Biomarkers in Early Diagnosis and Early Stage Lung Cancer: The Clinician’s Point of View
Abstract
:Author Contributions
Funding
Conflicts of Interest
References
- Ulivi, P.; Petracci, E.; Marisi, G.; Baglivo, S.; Chiari, R.; Billi, M.; Canale, M.; Pasini, L.; Racanicchi, S.; Vagheggini, A.; et al. Prognostic role of circulating miRNAs in Early-Stage Non-Small Cell Lung Cancer. J. Clin. Med. 2019, 8, 131. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- McGuire, A.L.; Hughesman, C.B.; McConechy, M.K.; Melosky, B.; Lam, S.; Myers, R.; Yee, J.; Tang, E.; Yip, S. Optimizing molecular residual disease detection using liquid biopsy postoperatively in early stage lung cancer. Lung Cancer Manag. 2020, 9, LMT24. [Google Scholar] [CrossRef] [PubMed]
- Pantel, K.; Alix-Panabières, C. Liquid biopsy and minimal residual Disease-Latest advances and implications for cure. Nat. Rev. Clin. Oncol. 2019, 16, 409–424. [Google Scholar] [CrossRef]
- Fitzmaurice, C.; Abate, D.; Abbasi, N.; Abbastabar, H.; Abd-Allah, F.; Abdel-Rahman, O.; Abdelalim, A.; Abdoli, A.; Abdollahpour, I.; Abdulle, A.S.M.; et al. Global, regional, and national cancer incidence, mortality, years of life lost, years lived with disability, and Disability-Adjusted Life-Years for 29 cancer groups, 1990 to 2017: A systematic analysis for the global burden of disease study. JAMA Oncol. 2019, 5, 1749–1768. [Google Scholar]
- Abubakar, I.I.; Tillmann, T.; Banerjee, A. Global, regional, and national Age–Sex specific All-Cause and Cause-Specific mortality for 240 causes of death, 1990–2013: A systematic analysis for the Global Burden of Disease Study 2013. Lancet 2015, 385, 117–171. [Google Scholar]
- Goldstraw, P.; Crowley, J.; Chansky, K.; Giroux, D.J.; Groome, P.A.; Rami-Porta, R.; Postmus, P.E.; Rusch, V.; Sobin, L. The IASLC lung cancer staging project: Proposals for the revision of the tnm stage groupings in the forthcoming (seventh) edition of the TNM classification of malignant tumours. J. Thorac. Oncol. 2007, 2, 706–714. [Google Scholar] [CrossRef] [Green Version]
- Sears, C.R.; Mazzone, P.J. Biomarkers in lung cancer. Clin. Chest Med. 2020, 41, 115–127. [Google Scholar] [CrossRef] [PubMed]
- National Lung Screening Trial Research Team; Aberle, D.R.; Adams, A.M.; Berg, C.D.; Black, W.C.; Clapp, J.D.; Fagerstrom, R.M.; Gareen, I.F.; Gatsonis, C.; Marcus, P.M.; et al. The national lung screening trial research team reduced Lung-Cancer mortality with Low-Dose computed tomographic screening. N. Engl. J. Med. 2011, 365, 395–409. [Google Scholar]
- Bach, P.B.; Mirkin, J.; Oliver, T.K.; Azzoli, C.G.; Berry, D.; Brawley, O.W.; Byers, T.; Colditz, G.A.; Gould, M.K.; Jett, J.R.; et al. Benefits and harms of CT screening for lung cancer: A systematic review. JAMA 2012, 307, 2418–2429. [Google Scholar] [CrossRef] [Green Version]
- Schwaederle, M.; Daniels, G.A.; Piccioni, D.E.; Fanta, P.T.; Schwab, R.B.; Shimabukuro, K.A.; Parker, B.A.; Kurzrock, R. On the road to precision cancer medicine: Analysis of genomic biomarker actionability in 439 patients. Mol. Cancer Ther. 2015, 14, 1488–1494. [Google Scholar] [CrossRef] [Green Version]
