10 januari 2025: Bronnen: Nature en Amanda Heidt

Uit de resultaten van de CLEVER studie blijkt dat slapende tumorcellen in het beenmerg van borstkankerpatiënten die ondanks een succesvolle behandeling na jaren weer actief worden uitstekend te behandelen zijn met een behandeling van de slapende tumorcellen in het beenmerg met Hydroxychloroquine plus Everolimus

De CLEVER studie behandelde in totaal 51 borstkankerpatiënten met aantoonbare slapende tumorcellen in het beenmerg met Hydroxychloroquine  (n=15), Everolimus (n=15) of Hydroxychloroquine  + Everolimus (n=21). De behandeling was haalbaar en verdraagbaar; slechts één patiënt stopte vroegtijdig vanwege toxiciteit van graad 3.

Na een mediane follow-up van 42 maanden was de 3-jaars recidiefvrije overleving voor Hydroxychloroquine , Everolimus en Hydroxychloroquine  + Everolimus respectievelijk 91,7%, 92,9% en 100%.
Bij alle patiënten waren binnen vijf jaar na de diagnose slapende tumorcellen gevonden in het beenmerg.

Naar aanleiding van deze studie schreef Amanda Heidt, een bekende journaliste op het gebied van de medische wetenschap, voor Nature een artikel met als titel vertaalt in het Nederlands: Waarom kanker jaren later kan terugkeren — en hoe dit te voorkomen (Why cancer can come back years later — and how to stop it)

Daarin legt zij uit waarom onderzoekers zich in het voorkomen van een recidief richten op de slapende tumorcellen in het beenmerg. 

Het UMC Utrecht schreef vorig jaar over slapende tumorcellen in de longen die door een Covid infectie geactiveerd zouden worden, zie dit artikel: COVID-19-infectie kan slapende kankercellen activeren

Het studieverslag van de CLEVER studie is tegen betaling en voor artsen gratis via hun werkgever in te zien. Hier het abstract van deze studie:

  • Article
  • Published: 

Targeting dormant tumor cells to prevent recurrent breast cancer: a randomized phase 2 trial

Abstract

Breast cancer recurrence may arise from dormant disseminated tumor cells (DTCs) that persist in bone marrow and other sites. Clinically, DTCs are independently associated with breast cancer recurrence and death. Preclinical studies in mouse models identified autophagy and mammalian target of rapamycin (mTOR) signaling as critical mechanisms of tumor dormancy and escape. We subsequently tested the effects of transient versus chronic inhibition of autophagy with chloroquine or hydroxychloroquine (HCQ) and mTOR signaling with rapamycin (RAPA) or everolimus (EVE) on residual tumor cell (RTC) burden and recurrence-free survival (RFS). In mice harboring dormant RTCs, inhibition of mTOR alone or in combination with autophagy inhibition decreased RTC burden and improved RFS in a duration-dependent manner. RTC number was strongly and inversely correlated with RFS, suggesting that RTC reduction mediated an improvement in RFS. To translate findings clinically, we performed a randomized phase 2 trial (CLEVER) of HCQ, EVE or their combination in breast cancer survivors within 5 years of diagnosis who had detectable DTCs on bone marrow aspirate. Primary endpoints were feasibility and safety; secondary endpoints included DTC reduction/clearance and RFS. In total, 51 DTC+ patients initiated HCQ (n = 15), EVE (n = 15) or HCQ + EVE (n = 21). Treatment was feasible and tolerable; only one patient discontinued early for grade 3 toxicity. At 42 months median follow-up, landmark 3-year RFS for HCQ, EVE and HCQ + EVE was 91.7%, 92.9% and 100%, respectively, and was greater in those who cleared DTCs versus those who did not (hazard ratio (HR) = 0.21 (95% confidence interval 0.01–3.4)). Posterior probabilities were 98–99.9% that three cycles of HCQ, EVE or HCQ + EVE led to reduced or undetectable DTCs compared to observation alone, with estimated DTC reductions of 80%, 78% and 87%, respectively. These findings provide proof-of-concept that targeting dormant RTCs with HCQ, EVE or their combination in breast cancer survivors or mouse models depletes minimal residual disease, warranting a definitive human randomized controlled trial. ClinicalTrials.gov registration: NCT03032406.

