Biomarkers in Lung Cancer Screening: Achievements, Promises, and Challenges
Tài liệu tham khảo
Aberle, 2011, Reduced lung-cancer mortality with low-dose computed tomographic screening, N Engl J Med, 365, 395, 10.1056/NEJMoa1102873
Henschke, 2006, CT screening for lung cancer: significance of diagnoses in its baseline cycle, Clin Imaging, 30, 11, 10.1016/j.clinimag.2005.07.003
Yousaf-Khan, 2017, Final screening round of the NELSON lung cancer screening trial: the effect of a 2.5-year screening interval, Thorax, 72, 48, 10.1136/thoraxjnl-2016-208655
De Koning H, Van Der Aalst C, ten Haaf K, Oudkerk M. Effects of volume CT lung cancer screening: mortality results of the NELSON randomized-controlled population trial. Paper presented at: 19th World Conference on Lung Cancer. September 23–26, 2018; Toronto, Canada.
Oudkerk, 2017, European position statement on lung cancer screening, Lancet Oncol, 18, e754, 10.1016/S1470-2045(17)30861-6
Moyer, 2014, Screening for lung cancer: U.S. preventive services task force recommendation statement, Ann Intern Med, 160, 330
Roberts, 2013, Screening high-risk populations for lung cancer: guideline recommendations, J Thorac Oncol, 8, 1232, 10.1097/JTO.0b013e31829fd3d5
Mazzone, 2018, Screening for lung cancer: CHEST guideline and expert panel report, Chest, 153, 954, 10.1016/j.chest.2018.01.016
Sanchez-Salcedo, 2015, Improving selection criteria for lung cancer screening: the potential role of emphysema, Am J Respir Crit Care Med, 191, 924, 10.1164/rccm.201410-1848OC
Pinsky, 2012, Applying the National Lung Screening Trial eligibility criteria to the US population: what percent of the population and of incident lung cancers would be covered?, J Med Screen, 19, 154, 10.1258/jms.2012.012010
Tammemägi, 2013, Selection criteria for lung-cancer screening, N Engl J Med, 368, 728, 10.1056/NEJMoa1211776
Tanner, 2017, Assessing the generalizability of the National Lung Screening Trial: comparison of patients with stage 1 disease, Am J Respir Crit Care Med, 196, 602, 10.1164/rccm.201705-0914OC
Wood, 2018, POINT: should lung cancer screening be expanded to persons who don’t currently meet accepted criteria set forth by the CHEST guidelines on lung cancer screening? Yes, Chest, 153, 1299, 10.1016/j.chest.2018.03.017
Tammemagi, 2011, Lung cancer risk prediction: prostate, lung, colorectal and ovarian cancer screening trial models and validation, J Natl Cancer Inst, 103, 1058, 10.1093/jnci/djr173
ten Haaf, 2017, Risk prediction models for selection of lung cancer screening candidates: a retrospective validation study, PLoS Med, 14, e10002277, 10.1371/journal.pmed.1002277
Wang, 2017, Genetic predisposition to lung cancer: comprehensive literature integration, meta-analysis, and multiple evidence assessment of candidate-gene association studies, Sci Rep, 7, 8371, 10.1038/s41598-017-07737-0
De-Torres, 2015, Lung cancer in patients with chronic obstructive pulmonary disease: development and validation of the COPD lung cancer screening score, Am J Respir Crit Care Med, 191, 285, 10.1164/rccm.201407-1210OC
Van Riel, 2017, Malignancy risk estimation of pulmonary nodules in screening CTs: comparison between a computer model and human observers, PLoS One, 12, e0185032, 10.1371/journal.pone.0185032
Tammemagi, 2017, Participant selection for lung cancer screening by risk modelling (the Pan-Canadian Early Detection of Lung Cancer [PanCan] study): a single-arm, prospective study, Lancet Oncol, 18, 1523
Peled, 2015, Screening for lung cancer: what comes next?, J Clin Oncol, 33, 3847, 10.1200/JCO.2015.63.1713
Amos, 2017, The OncoArray Consortium: a network for understanding the genetic architecture of common cancers, Cancer Epidemiol Biomarkers Prev, 26, 126, 10.1158/1055-9965.EPI-16-0106
