Expression profiles for prognosis and prediction Laura J. Van ‘t Veer The Netherlands Cancer Institute, Amsterdam.

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Presentation transcript:

Expression profiles for prognosis and prediction Laura J. Van ‘t Veer The Netherlands Cancer Institute, Amsterdam

Breast Cancer - Survival premenopausal patients, lymph node negative time (years) survival ~30% die of breast cancer ~70% survive breast cancer Kaplan-Meier Survival Curves 1) Who to treat 2) How to treat

61 y-old, fit, postmenopausal Node negative pT = 0.9 cm ductal cancer ER and PR negative HER2 negative Grade 2 HOW SHOULD ONE TREAT A SMALL (<1CM) BREAST TUMOR ? FA(E)C x 6 % Choices of 40 experts worldwide Courtesy of Martine Piccart

Gene expression profiling to improve prediction of clinical outcome aim -to identify patients at risk to develop distant metastases and die of cancer -to accurately select for adjuvant therapy -to predict treatment response

Cy3-dUTP green fluorescent reverse transcriptase, T7 RNA polymerase Cy5-dUTP red fluorescent cRNA sample 2 (reference) RNA cDNA sample 1 (tumor tissue) RNA cDNA cRNA RNA extraction and labeling to determine expression level sample of interest compared to standard reference

Scanned image of flexjet 25K human oligonucleotide microarray Hybridized with mixture of ‘red’- labeled cRNA of a tumor sample and ‘green’-labeled reference cRNA (pool of tumor samples) Determine: fluorescence intensities fluorescence ratio’s

2010: Outcome for Prognosis Micro-array Treatment 2 Prognosis poor Treatment 1 Treatment 3 Classifier Tumor

Response for treatment 1 Micro-array Treatment 2 Prognosis poor Treatment 1 resistant Treatment 3 Classifier Tumor

Micro-array Treatment 2 sensitive Prognosis poor Treatment 1 resistant Treatment 3 Response for treatment 2 Classifier Tumor

Response for treatment 3 Tumor Micro-array Classifier Treatment 2 sensitive Prognosis poor Treatment 1 resistant Treatment 3 sensitive

78 breast tumors (‘83-’94) patients < 55 years tumor size < 5 cm lymph node negative (LN0) no adjuvant therapy no distant metastases in at least 5 years (n=44) distant metastases < 5 years (n=34) Prognosis Reporter Genes Who to treat? Retrospective series – Tissuebank No adjuvant treatment

Classification Prognosis 78 tumors good signature poor signature threshold threshold set with 10% false negatives 91 % sensitivity, 73% specificity metastases (white = +) 70 significant prognosis genes Nature 415, p , 2002

Breast Cancer - Metastases risk by profiling time (years) 151 patients, <53, LN0 10 year survival curve Distinguish in: 40% good profile, 60% poor profile metastases-free good profile: ~13% develop metastases ~87% disease-free poor profile: ~56% develop metastases ~44% disease-free

Implementation of Profiling Breast cancer patients, lymph node negative: ~20-30% reduction of unnecessary treatment and avoidance of 2-3% undertreatment Who to treat

70 genes Prospective NKI - Raster trial - work in progress Good signature Low risk Poor signature High risk accrual 75 patients microarray 40 patients 24 low, 16 high risk

- biopsy of primary tumor - upfront chemotherapy - response of primary tumor by imaging determine therapy response profiles in biospy How to treat Neo-adjuvant trials

Chang et al, Lancet 2003 Neo-adjuvant docetaxol response 92 differentially expressed genes differentiate sensitive and Resistant breast tumors. Confirmed in ‘6’ sensitive tumors

identification of predictive factors to neoadjuvant chemotherapy using gene expression profiling comparison of two different drug combinations: –AC (adriamycine/cyclophosphamide) –AD (adriamycine/docetaxel) Neo-adjuvant response profile NKI/AVL study locally advanced breast cancer S. Rodenhuis, M. van de Vijver

Why these drugs ? standard drug combination for neoadjuvant chemotherapy: AC –but: resistance against anthracyclines can exist or develop under primary therapy good responses observed with docetaxel containing combinations –high activity also in anthracycline-resistant disease –but: very toxic agent

Study design (NOODCD) prospective phase III trial within the NKI/AvL

Patients included first 62 patients included into the study enough RNA obtained from 49 patients: –  50% tumour cells –46 biopsies, 18 tumours

Patients response CR: complete remission PR: partial remission MR: minor remission SD: stable disease PD: progressive disease

Interim Conclusions NOODCD Thus far, no major differences in gene expression between tumours from patients with a CR compared to all other patients –(work in progress) significant differences in gene expression in tumour specimens before and after treatment

Neo-adjuvant or Metastatic response relevant for Adjuvant? Are gene activities similar or different when comparing the primary tumor and metastasis

Expression profiling of matched pairs Primary tumors – lymph node metastases Primary tumors – distant metastases microarrays

ER-  positive ER-  negative 15 primary breast tumors and lymph node metastases of the same patient Hierarchical clustering Primary breast tumors – lymph node metastases

Hierarchical clustering Primary breast tumors – distant metastases 8 primary breast tumors and distant metastases of the same patient

How to treat Neo-adjuvant therapy response profiles similarity of primary/metastasis profile implies: therapy recommendations based on expression profile of the primary tumor are a rational approach towards preventing the outgrowth of micrometastases - biopsy of primary tumor profiled - upfront chemotherapy - response of primary tumor by imaging

Who to treat: Prognosis profile as diagnostic tool -> improvement of accurate selection for adjuvant therapy (less under- and overtreatment) Prognosis profile implemented in clinical trials -> reduction in number of patients & costs (select only patients that are at metastases risk) Therapeutic implications How to treat: Predictive profile for drug response -> selection of patients who benefit