Dataset Information

Tasks and Experiences of the Prospective, Longitudinal, Multicenter MoMar (Molecular Markers) Study for the Early Detection of Mesothelioma in Individuals Formerly Exposed to Asbestos Using Liquid Biopsies.

ABSTRACT: Mesothelioma is an aggressive cancer, strongly associated with prior exposure to asbestos. Commonly, tumors are detected at late stages of the disease. Detection at early stages might be meaningful, because therapies might be more effective when the tumor burden is relatively low and the tumor has not spread to distant sites. Circulating biomarkers in blood might be a promising tool to improve the early detection of mesothelioma, but for screening in asymptomatic subjects, candidate biomarkers need to be validated in appropriate studies. This study was conducted to assess the performance of biomarkers in liquid biopsies to detect mesothelioma at early stages. Over a period of 10 years, 2769 volunteers formerly exposed to asbestos were annually examined and liquid biopsies were collected. A follow-up was completed 17 months after the last blood collection. The article provides a detailed overview of our lessons learned and experiences of conducting a prospective, longitudinal, multicenter study. The existing cohort of individuals at risk is highly suitable for the validation of blood-based biomarkers for the early detection of mesothelioma as well as lung cancer.

SUBMITTER: Weber DG

PROVIDER: S-EPMC10742125 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Tasks and Experiences of the Prospective, Longitudinal, Multicenter MoMar (Molecular Markers) Study for the Early Detection of Mesothelioma in Individuals Formerly Exposed to Asbestos Using Liquid Biopsies.

Weber Daniel Gilbert DG Casjens Swaantje S Wichert Katharina K Lehnert Martin M Taeger Dirk D Rihs Hans-Peter HP Brüning Thomas T Johnen Georg G The MoMar Study Group

Cancers 20231218 24

Mesothelioma is an aggressive cancer, strongly associated with prior exposure to asbestos. Commonly, tumors are detected at late stages of the disease. Detection at early stages might be meaningful, because therapies might be more effective when the tumor burden is relatively low and the tumor has not spread to distant sites. Circulating biomarkers in blood might be a promising tool to improve the early detection of mesothelioma, but for screening in asymptomatic subjects, candidate biomarkers n ...[more]

PMID: 38136442

Similar Datasets

Project description:BackgroundMalignant pleural mesothelioma (MM) is an aggressive, asbestos-related pulmonary cancer that is increasing in incidence. Because diagnosis is difficult and the disease is relatively rare, most patients present at a clinically advanced stage where possibility of cure is minimal. To improve surveillance and detection of MM in the high-risk population, we completed a series of clinical studies to develop a noninvasive test for early detection.Methodology/principal findingsWe conducted multi-center case-control studies in serum from 117 MM cases and 142 asbestos-exposed control individuals. Biomarker discovery, verification, and validation were performed using SOMAmer proteomic technology, which simultaneously measures over 1000 proteins in unfractionated biologic samples. Using univariate and multivariate approaches we discovered 64 candidate protein biomarkers and derived a 13-marker random forest classifier with an AUC of 0.99±0.01 in training, 0.98±0.04 in independent blinded verification and 0.95±0.04 in blinded validation studies. Sensitivity and specificity at our pre-specified decision threshold were 97%/92% in training and 90%/95% in blinded verification. This classifier accuracy was maintained in a second blinded validation set with a sensitivity/specificity of 90%/89% and combined accuracy of 92%. Sensitivity correlated with pathologic stage; 77% of Stage I, 93% of Stage II, 96% of Stage III and 96% of Stage IV cases were detected. An alternative decision threshold in the validation study yielding 98% specificity would still detect 60% of MM cases. In a paired sample set the classifier AUC of 0.99 and 91%/94% sensitivity/specificity was superior to that of mesothelin with an AUC of 0.82 and 66%/88% sensitivity/specificity. The candidate biomarker panel consists of both inflammatory and proliferative proteins, processes strongly associated with asbestos-induced malignancy.SignificanceThe SOMAmer biomarker panel discovered and validated in these studies provides a solid foundation for surveillance and diagnosis of MM in those at highest risk for this disease.

Project description:The analysis of tumours using biomarkers in blood is transforming cancer diagnosis and therapy. Cancers are characterised by evolving genetic alterations, making it difficult to develop reliable and broadly applicable DNA-based biomarkers for liquid biopsy. In contrast to the variability in gene mutations, the methylation pattern remains generally constant during carcinogenesis. Thus, methylation more than mutation analysis may be exploited to recognise tumour features in the blood of patients. In this work, we investigated the possibility of using global CpG (CpG means a CG motif in the context of methylation. The p represents the phosphate. This is used to distinguish CG sites meant for methylation from other CG motifs or from mentions of CG content) island methylation profiles as a basis for the prediction of cancer state of patients utilising liquid biopsy samples. We retrieved existing GEO methylation datasets on hepatocellular carcinoma (HCC) and cell-free DNA (cfDNA) from HCC patients and healthy donors, as well as healthy whole blood and purified peripheral blood mononuclear cell (PBMC) samples, and used a random forest classifier as a predictor. Additionally, we tested three different feature selection techniques in combination. When using cfDNA samples together with solid tumour samples and healthy blood samples of different origin, we could achieve an average accuracy of 0.98 in a 10-fold cross-validation. In this setting, all the feature selection methods we tested in this work showed promising results. We could also show that it is possible to use solid tumour samples and purified PBMCs as a training set and correctly predict a cfDNA sample as cancerous or healthy. In contrast to the complete set of samples, the feature selections led to varying results of the respective random forests. ANOVA feature selection worked well with this training set, and the selected features allowed the random forest to predict all cfDNA samples correctly. Feature selection based on mutual information could also lead to better than random results, but LASSO feature selection would not lead to a confident prediction. Our results show the relevance of CpG islands as tumour markers in blood.

