Biomarkers of risk to develop lung cancer in the new screening era

Annals of Translational Medicine

Volumn 4, Issue 8, 2016, Pages

  Atwater, Thomas ^a   Massion, Pierre P ^b,c  

^a VANDERBILT UNIVERSITY MEDICAL CENTER   (United States)

^b VANDERBILT INGRAM CANCER CENTER   (United States)

^c Healthcare System   (United States)

Author keywords

Adenocarcinoma; Granuloma; Parallel reaction monitoring; Shotgun proteomics

Indexed keywords

TUMOR MARKER;

BRONCHOSCOPY; CANCER GENETICS; CANCER GROWTH; CANCER RISK; CANCER SCREENING; COMPUTER ASSISTED TOMOGRAPHY; COST EFFECTIVENESS ANALYSIS; DIAGNOSTIC ACCURACY; DIAGNOSTIC VALUE; EARLY DIAGNOSIS; FALSE POSITIVE RESULT; GENETIC RISK; GENETIC SCREENING; HEALTH CARE COST; HEALTH PROGRAM; HIGH RISK PATIENT; HUMAN; LUNG CANCER; LUNG CARCINOGENESIS; MOLECULAR DIAGNOSIS; MOLECULAR GENETICS; PREDICTIVE VALUE; REVIEW; RISK ASSESSMENT; THORAX RADIOGRAPHY;

EID: 84979263824     PISSN: 23055839     EISSN: 23055847     Source Type: Journal    
DOI: 10.21037/atm.2016.03.46     Document Type: Review

References (53)

