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  • Perspective
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Practical recommendations for using ctDNA in clinical decision making

Nature volume 619, pages 259–268 (2023)Cite this article

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Abstract

The continuous improvement in cancer care over the past decade has led to a gradual decrease in cancer-related deaths. This is largely attributed to improved treatment and disease management strategies. Early detection of recurrence using blood-based biomarkers such as circulating tumour DNA (ctDNA) is being increasingly used in clinical practice. Emerging real-world data shows the utility of ctDNA in detecting molecular residual disease and in treatment-response monitoring, helping clinicians to optimize treatment and surveillance strategies. Many studies have indicated ctDNA to be a sensitive and specific biomarker for recurrence. However, most of these studies are largely observational or anecdotal in nature, and peer-reviewed data regarding the use of ctDNA are mainly indication-specific. Here we provide general recommendations on the clinical utility of ctDNA and how to interpret ctDNA analysis in different treatment settings, especially in patients with solid tumours. Specifically, we provide an understanding around the implications, strengths and limitations of this novel biomarker and how to best apply the results in clinical practice.

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Fig. 1: Interpretation of ctDNA results in the peri-operative setting and prognostic value of ctDNA status prior to surgery for predicting survival outcomes.
Fig. 2: ctDNA detection in different clinical scenarios.

Data availability

All data generated or analysed during this study are included in this Perspective. Informed consent was obtained as part of the ordering assay. This study was approved by the corresponding Ethical and Independent Review Services (protocol no. 20-049-ALL) and was conducted in accordance with the Declaration of Helsinki. Further enquiries can be directed to the corresponding author.

References

  1. American Cancer Society. Risk of Dying from Cancer Continues to Drop at an Accelerated Pace https://www.cancer.org/latest-news/facts-and-figures-2022.html (2022).

  2. Arnold, M. et al. Progress in cancer survival, mortality, and incidence in seven high-income countries 1995–2014 (ICBP SURVMARK-2): a population-based study. Lancet Oncol. 20, 1493–1505 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  3. Pinzani, P. et al. Updates on liquid biopsy: current trends and future perspectives for clinical application in solid tumors. Clin. Chem. Lab. Med. 59, 1181–1200 (2021).

    Article  CAS  PubMed  Google Scholar 

  4. Long, N. M. & Smith, C. S. Causes and imaging features of false positives and false negatives on F-PET/CT in oncologic imaging. Insights Imaging 2, 679–698 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Sørensen, C. G., Karlsson, W. K., Pommergaard, H. C., Burcharth, J. & Rosenberg, J. The diagnostic accuracy of carcinoembryonic antigen to detect colorectal cancer recurrence—a systematic review. Int. J. Surg. 25, 134–144 (2016).

    Article  PubMed  Google Scholar 

  6. Hing, J. X. et al. Clinical utility of tumour marker velocity of cancer antigen 15–3 (CA 15–3) and carcinoembryonic antigen (CEA) in breast cancer surveillance. Breast 52, 95–101 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Litvak, A. et al. False-positive elevations of carcinoembryonic antigen in patients with a history of resected colorectal cancer. J. Natl Compr. Canc. Netw. 12, 907–913 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Moss, E. L., Hollingworth, J. & Reynolds, T. M. The role of CA125 in clinical practice. J. Clin. Pathol. 58, 308 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Long, G. et al. Impact of baseline serum lactate dehydrogenase concentration on the efficacy of pembrolizumab and ipilimumab in patients with advanced melanoma: data from KEYNOTE-006. Eur. J. Cancer 72, S122–S123 (2017).

    Article  Google Scholar 

  10. Bachet, J. B. et al. RAS mutation analysis in circulating tumor DNA from patients with metastatic colorectal cancer: the AGEO RASANC prospective multicenter study. Ann. Oncol. 29, 1211–1219 (2018).

