ETH Zurich – J ST Workshop on Medical Research 15 t h – 16 th of Sept ember 2008, ETH Zurich Session 3 Predict ive biomarker f or molecular t arget drugs- prot eomic and glycobiological approach Kazut o Nishio, MD PhD Depar t ment of Genome Biology Kinki University School of Medicine Dept Genome Biology
Biomarkers Def init ion Biomarkers are ‘ a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes , pathogenic processes , or pharmacologic responses to a therapeutic intervention ’. Biomarkers Definitions Working Group (2001) Clin. Pharmacol. Ther. 69, 89–95 Dept Genome Biology
The need f or bet t er predict ive markers The need f or bet t er predict ive markers The average response rate to dr ug t reat ment is not accept able. Slide: Paul Warning, Genent ech (modif ied)
分子標的薬 Molecular t arget t herapy Target : Molecules Dept Genome Biology
Oncology New Drug Approvals ( FDA ) 2001-2006 Chabner AACR 2006 Molecular Targeted Drug � 67 % ( 2015 ＞ 75% ) ( 27 % Patient Selection ) Non- Targeted Drug � 33% Dept Genome Biology
A p p r o v e d M o l T a r g e t D r u g s （ s m a l l m o l e c u l e s a n d a n t i b o d i e s ） D r u g s T a r g e t A p p l i c a t i o n F D A J a p a n * * R i t u x a n C D 2 0 B C L L 1 9 9 7 2 0 0 1 H e r c e p t i n H e r 2 * b r e a s t c a 1 9 9 8 2 0 0 1 * C G l e e v e c B c r - A b l / K i t M L , G I S T 2 0 0 1 2 0 0 1 I r e s s a E G F R * N S C L C 2 0 0 3 2 0 0 2 V e l c a d e P r o t e a s o m e M M 2 0 0 3 年 2 0 0 7 2 0 0 7 A v a s t i n V E G F C R C 2 0 0 4 2 0 0 8 E r b i t u x E G F R * C R C 2 0 0 4 a p p l i e d T a r c e v a E E G F R * N S C L C , p a n c c a 2 0 0 5 2 0 0 7 G F R N e x a v a r M u l t i - k i n a s e s * R C C 2 0 0 5 2 0 0 7 S u t e n t M u l t i - k i n a s e s * G I S T , R C C 2 0 0 6 a p p l i e d * C S p r y c e l B c r - A b l / S r c M L , P h + A L L 2 0 0 6 a p p l i e d * * k i n a s e i n h i b i t o r * k i n a s e i n h i b i t o r * * G l e e v e c - r e s i s t a n c e Dept Genome Biology
Biomarkers f or patient selection Compounds Target Tumors Diagnosis I H (Hercep t est ) Humanized ant i Overexpression of Herceptin HER2 Ab HER2 FI SH I H Chimeric ant i CD20 (+) B- cell non Rituxisan CD30 m- Ab Hodking lymphoma FCM Chromosomal t est 1. CML bcr- abl / c- Gleevec Gene analysis 2. GI ST wit h KI T kit - TKI （ D117 ） C +g I H I nvader assay Topo I NSCLC or ovarian ca. I rinotecan (UGT1A1gene inhibit or e. g. polymorphism)
New, more inf ormat ive t rial designs Approach: Pair diagnostic with therapeutic ● I dent if y r esponder s and non-r esponder s ● Pr event t oxicit y ● Monit or r esponse Answer ser ies of quest ions, e.g., ● Which dose is cor r ect f or which sub-populat ion? ● Which sub-populat ion should be t r eat ed?
Biomarker study f or target based drugs - Feasibility - Power f or prediction - Sensitivity - Accuracy : f alse positive e. g. Operative We f ocused on Biopsy Cytology PBMC (Blood) Serum (Blood) Plasma (Blood) Pleural ef f usion Dept Genome Biology
Search f or biomarkers Search f or biomarkers in surrogat e t issue in surrogat e t issue (circulat ing samples) (circulat ing samples) 1. EGFR somat ic mut at ion in circulat ing t umor cells in lung cancer 2. Gene expression prof ile in PBMC 3. Serum prot eomics 4. Mult iplex ELI SA using bio beads 5. Glycoprof iling
EGFR tyrosine kinase inhibitors (EGFR- - TKI s) TKI s) EGFR tyrosine kinase inhibitors (EGFR EGFR lig a nd lig a nd EGFR expression in NSCLC R R R R Squamous cell ca. Squamous cell ca. CM CM Small molecule kina se kina se kina se kina se Kinase Kinase Kinase Kinase tyrosine kinase inhibitors Gef itinib (I ressa) Erlotinib (Tarceva) P P Adenocarcinoma Adenocarcinoma Cell cycle Cell cycle Angiogenesis Angiogenesis progression progression Prolif eration Metast asis Prolif eration Metast asis Decreased Decreased apoptosis apoptosis Dept Genome Biology
EGFR mutation Del746-750 2235 20% G768I 1% Del746-750 2236 11% Exon 20 I ns 5% L861Q Mutati ons 1% T790M 1% G719X 4% L858R Mutati ons 39% EXON 19 EXON 18 EXON 20 EXON 21 EXON 22 EXON 23 EXON 24 Ot her Exon 19 del 13%. 2237_2251del15; 2237_2254del18; 2237_2255> T (complex); 2236_2250del15; 2238_2255del18; 2238_2248> GC (complex); 2238_2252> GCA (compl ex); 2239_2247del9; 2239_2253del15; 2239_2256del18; 2239_2248TTAAGAGAAG> C (complex) 2239_2258> CA (complex); 2240_2251del12; 2240_2257del18; 2240_2254del15; 2239_2251> C (complex); 2235_2252>AAT (complex)
