Establishment of chemosensitivity tests in triple-negative and BRCA-mutated breast cancer patient-derived xenograft models

English version

Autoři: Hyung Seok Park ^aff001; Jeong Dong Lee ^aff002; Jee Ye Kim ^aff001; Seho Park ^aff001; Joo Heung Kim ^aff001; Hyun Ju Han ^aff003; Yeon A. Choi ^aff003; Ae Ran Choi ^aff003; Joo Hyuk Sohn ^aff004; Seung Il Kim ^aff001
Působiště autorů: Department of Surgery, Yonsei University College of Medicine, Seoul, Korea ^aff001; Department of Human Biology and Genomics, Brain Korea 21 PLUS Project for Medical Sciences, Yonsei University College of Medicine, Seoul, Korea ^aff002; Avison Biomedical Research Center, Yonsei University College of Medicine, Seoul, Korea ^aff003; Division of Medical Oncology, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea ^aff004
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0225082

Souhrn

Purpose

A patient-derived xenograft (PDX) model is an in vivo animal model which provides biological and genomic profiles similar to a primary tumor. The characterization of factors that influence the establishment of PDX is crucial. Furthermore, PDX models can provide a platform for chemosensitivity tests to evaluate the effectiveness of a target agent before applying it in clinical trials.

Methods

We implanted 83 cases of breast cancer into NOD.Cg-Prkdcscid Il2rgtm1Sug/Jic mice, to develop PDX models. Clinicopathological factors of primary tumors were reviewed to identify the factors affecting engraftment success rates. After the establishment of PDX models, we performed olaparib and carboplatin chemosensitivity tests. We used PDX models from triple-negative breast cancer (TNBC) with neoadjuvant chemotherapy and/or germline BRCA1 mutations in chemosensitivity tests.

Results

The univariate analyses (p<0.05) showed factors which were significantly associated with successful engraftment of PDX models include poor histologic grade, presence of BRCA mutation, aggressive diseases, and death. Factors which were independently associated with successful engraftment of PDX models on multivariate analyses include poor histologic grade and aggressive diseases status. In chemosensitivity tests, a PDX model with the BRCA1 L1780P mutation showed partial response to olaparib and complete response to carboplatin.

Conclusions

Successful engraftment of PDX models was significantly associated with aggressive diseases. Patients who have aggressive diseases status, large tumors, and poor histologic grade are ideal candidates for developing successful PDX models. Chemosensitivity tests using the PDX models provide additional information about alternative treatment strategies for residual TNBC after neoadjuvant chemotherapy.

Klíčová slova:

Breast cancer – Cancer chemotherapy – Cancer treatment – Drug research and development – Genetic causes of cancer – Histology – Mammalian genomics – Medical implants

Zdroje

1. Ovcaricek T, Frkovic SG, Matos E, Mozina B, Borstnar S. Triple negative breast cancer—prognostic factors and survival. Radiol Oncol. 2011;45(1):46–52. doi: 10.2478/v10019-010-0054-4 22933934; PubMed Central PMCID: PMC3423721.

2. Isakoff SJ. Triple-negative breast cancer: role of specific chemotherapy agents. Cancer J. 2010;16(1):53–61. doi: 10.1097/PPO.0b013e3181d24ff7 20164691; PubMed Central PMCID: PMC2882502.

3. DiMasi JA, Hansen RW, Grabowski HG. The price of innovation: new estimates of drug development costs. J Health Econ. 2003;22(2):151–85. doi: 10.1016/S0167-6296(02)00126-1 12606142.

4. Kaitin KI, Healy EM. The new drug approvals of 1996, 1997, and 1998: Drug development trends in the user fee era. Drug Inf J. 2000;34(1):1–14. WOS:000085436000001.

5. Adams CP, Brantner VV. Estimating the cost of new drug development: is it really 802 million dollars? Health Aff (Millwood). 2006;25(2):420–8. doi: 10.1377/hlthaff.25.2.420 16522582.

