trp/Kyn can therefore serve as a promising concept for skin cancer diagnostics. By performing in vitro pig skin permeability studies, we conclude that non-invasive topical sampling of Trp and Kyn is feasible. We explore the influence of different experimental conditions, which are relevant for the clinical in vivo setting, such as pH variations, sampling time, and microbial degradation of Trp and Kyn. The permeabilities of Trp and Kyn are overall similar. However, the permeated Trp/Kyn ratio is generally higher than unity due to endogenous Trp, which should be taken into account to obtain a non-biased Trp/Kyn ratio accurately reflecting systemic concentrations. Additionally, prolonged sampling time is associated with bacterial Trp and Kyn degradation and should be considered in a clinical setting. Finally, the experimental results are supported by the four permeation pathways model, predicting that the hydrophilic Trp and Kyn molecules mainly permeate through lipid defects (i.e., the porous pathway). However, the hydrophobic indole ring of Trp is suggested to result in a small but noticeable relative increase of Trp diffusion via pathways across the SC lipid lamellae, while the shunt pathway is proposed to slightly favor permeation of Kyn relative to Trp.

Spike glycoprotein is essential for the reproduction of the SARS-CoV-2 virus, and its inhibition using already approved antiviral drugs may open new avenues for the treatment of patients with the COVID-19 disease. Because of that, we analyzed the inhibition of SARS-CoV-2 spike glycoprotein with FDA-approved antiviral drugs and their double and triple combinations. We used the Vini in silico model of cancer to perform this virtual drug screening, showing HIV drugs to be the most effective. Besides, the combination of cobicistat-abacavir-rilpivirine HIV drugs demonstrated the highest in silico efficacy of inhibiting SARS-CoV-2 spike glycoprotein. Therefore, a clinical trial of cobicistat- abacavir-rilpivirine on a limited number of COVID- 19 patients in moderately severe and severe conditions is warranted.

Background A gel‐free proteomic approach was utilized to perform in‐depth tissue protein profiling of lung adenocarcinoma (ADC) and normal lung tissues from early and advanced stages of the disease. The long‐term goal of this study is to generate a large‐scale, label‐free proteomics dataset from histologically well‐classified lung ADC that can be used to increase further our understanding of disease progression and aid in identifying novel biomarkers. Methods and results Cases of early‐stage (I‐II) and advanced‐stage (III‐IV) lung ADCs were selected and paired with normal lung tissues from 22 patients. The histologically and clinically stratified human primary lung ADCs were analyzed by liquid chromatography‐tandem mass spectrometry. From the analysis of ADC and normal specimens, 4863 protein groups were identified. To examine the protein expression profile of ADC, a peak area‐based quantitation method was used. In early‐ and advanced‐stage ADC, 365 and 366 proteins were differentially expressed, respectively, between normal and tumor tissues (adjusted P‐value

Although natural products are an important source of drugs and drug leads, identification and validation of their target proteins have proven difficult. Here, we report the development of a systematic strategy for target identification and validation employing drug affinity responsive target stability (DARTS) and mass spectrometry imaging (MSI) without modifying or labeling natural compounds. Through a validation step using curcumin, which targets aminopeptidase N (APN), we successfully standardized the systematic strategy. Using label-free voacangine, an antiangiogenic alkaloid molecule as the model natural compound, DARTS analysis revealed vascular endothelial growth factor receptor 2 (VEGFR2) as a target protein. Voacangine inhibits VEGFR2 kinase activity and its downstream signaling by binding to the kinase domain of VEGFR2, as was revealed by docking simulation. Through cell culture assays, voacangine was found to inhibit the growth of glioblastoma cells expressing high levels of VEGFR2. Specific localization of voacangine to tumor compartments in a glioblastoma xenograft mouse was revealed by MSI analysis. The overlap of histological images with the MSI signals for voacangine was intense in the tumor regions and showed colocalization of voacangine and VEGFR2 in the tumor tissues by immunofluorescence analysis of VEGFR2. The strategy employing DARTS and MSI to identify and validate the targets of a natural compound as demonstrated for voacangine in this study is expected to streamline the general approach of drug discovery and validation using other biomolecules including natural products.