1. National Lung Screening Trial Research Team, Aberle DR, Adams AM, et al. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med 2011;365:395-409.
2. van Klaveren RJ, Oudkerk M, Prokop M, et al. Management of lung nodules detected by volume CT scanning. N Engl J Med 2009;361:2221-9.
3. Massion PP, Walker RC. Indeterminate pulmonary nodules: risk for having or for developing lung cancer? Cancer Prev Res (Phila) 2014;7:1173-8.
4. Srivastava S, Gopal-Srivastava R. Biomarkers in cancer screening: a public health perspective. J Nutr 2002;132:2471S-2475S.
5. Bach PB, Kattan MW, Thornquist MD, et al. Variations in lung cancer risk among smokers. J Natl Cancer Inst 2003;95:470-8.
6. Cassidy A, Myles JP, van Tongeren M, et al. The LLP risk model: an individual risk prediction model for lung cancer. Br J Cancer 2008;98:270-6.
7. Peto R, Darby S, Deo H, et al. Smoking, smoking cessation, and lung cancer in the UK since 1950:combination of national statistics with two case-control studies. BMJ 2000;321:323-9.
8. Prindiville SA, Byers T, Hirsch FR, et al. Sputum cytological atypia as a predictor of incident lung cancer in a cohort of heavy smokers with airflow obstruction. Cancer Epidemiol Biomarkers Prev 2003;12:987-93.
9. Spitz MR, Hong WK, Amos CI, et al. A risk model for prediction of lung cancer. J Natl Cancer Inst 2007;99:715-26.
10. Tammemagi MC, Freedman MT, Pinsky PF, et al. Prediction of true positive lung cancers in individuals with abnormal suspicious chest radiographs: a prostate, lung, colorectal, and ovarian cancer screening trial study. J Thorac Oncol 2009;4:710-21.
11. Tammemagi CM, Pinsky PF, Caporaso NE, et al. Lung cancer risk prediction: Prostate, Lung, Colorectal And Ovarian Cancer Screening Trial models and validation. J Natl Cancer Inst 2011;103:1058-68.
12. Kovalchik SA, Tammemagi M, Berg CD, et al. Targeting of low-dose CT screening according to the risk of lungcancer death. N Engl J Med 2013;369:245-54.
13. Cronin KA, Gail MH, Zou Z, et al. Validation of a model of lung cancer risk prediction among smokers. J Natl Cancer Inst 2006;98:637-40.
14. McRonald FE, Yadegarfar G, Baldwin DR, et al. The UK Lung Screen (UKLS): demographic profile of first 88,897 approaches provides recommendations for population screening. Cancer Prev Res (Phila) 2014;7:362-71.
15. Marcus MW, Chen Y, Raji OY, et al. LLPi: Liverpool Lung Project Risk Prediction Model for Lung Cancer Incidence. Cancer Prev Res (Phila) 2015;8:570-5.
16. Wiener RS, Gould MK, Arenberg DA, et al. An official American Thoracic Society/American College of Chest Physicians policy statement: implementation of lowdose computed tomography lung cancer screening programs in clinical practice. Am J Respir Crit Care Med 2015;192:881-91.
17. Mazzone P, Powell CA, Arenberg D, et al. Components necessary for high-quality lung cancer screening: American College of Chest Physicians and American Thoracic Society Policy Statement. Chest 2015;147:295-303.
18. Hassanein M, Callison JC, Callaway-Lane C, et al. The state of molecular biomarkers for the early detection of lung cancer. Cancer Prev Res (Phila) 2012;5:992-1006.
19. Maisonneuve P, Bagnardi V, Bellomi M, et al. Lung cancer risk prediction to select smokers for screening CT--a model based on the Italian COSMOS trial. Cancer Prev Res (Phila) 2011;4:1778-89.
20. Pine SR, Mechanic LE, Enewold L, et al. Increased levels of circulating interleukin 6, interleukin 8, C-reactive protein, and risk of lung cancer. J Natl Cancer Inst 2011;103:1112-22.
21. Chen X, Ba Y, Ma L, et al. Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases. Cell Res 2008;18:997-1006.
22. Boeri M, Verri C, Conte D, et al. MicroRNA signatures in tissues and plasma predict development and prognosis of computed tomography detected lung cancer. Proc Natl Acad Sci U S A 2011;108:3713-8.
23. Bianchi F, Nicassio F, Marzi M, et al. A serum circulating miRNA diagnostic test to identify asymptomatic high-risk individuals with early stage lung cancer. EMBO Mol Med 2011;3:495-503.
24. Sozzi G, Boeri M, Rossi M, et al. Clinical utility of a plasma-based miRNA signature classifier within computed tomography lung cancer screening: a correlative MILD trial study. J Clin Oncol 2014;32:768-73.
25. Montani F, Marzi MJ, Dezi F, et al. miR-Test: a blood test for lung cancer early detection. J Natl Cancer Inst 2015;107:djv063.
26. Wozniak MB, Scelo G, Muller DC, et al. Circulating MicroRNAs as Non-Invasive Biomarkers for Early Detection of Non-Small-Cell Lung Cancer. PLoS One 2015;10:e0125026.
