Skip to main content
Home
Zeitschriften
Zeitungen
Podcast
Gesundheitspolitik
Praxis
Allerlei
Jobs
Fachgebiete
Allgemeinmedizin Anästhesiologie & Intensivmedizin Apotheke Augenheilkunde Chirurgie Dermatologie Gynäkologie und Geburtshilfe HNO Innere Medizin Kinder & Jugendheilkunde Neurologie & Psychiatrie Orthopädie & Unfallchirurgie Pflege Urologie Zahnmedizin
Subfächer Innere Medizin
Diabetologie Gastroenterologie Infektiologie Kardiologie Onkologie und Hämatologie Pneumologie Rheumatologie
Fortbildungen
Überblick Fortbildungen DFP-Literaturstudium-Artikel DFP-Webcast Fortbildungen DFP-Podcasts
Erweiterte Suche
Anmelden
nach oben
memo - Magazine of European Medical Oncology
Erschienen in:

01.09.2013 | review

Personalized medicine for breast cancer: dream or reality?

verfasst von: Lina Pugliano, Dimitrios Zardavas, Martine Piccart, MD

Erschienen in: memo - Magazine of European Medical Oncology | Ausgabe 3/2013

Einloggen, um Zugang zu erhalten

Abstract

The National Cancer Institute of the United States defines personalized medicine (PM) as “a form of medicine that uses information about a person’s genes, proteins and environment to prevent, diagnose and treat disease” (National Cancer Institute, Dictionary of Cancer Terms) [1]. Consequently, the ultimate dream is the generation of a “molecular fingerprint” via a simple blood test or tumor sample that allows the physician to refine an individual patient’s prognosis, select the best possible therapeutic option, and minimize the toxicity from therapies by identification of distinct genetic markers. The enormous gains to patients and ultimately health care systems are unmistakable.
Vorheriger Artikel Focus on gastrointestinal tumors
Nächster Artikel ASH Annual Meeting 2012—Chronic Myeloid Leukemia Update
Literatur
1.
National Cancer Institute. Dictionary of Cancer Terms.
2.
World Health Organization GLOBCAN. Cancer incidence, mortality and prevalence worldwide in 2008.
3.
O’Shaughnessy J Extending survival with chemotherapy in metastatic breast cancer. Oncologist. 2005;10(Suppl. 3):20–90.
4.
Balmaña J, Díez O, Rubio IT, Cardoso F EGWG BRCA 2 breast cancer. ESMO clinical practice guidelines. Ann Oncol. 2011;22:vi3–4.
5.
Sotiriou C, Pusztai L. Gene-expression signatures in breast cancer. N Engl J Med. 2009;360:790–800.PubMedCrossRef
6.
Reis-Filho JS, Weigelt B, Fumagalli D, Sotiriou C. Molecular profiling: moving away from tumor philately. Sci Transl Med. 2010;2:47ps43.
7.
Wirapati P, et al. Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures. Breast Cancer Res. 2008;10:R65.CrossRef
8.
Cuzick J, Sestak I, Ferree S, Cowens JW, Dowsett M. Prediction of late breast cancer recurrence by the ROR (PAM50) score in postmenopausal women in the TransATAC cohort. Ann Oncol. 2012;23:Abstr. 1201.
9.
Dubsky P, Brase JC, Fisch K, Jakesz R, Singer CF, Greil R, Dietze O, Weber KE, Petry C, Kronenwett R, Rudas M, Knauer M, Gnant M, Filipits M. The EndoPredict score identifies late distant metastases in ER+/HER2– breast cancer patients. Cancer Res. 2012;72:Abstr. S4–3.
10.
Sgroi DC, Sestak I, Cuzick J, Zhang Y, Schnabel CA, Erlander MG, Goss PE, Dowsett M. Comparative Performance of Breast Cancer Index (BCI) vs. Oncotype Dx and IHC4 in the Prediction of Late Recurrence in Hormonal Receptor-Positive Lymph Node-Negative Breast Cancer Patients: a TransATAC Study. Cancer Res. 2012;72:Abstr. S1–9.
