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22 mei 2019: Bron: Breast Cancer Res. 2019; 21: 2. Published online 2019 Jan 7

Het is algemeen bekend dat vrouwen met hormonale borstkanker (ER+) hun actieve borstkanker jarenlang onder controle kunnen houden met vormen van hormoontherapie maar dan vele jaren later (tot wel 10 / 20 jaar later) alsnog een recidief krijgen. Femara - letrozole is denk ik een van de meest gebruikte vormen van hormoontherapie.

Recent is een interessante studie gepubliceerd waarin bij een aantal vrouwen met hormonale borstkanker (N = 42) op verschillende momenten bloedmonsters zijn genomen om daaruit een mutatieprofiel is halen. Daarbij werd gekeken waarom er resistentie en/of een recidief ontstond. En er is daarbij gekeken of het gaat om resistente kankercellen met zelfde DNA profiel als de primaire tumorcellen of om de zogeheten kankerstamcellen, ook wel slapende tumorcellen genoemd die vaak een ander DNA profiel hebben.

Wat opvalt is dat bepaalde specifieke mutaties al te zien in de eerste maanden van de behandeling en kunnen voorspellen of er vele jaren later een recidief op zal treden. Dat wetende zou de eerste behandeling daarop kunnen worden aangepast schrijven de onderzoekers.

In onderstaande grafiek zie je de momenten van de meding en het onderscheid in resistente tumorcellen en slapende tumorcellen. Gekoppeld aan de kans op een recidief.

Fig. 1

Long-term oestrogen deprivation therapy as a clinical model to investigate breast cancer dormancy and acquired resistance. a Extended (4–45 months) letrozole treatment was exploited as a clinical model of breast cancer dormancy and acquired resistance. Sequential clinical samples from the same patient with no surgery and extended treatment were used to model clinical breast cancer dormancy and resistance. Before (pre, ≤ 0 days), early-on (early, 13–120 days) and long-term (long, > 120 days) neoadjuvant aromatase inhibitor therapy with letrozole. b Dynamic change in tumour size by ultrasound scan (USS) and mean expression of proliferation markers MKI67, PCNA, and MCM2 were used to classify patients into two categories: dormant (blue) and resistant (red). Overall comparisons of classifications per patient based on USS and mean change in proliferation markers with final classification are shown. c The duration of letrozole treatment (days) for samples from dormant (blue) and resistant (red) patients. Each bar represents a sample. Samples are ordered by time on treatment. d Intrinsic subtype classification by PAM50 of samples at each time point. Stacked bar graphs on the right show the percentage of each subtype of samples from dormant and resistant patients. e Kaplan-Meier plot showing disease-free survival probability in patients with dormant versus resistant tumours (log-rank test). Disease-free survival was defined from time of surgery. f Density plot showing the distribution of time to recurrence (in years; defined from time of surgery) in patients with dormant and resistant tumours. CI confidence interval, HR hazard ratio, LumA luminal A, LumB luminal B

Het volledige studierapport: Molecular changes during extended neoadjuvant letrozole treatment of breast cancer: distinguishing acquired resistance from dormant tumours is gratis in te zien en geeft een gedetailleerde beschrijving van de waarde van de metingen van DNA mutaties, waarbij opvalt dat bepaalde specifieke mutaties al te zien in de eerste maanden van de behandeling kunnen voorspellen of er vele jaren later een recidief op zal treden. Dat wetende zou de eerste behandeling daarop kunnen worden aangepast schrijven de onderzoekers.

Conclusie vertaald: We hebben een eerste studie uitgevoerd van opeenvolgende tumormonsters van borstkankerpatiënten die langdurige neoadjuvante hortmoontherapie met femara / letrozole ontvingen als een klinisch model om slapende tumorcellen en resistente tumorcellen te meten.

Onze analyse suggereert dat moleculaire verschillen tussen slapende en resistente tumoren aanvankelijk subtiel zijn en pas na langdurige behandeling duidelijker worden. Deze studie benadrukt dat veranderingen in DNA-methylatie tijdens de eerste maanden van de behandeling kunnen voorspellen welke patiënte uiteindelijk resistentie / recidief zullen ontwikkelen.

