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Serial ctDNA analysis predicts clinical progression in patients with advanced urothelial carcinoma

Abstract

Background

Targeted sequencing of circulating tumour DNA (ctDNA) is a promising tool to monitor dynamic changes in the variant allele frequencies (VAF) of genomic alterations and predict clinical outcomes in patients with advanced urothelial carcinoma (UC).

Methods

We performed targeted sequencing of 182 serial ctDNA samples from 53 patients with advanced UC.

Results

Serial ctDNA-derived metrics predicted the clinical outcomes in patients with advanced UC. Combining serial ctDNA aggregate VAF (aVAF) values with clinical factors, including age, sex, and liver metastasis, improved the performance of prognostic models. An increase of the ctDNA aVAF by ≥1 in serial ctDNA samples predicted disease progression within 6 months in 90% of patients. The majority of patients with aVAFs ≤0.7 in three consecutive ctDNA samples achieved durable clinical responses (≥6 months).

Conclusions

Serial ctDNA analysis predicts disease progression and enables dynamic monitoring to guide precision medicine in patients with advanced UC.

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Fig. 1: Swimmer plot showing the disease course in each patient, treatment, ctDNA status, and radiographic response.
Fig. 2: Serial ctDNA captures actionable genomic alterations.
Fig. 3: ctDNA measurements are prognostic.
Fig. 4: ctDNA dynamics reflect radiographic disease burden.
Fig. 5: Serial ctDNA predicts clinical outcomes.

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Data availability

Data access and responsibility: NJV and BMF had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Data sharing policy: Data are available for bona fide researchers upon request from the authors.

References

  1. Robertson AG, Kim J, Al-Ahmadie H, Bellmunt J, Guo G, Cherniack AD, et al. Comprehensive molecular characterization of muscle-invasive bladder. Cancer Cell. 2017;171:540–556.e25.

    CAS  Google Scholar 

  2. Sailer V, Eng KW, Zhang T, Bareja R, Pisapia DJ, Sigaras A, et al. Integrative molecular analysis of patients with advanced and metastatic cancer. JCO Precis Oncol. 2019;3:1–12.

    Google Scholar 

  3. Faltas BM, Prandi D, Tagawa ST, Molina AM, Nanus DM, Sternberg C, et al. Clonal evolution of chemotherapy-resistant urothelial carcinoma. Nat Genet. 2016;48:1490–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Diehl F, Schmidt K, Choti MA, Romans K, Goodman S, Li M, et al. Circulating mutant DNA to assess tumor dynamics. Nat Med. 2008;14:985–90.

    Article  CAS  PubMed  Google Scholar 

  5. Razavi P, Li BT, Brown DN, Jung B, Hubbell E, Shen R, et al. High-intensity sequencing reveals the sources of plasma circulating cell-free DNA variants. Nat Med. 2019;25:1928–37.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Bettegowda C, Sausen M, Leary RJ, Kinde I, Wang Y, Agrawal N, et al. Detection of circulating tumor DNA in early- and late-stage human malignancies. Sci Transl Med. 2014;6:224ra24–224ra24.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Lanman RB, Mortimer SA, Zill OA, Sebisanovic D, Lopez R, Blau S, 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;10:1–27.

    Article  Google Scholar 

  8. Agarwal N, Pal SK, Hahn AW, Nussenzveig RH, Pond GR, Gupta SV, et al. Characterization of metastatic urothelial carcinoma via comprehensive genomic profiling of circulating tumor DNA. Cancer. 2018;124:2115–24.

    Article  CAS  PubMed  Google Scholar 

  9. Birkenkamp-Demtröder K, Nordentoft I, Christensen E, Høyer S, Reinert T, Vang S, et al. Genomic alterations in liquid biopsies from patients with bladder cancer. Eur Urol. 2016;70:75–82.

    Article  PubMed  Google Scholar 

  10. Christensen E, Birkenkamp-Demtröder K, Sethi H, Shchegrova S, Salari R, Nordentoft I, 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. 2019;37:1547–57.

    Article  CAS  PubMed  Google Scholar 

  11. Powles TB, Assaf ZJ, Davarpanah N, Hussain M, Oudard S, Gschwend JE, et al. Clinical outcomes in post-operative ctDNA-positive muscle-invasive urothelial carcinoma (MIUC) patients after atezolizumab adjuvant therapy. Ann Oncol. 2020;31:S1417.

    Article  Google Scholar 

  12. Frenel JS, Carreira S, Goodall J, Roda D, Perez-Lopez R, Tunariu N, et al. Serial next-generation sequencing of circulating cell-free DNA evaluating tumor clone response to molecularly targeted drug administration. Clin Cancer Res. 2015;21:4586–96.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Patel KM, Van Der Vos KE, Smith CG, Mouliere F, Tsui D, Morris J, et al. Association of plasma and urinary mutant DNA with clinical outcomes in muscle invasive bladder cancer. Sci Rep. 2017;7:1–12.

