Nivolumab reaches brain lesions in patients with recurrent glioblastoma and induces T-cell activity and upregulation of checkpoint pathways.

Glioblastoma (GBM) is an aggressive brain tumor with poor prognosis. Although immunotherapy is being explored as a potential treatment option for patients with GBM, it is unclear whether systemic immunotherapy can reach and modify the tumor microenvironment in the brain. We evaluated immune characteristics in patients receiving the anti-PD1 immune checkpoint inhibitor Nivolumab one week prior to surgery, compared to control patients receiving salvage resection without prior Nivolumab treatment. We observed saturating levels of Nivolumab bound to intratumorally- and tissue-resident T cells in the brain, implicating saturating levels of Nivolumab reaching brain tumors. Following Nivolumab treatment, significant changes in T-cell activation and proliferation were observed in the tumor resident T-cell population, and peripheral T cells upregulated chemokine receptors related to brain homing. A strong Nivolumab-driven upregulation in compensatory checkpoint inhibition molecules, TIGIT, LAG-3, TIM-3 and CTLA-4 was observed, potentially counteracting the treatment effect. Finally, tumor-reactive tumor-infiltrating lymphocytes (TILs) were found in a subset of Nivolumab-treated patients with prolonged survival, and neoantigen-reactive T cells were identified in both TILs and blood. This indicates a systemic response towards GBM in a subset of patients, which was further boosted by Nivolumab, with T-cell responses towards tumor-derived neoantigens. Our study demonstrates that Nivolumab does reach the GBM tumor lesion and enhances antitumor T-cell responses both intratumorally and systemically. However, various anti-inflammatory mechanisms mitigate the clinical efficacy of the anti-PD1 treatment.

The NSP3 protein of SARS-CoV-2 binds fragile X mental retardation proteins to disrupt UBAP2L interactions.

Viruses interact with numerous host factors to facilitate viral replication and to dampen antiviral defense mechanisms. We currently have a limited mechanistic understanding of how SARS-CoV-2 binds host factors and the functional role of these interactions. Here, we uncover a novel interaction between the viral NSP3 protein and the fragile X mental retardation proteins (FMRPs: FMR1, FXR1-2). SARS-CoV-2 NSP3 mutant viruses preventing FMRP binding have attenuated replication in vitro and reduced levels of viral antigen in lungs during the early stages of infection. We show that a unique peptide motif in NSP3 binds directly to the two central KH domains of FMRPs and that this interaction is disrupted by the I304N mutation found in a patient with fragile X syndrome. NSP3 binding to FMRPs disrupts their interaction with the stress granule component UBAP2L through direct competition with a peptide motif in UBAP2L to prevent FMRP incorporation into stress granules. Collectively, our results provide novel insight into how SARS-CoV-2 hijacks host cell proteins and provides molecular insight into the possible underlying molecular defects in fragile X syndrome.

SARS-CoV-2 hijacks fragile X mental retardation proteins for efficient infection.

Viruses interact with numerous host factors to facilitate viral replication and to dampen antiviral defense mechanisms. We currently have a limited mechanistic understanding of how SARS-CoV-2 binds host factors and the functional role of these interactions. Here, we uncover a novel interaction between the viral NSP3 protein and the fragile X mental retardation proteins (FMRPs: FMR1 and FXR1-2). SARS-CoV-2 NSP3 mutant viruses preventing FMRP binding have attenuated replication in vitro and have delayed disease onset in vivo. We show that a unique peptide motif in NSP3 binds directly to the two central KH domains of FMRPs and that this interaction is disrupted by the I304N mutation found in a patient with fragile X syndrome. NSP3 binding to FMRPs disrupts their interaction with the stress granule component UBAP2L through direct competition with a peptide motif in UBAP2L to prevent FMRP incorporation into stress granules. Collectively, our results provide novel insight into how SARS-CoV-2 hijacks host cell proteins for efficient infection and provides molecular insight to the possible underlying molecular defects in fragile X syndrome.

Foresight in clinical proteomics: current status, ethical considerations, and future perspectives.