    Article  CAS  PubMed  Google Scholar 

  11. Elazezy, M. & Joosse, S. A. Techniques of using circulating tumor DNA as a liquid biopsy component in cancer management. Comput. Struct. Biotechnol. J. 16, 370–378 (2018). This review summarizes how ctDNA may be used in the clinical management of patients with cancer, as well as the current technologies that are available for measuring ctDNA.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Hasenleithner, S. O. & Speicher, M. R. A clinician’s handbook for using ctDNA throughout the patient journey. Mol. Cancer 21, 81 (2022). This review discusses the various approaches to measuring ctDNA, how to select the most appropriate test for each clinical application, and the pipeline of tests available.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Bos, M. K. et al. Comparison of variant allele frequency and number of mutant molecules as units of measurement for circulating tumor DNA. Mol. Oncol. 15, 57–66 (2021).

    Article  CAS  PubMed  Google Scholar 

  14. Krebs, M. G. et al. Practical considerations for the use of circulating tumor DNA in the treatment of patients with cancer: a narrative review. JAMA Oncol. 8, 1830–1839 (2022). This narrative review summarizes the considerations required for including ctDNA testing in the clinical management of patients with cancer, including the decision on which assay is most appropriate for each clinical use.

    Article  PubMed  Google Scholar 

  15. Boonstra, P. A. et al. Clinical utility of circulating tumor DNA as a response and follow-up marker in cancer therapy. Cancer Metastasis Rev. 39, 999–1013 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Kasi, P. M. et al. Impact of circulating tumor DNA-based detection of molecular residual disease on the conduct and design of clinical trials for solid tumors. JCO Precis. Oncol. 6, e2100181 (2022). This review surveys the landscape of clinical trials that integrate ctDNA into the evaluation of patients and treatment outcomes.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Bratman, S. V. et al. Personalized circulating tumor DNA analysis as a predictive biomarker in solid tumor patients treated with pembrolizumab. Nat. Cancer 1, 873–881 (2020). This prospective phase 2 clinical trial evaluated ctDNA in patients with advanced solid tumors treated with pembolizumab.

    Article  CAS  PubMed  Google Scholar 

  18. Christensen, E. et al. Early detection of metastatic relapse and monitoring of therapeutic efficacy by ultra-deep sequencing of plasma cell-free DNA in patients with urothelial bladder carcinoma. J. Clin. Oncol. 37, 1547–1557 (2019).

    Article  CAS  PubMed  Google Scholar 

  19. Coombes, R. C. et al. Personalized detection of circulating tumor DNA antedates breast cancer metastatic recurrence. Clin. Cancer Res. 25, 4255–4263 (2019).

    Article  CAS  PubMed  Google Scholar 

  20. Reinert, T. et al. Analysis of plasma cell-free DNA by ultradeep sequencing in patients with stages I to III colorectal cancer. JAMA Oncol. 5, 1124–1131 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Cisneros-Villanueva, M. et al. Cell-free DNA analysis in current cancer clinical trials: a review. Br. J. Cancer 126, 391–400 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Malla, M., Loree, J. M., Kasi, P. M. & Parikh, A. R. Using circulating tumor DNA in colorectal cancer: current and evolving practices. J. Clin. Oncol. 40, 2846–2857 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Chen, K. et al. Commercial ctDNA assays for minimal residual disease detection of solid tumors. Mol. Diagn. Ther. 25, 757–774 (2021). This review summarizes the commercial platforms and underlying technologies as well as clinical trials that are incorporating ctDNA evaluation for MRD detection.

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  24. Gale, D. et al. Residual ctDNA after treatment predicts early relapse in patients with early-stage non-small cell lung cancer. Ann. Oncol. 33, 500–510 (2022).

    Article  CAS  PubMed  Google Scholar 

  25. Parikh, A. R. et al. Minimal residual disease detection using a plasma-only circulating tumor DNA assay in patients with colorectal cancer. Clin. Cancer Res. 27, 5586–5594 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Ogawa, M., Yokoyama, K., Imoto, S. & Tojo, A. Role of circulating tumor DNA in hematological malignancy. Cancers 13, 2078 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Tan, X., Yan, H., Chen, L., Zhang, Y. & Sun, C. Clinical value of ctDNA in hematological malignancies (lymphomas, multiple myeloma, myelodysplastic syndrome, and leukemia): a meta-analysis. Front. Oncol. 11, 632910 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Klein, E. A. et al. Clinical validation of a targeted methylation-based multi-cancer early detection test using an independent validation set. Ann. Oncol. 32, 1167–1177 (2021).

