Patient specific circulating tumor DNA fingerprints to monitor treatment response across multiple tumors

Journal of Translational Medicine - 2020
Jiaping Li1, Wei Jiang2, Jie Wei3, Jianwei Zhang4, Linbo Cai5, Minjie Luo6, Zhan Wang7, Weitao Sun3, Shengzhou Wang3, Chen Wang3, Chun Dai3, Jun Li3, Guan Wang3, Jiping Wang8, Qiang Xu3, Yanhong Deng4
1Department of Interventional Oncology, The First Affiliated Hospital of Sun Yat-sen University, Guangdong, China
2Department of Radiation Oncology, Huanhu Hospital, Tianjin, China
3GenomiCare Biotechnology Co. Ltd, Shanghai, China
4Department of Medical Oncology, The Sixth Affiliated Hospital of Sun Yat-sen University, No. 26 Erheng Road, Tianhe District, Guangzhou, 510655, China
5Department of Oncology, Guangdong 999 Brain Hospital, Guangdong, China
6Department of Pediatric Neurosurgery, Zhujiang Hospital of Southern Medical University, Guangdong, China
7Department of Medical Oncology, Changzheng Hospital, The Second Military Medical University, Shanghai, China
8Division of Surgical Oncology, Brigham and Women’s Hospital, Boston, MA, USA

Tóm tắt

Abstract Background Circulating tumor DNA (ctDNA) offers a convenient way to monitor tumor progression and treatment response. Because tumor mutational profiles are highly variable from person to person, a fixed content panel may be insufficient to track treatment response in all patients. Methods We design ctDNA fingerprint panels specific to individual patients which are based on whole exome sequencing and target to high frequency clonal population clusters in patients. We test the fingerprint panels in 313 patients who together have eight tumor types (colorectal, hepatocellular, gastric, breast, pancreatic, and esophageal carcinomas and lung cancer and cholangiocarcinoma) and exposed to multiple treatment methods (surgery, chemotherapy, radiotherapy, targeted-drug therapy, immunotherapy, and combinations of them). We also monitor drug-related mutations in the patients using a pre-designed panel with eight hotspot genes. Results 291 (93.0%) designed fingerprint panels harbor less than ten previously known tumor genes. We detected 7475 ctDNA mutations in 238 (76%) patients and 6196 (96.0%) of the mutations are detected in only one test. Both the level of ctDNA content fraction (CCF) and fold change of CCF (between the definitive and proceeding tests) are highly correlated with clinical outcomes (p-values 1.36e-6 for level and 5.64e-10 for fold change, Kruskal–Wallis test). The CCFs of PD patients are an order of magnitude higher than the CCFs of SD and OR patients (median/mean 2.22%/8.96% for SD, 0.18/0.21% for PD, and 0.31/0.54% for OR; pairwise p-values 7.8e-6 for SD ~ PD, 2.7e-4 for OR ~ PD, and 7.0e-3 for SD ~ OR, Wilcoxon rank sum test). The fold change of CCF distinguishes the patient groups even better, which increases for PD, remains stable for SD, and decreases for OR patients (p-values 0.002, ~ 1, and 0.0001 respectively, Wilcoxon signed-rank test). Eleven drug-related mutations are identified from nine out of the 313 patients. Conclusions The ctDNA fingerprint method improves both specificity and sensitivity of monitoring treatment response across several tumor types. It can identify tumor relapse/recurrence potentially earlier than imaging-based diagnosis. When augmented with tumor hotspot genes, it can track acquired drug-related mutations in patients.

Từ khóa


Tài liệu tham khảo

Wan JCM, et al. Liquid biopsies come of age: towards implementation of circulating tumour DNA. Nat Rev Cancer. 2017;17:223–38.

Diehl F, et al. Circulating mutant DNA to assess tumor dynamics. Nat Med. 2008;14:985–90.

Xu R, et al. Circulating tumour DNA methylation markers for diagnosis and prognosis of hepatocellular carcinoma. Nat Mater. 2017;16:1155–61.

Sawyers CL. The cancer biomarker problem. Nature. 2008;452:548–52.

Umelo IA, Costanza B, Castronovo V. Innovative methods for biomarker discovery in the evaluation and development of cancer precision therapies. Cancer Metastasis Rev. 2018;37:125–45.

Cescon DW, Bratman SV, Chan SM, Siu LL. Circulating tumor DNA and liquid biopsy in oncology. Nat Cancer. 2020;1:276–90.

Jia N, et al. Serial monitoring of circulating tumor DNA in patients with metastatic colorectal cancer to predict the therapeutic response. Front Genet. 2019;10:470.

Parikh AR, et al. Serial ctDNA monitoring to predict response to systemic therapy in metastatic gastrointestinal cancers. Clin Cancer Res. 2020;26:1877–85.

Tie J, et al. Circulating tumor DNA as an early marker of therapeutic response in patients with metastatic colorectal cancer. Ann Oncol Off J Eur Soc Med Oncol. 2015;26:1715–22.

Corcoran RB, et al. Combined BRAF, EGFR, and MEK inhibition in patients with BRAFV600E-mutant colorectal cancer. Cancer Discov. 2018;8:428–43.

Riva F, et al. Patient-Specific circulating tumor DNA detection during neoadjuvant chemotherapy in triple-negative breast cancer. Clin Chem. 2017;63:691–9.

Araujo DV, Bratman SV, Siu LL. Designing circulating tumor DNA-based interventional clinical trials in oncology. Genome Med. 2019;11:22.

Lam SN, et al. Comparison of target enrichment platforms for circulating tumor DNA detection. Sci Rep. 2020;10:4124.