With the advent of robust and high-throughput mass spectrometric technologies and bioinformatics tools to analyze large data sets, proteomics has penetrated broadly into basic and translational life sciences research. More than 95% of FDA-approved drugs currently target proteins, and most diagnostic tests are protein-based. The introduction of proteomics to the clinic, for instance to guide patient stratification and treatment, is already ongoing. Importantly, ethical challenges come with this success, which must also be adequately addressed by the proteomics and medical communities. Consortium members of the H2020 European Union-funded proteomics initiative: European Proteomics Infrastructure Consortium-providing access (EPIC-XS) met at the Core Technologies for Life Sciences (CTLS) conference to discuss the emerging role and implementation of proteomics in the clinic. The discussion, involving leaders in the field, focused on the current status, related challenges, and future efforts required to make proteomics a more mainstream technology for translational and clinical research. Here we report on that discussion and provide an expert update concerning the feasibility of clinical proteomics, the ethical implications of generating and analyzing large-scale proteomics clinical data, and recommendations to ensure both ethical and effective implementation in real-world applications.

Organ-specific metabolic pathways distinguish prediabetes, type 2 diabetes, and normal tissues.

Environmental and genetic factors cause defects in pancreatic islets driving type 2 diabetes (T2D) together with the progression of multi-tissue insulin resistance. Mass spectrometry proteomics on samples from five key metabolic tissues of a cross-sectional cohort of 43 multi-organ donors provides deep coverage of their proteomes. Enrichment analysis of Gene Ontology terms provides a tissue-specific map of altered biological processes across healthy, prediabetes (PD), and T2D subjects. We find widespread alterations in several relevant biological pathways, including increase in hemostasis in pancreatic islets of PD, increase in the complement cascade in liver and pancreatic islets of PD, and elevation in cholesterol biosynthesis in liver of T2D. Our findings point to inflammatory, immune, and vascular alterations in pancreatic islets in PD that are hypotheses to be tested for potential contributions to hormonal perturbations such as impaired insulin and increased glucagon production. This multi-tissue proteomic map suggests tissue-specific metabolic dysregulations in T2D.

A knowledge graph to interpret clinical proteomics data.

Implementing precision medicine hinges on the integration of omics data, such as proteomics, into the clinical decision-making process, but the quantity and diversity of biomedical data, and the spread of clinically relevant knowledge across multiple biomedical databases and publications, pose a challenge to data integration. Here we present the Clinical Knowledge Graph (CKG), an open-source platform currently comprising close to 20 million nodes and 220 million relationships that represent relevant experimental data, public databases and literature. The graph structure provides a flexible data model that is easily extendable to new nodes and relationships as new databases become available. The CKG incorporates statistical and machine learning algorithms that accelerate the analysis and interpretation of typical proteomics workflows. Using a set of proof-of-concept biomarker studies, we show how the CKG might augment and enrich proteomics data and help inform clinical decision-making.

Multiomic characterization of oncogenic signaling mediated by wild-type and mutant RIT1.

Aberrant activation of the RAS family of guanosine triphosphatases (GTPases) is prevalent in lung adenocarcinoma, with somatic mutation of KRAS occurring in ~30% of tumors. We previously identified somatic mutations and amplifications of the gene encoding RAS family GTPase RIT1 in lung adenocarcinomas. To explore the biological pathways regulated by RIT1 and how they relate to the oncogenic KRAS network, we performed quantitative proteomic, phosphoproteomic, and transcriptomic profiling of isogenic lung epithelial cells in which we ectopically expressed wild-type or cancer-associated variants of RIT1 and KRAS. We found that both mutant KRAS and mutant RIT1 promoted canonical RAS signaling and that overexpression of wild-type RIT1 partially phenocopied oncogenic RIT1 and KRAS, including induction of epithelial-to-mesenchymal transition. Our findings suggest that RIT1 protein abundance is a factor in its pathogenic function. Therefore, chromosomal amplification of wild-type RIT1 in lung and other cancers may be tumorigenic.

A highly multiplexed quantitative phosphosite assay for biology and preclinical studies.

