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Hubers AJ, Heideman DAM, Burgers SA, Herder GJM, Sterk PJ, Rhodius RJ, Smit HJ, Krouwels F, Welling A, Witte BI, Duin S, Koning R, Comans EFI, Steenbergen RDM, Postmus PE, Meijer GA, Snijders PJF, Smit EF, Thunnissen E. DNA hypermethylation analysis in sputum for the diagnosis of lung cancer: training validation set approach. Br J Cancer 2015; 112:1105-13. [PMID: 25719833 PMCID: PMC4366885 DOI: 10.1038/bjc.2014.636] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2014] [Revised: 10/06/2014] [Accepted: 12/01/2014] [Indexed: 01/22/2023] Open
Abstract
Background: Lung cancer has the highest mortality of all cancers. The aim of this study was to examine DNA hypermethylation in sputum and validate its diagnostic accuracy for lung cancer. Methods: DNA hypermethylation of RASSF1A, APC, cytoglobin, 3OST2, PRDM14, FAM19A4 and PHACTR3 was analysed in sputum samples from symptomatic lung cancer patients and controls (learning set: 73 cases, 86 controls; validation set: 159 cases, 154 controls) by quantitative methylation-specific PCR. Three statistical models were used: (i) cutoff based on Youden's J index, (ii) cutoff based on fixed specificity per marker of 96% and (iii) risk classification of post-test probabilities. Results: In the learning set, approach (i) showed that RASSF1A was best able to distinguish cases from controls (sensitivity 42.5%, specificity 96.5%). RASSF1A, 3OST2 and PRDM14 combined demonstrated a sensitivity of 82.2% with a specificity of 66.3%. Approach (ii) yielded a combination rule of RASSF1A, 3OST2 and PHACTR3 (sensitivity 67.1%, specificity 89.5%). The risk model (approach iii) distributed the cases over all risk categories. All methods displayed similar and consistent results in the validation set. Conclusions: Our findings underscore the impact of DNA methylation markers in symptomatic lung cancer diagnosis. RASSF1A is validated as diagnostic marker in lung cancer.
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Affiliation(s)
- A J Hubers
- Department of Pathology, VU University Medical Center, De Boelelaan 1117, Amsterdam 1081 HV, The Netherlands
| | - D A M Heideman
- Department of Pathology, VU University Medical Center, De Boelelaan 1117, Amsterdam 1081 HV, The Netherlands
| | - S A Burgers
- Department of Thoracic Oncology, NKI-Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
| | - G J M Herder
- Department of Pulmonary Diseases, Sint Antonius Hospital, Nieuwegein, The Netherlands
| | - P J Sterk
- Department of Pulmonary Diseases, Academic Medical Center, Amsterdam, The Netherlands
| | - R J Rhodius
- Department of Pulmonary Diseases, Academic Medical Center, Amsterdam, The Netherlands
| | - H J Smit
- Department of Pulmonary Diseases, Sint Lucas Andreas Hospital, Amsterdam, The Netherlands
| | - F Krouwels
- Department of Pulmonary Diseases, Spaarne Hospital, Hoofddorp, The Netherlands
| | - A Welling
- Department of Pulmonary Diseases, Medisch Centrum Alkmaar, Alkmaar, The Netherlands
| | - B I Witte
- Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands
| | - S Duin
- Department of Pathology, VU University Medical Center, De Boelelaan 1117, Amsterdam 1081 HV, The Netherlands
| | - R Koning
- Department of Pathology, VU University Medical Center, De Boelelaan 1117, Amsterdam 1081 HV, The Netherlands
| | - E F I Comans
- Department of Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands
| | - R D M Steenbergen
- Department of Pathology, VU University Medical Center, De Boelelaan 1117, Amsterdam 1081 HV, The Netherlands
| | - P E Postmus
- Department of Pulmonary Diseases, VU University Medical Center, Amsterdam, The Netherlands
| | - G A Meijer
- Department of Pathology, VU University Medical Center, De Boelelaan 1117, Amsterdam 1081 HV, The Netherlands
| | - P J F Snijders
- Department of Pathology, VU University Medical Center, De Boelelaan 1117, Amsterdam 1081 HV, The Netherlands
| | - E F Smit
- Department of Pulmonary Diseases, VU University Medical Center, Amsterdam, The Netherlands
| | - E Thunnissen
- Department of Pathology, VU University Medical Center, De Boelelaan 1117, Amsterdam 1081 HV, The Netherlands
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Hubers AJ, Prinsen CFM, Sozzi G, Witte BI, Thunnissen E. Molecular sputum analysis for the diagnosis of lung cancer. Br J Cancer 2013; 109:530-7. [PMID: 23868001 PMCID: PMC3738145 DOI: 10.1038/bjc.2013.393] [Citation(s) in RCA: 78] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2013] [Revised: 05/08/2013] [Accepted: 06/21/2013] [Indexed: 12/20/2022] Open
Abstract
Lung cancer is the leading cause of cancer mortality rate worldwide, mainly because of the presence of metastatic disease at the time of diagnosis. Early detection of lung cancer improves prognosis, and towards this end, large screening trials in high-risk individuals have been conducted since the past century. Despite all efforts, the need for novel (complementary) lung cancer diagnostic and screening methods still exists. In this review, we focus on the assessment of lung cancer-related biomarkers in sputum in the past decennium. Besides cytology, mutation and microRNA analysis, special attention has been paid to DNA promoter hypermethylation, of which all available literature is summarised without time restriction. A model is proposed to aid in the distinction between diagnostic and risk markers. Research on the use of sputum for non-invasive detection of early-stage lung cancer has brought new insights and advanced molecular techniques. The sputum shows a promising potential for routine diagnostic and possibly screening purposes.
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Affiliation(s)
- A J Hubers
- Department of Pathology, VU University Medical Center, Amsterdam, The Netherlands
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