Deploying the full transcriptome using RNA sequencing. Jo Vandesompele, CSO and co-founder The Non-Coding Genome May 12, 2016, Leuven

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1 Deploying the full transcriptome using RNA sequencing Jo Vandesompele, CSO and co-founder The Non-Coding Genome May 12, 2016, Leuven

2 Roadmap Biogazelle the power of RNA reasons to study non-coding RNA tech development and tools for ncrna sequencing reference transcriptome abundant small RNA depletion from biofluids functional annotation of long non-coding RNAs

3 Biogazelle research & development stage biotech company deploying the power of RNA for next generation diagnostics and therapeutics in the field of oncology internal R&D programs service / co-development for customers / partners focus on non-coding RNA focus on clinically relevant samples

4 RNA the movie DNA a picture

5 The power of RNA dynamic nature (time, location and condition specific) diverse different types: messenger, micro, long non-coding, transfer, ribosomal, etc. varying abundance levels: 1 copy/cell > 100,000 copies/cell structural differences: splicing, isoforms, fusion, mutations measurement technologies are ready (discovery - validation) same transcript can be biomarker and therapeutic target rational drug design

6 RNA is the new DNA Nature Reviews Genetics, 2016

7 microrna profiling in biofluids RNA equivalent of µl biofluid good reproducibility and sensitivity

8 Total RNA sequencing on FFPE excellent concordance with mrna capture sequencing good sensitivity for detecting differentially expressed lncrnas fo ld c ha ng e (lo g 2) a c c ord ing to m RNA c a p ture se q ue nc ing g e ne c o unt lncrna mrna fo ld c ha ng e (lo g 2) a c c ord ing to to ta l RNA se q ue nc ing 0 a ve ra g e d e te c te d d iffe re ntia lly e xp re sse d

9 Total RNA sequencing on FFPE excellent concordance with mrna capture sequencing good sensitivity for detecting differentially expressed lncrnas MYC lncrna AC tumor normal

10 Pioneers in the ncrna field 2010 mirna expression profiling (768) qpcr platform to measure 1718 lncrnas 2012 custom microarray 20,000 lncrnas EU FP7 SysKid & MIAMI, 1000 s samples today qpcr assays for entire LNCipedia Integrated DNA Technologies (IDT) will bring lncrna PrimeTime qpcr assays to the market total RNA and small RNA sequencing

11 Six reasons to look at the non-coding genome 1. Non-coding RNAs are master regulators of gene expression, in health and disease

12 Six reasons to look at the non-coding genome 1. Non-coding RNAs are master regulators of gene expression, in health and disease 2. Growing evidence for the potential of non-coding RNAs as excellent biomarkers % % mrna microrna lncrna

13 Six reasons to look at the non-coding genome 1. Non-coding RNAs are master regulators of gene expression, in health and disease 2. Growing evidence for the potential of non-coding RNAs as excellent biomarkers 3. Attractive intellectual property landscape

14 Six reasons to look at the non-coding genome 1. Non-coding RNAs are master regulators of gene expression, in health and disease 2. Growing evidence for the potential of non-coding RNAs as excellent biomarkers 3. Attractive intellectual property landscape 4. Tissue and disease specific non-coding RNA expression patterns

15 Six reasons to look at the non-coding genome 1. Non-coding RNAs are master regulators of gene expression, in health and disease 2. Growing evidence for the potential of non-coding RNAs as excellent biomarkers 3. Attractive intellectual property landscape 4. Tissue and disease specific non-coding RNA expression patterns 5. Increase the chances of finding robust biomarker signatures

16 Total RNA seq doubles the number of differentially expressed genes mrna pond total RNA pond

17 Total RNA sequencing identifies RNAs in circulation top 5 genes lnc-irs4-2 lnc-tpte-3 lnc-tmem132c-11 lnc-linc lnc-lrr1-1 Biogazelle collaboration with Illumina to optimize workflows on liquid biopsies

18 Six reasons to look at the non-coding genome 1. Non-coding RNAs are master regulators of gene expression, in health and disease 2. Growing evidence for the potential of non-coding RNAs as excellent biomarkers 3. Attractive intellectual property landscape 4. Tissue and disease specific non-coding RNA expression patterns 5. Increase the chances of finding robust biomarker signatures 6. Excellent therapeutic targets for RNA-targeting therapies

19 Leucci et al., Nature, 2016 only expressed in malignant melanoma, not in melanocytes nor any other cell type antisense mediated knockdown kills melanoma cells in vitro and in vivo important role in mitochondrial biogenesis