11.
Gnant M, Filipits M, Dubsky P, Rudas M, Balic M, Greil R, Ferree S, Cowens JW, Schaper C, NT Predicting risk for late metastasis: the PAM50 risk of recurrence (ROR) score after 5 years of endocrine therapy in postmenopausal women with HR+ early breast cancer: a study on 1,478 patients from the ABCSG-8 trial. Ann Oncol. 2013;24:Abstr. 530_PR.
12.
Sestak I, Dowsett M, Sgroi D, Erlander M, Ferree S, Cowens J, Cuzick J. Comparison of five different scores for the prediction of late recirrence for oestrogen receptor-positive breast cancer. Ann Oncol. 2013;24:Abstr. 540_PR.
13.
Cardoso F, et al. Clinical application of the 70-gene profile: the MINDACT trial. J Clin Oncol. 2008;26:729–35.PubMedCrossRef
14.
Sparano JA, Paik S. Development of the 21-gene assay and its application in clinical practice and clinical trials. J Clin Oncol. 2008;26:721–28.PubMedCrossRef
15.
Ma X-J, Dahiya S, Richardson E, Erlander M, Sgroi DC. Gene expression profiling of the tumor microenvironment during breast cancer progression. Breast Cancer Res. 2009;11:R7.
16.
Desmedt C, et al. Biological processes associated with breast cancer clinical outcome depend on the molecular subtypes. Clin Cancer Res. 2008;14:5158–65.PubMedCrossRef
17.
Iwamoto T, et al. Gene pathways associated with prognosis and chemotherapy sensitivity in molecular subtypes of breast cancer. J Natl Cancer Inst. 2011;103:264–72.PubMedCrossRef
18.
Albain KS, et al. Prognostic and predictive value of the 21-gene recurrence score assay in postmenopausal women with node-positive, oestrogen-receptor-positive breast cancer on chemotherapy: a retrospective analysis of a randomised trial. Lancet Oncol. 2010;11:55–65.PubMedCrossRef
19.
Desmedt C, et al. Multifactorial approach to predicting resistance to anthracyclines. J Clin Oncol. 2011;29:1578–86.PubMedCrossRef
20.
Symmans WF, et al. Genomic index of sensitivity to endocrine therapy for breast cancer. J Clin Oncol. 2010;28:4111–9.PubMedCrossRef
21.
Juul N, et al. Assessment of an RNA interference screen-derived mitotic and ceramide pathway metagene as a predictor of response to neoadjuvant paclitaxel for primary triple-negative breast cancer: a retrospective analysis of five clinical trials. Lancet Oncol. 2010;11:358–65.PubMedCrossRef
22.
Barretina J, et al. The cancer cell line encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature. 2012;483:603–7.PubMedCrossRef
23.
Garnett MJ, et al. Systematic identification of genomic markers of drug sensitivity in cancer cells. Nature. 2012;483:570–5.PubMedCrossRef
24.
Frueh FW, et al. Pharmacogenomic biomarker information in drug labels approved by the United States food and drug administration: prevalence of related drug use. Pharmacotherapy. 2008;28:992–8.PubMedCrossRef
25.
Nowell SA, et al. Association of genetic variation in tamoxifen-metabolizing enzymes with overall survival and recurrence of disease in breast cancer patients. Breast Cancer Res Treat. 2005;91:249–58.PubMedCrossRef
26.
Okishiro M, et al. Genetic polymorphisms of CYP2D6 10 and CYP2C19 2, 3 are not associated with prognosis, endometrial thickness, or bone mineral density in Japanese breast cancer patients treated with adjuvant tamoxifen. Cancer. 2009;115:952–61.PubMedCrossRef
27.