Reliable methods to quantify dynamic signaling changes across diverse pathways are needed to better understand the effects of disease and drug treatment in cells and tissues but are presently lacking. Here, we present SigPath, a targeted mass spectrometry (MS) assay that measures 284 phosphosites in 200 phosphoproteins of biological interest. SigPath probes a broad swath of signaling biology with high throughput and quantitative precision. We applied the assay to investigate changes in phospho-signaling in drug-treated cancer cell lines, breast cancer preclinical models, and human medulloblastoma tumors. In addition to validating previous findings, SigPath detected and quantified a large number of differentially regulated phosphosites newly associated with disease models and human tumors at baseline or with drug perturbation. Our results highlight the potential of SigPath to monitor phosphoproteomic signaling events and to nominate mechanistic hypotheses regarding oncogenesis, response, and resistance to therapy.

Expression of GNAZ, encoding the Gαz protein, predicts survival in mantle cell lymphoma.

Mantle cell lymphoma (MCL), a malignancy of B-lymphocytes, has a poor prognosis. It is thus necessary to improve the understanding of the pathobiology of MCL and identify factors contributing to its aggressiveness. Our studies, based on Affymetrix data from 17 MCL biopsies, real-time quantitative polymerase chain reaction data from 18 sorted primary MCL cells and 108 MCL biopsies compared to non-malignant tissue, reveals that GNAZ expression predicts poor clinical outcome of MCL patients (Cox regression, P = 0·014) and lymphocytosis (Mann-Whitney, P = 0·011). We show that GNAZ translates to Gαz protein - a signalling molecule within the G-protein coupled receptor network. Our findings suggest that GNAZ/Gαz contribute to the MCL pathobiology.

A Curated Resource for Phosphosite-specific Signature Analysis.

Signaling pathways are orchestrated by post-translational modifications (PTMs) such as phosphorylation. However, pathway analysis of PTM data sets generated by mass spectrometry (MS)-based proteomics is typically performed at a gene-centric level because of the lack of appropriately curated PTM signature databases and bioinformatic tools that leverage PTM site-specific information. Here we present the first version of PTMsigDB, a database of modification site-specific signatures of perturbations, kinase activities and signaling pathways curated from more than 2,500 publications. We adapted the widely used single sample Gene Set Enrichment Analysis approach to utilize PTMsigDB, enabling PTMSignature Enrichment Analysis (PTM-SEA) of quantitative MS data. We used a well-characterized data set of epidermal growth factor (EGF)-perturbed cancer cells to evaluate our approach and demonstrated better representation of signaling events compared with gene-centric methods. We then applied PTM-SEA to analyze the phosphoproteomes of cancer cells treated with cell-cycle inhibitors and detected mechanism-of-action specific signatures of cell cycle kinases. We also applied our methods to analyze the phosphoproteomes of PI3K-inhibited human breast cancer cells and detected signatures of compounds inhibiting PI3K as well as targets downstream of PI3K (AKT, MAPK/ERK) covering a substantial fraction of the PI3K pathway. PTMsigDB and PTM-SEA can be freely accessed at https://github.com/broadinstitute/ssGSEA2.0.

Proteomics, Post-translational Modifications, and Integrative Analyses Reveal Molecular Heterogeneity within Medulloblastoma Subgroups.

There is a pressing need to identify therapeutic targets in tumors with low mutation rates such as the malignant pediatric brain tumor medulloblastoma. To address this challenge, we quantitatively profiled global proteomes and phospho-proteomes of 45 medulloblastoma samples. Integrated analyses revealed that tumors with similar RNA expression vary extensively at the post-transcriptional and post-translational levels. We identified distinct pathways associated with two subsets of SHH tumors, and found post-translational modifications of MYC that are associated with poor outcomes in group 3 tumors. We found kinases associated with subtypes and showed that inhibiting PRKDC sensitizes MYC-driven cells to radiation. Our study shows that proteomics enables a more comprehensive, functional readout, providing a foundation for future therapeutic strategies.