Graphical abstract, Typing of amyloidosis by mass spectrometry (MS) based proteomic analysis contribute to the diagnosis of amyloidosis. For MS analysis, laser microdissection (LMD) is used for amyloid specific sampling. This study aimed to establish a method for selectively extracting amyloids from formalin-fixed, paraffin-embedded (FFPE) specimens by organic solvent instead of LMD. The extracts using dimethyl sulfoxide (DMSO), dimethylformamide (DMF), methanol, trifluoroethanol (TFE) or hexafluoro-2-propanol from FFPE brain of alzheimer’s disease mouse model generated protein bands on SDS-PAGE, and Aβ was identified in the extract of DMF using mass spectrometry. The extract using DMSO from the kidney of a AA amyloidosis patient produced a protein band in SDS-PAGE. This protein band was identified to be serum amyloid A (SAA) by Western blotting and mass spectrometry. Circular dichroism spectrometry revealed that the secondary structures of Aβ and transthyretin were converted to α-helices from β-sheets in TFE. Our results suggest that organic solvents can extract amyloids from FFPE specimens by converting their secondary structure. This method could eliminate the LMD step and simplified amyloid typing by MS analysis. • DMSO, DMF, methanol, TFE and HFIP can extract Aβ specifically from the FFPE brain of a Alzheimer’ disease mouse model. • DMSO can extract SAA specifically from a FFPE section of AA amyloidosis. • Secondary structures of Aβ and transthyretin converted from β-sheet to α-helix in TFE.

In comparison to other human cancer types, malignant melanoma exhibits the greatest amount of heterogeneity. After DNA-based detection of the BRAF V600E mutation in melanoma patients, targeted inhibitor treatment is the current recommendation. This approach, however, does not take the abundance of the therapeutic target, i.e., the B-raf V600E protein, into consideration. As shown by immunohistochemistry, the protein expression profiles of metastatic melanomas clearly reveal the existence of inter- and intra-tumor variability. Nevertheless, the technique is only semi-quantitative. To quantitate the mutant protein there is a fundamental need for more precise techniques that are aimed at defining the currently non-existent link between the levels of the target protein and subsequent drug efficacy. Using cutting-edge mass spectrometry combined with DNA and mRNA sequencing, the mutated B-raf protein within metastatic tumors was quantitated for the first time. B-raf V600E protein analysis revealed a subjacent layer of heterogeneity for mutation-positive metastatic melanomas. These were characterized into two distinct groups with different tumor morphologies, protein profiles and patient clinical outcomes. This study provides evidence that a higher level of expression in the mutated protein is associated with a more aggressive tumor progression. Our study design, comprised of surgical isolation of tumors, histopathological characterization, tissue biobanking, and protein analysis, may enable the eventual delineation of patient responders/non-responders and subsequent therapy for malignant melanoma.

Studying how and where drugs are metabolized in the brain is challenging. In an entire organism, peripheral metabolism produces many of the same metabolites as those in the brain, and many of these metabolites can cross the blood-brain barrier from the periphery, thus making the relative contributions of hepatic and brain metabolism difficult to study in vivo. In addition, drugs and metabolites contained in ventricles and in the residual blood of capillaries in the brain may overestimate drugs' and metabolites' concentrations in the brain. In this study, we examine locusts and zebrafish using matrix assisted laser desorption ionization mass spectrometry imaging to study brain metabolism and distribution. These animal models are cost-effective and ethically sound for initial drug development studies.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy. Here we show that shotgun and targeted protein sequencing can be used to identify potential prognostic biomarkers in formalin-fixed paraffin-embedded specimens from 9 patients with PDAC with “short” survival (45 months) undergoing surgical resection. A total of 24 and 147 proteins were significantly upregulated [fold change ≥2 or ≤0.5 and P