    Article  CAS  PubMed  Google Scholar 

  29. Gao, Q. et al. Circulating cell-free DNA for cancer early detection. Innovation 3, 100259 (2022).

    CAS  PubMed  PubMed Central  ADS  Google Scholar 

  30. Keller, L., Belloum, Y., Wikman, H. & Pantel, K. Clinical relevance of blood-based ctDNA analysis: mutation detection and beyond. Br. J. Cancer 124, 345–358 (2021).

    Article  PubMed  Google Scholar 

  31. Bredno, J., Lipson, J., Venn, O., Aravanis, A. M. & Jamshidi, A. Clinical correlates of circulating cell-free DNA tumor fraction. PLoS ONE 16, e0256436 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Bettegowda, C. et al. Detection of circulating tumor DNA in early- and late-stage human malignancies. Sci. Transl. Med. 6, 224ra224 (2014). The data presented in this study demonstrate that ctDNA can be detected across multiple cancer types, although detection rates varied on the basis of cancer type and disease progression.

    Article  Google Scholar 

  33. Tivey, A., Church, M., Rothwell, D., Dive, C. & Cook, N. Circulating tumour DNA—looking beyond the blood. Nat. Rev. Clin. Oncol. 19, 600–612 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Ohara, S. et al. Prognostic implications of preoperative versus postoperative circulating tumor DNA in surgically resected lung cancer patients: a pilot study. Transl. Lung Cancer Res. 9, 1915–1923 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Baumgartner, J. M. et al. Preoperative circulating tumor DNA in patients with peritoneal carcinomatosis is an independent predictor of progression-free survival. Ann. Surg. Oncol. 25, 2400–2408 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Lee, J. H. et al. Pre-operative ctDNA predicts survival in high-risk stage III cutaneous melanoma patients. Ann. Oncol. 30, 815–822 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Dhakal, B. et al. Assessment of molecular residual disease using circulating tumor DNA to identify multiple myeloma patients at high risk of relapse. Front. Oncol. 12, 786451 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Lam, V. K. et al. Genotype-specific differences in circulating tumor DNA levels in advanced NSCLC. J. Thorac. Oncol. 16, 601–609 (2021).

    Article  CAS  PubMed  Google Scholar 

  39. Calderwood, S. K. Tumor heterogeneity, clonal evolution, and therapy resistance: an opportunity for multitargeting therapy. Discov. Med. 15, 188–194 (2013).

    PubMed  PubMed Central  Google Scholar 

  40. Henriksen, T. V. et al. The effect of surgical trauma on circulating free DNA levels in cancer patients-implications for studies of circulating tumor DNA. Mol. Oncol. 14, 1670–1679 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Kasi, P. M. et al. BESPOKE study protocol: a multicentre, prospective observational study to evaluate the impact of circulating tumour DNA guided therapy on patients with colorectal cancer. BMJ Open 11, e047831 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  42. Cohen, S. A. et al. Kinetics of postoperative circulating cell-free DNA and impact on minimal residual disease detection rates in patients with resected stage I–III colorectal cancer. J. Clin. Oncol. 41, 5 (2023).

    Article  Google Scholar 

  43. Garcia-Murillas, I. et al. Assessment of molecular relapse detection in early-stage breast cancer. JAMA Oncol 5, 1473–1478 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Olsson, E. et al. Serial monitoring of circulating tumor DNA in patients with primary breast cancer for detection of occult metastatic disease. EMBO Mol. Med. 7, 1034–1047 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Parsons, H. A. et al. Sensitive detection of minimal residual disease in patients treated for early-stage breast cancer. Clin. Cancer Res. 26, 2556–2564 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Scholer, L. V. et al. Clinical implications of monitoring circulating tumor DNA in patients with colorectal cancer. Clin. Cancer Res. 23, 5437–5445 (2017).