Feldman, 2017, Prognostic and predictive biomarkers post curative intent therapy, Ann Transl Med, 5, 374, 10.21037/atm.2017.07.34
Martínez-Terroba, 2018, A novel protein-based prognostic signature improves risk stratification to guide clinical management in early lung adenocarcinoma patients, J Pathol, 245, 421, 10.1002/path.5096
Atkinson, 2001, Biomarkers and surrogate endpoints: preferred definitions and conceptual framework, Clin Pharmacol Ther, 69, 89, 10.1067/mcp.2001.113989
Mazzone, 2017, Evaluating molecular biomarkers for the early detection of lung cancer: when is a biomarker ready for clinical use? An official American Thoracic Society policy statement, Am J Respir Crit Care Med, 196, e15, 10.1164/rccm.201708-1678ST
Pepe, 2001, Phases of biomarker development for early detection of cancer, J Natl Cancer Inst, 93, 1054, 10.1093/jnci/93.14.1054
Atwater, 2016, The pursuit of noninvasive diagnosis of lung cancer, Semin Respir Crit Care Med, 37, 670, 10.1055/s-0036-1592314
Rodriguez, 2010, Analytical validation of protein-based multiplex assays: a workshop report by the NCI-FDA interagency oncology task force on molecular diagnostics, Clin Chem, 56, 237, 10.1373/clinchem.2009.136416
Pecot, 2012, Added value of a serum proteomic signature in the diagnostic evaluation of lung nodules, Cancer Epidemiol Biomarkers Prev, 21, 786, 10.1158/1055-9965.EPI-11-0932
Silvestri, 2015, A bronchial genomic classifier for the diagnostic evaluation of lung cancer, N Engl J Med, 373, 243, 10.1056/NEJMoa1504601
Lam, 2011, EarlyCDT-Lung: an immunobiomarker test as an aid to early detection of lung cancer, Cancer Prev Res, 4, 1126, 10.1158/1940-6207.CAPR-10-0328
Macdonald, 2012, Application of a high throughput method of biomarker discovery to improvement of the EarlyCDT®-Lung test, PLoS One, 7, e51002, 10.1371/journal.pone.0051002
Chapman, 2012, EarlyCDT®-Lung test: improved clinical utility through additional autoantibody assays, Tumor Biol, 33, 1319, 10.1007/s13277-012-0379-2
Healey, 2013, Signal stratification of autoantibody levels in serum samples and its application to the early detection of lung cancer, J Thorac Dis, 5, 618
Jett, 2014, Audit of the autoantibody test, EarlyCDT®-Lung, in 1600 patients: an evaluation of its performance in routine clinical practice, Lung Cancer, 83, 51, 10.1016/j.lungcan.2013.10.008
Massion, 2017, Autoantibody signature enhances the positive predictive power of computed tomography and nodule-based risk models for detection of lung cancer, J Thorac Oncol, 12, 578, 10.1016/j.jtho.2016.08.143
Sullivan, 2017, Detection in blood of autoantibodies to tumour antigens as a case-finding method in lung cancer using the EarlyCDT®-Lung Test (ECLS): study protocol for a randomized controlled trial, BMC Cancer, 17, 187, 10.1186/s12885-017-3175-y
Edelsberg, 2018, Cost-effectiveness of an autoantibody test ( Early CDT-Lung ) as an aid to early diagnosis of lung cancer in patients with incidentally detected pulmonary nodules, Oncoimmunology, 442, 1
Boyle, 2011, Clinical validation of an autoantibody test for lung cancer, Ann Oncol, 22, 383, 10.1093/annonc/mdq361
Doseeva, 2015, Performance of a multiplexed dual analyte immunoassay for the early detection of non-small cell lung cancer, J Transl Med, 13, 55, 10.1186/s12967-015-0419-y
Ajona, 2013, Investigation of complement activation product C4d as a diagnostic and prognostic biomarker for lung cancer, J Natl Cancer Inst, 105, 1385, 10.1093/jnci/djt205
Ajona, 2018, Complement C4d-specific antibodies for the diagnosis of lung cancer, Oncotarget, 9, 6346, 10.18632/oncotarget.23690
Verri, 2017, Mutational profile from targeted NGS predicts survival in LDCT screening–detected lung cancers, J Thorac Oncol, 12, 922, 10.1016/j.jtho.2017.03.001
