The Cancer genome atlas (TCGA) and the search for a CUP genetic/epigenetic signature Manel Esteller, MD, PhD. Director, Josep Carreras Leukaemia Research Institute (IJC) Director, Cancer Epigenetics and Biology Program (PEBC) ICREA Research Professor Genetics Chairman, School of Medicine, University of Barcelona

2 years 35 >150 47 TCGA CUP project Sept 2018– Sept 2020 participating institutions >150 collaborators 47 paired CUP cases (N&T) Goal n=500 2 years Sept 2018– Sept 2020 TCGA CUP project

Project budget Cost to NCI is approximately: Tissue Acquisition: $500 per case, for a total of $250,000 Tissue Processing: $2000/per case, for a total cost of $1,000,000. Tissue Characterization: $5000/case, for a total of 2,500,000 Total Investment: $3,750,000$

TCGA CUP project Collate 500 paired CUP/normal samples with comprehensive clinical information to perform a multi-omic characterization Genomic Epigenomic Transcriptomic Clinical data Genomic Epi genomic Trans- criptomic

Material Transfer and Data Use Agreements Collaborators from America *samples are submitted directly to NCH MTA must be established between your institution and the Nationwide Children’s Hospital (NCH) at USA. Collaborators outside America The NCH does not require to sign a MTA with collaborator institutions that do not are sending samples directly to NCH. However, if your institution requires to establish an agreement or contract, our institution (IJC) will be glad to sign it.

TGCA CUPP collaborator institutions 1 2 3 4 15

Are you interested in becoming part of this multicentric world-wide TCGA project, providing CUP samples? Collaborator Hospitals & Institutions around the world Tumor Clinical data Frozen tissue (50 mg) FFPE block FFPE sections (10-20 sections, 10 um) + Normal Frozen blood (8-10 ml, EDTA tube) FFPE block (normal tissue) FFPE sections (10-20 sections, 10 um) PROSPECTIVE SAMPLES PROSPECTIVE & RETROSPECTIVE SAMPLES (RS) LAST OPTION *express shipping *risk of degradation

TGCA CUPP OUTCOME Expand our knowledge about the molecular mechanisms governing CUP development. Define the existence of different entities, now grouped as CUPs. Identify potential therapeutic targets that can be translated to the clinical practice.

DNA extraction Bioinformatic >250 ng Pre-anti-PD1 FFPE samples from NSCLC Fully clinically annotated Genome-wide DNA methylation profile: Illumina 850k array beadchip Methylation level in each CpG explored Duruisseaux et al., The Lancet Respiratory Medicine 2018

EPIMMUNE Positive NSCLC : Prediction of Response to Anti-PD1 Therapy EPIMMUNE + (N=10) EPIMMUNE + (N=10) EPIMMUNE – (N=24) EPIMMUNE – (N=24) Log-rank; P < 10-3 HR (95%CI)= 0.080 (0.017 – 0.373); P=0.001 Log-rank; P < 10-6 HR (95%CI)= 0.010 (3.29x10-4 – 0.0282); P=0.007 At risk:   EPIMMUNE 10 7 5 4 + 24 1 - At risk:   EPIMMUNE 10 8 7 + 24 11 5 - B PD-L1 positive CD8 high Log-rank; P= 0.004 HR (95%CI)= 0.330 (0.149 – 0.727); P=0.006 EPIMMUNE + (N=14) Mutational Load EPIMMUNE – (N=33) At risk:   EPIMMUNE 14 6 + 33 2 - Duruisseaux et al. The Lancet Respiratory Medicine 2018

EPIMMUNE-TCGA Positive NSCLC : Prediction of Response to Anti-PD1 Therapy B NSCLC Discovery Cohort (N=34) EPIMMUNE-TCGA signature NSCLC Discovery Cohort (N=34) EPIMMUNE-TCGA signature TCGA NSCLC cohorts (N=582) EPIMMUNE -TCGA signature Log-rank; P< 10-5 HR (95%CI)= 0.124 (0.043 - 0.356);P<0.001 Log-rank; P=0.019 HR (95%CI)= 0.293 (0.100 – 0.863);P=0.026 EPIMMUNE – (N=22) EPIMMUNE + (N=12) Log-rank; P=0.927 HR (95%CI)= 0.989 (0.587 – 1.665);P=0.967 EPIMMUNE + (N=12) EPIMMUNE + (N=110) EPIMMUNE – (N=22) EPIMMUNE – (N=472) At risk:   EPIMMUNE 12 10 7 5 4 + 22 1 - At risk:   EPIMMUNE 12 10 9 7 6 + 22 11 - At risk:   EPIMMUNE 110 74 71 70 + 472 300 282 280 279 - Duruisseaux et al. The Lancet Respiratory Medicine 2018

DNA Methylation Profiling Could Predict Clinical Response to PD1 Blockade in CUP-NSCLC

BENEFITS FOR COLLABORATORS Access to multi-omic data for CUP cases. Authorship in top high-impact publications (i.e. Nature, Science, Cell…)

mesteller@carrerasresearch.org