- Yamashita, K.; Hosoda, K.; Nishizawa, N.; Katoh, H.; Watanabe, M. Epigenetic biomarkers of promoter DNA methylation in the new era of cancer treatment. Cancer Sci. 2018, 109, 3695–3706. [Google Scholar] [CrossRef] [PubMed]
- Heitzer, E.; Haque, I.S.; Roberts, C.E.S.; Speicher, M.R. Current and future perspectives of liquid biopsies in genomics-driven oncology. Nat. Rev. Genet. 2018, 20, 71–88. [Google Scholar] [CrossRef] [PubMed]
- De Anda-Jáuregui, G.; Hernández-Lemus, E. Computational Oncology in the Multi-Omics Era: State of the Art. Front. Oncol. 2020, 10, 423. [Google Scholar] [CrossRef] [PubMed]
- Seijo, L.M.; Peled, N.; Ajona, D.; Boeri, M.; Field, J.; Sozzi, G.; Pio, R.; Zulueta, J.J.; Spira, A.; Massion, P.P.; et al. Biomarkers in lung cancer screening: Achievements, promises, and challenges. J. Thorac. Oncol. 2019, 14, 343–357. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Robles, A.I.; Harris, C.C. Integration of multiple “OMIC” biomarkers: A precision medicine strategy for lung cancer. Lung Cancer 2016, 107, 50–58. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Mishra, A.; Verma, M. Cancer Biomarkers: Are we ready for the prime time? Cancers 2010, 2, 190–208. [Google Scholar] [CrossRef]
- Inage, T.; Nakajima, T.; Yoshino, I.; Yasufuku, K. Early lung cancer detection. Clin. Chest Med. 2018, 39, 45–55. [Google Scholar] [CrossRef]
- Mazzone, P.J.; Sears, C.R.; Arenberg, D.A.; Gaga, M.; Gould, M.K.; Massion, P.P.; Nair, V.S.; Powell, C.A.; Silvestri, G.A.; Vachani, A.; et al. 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. 2017, 196, e15–e29. [Google Scholar] [CrossRef]
- Duffy, M.J.; O’Byrne, K. Tissue and blood biomarkers in lung cancer: A review. Adv. Clin. Chem. 2018, 86, 1–21. [Google Scholar]
- Arbour, K.C.; Riely, G.J. Systemic therapy for locally advanced and metastatic Non-Small cell lung cancer: A review. JAMA 2019, 322, 764–774. [Google Scholar] [CrossRef]
- Hirsch, F.R.; Scagliotti, G.V.; Mulshine, J.L.; Kwon, R.; Curran, W.J.; Wu, Y.-L.; Paz-Ares, L. Lung cancer: Current therapies and new targeted treatments. Lancet 2017, 389, 299–311. [Google Scholar] [CrossRef]
- Paulsen, E.-E.; Kilvaer, T.K.; Khanehkenari, M.R.; Al-Saad, S.; Hald, S.M.; Andersen, S.; Richardsen, E.; Ness, N.; Busund, L.-T.; Bremnes, R.M.; et al. Assessing PDL-1 and PD-1 in Non–Small Cell Lung Cancer: A novel immunoscore approach. Clin. Lung Cancer 2017, 18, 220–233. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- De Sousa, V.M.L.; Carvalho, L. Heterogeneity in lung cancer. Pathobiology 2018, 85, 96–107. [Google Scholar] [CrossRef]
- Gerlinger, M.; Horswell, S.; Larkin, J.; Rowan, A.J.; Salm, M.; Varela, I.; Fisher, R.; McGranahan, N.; Matthews, N.; Santos, C.R.; et al. Genomic architecture and evolution of clear cell renal cell carcinomas defined by multiregion sequencing. Nat. Genet. 2014, 46, 225–233. [Google Scholar] [CrossRef] [PubMed]
- Bedard, P.L.; Hansen, A.R.; Ratain, M.J.; Siu, L.L. Tumour heterogeneity in the clinic. Nature 2013, 501, 355–364. [Google Scholar] [CrossRef] [Green Version]
- Marusyk, A.; Polyak, K. Tumor heterogeneity: Causes and consequences. Biochim. Biophys. Acta Rev. Cancer 2010, 1805, 105–117. [Google Scholar] [CrossRef] [Green Version]
- Gerlinger, M.; Rowan, A.J.; Horswell, S.; Math, M.; Larkin, J.; Endesfelder, D.; Grönroos, E.; Martinez, P.; Matthews, N.; Stewart, A.; et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N. Engl. J. Med. 2012, 366, 883–892. [Google Scholar] [CrossRef] [Green Version]
- Hofman, P. The challenges of evaluating predictive biomarkers using small biopsy tissue samples and liquid biopsies from Non-Small cell lung cancer patients. J. Thorac. Dis. 2019, 11, S57–S64. [Google Scholar] [CrossRef]
- Edelsberg, J.; Weycker, D.; Atwood, M.; Hamilton-Fairley, G.; Jett, J.R. Cost-Effectiveness of an autoantibody test (EarlyCDT-Lung) as an aid to early diagnosis of lung cancer in patients with incidentally detected pulmonary nodules. PLoS ONE 2018, 13, e0197826. [Google Scholar] [CrossRef]
- Boyle, P.; Chapman, C.J.; Holdenrieder, S.; Murray, A.; Robertson, C.; Wood, W.C.; Maddison, P.; Healey, G.; Fairley, G.H.; Barnes, A.C.; et al. Clinical validation of an autoantibody test for lung cancer. Ann. Oncol. 2011, 22, 383–389. [Google Scholar] [CrossRef]
- Lam, S.; Boyle, P.; Healey, G.F.; Maddison, P.; Peek, L.; Murray, A.; Chapman, C.J.; Allen, J.; Wood, W.C.; Sewell, H.F.; et al. EarlyCDT-Lung: An immunobiomarker test as an aid to early detection of lung cancer. Cancer Prev. Res. 2011, 4, 1126–1134. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Chen, D.-T.; Hsu, Y.-L.; Fulp, W.J.; Coppola, M.; Haura, E.B.; Yeatman, T.J.; Cress, W.D. Prognostic and predictive value of a Malignancy-Risk gene signature in Early-Stage Non–Small cell lung cancer. J. Natl. Cancer Inst. 2011, 103, 1859–1870. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ajona, D.; Okrój, M.; Pajares, M.J.; Agorreta, J.; Lozano, M.D.; Zulueta, J.J.; Verri, C.; Roz, L.; Sozzi, G.; Pastorino, U.; et al. Complement C4d-Specific antibodies for the diagnosis of lung cancer. Oncotarget 2018, 9, 6346–6355. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Zhang, Y.; Sui, J.; Shen, X.; Li, C.; Yao, W.; Hong, W.; Peng, H.; Pu, Y.; Yin, L.; Liang, G. Differential expression profiles of microRNAs as potential biomarkers for the early diagnosis of lung cancer. Oncol. Rep. 2017, 37, 3543–3553. [Google Scholar] [CrossRef] [Green Version]
- Sozzi, G.; Boeri, M.; Rossi, M.; Verri, C.; Suatoni, P.; Bravi, F.; Roz, L.; Conte, D.; Grassi, M.; Sverzellati, N.; 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, 768–773. [Google Scholar] [CrossRef]
- Montani, F.; Marzi, M.J.; Dezi, F.; Dama, E.; Carletti, R.M.; Bonizzi, G.; Bertolotti, R.; Bellomi, M.; Rampinelli, C.; Maisonneuve, P.; et al. MIR-Test: A blood test for lung cancer early detection. J. Natl. Cancer Inst. 2015, 107, djv063. [Google Scholar] [CrossRef] [Green Version]
- Chaudhuri, A.A.; Chabon, J.J.; Lovejoy, A.F.; Newman, A.M.; Stehr, H.; Azad, T.; Khodadoust, M.S.; Esfahani, M.S.; Liu, C.L.; Zhou, L.; et al. Early detection of molecular residual disease in localized lung cancer by circulating tumor DNA profiling. Cancer Discov. 2017, 7, 1394–1403. [Google Scholar] [CrossRef] [Green Version]
- Cohen, J.D.; Li, L.; Wang, Y.; Thoburn, C.; Afsari, B.; Danilova, L.V.; Douville, C.; Javed, A.A.; Wong, F.; Mattox, A.; et al. Detection and localization of surgically resectable cancers with a Multi-Analyte blood test. Science 2018, 359, 926–930. [Google Scholar] [CrossRef] [Green Version]
- Oxnard, G.R.; Maddala, T.; Hubbell, E.; Aravanis, A.; Zhang, N.; Venn, O.; Valouev, A.; Shen, L.; Patel, S.; Jamshidi, A.; et al. Genome-Wide sequencing for early stage lung cancer detection from plasma Cell-Free DNA (cfDNA): The circulating cancer genome atlas (CCGA) study. J. Clin. Oncol. 2018, 36, LBA8501. [Google Scholar] [CrossRef]
- Gasparri, R.; Sedda, G.; Noberini, R.; Bonaldi, T.; Spaggiari, L. Clinical application of mass Spectrometry-Based proteomics in lung cancer early diagnosis. PROTEOM Clin. Appl. 2020. [Google Scholar] [CrossRef]
- Li, D.; Yang, W.; Zhang, Y.; Yang, J.Y.; Guan, R.; Xu, N.; Yang, M.Q. Genomic analyses based on pulmonary adenocarcinoma in situ reveal early lung cancer signature. BMC Med Genom. 2018, 11, 106. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Mu, Y.; Zhou, Y.; Wang, Y.; Li, W.; Zhou, L.; Lu, X.; Gao, P.; Gao, M.; Zhao, Y.; Wang, Q.; et al. Serum metabolomics study of nonsmoking female patients with non-small cell lung cancer using gas Chromatography–Mass spectrometry. J. Proteome Res. 2019, 18, 2175–2184. [Google Scholar] [CrossRef] [PubMed]
- Callejón-Leblic, B.; García-Barrera, T.; Pereira-Vega, A.; Gómez-Ariza, J.L. Metabolomic study of serum, urine and bronchoalveolar lavage fluid based on gas chromatography mass spectrometry to delve into the pathology of lung cancer. J. Pharm. Biomed. Anal. 2019, 163, 122–129. [Google Scholar] [CrossRef] [PubMed]
- Gasparri, R.; Santonico, M.; Valentini, C.; Sedda, G.; Borri, A.; Petrella, F.; Maisonneuve, P.; Pennazza, G.; D’Amico, A.; Di Natale, C.; et al. Volatile signature for the early diagnosis of lung cancer. J. Breath Res. 2016, 10, 16007. [Google Scholar] [CrossRef]
- Heavner, D.L.; Richardson, J.D.; Morgan, W.T.; Ogden, M.W. Validation and application of a method for the determination of nicotine and five major metabolites in smokers’ urine by Solid-Phase extraction and liquid Chromatography-Tandem mass spectrometry. Biomed. Chromatogr. 2005, 19, 312–328. [Google Scholar] [CrossRef]
- Carrola, J.; Rocha, C.; Barros, A.; Gil, A.M.; Goodfellow, B.; Carreira, I.M.; Bernardo, J.; Gomes, A.; De Sousa, V.M.L.; Carvalho, L.; et al. Metabolic signatures of lung cancer in biofluids: NMR-Based metabonomics of urine. J. Proteome Res. 2011, 10, 221–230. [Google Scholar] [CrossRef]
- An, Z.; Chen, Y.; Zhang, R.; Song, Y.; Sun, J.; He, J.; Bai, J.; Dong, L.; Zhan, Q.; Abliz, Z. Integrated Ionization Approach for RRLC−MS/MS-based metabonomics: Finding potential biomarkers for lung cancer. J. Proteome Res. 2010, 9, 4071–4081. [Google Scholar] [CrossRef]
- Yang, Q.; Shi, X.; Wang, Y.; Wang, W.; He, H.; Lü, X.; Xu, G. Urinary metabonomic study of lung cancer by a fully automatic hyphenated hydrophilic interaction/RPLC-MS system. J. Sep. Sci. 2010, 33, 1495–1503. [Google Scholar] [CrossRef]
- Nolen, B.M.; Lomakin, A.; Marrangoni, A.; Velikokhatnaya, L.; Prosser, D.; Lokshin, A. Urinary protein biomarkers in the early detection of lung cancer. Cancer Prev. Res. 2014, 8, 111–119. [Google Scholar] [CrossRef] [Green Version]
- Mathe, E.A.; Patterson, A.; Haznadar, M.; Manna, S.K.; Krausz, K.W.; Bowman, E.D.; Shields, P.G.; Idle, J.; Smith, P.B.; Anami, K.; et al. Noninvasive urinary metabolomic profiling identifies diagnostic and prognostic markers in lung cancer. Cancer Res. 2014, 74, 3259–3270. [Google Scholar] [CrossRef] [Green Version]
- Lai, J.; Du, B.; Wang, Y.; Wu, R.; Yu, Z. Next-Generation sequencing of circulating tumor DNA for detection of gene mutations in lung cancer: Implications for precision treatment. OncoTargets Ther. 2018, 11, 9111–9116. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Liang, W.; Zhao, Y.; Huang, W.; Gao, Y.; Xu, W.; Tao, J.; Yang, M.; Li, L.; Ping, W.; Shen, H.; et al. Non-Invasive diagnosis of Early-Stage lung cancer using High-Throughput targeted DNA methylation sequencing of circulating tumor DNA (ctDNA). Theranostics 2019, 9, 2056–2070. [Google Scholar] [CrossRef] [PubMed]
- Barrett, I.P. Cancer genome analysis informatics. In Choice Reviews Online; Barnes, M.R., Breen, G., Eds.; Methods in Molecular Biology; Humana Press: Totowa, NJ, USA, 2010; Volume 628, pp. 75–102. [Google Scholar]
- Chang, J.T.-H.; Lee, Y.-M.; Huang, R.S. The impact of the Cancer Genome Atlas on lung cancer. Transl. Res. 2015, 166, 568–585. [Google Scholar] [CrossRef] [Green Version]
- Srivastava, M.; Khurana, P.; Sugadev, R. Lung cancer signature biomarkers: Tissue specific semantic similarity based clustering of Digital Differential Display (DDD) data. BMC Res. Notes 2012, 5, 617. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Goncalves, R.; Bose, R. Using multigene tests to select treatment for Early-Stage breast cancer. J. Natl. Compr. Cancer Netw. 2013, 11, 174–182. [Google Scholar] [CrossRef]
- Okayama, H.; Schetter, A.J.; Ishigame, T.; Robles, A.I.; Kohno, T.; Yokota, J.; Takenoshita, S.; Harris, C.C. The Expression of Four Genes as a Prognostic Classifier for Stage I Lung Adenocarcinoma in 12 Independent Cohorts. Cancer Epidemiol. Biomarkers Prev. 2014, 23, 2884–2894. [Google Scholar] [CrossRef] [Green Version]
- Mazzone, P.J.; Wang, X.-F.; Han, X.; Choi, H.; Seeley, M.; Scherer, R.; Doseeva, V. Evaluation of a Serum Lung Cancer Biomarker Panel. Biomark. Insights 2018, 13. [Google Scholar] [CrossRef] [Green Version]
- Doseeva, V.; Colpitts, T.; Gao, G.; Woodcock, J.; Knezevic, V. Performance of a multiplexed dual analyte immunoassay for the early detection of Non-Small cell lung cancer. J. Transl. Med. 2015, 13, 55. [Google Scholar] [CrossRef] [Green Version]
- Abbosh, C.; Birkbak, N.J.; Wilson, G.A.; Jamal-Hanjani, M.; Constantin, T.; Salari, R.; Le Quesne, J.; Moore, D.A.; Veeriah, S.; Rosenthal, R.; et al. Phylogenetic ctDNA analysis depicts Early-Stage lung cancer evolution. Nature 2017, 545, 446–451. [Google Scholar] [CrossRef]
- Martínez-Terroba, E.; Behrens, C.; De Miguel, F.J.; Agorreta, J.; Monsó, E.; Millares, L.; Sainz, C.; Mesa-Guzman, M.; Perez-Gracia, J.L.; Lozano, M.D.; et al. A novel protein-based prognostic signature improves risk stratification to guide clinical management in Early-Stage lung adenocarcinoma patients. J. Pathol. 2018, 245, 421–432. [Google Scholar] [CrossRef]
- Okayama, A.; Miyagi, Y.; Oshita, F.; Nishi, M.; Nakamura, Y.; Nagashima, Y.; Akimoto, K.; Ryo, A.; Hirano, H. Proteomic analysis of proteins related to prognosis of lung adenocarcinoma. J. Proteome Res. 2014, 13, 4686–4694. [Google Scholar] [CrossRef] [PubMed]
- Pepe, M.S.; Etzioni, R.; Feng, Z.; Potter, J.D.; Thompson, M.L.; Thornquist, M.; Winget, M.; Yasui, Y. Phases of biomarker development for early detection of cancer. J. Natl. Cancer Inst. 2001, 93, 1054–1061. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Pepe, M.S.; Janes, H.; Li, C.I.; Bossuyt, P.M.; Feng, Z.; Hilden, J. Early-Phase studies of biomarkers: What target sensitivity and specificity values might confer clinical utility? Clin. Chem. 2016, 62, 737–742. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Global Burden of Disease Cancer Collaboration; Fitzmaurice, C.; Akinyemiju, T.F.; Al Lami, F.H.; Alam, T.; Alizadeh-Navaei, R.; Allen, C.; Alsharif, U.; Alvis-Guzman, N.; Amini, E.; et al. Global, regional, and national cancer incidence, mortality, years of life lost, years lived with disability, and Disability-Adjusted Life-Years for 29 Cancer Groups, 1990 to 2016: A systematic analysis for the global burden of disease study. JAMA Oncol. 2018, 4, 1553–1568. [Google Scholar]
- Topol, E.J. High-Performance medicine: The convergence of human and artificial intelligence. Nat. Med. 2019, 25, 44–56. [Google Scholar] [CrossRef]
- Miller, D.D.; Brown, E.W. Artificial intelligence in medical practice: The question to the answer? Am. J. Med. 2017, 131, 129–133. [Google Scholar] [CrossRef]
- Burki, T.K. Predicting lung cancer prognosis using machine learning. Lancet Oncol. 2016, 17, e421. [Google Scholar] [CrossRef]
- Goecks, J.; Jalili, V.; Heiser, L.M.; Gray, J.W. How machine learning will transform biomedicine. Cell 2020, 181, 92–101. [Google Scholar] [CrossRef]
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Gasparri, R.; Sedda, G.; Spaggiari, L. Biomarkers in Early Diagnosis and Early Stage Lung Cancer: The Clinician’s Point of View. J. Clin. Med. 2020, 9, 1790. https://doi.org/10.3390/jcm9061790
Gasparri R, Sedda G, Spaggiari L. Biomarkers in Early Diagnosis and Early Stage Lung Cancer: The Clinician’s Point of View. Journal of Clinical Medicine. 2020; 9(6):1790. https://doi.org/10.3390/jcm9061790
Chicago/Turabian StyleGasparri, Roberto, Giulia Sedda, and Lorenzo Spaggiari. 2020. "Biomarkers in Early Diagnosis and Early Stage Lung Cancer: The Clinician’s Point of View" Journal of Clinical Medicine 9, no. 6: 1790. https://doi.org/10.3390/jcm9061790
APA StyleGasparri, R., Sedda, G., & Spaggiari, L. (2020). Biomarkers in Early Diagnosis and Early Stage Lung Cancer: The Clinician’s Point of View. Journal of Clinical Medicine, 9(6), 1790. https://doi.org/10.3390/jcm9061790