Serum Proteomics and Plasma Fibulin-3 in Differentiation of Mesothelioma From Asbestos-Exposed Controls and Patients With Other Pleural Diseases

Tsim, Selina; Alexander, Laura E. Crotty; Kelly, Caroline; Shaw, Ann; Hinsley, Samantha; Clark, Stephen W.; Evison, Matthew; Holme, Jayne; Cameron, Euan; Sharma, Davand; Wright, Angela; Grundy, Seamus; Grieve, Douglas; Ionescu, Alina; Breen, David P.; Paramasivam, Elankumaran; Psallidas, Ioannis; Mukherjee, Dipak; Chetty, Mahendran; Cox, G.; Hart-Thomas, Alan; Naseer, R.; Edwards, John; Daneshvar, Cyrus; Panchal, Rakesh; Munavvar, Mohammed; Ostroff, Rachel; Alexander, Leigh; Hall, Holly; Neilson, Matthew; Miller, Crispin; McCormick, Carol; Thomson, F.; Chalmers, Anthony J.; Maskell, Nick A; Blyth, Kevin G.

doi:10.1016/j.jtho.2021.05.018

Cited by 12 publications

(12 citation statements)

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“…Several studies have compared the expression of fibulin-3 against other candidate biomarkers in MPM, concluding that the detection of this protein alone may be insufficient to predict patient survival but can provide positive identification of MPM patients and could be useful for patient selection and stratification before treatment ( 55 – 57 ). It should be noted that fibulin-3 remains controversial as a biomarker ( 14 ), even though the original observations of circulating fibulin-3 in MPM patients in the US ( 13 ) have been validated in blinded fashion in population cohorts from Turkey ( 28 ), China ( 29 ) and Egypt ( 30 ). Accordingly, several meta-analyses have pointed out the value of fibulin-3 for positive identification of mesothelioma ( 31 – 33 ).…”

Section: Discussionmentioning

confidence: 99%

“…Fibulin-3 (gene EFEMP1 ) is an extracellular matrix (ECM) protein involved in organizing the ECM scaffold and promoting cell-ECM adhesion in normal connective tissues ( 11 , 12 ). Fibulin-3 is elevated in pleural effusions from MPM patients and has been used to distinguish these patients from normal individuals and from those who have non-malignant pleural inflammation ( 13 , 14 ). Comparative analysis of fibulin-3 and mesothelin has suggested that mesothelin correlates with MPM diagnosis more accurately than fibulin-3 but the latter could be a better prognostic factor ( 15 , 16 ).…”

Section: Introductionmentioning

confidence: 99%

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The extracellular matrix protein fibulin-3/EFEMP1 promotes pleural mesothelioma growth by activation of PI3K/Akt signaling

et al. 2022

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Malignant pleural mesothelioma (MPM) is an aggressive tumor with poor prognosis and limited therapeutic options. The extracellular matrix protein fibulin-3/EFEMP1 accumulates in the pleural effusions of MPM patients and has been proposed as a prognostic biomarker of these tumors. However, it is entirely unknown whether fibulin-3 plays a functional role on MPM growth and progression. Here, we demonstrate that fibulin-3 is upregulated in MPM tissue, promotes the malignant behavior of MPM cells, and can be targeted to reduce tumor progression. Overexpression of fibulin-3 increased the viability, clonogenic capacity and invasion of mesothelial cells, whereas fibulin-3 knockdown decreased these phenotypic traits as well as chemoresistance in MPM cells. At the molecular level, fibulin-3 activated PI3K/Akt signaling and increased the expression of a PI3K-dependent gene signature associated with cell adhesion, motility, and invasion. These pro-tumoral effects of fibulin-3 on MPM cells were disrupted by PI3K inhibition as well as by a novel, function-blocking, anti-fibulin-3 chimeric antibody. Anti-fibulin-3 antibody therapy tested in two orthotopic models of MPM inhibited fibulin-3 signaling, resulting in decreased tumor cell proliferation, reduced tumor growth, and extended animal survival. Taken together, these results demonstrate for the first time that fibulin-3 is not only a prognostic factor of MPM but also a relevant molecular target in these tumors. Further development of anti-fibulin-3 approaches are proposed to increase early detection and therapeutic impact against MPM.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The extracellular matrix protein fibulin-3/EFEMP1 promotes pleural mesothelioma growth by activation of PI3K/Akt signaling

et al. 2022

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“…By describing the variety of clinical phenotypes, it will provide insight into different disease pathways and outcomes. The repository of serial biological samples will provide a resource for exploring unanswered questions about blood and pleural biomarkers of diagnosis,28 prognostication29–34 and treatment response 35 36. Biological samples will also enable investigation into the pathological, immunological and genetic processes involved in disease evolution and progression.…”