A multiple reaction monitoring (MRM) assay was developed for precise quantitation of 87 plasma proteins including the three isoforms of apolipoprotein E (APOE) associated with cardiovascular diseases using nanoscale liquid chromatography separation and stable isotope dilution strategy. The analytical performance of the assay was evaluated and we found an average technical variation of 4.7% in 4-5 orders of magnitude dynamic range (≈0.2 mg/L to 4.5 g/L) from whole plasma digest. Here, we report a complete workflow, including sample processing adapted to 96-well plate format and normalization strategy for large-scale studies. To further investigate the MS-based quantitation the amount of six selected proteins was measured by routinely used clinical chemistry assays as well and the two methods showed excellent correlation with high significance (p-value10e-5) for the six proteins, in addition for the cardiovascular predictor factor, APOB: APOA1 ratio (r = 0.969, p-value10e-5). Moreover, we utilized the developed assay for screening of biobank samples from patients with myocardial infarction and performed the comparative analysis of patient groups with STEMI (ST- segment elevation myocardial infarction), NSTEMI (non ST- segment elevation myocardial infarction) and type-2 AMI (type-2 myocardial infarction) patients.

Resistance mechanisms against antiangiogenic drugs are unclear. Here, we correlated the antitumor and antivascular properties of five different antiangiogenic receptor tyrosine kinase inhibitors (RTKIs) (motesanib, pazopanib, sorafenib, sunitinib, vatalanib) with their intratumoral distribution data obtained by matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI). In the first mouse model, only sunitinib exhibited broad-spectrum antivascular and antitumor activities by simultaneously suppressing vascular endothelial growth factor receptor-2 (VEGFR2) and desmin expression, and by increasing intratumoral hypoxia and inhibiting both tumor growth and vascularisation significantly. Importantly, the highest and most homogeneous intratumoral drug concentrations have been found in sunitinib-treated animals. In another animal model, where - in contrast to the first model - vatalanib was detectable at homogeneously high intratumoral concentrations, the drug significantly reduced tumor growth and angiogenesis. In conclusion, the tumor tissue penetration and thus the antiangiogenic and antitumor potential of antiangiogenic RTKIs vary among the tumor models and our study demonstrates the potential of MALDI-MSI to predict the efficacy of unlabelled small molecule antiangiogenic drugs in malignant tissue. Our approach is thus a major technical and preclinical advance demonstrating that primary resistance to angiogenesis inhibitors involves limited tumor tissue drug penetration. We also conclude that MALDI-MSI may significantly contribute to the improvement of antivascular cancer therapies. OA gold

Background Alzheimer's disease (AD) is the most common neurodegenerative disorder. Depositions of amyloid β peptide (Aβ) and tau protein are among the major pathological hallmarks of AD. Aβ and tau burden follows predictable spatial patterns during the progression of AD. Nevertheless, it remains obscure why certain brain regions are more vulnerable than others; to investigate this and dysregulated pathways during AD progression, a mass spectrometry-based proteomics study was performed. Methods In total 103 tissue samples from regions early (entorhinal and parahippocampal cortices - medial temporal lobe (MTL)) and late affected (temporal and frontal cortices - neocortex) by tau pathology were subjected to label-free quantitative proteomics analysis. Results Considering dysregulated proteins during AD progression, the majority (625 out of 737 proteins) was region specific, while some proteins were shared between regions (101 proteins altered in two areas and 11 proteins altered in three areas). Analogously, many dysregulated pathways during disease progression were exclusive to certain regions, but a few pathways altered in two or more areas. Changes in protein expression indicate that synapse loss occurred in all analyzed regions, while translation dysregulation was preponderant in entorhinal, parahippocampal and frontal cortices. Oxidative phosphorylation impairment was prominent in MTL. Differential proteomic analysis of brain areas in health state (controls) showed higher metabolism and increased expression of AD-related proteins in the MTL compared to the neocortex. In addition, several proteins that differentiate brain regions in control tissue were dysregulated in AD. Conclusions This work provides the comparison of proteomic changes in brain regions affected by tau pathology at different stages of AD. Although we identified commonly regulated proteins and pathways during disease advancement, we found that the dysregulated processes are predominantly region specific. In addition, a distinct proteomic signature was found between MTL and neocortex in healthy subjects that might be related to AD vulnerability. These findings highlight the need for investigating AD's cascade of events throughout the whole brain and studies spanning more brain areas are required to better understand AD etiology and region vulnerability to disease.