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Data availability

All data supporting the findings of this study are available within the paper. The data used and/or analyzed during the current study are available in the Supplementary Information or from the corresponding author(s) on request, recognizing that certain patient-related data not included in the paper were generated as part of the clinical trial and may be subject to patient confidentiality. It is estimated that the corresponding authors will respond to external data requests within 2 weeks of receipt of the request to verify whether the request is subject to any intellectual property or confidentiality obligations. Uncropped original western blots corresponding to Extended Data Fig. 2e,f,k,l are provided. The authors do not have IRB approval or patient consent to share identifying or sensitive data on CLEVER clinical trial participants and therefore cannot report data in a public repository. Source data are provided with this paper.

Code availability

This study used custom code for Bayesian data modeling, which will be made available upon request. It is estimated that the corresponding authors will respond to requests for code within 2 weeks of receipt of the request.

References

  1. Pedersen, R. N. et al. The incidence of breast cancer recurrence 10–32 years after primary diagnosis. J. Natl Cancer Inst. 114, 391–399 (2022).

    Article PubMed Google Scholar 

  2. Colleoni, M. et al. Annual hazard rates of recurrence for breast cancer during 24 years of follow-up: results from the international breast cancer study group trials I to V. J. Clin. Oncol. 34, 927–935 (2016).

    Article CAS PubMed PubMed Central Google Scholar 

  3. Early Breast Cancer Trialists’ Collaborative Group (EBCTCG). Long-term outcomes for neoadjuvant versus adjuvant chemotherapy in early breast cancer: meta-analysis of individual patient data from ten randomised trials. Lancet Oncol. 19, 27–39 (2018).

    Article Google Scholar 

  4. 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 

  5. Loi, S., Buyse, M., Sotiriou, C. & Cardoso, F. Challenges in breast cancer clinical trial design in the postgenomic era. Curr. Opin. Oncol. 16, 536–541 (2004).

    Article PubMed Google Scholar 

  6. Cescon, D. W. et al. Therapeutic targeting of minimal residual disease to prevent late recurrence in hormone-receptor positive breast cancer: challenges and new approaches. Front. Oncol. 11, 667397 (2021).

    Article CAS PubMed Google Scholar 

  7. Banys-Paluchowski, M., Reinhardt, F. & Fehm, T. Disseminated tumor cells and dormancy in breast cancer progression. Adv. Exp. Med. Biol. 1220, 35–43 (2020).

    Article CAS PubMed Google Scholar 

  8. Roy, R. et al. Escape from breast tumor dormancy: the convergence of obesity and menopause. Proc. Natl Acad. Sci. USA 119, e2204758119 (2022).

    Article CAS PubMed PubMed Central Google Scholar 

  9. Ruth, J. R. et al. Cellular dormancy in minimal residual disease following targeted therapy. Breast Cancer Res. 23, 63 (2021).

    Article CAS PubMed PubMed Central Google Scholar 

  10. Ecker, B. L. et al. Impact of obesity on breast cancer recurrence and minimal residual disease. Breast Cancer Res. 21, 41 (2019).

    Article PubMed PubMed Central Google Scholar 

  11. Abravanel, D. L. et al. Notch promotes recurrence of dormant tumor cells following HER2/neu-targeted therapy. J. Clin. Invest. 125, 2484–2496 (2015).

    Article PubMed PubMed Central Google Scholar 

  12. Dalla, E., Sreekumar, A., Aguirre-Ghiso, J. A. & Chodosh, L. A. Dormancy in breast cancer. Cold Spring Harb. Perspect. Med. 13, a041331 (2023).

    Article CAS PubMed PubMed Central Google Scholar 

  13. Braun, S. et al. A pooled analysis of bone marrow micrometastasis in breast cancer. N. Engl. J. Med. 353, 793–802 (2005).

    Article CAS PubMed Google Scholar 

  14. Hall, C. et al. Disseminated tumor cells predict survival after neoadjuvant therapy in primary breast cancer. Cancer 118, 342–348 (2012).

    Article PubMed Google Scholar 

  15. Mathiesen, R. R. et al. Persistence of disseminated tumor cells after neoadjuvant treatment for locally advanced breast cancer predicts poor survival. Breast Cancer Res. 14, R117 (2012).

    Article PubMed PubMed Central Google Scholar 

  16. Hartkopf, A. D. et al. Disseminated tumour cells from the bone marrow of early breast cancer patients: results from an international pooled analysis. Eur. J. Cancer 154, 128–137 (2021).