    Article  Google Scholar 

  14. Grivas P, Lalani A-KA, Pond GR, Nagy RJ, Faltas B, Agarwal N, et al. Circulating tumor DNA alterations in advanced urothelial carcinoma and association with clinical outcomes: a pilot study. Eur Urol Oncol. 2020;3:695–9.

    Article  PubMed  Google Scholar 

  15. Hilke FJ, Muyas F, Admard J, Kootz B, Nann D, Welz S, et al. Dynamics of cell-free tumour DNA correlate with treatment response of head and neck cancer patients receiving radiochemotherapy. Radiother Oncol. 2020;151:182–9.

    Article  CAS  PubMed  Google Scholar 

  16. Vandekerkhove G, Lavoie J, Annala M, Murtha AJ, Sundahl N, Walz S, et al. Plasma ctDNA is a tumor tissue surrogate and enables clinical-genomic stratification of metastatic bladder cancer. Nat Commun. 2021;12:184.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Powles T, Carroll D, Chowdhury S, Gravis G, Joly F, Carles J, et al. An adaptive, biomarker-directed platform study of durvalumab in combination with targeted therapies in advanced urothelial cancer. Nat Med. 2021;27:793–801.

    Article  CAS  PubMed  Google Scholar 

  18. Raja R, Kuziora M, Brohawn PZ, Higgs BW, Gupta A, Dennis PA, et al. Early reduction in ctDNA predicts survival in patients with lung and bladder cancer treated with durvalumab. Clin Cancer Res. 2018;24:6212–22.

    Article  CAS  PubMed  Google Scholar 

  19. Sundahl N, Vandekerkhove G, Decaestecker K, Meireson A, De Visschere P, Fonteyne V, et al. Randomized phase 1 trial of pembrolizumab with sequential versus concomitant stereotactic body radiotherapy in metastatic urothelial carcinoma. Eur Urol. 2019;75:707–11.

    Article  CAS  PubMed  Google Scholar 

  20. Powles T, Assaf ZJ, Davarpanah N, Banchereau R, Szabados BE, Yuen KC, et al. ctDNA guiding adjuvant immunotherapy in urothelial carcinoma. Nature. 2021;595:432–7.

    Article  CAS  PubMed  Google Scholar 

  21. Odegaard JI, Vincent JJ, Mortimer S, Vowles JV, Ulrich BC, Banks KC, et al. Validation of a plasma-based comprehensive cancer genotyping assay utilizing orthogonal tissue- and plasma-based methodologies. Clin Cancer Res. 2018;24:3539–49.

    Article  CAS  PubMed  Google Scholar 

  22. Vosoughi A, Zhang T, Shohdy KS, Vlachostergios PJ, Wilkes DC, Bhinder B, et al. Common germline-somatic variant interactions in advanced urothelial cancer. Nat Commun. 2020;11:6195.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Rhodes DR, Kalyana-Sundaram S, Mahavisno V, Varambally R, Yu J, Briggs BB, et al. Oncomine 3.0: Genes, pathways, and networks in a collection of 18,000 cancer gene expression profiles. Neoplasia. 2007;9:166–80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Rhodes DR, Yu J, Shanker K, Deshpande N, Varambally R, Ghosh D, et al. ONCOMINE: a cancer microarray database and integrated data-mining platform. Neoplasia. 2004;6:1–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Huang L, Fernandes H, Zia H, Tavassoli P, Rennert H, Pisapia D, et al. The cancer precision medicine knowledge base for structured clinical-grade mutations and interpretations. J Am Med Inform Assoc. 2017;24:513–9.

    Article  PubMed  Google Scholar 

  26. Chakravarty D, Gao J, Phillips S, Kundra R, Zhang H, Wang J, et al. OncoKB: a precision oncology knowledge base. JCO Precis Oncol. 2017;1:1–16.

    Google Scholar 

  27. Iyer G, Hanrahan AJ, Milowsky MI, Al-Ahmadie H, Scott SN, Janakiraman M, et al. Genome sequencing identifies a basis for everolimus sensitivity. Science 2012;338:221–221.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Loriot Y, Necchi A, Park SH, Garcia-Donas J, Huddart R, Burgess E, et al. Erdafitinib in locally advanced or metastatic urothelial carcinoma. N. Engl J Med. 2019;381:338–48.