6. Dickersin K, Rennie D. Registering clinical trials. JAMA. 2003;290(4):516–23. doi: 10.1001/jama.290.4.516 12876095.

7. Allen DD, Caviedes R, Cardenas AM, Shimahara T, Segura-Aguilar J, Caviedes PA. Cell lines as in vitro models for drug screening and toxicity studies. Drug Dev Ind Pharm. 2005;31(8):757–68. doi: 10.1080/03639040500216246 16221610.

8. Astashkina A, Mann B, Grainger DW. A critical evaluation of in vitro cell culture models for high-throughput drug screening and toxicity. Pharmacol Ther. 2012;134(1):82–106. doi: 10.1016/j.pharmthera.2012.01.001 22252140.

9. Siolas D, Hannon GJ. Patient-derived tumor xenografts: transforming clinical samples into mouse models. Cancer Res. 2013;73(17):5315–9. doi: 10.1158/0008-5472.CAN-13-1069 23733750; PubMed Central PMCID: PMC3766500.

10. Hidalgo M, Amant F, Biankin AV, Budinska E, Byrne AT, Caldas C, et al. Patient-derived xenograft models: an emerging platform for translational cancer research. Cancer Discov. 2014;4(9):998–1013. doi: 10.1158/2159-8290.CD-14-0001 25185190; PubMed Central PMCID: PMC4167608.

11. Clarke R. Human breast cancer cell line xenografts as models of breast cancer. The immunobiologies of recipient mice and the characteristics of several tumorigenic cell lines. Breast Cancer Res Treat. 1996;39(1):69–86. doi: 10.1007/bf01806079 8738607.

12. Sausville EA, Burger AM. Contributions of human tumor xenografts to anticancer drug development. Cancer Res. 2006;66(7):3351–4, discussion 4. doi: 10.1158/0008-5472.CAN-05-3627 16585151.

13. Daniel VC, Marchionni L, Hierman JS, Rhodes JT, Devereux WL, Rudin CM, et al. A primary xenograft model of small-cell lung cancer reveals irreversible changes in gene expression imposed by culture in vitro. Cancer Res. 2009;69(8):3364–73. doi: 10.1158/0008-5472.CAN-08-4210 19351829; PubMed Central PMCID: PMC2821899.

14. Dangles-Marie V, Pocard M, Richon S, Weiswald LB, Assayag F, Saulnier P, et al. Establishment of human colon cancer cell lines from fresh tumors versus xenografts: comparison of success rate and cell line features. Cancer Res. 2007;67(1):398–407. doi: 10.1158/0008-5472.CAN-06-0594 17210723.

15. Gagos S, Iliopoulos D, Tseleni-Balafouta S, Agapitos M, Antachopoulos C, Kostakis A, et al. Cell senescence and a mechanism of clonal evolution leading to continuous cell proliferation, loss of heterozygosity, and tumor heterogeneity: studies on two immortal colon cancer cell lines. Cancer Genet Cytogenet. 1996;90(2):157–65. doi: 10.1016/s0165-4608(96)00049-0 8830727.

16. Manning HC, Buck JR, Cook RS. Mouse Models of Breast Cancer: Platforms for Discovering Precision Imaging Diagnostics and Future Cancer Medicine. J Nucl Med. 2016;57 Suppl 1:60S–8S. doi: 10.2967/jnumed.115.157917 26834104.

17. Chijiwa T, Kawai K, Noguchi A, Sato H, Hayashi A, Cho H, et al. Establishment of patient-derived cancer xenografts in immunodeficient NOG mice. Int J Oncol. 2015;47(1):61–70. doi: 10.3892/ijo.2015.2997 25963555; PubMed Central PMCID: PMC4485657.

18. Kawaguchi T, Foster BA, Young J, Takabe K. Current Update of Patient-Derived Xenograft Model for Translational Breast Cancer Research. J Mammary Gland Biol Neoplasia. 2017;22(2):131–9. doi: 10.1007/s10911-017-9378-7 28451789.

19. Cho SY, Kang W, Han JY, Min S, Kang J, Lee A, et al. An Integrative Approach to Precision Cancer Medicine Using Patient-Derived Xenografts. Mol Cells. 2016;39(2):77–86. doi: 10.14348/molcells.2016.2350 26831452; PubMed Central PMCID: PMC4757806.

20. Byrne AT, Alferez DG, Amant F, Annibali D, Arribas J, Biankin AV, et al. Interrogating open issues in cancer precision medicine with patient-derived xenografts. Nat Rev Cancer. 2017;17(4):254–68. doi: 10.1038/nrc.2016.140 28104906.

21. Gao H, Korn JM, Ferretti S, Monahan JE, Wang Y, Singh M, et al. High-throughput screening using patient-derived tumor xenografts to predict clinical trial drug response. Nat Med. 2015;21(11):1318–25. doi: 10.1038/nm.3954 26479923.

22. Wu L, Allo G, John T, Li M, Tagawa T, Opitz I, et al. Patient-Derived Xenograft Establishment from Human Malignant Pleural Mesothelioma. Clin Cancer Res. 2017;23(4):1060–7. doi: 10.1158/1078-0432.CCR-16-0844 27683181.

23. Peng S, Creighton CJ, Zhang Y, Sen B, Mazumdar T, Myers JN, et al. Tumor grafts derived from patients with head and neck squamous carcinoma authentically maintain the molecular and histologic characteristics of human cancers. J Transl Med. 2013;11:198. doi: 10.1186/1479-5876-11-198 23981300; PubMed Central PMCID: PMC3844397.

24. Lee HW, Lee JI, Lee SJ, Cho HJ, Song HJ, Jeong DE, et al. Patient-derived xenografts from non-small cell lung cancer brain metastases are valuable translational platforms for the development of personalized targeted therapy. Clin Cancer Res. 2015;21(5):1172–82. doi: 10.1158/1078-0432.CCR-14-1589 25549722.

25. Dong R, Qiang W, Guo H, Xu X, Kim JJ, Mazar A, et al. Histologic and molecular analysis of patient derived xenografts of high-grade serous ovarian carcinoma. J Hematol Oncol. 2016;9(1):92. doi: 10.1186/s13045-016-0318-6 27655386; PubMed Central PMCID: PMC5031262.

26. Tentler JJ, Tan AC, Weekes CD, Jimeno A, Leong S, Pitts TM, et al. Patient-derived tumour xenografts as models for oncology drug development. Nat Rev Clin Oncol. 2012;9(6):338–50. doi: 10.1038/nrclinonc.2012.61 22508028; PubMed Central PMCID: PMC3928688.

27. Kato C, Fujii E, Chen YJ, Endaya BB, Matsubara K, Suzuki M, et al. Spontaneous thymic lymphomas in the non-obese diabetic/Shi-scid, IL-2R gamma (null) mouse. Lab Anim. 2009;43(4):402–4. doi: 10.1258/la.2009.009012 19505936.

28. Paez-Ribes M, Man S, Xu P, Kerbel RS. Development of Patient Derived Xenograft Models of Overt Spontaneous Breast Cancer Metastasis: A Cautionary Note. PLoS One. 2016;11(6):e0158034. doi: 10.1371/journal.pone.0158034 27355476; PubMed Central PMCID: PMC4927067.

29. Morton CL, Houghton PJ. Establishment of human tumor xenografts in immunodeficient mice. Nat Protoc. 2007;2(2):247–50. doi: 10.1038/nprot.2007.25 17406581.

30. DeRose YS, Wang G, Lin YC, Bernard PS, Buys SS, Ebbert MT, et al. Tumor grafts derived from women with breast cancer authentically reflect tumor pathology, growth, metastasis and disease outcomes. Nat Med. 2011;17(11):1514–20. doi: 10.1038/nm.2454 22019887; PubMed Central PMCID: PMC3553601.

31. Zhang X, Claerhout S, Prat A, Dobrolecki LE, Petrovic I, Lai Q, et al. A renewable tissue resource of phenotypically stable, biologically and ethnically diverse, patient-derived human breast cancer xenograft models. Cancer Res. 2013;73(15):4885–97. doi: 10.1158/0008-5472.CAN-12-4081 23737486; PubMed Central PMCID: PMC3732575.