    Article CAS PubMed Google Scholar 

  17. Fehm, T. et al. Pooled analysis of the prognostic relevance of disseminated tumor cells in the bone marrow of patients with ovarian cancer. Int. J. Gynecol. Cancer 23, 839–845 (2013).

    Article PubMed Google Scholar 

  18. Moody, S. E. et al. Conditional activation of Neu in the mammary epithelium of transgenic mice results in reversible pulmonary metastasis. Cancer Cell 2, 451–461 (2002).

    Article CAS PubMed Google Scholar 

  19. Gunther, E. J. et al. Impact of p53 loss on reversal and recurrence of conditional Wnt-induced tumorigenesis. Genes Dev. 17, 488–501 (2003).

    Article CAS PubMed PubMed Central Google Scholar 

  20. Moody, S. E. et al. The transcriptional repressor Snail promotes mammary tumor recurrence. Cancer Cell 8, 197–209 (2005).

    Article CAS PubMed Google Scholar 

  21. Vera-Ramirez, L., Vodnala, S. K., Nini, R., Hunter, K. W. & Green, J. E. Autophagy promotes the survival of dormant breast cancer cells and metastatic tumour recurrence. Nat. Commun. 9, 1944 (2018).

    Article PubMed PubMed Central Google Scholar 

  22. Dwyer, S., Ruth, J., Seidel, H. E., Raz, A. A. & Chodosh, L. A. Autophagy is required for mammary tumor recurrence by promoting dormant tumor cell survival following therapy. Breast Cancer Res. 26, 143 (2024).

    Article CAS PubMed PubMed Central Google Scholar 

  23. Paul, M. R. et al. Genomic landscape of metastatic breast cancer identifies preferentially dysregulated pathways and targets. J. Clin. Invest. 130, 4252–4265 (2020).

    CAS PubMed PubMed Central Google Scholar 

  24. D’Cruz, C. M. et al. c-MYC induces mammary tumorigenesis by means of a preferred pathway involving spontaneous Kras2 mutations. Nat. Med. 7, 235–239 (2001).

    Article PubMed Google Scholar 

  25. Sreekumar, A. et al. B3GALT6 promotes dormant breast cancer cell survival and recurrence by enabling heparan sulfate-mediated FGF signaling. Cancer Cell 42, 52–69 (2024).

    Article CAS PubMed Google Scholar 

  26. Finbloom, D. S., Silver, K., Newsome, D. A. & Gunkel, R. Comparison of hydroxychloroquine and chloroquine use and the development of retinal toxicity. J. Rheumatol. 12, 692–694 (1985).

    CAS PubMed Google Scholar 

  27. La Belle Flynn, A. et al. Autophagy inhibition elicits emergence from metastatic dormancy by inducing and stabilizing Pfkfb3 expression. Nat. Commun. 10, 3668 (2019).

    Article PubMed PubMed Central Google Scholar 

  28. Sosa, M. S., Bragado, P. & Aguirre-Ghiso, J. A. Mechanisms of disseminated cancer cell dormancy: an awakening field. Nat. Rev. Cancer 14, 611–622 (2014).

    Article CAS PubMed PubMed Central Google Scholar 

  29. Aqbi, H. F. et al. Autophagy-deficient breast cancer shows early tumor recurrence and escape from dormancy. Oncotarget 9, 22113–22122 (2018).

    Article PubMed PubMed Central Google Scholar 

  30. Lu, Z. et al. The tumor suppressor gene ARHI regulates autophagy and tumor dormancy in human ovarian cancer cells. J. Clin. Invest. 118, 3917–3929 (2008).

    CAS PubMed PubMed Central Google Scholar 

  31. Chery, L. et al. Characterization of single disseminated prostate cancer cells reveals tumor cell heterogeneity and identifies dormancy associated pathways. Oncotarget 5, 9939–9951 (2014).

    Article PubMed PubMed Central Google Scholar 

  32. Marshall, J. C. et al. Effect of inhibition of the lysophosphatidic acid receptor 1 on metastasis and metastatic dormancy in breast cancer. J. Natl Cancer Inst. 104, 1306–1319 (2012).

    Article CAS PubMed PubMed Central Google Scholar 

  33. Kobayashi, A. et al. Bone morphogenetic protein 7 in dormancy and metastasis of prostate cancer stem-like cells in bone. J. Exp. Med. 208, 2641–2655 (2011).

    Article CAS PubMed PubMed Central Google Scholar 

  34. Bragado, P. et al. TGF-β2 dictates disseminated tumour cell fate in target organs through TGF-β-RIII and p38α/β signalling. Nat. Cell Biol. 15, 1351–1361 (2013).