    Article  CAS  PubMed  Google Scholar 

  29. Findlay GM, Daza RM, Martin B, Zhang MD, Leith AP, Gasperini M, et al. Accurate classification of BRCA1 variants with saturation genome editing. Nature. 2018;562:217–22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Bick AG, Weinstock JS, Nandakumar SK, Fulco CP, Bao EL, Zekavat SM, et al. Inherited causes of clonal haematopoiesis in 97,691 whole genomes. Nature. 2020;586:763–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Nassar AH, Mouw KW, Jegede O, Shinagare AB, Kim J, Liu C-J, et al. A model combining clinical and genomic factors to predict response to PD-1/PD-L1 blockade in advanced urothelial carcinoma. Br J Cancer. 2020;122:555–63.

    Article  CAS  PubMed  Google Scholar 

  32. Khaki AR, Li A, Diamantopoulos LN, Miller NJ, Carril-Ajuria L, Castellano D, et al. A new prognostic model in patients with advanced urothelial carcinoma treated with first-line immune checkpoint inhibitors. Eur Urol Oncol. 2021;4:464–72.

    Article  PubMed  Google Scholar 

  33. Shen J, Ju Z, Zhao W, Wang L, Peng Y, Ge Z, et al. ARID1A deficiency promotes mutability and potentiates therapeutic antitumor immunity unleashed by immune checkpoint blockade. Nat Med. 2018;24:556–62.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Lee HW, Sa JK, Gualberto A, Scholz C, Sung HH, Jeong BC, et al. A phase II trial of tipifarnib for patients with previously treated, metastatic urothelial carcinoma harboring hras mutations. Clin Cancer Res. 2020;26:5113–9.

    Article  CAS  PubMed  Google Scholar 

  35. Bajorin DF, Dodd PM, Mazumdar M, Fazzari M, McCaffrey JA, Scher HI, et al. Long-term survival in metastatic transitional-cell carcinoma and prognostic factors predicting outcome of therapy. J Clin Oncol. 1999;17:3173–81.

    Article  CAS  PubMed  Google Scholar 

  36. Apolo AB, Ostrovnaya I, Halabi S, Iasonos A, Philips GK, Rosenberg JE, et al. Prognostic model for predicting survival of patients with metastatic urothelial cancer treated with cisplatin-based chemotherapy. J Natl Cancer Inst. 2013;105:499–503.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Bratman SV, Yang SYC, Iafolla MAJ, Liu Z, Hansen AR, Bedard PL, et al. Personalized circulating tumor DNA analysis as a predictive biomarker in solid tumor patients treated with pembrolizumab. Nat Cancer. 2020;1:873–81.

    Article  Google Scholar 

  38. Birkenkamp-Demtröder K, Christensen E, Nordentoft I, Knudsen M, Taber A, Høyer S, et al. Monitoring treatment response and metastatic relapse in advanced bladder cancer by liquid biopsy analysis. Eur Urol. 2018;73:535–40.

    Article  PubMed  Google Scholar 

  39. Avanzini S, Kurtz DM, Chabon JJ, Moding EJ, Hori SS, Gambhir SS, et al. A mathematical model of ctDNA shedding predicts tumor detection size. Sci Adv. 2020;6:1–10.

    Article  Google Scholar 

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Acknowledgements

BMF was supported by the Department of Defense CDMRP grant (CA160212), a STARR Cancer Consortium grant (I14-0047), and the Gellert Family-John P. Leonard, MD Research Scholarship in Hematology and Medical Oncology. This work was also supported by a Conquer Cancer Foundation Long Term International Fellowship Award (KSS) and the Englander Institute for Precision Medicine at WCM (OE, BMF). Guardant performed sequencing and initial mutational testing of ctDNA samples. We thank Duy Nguyen for his assistance with editing the text.

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Author information

Authors and Affiliations

Authors

Contributions

Initiation and design of the study: KSS, KSP, RN, PG, NJV and BMF. Subject enrollment, sample, and clinical data collection: KSS, DV, YC, JT, STT, AMM, CNS, DMN, JMM, OE, GPS, PV, NJV and BMF. Sample sequencing: KSP and RN. Statistical, and bioinformatic analyses: KSS and OE. Supervision of research: NV and BMF. Writing of the first draft of the manuscript: KSS, OE, GPV, PG, NV and BMF. All authors contributed to the writing and editing of the revised manuscript and approved the manuscript.

Corresponding authors

Correspondence to Nicholas J. Vogelzang or Bishoy Morris Faltas.