Sozzi, 2014, Clinical utility of a plasma-based miRNA signature classifier within computed tomography lung cancer screening: a correlative MILD trial study, J Clin Oncol, 32, 768, 10.1200/JCO.2013.50.4357
Montani, 2015, MiR-test: a blood test for lung cancer early detection, J Natl Cancer Inst, 107, djv063, 10.1093/jnci/djv063
Sestini, 2015, Circulating microRNA signature as liquid-biopsy to monitor lung cancer in low-dose computed tomography screening, Oncotarget, 6, 32868, 10.18632/oncotarget.5210
Jenkins, 2017, Plasma ctDNA analysis for detection of the EGFR T790M mutation in patients with advanced non–small cell lung cancer, J Thorac Oncol, 12, 1061, 10.1016/j.jtho.2017.04.003
Giroux Leprieur, 2018, Circulating tumor DNA evaluated by next-generation sequencing is predictive of tumor response and prolonged clinical benefit with nivolumab in advanced non-small cell lung cancer, Oncoimmunology, 7, e1424675, 10.1080/2162402X.2018.1424675
Merker, 2018, Circulating tumor DNA analysis in patients with cancer: American Society of Clinical Oncology and College of American Pathologists joint review, J Clin Oncol, 36, 1631, 10.1200/JCO.2017.76.8671
Abbosh, 2017, Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution, Nature, 545, 446, 10.1038/nature22364
Cohen, 2018, Detection and localization of surgically resectable cancers with a multi-analyte blood test, Science, 359, 926, 10.1126/science.aar3247
Ehrlich, 2009, DNA hypomethylation in cancer cells, Epigenomics, 1, 239, 10.2217/epi.09.33
Esteller, 1999, Detection of aberrant promoter hypermethylation of tumor suppressor genes in serum DNA from non-small cell lung cancer patients, Cancer Res, 59, 67
Wielscher, 2015, Diagnostic performance of plasma DNA methylation profiles in lung cancer, pulmonary fibrosis and COPD, EBioMedicine, 2, 929, 10.1016/j.ebiom.2015.06.025
Ooki, 2017, A panel of novel detection and prognostic methylated DNA markers in primary non–small cell lung cancer and serum DNA, Clin Cancer Res, 23, 7141, 10.1158/1078-0432.CCR-17-1222
Hulbert, 2016, Early detection of lung cancer using DNA promoter hypermethylation in plasma and sputum, Clin Cancer Res, 23, 1998, 10.1158/1078-0432.CCR-16-1371
Mazzone, 2018, Evaluation of a serum lung cancer biomarker panel, Biomark Insights, 13, 10.1177/1177271917751608
Molina, 2016, Assessment of a combined panel of six serum tumor markers for lung cancer, Am J Respir Crit Care Med, 193, 427, 10.1164/rccm.201404-0603OC
Silvestri, 2018, Assessment of plasma proteomics biomarker’s ability to distinguish benign from malignant lung nodules: results of the PANOPTIC (PulmonAry NOdule Plasma proTeomIc Classifier) trial, Chest, 154, 491, 10.1016/j.chest.2018.02.012
Billatos, 2018, The airway transcriptome as a biomarker for early lung cancer detection, Clin Cancer Res, 24, 2984, 10.1158/1078-0432.CCR-16-3187
Spira, 2007, Airway epithelial gene expression in the diagnostic evaluation of smokers with suspect lung cancer, Nat Med, 13, 361, 10.1038/nm1556
Blomquist, 2009, Pattern of antioxidant and DNA repair gene expression in normal airway epithelium associated with lung cancer diagnosis, Cancer Res, 69, 8629, 10.1158/0008-5472.CAN-09-1568
Whitney, 2015, Derivation of a bronchial genomic classifier for lung cancer in a prospective study of patients undergoing diagnostic bronchoscopy, BMC Med Genomics, 8, 18, 10.1186/s12920-015-0091-3
Hu, 2016, Analytical performance of a bronchial genomic classifier, BMC Cancer, 16, 161, 10.1186/s12885-016-2153-0
Vachani, 2016, Clinical utility of a bronchial genomic classifier in patients with suspected lung cancer, Chest, 150, 210, 10.1016/j.chest.2016.02.636
Hogarth DK, Dotson TL, Lee HL, Whitten PE, Smith K, Lenburg ME. The Percepta® Registry: a prospective registry to evaluate percepta bronchial genomic classifier patient data. Paper presented at: CHEST Annual Meeting. October 22–26, 2016; Los Angeles, CA.