    Article CAS PubMed PubMed Central Google Scholar 

  35. Feng, Y. et al. SPSB1 promotes breast cancer recurrence by potentiating c-MET signaling. Cancer Discov. 4, 790–803 (2014).

    Article CAS PubMed PubMed Central Google Scholar 

  36. Alvarez, J. V. et al. Par-4 downregulation promotes breast cancer recurrence by preventing multinucleation following targeted therapy. Cancer Cell 24, 30–44 (2013).

    Article CAS PubMed Google Scholar 

  37. Chen, S. et al. PAQR8 promotes breast cancer recurrence and confers resistance to multiple therapies. Breast Cancer Res. 25, 1 (2023).

    Article PubMed PubMed Central Google Scholar 

  38. Rueda, O. M. et al. Dynamics of breast-cancer relapse reveal late-recurring ER-positive genomic subgroups. Nature 567, 399–404 (2019).

    Article CAS PubMed PubMed Central Google Scholar 

  39. Bidard, F. C. et al. Disseminated tumor cells of breast cancer patients: a strong prognostic factor for distant and local relapse. Clin. Cancer Res. 14, 3306–3311 (2008).

    Article CAS PubMed Google Scholar 

  40. Naume, B. et al. Clinical outcome with correlation to disseminated tumor cell (DTC) status after DTC-guided secondary adjuvant treatment with docetaxel in early breast cancer. J. Clin. Oncol. 32, 3848–3857 (2014).

    Article PubMed Google Scholar 

  41. Consortium, I. S. T. et al. Association of event-free and distant recurrence-free survival with individual-level pathologic complete response in neoadjuvant treatment of stages 2 and 3 breast cancer: three-year follow-up analysis for the I-SPY2 adaptively randomized clinical trial. JAMA Oncol. 6, 1355–1362 (2020).

    Article Google Scholar 

  42. Chavez-MacGregor, M. et al. Phase III randomized, placebo-controlled trial of endocrine therapy ± 1 year of everolimus in patients with high-risk, hormone receptor-positive, early-stage breast cancer. J. Clin. Oncol. 42, 3012–3021 (2024).

    Article CAS PubMed Google Scholar 

  43. 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 

  44. Garcia-Murillas, I. et al. Mutation tracking in circulating tumor DNA predicts relapse in early breast cancer. Sci. Transl. Med. 7, 302ra133 (2015).

    Article PubMed Google Scholar 

  45. Kaplan, E. L. & Meier, P. Nonparametric estimation from incomplete observations. J. Am. Stat. Assoc. 53, 457–481 (1958).

    Article Google Scholar 

  46. Tukey, J. W. Exploratory Data Analysis (Addison-Wesley, 1977).

  47. Mann, H. B. & Whitney, D. R. On a test of whether one of two random variables is stochastically larger than the other. Ann. Math. Stat. 18, 50–60 (1947).

    Article Google Scholar 

  48. Fehm, T. et al. A concept for the standardized detection of disseminated tumor cells in bone marrow from patients with primary breast cancer and its clinical implementation. Cancer 107, 885–892 (2006).

    Article PubMed Google Scholar 

  49. Tolaney, S. M. et al. Updated standardized definitions for efficacy end points (STEEP) in adjuvant breast cancer clinical trials: STEEP version 2.0. J. Clin. Oncol. 39, 2720–2731 (2021).

    Article PubMed PubMed Central Google Scholar 

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Acknowledgements

We thank the Abramson Cancer Center and Penn Medicine for their support of the 2-PREVENT Translational Center of Excellence, as well as the staff and members of the 2-PREVENT TCE for their efforts in support of the CLEVER study. We acknowledge support from the following funders: the National Cancer Institute (R01CA208273 to A.D. and L.C.), Department of Defense (BC160784 to A.D. and L.C.), V Foundation, Breast Cancer Research Foundation (to A.D. and L.C.), QVC ‘Shoes on Sale’ (to A.D.), Jerry S. Rosenbloom (to A.D. and L.C.), Sara and Jim Gowing (to A.D. and L.C.), Avon Foundation (to A.D. and L.C.), Raynier Institute & Foundation (to A.D. and L.C.), Rhoda Polly Danziger and Michael Danziger (to L.C.), Andrea Orsher and Robert Orsher (to A.D.), the Dietz & Watson Family (to A.D.), and Novartis for providing Everolimus for the CLEVER trial. We appreciate the important contribution of the 2-PREVENT TCE Patient Advocate Board—J. Perlmutter, J. LaScala, C. Abi-Khattar, J. Bowles, M. Ayres, L. Mikulski and S. Axler. Finally, we are indebted to the CLEVER trial participants and their families, without whom this research would not be possible. This study was presented at the European Society of Clinical Oncology on 23 October 2023.