Extracellular vesicles (EVs) are submicron, membrane-enclosed particles that are released from cells in various pathophysiological states. The molecular cargo of these vesicles is considered to reflect the composition of the cell of origin, and the EV proteome is therefore a potential source of biomarkers for various diseases. Our aim was to determine whether EVs isolated from plasma provide additional diagnostic value or improved pathophysiological understanding compared to plasma alone in the context of myocardial infarction (MI). A panel of proximity extension assays (n = 92) was employed to analyze EV lysates and plasma from patients with MI (n = 60) and healthy controls (n = 22). After adjustment for multiple comparisons, a total of 11 dysregulated proteins were identified in EVs of MI patients compared to the controls (q

Metastatic melanoma is one of the most common deadly cancers, and robust biomarkers are still needed, e.g. to predict survival and treatment efficiency. Here, protein expression analysis of one hundred eleven melanoma lymph node metastases using high resolution mass spectrometry is coupled with in-depth histopathology analysis, clinical data and genomics profiles. This broad view of protein expression allowed to identify novel candidate protein markers that improved prediction of survival in melanoma patients. Some of the prognostic proteins have not been reported in the context of melanoma before, and few of them exhibit unexpected relationship to survival, which likely reflects the limitations of current knowledge on melanoma and shows the potential of proteomics in clinical cancer research.

To acquire a deeper understanding of malignant melanoma (MM), it is essential to study the proteome of patient tissues. In particular, phosphoproteomics of MM has become of significant importance because of the central role that phosphorylation plays in the development of MM. Investigating clinical samples, however, is an extremely challenging task as there is usually only very limited quantities of material available to perform targeted enrichment approaches. Here, an automated phosphopeptide enrichment protocol using the AssayMap Bravo platform was applied to MM tissues and assessed for performance. The strategy proved to be highly-sensitive, less prone to variability, less laborious than existing techniques and adequate for starting quantities at the microgram level. An Fe(III)-NTA-IMAC-based enrichment workflow was applied to a dilution series of MM tissue lysates. The workflow was efficient in terms of sensitivity, reproducibility and phosphosite localization; and from only 12.5 μg of sample, more than 1,000 phosphopeptides were identified. In addition, from 60 μg of protein material the number of identified phosphoproteins from individual MM samples was comparable to previous reports that used extensive fractionation methods. Our data set included key pathways that are involved in MM progression; such as MAPK, melanocyte development and integrin signaling. Moreover, tissue-specific immunological proteins were identified, that have not been previously observed in the proteome of MM-derived cell lines. In conclusion, this workflow is suitable to study large cohorts of clinical samples that demand automatic and careful handling.

The Biology/Disease-driven (B/D) working groups of the Human Proteome Project are alliances of research groups aimed at developing or improving proteomic tools to support specific biological or disease-related research areas. Here, we describe the activities and progress to date of the B/D working group focused on protein aggregation diseases (PADs). PADs are characterized by the intra- or extracellular accumulation of aggregated proteins and include devastating diseases such as Parkinson's and Alzheimer's disease and systemic amyloidosis. The PAD B/D working group aims for the development of proteomic assays for the quantification of aggregation-prone proteins involved in PADs to support basic and clinical research on PADs. Because the proteins in PADs undergo aberrant conformational changes, a goal is to quantitatively resolve altered protein structures and aggregation states in complex biological specimens. We have developed protein-extraction protocols and a set of mass spectrometric (MS) methods that enable the detection and quantification of proteins involved in the systemic and localized amyloidosis and the probing of aberrant protein conformational transitions in cell and tissue extracts. In several studies, we have demonstrated the potential of MS-based proteomics approaches for specific and sensitive clinical diagnoses and for the subtyping of PADs. The developed methods have been detailed in both protocol papers and manuscripts describing applications to facilitate implementation by nonspecialized laboratories, and assay coordinates are shared through public repositories and databases. Clinicians actively involved in the PAD working group support the transfer to clinical practice of the developed methods, such as assays to quantify specific disease related proteins and their fragments in biofluids and multiplexed MS-based methods for the diagnosis and typing of systemic amyloidosis. We believe that the increasing availability of tools to precisely measure proteins involved in PADs will positively impact research on the molecular bases of these diseases and support early disease diagnosis and a more-confident subtyping.