32. Park JS, Nam EJ, Park HS, Han JW, Lee JY, Kim J, et al. Identification of a Novel BRCA1 Pathogenic Mutation in Korean Patients Following Reclassification of BRCA1 and BRCA2 Variants According to the ACMG Standards and Guidelines Using Relevant Ethnic Controls. Cancer Res Treat. 2017;49(4):1012–21. doi: 10.4143/crt.2016.433 28111427; PubMed Central PMCID: PMC5654176.

33. Rottenberg S, Jaspers JE, Kersbergen A, van der Burg E, Nygren AO, Zander SA, et al. High sensitivity of BRCA1-deficient mammary tumors to the PARP inhibitor AZD2281 alone and in combination with platinum drugs. Proc Natl Acad Sci U S A. 2008;105(44):17079–84. doi: 10.1073/pnas.0806092105 18971340; PubMed Central PMCID: PMC2579381.

34. Erriquez J, Olivero M, Mittica G, Scalzo MS, Vaira M, De Simone M, et al. Xenopatients show the need for precision medicine approach to chemotherapy in ovarian cancer. Oncotarget. 2016;7(18):26181–91. doi: 10.18632/oncotarget.8325 27027433; PubMed Central PMCID: PMC5041973.

35. S A. FastQC: a quality control tool for high throughput sequence data. 2010. Available from: http://www.bioinformatics.babraham.ac.uk/projects/fastqc.

36. Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. 2011. 2011;17(1). doi: 10.14806/ej.17.1.200 pp. 10–12.

37. Bushnell B. BBMap: A Fast, Accurate, Splice-Aware Aligner. 2014 LBNL-7065E.

38. Cancer Genome Atlas N. [cited 2019 30, August]. Available from: https://portal.gdc.cancer.gov/genes/ENSG00000012048.

39. McAuliffe PF, Evans KW, Akcakanat A, Chen K, Zheng X, Zhao H, et al. Ability to Generate Patient-Derived Breast Cancer Xenografts Is Enhanced in Chemoresistant Disease and Predicts Poor Patient Outcomes. PLoS One. 2015;10(9):e0136851. doi: 10.1371/journal.pone.0136851 26325287; PubMed Central PMCID: PMC4556673.

40. Park B, Jeong BC, Choi YL, Kwon GY, Lim JE, Seo SI, et al. Development and characterization of a bladder cancer xenograft model using patient-derived tumor tissue. Cancer Sci. 2013;104(5):631–8. doi: 10.1111/cas.12123 23384396.

41. Jun E, Jung J, Jeong SY, Choi EK, Kim MB, Lee JS, et al. Surgical and Oncological Factors Affecting the Successful Engraftment of Patient-derived Xenografts in Pancreatic Ductal Adenocarcinoma. Anticancer Res. 2016;36(2):517–21. 26851005.

42. Creighton CJ, Li X, Landis M, Dixon JM, Neumeister VM, Sjolund A, et al. Residual breast cancers after conventional therapy display mesenchymal as well as tumor-initiating features. Proc Natl Acad Sci U S A. 2009;106(33):13820–5. doi: 10.1073/pnas.0905718106 19666588; PubMed Central PMCID: PMC2720409.

43. Landis MD, Lehmann BD, Pietenpol JA, Chang JC. Patient-derived breast tumor xenografts facilitating personalized cancer therapy. Breast Cancer Res. 2013;15(1):201. doi: 10.1186/bcr3355 23339383; PubMed Central PMCID: PMC3672825.

44. Moon HG, Oh K, Lee J, Lee M, Kim JY, Yoo TK, et al. Prognostic and functional importance of the engraftment-associated genes in the patient-derived xenograft models of triple-negative breast cancers. Breast Cancer Res Treat. 2015;154(1):13–22. doi: 10.1007/s10549-015-3585-y 26438141.

