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1 How to improve the sensitivity of the multiplex detection of cancer biomarkers? Zhugen Yang a, Yann Chevolot a, Yasemin Ataman-Önal b, Geneviève Choquet-Kastylevsky b, Claude Lambert c, Eliane Souteyrand a and Emmanuelle Laurenceau a a Université de Lyon, Institut des Nanotechnologies de Lyon, UMR-CNRS 5270, Ecole Centrale de Lyon (France) b biomérieux, Département biomarqueurs, Marcy l Etoile (France) c Laboratoire d Immunologie clinique IFR143, CHU Saint-Etienne Hôpital Nord (France) 1

2 Context of the study Colorectal cancer is the third cancer worldwide with a survival rate ~ 56% Efficient decrease of mortality with mass-screening (FOBT) good specificity = 98% low sensitivity ~ 50-60% Antibody-based b d ifobt: sensitivity but specificity it Urgent need to develop blood-based assay for cancer biomarkers detection increase sensitivity and keep high specificity improve patient s compliance reduce mortality 2

3 Customized antibody microarray on 3D-microstructured Chip (Mazurczyk R et al. Sens Actuators B chem, 2008; 128(2): ) 559) 40 microwells Volume = 250 nl parallel screening of 40 biological samples or experimental conditions tiny sample requirement Detection antibody (concentration, label) Target cancer biomarker (protein, peptide, carbohydrate) Capture antibody (spotting buffer, probe concentration) ti Solid support (glass slide) Surface chemistry (fonctional groups, surface energy, composition) 3

4 Previous results (Yang Z. et al. Sens Actuators B chem, 2012; 175: 22-28) 5 Cancer biomarkers: CEA,,p p53, Hsp60, PDI, DefA6 6 surface chemistries: -COOH, -NHS / CMD, MAMVE, -NH 2 (APDMES) / Chitosan 3 spotting buffers: Acetate (ph 4.5), PBS (ph 7.4), Carbonate (ph 9.6) Optimization of capture antibody immobilization Spotting buffer: Carbonate (ph9.6) [capture Ab] = 10 µm Acetate (ph4.5) 4

5 Previous results (Yang Z. et al. Sens Actuators B chem, 2012; 175: 22-28) Optimization of biological recognition LOD Cut off=mean+3sd Tumor antigens Optimal surfaces LOD Dynamic range CEA MAMVE/CMD 10 pm 4.7 log/4.0 log HSP60 NHS/Chitosan/MAMVE 10 pm 47log/40log/47log 4.7 log/4.0 /4.7 PDI NHS 10 pm 4.7 log DEFA6 Chitosan 10 pm 4.7 log CA19-9 NHS/CMD 10 U/mL 3.0 log/3.0 log Selected surfaces: NHS MAMVE Chitosan 5

6 Spotting design and conditions Anti-CEA Anti-Hsp60 Anti-PDI Anti-DefA6 Anti-p53 B1=Acetate t % 05% PVA IgG-Cy3 in B1 Capture Ab in B1 IgG-Cy3 in B2 Capture Ab in B2 B2=Carbonate % PVA sera Detection Ab Capture Ab Blank = buffer (B1, B2) Positive control = purified cancer biomarker (10 nm) 2 healthy donors sera = N1, N2 (1/250) 4 CRC sera = CRC1, CRC2, CRC3, CRC4 (1/250) 6

7 Results : Proof of Concept buffer: white bar / 2 normal sera (red, pink bars) 4 colorectal cancer sera (blue, orange, green, yellow bars) purified antigen: black bar Detection of cancer biomarker significantly depends on surface chemistry 7

8 Conclusion CRC1 CEA Hsp60 PDI DefA6 p53 NHS Chitosan Chitosan NHS NHS CRC2 Chitosan NHS NHS CRC3 MAMVE NHS Chitosan NHS CRC4 Positive CRC sera 1/4 2/4 2/4 3/4 3/4 Detection of a single cancer biomarker display low sensitivity Multiplex detection of cancer biomarkers in optimal conditions (surface chemistry, [probe], spotting buffer) significantly increase the sensitivity 8

9 Perspectives Future work will focus on: enlarge patients cohorte to validate the number of cancer biomarkers to be detected integration of optimal chemistries on the same support to improve the accuracy of a cost-effective test compare antibody microarrays to Vidas determine reproducibility and linearity of the multiplex detection evaluate LOD, LOB, LOQ 9

10 Financial support: PhD fellowship BQR C NANO Rhône-Alpes Technical support: NANOLYON Plate-forme Acknowledgements Prof. T. Delair (Laboratoire des Matériaux Polymères et Biomatériaux) Zhugen Yang (PhD student) Dr. Yann Chevolot Dr. Eliane Souteyrand Dr. Thomas Géhin Dr. Claude Lambert Dr Yasemin Ataman-Önal Dr Geneviève Choquet-Kastylevsky 10

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