Project description:ObjectivesThe knowledge of past asbestos exposure may lead to chronic psychological strain. In addition, the information about an increased cancer risk can place a psychological burden on individuals triggering mental health symptoms of depression or anxiety. This applies in particular to individuals with non-malignant asbestos-related disease (ARD) such as lung fibrosis and pleural thickening with or without lung function impairment. ARDs with or without lung function impairment may develop even years after exposure cessation. Therefore, the aim of the present study was to test for our cohort whether non-malignant ARD and lung function impairment have differential effects on mental health and psychological strain.DesignCross-sectional study.Participants and settingOverall, 612 male participants (mean age=66.2 years, SD=9.5) attending a surveillance programme for ARDs received routine examinations including lung function testing (24% refused to fill in the psychological questionnaire) at a German university hospital study centre from August 2008 to August 2013.Outcome measuresUsing multiple hierarchical regression analysis, ARD diagnosis and lung function impairment were used to predict psychological health as measured with validated questionnaires for depression and anxiety. Psychological strain was operationalised by intrusive thoughts and specific fear of cancer.ResultsThe strongest predictor for mental health was obstructive functional impairment (eg, anxiety: β=0.22, p<0.001). Psychological strain was predicted by the presence of a non-malignant ARD (eg, intrusive thoughts: β=0.17, p=0.003).ConclusionsThe presence of mental health symptoms is associated with ventilation disturbances, whereas the knowledge of an already initiated morphological change-caused by asbestos exposure-is primarily associated with psychological strain. Specifically, the affected individuals are more prone to intrusive thoughts and specific fear of asbestos-related cancer. As an implication, physicians should be sensitised about possible consequences of risk communication and functional impairment to counteract excessive fear or anxiety.

Project description:IntroductionMalignant pleural mesothelioma (MPM) is difficult to diagnose. An accurate blood biomarker could prompt specialist referral or be deployed in future screening. In earlier retrospective studies, SOMAscan proteomics (Somalogic, Boulder, CO) and fibulin-3 seemed highly accurate, but SOMAscan has not been validated prospectively and subsequent fibulin-3 data have been contradictory.MethodsA multicenter prospective observational study was performed in 22 centers, generating a large intention-to-diagnose cohort. Blood sampling, processing, and diagnostic assessment were standardized, including a 1-year follow-up. Plasma fibulin-3 was measured using two enzyme-linked immunosorbent assays (CloudClone [used in previous studies] and BosterBio, Pleasanton, CA). Serum proteomics was measured using the SOMAscan assay. Diagnostic performance (sensitivity at 95% specificity, area under the curve [AUC]) was benchmarked against serum mesothelin (Mesomark, Fujirebio Diagnostics, Malvern, PA). Biomarkers were correlated against primary tumor volume, inflammatory markers, and asbestos exposure.ResultsA total of 638 patients with suspected pleural malignancy (SPM) and 110 asbestos-exposed controls (AECs) were recruited. SOMAscan reliably differentiated MPM from AECs (75% sensitivity, 88.2% specificity, validation cohort AUC 0.855) but was not useful in patients with differentiating non-MPM SPM. Fibulin-3 (by BosterBio after failed CloudClone validation) revealed 7.4% and 11.9% sensitivity at 95% specificity in MPM versus non-MPM SPM and AECs, respectively (associated AUCs 0.611 [0.557-0.664], p = 0.0015) and 0.516 [0.443-0.589], p = 0.671), both inferior to mesothelin. SOMAscan proteins correlated with inflammatory markers but not with asbestos exposure. Neither biomarker correlated with tumor volume.ConclusionsSOMAscan may prove useful as a future screening test for MPM in asbestos-exposed persons. Neither fibulin-3 nor SOMAscan should be used for diagnosis or pathway stratification.

Dataset Information

Tasks and Experiences of the Prospective, Longitudinal, Multicenter MoMar (Molecular Markers) Study for the Early Detection of Mesothelioma in Individuals Formerly Exposed to Asbestos Using Liquid Biopsies.

Publications

Tasks and Experiences of the Prospective, Longitudinal, Multicenter MoMar (Molecular Markers) Study for the Early Detection of Mesothelioma in Individuals Formerly Exposed to Asbestos Using Liquid Biopsies.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets