Early responses of EGFR circulating tumor DNA to EGFR tyrosine kinase inhibitors in lung cancer treatment

Fumio Imamura, Junji Uchida, Yoji Kukita, Toru Kumagai, Kazumi Nishino, Takako Inoue, Madoka Kimura, Kikuya Kato, Fumio Imamura, Junji Uchida, Yoji Kukita, Toru Kumagai, Kazumi Nishino, Takako Inoue, Madoka Kimura, Kikuya Kato

Abstract

Objectives: Early evaluation of the effect of treatment is helpful in the management of cancer patients. Circulating biomarkers are an ideal tool for this if they are highly specific to tumors and respond rapidly to tumor volume changes. Circulating tumor DNA (ctDNA) is one such candidate. We conducted a prospective study to test the utility of EGFR ctDNA in early evaluation of EGFR-TKI effects.

Results: Twenty-one patients with EGFR-mutant lung cancer who were naïve to EGFR-TKI were enrolled. PM scores of EGFR ctDNA with activating mutations decreased rapidly in response to EGFR-TKI. Of the 14 patients with positive pretreatment PM scores, complete disappearance of major EGFR ctDNA was observed in 14.3%, 42.9%, and 57.1% on days 2 - 4, 8, and 15, respectively. These responses of EGFR ctDNA were most prominent among the measures used to evaluate responses, and correlated with early radiologic responses evaluated by chest X-rays.

Materials and methods: EGFR ctDNA in serial plasma samples was amplified and 105 copies were sequenced with a next-generation sequencer. Plasma mutation (PM) score was defined as the number of reads containing deletions/substitutions in 105EGFR cell free DNA (cfDNA). When EGFR mutation in ctDNA was the same as that detected in cancer tissue, the ctDNA was defined as major EGFR ctDNA.

Conclusions: The results indicate the usefulness of ctDNA as a highly specific biomarker for prediction of early response to treatment and that it can be applied to various types of cancer.

Keywords: EGFR; EGFR-TKI; lung cancer; mutation; response evaluation.

Conflict of interest statement

CONFLICTS OF INTEREST

K. Kato will be an employee of DNA Chip Research Inc. from 1st April 2016.

Figures

Figure 1. Response pattern of major EGFR…
Figure 1. Response pattern of major EGFR ctDNA to EGFR-TKI treatment during the first 14 days
(A) All patients with positive pretreatment EGFR ctDNA values. Red, black, and blue lines represent CR, PR, and SD cases, respectively. (B) Patients in whom the response to an EGFR-TKI during the first 14 days was evaluable in chest X-p. Black, orange, and blue lines represent PR, MR, and SD cases, respectively. CR, complete regression; PR, partial regression; MR, minor regression; SD, stable disease.
Figure 2. Percent values of EGFR ctDNA…
Figure 2. Percent values of EGFR ctDNA in 14 patients in the periods 1 – 3 in comparison with the pretreatment values
Figure 3. Response of minor EGFR ctDNA…
Figure 3. Response of minor EGFR ctDNA to EGFR-TKI treatment during the first 14 days
Minor ctDNA appeared in 8 patients. Solid and dashed lines represent EGFR ctDNA with activating mutations (4 cases) and T790M (4 cases), respectively.
Figure 4. Mathematical models of circulating biomarkers
Figure 4. Mathematical models of circulating biomarkers
The half-life of tumor regression is postulated to be 6 days. (A) Effect of half-life on concentration of biomarkers. Solid and dashed lines represent biomarkers with a half-life of 2 hours and 7 days, respectively. (B) The effect of sensitive cancer cell volume on concentration of biomarkers. Solid and dashed lines represent biomarkers in the sensitive volume of cancer cells to be 100% and 50%, respectively. The half-life of the biomarker is postulated to be 2 hours.
Figure 5. Changes in various circulating biomarkers…
Figure 5. Changes in various circulating biomarkers during the first two weeks in 6 patients with positive pretreatment values both in EGFR ctDNA and at least one widely used tumor marker
Continuous lines, dashed lines, and long dashed dotted lines represent EGFR ctDNA, CEA, and CYFRA, respectively. Figure 1.