Reproducible workflow for multiplexed deep-scale proteome and phosphoproteome analysis of tumor tissues by liquid chromatography-mass spectrometry.

Here we present an optimized workflow for global proteome and phosphoproteome analysis of tissues or cell lines that uses isobaric tags (TMT (tandem mass tags)-10) for multiplexed analysis and relative quantification, and provides 3× higher throughput than iTRAQ (isobaric tags for absolute and relative quantification)-4-based methods with high intra- and inter-laboratory reproducibility. The workflow was systematically characterized and benchmarked across three independent laboratories using two distinct breast cancer subtypes from patient-derived xenograft models to enable assessment of proteome and phosphoproteome depth and quantitative reproducibility. Each plex consisted of ten samples, each being 300 µg of peptide derived from <50 mg of wet-weight tissue. Of the 10,000 proteins quantified per sample, we could distinguish 7,700 human proteins derived from tumor cells and 3100 mouse proteins derived from the surrounding stroma and blood. The maximum deviation across replicates and laboratories was <7%, and the inter-laboratory correlation for TMT ratio-based comparison of the two breast cancer subtypes was r > 0.88. The maximum deviation for the phosphoproteome coverage was <24% across laboratories, with an average of >37,000 quantified phosphosites per sample and differential quantification correlations of r > 0.72. The full procedure, including sample processing and data generation, can be completed within 10 d for ten tissue samples, and 100 samples can be analyzed in ~4 months using a single LC-MS/MS instrument. The high quality, depth, and reproducibility of the data obtained both within and across laboratories should enable new biological insights to be obtained from mass spectrometry-based proteomics analyses of cells and tissues together with proteogenomic data integration.

Mass Spectrometry-Based Proteomics Reveals Potential Roles of NEK9 and MAP2K4 in Resistance to PI3K Inhibition in Triple-Negative Breast Cancers.

Activation of PI3K signaling is frequently observed in triple-negative breast cancer (TNBC), yet PI3K inhibitors have shown limited clinical activity. To investigate intrinsic and adaptive mechanisms of resistance, we analyzed a panel of patient-derived xenograft models of TNBC with varying responsiveness to buparlisib, a pan-PI3K inhibitor. In a subset of patient-derived xenografts, resistance was associated with incomplete inhibition of PI3K signaling and upregulated MAPK/MEK signaling in response to buparlisib. Outlier phosphoproteome and kinome analyses identified novel candidates functionally important to buparlisib resistance, including NEK9 and MAP2K4. Knockdown of NEK9 or MAP2K4 reduced both baseline and feedback MAPK/MEK signaling and showed synthetic lethality with buparlisib in vitro A complex in/del frameshift in PIK3CA decreased sensitivity to buparlisib via NEK9/MAP2K4-dependent mechanisms. In summary, our study supports a role for NEK9 and MAP2K4 in mediating buparlisib resistance and demonstrates the value of unbiased omic analyses in uncovering resistance mechanisms to targeted therapy.Significance: Integrative phosphoproteogenomic analysis is used to determine intrinsic resistance mechanisms of triple-negative breast tumors to PI3K inhibition. Cancer Res; 78(10); 2732-46. ©2018 AACR.

Integrated multi-omic analysis of host-microbiota interactions in acute oak decline.