Hier het abstract van de studie met referentielijst:

Epigenetic alterations may lead to escape from dormancy and drive acquired resistance in a subset of patients, supporting a potential role for therapy targeted at these epigenetic alterations in the management of resistance to oestrogen deprivation therapy.

. 2019; 21: 2.

Published online 2019 Jan 7. doi: 10.1186/s13058-018-1089-5

PMCID: PMC6323855

PMID: 30616553

Molecular changes during extended neoadjuvant letrozole treatment of breast cancer: distinguishing acquired resistance from dormant tumours

Cigdem Selli,^1,² Arran K. Turnbull,^1,³ Dominic A. Pearce,¹ Ang Li,¹ Anu Fernando,^1,³ Jimi Wills,⁴ Lorna Renshaw,³ Jeremy S. Thomas,³ J. Michael Dixon,³ and Andrew H. Sims¹

Abstract

Background

The risk of recurrence for endocrine-treated breast cancer patients persists for many years or even decades following surgery and apparently successful adjuvant therapy. This period of dormancy and acquired resistance is inherently difficult to investigate; previous efforts have been limited to in-vitro or in-vivo approaches. In this study, sequential tumour samples from patients receiving extended neoadjuvant aromatase inhibitor therapy were characterised as a novel clinical model.

Methods

Consecutive tumour samples from 62 patients undergoing extended (4–45 months) neoadjuvant aromatase inhibitor therapy with letrozole were subjected to transcriptomic and proteomic analysis, representing before (≤ 0), early (13–120 days), and long-term (> 120 days) neoadjuvant aromatase inhibitor therapy with letrozole. Patients with at least a 40% initial reduction in tumour size by 4 months of treatment were included. Of these, 42 patients with no subsequent progression were classified as “dormant”, and the remaining 20 patients as “acquired resistant”.

Results

Changes in gene expression in dormant tumours begin early and become more pronounced at later time points. Therapy-induced changes in resistant tumours were common features of treatment, rather than being specific to the resistant phenotype. Comparative analysis of long-term treated dormant and resistant tumours highlighted changes in epigenetics pathways including DNA methylation and histone acetylation. The DNA methylation marks 5-methylcytosine and 5-hydroxymethylcytosine were significantly reduced in resistant tumours compared with dormant tissues after extended letrozole treatment.

Conclusions

This is the first patient-matched gene expression study investigating long-term aromatase inhibitor-induced dormancy and acquired resistance in breast cancer. Dormant tumours continue to change during treatment whereas acquired resistant tumours more closely resemble their diagnostic samples. Global loss of DNA methylation was observed in resistant tumours under extended treatment. Epigenetic alterations may lead to escape from dormancy and drive acquired resistance in a subset of patients, supporting a potential role for therapy targeted at these epigenetic alterations in the management of resistance to oestrogen deprivation therapy.

Electronic supplementary material

The online version of this article (10.1186/s13058-018-1089-5) contains supplementary material, which is available to authorized users.

References

1. EBCTCG Aromatase inhibitors versus tamoxifen in early breast cancer: patient-level meta-analysis of the randomised trials. Lancet. 2015;386(10001):1341–1352. [PubMed] [Google Scholar]

2. Demicheli R, Ardoino I, Boracchi P, Coradini D, Agresti R, Ferraris C, et al. Recurrence and mortality according to estrogen receptor status for breast cancer patients undergoing conservative surgery. Ipsilateral breast tumour recurrence dynamics provides clues for tumour biology within the residual breast. BMC Cancer. 2010;10:656. [PMC free article] [PubMed] [Google Scholar]

3. Pan HC, Gray R, Braybrooke J, Davies C, Taylor C, McGale P, et al. 20-Year risks of breast-cancer recurrence after stopping endocrine therapy at 5 years. N Engl J Med. 2017;377(19):1836–1846. [PMC free article] [PubMed] [Google Scholar]

4. Weigelt B, Glas AM, Wessels LF, Witteveen AT, Peterse JL, van't Veer LJ. Gene expression profiles of primary breast tumors maintained in distant metastases. Proc Natl Acad Sci U S A. 2003;100(26):15901–15905. [PMC free article] [PubMed] [Google Scholar]

5. Tang MH, Dahlgren M, Brueffer C, Tjitrowirjo T, Winter C, Chen Y, et al. Remarkable similarities of chromosomal rearrangements between primary human breast cancers and matched distant metastases as revealed by whole-genome sequencing. Oncotarget. 2015;6(35):37169–37184. [PMC free article] [PubMed] [Google Scholar]

6. Kroigard AB, Larsen MJ, Thomassen M, Kruse TA. Molecular concordance between primary breast cancer and matched metastases. Breast J. 2016;22(4):420–430. [PubMed] [Google Scholar]

7. Demicheli R, Terenziani M, Bonadonna G. Estimate of tumor growth time for breast cancer local recurrences: rapid growth after wake-up? Breast Cancer Res Treat. 1998;51(2):133–137. [PubMed] [Google Scholar]

8. Uhr JW, Pantel K. Controversies in clinical cancer dormancy. Proc Natl Acad Sci U S A. 2011;108(30):12396–12400. [PMC free article] [PubMed] [Google Scholar]

9. Sosa MS, Bragado P, Aguirre-Ghiso JA. Mechanisms of disseminated cancer cell dormancy: an awakening field. Nat Rev Cancer. 2014;14(9):611–622. [PMC free article] [PubMed] [Google Scholar]

10. Dittmer J. Mechanisms governing metastatic dormancy in breast cancer. Semin Cancer Biol. 2017;44:72–82. [PubMed] [Google Scholar]

11. Selli C, Dixon JM, Sims AH. Accurate prediction of response to endocrine therapy in breast cancer patients: current and future biomarkers. Breast Cancer Res. 2016;18(1):118. [PMC free article] [PubMed] [Google Scholar]

12. Clarke R, Tyson JJ, Dixon JM. Endocrine resistance in breast cancer—an overview and update. Mol Cell Endocrinol. 2015;418(Pt 3):220–234. [PMC free article] [PubMed] [Google Scholar]

13. Ma CX, Reinert T, Chmielewska I, Ellis MJ. Mechanisms of aromatase inhibitor resistance. Nat Rev Cancer. 2015;15(5):261–275. [PubMed] [Google Scholar]

14. Sims AH, Bartlett JMS. Approaches towards expression profiling the response to treatment. Breast Cancer Res. 2008;10(6):115. [PMC free article] [PubMed] [Google Scholar]

15. Vendrell JA, Robertson KE, Ravel P, Bray SE, Bajard A, Purdie CA, et al. A candidate molecular signature associated with tamoxifen failure in primary breast cancer. Breast Cancer Res. 2008;10(5):R88. [PMC free article] [PubMed] [Google Scholar]

16. Turnbull AK, Arthur LM, Renshaw L, Larionov AA, Kay C, Dunbier AK, et al. Accurate prediction and validation of response to endocrine therapy in breast cancer. J Clin Oncol. 2015;33(20):2270–2278. [PubMed] [Google Scholar]

17. Dunbier AK, Ghazoui Z, Anderson H, Salter J, Nerurkar A, Osin P, et al. Molecular profiling of aromatase inhibitor-treated postmenopausal breast tumors identifies immune-related correlates of resistance. Clin Cancer Res. 2013;19(10):2775–2786. [PubMed] [Google Scholar]

18. Patani N, Dunbier AK, Anderson H, Ghazoui Z, Ribas R, Anderson E, et al. Differences in the transcriptional response to fulvestrant and estrogen deprivation in ER-positive breast cancer. Clin Cancer Res. 2014;20(15):3962–3973. [PMC free article] [PubMed] [Google Scholar]

19. Arthur LM, Turnbull AK, Webber VL, Larionov AA, Renshaw L, Kay C, et al. Molecular changes in lobular breast cancers in response to endocrine therapy. Cancer Res. 2014;74(19):5371–5376. [PubMed] [Google Scholar]

20. Turnbull AK, Kitchen RR, Larionov AA, Renshaw L, Dixon JM, Sims AH. Direct integration of intensity-level data from Affymetrix and Illumina microarrays improves statistical power for robust reanalysis. BMC Med Genet. 2012;5:35. [PMC free article] [PubMed] [Google Scholar]