Perez-Rogers, 2017, Shared gene expression alterations in nasal and bronchial epithelium for lung cancer detection, J Natl Cancer Inst, 109, 10.1093/jnci/djw327
Boeri, 2015, Recent advances of microRNA-based molecular diagnostics to reduce false-positive lung cancer imaging, Expert Rev Mol Diagn, 15, 801, 10.1586/14737159.2015.1041377
Filippo, 2015, Smoking cessation intervention within the framework of a lung cancer screening program: preliminary results and clinical perspectives from the “Cosmos-II” Trial, Lung, 193, 147, 10.1007/s00408-014-9661-y
Smyth, 2018, Brief report on the detection of the EGFR-T790M mutation in exhaled breath condensate from lung cancer patients, J Thorac Oncol, 13, 1213, 10.1016/j.jtho.2018.04.033
Mazzone, 2015, Progress in the development of volatile exhaled breath signatures of lung cancer, Ann Am Thorac Soc, 12, 752, 10.1513/AnnalsATS.201411-540OC
Nakhleh, 2017, Diagnosis and classification of 17 diseases from 1404 subjects via pattern analysis of exhaled molecules, ACS Nano, 11, 112, 10.1021/acsnano.6b04930
Peled, 2012, Non-invasive breath analysis of pulmonary nodules, J Thorac Oncol, 7, 1528, 10.1097/JTO.0b013e3182637d5f
Nardi-Agmon, 2016, Exhaled breath analysis for monitoring response to treatment in advanced lung cancer, J Thorac Oncol, 11, 827, 10.1016/j.jtho.2016.02.017
Hakim, 2012, Volatile organic compounds of lung cancer and possible biochemical pathways, Chem Rev, 112, 5949, 10.1021/cr300174a
Peled, 2013, Volatile fingerprints of cancer specific genetic mutations, Nanomedicine, 9, 758, 10.1016/j.nano.2013.01.008
Peng, 2010, Detection of lung, breast, colorectal, and prostate cancers from exhaled breath using a single array of nanosensors, Br J Cancer, 103, 542, 10.1038/sj.bjc.6605810
Meyer, 2015, The Cell-CT 3-dimensional cell imaging technology platform enables the detection of lung cancer using the noninvasive LuCED sputum test, Cancer Cytopathol, 123, 512, 10.1002/cncy.21576
Nelson, 2014, Early detection of lung cancer based on three-dimensional, morphometric analysis of cells from sputum [abstract], J Clin Oncol, 32, 7547, 10.1200/jco.2014.32.15_suppl.7547
Yu, 2017, Next-generation metabolomics in lung cancer diagnosis, treatment and precision medicine: mini review, Oncotarget, 8, 115774, 10.18632/oncotarget.22404
Puchades-Carrasco, 2016, Serum metabolomic profiling facilitates the non-invasive identification of metabolic biomarkers associated with the onset and progression of non-small cell lung cancer, Oncotarget, 7, 12904, 10.18632/oncotarget.7354
Rezola, 2014, In-silico prediction of key metabolic differences between two non-small cell lung cancer subtypes, PLoS One, 9, e103998, 10.1371/journal.pone.0103998
Caiola, 2016, Different metabolic responses to PI3K inhibition in NSCLC cells harboring wild-type and G12C mutant KRAS, Oncotarget, 7, 51462, 10.18632/oncotarget.9849
Mathé, 2014, Noninvasive urinary metabolomic profiling identifies diagnostic and prognostic markers in lung cancer, Cancer Res, 74, 3259, 10.1158/0008-5472.CAN-14-0109
Haznadar, 2016, Urinary metabolite risk biomarkers of lung cancer: a prospective cohort study, Cancer Epidemiol Biomarkers Prev, 25, 978, 10.1158/1055-9965.EPI-15-1191
Roś-Mazurczyk, 2017, Panel of serum metabolites discriminates cancer patients and healthy participants of lung cancer screening - a pilot study, Acta Biochim Pol, 64, 513, 10.18388/abp.2017_1517
Wikoff, 2015, Diacetylspermine is a novel prediagnostic serum biomarker for non-small-cell lung cancer and has additive performance with pro-surfactant protein B, J Clin Oncol, 33, 3880, 10.1200/JCO.2015.61.7779
Wen, 2015, The ability of bilirubin in identifying smokers with higher risk of lung cancer: a large cohort study in conjunction with global metabolomic profiling, Clin Cancer Res, 21, 193, 10.1158/1078-0432.CCR-14-0748