Large cohorts of carefully collected clinical tissue materials play a central role in acquiring sufficient depth and statistical power to discover disease-related mechanisms and biomarkers of clinical significance. Manual preparation of such large sample cohorts requires experienced laboratory personnel. This carries other possible downsides such as low throughput, high risk of errors, and low reproducibility. In this work, three automated technologies for high-throughput proteomics of frozen sectioned tissues were compared. The instruments evaluated included the Bioruptor for tissue disruption and protein extraction; the Barocycler, which is able to disrupt tissues and digest the proteins; and the AssayMAP Bravo, a microchromatography platform for protein digestion, peptide desalting, and fractionation. Wide varieties of tissue samples from rat spleen, malignant melanoma, and pancreatic tumors were used for the assessment. The three instruments displayed reproducible and consistent results, as was proven by high correlations and low coefficients of variation between technical replicates and even more importantly, between replicates that were processed in different batches or at different time points. The results from this study allowed us to integrate these technologies into an automated sample preparation workflow for large-scale proteomic studies that are currently ongoing. Data are available via ProteomeXchange with identifiers PXD010296 and PXD011295.

Extracellular vesicles (ECVs), including microparticles (MPs) and exosomes, are submicron membrane vesicles released by diverse cell types upon activation or stress. Circulating ECVs are potential reservoirs of disease biomarkers, and the complexity of these vesicles is significantly lower compared to their source, blood plasma, which makes the ECV-based biomarker studies more promising. Proteomic profiling of ECVs is important not only to discover new diagnostic or prognostic markers, but also to understand their roles in biological function. In the current study we investigated the protein composition of plasma-derived ECVs isolated by acoustic seed trapping. Additionally, the protein composition of ECVs isolated with acoustic trapping was compared to those isolated with a conventional differential centrifugation protocol. Finally, the proteome of ECVs originating from ST-elevation myocardial infarction (STEMI) patients was compared with healthy controls using label-free LC-MS quantification. The acoustic trapping platform allows rapid and automated preparation of ECVs from small sample volumes, and therefore well suited for biobank repositories. We found that the protein composition of trapped ECVs is very similar to those, which were isolated by the conventional differential centrifugation method.

[Background]: Currently, only a limited number of molecular biomarkers for malignant melanoma exist. This is the case for both diagnosing the disease, staging, and efficiently measuring the response to therapy by tracing the progression of disease development and drug impact. There is a great need to identify novel landmarks of disease progression and alterations., [Methods]: Matrix-assisted laser desorption ionisation mass spectrometry imaging (MALDI-MSI) has been developed within our group to study drug localisation within micro environmental tissue compartments. Here, we expand further on this technology development and introduce for the frst time melanoma tumour tissues to map metabolite localisation utilising high resolution mass spectrometry. MALDI-MSI can measure and localise the distribution pattern of a number of small molecule metabolites within tissue compartments of tumours isolated from melanoma patients. Data on direct measurements of metabolite identities attained at the local sites in tissue compartments has not been readily available as a measure of a clinical index for most cancer diseases. The current development on the mapping of endogenous molecular expression melanoma tumours by mass spectrometry imaging focuses on the establish‑ment of a cancer tissue preparation process whereby a matrix crystal formation is homogenously built on the tissue surface, providing uniform molecular mapping. We apply this micro-preparation technology to disease presentation by mapping the molecular signatures from patient tumour sections., [Results]: We have automated the process with a micro-technological dispensing platform. This provides the basis for thin film generation of the cancer patient tissues prior to imaging screening. Compartmentalisation of the tumour regions are displayed within the image analysis interfaced with histopathological grading and characterisation., [Conclusions]: This enables site localisation within the tumour with image mapping to disease target areas such as melanoma cells, macrophages, and lymphocytes., This study was supported by a joint grant from the Berta Kamprad Founda‑tion (Melanoma Cancer Moonshot) and by grants from the National Research Foundation of Korea (NRF-2015K1A1A2028365, 2016K2A9A1A03904900), the Brain Korea 21 Plus Project, Republic of Korea, and KNN121510 by the National Research, Development and Innovation Ofce of Hungary.