    Article  CAS  PubMed  Google Scholar 

  47. Tarazona, N. et al. Targeted next-generation sequencing of circulating-tumor DNA for tracking minimal residual disease in localized colon cancer. Ann. Oncol. 30, 1804–1812 (2019).

    Article  CAS  PubMed  Google Scholar 

  48. Wang, Y. et al. Prognostic potential of circulating tumor DNA measurement in postoperative surveillance of nonmetastatic colorectal cancer. JAMA Oncol. 5, 1118–1123 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  49. Fakih, M. et al. Evaluation of comparative surveillance strategies of circulating tumor DNA, imaging, and carcinoembryonic antigen levels in patients with resected colorectal cancer. JAMA Netw. Open 5, e221093 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Dasari, A. et al. ctDNA applications and integration in colorectal cancer: an NCI Colon and Rectal–Anal Task Forces whitepaper. Nat. Rev. Clin. Oncol. 17, 757–770 (2020). This review, from a panel convened from the Colon and Rectal-Anal Task Forces of the US National Cancer Institute, highlights clinical applications of ctDNA testing that could change decision making.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Argilés, G. et al. Localised colon cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann. Oncol. 31, 1291–1305 (2020).

    Article  PubMed  Google Scholar 

  52. Peng, Y., Mei, W., Ma, K. & Zeng, C. Circulating tumor DNA and minimal residual disease (MRD) in solid tumors: current horizons and future perspectives. Front. Oncol. 11, 763790 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Loupakis, F. et al. Detection of molecular residual disease using personalized circulating tumor DNA assay in patients with colorectal cancer undergoing resection of metastases. JCO Precis. Oncol. 5, 1166–1177 (2021).

    Article  Google Scholar 

  54. Henriksen, T. V. et al. Circulating tumor DNA in stage III colorectal cancer, beyond minimal residual disease detection, toward assessment of adjuvant therapy efficacy and clinical behavior of recurrences. Clin. Cancer Res. 28, 507–517 (2022). This prospective study of 168 patients with stage III colorectal cancer demonstrated that serial ctDNA measurements following surgery is prognostic of survival outcomes.

    Article  CAS  PubMed  Google Scholar 

  55. Abbosh, C. et al. Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution. Nature 545, 446–451 (2017).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  56. Groot, V. P. et al. Circulating tumor DNA as a clinical test in resected pancreatic cancer. Clin. Cancer Res. 25, 4973–4984 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Parikh, A. R. et al. Analysis of DNA damage response gene alterations and tumor mutational burden across 17,486 tubular gastrointestinal carcinomas: implications for therapy. Oncologist 24, 1340–1347 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Tie, J. et al. Circulating tumor DNA analyses as markers of recurrence risk and benefit of adjuvant therapy for stage III colon cancer. JAMA Oncol. 5, 1710–1717 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  59. Garcia-Murillas, I. et al. Detection of ctDNA following surgery predicts relapse in breast cancer patients receiving primary surgery. Cancer Res. 82, P2-01-10 (2022).

    Article  Google Scholar 

  60. Kotani, D. et al. Molecular residual disease and efficacy of adjuvant chemotherapy in patients with colorectal cancer. Nat. Med. 29, 127–134 (2023). This study presents results from an interim analysis of GALAXY, a prospective, observational arm of CIRCULATE-Japan that establishes ctDNA as a prognostic and predictive biomarker in patients with CRC.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Song, Y. et al. Circulating tumor DNA clearance predicts prognosis across treatment regimen in a large real-world longitudinally monitored advanced non-small cell lung cancer cohort. Transl. Lung Cancer Res. 9, 269–279 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Ricciuti, B. et al. Early plasma circulating tumor DNA (ctDNA) changes predict response to first-line pembrolizumab-based therapy in non-small cell lung cancer (NSCLC). J. Immunother. Cancer 9, e001504 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  63. Raja, R. et al. Early reduction in ctDNA predicts survival in patients with lung and bladder cancer treated with durvalumab. Clin. Cancer Res. 24, 6212–6222 (2018).