45. Assayag F, Nicolas A, Vacher S, Dehainault C, Bieche I, Meseure D, et al. Combination of Carboplatin and Bevacizumab Is an Efficient Therapeutic Approach in Retinoblastoma Patient-Derived Xenografts. Invest Ophthalmol Vis Sci. 2016;57(11):4916–26. doi: 10.1167/iovs.15-18725 27654418.

46. Ibrahim YH, Garcia-Garcia C, Serra V, He L, Torres-Lockhart K, Prat A, et al. PI3K inhibition impairs BRCA1/2 expression and sensitizes BRCA-proficient triple-negative breast cancer to PARP inhibition. Cancer Discov. 2012;2(11):1036–47. doi: 10.1158/2159-8290.CD-11-0348 22915752; PubMed Central PMCID: PMC5125254.

47. Juvekar A, Burga LN, Hu H, Lunsford EP, Ibrahim YH, Balmana J, et al. Combining a PI3K inhibitor with a PARP inhibitor provides an effective therapy for BRCA1-related breast cancer. Cancer Discov. 2012;2(11):1048–63. doi: 10.1158/2159-8290.CD-11-0336 22915751; PubMed Central PMCID: PMC3733368.

48. Goetz MP, Kalari KR, Suman VJ, Moyer AM, Yu J, Visscher DW, et al. Tumor Sequencing and Patient-Derived Xenografts in the Neoadjuvant Treatment of Breast Cancer. J Natl Cancer Inst. 2017;109(7). doi: 10.1093/jnci/djw306 28376176; PubMed Central PMCID: PMC5408989.

49. Robson M, Im SA, Senkus E, Xu B, Domchek SM, Masuda N, et al. Olaparib for Metastatic Breast Cancer in Patients with a Germline BRCA Mutation. N Engl J Med. 2017;377(6):523–33. doi: 10.1056/NEJMoa1706450 28578601.

50. Guan Z, Lan H, Chen X, Jiang X, Wang X, Jin K. Individualized drug screening based on next generation sequencing and patient derived xenograft model for pancreatic cancer with bone metastasis. Mol Med Rep. 2017;16(4):4784–90. doi: 10.3892/mmr.2017.7213 28849200.

51. Xie T, Musteanu M, Lopez-Casas PP, Shields DJ, Olson P, Rejto PA, et al. Whole Exome Sequencing of Rapid Autopsy Tumors and Xenograft Models Reveals Possible Driver Mutations Underlying Tumor Progression. PLoS One. 2015;10(11):e0142631. doi: 10.1371/journal.pone.0142631 26555578; PubMed Central PMCID: PMC4640827.

52. Morton JJ, Bird G, Keysar SB, Astling DP, Lyons TR, Anderson RT, et al. XactMice: humanizing mouse bone marrow enables microenvironment reconstitution in a patient-derived xenograft model of head and neck cancer. Oncogene. 2016;35(3):290–300. doi: 10.1038/onc.2015.94 25893296; PubMed Central PMCID: PMC4613815.

53. Morton JJ, Bird G, Refaeli Y, Jimeno A. Humanized Mouse Xenograft Models: Narrowing the Tumor-Microenvironment Gap. Cancer Res. 2016;76(21):6153–8. doi: 10.1158/0008-5472.CAN-16-1260 27587540; PubMed Central PMCID: PMC5093075.

54. Choi YY, Lee JE, Kim H, Sim MH, Kim KK, Lee G, et al. Establishment and characterisation of patient-derived xenografts as paraclinical models for gastric cancer. Sci Rep. 2016;6:22172. doi: 10.1038/srep22172 26926953; PubMed Central PMCID: PMC4772087.

Establishment of chemosensitivity tests in triple-negative and BRCA-mutated breast cancer patient-derived xenograft models

Souhrn

Purpose

Methods

Results

Conclusions

Klíčová slova:

Zdroje

PLOS One

Svět praktické medicíny 1/2024 (znalostní test z časopisu)

Koncepce osteologické péče pro gynekology a praktické lékaře

Sekvenční léčba schizofrenie

Hypertenze a hypercholesterolémie – synergický efekt léčby

Význam metforminu pro „udržitelnou“ terapii diabetu