Mario Giuliano Trieste Novembre 2015

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Transcription:

Mario Giuliano Trieste 20-21 Novembre 2015

Metastatic Cascade Main Actors A small fraction of cells detaching from primary tumors end up forming metastatic lesions. 1 0 Tumor Circulating Tumor Cells (CTCs) Detected in patients at both early and advanced stage of disease Initiator of metastatic process, especially those with EMT and stem cell-like phenotype 1 CTCs Bone Marrow Distant Tissues Disseminated Tumor Cells (DTCs) Earliest detectable form of metastatic disease DTCs Bone marrow DTCs independent predictor of poor outcome 2 Persistence of DTCs after therapy associated with higher risk of relapse in BC patients 3 1. Aktas et al. BCR 2009 2. Braun et al. NEJM 2005 3. Janni et al. CCR 2011 Adapted from Pantel et al., Nat Rev Clin Oncol, 2009

Study of CTCs and DTCs in EBC Promise Analysis of CTCs and DTCs is the ideal tool to study the metastatic cascade in early breast cancer Challenges Low number of CTCs detected in a limited percentage of EBC patients 1 Limited numbers of DTCs isolated in bone marrow aspirates of standard volume 2 Impossibility to perform longitudinal study of DTCs due to limited access to bone marrow aspirates 1.Rack et al. JNCI 2014 2. Braun et al. NEJM 2005

Study of CTCs and DTCs in EBC Requisites Our strategy Patient-derived Xenografts (PdX) Higher numbers of cells Constant and renewable source of CTCs/DTCs Possibility to perform longitudinal studies to test treatment effect Possibility to analyze molecular phenotype of cells surviving to therapy Zhang et al. Cancer Res 2013

Study design Lungs Identification of lung metastases by IHC (Hematoxylin and eosin) RBC lysis Blood (500-700 ul) Peripheral blood nucleated cells Bones Bone marrow cells BM flushed from femur, tibia, hip Identification of CTCs/DTCs by immunostaining as human pan-ck+ and nuclear counter stain+ cells

CTCs/DTCs in PdX models Main findings Overall 18 PdX lines and a total of 81 mice were screened Detection rate in PdX lines CTCs DTCs 83% 62.5% Detection rate in mice 17% to 100% 20 to 100% Number of detected cells 1-91 (per 20 µl blood) 1 132 (per 2x10 6 nucleated cells)

CTCs and DTCs in PdX-bearing mice CTCs as isolated cells (mostly) CTC clusters in 6/18 PdX lines (33%) DTCs as isolated cells (mostly) BM micrometastases in 4/16 PdX lines (25%)

Lung metastases in PdX-bearing mice Lung metastases were detected in 9 of the 18 PdX lines screened

CTCs and metastatic potential All the PdX lines where CTCs were detected had also DTCs and/or lung metastases Strong correlation between CTCs and DTCs-positivity within the same mouse Fisher s exact test: P: 0.0047 Mice with DTCs+ Mice with DTCs - Mice with CTCs + 16 13 Mice with CTCs - 2 15 These results are consistent with what observed in early breast cancer patients (Fehm et al., BCR 2009)

CTC clusters and metastatic potential Significant correlation between CTC clusters and lung metastases PdX lines withctc clusters Pdx lines withoutctc clusters Fisher s exact test: P: 0.009 PdX lines withlung mets PdX lines without lung mets 6 0 3 9 Consistent results from the clinical settings support the role of CTC clusters in metastatic dissemination 1,2,3 1. Yu et al. Science 2013 2. Hou et al. JCO 2012 3. Kats-Ugurlu et al. J Pathol 2009

Gene signature associated with metastatic potential Gene expression profiling of primary tumors Signature associated with detection of CTC clusters (35 genes) Signature associated with detection of lung metastases (34 genes) Overlapped signature HLA-DP1A GJA1 PEG3 XIST

Clinical validation of the 4-Gene signature

Summary of findings PdX bearing mice can provide a constant and renewable source ofhuman CTCs and DTCs The presence of CTCs correlates with high metastatic potential CTCs clusters are strongly associated with lung metastases Our model represent a novel and promising experimental resource for studying metastatic process in breast cancer

Future strategies (I) Patient avatar of drug response What drugs or combinations of drugs can shrink primary tumors but also kill micrometastases

Future strategies (II) Molecular profiling of micrometastatic disease Laser capture microdissection Cell sorting using lineage markers (i.e. HLA, H2Kd) Genomic analysis

Future strategies (III) Development of in vitro metastatic niches In vitro culture +/- GFP+ reduction mammary fibroblasts (RMFs) in mammosphere conditions CK19 GFP 10 um 50 um Giuliano et al. AACR 2012

Future strategies (III) Development of in vitro metastatic niches CK19 GFP