Faculty Bibliography

Identification of biomarkers for early detection of lung cancer (LC) is important, in turn leading to more effective treatment and reduction of mortality. Serological proteome analysis (SERPA) was used to identify proteins around 34 kD as ECH1 and HNRNPA2B1, which had been recognized by serum autoantibody from 25 LC patients. In the validation study, including 90 sera from LC patients and 89 sera from normal individuals, autoantibody to ECH1 achieved an area under the curve (AUC) of 0.799 with sensitivity of 62.2% and specificity of 95.5% in discriminating LC from normal individuals, and showed negative correlation with tumor size (rs = -0.256, p = 0.023). Autoantibody to HNRNPA2B1 performed an AUC of 0.874 with sensitivity of 72.2% and specificity of 95.5%, and showed negative correlation with lymph node metastasis (rs = -0.279, p = 0.012). By using longitudinal preclinical samples, autoantibody to ECH1 showed an AUC of 0.763 with sensitivity of 60.0% and specificity of 89.3% in distinguishing early stage LC from matched normal controls, and elevated autoantibody levels could be detected greater than 2 y before LC diagnosis. ECH1 and HNRNPA2B1 are autoantigens that elicit autoimmune responses in LC and their autoantibody can be the potential biomarkers for the early detection of LC.

Quality improvement requires novel, and perhaps simple, ideas for adaptation, like a lymph node kit, and the ability to objectively document benchmark upgrading.

BACKGROUND: The number of pulmonary nodules detected in the US is expected to increase substantially following recent recommendations for nationwide CT-based lung cancer screening. Given the low specificity of CT screening, non-invasive adjuvant methods are needed to differentiate cancerous lesions from benign nodules to help avoid unnecessary invasive procedures in the asymptomatic population. We have constructed a serum-based multi-biomarker panel and assessed its clinical accuracy in a retrospective analysis of samples collected from participants with suspicious radiographic findings in the Prostate, Lung, Chest and Ovarian (PLCO) cancer screening trial. METHODS: Starting with a set of 9 candidate biomarkers, we identified 8 that exhibited limited pre-analytical variability with increasing clotting time, a key pre-analytical variable associated with the collection of serum. These 8 biomarkers were evaluated in a training study consisting of 95 stage I NSCLC patients and 186 smoker controls where a 5-biomarker pulmonary nodule classifier (PNC) was selected. The clinical accuracy of the PNC was determined in a blinded study of asymptomatic individuals comprising 119 confirmed malignant nodule cases and 119 benign nodule controls selected from the PLCO screening trial. RESULTS: A PNC comprising 5 biomarkers: CEA, CYFRA 21-1, OPN, SCC, and TFPI, was selected in the training study. In an independent validation study, the PNC resolved lung cancer cases from benign nodule controls with an AUC of 0.653 (p < 0.0001). CEA and CYFRA 21-1, two of the markers included in the PNC, also accurately distinguished malignant lesions from benign controls. CONCLUSIONS: A 5-biomarker blood test has been developed for the diagnostic evaluation of asymptomatic individuals with solitary pulmonary nodules.

INTRODUCTION: Current T component for malignant pleural mesothelioma (MPM) has been predominantly informed by surgical datasets and consensus. The International Association for the Study of Lung Cancer undertook revision of the 7th Edition staging system for MPM with the goal of developing recommendations for the 8th edition. METHODS: Data elements including detailed T descriptors were developed by consensus. Tumor thickness at three pleural levels was also recorded. An electronic data capture system was established to facilitate data submission. RESULTS: 3,519 cases were submitted to the database. Of those eligible for T component analysis, 509 cases had only clinical staging; 836 cases had only surgical staging; and 642 cases had both available. Survival was examined for T categories according to the current 7th edition staging system. There was clear separation between all clinically staged categories except T1a vs. T1b (HR 0.99, p=0.95) and T3 vs. T4 (HR 1.22, P=0.09), although numbers of T4 cases were small. Pathological staging failed to demonstrate a survival difference between adjacent categories with the exception of T3 vs. T4. Performance improved with collapse of T1a and T1b into a single T1 category; no current descriptors were shifted or eliminated. Tumour thickness and nodular or rind-like morphology were significantly associated with survival. CONCLUSIONS: A recommendation to collapse both clinical and pathological T1a and T1b into a T1 classification will be made for the 8th edition staging system. Simple measurement of pleural thickness has prognostic significance and should be examined further with a view to incorporation into future staging.