Stetson D et al., Orthogonal comparison of four plasma NGS tests with tumor suggests technical factors are a major source of assay discordance. JCO Precis Oncol. 2019; 1–9.

Abbosh C, et al. Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution. Nature. 2017;545:446–51.

McDonald BR, et al. Personalized circulating tumor DNA analysis to detect residual disease after neoadjuvant therapy in breast cancer. Sci Transl Med. 2019;11:eaax7392.

Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009;25:1754–60.

DePristo MA, et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat Genet. 2011;43:491–8.

Zang Y, et al. Comprehensive analysis of potential immunotherapy genomic biomarkers in 1000 Chinese patients with cancer. Cancer Med. 2019;8:4699–708.

McLaren W, et al. The ensembl variant effect predictor. Genome Biol. 2016;17:122.

Chalmers ZR, et al. Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden. Genome Med. 2017;9:34.

Loman NJ, et al. Correction: corrigendum: performance comparison of benchtop high-throughput sequencing platforms. Nat Biotechnol. 2012;30:562.

Chennagiri N, et al. Orthogonal NGS for high throughput clinical diagnostics. Sci Rep. 2016;6:24650.

Miller CA, et al. SciClone: inferring clonal architecture and tracking the spatial and temporal patterns of tumor evolution. PLoS Comput Biol. 2014;10:e1003665.

Koboldt DC, et al. VarScan 2: somatic mutation and copy number alteration discovery in cancer by exome sequencing. Genome Res. 2012;22:568–76.

COSMIC, Catalogue of Somatic Mutations in Cancer—drug resistance. Welcome Sanger Inst. (June 24, 2020). 2020

Holohan C, Van Schaeybroeck S, Longley DB, Johnston PG. Cancer drug resistance: an evolving paradigm. Nat Rev Cancer. 2013;13:714–26.

Li H, et al. The sequence alignment/map format and SAMtools. Bioinformatics. 2009;25:2078–9.

Griffith M, et al. CIViC is a community knowledgebase for expert crowdsourcing the clinical interpretation of variants in cancer. Nat Genet. 2017;49:170–4.

Corcoran RB, Chabner BA. Application of cell-free DNA analysis to cancer treatment. N Engl J Med. 2018;379:1754–65.

Merker JD, et al. Circulating tumor DNA analysis in patients with cancer: American society of clinical oncology and college of American pathologists joint review. J Clin Oncol Off J Am Soc Clin Oncol. 2018;36:1631–41.

Zill OA, et al. The landscape of actionable genomic alterations in cell-free circulating tumor DNA from 21,807 advanced cancer patients. Clin Cancer Res. 2018;24:3528.

Reinert T, et al. Analysis of circulating tumour DNA to monitor disease burden following colorectal cancer surgery. Gut. 2016;65:625.

Tie J, et al. Circulating tumor DNA analysis detects minimal residual disease and predicts recurrence in patients with stage II colon cancer. Sci Transl Med. 2016;8:346ra92.

Hsu H-C, et al. Targeted sequencing of circulating tumor DNA to monitor genetic variants and therapeutic response in metastatic colorectal cancer. Mol Cancer Ther. 2018;17:2238.

Birkenkamp-Demtröder K, et al. Monitoring treatment response and metastatic relapse in advanced bladder cancer by liquid biopsy analysis. Eur Urol. 2018;73:535–40.

Dawson S-J, et al. Analysis of circulating tumor DNA to monitor metastatic breast cancer. N Engl J Med. 2013;368:1199–209.

Lee JH, et al. Association between circulating tumor DNA and pseudoprogression in patients with metastatic melanoma treated with anti-programmed cell death 1 antibodies. JAMA Oncol. 2018;4:717–21.

Razavi P, et al. Cell-free DNA (cfDNA) mutations from clonal hematopoiesis: implications for interpretation of liquid biopsy tests. J Clin Oncol. 2017;35:11526.

Genovese G, et al. Clonal hematopoiesis and blood-cancer risk inferred from blood DNA sequence. N Engl J Med. 2014;371:2477–87.

Chaudhuri AA, et al. Early detection of molecular residual disease in localized lung cancer by circulating tumor DNA profiling. Cancer Discov. 2017;7:1394–403.

Abbosh C, Birkbak NJ, Swanton C. Early stage NSCLC—challenges to implementing ctDNA-based screening and MRD detection. Nat Rev Clin Oncol. 2018;15:577–86.

Newman AM, et al. An ultrasensitive method for quantitating circulating tumor DNA with broad patient coverage. Nat Med. 2014;20:548–54.

Lanman RB, et al. Analytical and clinical validation of a digital sequencing panel for quantitative, highly accurate evaluation of cell-free circulating tumor DNA. PLoS ONE. 2015;10:e0140712.

Samstein RM, et al. Tumor mutational load predicts survival after immunotherapy across multiple cancer types. Nat Genet. 2019;51:202–6.

Galsky M et al., Nivolumab in patients with advanced platinum-resistant Urothelial Carcinoma: efficacy, safety, and biomarker analyses with extended follow-up from CheckMate 275. Clin. Cancer Res. 2020.

Giroux Leprieur E, et al. 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. 2018;7:e1424675.

Reinert T, et al. Analysis of plasma cell-free DNA by Ultradeep sequencing in patients with stages I to III colorectal cancer. JAMA Oncol. 2019;5:1124–31.

Wang Y, et al. Prognostic potential of circulating tumor DNA measurement in postoperative surveillance of nonmetastatic colorectal cancer. JAMA Oncol. 2019;5:1118–23.

Thông tin
Thông tin xuất bản

Journal of Translational Medicine

Thông tin tác giả