21. Du P, Kibbe WA, Lin SM. lumi: a pipeline for processing Illumina microarray. Bioinformatics. 2008;24(13):1547–1548. [PubMed] [Google Scholar]

22. Yu G, He QY. ReactomePA: an R/Bioconductor package for reactome pathway analysis and visualization. Mol BioSyst. 2016;12(2):477–479. [PubMed] [Google Scholar]

23. Hong FX, Breitling R, McEntee CW, Wittner BS, Nemhauser JL, Chory J. RankProd: a bioconductor package for detecting differentially expressed genes in meta-analysis. Bioinformatics. 2006;22(22):2825–2827. [PubMed] [Google Scholar]

24. Likhite N, Warawdekar UM. A unique method for isolation and solubilization of proteins after extraction of RNA from tumor tissue using trizol. J Biomol Tech. 2011;22(1):37–44. [PMC free article] [PubMed] [Google Scholar]

25. Coleman O, Henry M, Clynes M, Meleady P. Filter-Aided Sample Preparation (FASP) for improved proteome analysis of recombinant Chinese hamster ovary cells. Methods Mol Biol. 2017;1603:187–194. [PubMed] [Google Scholar]

26. Rappsilber J, Ishihama Y, Mann M. Stop and go extraction tips for matrix-assisted laser desorption/ionization, nanoelectrospray, and LC/MS sample pretreatment in proteomics. Anal Chem. 2003;75(3):663–670. [PubMed] [Google Scholar]

27. Cox J, Mann M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat Biotechnol. 2008;26(12):1367–1372. [PubMed] [Google Scholar]

28. Vizcaino JA, Csordas A, Del-Toro N, Dianes JA, Griss J, Lavidas I, et al. 2016 update of the PRIDE database and its related tools. Nucleic Acids Res. 2016;44(22):11033. [PMC free article] [PubMed] [Google Scholar]

29. Haffner MC, Chaux A, Meeker AK, Esopi DM, Gerber J, Pellakuru LG, et al. Global 5-hydroxymethylcytosine content is significantly reduced in tissue stem/progenitor cell compartments and in human cancers. Oncotarget. 2011;2(8):627–637. [PMC free article] [PubMed] [Google Scholar]

30. Perou CM, Sorlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, et al. Molecular portraits of human breast tumours. Nature. 2000;406(6797):747–752. [PubMed] [Google Scholar]

31. Nielsen TO, Parker JS, Leung S, Voduc D, Ebbert M, Vickery T, et al. A comparison of PAM50 intrinsic subtyping with immunohistochemistry and clinical prognostic factors in tamoxifen-treated estrogen receptor-positive breast cancer. Clin Cancer Res. 2010;16(21):5222–5232. [PMC free article] [PubMed] [Google Scholar]

32. Cochrane DR, Bernales S, Jacobsen BM, Cittelly DM, Howe EN, D'Amato NC, et al. Role of the androgen receptor in breast cancer and preclinical analysis of enzalutamide. Breast Cancer Res. 2014;16(1):R7. [PMC free article] [PubMed] [Google Scholar]

33. Barbie DA, Tamayo P, Boehm JS, Kim SY, Moody SE, Dunn IF, et al. Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1. Nature. 2009;462(7269):108–U122. [PMC free article] [PubMed] [Google Scholar]

34. Chen EY, Tan CM, Kou Y, Duan Q, Wang Z, Meirelles GV, et al. Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinformatics. 2013;14:128. [PMC free article] [PubMed] [Google Scholar]

35. Ellis MJ, Suman VJ, Hoog J, Goncalves R, Sanati S, Creighton CJ, et al. Ki67 proliferation index as a tool for chemotherapy decisions during and after neoadjuvant aromatase inhibitor treatment of breast cancer: results from the American College of Surgeons Oncology group Z1031 trial (Alliance) J Clin Oncol. 2017;35(10):1061–1069. [PMC free article] [PubMed] [Google Scholar]

