1. microRNA and lung cancer Gabriella Sozzi

2. Lung Cancer Screening by LDCT : critical issues Recent clinical trials results (DANTE, 2009, DLCST, 2012, MILD 2012; ~10.000 subjects overall; NLST 2011,53.454 persons), indicate that LDCT screening in high risk subjects may reduce lung cancer mortality. The high false positive rates of LDCT, leading to multiple screening rounds, over-diagnosis, unnecessary (harmful?)diagnostic follow –up and costs underscore the need for non-invasive complementary biomarkers for standardized use.

3. Sources of blood-based biomarkers. Novel promising biomarkers are generated by cancer cells, tumor microenvironment, the host response and their dynamic interaction. Novel promising biomarkers are generated by cancer cells, tumor microenvironment, the host response and their dynamic interaction.

4. Microsatellite changes, KRAS and p53 mutation in case- control series (Sozzi G. Cancer Research 1999; Andriani F. IJC 2004) Methylation markers plasma samples in case-control series (Bearzatto A. Clin Cancer Res. 2002 ) Circulating plasma DNA (hTERT) quantification in case- control series and in pilot INT-IEO and MILD screening trial (Sozzi G., Can Res 2001; Sozzi G., J Clin Oncol. 2003; Sozzi G., AJRCCM 2009; Roz L. Lung Cancer 2009) Highthroughput microRNAs expression profiles in plasma samples in independent screening trials (INT-IEO, MILD) (Boeri M. et al., PNAS 2011; Sozzi G. Cell Cycle 2011; Boeri M. et al., Cancer J 2012) Plasma biomarkers studies at INT (Milan)

5. mRNA One miRNA mRNA … small noncoding RNAs that regulate gene expression by binding complementary sequences of target mRNAs and inducing their degradation or translational repression Evolutionary conserved One miRNA has multiple targets microRNA: a new class of biomarkers

6. microRNA : plasma/serum-based biomarkers for cancer detection? Blood-based miRNA studies are in their infancy miRNA remain rather intact and stable in plasma/serum Simple universally applicable assay for quantification (i.e. qRT-PCR) In lung cancer plasma/serum levels of miRNAs might have diagnostic (Silva J, ERJ. 2010; Shen J, Lab Invest. 2010; Foss KM, J TO 2011; Hennessey PT, PLoS One 2012) and prognostic value (Hu et al., JCO, 2010). miRNAs have been found packaged in exosomes derived from multivesicular bodies (7) or be exported in the presence of RNA- binding proteins (i.e. Ago-2)(8) or might be exported microvesicles shed during membrane blebbing (9). Once in the extracellular space, these miRNAs could be taken up by other cells, degraded by RNases, or excreted(10).

8. microRNA in LUNG TISSUE SAMPLES TUMOUR TISSUES NORMAL TISSUES

9. microRNA in PLASMA SAMPLES 1196ALIVE 40 samples (19 patients) DEAD824 At disease 1y before 2y beforeenrollment TAC- TAC+ CONTROLS 5 POOLS (28 individuals) CONTROLS 5 POOLS (28 individuals) Training Set (INT- IEO trial) CONTROLS 10 POOLS (54 individuals) CONTROLS 10 POOLS (54 individuals) 1377ALIVE 34 samples (22 patients) DEAD322 At disease1y before 2y beforeenrollment TAC- TAC+ Validation Set (MILD trial)

10. ANALYSIS ON PLASMA SAMPLES NORMALIZATION ISSUE TaqMan® Array Human MicroRNA Cards Megaplex™ : 378 microRNAs per sample NORMALIZATION ON THE MEAN OF EACH CARD TRAINING SET TECHNICAL VALIDATION (training set) & VALIDATION SET TaqMan® MicroRNA Assays Multiplex™ O nly on miRNA of interest TO BYPASS NORMALIZATION ISSUE (no plasma housekeeping miRNA): analysis of miRNAs RATIOS RECIPROCAL RATIOS AMONG miRNAs

11. Risk 10 Diagnosis 9 4 1 1 Risk Aggressive disease (RAD) Diagnosis Aggressive disease (PAD) 2 2 6 6 miRNA and miRNA ratios distribution and discrimination power in the analyses miRNA RATIOS miRNA Risk Diagnosis Risk Aggressive disease (RAD) Diagnosis Aggressive disease (PAD) 3 2 2 2 1 1 1 1 2 1 3 2

12. ANALYSIS OF miRNA RATIOS in plasma Technical Validation Multiplex™ Validation Set Multiplex™ Filter for Ratios with a minimal intra-pool variability Training Set TaqMan® Array Human MicroRNA Cards Megaplex™ 24 microRNAs ANALYSIS OF miRNA RATIOS

13. AUC=0.85 p<0.0001 RISK OF LUNG CANCER 1-2 YEARS BEFORE CT RISK OF AGGRESSIVE LUNG CANCER (RAD) Time (months) p=0.0006 Sample size25 Patients15 Controls10 Sample size37 RAD+17 RAD-20 DIAGNOSIS OF LUNG CANCER AUC=0.88 p<0.0001 Sample size26 Patients16 Controls10 p=0.0001 Time (months) Sample size31 PAD+13 PAD-18 DIAGNOSIS OF AGGRESSIVE LUNG CANCER (PAD)

14. CONTROLS 100 disease free individuals CONTROLS 100 disease free individuals 40 194Alive 51 PATIENTS Dead871 At disease1-2y before >2y beforeenrollment TAC- TAC+ 24 microRNA signatures: extended Validation Set (MILD trial) using custom-made microfluidic card mir-16, mir-17, mir-21, mir-101, mir-126, mir-145, mir-197, mir-221, mir-320, mir-451, mir-660, mir-106a, mir-133a, mir-140-3p, mir-140-5p, mir-142-3p, mir-148a, mir-15b, mir-19b, mir-28-3p, mir-30b, mir-30c, mir-486-5p and mir- 92a. AUC = 0.89 RISK AUC = 0.97 RISK of AGGRESSIVE DISEASE AUC = 0.92 AUC = 0.93 PRESENCE of AGGRESSIVE DISEASE PRESENCE of DISEASE

15. Performance of the miRNA signatures in plasma samples collected pre-disease, at the time of disease detection, and after surgery (disease-free) from 19 patients.

16. 1000 controls (no disease) 130 samples (13%): haemolyzed 872 controls suitable for analyses: 594 LDCT arm; 286 observational arm 85 lung cancer patients 9 patients (11%) : samples not available 7 patients (9%): haemolyzed samples 69 Lung Cancer patients: 44 at cancer diagnosis, 54 before diagnosis, 19 post- surgery Study Design & Aims  Diagnostic performance of miRNA test for lung cancer detection across LDCT and observational arms  Combination of LDCT and plasma miRNA test  Prognostic value of the miRNA assay

17. bioMILD prospective trial 4,000 smokers ≥ 50 anni Grants from AIRC and MoH

18. bioMILD - 2011 biomarker-based prospective study validate miRNA profile combination of CT e miRNA CT dose according to risk Biology-based therapy Pharmacologic prevention

19. ci servono 4000 volontari www.biomild.org

20. TUMOR GENOMICS UNIT Mattia Boeri Carla Verri Davide Conte Mavis Mensah Luca Roz Federica Facchinetti Francesca Andriani Ohio State University Cancer Center, Columbus, OH, USA Carlo M. Croce UNIT of THORACIC SURGERY Paola Suatoni Ugo Pastorino Special Program “Innovative Tools for Cancer Risk Assessment and early Diagnosis”, 5X1000/5 per mille Supported by Italian Ministry of Heatlh Ricerca Finalizzata 20120