    Article  CAS  PubMed  Google Scholar 

  64. Bockelman, C., Engelmann, B. E., Kaprio, T., Hansen, T. F. & Glimelius, B. Risk of recurrence in patients with colon cancer stage II and III: a systematic review and meta-analysis of recent literature. Acta Oncol. 54, 5–16 (2015).

    Article  PubMed  Google Scholar 

  65. Koenig, J. L. et al. Microsatellite instability and adjuvant chemotherapy in stage II colon cancer. Am. J. Clin. Oncol. 42, 573–580 (2019).

    Article  CAS  PubMed  Google Scholar 

  66. Tie, J. et al. Circulating tumor DNA analysis guiding adjuvant therapy in stage II colon cancer. New Engl. J. Med. 386, 2261–2272 (2022).

    Article  CAS  PubMed  Google Scholar 

  67. Verbus, E. A. et al. Circulating tumor DNA as a predictive biomarker in adjuvant chemotherapy for patients with stage 2a colon cancer (COBRA). Ann. Surg. Oncol. 28, 4095–4097 (2021).

    Article  PubMed  Google Scholar 

  68. Folprecht, G. et al. The CIRCULATE trial: circulating tumor dna based decision for adjuvant treatment in colon cancer stage II evaluation (AIO-KRK-0217). Clin. Colorectal Cancer 21, 170–174 (2022).

    Article  PubMed  Google Scholar 

  69. Taieb, J. & Gallois, C. Adjuvant chemotherapy for stage III colon cancer. Cancers 12, 2679 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Taniguchi, H. et al. CIRCULATE-Japan: circulating tumor DNA-guided adaptive platform trials to refine adjuvant therapy for colorectal cancer. Cancer Sci. 112, 2915–2920 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Dasari, A. et al. NRG-GI008: colon adjuvant chemotherapy based on evaluation of residual disease (CIRCULATE-US). J. Clin. Oncol. 40, TPS212 (2022).

    Article  Google Scholar 

  72. Lonardi, S. et al. The PEGASUS trial: post-surgical liquid biopsy-guided treatment of stage III and high-risk stage II colon cancer patients. J. Clin. Oncol. 38, TPS4124 (2020).

    Article  Google Scholar 

  73. Early Breast Cancer Trialists' Collaborative Group (EBCTCG) Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Lancet 365, 1687–1717 (2005).

    Article  Google Scholar 

  74. American Cancer Society. Treatment of Breast Cancer Stages I–III https://www.cancer.org/cancer/breast-cancer/treatment/treatment-of-breast-cancer-by-stage/treatment-of-breast-cancer-stages-i-iii.html (2022).

  75. Henry, N. L. et al. Promoting quality and evidence-based care in early-stage breast cancer follow-up. J. Natl Cancer Inst. 106, dju034 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  76. Markopoulos, C. et al. Multigene assays in early breast cancer: Insights from recent phase 3 studies. Eur. J. Surg. Oncol. 46, 656–666 (2020).

    Article  CAS  PubMed  Google Scholar 

  77. Cailleux, F. et al. Circulating tumor DNA after neoadjuvant chemotherapy in breast cancer is associated with disease relapse. JCO Precis. Oncol. 6, e2200148 (2022).

    Article  PubMed  Google Scholar 

  78. Shaw, J. et al. Serial postoperative ctDNA monitoring of breast cancer recurrence. J. Clin. Oncol. 40, 562 (2022).

    Article  Google Scholar 

  79. Felip, E. et al. 1O IMpower010: ctDNA status in patients (pts) with resected NSCLC who received adjuvant chemotherapy (chemo) followed by atezolizumab (atezo) or best supportive care (BSC). Immun. Oncol. Technol. 16, 1001106 (2022).