Fahrmann, 2016, Serum phosphatidylethanolamine levels distinguish benign from malignant solitary pulmonary nodules and represent a potential diagnostic biomarker for lung cancer, Cancer Biomarkers, 16, 609, 10.3233/CBM-160602
Cameron, 2016, The metabolomic detection of lung cancer biomarkers in sputum, Lung Cancer, 94, 88, 10.1016/j.lungcan.2016.02.006
Peralbo-Molina, 2016, Identification of metabolomics panels for potential lung cancer screening by analysis of exhaled breath condensate, J Breath Res, 10, 026002, 10.1088/1752-7155/10/2/026002
Lee, 2016, Characterization of microbiome in bronchoalveolar lavage fluid of patients with lung cancer comparing with benign mass like lesions, Lung Cancer, 102, 89, 10.1016/j.lungcan.2016.10.016
Cassidy, 2008, The LLP risk model: an individual risk prediction model for lung cancer, Br J Cancer, 98, 270, 10.1038/sj.bjc.6604158
McKay, 2017, Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes, Nat Genet, 49, 1126, 10.1038/ng.3892
Field, 2016, The UK Lung Cancer Screening Trial: a pilot randomised controlled trial of low-dose computed tomography screening for the early detection of lung cancer, Health Technol Assess (Rockv), 20, 1, 10.3310/hta20400
Ji, 2018, Identification of susceptibility pathways for the role of chromosome 15q25.1 in modifying lung cancer risk, Nat Commun, 9, 3221, 10.1038/s41467-018-05074-y
Fusco JP, Pita G, Pajares MJ, et al. Genomic characterization of individuals presenting extreme phenotypes of high and low risk to develop tobacco-induced lung cancer [e-pub ahead of print]. Cancer Med. https://doi.org/10.1002/cam4.1500, accessed
Mieth, 2016, Combining multiple hypothesis testing with machine learning increases the statistical power of genome-wide association studies, Sci Rep, 6, 36671, 10.1038/srep36671
Schrider, 2018, Supervised machine learning for population genetics: a new paradigm, Trends Genet, 34, 301, 10.1016/j.tig.2017.12.005
Lambin, 2012, Radiomics: Extracting more information from medical images using advanced feature analysis, Eur J Cancer, 48, 441, 10.1016/j.ejca.2011.11.036
Chen, 2017, Development and clinical application of radiomics in lung cancer, Radiat Oncol, 12, 154, 10.1186/s13014-017-0885-x
Shen, 2015, Multi-scale convolutional neural networks for lung nodule classification, Inf Process Med Imaging, 24, 588
Arindra, 2016, Pulmonary nodule detection in CT images: false positive reduction using multi-view convolutional networks, IEEE Trans Med Imaging, 35, 1160, 10.1109/TMI.2016.2536809
Liu, 2016, Radiomic features are associated with egfr mutation status in lung adenocarcinomas, Clin Lung Cancer, 17, 441, 10.1016/j.cllc.2016.02.001
Rios Velazquez, 2017, Somatic mutations drive distinct imaging phenotypes in lung cancer, Cancer Res, 77, 3922, 10.1158/0008-5472.CAN-17-0122
Lee, 2018, A quantitative CT imaging signature predicts survival and complements established prognosticators in stage I non-small cell lung cancer, Int J Radiat Oncol, 102, 1098, 10.1016/j.ijrobp.2018.01.006
Lin, 2017, A classifier integrating plasma biomarkers and radiological characteristics for distinguishing malignant from benign pulmonary nodules, Int J Cancer, 141, 1240, 10.1002/ijc.30822
Ma, 2017, A prediction model based on biomarkers and clinical characteristics for detection of lung cancer in pulmonary nodules, Transl Oncol, 10, 40, 10.1016/j.tranon.2016.11.001
Jiang, 2017, Combining PET/CT with serum tumor markers to improve the evaluation of histological type of suspicious lung cancers, PLoS One, 12, e0184338, 10.1371/journal.pone.0184338
Jiang, 2009, Combined genetic analysis of sputum and computed tomography for noninvasive diagnosis of non-small-cell lung cancer, Lung Cancer, 66, 58, 10.1016/j.lungcan.2009.01.004
Grossmann P, Stringfield O, El-Hachem N, et al. Defining the biological basis of radiomic phenotypes in lung cancer. Elife. https://doi.org/10.7554/eLife.23421. Accessed June 26, 2018.
