Early Detection of Malignant Pleural Mesothelioma in Asbestos-Exposed Individuals with a Noninvasive Proteomics-Based Surveillance Tool

<div><h3>Background</h3><p>Malignant 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.</p> <h3>Methodology/Principal Findings</h3><p>We 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.</p> <h3>Significance</h3><p>The 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.</p> </div

ROC curves of individual MM biomarkers measured by commercial ELISA kits.

<p>AUC values and 95% confidence intervals for F9 (green), CXCL13 (red), C9 (blue), FCN2 (purple) were derived from measurements in the validation study samples.</p

ROC curves comparing the random forest classifier to mesothelin.

<p>Performance of the random forest classifier (red) compared to a commercial mesothelin assay (blue) on the same cohort of 32 MM cases and 34 asbestos exposed controls. ROC curves are plotted with corresponding AUC values and 95% confidence intervals.</p

Cohort demographics.

<p>Cohort demographics.</p

Classifier performance for training, verification and validation.

<p>Percentage values at the predefined decision threshold and 95% confidence intervals.</p

MM detection by pathologic stage and study cohort.

<p>MM detection by pathologic stage and study cohort.</p

ROC curves for classifier training, blinded verification and validation.

<p>Training (blue), verification (purple), and validation (red) study ROC curves are plotted with corresponding AUC values and 95% confidence intervals.</p

FCN2 SOMAmer and ELISA correlation in the training cohort.

<p>FCN2 measurements for MM cases (red triangles) and asbestos-exposed controls (blue squares) are reported as RFU for SOMAmer and ng/ml for ELISA measurements. Spearman correlation is 0.87.</p

Biomarkers in random forest classifier and their statistical significance.

*<p>Up or down regulation in MM cases relative to controls.</p

Distribution of the 13 protein biomarkers by pathologic stage.

<p>Teal boxes are samples from training and verification combined. Purple boxes are samples from the validation study. Relative fluorescence unit (RFU) distributions are separately shown for control (C) and pathologic stages (I–IV) to illustrate the change in signal as a function of disease burden. Some outlying points have been omitted to make the box plots easier to see: APOA1 (1 point), CDK5-CDK5R1 (1 point), MDK (6 points), and TNFRSF8 (8 points).</p