There is an increasing global interest to support research areas that can assist in understanding disease and improving patient care. The National Cancer Institute (NIH) has identified precision medicine-based approaches as key research strategies to expedite advances in cancer research. The Cancer Moonshot program (https://www.cancer.gov/research/key-initiatives/moonshot-cancer-initiative) is the largest cancer program of all time, and has been launched to accelerate cancer research that aims to increase the availability of therapies to more patients and, ultimately, to eradicate cancer. Mass spectrometry-based proteomics has been extensively used to study the molecular mechanisms of cancer, to define molecular subtypes of tumors, to map cancer-associated protein interaction networks and post-translational modifications, and to aid in the development of new therapeutics and new diagnostic and prognostic tests. To establish the basis for our melanoma studies, we have established the Southern Sweden Malignant Melanoma Biobank. Tissues collected over many years have been accurately characterized with respect to the tumor and patient information. The extreme variability displayed in the protein profiles and the detection of missense mutations has confirmed the complexity and heterogeneity of the disease. It is envisaged that the combined analysis of clinical, histological, and proteomic data will provide patients with a more personalized medical treatment. With respect to disease presentation, targeted treatment and medical mass spectrometry analysis and imaging, this overview report will outline and summarize the current achievements and status within malignant melanoma. We present data generated by our cancer research center in Lund, Sweden, where we have built extensive capabilities in biobanking, proteogenomics, and patient treatments over an extensive time period. © 2018, The Author(s)., Funding information This study was supported by a joint grant from Berta Kamprad Foundation, and grants from the National Research Foundation of Korea, funded by the government of Republic of Korea (MSIP; 2012M3A9D1054520, 2015K1A1A2028365, 2015M3A9C4076 321), European Union’s Horizon 2020, Interreg. Program: NYPS 20200407, BReproUnion^, and European Union Regional Development Fund, Interreg. Oresund, BMAX4ESSFUN, LU-062^.

To acquire a deeper understanding of malignant melanoma (MM), it is essential to study the proteome of patient tissues. In particular, phosphoproteomics of MM has become of significant importance because of the central role that phosphorylation plays in the development of MM. Investigating clinical samples, however, is an extremely challenging task as there is usually only very limited quantities of material available to perform targeted enrichment approaches. Here, an automated phosphopeptide enrichment protocol using the AssayMap Bravo platform was applied to MM tissues and assessed for performance. The strategy proved to be highly-sensitive, less prone to variability, less laborious than existing techniques and adequate for starting quantities at the microgram level. An Fe(III)-NTA-IMAC-based enrichment workflow was applied to a dilution series of MM tissue lysates. The workflow was efficient in terms of sensitivity, reproducibility and phosphosite localization; and from only 12.5 μg of sample, more than 1,000 phosphopeptides were identified. In addition, from 60 μg of protein material the number of identified phosphoproteins from individual MM samples was comparable to previous reports that used extensive fractionation methods. Our data set included key pathways that are involved in MM progression; such as MAPK, melanocyte development and integrin signaling. Moreover, tissue-specific immunological proteins were identified, that have not been previously observed in the proteome of MM-derived cell lines. In conclusion, this workflow is suitable to study large cohorts of clinical samples that demand automatic and careful handling.

Glioblastoma (GBM), the most malignant of primary brain tumors, is a devastating and deadly disease, with a median survival of 14 months from diagnosis, despite standard regimens of radical brain tumor surgery, maximal safe radiation, and concomitant chemotherapy. GBM tumors nearly always re-emerge after initial treatment and frequently display resistance to current treatments. One theory that may explain GBM re-emergence is the existence of glioma stem-like cells (GSCs). We sought to identify variant protein features expressed in low passage GSCs derived from patient tumors. To this end, we developed a proteomic database that reflected variant and non-variant sequences in the human proteome, and applied a novel retrograde proteomic workflow, to identify and validate the expression of 126 protein variants in 33 glioma stem cell strains. These newly identified proteins may harbor a subset of novel protein targets for future development of GBM therapy.

Despite the maturity reached by targeted proteomic strategies, reliable and standardized protocols are urgently needed to enhance reproducibility among different laboratories and analytical platforms, facilitating a more widespread use in biomedical research. To achieve this goal, the use of dimensionless relative retention times (iRT), defined on the basis of peptide standard retention times (RT), has lately emerged as a powerful tool. The robustness, reproducibility and utility of this strategy were examined for the first time in a multicentric setting, involving 28 laboratories that included 24 of the Spanish network of proteomics laboratories (ProteoRed-ISCIII). According to the results obtained in this study, dimensionless retention time values (iRTs) demonstrated to be a useful tool for transferring and sharing peptide retention times across different chromatographic set-ups both intra- and inter-laboratories. iRT values also showed very low variability over long time periods. Furthermore, parallel quantitative analyses showed a high reproducibility despite the variety of experimental strategies used, either MRM (multiple reaction monitoring) or pseudoMRM, and the diversity of analytical platforms employed. [Biological significance]: From the very beginning of proteomics as an analytical science there has been a growing interest in developing standardized methods and experimental procedures in order to ensure the highest quality and reproducibility of the results. In this regard, the recent (2012) introduction of the dimensionless retention time concept has been a significant advance. In our multicentric (28 laboratories) study we explore the usefulness of this concept in the context of a targeted proteomics experiment, demonstrating that dimensionless retention time values is a useful tool for transferring and sharing peptide retention times across different chromatographic set-ups., All laboratories from Spain are members of ProteoRed (Plataforma de Recursos Biomoleculares y Bioinformáticos) and are supported bygrant PT13/0001 funded by Instituto de Salud Carlos III (ISCIII) andFEDER

Currently there are no clinically recognized molecular biomarkers for malignant melanoma (MM) for either diagnosing disease stage or measuring response to therapy. The aim of this feasibility study was to develop targeted selected reaction monitoring (SRM) assays for identifying candidate protein biomarkers in metastatic melanoma tissue lysate. In a pilot study applying the SRM assay, the tissue expression of nine selected proteins [complement 3 (C3), T-cell surface glycoprotein CD3 epsilon chain E (CD3E), dermatopontin, minichromosome maintenance complex component (MCM4), premelanosome protein (PMEL), S100 calcium binding protein A8 (S100A8), S100 calcium binding protein A13 (S100A13), transgelin-2 and S100B] was quantified in a small cohort of metastatic malignant melanoma patients. The SRM assay was developed using a TSQ Vantage triple quadrupole mass spectrometer that generated highly accurate peptide quantification. Repeated injection of internal standards spiked into matrix showed relative standard deviation (RSD) from 6% to 15%. All nine target proteins were identified in tumor lysate digests spiked with heavy peptide standards. The multiplex SRM peptide assay panel was then measured and quantified on a set of frozen MM tissue samples obtained from the Malignant Melanoma Biobank collected in Lund, Sweden. All nine proteins could be accurately quantified using the new SRM assay format. This study provides preliminary data on the heterogeneity of biomarker expression within MM patients. The S100B protein, which is clinically used as the pathology identifier of MM, was identified in 9 out of 10 MM tissue lysates. The use of the targeted SRM assay provides potential advancements in the diagnosis of MM that can aid in future assessments of disease in melanoma patients.

Prostate specific antigen (PSA) is a well-established tumor marker that is frequently employed as model biomarker in the development and evaluation of emerging quantitative proteomics techniques, partially as a result of wide access to commercialized immunoassays serving as “gold standards.” We designed a multiple reaction monitoring (MRM) assay to detect PSA proteoforms in clinical samples (n = 72), utilizing the specificity and sensitivity of the method. We report, for the first time, a PSA proteoform coded by SNP-L132I (rs2003783) that was observed in nine samples in both heterozygous (n = 7) and homozygous (n = 2) expression profiles. Other isoforms of PSA, derived from protein databases, were not identified by four unique proteotypic tryptic peptides. We have also utilized our MRM assay for precise quantitative analysis of PSA concentrations in both seminal and blood plasma samples. The analytical performance was evaluated, and close agreement was noted between quantitations based on three selected peptides (LSEPAELTDAVK, IVGGWECEK, and SVILLGR) and a routinely used commercialized immunoassay. Additionally, we disclose that the peptide IVGGWECEK is shared with kallikrein-related peptidase 2 and therefore is not unique for PSA. Thus, we propose the use of another tryptic sequence (SVILLGR) for accurate MRM quantification of PSA in clinical samples.

PMCID: PMC3539432; NIHMSID: NIHMS430346.-- et al., A first research development progress report of the Chromosome 19 Consortium with members from Sweden, Norway, Spain, United States, China and India, a part of the Chromosome-centric Human Proteome Project (C-HPP) global initiative, is presented (http://www.c-hpp.org). From the chromosome 19 peptide-targeted library constituting 6159 peptides, a pilot study was conducted using a subset with 125 isotope-labeled peptides. We applied an annotation strategy with triple quadrupole, ESI-Qtrap, and MALDI mass spectrometry platforms, comparing the quality of data within and in between these instrumental set-ups. LC-MS conditions were outlined by multiplex assay developments, followed by MRM assay developments. SRM was applied to biobank samples, quantifying kallikrein 3 (prostate specific antigen) in plasma from prostate cancer patients. The antibody production has been initiated for more than 1200 genes from the entire chromosome 19, and the progress developments are presented. We developed a dedicated transcript microarray to serve as the mRNA identifier by screening cancer cell lines. NAPPA protein arrays were built to align with the transcript data with the Chromosome 19 NAPPA chip, dedicated to 90 proteins, as the first development delivery. We have introduced an IT-infrastructure utilizing a LIMS system that serves as the key interface for the research teams to share and explore data generated within the project. The cross-site data repository will form the basis for sample processing, including biological samples as well as patient samples from national Biobanks. © 2012 American Chemical Society., This work was supported by grants from the Swedish Academy of Pharmaceutical Sciences who is the core founder our consortium, Swedish Research Council, the Swedish Foundation for Strategic Research, Vinnova, Ingabritt & Arne Lundbergs forskningsstiftelse, the Crafoord Foundation and by Thermo Fisher Scientific for mass spectrometry instrument support. T.E.F. is supported by the Mobilitas Program sponsored by the European Union Social Fund and administered by the Estonian Science Foundation. We gratefully acknowledge financial support to M.F. from Health Institute Carlos III of Spain (ISCIII, FIS PI02114) and M.G.-G. is supported by a PhD scholarship of ISCIII FI08/00721. C.L.N. is supported by the Cancer Prevention and Research Institute of Texas and the University of Texas Medical Branch. [11-0624]; National Cancer Institute [R33 CA 127768-03, R01CA160816, and P50-CA92629]; Sidney Kimmel Center for Prostate and Urologic Cancers; and David H. Koch through the Prostate Cancer Foundation.

Background: The Southern Swedish Malignant Melanoma (SSMM) research team is a truly cross functional group with members from oncology, clinical, surgery, bioinformatics, proteomics, and genomics initiatives. The SSMM’s objectives and goals are to develop, build and utilize cutting edge biobanks and OMICS platforms to better understand disease pathology and drug mechanisms. Within the research team there are members who daily diagnose patients with suspect melanomas, do follow-ups on malignant melanoma patients and remove primary or metastatic lesions by surgery. This inter-disciplinary clinical patient care ensures a competence build as well as a best practice procedure where the patient benefits. The science output in these resulting study outcomes further strengthens the build of healthcare benefit in the complex challenges of malignant melanoma pathophysiology that is addressed by the novel personalized medicines entering the market. These patient biobank archives will be fully automated with novel ultralow temperature biobank storage units and used as a clinical resource. Methods: Clinical materials from patients before, during and after treatments, with clinical end points are being collected. Tissue samples as well as bio-fluid samples such as blood fractions, plasma, serum and whole blood will be archived in 384-high density sample tube formats. We are developing standardized approaches for patient selections, patient sampling, sample-processing and analysis platforms with dedicated protein assays and genomics platforms that will hold value for the research community. Results: An IT-infrastructure using a laboratory information management system (LIMS) has been established, that will be the key interface for the research teams in order to share and explore data generated within the project. The cross-site data repository in Lund will form the basis for sample processing, together with biological samples in southern Sweden, including blood fractions and tumor tissues. Clinical registries are being associated with the biobank materials, including pathology reports on disease diagnosis on the MM patients. Conclusions: We provide data on the developments of protein profiling and targeted protein target assays on isolated melanoma tumors, as well as reference blood standards that is used by the team members in the respective laboratories. These pilot data show biobank access and feasibility of performing quantitative proteomics in MM biobank repositories collected in southern Sweden.