J Tie1, I Kinde2, Y Wang2, H L Wong3, J Roebert4, M Christie5, M Tacey6, R Wong7, M Singh8, C S Karapetis9, J Desai5, B Tran10, R L Strausberg11, L A Diaz2, N Papadopoulos2, K W Kinzler2, B Vogelstein2, P Gibbs12. 1. Division of Systems Biology and Personalised Medicine, Walter and Eliza Hall Institute of Medical Research, Melbourne Department of Medical Oncology, Western Hospital, Melbourne Department of Medical Oncology, The Royal Melbourne Hospital, Melbourne Faculty of Medicine Dentistry and Health Sciences, The University of Melbourne, Melbourne, Australia jeanne.tie@mh.org.au. 2. Ludwig Center for Cancer Genetics and Therapeutics, Howard Hughes Medical Institute at Johns Hopkins Kimmel Cancer Center, Baltimore, USA. 3. Division of Systems Biology and Personalised Medicine, Walter and Eliza Hall Institute of Medical Research, Melbourne Department of Medical Oncology, The Royal Melbourne Hospital, Melbourne Faculty of Medicine Dentistry and Health Sciences, The University of Melbourne, Melbourne, Australia Faculty of Medicine, Nursing and Health Sciences, Monash University, Eastern Health Clinical School, Melbourne. 4. MIA Radiology, Melbourne. 5. Division of Systems Biology and Personalised Medicine, Walter and Eliza Hall Institute of Medical Research, Melbourne Department of Medical Oncology, The Royal Melbourne Hospital, Melbourne Faculty of Medicine Dentistry and Health Sciences, The University of Melbourne, Melbourne, Australia. 6. Melbourne EpiCentre, Department of Medicine, The University of Melbourne, Melbourne. 7. Faculty of Medicine, Nursing and Health Sciences, Monash University, Eastern Health Clinical School, Melbourne. 8. Andrew Love Cancer Centre, Barwon Health, Geelong. 9. Department of Medical Oncology, Flinders University, Adelaide, Australia. 10. Division of Systems Biology and Personalised Medicine, Walter and Eliza Hall Institute of Medical Research, Melbourne Department of Medical Oncology, Western Hospital, Melbourne Department of Medical Oncology, The Royal Melbourne Hospital, Melbourne Faculty of Medicine Dentistry and Health Sciences, The University of Melbourne, Melbourne, Australia. 11. Ludwig Institute for Cancer Research, New York, USA. 12. Division of Systems Biology and Personalised Medicine, Walter and Eliza Hall Institute of Medical Research, Melbourne Department of Medical Oncology, Western Hospital, Melbourne Department of Medical Oncology, The Royal Melbourne Hospital, Melbourne Faculty of Medicine Dentistry and Health Sciences, The University of Melbourne, Melbourne, Australia Ludwig Institute for Cancer Research, New York, USA Ludwig Institute for Cancer Research, Melbourne, Australia.
Abstract
BACKGROUND: Early indicators of treatment response in metastatic colorectal cancer (mCRC) could conceivably be used to optimize treatment. We explored early changes in circulating tumor DNA (ctDNA) levels as a marker of therapeutic efficacy. PATIENTS AND METHODS: This prospective study involved 53 mCRC patients receiving standard first-line chemotherapy. Both ctDNA and CEA were assessed in plasma collected before treatment, 3 days after treatment and before cycle 2. Computed tomography (CT) scans were carried out at baseline and 8-10 weeks and were centrally assessed using RECIST v1.1 criteria. Tumors were sequenced using a panel of 15 genes frequently mutated in mCRC to identify candidate mutations for ctDNA analysis. For each patient, one tumor mutation was selected to assess the presence and the level of ctDNA in plasma samples using a digital genomic assay termed Safe-SeqS. RESULTS: Candidate mutations for ctDNA analysis were identified in 52 (98.1%) of the tumors. These patient-specific candidate tissue mutations were detectable in the cell-free DNA from the plasma of 48 of these 52 patients (concordance 92.3%). Significant reductions in ctDNA (median 5.7-fold; P < 0.001) levels were observed before cycle 2, which correlated with CT responses at 8-10 weeks (odds ratio = 5.25 with a 10-fold ctDNA reduction; P = 0.016). Major reductions (≥10-fold) versus lesser reductions in ctDNA precycle 2 were associated with a trend for increased progression-free survival (median 14.7 versus 8.1 months; HR = 1.87; P = 0.266). CONCLUSIONS: ctDNA is detectable in a high proportion of treatment naïve mCRC patients. Early changes in ctDNA during first-line chemotherapy predict the later radiologic response.
BACKGROUND: Early indicators of treatment response in metastatic colorectal cancer (mCRC) could conceivably be used to optimize treatment. We explored early changes in circulating tumor DNA (ctDNA) levels as a marker of therapeutic efficacy. PATIENTS AND METHODS: This prospective study involved 53 mCRC patients receiving standard first-line chemotherapy. Both ctDNA and CEA were assessed in plasma collected before treatment, 3 days after treatment and before cycle 2. Computed tomography (CT) scans were carried out at baseline and 8-10 weeks and were centrally assessed using RECIST v1.1 criteria. Tumors were sequenced using a panel of 15 genes frequently mutated in mCRC to identify candidate mutations for ctDNA analysis. For each patient, one tumor mutation was selected to assess the presence and the level of ctDNA in plasma samples using a digital genomic assay termed Safe-SeqS. RESULTS: Candidate mutations for ctDNA analysis were identified in 52 (98.1%) of the tumors. These patient-specific candidate tissue mutations were detectable in the cell-free DNA from the plasma of 48 of these 52 patients (concordance 92.3%). Significant reductions in ctDNA (median 5.7-fold; P < 0.001) levels were observed before cycle 2, which correlated with CT responses at 8-10 weeks (odds ratio = 5.25 with a 10-fold ctDNA reduction; P = 0.016). Major reductions (≥10-fold) versus lesser reductions in ctDNA precycle 2 were associated with a trend for increased progression-free survival (median 14.7 versus 8.1 months; HR = 1.87; P = 0.266). CONCLUSIONS: ctDNA is detectable in a high proportion of treatment naïve mCRC patients. Early changes in ctDNA during first-line chemotherapy predict the later radiologic response.
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