GR. Oxnard T. Maddala E. Hubbell et al. Genome-wide sequencing for early stage lung cancer detection from plasma cell-free DNA (cfDNA): the Circulating Cancer Genome Atlas (CCGA) study. Paper presented at: 2018 American Society of Clinical Oncology Annual Meeting. June 1–5, 2018; Chicago, IL.
Aravanis, 2017, Next-generation sequencing of circulating tumor dna for early cancer detection, Cell, 168, 571, 10.1016/j.cell.2017.01.030
Tuck, 2009, Standard operating procedures for serum and plasma collection: early detection research network consensus statement standard operating procedure integration working group, J Proteome Res, 8, 113, 10.1021/pr800545q
Minari, 2018, Tensions in ethics and policy created by National Precision Medicine Programs, Hum Genomics, 12, 22, 10.1186/s40246-018-0151-9
Liu, 2017, The combination of the tumor markers suggests the histological diagnosis of lung cancer, Biomed Res Int, 2017, 2013989
Boeri, 2011, MicroRNA signatures in tissues and plasma predict development and prognosis of computed tomography detected lung cancer, Proc Natl Acad Sci, 108, 3713, 10.1073/pnas.1100048108
Bianchi, 2011, A serum circulating miRNA diagnostic test to identify asymptomatic high-risk individuals with early stage lung cancer, EMBO Mol Med, 3, 495, 10.1002/emmm.201100154
Maisonneuve, 2011, Lung cancer risk prediction to select smokers for screening CT–a model based on the Italian COSMOS trial, Cancer Prev Res (Phila), 4, 1778, 10.1158/1940-6207.CAPR-11-0026
Yanaihara, 2006, Unique microRNA molecular profiles in lung cancer diagnosis and prognosis, Cancer Cell, 9, 189, 10.1016/j.ccr.2006.01.025
Weiss, 2017, Validation of the SHOX2/PTGER4 DNA methylation marker panel for plasma-based discrimination between patients with malignant and nonmalignant lung disease, J Thorac Oncol, 12, 77, 10.1016/j.jtho.2016.08.123
Newman, 2014, An ultrasensitive method for quantitating circulating tumor DNA with broad patient coverage, Nat Med, 20, 548, 10.1038/nm.3519
Guo, 2016, Circulating tumor DNA detection in lung cancer patients before and after surgery, Sci Rep, 6, 33519, 10.1038/srep33519
Phallen, 2017, Direct detection of early-stage cancers using circulating tumor DNA, Sci Transl Med, 9, 10.1126/scitranslmed.aan2415
Showe, 2009, Gene expression profiles in peripheral blood mononuclear cells can distinguish patients with non-small cell lung cancer from patients with nonmalignant lung disease, Cancer Res, 69, 9202, 10.1158/0008-5472.CAN-09-1378
Halling, 2006, A comparison of cytology and fluorescence in situ hybridization for the detection of lung cancer in bronchoscopic specimens, Chest, 130, 694, 10.1378/chest.130.3.694
Nichols, 2014, Genetic test to stop smoking (GeTSS) trial protocol: randomised controlled trial of a genetic test (Respiragene) and Auckland formula to assess lung cancer risk, BMC Pulm Med, 14, 77, 10.1186/1471-2466-14-77
Zhang, 2017, DNA methylation analysis of the SHOX2 and RASSF1A panel in bronchoalveolar lavage fluid for lung cancer diagnosis, J Cancer, 8, 3585, 10.7150/jca.21368
Xing, 2015, Sputum microRNA biomarkers for identifying lung cancer in indeterminate solitary pulmonary nodules, Clin Cancer Res, 21, 484, 10.1158/1078-0432.CCR-14-1873
Subramanian, 2016, Procedures for risk-stratification of lung cancer using buccal nanocytology, Biomed Opt Express, 7, 3795, 10.1364/BOE.7.003795
Patriquin, 2015, Early detection of lung cancer with meso tetra (4-carboxyphenyl) porphyrin-labeled sputum, J Thorac Oncol, 10, 1311, 10.1097/JTO.0000000000000627