    Google Scholar 

  80. Kim, C. et al. Longitudinal circulating tumor DNA analysis in blood and saliva for prediction of response to osimertinib and disease progression in EGFR-mutant lung adenocarcinoma. Cancers 13, 3342 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Bennouna, J. et al. Phase II study evaluating the mechanisms of resistance on tumor tissue and liquid biopsy in patients with EGFR-mutated non-pretreated advanced lung cancer receiving osimertinib until and beyond radiologic progression: the MELROSE trial. Clin. Lung Cancer 21, e10–e14 (2020).

    Article  CAS  PubMed  Google Scholar 

  82. Babjuk, M. et al. European Association of Urology Guidelines on Non-muscle-invasive Bladder Cancer (TaT1 and carcinoma in situ)—2019 update. Eur. Urol. 76, 639–657 (2019).

    Article  CAS  PubMed  Google Scholar 

  83. National Comprehensive Cancer Network. NCCN Guidelines: Bladder Cancer Version 2 https://www.nccn.org/professionals/physician_gls/pdf/bladder.pdf (2022).

  84. Powles, T. et al. ctDNA guiding adjuvant immunotherapy in urothelial carcinoma. Nature 595, 432–437 (2021). Data from the IMvigor010 trial suggested that ctDNA testing in patients with urothelial carcinoma may help to guide adjuvant therapy decisions.

    Article  CAS  PubMed  ADS  Google Scholar 

  85. De Mattos-Arruda, L. et al. Cerebrospinal fluid-derived circulating tumour DNA better represents the genomic alterations of brain tumours than plasma. Nat. Commun. 6, 8839 (2015).

    Article  PubMed  PubMed Central  ADS  Google Scholar 

  86. Beagan, J. J. et al. Circulating tumor DNA as a preoperative marker of recurrence in patients with peritoneal metastases of colorectal cancer: a clinical feasibility study. J. Clin. Med. 9, 1738 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Bando, H. et al. Effects of metastatic sites on circulating tumor DNA in patients with metastatic colorectal cancer. JCO Precis. Oncol. 6, e2100535 (2022).

    Article  PubMed  Google Scholar 

  88. Waldeck, S. et al. Early assessment of circulating tumor DNA after curative‐intent resection predicts tumor recurrence in early‐stage and locally advanced non‐small‐cell lung cancer. Mol. Oncol. 16, 527–537 (2022).

    Article  CAS  PubMed  Google Scholar 

  89. Taieb, J. et al. Analysis of circulating tumour DNA (ctDNA) from patients enrolled in the IDEA-FRANCE phase III trial: prognostic and predictive value for adjuvant treatment duration. Ann. Oncol. 30, v867 (2019).

    Article  Google Scholar 

  90. Qiu, B. et al. Dynamic recurrence risk and adjuvant chemotherapy benefit prediction by ctDNA in resected NSCLC. Nat. Commun. 12, 6770 (2021).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  91. Prowell, T. M. & Pazdur, R. Pathological complete response and accelerated drug approval in early breast cancer. New Engl. J. Med. 366, 2438–2441 (2012).

    Article  CAS  PubMed  Google Scholar 

  92. Fayanju, O. M. et al. The clinical significance of breast-only and node-only pathologic complete response (pCR) after neoadjuvant chemotherapy (NACT): a review of 20,000 breast cancer patients in the National Cancer Data Base (NCDB). Ann. Surg. 268, 591–601 (2018).

    Article  PubMed  Google Scholar 

  93. Waingankar, N. et al. The impact of pathologic response to neoadjuvant chemotherapy on conditional survival among patients with muscle-invasive bladder cancer. Urol. Oncol. 37, 572.e521 (2019).

    Article  Google Scholar 

  94. Li, S. et al. Circulating tumor DNA predicts the response and prognosis in patients with early breast cancer receiving neoadjuvant chemotherapy. JCO Precis. Oncol. 4, 244–257 (2020).