Schroth W, et al. Association between CYP2D6 polymorphisms and outcomes among women with early stage breast cancer treated with tamoxifen. JAMA. 2009;302:1429–36.PubMedCrossRef
28.
Goetz MP, et al. CYP2D6 metabolism and patient outcome in the Austrian Breast and Colorectal Cancer Study Group trial (ABCSG) 8. Clin Cancer Res. 2013;19:500–7.PubMedCrossRef
29.
Braun S, et al. A pooled analysis of bone marrow micrometastasis in breast cancer. N Engl J Med. 2005;353:793–802.PubMedCrossRef
30.
Cote R, Giuliano AE, Hawes D, Ballman KV, Whitworth PW, Blumencranz PW, Reintgen DS, Morrow M, Leitch AM, Hunt K. ACOSOG Z0010: a multicenter prognostic study of sentinel node (SN) and bone marrow (BM) micrometastases in women with clinical T1/T2 N0 M0 breast cancer. J Clin Oncol. 2010;28:Abstr. CRA504.
31.
Janni W, et al. Persistence of disseminated tumor cells in the bone marrow of breast cancer patients predicts increased risk for relapse—a European pooled analysis. Clin Cancer Res. 2011;17:2967–76.PubMedCrossRef
32.
Cristofanilli M, et al. Circulating tumor cells, disease progression, and survival in metastatic breast cancer. N Engl J Med. 2004;351:781–91.PubMedCrossRef
33.
Pierga J-Y, et al. High independent prognostic and predictive value of circulating tumor cells compared with serum tumor markers in a large prospective trial in first-line chemotherapy for metastatic breast cancer patients. Ann Oncol. 2012;23:618–24.PubMedCrossRef
34.
Budd GT, et al. Circulating tumor cells versus imaging–predicting overall survival in metastatic breast cancer. Clin Cancer Res. 2006;12:6403–9.PubMedCrossRef
35.
De Giorgi U et al Circulating tumor cells and [18F]fluorodeoxyglucose positron emission tomography/computed tomography for outcome prediction in metastatic breast cancer. J Clin Oncol. 2009;27:3303–11.PubMedCrossRef
36.
Liu MC, et al. Circulating tumor cells: a useful predictor of treatment efficacy in metastatic breast cancer. J Clin Oncol. 2009;27:5153–9.PubMedCrossRef
37.
Bidard F-C, et al. Single circulating tumor cell detection and overall survival in nonmetastatic breast cancer. Ann Oncol. 2010;21:729–33.PubMedCrossRef
38.
Rack B, Schindlbeck C, Andergassen U, Lorenz R, Zwingers T, Schneeweiss A, Lichtenegger W, Beckmann M, Sommer H, Pantel K, Friese K, Janni W. Prognostic relevance of circulating tumor cells in the peripheral blood of primary breast cancer patients. San Antonio Breast Cancer Conference. 2010:Abstr. S6–5.
39.
Pierga J-Y, et al. Circulating tumor cell detection predicts early metastatic relapse after neoadjuvant chemotherapy in large operable and locally advanced breast cancer in a phase II randomized trial. Clin Cancer Res. 2008;14:7004–10.PubMedCrossRef
40.
Riethdorf S, et al. Detection and HER2 expression of circulating tumor cells: prospective monitoring in breast cancer patients treated in the neoadjuvant GeparQuattro trial. Clin Cancer Res. 2010;16:2634–45.PubMedCrossRef
41.
Hanash SM, Baik CS, Kallioniemi O. Emerging molecular biomarkers–blood-based strategies to detect and monitor cancer. Nat Rev Clin Oncol. 2011;8:142–50.PubMedCrossRef
42.
McBride DJ, et al. Use of cancer-specific genomic rearrangements to quantify disease burden in plasma from patients with solid tumors. Genes chromosome cancer. 2010;49:1062–9.
43.
Leary RJ, et al Development of personalized tumor biomarkers using massively parallel sequencing. Sci Translational Med. 2010;2:20ra14.
44.
Zardavas D, Baselga J, Piccart M. Emerging targeted agents in metastatic breast cancer. Nat Rev Clin Oncol. 2013;10:191–210.PubMedCrossRef
45.
Bates SE, Amiri-Kordestani L, Giaccone G. Drug development: portals of discovery. Clin Cancer Res. 2012;18:23–32.PubMedCrossRef
46.
O’Shaughnessy J, Schwartzberg LS, Danso MA, et al. A randomized phase III study of iniparib (BSI-201) in combination with gemcitabine/carboplatin (G/C) in metastatic triple-negative breast cancer (TNBC). J Clin Oncol. 2011;29:Abstr. 1007, presented data—ASCO Annual Meeting 2011.
47.
Verdine GL, Walensky LD. The challenge of drugging undruggable targets in cancer: lessons learned from targeting BCL-2 family members. Clin Cancer Res. 2007;13:7264–70.PubMedCrossRef
48.
Yee D. Insulin-like growth factor receptor inhibitors: baby or the bathwater? J Natl Cancer Inst. 2012;104:975–81.PubMedCrossRef
49.
De Palma M, Hanahan D. The biology of personalized cancer medicine: facing individual complexities underlying hallmark capabilities. Mol Oncol. 2012;6:111–27.PubMedCrossRef
50.
Buyse M, Sargent DJ, Grothey A, Matheson A, De Gramont A. Biomarkers and surrogate end points—the challenge of statistical validation. Nat Rev Clin Oncol. 2010;7:309–17.PubMedCrossRef
51.
Graham ID, Logan J, Harrison MB, Straus SE, Tetroe J, Caswell W, Robinson N. Lost in knowledge translation: time for a map? J Contin Educ Health Prof. 2006;26:13–24.PubMedCrossRef
52.
Sung NS, et al. Central challenges facing the national clinical research enterprise. JAMA. 2003;289:1278–87.PubMedCrossRef
53.
Westfall J, Mold J, Fagnan L. Practiced-based-research—“Blue Highways” on the NIH roadmap. JAMA. 2007;297:403–6.PubMedCrossRef
54.
DiMasi JA, Grabowski HG. Economics of new oncology drug development. J Clin Oncol. 2007;25:209–16.PubMedCrossRef
55.
Gianni L, et al. Efficacy and safety of neoadjuvant pertuzumab and trastuzumab in women with locally advanced, inflammatory, or early HER2-positive breast cancer (NeoSphere): a randomised multicentre, open-label, phase 2 trial. Lancet Oncol. 2012;13:25–32.PubMedCrossRef
56.
Baselga J, et al. Pertuzumab plus trastuzumab plus docetaxel for metastatic breast cancer. N Engl J Med. 2012;366:109–19.PubMedCrossRef
57.
Beyond the pill. The economist. 2007;October 25.
58.
Melese T, Lin SM, Chang JL, Cohen NH. Open innovation networks between academia and industry: an imperative for breakthrough therapies. Nat Med. 2009;15:502–7.PubMedCrossRef
59.
Pugliano L, Fumagalli D, Irrthum A, Schenk B, Saini KS, Dolci SM, Arahmani A, Piccart MJ, Bucur A. Integrate: a new model in collaborative breast cancer research. Advanced Breast Cancer Conference 1. 2011:Poster PO43.
60.
Oestreicher N, et al. Gene expression profiling and breast cancer care: what are the potential benefits and policy implications? Genet Med. 2005;7:380–9.PubMedCrossRef
61.
Hornberger J, Cosler LE, Lyman GH. Economic analysis of targeting chemotherapy using a 21-gene RT-PCR assay in lymph-node-negative, estrogen-receptor-positive, early-stage breast cancer. Am J Manag Care. 2005;11:313–24.PubMed
62.
Lo SS, et al. Prospective multicenter study of the impact of the 21-gene recurrence score assay on medical oncologist and patient adjuvant breast cancer treatment selection. J Clin Oncol. 2010;28:1671–6.PubMedCrossRef
63.
Finak G, et al. Stromal gene expression predicts clinical outcome in breast cancer. Nat Med. 2008;14:518–27.PubMedCrossRef
64.
Desmedt C, et al. Characterization and clinical evaluation of CD10+ stroma cells in the breast cancer microenvironment. Clin Cancer Res. 2012;18:1004–14.PubMedCrossRef
65.
Teschendorff AE, Miremadi A, Pinder SE, Ellis IO, Caldas C. An immune response gene expression module identifies a good prognosis subtype in estrogen receptor negative breast cancer. Genome Biol. 2007;8:R157.CrossRef
66.
Yau C, et al. A multigene predictor of metastatic outcome in early stage hormone receptor-negative and triple-negative breast cancer. Breast Cancer Res. 2010;12:R85.
67.
Liedtke C, et al. Response to neoadjuvant therapy and long-term survival in patients with triple-negative breast cancer. J Clin Oncol. 2008;26:1275–81.PubMedCrossRef
68.
Chang J, et al. Apoptosis and proliferation as predictors of chemotherapy response in patients with breast carcinoma. Cancer. 2000;89:2145–52.PubMedCrossRef
69.
Gámez C, Flamen P, Holmes E, Robles J, Gebhart G, Di Cosimo S, Eidtmann H, Piccart-Gebhart M, Baselga J, de Azambuja E, Team, on behalf of the N.-A. S. FDG-PET/CT for Early Prediction of Response to Neoadjuvant Lapatinib, Trastuzumab, and their Combination in HER2 Positive Breast Cancer Patients: The Neo-ALTTO PET Study Results. European Society for Medical Oncology Annual Meeting. 2011:Abstr. S–S013.
70.
Tice JA, Cummings SR, Ziv E, Kerlikowske K. Mammographic breast density and the Gail model for breast cancer risk prediction in a screening population. Breast Cancer Res Treat. 2005;94:115–22.PubMedCrossRef
71.
Gnant M, Baselga J, Rugo HS, Noguchi S, Pritchard KI, Burris HA, Piccart-Gebhart MJ, Hart LL, Eakle JF, Mukai H, Iwata H, El-Hashimy M, Rao S, Taran T, Sahmoud T, Lebwohl DE, Hortobagyi GN. Effects of everolimus (EVE) on disease progression in bone and bone markers (BM) in patients (pts) with bone metastases (mets). J Clin Oncol. 2012;30:Abstr. 512.
72.
Geisler J, Haynes B, Anker G, Dowsett M, Lønning PE. Influence of letrozole and anastrozole on total body aromatization and plasma estrogen levels in postmenopausal breast cancer patients evaluated in a randomized, cross-over study. J Clin Oncol. 2002;20:751–7.PubMedCrossRef
Metadaten
Titel
Personalized medicine for breast cancer: dream or reality?
verfasst von
Lina Pugliano
Dimitrios Zardavas
Martine Piccart, MD
Publikationsdatum
01.09.2013
Verlag
Springer Vienna
Erschienen in
memo - Magazine of European Medical Oncology / Ausgabe 3/2013
Print ISSN: 1865-5041
Elektronische ISSN: 1865-5076
DOI
https://doi.org/10.1007/s12254-013-0104-x

Weitere Artikel der Ausgabe 3/2013

Radiofrequency ablation in gastrointestinal cancer: obstacles and goals

  • short review

Philadelphia-negative myeloproliferative neoplasms at the 2012 ASH meeting: a personal summary

  • short review

Controversial issues in the therapy of oesophageal carcinoma

  • short review

Acute myeloid leukemia: highlights from the 54th ASH meeting held in Atlanta, Georgia

  • short review

ASH 2012 update chronic lymphocytic leukemia—the best is yet to come

  • short review

Molecular therapies of colorectal cancer: where will we go from here?

  • short review