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21 Unified reference transcriptome for transcript annotation mrna small ncrna lncrna pseudogenes lncrna

22 Unified reference transcriptome for transcript annotation remove redundant gene models for accurate gene/transcript level quantification deal with noisy data sources (e.g. intron-retention transcripts from NONCODE) maintain links to both Ensembl and LNCipedia result is a unique and rich annotation resource

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24 Murine serum samples phase I Good quality data but very low abundance of mirna reads

25 Murine serum samples phase I On average only 169 mirnas detected Most reads are consumed by trnas

26 trna fragment depletion (phase II) 11 biotin-labeled DNA probes designed based on most abundant sequences of phase I samples (trna-glu, trna-gly, trna-his) Good quality data and higher mirna fraction

27 trna fragment depletion (phase II) trnas (trna-glu, trna-gly, trna-his) successfully removed On average 450 mirnas are detected Still many reads consumed by trna fragments New trna fragments emerge as abundant (trna-val, trna- Met)

28 trna fragment depletion with more probes (phase III) 16 probes designed based on most abundant sequences of phase 1+2 samples (trna-glu, trna-gly, trna-his, trna-val, trna-met) On average 570 mirnas detected (50 µl serum equivalent) Most reads align to mirnas

29 Depletion comparisons phase I phase II phase III probes: avg mirnas: trna %: 53.44% 40.09% 3.88% mirna %: 1.12% 19.41% 28.33% successful depletion from tiny volumes of biofluids others, e.g. Y-RNAs in human plasma

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31 Therapeutic target selection 126 primary samples (normal and tumors) (9B reads) colon liver lung breast, ovarian, melanoma, bladder, prostate, kidney T N T N T N T N cancer perturbation experiments 180 in vitro perturbations (9B reads) total RNA sequencing public tumor RNA sequencing data (The Cancer Genome Atlas) total RNA sequencing complete lncrnome (polya+ and polya-) polya+ lncrnome complete lncrnome (polya+ and polya-) mrna lncrna guilt-by-association tumor > normal cancer specific lncrnas primary selection criteria predicted function in proliferation and survival pathways (LNCarta) copy number variation / GWAS / cancer gene proximity secondary selection criteria screening cell line transcriptome filter (total RNA sequencing) lncrna targets

32 Example of colon cancer specific lncrna

33 LNCarta database of lncrna functions

34 Identifying candidate therapeutic lncrnas LNCarta o CELL CYCLE o APOPTOSIS o PROLIFERATION o lncrna expression o tumor vs normal o colon, liver, lung therapeutic lncrnas for experimental validation

35 LNCarta workflow identifies known oncogenic lncrnas CRNDE CRNDE, a long-noncoding RNA, promotes glioma cell growth and invasion through mtor signaling BCYRN1 BCYRN1, a c-myc-activated long non-coding RNA, regulates cell metastasis of non-small-cell lung cancer HOX-AS2 Long noncoding RNA HOXA-AS2 promotes gastric cancer proliferation by epigenetically silencing P21/PLK3/DDIT3 expression. HOX antisense lincrna HOXA AS2 is an apoptosis repressor in all-trans retinoic acid treated NB4 promyelocytic leukemia cells ZFAS1 Amplification of long noncoding RNA ZFAS1 promotes metastasis in hepatocellular carcinoma Up-regulated expression of long non-coding RNA ZFAS1 associates with aggressive tumor progression and poor prognosis in gastric cancer patients

36 Biogazelle s RNA targeting therapeutics programs RNA target discovery RNA target validation drug optimization clinical validation BGZ-Tx1 LUNG BGZ-Tx2 LIVER BGZ-Tx3 COLON 3 cancer types 300 lncrna targets antisense molecules lung cancer liver cancer colon cancer

37 Take home message non-coding RNA has great potential biomarker, mode of action, disease mechanism Biogazelle has developed optimized RNA sequencing tools clinically relevant samples (low input, fragmented RNA) depletion of unwanted highly abundant small RNAs unified reference transcriptome LNCarta database of predicted lncrna functions to speed up downstream analyses

38 Acknowledgements Alan Van Goethem Pieter-Jan Volders Pieter Mestdagh Thomas Piofczyk Nele Nijs Carolina Fierro Manuel Luypaert Anneleen Beckers Gert Van Peer Ariane De Ganck Jan Hellemans