References

    1. Usmanij EA, de Geus-Oei LF, Troost EG, Peters-Bax L, van der Heijden EH, Kaanders JH, Oyen WJ, Schuurbiers OC, Bussink J. 18F-FDG PET early response evaluation of locally advanced non-small cell lung cancer treated with concomitant chemoradiotherapy. J Nucl Med. 2013;54:1528–1534.
    1. Takahashi R1, Hirata H, Tachibana I, Shimosegawa E, Inoue A, Nagatomo I, Takeda Y, Kida H, Goya S, Kijima T, Yoshida M, Kumagai T, Kumanogoh A, et al. Early [18F]fluorodeoxyglucose positron emission tomography at two days of gefitinib treatment predicts clinical outcome in patients with adenocarcinoma of the lung. Clin Cancer Res. 2012;18:220–228.
    1. Schwarzenbach H, Hoon DS, Pantel K. Cell-free nucleic acids as biomarkers in cancer patients. Nat Rev Cancer. 2011;11:426–437.
    1. Diehl F, Schmidt K, Choti MA, Romans K, Goodman S, Li M, Thornton K, Agrawal N, Sokoll L, Szabo SA, Kinzler KW, Vogelstein B, Diaz LA., Jr Circulating mutant DNA to assess tumor dynamics. Nature Med. 2008;14:985–990.
    1. Jiang T, Ren S, Zhou C. Role of circulating-tumor DNA analysis in non-small cell lung cancer. Lung Cancer. 2015;90:128–134.
    1. Maemondo M, Inoue A, Kobayashi K, Sugawara S, Oizumi S, Isobe H, Gemma A, Harada M, Yoshizawa H, Kinoshita I, Fujita Y, Okinaga S, Hirano H, et al. Gefitinib or chemotherapy for non-small-cell lung cancer with mutated EGFR. N Engl J Med. 2010;362:2380–2388.
    1. Rosell R, Carcereny E, Gervais R, Vergnenegre A, Massuti B, Felip E, Palmero R, Garcia-Gomez R, Pallares C, Sanchez JM, Porta R, Cobo M, Garrido P, et al. Erlotinib versus standard chemotherapy as first-line treatment for European patients with advanced EGFR mutation-positive non-small-cell lung cancer (EURTAC): a multicentre, open-label, randomised phase 3 trial. Lancet Oncol. 2012;13:239–246.
    1. Uchida J, Imamura F, Kukita Y, Oba S, Kumagai T, Nishino K, Inoue T, Kimura M, Kato K. Dynamics of circulating tumor DNA represented by the activating and resistant mutations in the EGFR-TKI treatment. Cancer Sci. 2015 in press.
    1. Imamura F, Uchida J, Kukita Y, Kumagai T, Nishino K, Inoue T, Kimura M, Oba S, Kato K. Monitoring of treatment responses and clonal evolution of tumor cells by circulating tumor DNA of heterogeneous mutant EGFR genes in lung cancer. Lung cancer. 2016;94:68–73.
    1. Eisenhauer EA, Therasse P, Bogaerts J, Schwartz LH, Sargent D, Ford R, Dancey J, Arbuck S, Gwyther S, Mooney M, Rubinstein L, Shankar L, Dodd L, et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version1. 1) Eur J Cancer. 2009;45:228–247.
    1. Marchetti A, Palma JF, Felicioni L, De Pas TM, Chiari R, Grammastro MD, Filice G, Ludovini V, Brandes AA, Chella A, Malorgio F, Guglielmi F, Tursi MD, et al. Early prediction of response to tyrosine kinase inhibitors by quantification of EGFR mutations in plasma of NSCLC patients. J Thorac Oncol. 2015;10:1437–1443.
    1. Karachaliou N, de las Casas CM, Queralt C, de Aguirre I, Melloni B, Cardenal F, Garcia-Gomez R, Massuti B, Sánchez JM, Porta R, Ponce-Aix S, Moran T, Carcereny E, et al. Association of EGFR L858R mutation in circulating free DNA with survival in the EURTAC trial. JAMA Oncol. 2015;1:149–157.
    1. Taniguchi K, Uchida J, Nishino K, Kumagai T, Okuyama T, Okami J, Higashiyama M, Kodama K, Imamura F, Kato K. Quantitative detection of EGFR mutations in circulating tumor DNA derived from lung adenocarcinomas. Clin Cancer Res. 2011;17:7808–7815.
    1. Kukita Y, Uchida J, Oba S, Nishino K, Kumagai T, Taniguchi K, Okuyama T, Imamura F, Kato K. Quantitative identification of mutant alleles derived from lung cancer in plasma cell-free DNA via anomaly detection using deep sequencing data. PLoS One. 2013;8:e81468.
    1. Uchida J, Kato K, Kukita Y, Kumagai T, Nishino K, Daga H, Nagatomo I, Inoue T, Kimura M, Oba S, Ito Y, Takeda K, Imamura F. Diagnostic accuracy of noninvasive genotyping of EGFR in lung cancer patients by deep sequencing of plasma cell-free DNA. Clin Chem. 2015;61:1191–1196.
    1. Diaz Jr LA, Bardelli A. Liquid biopsies: Genotyping circulating tumor DNA. J Clin Oncol. 2014;32:579–586.
    1. Bidart JM, Thuillier F, Augereau C, Chalas J, Daver A, Jacob N, Labrousse F, Voitot H. Kinetics of serum tumor marker concentrations and usefulness in clinical monitoring. Clinical Chemistry. 1999;45:10. 1695–1707.

Source: PubMed

3
Prenumerera