Section: Discussionmentioning

confidence: 99%

Protocol for a prospective observational cohort study collecting data on demographics, symptoms and biomarkers in people with mesothelioma (ASSESS-meso)

et al. 2022

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IntroductionMesothelioma is a heterogeneous disease that can be challenging to monitor and prognosticate. ASSESS-meso is a multicentre, prospective, longitudinal observational cohort study of patients with mesothelioma. The primary aim is to describe different clinical phenotypes and investigate predictive and prognostic factors, including biomarkers from blood and pleural fluid. The secondary aim is to provide a resource for future trials and substudies.Methods and analysisWe aim to recruit 700 patients with a histological, cytological or clinicopathological diagnosis of mesothelioma, at any anatomical site (pleural, peritoneal, pericardial, etc). Longitudinal data will be collected, including clinical information, radiological investigations, blood tests and patient-reported outcome measures for breathlessness, chest pain and sweats. Preplanned analyses will use Cox proportional hazards method to evaluate factors associated with survival, linear and logistic regression models to investigate associations with symptoms, and analysis of variance modelling to explore changes in symptoms over time.Ethics and disseminationEthical approval has been granted by the Research Ethics Committee South West—Central Bristol (17-SW-0019) and Health Research Authority (IRAS ID 220360). A study steering committee has been established and results will be published OpenAccess in peer-reviewed journals.Trial registration numberISRCTN: 61861764.

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“…Cases were selected from two multicentre MPM biomarker studies, led by the senior author, that have recently completed recruitment (DIAPHRAGM, Diagnostic and Prognostic Biomarkers in the Rational Assessment of Mesothelioma 17 and PRISM, Prediction of Resistance to chemotherapy using Somatic Copy Number Variation in Mesothelioma 18 ). DIAPHRAGM prospectively recruited 649 patients at presentation for evaluation of diagnostic blood biomarkers, 152 of whom were diagnosed with MPM.…”

Section: Methodsmentioning

confidence: 99%

Fully automated volumetric measurement of malignant pleural mesothelioma by deep learning AI: validation and comparison with modified RECIST response criteria

Kidd

Anderson

Cowell

et al. 2022

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BackgroundIn malignant pleural mesothelioma (MPM), complex tumour morphology results in inconsistent radiological response assessment. Promising volumetric methods require automation to be practical. We developed a fully automated Convolutional Neural Network (CNN) for this purpose, performed blinded validation and compared CNN and human response classification and survival prediction in patients treated with chemotherapy.MethodsIn a multicentre retrospective cohort study; 183 CT datasets were split into training and internal validation (123 datasets (80 fully annotated); 108 patients; 1 centre) and external validation (60 datasets (all fully annotated); 30 patients; 3 centres). Detailed manual annotations were used to train the CNN, which used two-dimensional U-Net architecture. CNN performance was evaluated using correlation, Bland-Altman and Dice agreement. Volumetric response/progression were defined as ≤30%/≥20% change and compared with modified Response Evaluation Criteria In Solid Tumours (mRECIST) by Cohen’s kappa. Survival was assessed using Kaplan-Meier methodology.ResultsHuman and artificial intelligence (AI) volumes were strongly correlated (validation set r=0.851, p<0.0001). Agreement was strong (validation set mean bias +31 cm3 (p=0.182), 95% limits 345 to +407 cm3). Infrequent AI segmentation errors (4/60 validation cases) were associated with fissural tumour, contralateral pleural thickening and adjacent atelectasis. Human and AI volumetric responses agreed in 20/30 (67%) validation cases κ=0.439 (0.178 to 0.700). AI and mRECIST agreed in 16/30 (55%) validation cases κ=0.284 (0.026 to 0.543). Higher baseline tumour volume was associated with shorter survival.ConclusionWe have developed and validated the first fully automated CNN for volumetric MPM segmentation. CNN performance may be further improved by enriching future training sets with morphologically challenging features. Volumetric response thresholds require further calibration in future studies.

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Serum Proteomics and Plasma Fibulin-3 in Differentiation of Mesothelioma From Asbestos-Exposed Controls and Patients With Other Pleural Diseases

Cited by 12 publications

References 33 publications

The extracellular matrix protein fibulin-3/EFEMP1 promotes pleural mesothelioma growth by activation of PI3K/Akt signaling

The extracellular matrix protein fibulin-3/EFEMP1 promotes pleural mesothelioma growth by activation of PI3K/Akt signaling

Protocol for a prospective observational cohort study collecting data on demographics, symptoms and biomarkers in people with mesothelioma (ASSESS-meso)

Fully automated volumetric measurement of malignant pleural mesothelioma by deep learning AI: validation and comparison with modified RECIST response criteria

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