BACKGROUND: Britain's native oak species are currently under threat from acute oak decline (AOD), a decline-disease where stem bleeds overlying necrotic lesions in the inner bark and larval galleries of the bark-boring beetle, Agrilus biguttatus, represent the primary symptoms. It is known that complex interactions between the plant host and its microbiome, i.e. the holobiont, significantly influence the health status of the plant. In AOD, necrotic lesions are caused by a microbiome shift to a pathobiome consisting predominantly of Brenneria goodwinii, Gibbsiella quercinecans, Rahnella victoriana and potentially other bacteria. However, the specific mechanistic processes of the microbiota causing tissue necrosis, and the host response, have not been established and represent a barrier to understanding and managing this decline. RESULTS: We profiled the metagenome, metatranscriptome and metaproteome of inner bark tissue from AOD symptomatic and non-symptomatic trees to characterise microbiota-host interactions. Active bacterial virulence factors such as plant cell wall-degrading enzymes, reactive oxygen species defence and flagella in AOD lesions, along with host defence responses including reactive oxygen species, cell wall modification and defence regulators were identified. B. goodwinii dominated the lesion microbiome, with significant expression of virulence factors such as the phytopathogen effector avrE. A smaller proportion of microbiome activity was attributed to G. quercinecans and R. victoriana. In addition, we describe for the first time the potential role of two previously uncharacterised Gram-positive bacteria predicted from metagenomic binning and identified as active in the AOD lesion metatranscriptome and metaproteome, implicating them in lesion formation. CONCLUSIONS: This multi-omic study provides novel functional insights into microbiota-host interactions in AOD, a complex arboreal decline disease where polymicrobial-host interactions result in lesion formation on tree stems. We present the first descriptions of holobiont function in oak health and disease, specifically, the relative lesion activity of B. goodwinii, G. quercinecans, Rahnella victoriana and other bacteria. Thus, the research presented here provides evidence of some of the mechanisms used by members of the lesion microbiome and a template for future multi-omic research into holobiont characterisation, plant polymicrobial diseases and pathogen defence in trees.

Molecular targets and signaling pathways regulated by nuclear translocation of syndecan-1.

BACKGROUND: The cell-surface heparan sulfate proteoglycan syndecan-1 is important for tumor cell proliferation, migration, and cell cycle regulation in a broad spectrum of malignancies. Syndecan-1, however, also translocates to the cell nucleus, where it might regulate various molecular functions. RESULTS: We used a fibrosarcoma model to dissect the functions of syndecan-1 related to the nucleus and separate them from functions related to the cell-surface. Nuclear translocation of syndecan-1 hampered the proliferation of fibrosarcoma cells compared to the mutant lacking nuclear localization signal. The growth inhibitory effect of nuclear syndecan-1 was accompanied by significant accumulation of cells in the G0/G1 phase, which indicated a possible G1/S phase arrest. We implemented multiple, unsupervised global transcriptome and proteome profiling approaches and combined them with functional assays to disclose the molecular mechanisms that governed nuclear translocation and its related functions. We identified genes and pathways related to the nuclear compartment with network enrichment analysis of the transcriptome and proteome. The TGF-ß pathway was activated by nuclear syndecan-1, and three genes were significantly altered with the deletion of nuclear localization signal: EGR-1 (early growth response 1), NEK11 (never-in-mitosis gene a-related kinase 11), and DOCK8 (dedicator of cytokinesis 8). These candidate genes were coupled to growth and cell-cycle regulation. Nuclear translocation of syndecan-1 influenced the activity of several other transcription factors, including E2F, NFκß, and OCT-1. The transcripts and proteins affected by syndecan-1 showed a striking overlap in their corresponding biological processes. These processes were dominated by protein phosphorylation and post-translation modifications, indicative of alterations in intracellular signaling. In addition, we identified molecules involved in the known functions of syndecan-1, including extracellular matrix organization and transmembrane transport. CONCLUSION: Collectively, abrogation of nuclear translocation of syndecan-1 resulted in a set of changes clustering in distinct patterns, which highlighted the functional importance of nuclear syndecan-1 in hampering cell proliferation and the cell cycle. This study emphasizes the importance of the localization of syndecan-1 when considering its effects on tumor cell fate.

Fast type I interferon response protects astrocytes from flavivirus infection and virus-induced cytopathic effects.