Ethics declarations

Competing interests

KSS, DMV, YC and JT: No competing interests. AMM: Honoraria—ASCO, Consulting or advisory role—EISAi; Exelixis; Janssen. KSP and RN: Employment—Guardant Health Inc. CNS: Consulting or advisory role—Astellas Pharma; AstraZeneca; Bayer; Genzyme; Immunomedics; Incyte; Medscape; Merck; MSD; Pfizer; Roche; UroToday. STT: Consulting or advisory role—Abbvie; Amgen; Astellas Pharma; Bayer; Clovis Oncology; Dendreon; Endocyte; Genentech; Immunomedics; Janssen; Karyopharm Therapeutics; Medivation; Pfizer; QED Therapeutics; Sanofi; Tolmar, Research funding—Abbvie (Inst); Amgen (Inst); Astellas Pharma (Inst); AstraZeneca (Inst); AVEO (Inst); Bayer (Inst); Boehringer Ingelheim (Inst); Bristol-Myers Squibb (Inst); Clovis Oncology (Inst); Dendreon (Inst); Endocyte (Inst); Exelixis (Inst); Genentech (Inst); Immunomedics (Inst); Inovio Pharmaceuticals (Inst); Janssen (Inst); Karyopharm Therapeutics (Inst); Lilly (Inst); Medivation (Inst); Merck (Inst); Millennium (Inst); Newlink Genetics (Inst); Novartis (Inst); Progenics (Inst); Rexahn Pharmaceuticals (Inst); Sanofi (Inst); Stem CentRx (Inst), Travel, Accommodations, expenses—Amgen; Immunomedics; Sanofi. DMN: Consulting or advisory role—Roche/Genentech, Research funding—Boehringer Ingelheim (Inst); Novartis (Inst); Zenith Epigenetics (Inst). JMM: Research funding—Personal genome diagnostics, Travel, accommodations, expenses—Personal genome diagnostics. OE: Stock and other ownership interests—OneThree Biotech; Owkin; Volastra Therapeutics. GPS: Honoraria—UpToDate, Consulting or advisory role—Astellas Pharma; AstraZeneca; Bicycle Therapeutics; Bristol-Myers Squibb; Eisai; EMD Serono; Exelixis; Genentech; Janssen; Merck; Pfizer; Seattle Genetics, Speakers’ Bureau - Medscape; Onclive; Physicans’ Education Resource; Research to practice, research funding—AstraZeneca (Inst); Janssen (Inst); Sanofi (Inst), Travel, Accommodations, expenses—Bristol-Myers Squibb, Other relationship—Astellas Pharma; AstraZeneca; Bavarian Nordic; Bristol-Myers Squibb; Debiopharm Group; Elsevier; QED Therapeutics. PG: Consulting or advisory role—AstraZeneca; Bayer; Bristol-Myers Squibb; Clovis Oncology; Driver, Inc; EMD Serono; Exelixis; Foundation Medicine; Genzyme; GlaxoSmithKline; HERON; Janssen; Merck; Mirati Therapeutics; Pfizer; QED Therapeutics; Roche; Seattle Genetics, Research funding—Bavarian Nordic (Inst); Bristol-Myers Squibb (Inst); Clovis Oncology (Inst); Debiopharm Group (Inst); Immunomedics (Inst); Pfizer (Inst). NJV: Employment—US Oncology, Stock and Other Ownership interests—Caris Life Sciences, Honoraria—Novartis; Pfizer; UpToDate, Consulting or Advisory role—Astellas Pharma, AstraZeneca; Bayer; Boehringer Ingelheim; Caris Life Sciences; Clovis Oncology; Corvus Pharmaceuticals; Eisai; Genentech/Roche; Janssen Oncology; Merck; Modra Pharmaceuticals; Pfizer; Tolero Pharmaceuticals, Speakers’ Bureau—Bayer; Bristol-Myers Squibb; Clovis Oncology; Genentech/Roche; Sanofi; Seattle Genetics/Astellas, Research funding—Endocyte (Inst); Merck (Inst); Suzhou Kintor Pharmaceuticals (Inst); US Oncology (Inst), Expert testimony—Novartis, Travel, accommodations, expenses—AstraZeneca/MedImmune; Bayer/Onyx; Exelixis; Genentech/Roche; Pfizer; Sanofi/Aventis; US Oncology. BMF: Honoraria—Digital Science Press, Consulting or advisory role—QED therapeutics, Immunomedics, Merck, Seattle Genetics. Patent royalties Immunomedics/Gilead Research funding—Eli Lilly.

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The study was approved by the Western Institutional Review Board (Protocol No. 20152817).

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Shohdy, K.S., Villamar, D.M., Cao, Y. et al. Serial ctDNA analysis predicts clinical progression in patients with advanced urothelial carcinoma. Br J Cancer 126, 430–439 (2022). https://doi.org/10.1038/s41416-021-01648-8

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  • DOI: https://doi.org/10.1038/s41416-021-01648-8

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