Sensitivity of transf ected cells with deletional mutation to EGFR- TKI AG1478 gef itinib 1.2 1.2 1.0 Gr owth r ati o 1.0 Gr owth r ati o 0.8 0.8 0.6 0.6 0.4 0.4 0.2 0.2 0 .01 1 10 100 0 .1 0 .01 .1 1 10 100 0 ZD1839 (µM) AG1478 (µM) M W D M W D M W D M:293_pcDNA3. 1/ Zeo Det ect ion of pEGFR W:293_pcDNA3. 1/ EGFR wt (1068) D:293_pcDNA3. 1/ EGFR15d ZD1839 0 0.01 0.1 uM f or 3h Ar ao et al. Cancer Res ‘05 Dept Genome Biology
I mpact of EGFR mutation on the response to EGFR- TKI (N=616) Paez et al., Science 2004 100 77% Lynch et al.,NEJM 2004 Tumor response (%) 90 Pao et al.,PNAS 2004 Huang et al., CCR 2004 80 Tokumo et al., CCR 2005 70 Mitsudomi et al., JCO 2005 60 Han et al., JCO 2005 50 Kim et al., CCR 2005 EGFR 40 Cotes-Funes et al., Ann Mutation Oncol 2005 30 12% Cappuzzo et al, JNCI 2005 Chou et al., CCR 2005 20 EGFR Taron et al., CCR 2005 10 Takano et al., JCO 2005 Wild type Wild-type 0
Analysis of circulat ing DNA Dept Genome Biology
Detection of EGFR mutation by Scorpion- ARMS in serum samples OS PFS Mut at ion + Mut at ion + Mut at ion - Mut at ion - 100 100 P* = 0. 078 P* = 0. 005 80 80 Percent age Percent age + + + 60 60 40 40 + + + + + + 20 20 + 0 200 400 600 800 0 200 400 600 800 Progression Free Survival (Days) Overall Survival (Days) Dept Genome Biology
Search f or biomarkers Search f or biomarkers in surrogat e t issue in surrogat e t issue (circulat ing samples) (circulat ing samples) 1. EGFR somat ic mut at ion in circulat ing t umor cells in lung cancer 2. Gene expression prof ile in PBMC 3. Serum prot eomics 4. Mult iplex ELI SA using bio beads 5. Glycoprof iling
prot eomics using LC-MS/ MS prot eomics using LC-MS/ MS
I dentif ication of t arget proteins bind to EGFR- TKI Base- peak Chromatograms of Chemical Pulldown Samples RT: 0.00 - 90.02 NL: 68.33 4.63E7 1113.38 100 Base Peak Control_01 67.18 39.38 69.03 18.21 57.35 F: MS 1113.23 738.23 49.44 1113.46 842.56 836.12 Control_01 19.53 41.95 34.24 50 13.53 762.70 77.72 Control 25.63 842.54 971.30 877.76 4.56 523.64 81.78 85.53 1326.17 453.44 515.41 845.85 738.15 0 NL: 68.54 3.87E7 1113.34 100 Base Peak Control_02 39.50 64.35 19.35 F: MS 738.29 57.33 69.27 842.59 937.47 control_02 34.54 49.51 17.79 836.14 1113.58 50 42.02 22.08 877.72 762.67 715.12 31.41 77.65 4.89 12.19 971.27 81.70 85.49 743.49 745.14 1326.13 515.53 531.33 561.16 743.35 0 NL: 39.76 Relative Abundance 1.95E7 738.26 100 Base Peak Iressa_01 19.39 34.37 69.21 40.47 F: MS 17.58 65.24 842.53 877.72 57.56 1113.36 49.67 iressa_01 742.94 gerfitib 937.40 715.16 21.74 836.19 50 31.17 837.37 69.66 44.48 743.50 78.06 8.29 12.22 745.18 81.68 85.45 1113.52 746.73 971.23 (Iressa) 512.57 502.63 531.16 899.19 0 NL: 39.54 2.67E7 738.28 69.21 100 Base Peak Iressa_02 39.72 18.96 1113.37 57.48 F: MS 49.60 64.81 842.58 738.33 34.15 17.20 iressa_02 836.09 762.68 937.42 50 877.73 21.58 42.03 69.98 715.14 26.42 78.03 4.74 10.85 971.25 81.66 84.91 743.53 1113.52 690.69 971.37 515.49 561.11 531.46 743.44 0 NL: 68.78 2.46E7 1113.34 39.63 100 Base Peak erlotinib Tarceva_01 64.81 57.43 738.24 F: MS 17.81 937.44 836.14 19.88 34.17 49.53 tarceva_01 715.14 (Tarceva) 50 56.42 71.78 842.52 877.74 762.71 47.80 31.01 77.88 4.77 13.97 836.13 81.57 86.16 1064.80 745.15 762.42 971.17 515.44 523.58 845.88 836.29 0 NL: 39.44 68.55 1.88E7 738.27 1113.34 100 Base Peak Tarceva_02 40.07 34.02 17.25 49.26 56.93 64.50 69.06 F: MS 742.93 19.74 877.70 837.38 715.12 836.25 937.36 tarceva_02 1113.43 842.51 50 30.67 44.05 59.91 13.73 77.67 4.45 745.16 79.77 746.67 86.21 1022.21 523.55 971.24 515.43 1163.82 743.62 0 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 Time (min )
1 st line gef itinib monotherapy Proteomic approach to detect biomarkers to predict gef itinib- response f or advanced NSCLC LC- MS/ MS analysis of serum samples
PR vs. SD (Pre) PCA 1 2 2 2 2 7 -0.7 24 1 SD PR
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