BACKGROUND: Neurotropic flaviviruses such as tick-borne encephalitis virus (TBEV), Japanese encephalitis virus (JEV), West Nile virus (WNV), and Zika virus (ZIKV) are causative agents of severe brain-related diseases including meningitis, encephalitis, and microcephaly. We have previously shown that local type I interferon response within the central nervous system (CNS) is involved in the protection of mice against tick-borne flavivirus infection. However, the cells responsible for mounting this protective response are not defined. METHODS: Primary astrocytes were isolated from wild-type (WT) and interferon alpha receptor knock out (IFNAR-/-) mice and infected with neurotropic flaviviruses. Viral replication and spread, IFN induction and response, and cellular viability were analyzed. Transcriptional levels in primary astrocytes treated with interferon or supernatant from virus-infected cells were analyzed by RNA sequencing and evaluated by different bioinformatics tools. RESULTS: Here, we show that astrocytes control viral replication of different TBEV strains, JEV, WNV, and ZIKV. In contrast to fibroblast, astrocytes mount a rapid interferon response and restrict viral spread. Furthermore, basal expression levels of key interferon-stimulated genes are high in astrocytes compared to mouse embryonic fibroblasts. Bioinformatic analysis of RNA-sequencing data reveals that astrocytes have established a basal antiviral state which contributes to the rapid viral recognition and upregulation of interferons. The most highly upregulated pathways in neighboring cells were linked to type I interferon response and innate immunity. The restriction in viral growth was dependent on interferon signaling, since loss of the interferon receptor, or its blockade in wild-type cells, resulted in high viral replication and virus-induced cytopathic effects. Astrocyte supernatant from TBEV-infected cells can restrict TBEV growth in astrocytes already 6 h post infection, the effect on neurons is highly reinforced, and astrocyte supernatant from 3 h post infection is already protective. CONCLUSIONS: These findings suggest that the combination of an intrinsic constitutive antiviral response and the fast induction of type I IFN production by astrocytes play an important role in self-protection of astrocytes and suppression of flavivirus replication in the CNS.

Proteogenomics connects somatic mutations to signalling in breast cancer.

Somatic mutations have been extensively characterized in breast cancer, but the effects of these genetic alterations on the proteomic landscape remain poorly understood. Here we describe quantitative mass-spectrometry-based proteomic and phosphoproteomic analyses of 105 genomically annotated breast cancers, of which 77 provided high-quality data. Integrated analyses provided insights into the somatic cancer genome including the consequences of chromosomal loss, such as the 5q deletion characteristic of basal-like breast cancer. Interrogation of the 5q trans-effects against the Library of Integrated Network-based Cellular Signatures, connected loss of CETN3 and SKP1 to elevated expression of epidermal growth factor receptor (EGFR), and SKP1 loss also to increased SRC tyrosine kinase. Global proteomic data confirmed a stromal-enriched group of proteins in addition to basal and luminal clusters, and pathway analysis of the phosphoproteome identified a G-protein-coupled receptor cluster that was not readily identified at the mRNA level. In addition to ERBB2, other amplicon-associated highly phosphorylated kinases were identified, including CDK12, PAK1, PTK2, RIPK2 and TLK2. We demonstrate that proteogenomic analysis of breast cancer elucidates the functional consequences of somatic mutations, narrows candidate nominations for driver genes within large deletions and amplified regions, and identifies therapeutic targets.

Diagnostic and prognostic value of soluble syndecan-1 in pleural malignancies.

BACKGROUND: The distinction between malignant and benign pleural effusions is a diagnostic challenge today and measuring soluble biomarkers could add to the diagnostic accuracy. Syndecan-1 is a proteoglycan involved in various cellular functions and is cleaved from the cell surface in a regulated manner. The shed fragment, which can be recovered in effusion supernatant and in serum, retains its binding capacities, but often with different functions and signalling properties than the cell-bound form. AIM: This study aimed to investigate the diagnostic and prognostic value of soluble syndecan-1 in pleural effusions and sera from patients with pleural malignancies. STUDY DESIGN: Using two cohorts of patients, we assessed the diagnostic and prognostic value of soluble syndecan-1 in pleural effusions and sera, using enzyme-linked immunosorbent assays. RESULTS: In pleural effusions, syndecan-1 distinguished malignant and benign diseases, with an odds ratio of 8.59 (95% CI 3.67 to 20.09). Furthermore, syndecan-1 in pleural effusions predicted a survival difference for patients with pleural metastatic disease and malignant mesothelioma of 11.2 and 9.2 months, respectively. However, no such effects were seen when syndecan-1 was measured in serum. CONCLUSION: Soluble syndecan-1 is a promising candidate biomarker for the cytopathological diagnosis and prognostication of malignant pleural effusions.