    Article  Google Scholar 

  95. Magbanua, M. J. M. et al. Circulating tumor DNA and magnetic resonance imaging to predict neoadjuvant chemotherapy response and recurrence risk. NPJ Breast Cancer 7, 32 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Lin, P.-H. et al. Circulating tumor DNA as a predictive marker of recurrence for patients with stage II–III breast cancer treated with neoadjuvant therapy. Front. Oncol. 11, 736769 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Radovich, M. et al. Association of circulating tumor DNA and circulating tumor cells after neoadjuvant chemotherapy with disease recurrence in patients with triple-negative breast cancer: preplanned secondary analysis of the BRE12-158 randomized clinical trial. JAMA Oncol. 6, 1410–1415 (2020). Secondary results from this trial demonstrated that the presence of ctDNA following neoadjuvant chemotherapy in patients with triple-negative breast cancer is predictive of disease recurrence.

    Article  PubMed  Google Scholar 

  98. Cavallone, L. et al. Prognostic and predictive value of circulating tumor DNA during neoadjuvant chemotherapy for triple negative breast cancer. Sci. Rep. 10, 14704 (2020).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  99. Szabados, B. et al. Final results of neoadjuvant atezolizumab in cisplatin-ineligible patients with muscle-invasive urothelial cancer of the bladder. Eur. Urol. 82, 212–222 (2022).

    Article  CAS  PubMed  Google Scholar 

  100. Hinsenveld, F. J. et al. Prediction of pathological response following neoadjuvant chemotherapy in patients with muscle-invasive bladder cancer: the PRE-PREVENCYS trial. BMC Cancer 21, 1161 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Hurvitz, S. A. et al. A careful reassessment of anthracycline use in curable breast cancer. NPJ Breast Cancer 7, 134 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. Abbosh, C. & Swanton, C. ctDNA: an emerging neoadjuvant biomarker in resectable solid tumors. PLoS Med. 18, e1003771 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Wang, Q.-x et al. The watch-and-wait strategy versus surgical resection for rectal cancer patients with a clinical complete response after neoadjuvant chemoradiotherapy. Radiat. Oncol. 16, 16 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  104. Murahashi, S. et al. Serial circulating tumour DNA analysis for locally advanced rectal cancer treated with preoperative therapy: prediction of pathological response and postoperative recurrence. Br. J. Cancer 123, 803–810 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Zhou, J. et al. Serial circulating tumor DNA in predicting and monitoring the effect of neoadjuvant chemoradiotherapy in patients with rectal cancer: a prospective multicenter study. Clin. Cancer Res. 27, 301–310 (2021).

    Article  CAS  PubMed  Google Scholar 

  106. Khakoo, S. et al. MRI tumor regression grade and circulating tumor DNA as complementary tools to assess response and guide therapy adaptation in rectal cancer. Clin. Cancer Res. 26, 183–192 (2020).

    Article  CAS  PubMed  Google Scholar 

  107. Borcoman, E. et al. Novel patterns of response under immunotherapy. Ann. Oncol. 30, 385–396 (2019). This review provides a comprehensive overview of the novel response patterns to immunotherapy, related clinical implications, as well as criteria that had been developed (prior to iRESICT) to measure these responses.

    Article  CAS  PubMed  Google Scholar 

  108. Ma, Y., Wang, Q., Dong, Q., Zhan, L. & Zhang, J. How to differentiate pseudoprogression from true progression in cancer patients treated with immunotherapy. Am. J. Cancer Res. 9, 1546–1553 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  109. Singla, R. et al. Hyperprogression after Immunotherapy: nivolumab. analysis of imaging findings associated with hyperprogression and tumor growth kinetics. Indian J. Radiol. Imaging 31, 345–349 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  110. Seymour, L. et al. iRECIST: guidelines for response criteria for use in trials testing immunotherapeutics. Lancet Oncol. 18, e143–e152 (2017). These guidelines lay the foundation for standardizing solid tumour measurements and definitions for tumour measurements, including objective changes in tumour size when immunotherapy is used.