36. Jankowitz RC, Oesterreich S, Lee AV, Davidson NE. New strategies in metastatic hormone receptor-positive breast cancer: searching for biomarkers to tailor endocrine and other targeted therapies. Clin Cancer Res. 2017;23(5):1126–1131. [PMC free article] [PubMed] [Google Scholar]

37. Miller WR, Larionov A. Changes in expression of oestrogen regulated and proliferation genes with neoadjuvant treatment highlight heterogeneity of clinical resistance to the aromatase inhibitor, letrozole. Breast Cancer Res. 2010;12(4):R52. [PMC free article] [PubMed] [Google Scholar]

38. Zhang XHF, Giuliano M, Trivedi MV, Schiff R, Osborne CK. Metastasis dormancy in estrogen receptor-positive breast cancer. Clin Cancer Res. 2013;19(23):6389–6397. [PMC free article] [PubMed] [Google Scholar]

39. Bartosh TJ. Cancer cell cannibalism and the SASP: ripples in the murky waters of tumor dormancy. Mol Cell Oncol. 2017;4(1):e1263715. [PMC free article] [PubMed] [Google Scholar]

40. Barkan D, Green JE, Chambers AF. Extracellular matrix: a gatekeeper in the transition from dormancy to metastatic growth. Eur J Cancer. 2010;46(7):1181–1188. [PMC free article] [PubMed] [Google Scholar]

41. Wang G, Platt-Higgins A, Carroll J, de Silva RS, Winstanley J, Barraclough R, et al. Induction of metastasis by S100P in a rat mammary model and its association with poor survival of breast cancer patients. Cancer Res. 2006;66(2):1199–1207. [PubMed] [Google Scholar]

42. Prica F, Radon T, Cheng Y, Crnogorac-Jurcevic T. The life and works of S100P—from conception to cancer. Am J Cancer Res. 2016;6(2):562–576. [PMC free article] [PubMed] [Google Scholar]

43. Yang RX, Stocker S, Schott S, Heil J, Marme F, Cuk K, et al. The association between breast cancer and S100P methylation in peripheral blood by multicenter case- control studies. Carcinogenesis. 2017;38(3):312–320. [PubMed] [Google Scholar]

44. Peng C, Chen H, Wallwiener M, Modugno C, Cuk K, Madhavan D, et al. Plasma S100P level as a novel prognostic marker of metastatic breast cancer. Breast Cancer Res Treat. 2016;157(2):329–338. [PubMed] [Google Scholar]

45. Dakhel S, Padilla L, Adan J, Masa M, Martinez JM, Roque L, et al. S100P antibody-mediated therapy as a new promising strategy for the treatment of pancreatic cancer. Oncogene. 2014;3:e92. [PMC free article] [PubMed] [Google Scholar]

46. Basse C, Arock M. The increasing roles of epigenetics in breast cancer: implications for pathogenicity, biomarkers, prevention and treatment. Int J Cancer. 2015;137(12):2785–2794. [PubMed] [Google Scholar]

47. Crea F, Nur Saidy NR, Collins CC, Wang Y. The epigenetic/noncoding origin of tumor dormancy. Trends Mol Med. 2015;21(4):206–211. [PubMed] [Google Scholar]

48. Fang F, Turcan S, Rimner A, Kaufman A, Giri D, Morris LG, et al. Breast cancer methylomes establish an epigenomic foundation for metastasis. Sci Transl Med. 2011;3(75):75ra25. [PMC free article] [PubMed] [Google Scholar]

49. Tsang JS, Vencken S, Sharaf O, Leen E, Kay EW, McNamara DA, et al. Global DNA methylation is altered by neoadjuvant chemoradiotherapy in rectal cancer and may predict response to treatment—a pilot study. Eur J Surg Oncol. 2014;40(11):1459–1466. [PubMed] [Google Scholar]

50. De Smet C, Loriot A. DNA hypomethylation in cancer: epigenetic scars of a neoplastic journey. Epigenetics. 2010;5(3):206–213. [PubMed] [Google Scholar]

51. Pathiraja TN, Xi Y, Lee AV, Santen R, Gannon F, Kaipparettu B, et al. Estrogen deprivation results in altered DNA methylation profile in breast cancer cells—role in endocrine resistance? Cancer Res. 2009;69(24):808s. [Google Scholar]