Proteome screening of pleural effusions identifies galectin 1 as a diagnostic biomarker and highlights several prognostic biomarkers for malignant mesothelioma.

Malignant mesothelioma is an aggressive asbestos-induced cancer, and affected patients have a median survival of approximately one year after diagnosis. It is often difficult to reach a conclusive diagnosis, and ancillary measurements of soluble biomarkers could increase diagnostic accuracy. Unfortunately, few soluble mesothelioma biomarkers are suitable for clinical application. Here we screened the effusion proteomes of mesothelioma and lung adenocarcinoma patients to identify novel soluble mesothelioma biomarkers. We performed quantitative mass-spectrometry-based proteomics using isobaric tags for quantification and used narrow-range immobilized pH gradient/high-resolution isoelectric focusing (pH 4-4.25) prior to analysis by means of nano liquid chromatography coupled to MS/MS. More than 1,300 proteins were identified in pleural effusions from patients with malignant mesothelioma (n = 6), lung adenocarcinoma (n = 6), or benign mesotheliosis (n = 7). Data are available via ProteomeXchange with identifier PXD000531. The identified proteins included a set of known mesothelioma markers and proteins that regulate hallmarks of cancer such as invasion, angiogenesis, and immune evasion, plus several new candidate proteins. Seven candidates (aldo-keto reductase 1B10, apolipoprotein C-I, galectin 1, myosin-VIIb, superoxide dismutase 2, tenascin C, and thrombospondin 1) were validated by enzyme-linked immunosorbent assays in a larger group of patients with mesothelioma (n = 37) or metastatic carcinomas (n = 25) and in effusions from patients with benign, reactive conditions (n = 16). Galectin 1 was identified as overexpressed in effusions from lung adenocarcinoma relative to mesothelioma and was validated as an excellent predictor for metastatic carcinomas against malignant mesothelioma. Galectin 1, aldo-keto reductase 1B10, and apolipoprotein C-I were all identified as potential prognostic biomarkers for malignant mesothelioma. This analysis of the effusion proteome furthers our understanding of malignant mesothelioma, identified galectin 1 as a potential diagnostic biomarker, and highlighted several possible prognostic biomarkers of this disease.

Hyaluronan and N-ERC/mesothelin as key biomarkers in a specific two-step model to predict pleural malignant mesothelioma.

PURPOSE: Diagnosis of malignant mesothelioma is challenging. The first available diagnostic material is often an effusion and biochemical analysis of soluble markers may provide additional diagnostic information. This study aimed to establish a predictive model using biomarkers from pleural effusions, to allow early and accurate diagnosis. PATIENTS AND METHODS: Effusions were collected prospectively from 190 consecutive patients at a regional referral centre. Hyaluronan, N-ERC/mesothelin, C-ERC/mesothelin, osteopontin, syndecan-1, syndecan-2, and thioredoxin were measured using ELISA and HPLC. A predictive model was generated and validated using a second prospective set of 375 effusions collected consecutively at a different referral centre. RESULTS: Biochemical markers significantly associated with mesothelioma were hyaluronan (odds ratio, 95% CI: 8.82, 4.82-20.39), N-ERC/mesothelin (4.81, 3.19-7.93), CERC/mesothelin (3.58, 2.43-5.59) and syndecan-1 (1.34, 1.03-1.77). A two-step model using hyaluronan and N-ERC/mesothelin, and combining a threshold decision rule with logistic regression, yielded good discrimination with an area under the ROC curve of 0.99 (95% CI: 0.97-1.00) in the model generation dataset and 0.83 (0.74-0.91) in the validation dataset, respectively. CONCLUSIONS: A two-step model using hyaluronan and N-ERC/mesothelin predicts mesothelioma with high specificity. This method can be performed on the first available effusion and could be a useful adjunct to the morphological diagnosis of mesothelioma.