Author information

Authors and Affiliations

Contributions

L.A.C. and A.D. conceived of the approach to prevent recurrence by depleting MRD, designed the overall study, oversaw its conduct and obtained funding to support it. A.D. wrote the CLEVER protocol and provided oversight of study conduct. A.D., A.S.C. and J.S. provided clinical care to CLEVER trial participants and charted source documentation of clinical research visits. A.D., A.S.C. and J.S. conducted study visits and clinical management of study patients. L.J.B. provided project management, supervision of staff, input on regulatory matters and design of case report forms. K.R. cleaned and prepared CLEVER data for analysis. K.R., L.R.B., D.B., L.J.B., L.A.C. and A.D. generated figures (Figs. 2 and 3 and Extended Data Fig. 4) describing CLEVER trial results. I.N. coordinated participant visits and data collection on the CLEVER trial and assisted with patient sample collection. P.W. analyzed CLEVER feasibility data. L.R.B. and D.B. analyzed and interpreted CLEVER recurrence-free survival and DTC-IHC data. S.D. collected and tracked patient samples and managed sample inventory. S.E.D. and L.A.C. generated, analyzed and interpreted mouse preclinical data on the effects of CQ and RAPA on RTC number and recurrence-free survival, on which the mouse study and CLEVER trial were based. C.J.S., N.M., G.K.B. and S.E.D. performed mouse studies. Y.C. and A.E. processed mouse tumor samples and performed ddPCR to enumerate RTCs. E.S., T.C.P., D.K.P., G.K.B. and L.A.C. analyzed and interpreted mouse CLEVER recurrence-free survival and residual disease data. H.M. and E.S. performed and quantified western blots on mouse samples. E.S., J.W. and G.K.B. performed and analyzed mouse immunofluorescence studies. E.S., T.C.P., G.K.B. and L.A.C. generated figures describing mouse preclinical study results. G.K.B. and L.A.C. provided project management. G.K.B. provided supervision, wrote animal protocols and provided input on regulatory matters. B.L.G. performed patient BMAs. J.W., E.M.C. and J.G. contributed to the processing of patient samples. E.M.C. and J.G. provided control cell lines for the DTC-IHC assay, assisted in transitioning the DTC-IHC assay to a Clinical Laboratory Improvement Amendments (CLIA) laboratory and performed hemodilution assessment of BMAs. E.M.C., N.S., L.J.B. and I.M. contributed to the design and reporting of DTC-IHC assay rescreen testing and the implementation of the dual readers and adjudication system. M.F. and N.S. oversaw the transition of the DTC-IHC assay to a CLIA laboratory. M.F. and A.N. evaluated patient bone marrow samples for the presence of DTCs by DTC-IHC, adjudicated discordant reads and generated source pathology reports documenting DTC-IHC results. N.S., L.J.B. and S.D. provided operational support and coordination for sample collection and processing for the DTC-IHC assay. A.D., L.A.C. and E.S. drafted the manuscript. All authors approved the final manuscript and contributed to critical revisions of its intellectual content.

Corresponding authors

Correspondence to Angela DeMichele or Lewis A. Chodosh.

Ethics declarations

Competing interests

A.D. has received institutional research funding from Novartis, Genentech, Pfizer and NeoGenomics. L.A.C. has received institutional research funding from Novartis, AstraZeneca and Merck Research Laboratories, and has served as an expert consultant to Teva Pharmaceuticals, Eisai, Sanofi, Takeda Pharmaceuticals, Eli Lilly, Whittaker, Clark and Daniels, Wyeth, Imerys, Becton Dickinson, Sterigenics and the U.S. Department of Justice in litigation. The other authors declare no competing interests.

Peer review

Peer review information

Nature Medicine thanks the anonymous reviewer(s) for their contribution to the peer review of this work. Primary Handling Editors: J. Nakhle and S. Sadanand, in collaboration with the Nature Medicine team.

Additional information

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Presentation of the study European Society of Clinical Oncology, 23 October 2023.


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