27. Zhong L, Coe SP, Stromberg AJ, et al. Profiling tumorassociated antibodies for early detection of non-small cell lung cancer. J Thorac Oncol 2006;1:513-9.
28. Trivers GE, De Benedetti VM, Cawley HL, et al. Anti-p53 antibodies in sera from patients with chronic obstructive pulmonary disease can predate a diagnosis of cancer. Clin Cancer Res 1996;2:1767-75.
29. Desmetz C, Bascoul-Mollevi C, Rochaix P, et al. Identification of a new panel of serum autoantibodies associated with the presence of in situ carcinoma of the breast in younger women. Clin Cancer Res 2009;15:4733-41.
30. Chapman CJ, Murray A, McElveen JE, et al. Autoantibodies in lung cancer: possibilities for early detection and subsequent cure. Thorax 2008;63:228-33.
31. Lam S, Boyle P, Healey GF, et al. EarlyCDT-Lung: an immunobiomarker test as an aid to early detection of lung cancer. Cancer Prev Res (Phila) 2011;4:1126-34.
32. Chapman CJ, Thorpe AJ, Murray A, et al. Immunobiomarkers in small cell lung cancer: potential early cancer signals. Clin Cancer Res 2011;17:1474-80.
33. Pedchenko T, Mernaugh R, Parekh D, et al. Early detection of NSCLC with scFv selected against IgM autoantibody. PLoS One 2013;8:e60934.
34. Varella-Garcia M, Chen L, Powell RL, et al. Spectral karyotyping detects chromosome damage in bronchial cells of smokers and patients with cancer. Am J Respir Crit Care Med 2007;176:505-12.
35. Varella-Garcia M, Kittelson J, Schulte AP, et al. Multitarget interphase fluorescence in situ hybridization assay increases sensitivity of sputum cytology as a predictor of lung cancer. Cancer Detect Prev 2004;28:244-51.
36. Varella-Garcia M, Schulte AP, Wolf HJ, et al. The detection of chromosomal aneusomy by fluorescence in situ hybridization in sputum predicts lung cancer incidence. Cancer Prev Res (Phila) 2010;3:447-53.
37. Teare MD, Woll PJ. Genomic tests: unreliable for cancer? A focus on circulating DNA and lung cancer. Expert Rev Mol Diagn 2007;7:699-702.
38. Bettegowda C, Sausen M, Leary RJ, et al. Detection of circulating tumor DNA in early- and late-stage human malignancies. Sci Transl Med 2014;6:224ra24.
39. Newman AM, Bratman SV, To J, et al. An ultrasensitive method for quantitating circulating tumor DNA with broad patient coverage. Nat Med 2014;20:548-54.
40. Timofeeva MN, Hung RJ, Rafnar T, et al. Influence of common genetic variation on lung cancer risk: metaanalysis of 14 900 cases and 29 485 controls. Hum Mol Genet 2012;21:4980-95.
41. Young RP, Hopkins RJ, Gamble GD. Clinical applications of gene-based risk prediction for lung cancer and the central role of chronic obstructive pulmonary disease. Front Genet 2012;3:210.
42. Spitz MR, Etzel CJ, Dong Q, et al. An expanded risk prediction model for lung cancer. Cancer Prev Res (Phila) 2008;1:250-4.
43. Raji OY, Agbaje OF, Duffy SW, et al. Incorporation of a genetic factor into an epidemiologic model for prediction of individual risk of lung cancer: the Liverpool Lung Project. Cancer Prev Res (Phila) 2010;3:664-9.
44. Young RP, Hopkins RJ, Hay BA, et al. Lung cancer susceptibility model based on age, family history and genetic variants. PLoS One 2009;4:e5302.
45. Hendriksen JM, Geersing GJ, Moons KG, et al. Diagnostic and prognostic prediction models. J Thromb Haemost 2013;11 Suppl 1:129-41.
46. Moons KG. Criteria for scientific evaluation of novel markers: a perspective. Clin Chem 2010;56:537-41.
47. Cook NR. Use and misuse of the receiver operating characteristic curve in risk prediction. Circulation 2007;115:928-35.
48. Pencina MJ, D'Agostino RB Sr, D'Agostino RB Jr, et al. Evaluating the added predictive ability of a new marker:from area under the ROC curve to reclassification and beyond. Stat Med 2008;27:157-72; discussion 207-12.
49. Pepe MS, Feng Z, Janes H, et al. Pivotal evaluation of the accuracy of a biomarker used for classification or prediction: standards for study design. J Natl Cancer Inst 2008;100:1432-8.
50. Bush WS, Oetjens MT, Crawford DC. Unravelling the human genome-phenome relationship using phenomewide association studies. Nat Rev Genet 2016;17:129-45.
51. Wang X, Pandey AK, Mulligan MK, et al. Joint mousehuman phenome-wide association to test gene function and disease risk. Nat Commun 2016;7:10464.
52. Gamazon ER, Wheeler HE, Shah KP, et al. A gene-based association method for mapping traits using reference transcriptome data. Nat Genet 2015;47:1091-8.
53. Wei WQ, Denny JC. Extracting research-quality phenotypes from electronic health records to support precision medicine. Genome Med 2015;7:41.