52. Harris ME, Bohni R, Schneiderman MH, Ramamurthy L, Schumperli D, Marzluff WF. Regulation of histone mRNA in the unperturbed cell cycle: evidence suggesting control at two posttranscriptional steps. Mol Cell Biol. 1991;11(5):2416–2424. [PMC free article] [PubMed] [Google Scholar]

53. Braunstein M, Liao L, Lyttle N, Lobo N, Taylor KJ, Krzyzanowski PM, et al. Downregulation of histone H2A and H2B pathways is associated with anthracycline sensitivity in breast cancer. Breast Cancer Res. 2016;18(1):16. [PMC free article] [PubMed] [Google Scholar]

54. Zhu Z, Edwards RJ, Boobis AR. Increased expression of histone proteins during estrogen-mediated cell proliferation. Environ Health Perspect. 2009;117(6):928–934. [PMC free article] [PubMed] [Google Scholar]

55. Sarkar S, Abujamra AL, Loew JE, Forman LW, Perrine SP, Faller DV. Histone deacetylase inhibitors reverse CpG methylation by regulating DNMT1 through ERK signaling. Anticancer Res. 2011;31(9):2723–2732. [PubMed] [Google Scholar]

56. Lee JH, Choy ML, Ngo L, Foster SS, Marks PA. Histone deacetylase inhibitor induces DNA damage, which normal but not transformed cells can repair. Proc Natl Acad Sci U S A. 2010;107(33):14639–14644. [PMC free article] [PubMed] [Google Scholar]

57. Bolden JE, Shi W, Jankowski K, Kan CY, Cluse L, Martin BP, et al. HDAC inhibitors induce tumor-cell-selective pro-apoptotic transcriptional responses. Cell Death Dis. 2013;4:e519. [PMC free article] [PubMed] [Google Scholar]

58. Ceccacci E, Minucci S. Inhibition of histone deacetylases in cancer therapy: lessons from leukaemia. Br J Cancer. 2016;114(6):605–611. [PMC free article] [PubMed] [Google Scholar]

59. Masri S, Lui K, Phung S, Ye J, Zhou D, Wang X, et al. Characterization of the weak estrogen receptor alpha agonistic activity of exemestane. Breast Cancer Res Treat. 2009;116(3):461–470. [PMC free article] [PubMed] [Google Scholar]

60. Aguilar H, Sole X, Bonifaci N, Serra-Musach J, Islam A, Lopez-Bigas N, et al. Biological reprogramming in acquired resistance to endocrine therapy of breast cancer. Oncogene. 2010;29(45):6071–6083. [PubMed] [Google Scholar]

61. Milosevic J, Klinge J, Borg AL, Foukakis T, Bergh J, Tobin NP. Clinical instability of breast cancer markers is reflected in long-term in vitro estrogen deprivation studies. BMC Cancer. 2013;13:473. [PMC free article] [PubMed] [Google Scholar]

62. Simigdala N, Gao Q, Pancholi S, Roberg-Larsen H, Zvelebil M, Ribas R, et al. Cholesterol biosynthesis pathway as a novel mechanism of resistance to estrogen deprivation in estrogen receptor-positive breast cancer. Breast Cancer Res. 2016;18:58. [PMC free article] [PubMed] [Google Scholar]

63. Coser KR, Wittner BS, Rosenthal NF, Collins SC, Melas A, Smith SL, et al. Antiestrogen-resistant subclones of MCF-7 human breast cancer cells are derived from a common monoclonal drug-resistant progenitor. Proc Natl Acad Sci U S A. 2009;106(34):14536–14541. [PMC free article] [PubMed] [Google Scholar]

64. Alves CL, Elias D, Lyng M, Bak M, Kirkegaard T, Lykkesfeldt AE, et al. High CDK6 protects cells from fulvestrant-mediated apoptosis and is a predictor of resistance to fulvestrant in estrogen receptor-positive metastatic breast cancer. Clin Cancer Res. 2016;22(22):5514–5526. [PubMed] [Google Scholar]