    Article  PubMed  PubMed Central  Google Scholar 

  111. Lee, J. H. et al. Association between circulating tumor DNA and pseudoprogression in patients with metastatic melanoma treated with anti-programmed cell death 1 antibodies. JAMA Oncol. 4, 717–721 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  112. Han, X.-J., Alu, A., Xiao, Y.-N., Wei, Y.-Q. & Wei, X.-W. Hyperprogression: a novel response pattern under immunotherapy. Clin. Transl. Med. 10, e167 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  113. Understanding hyperprogression in cancer. Cancer Discov. 9, 821 (2019).

  114. De La Torre, K., Cohen, E., Loeser, A., Hurlbert, M. & Metastatic Breast Cancer Alliance. Moonshots and metastatic disease: the need for a multi-faceted approach when studying atypical responses. NPJ Breast Cancer 3, 7 (2017).

    Article  PubMed  Google Scholar 

  115. Ramos-Casals, M. et al. Immune-related adverse events of checkpoint inhibitors. Nat. Rev. Dis. Primers 6, 38 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  116. Jin, Y. et al. The predicting role of circulating tumor DNA landscape in gastric cancer patients treated with immune checkpoint inhibitors. Mol. Cancer 19, 154 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Azzi, G. et al. Treatment response monitoring using a tumor-informed circulating tumor DNA test in an advanced triple-negative breast cancer patient: a case report. Case Rep. Oncol. 15, 473–479 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  118. Eroglu, Z. et al. Circulating tumor DNA-based molecular residual disease detection for treatment monitoring in advanced melanoma patients. Cancer 129, 1723–1734 (2023).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

Medical writing assistance was provided by Gord Fehringer, Allyson K. Malashevich and Meenakshi Malhotra.

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Authors and Affiliations

  1. Fred Hutchinson Cancer Center, Seattle, WA, USA

    Stacey A. Cohen

  2. University of Washington, Seattle, WA, USA

    Stacey A. Cohen

  3. Natera, Austin, TX, USA

    Minetta C. Liu & Alexey Aleshin

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  1. Stacey A. Cohen
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Contributions

S.A.C. and A.A. conceived and designed the objectives of the manuscript. All authors contributed to drafting and critically revised the manuscript for intellectual content. All authors approved the final version of the submitted report and agree to be accountable for all aspects.

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Correspondence to Stacey A. Cohen.

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Competing interests

S.A.C.: Natera (travel; local principal investigator (PI), funding to the institution (inst)), Kallyope (consultant), Istari Oncology (consultant), Pfizer (consultant; local PI, inst), Taiho (consultant), Delcath (consultant), Bayer (consultant), Merck/EMD Serono (local PI, inst), Isofol (local PI, inst), Polaris (local PI, inst), Boston Biomedical/Sumitomo Dainippon Pharma (local PI, inst), Faeth (local PI, inst) and Tempus (local PI, inst). M.C.L.: Natera (Employment and stocks), Eisai (grants and contracts to Mayo), Exact Sciences (grants and contracts to Mayo), Genentech/Roche (grants and contracts to Mayo), GRAIL (grants and contracts to Mayo; advisory board with compensation to Mayo), Merck (grants and contracts to Mayo; advisory board with compensation to Mayo), Novartis (grants and contracts to Mayo), Seattle Genetics (grants and contracts to Mayo; advisory board with compensation to Mayo), Tesaro (grants and contracts to Mayo), AstraZeneca (travel; advisory board with compensation to Mayo), Genomic Health (travel; grants and contracts to Mayo; advisory board with compensation to Mayo), Ionis (travel; advisory board with compensation to Mayo), Celgene (advisory board with compensation to Mayo), Pfizer (advisory board with compensation to Mayo) and Syndax (Advisory board with compensation to Mayo). A.A.: Natera (employment and stocks).

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Cohen, S.A., Liu, M.C. & Aleshin, A. Practical recommendations for using ctDNA in clinical decision making. Nature 619, 259–268 (2023). https://doi.org/10.1038/s41586-023-06225-y

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