Carga mutacional tumoral como biomarcador predictivo en el contexto de la inmuno-oncología

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1 Carga mutacional tumoral como biomarcador predictivo en el contexto de la inmuno-oncología Eva M Garrido-Martin, PhD Grupo de Investigación Clínica en Cancer de Pulmón H12O-CNIO

2 Disclaimer The opinions expressed during this presentation are those of the speaker and may not represent the opinions of Illumina. Any uses of Illumina s products described in this presentation may be uses that have not been cleared or approved by the FDA or any other applicable regulatory body. Illumina is compensating me to speak at this event.

3 Non-Small-Cell Lung Cancer Predictive biomarkers of checkpoint inhibitors efficacy: PD-L1, TMB Challenges for implementation of TMB calculation in clinical practice Our project

4 Lung cancer One of the most common cancers (2 nd in US) Leading cause of cancerrelated deaths in US Poor prognosis Late onset (>70% advanced) 5 year survival <50% in early stages Siegel et al, CA: A Cancer J for Clin 2018

5 Non-Small-Cell Lung Cancer (NSCLC) 85% of LC -ADC -SCC -LCC Chen et al, Nature Reviews Cancer 2014

6 Genetic aberrations in NSCLC Modified from TCGA Research Network, Nature 2012 & 2014

7 Current NSCLC Therapeutic profile Early stage local treatment Surgery -> Stages I-IIIA Perioperative chemotherapy High dose stereotactic body radiation therapy Others (radiofrequency ablation, standard radiotherapy, chemotherapy) Advanced stage systemic treatment Thoracic radiotherapy with delivery of doublet chemotherapy Molecular targeted therapies Platinum-based doublet therapy with or without bevacizumab. Checkpoint inhibitors

8 Timeline of targeted therapies in NSCLC Genomic aberrations discovered Drugs Development (TKIs) Politi et al, American Association for Cancer Res 2015

9 The cancer immunity cycle Immunotherapy sought-targets in NSCLC Chen and Mellman, Immunity (review) 2013

10 Checkpoint inhibitors in immuno-oncology: PD-1/PD-L1

11 The success of checkpoint inhibitors in NSCLC KEYNOTE-001 Advanced NSCLC Garon et al, New Eng J Med 2015

12 The success of checkpoint inhibitors in NSCLC CHECKMATE 057 Advanced NSCLC non squamous that progressed with chemo-platin Nivolumab vs docetaxel Borghaei et al, New Eng J Med 2015

13 Non-Small-Cell Lung Cancer Predictive biomarkers of checkpoint inhibitors efficacy: PD-L1, TMB Challenges for implementation of TMB calculation in clinical practice Our project

14 PD-L1 as a biomarker in I-O Garon et al, New Eng J Med 2015

15 PD-L1 as a biomarker in I-O KEYNOTE-024 Advanced NSCLC and PD-L1 expression>50% Pembrolizumab vs platinum-based chemo

16 Problems in standardization of PD-L1 detection in the routine clinical practice Blueprint study n=39 German harmonization study n=15 Not all the PD-L1 pos patients respond to anti-pd-1/pd-l1 and some PD-L1 neg patients are potential responders Hirsch et al, AACR 2016 Scheel et al. Modern Path 2016

17 Pitfalls of using PD-L1 IHC as a biomarker test for anti PD-1 1. Focal PD-L1 expression in some tumours may be missed in small biopsies 2. PD-L1 expression among multiple tumour lesions in an individual can vary over time and by anatomical site 3. PD-L1 expression in tumour biopsies collected long time ago might not accurately reflect PD-L1 status at the moment of treatment, as chemo, radio or TKIs between collection and immunotherapy can vary its expression 4. PD-L1 epitopes are potentially unstable with fixation and tissue handling 5. Different Ab have different affinities and specificities 6. PD-L1 expression can be membranous (functionally relevant) but also cytoplasmic 7. PD-L1 can be expressed by multiple cell types with the microenvironment Topalian et al. Nat Rev Cancer 2016

18 There is a clear need to find better biomarkers for CPI

19 From PD-L1 to TMB Politi et al, American Association for Cancer Res 2015

20 From PD-L1 to TMB CHECKMATE-026 Nivolumab was not associated with significantly higher PFS or OS than chemo in patients with untreated stage IV or recurrent NSCLC using PD- L1 as a biomarker Different cutoff (5%) BUT They did observed a factor that appear in retrospect to have had an influence on the better response of chemo: PD-L1 expression higher in the chemo group, and High TMB

21 Tumour Mutation Burden (TMB) TMB is the amount of non-synonym somatic mutations in the tumour coding DNA relative to healthy tissue Increased mutation rate is a well-characterized feature of human cancer Abnormal activity in several cellular pathways, including DNA damage repair and DNA replication, can increase the overall rate of somatic mutations in tumours, as can exposure to mutagens such as ultraviolet light and tobacco smoke Defects in DNA damage repair lead to the accumulation of mutations caused by replicative errors and environmental damage DNA damage / DNA mismatch repair abnormal activity DNA replication abnormal activity

22 TMB and response rate to PD-1 inhibition Rosemberg et al, Lancet 2016 Yarchoan et al. NEJM 2017

23 Tumour Mutation Burden (TMB) Alexandrov et al, Science 2013 Signatures of mutational processes in human cancer

24 Mutational landscape determines sensitivity to PD-1 blockade in NSCLC DCB: Durable clinical benefit (partial or stable response lasting >6 months) NDB: Non-durable benefit Rizvi et al, Science 2015 TMB and PD-L1 blockade sensitivity

25 Tumour Mutation Burden (TMB): an emerging biomarker in immuno-oncology Estimate of the neoantigen repertoire in human cancer Aminoacid sequence changes Frameshift changes (not included in all TMB calculations) Fusions/rearrangements (not included in all TMB calculations) Structure of the protein recognizable by MHC type I molecules and therefore, candidate to antigen presentation Schumacher et al, Science 2015 Neoantigens in cancer immunotherapy

26 Neoantigen load has also been correlated with response to immunotherapy Van Rooij N, van Buuren MM, Philips D, Velds A, Toeves M, Heemskerk B, et al. Tumor exome analysis reveals neoantigen-specific T-cell reactivity in an ipilimumab-responsive melanoma. JCO. 2013;31:e However no recurrent neoantigens have been found that predict response (to date) Van Allen EM, Miao D, Schilling B, Shukla SA, Blank C, Zimmer L, et al. Genomic correlates of response to CTLA4 blockade in metastatic melanoma. Science. 2015;350:

27 Mutational landscape determines sensitivity to PD-1 blockade in NSCLC DCB: Durable clinical benefit (partial or stable response lasting >6 months) NDB: Non-durable benefit Rizvi et al, Science 2015 TMB and PD-L1 blockade sensitivity

28 Checkmate 227: TMB as predictor of response with nivo+ipi Nivolumab anti-pd1 Ipilimumab anti-ctla-4

29 Checkmate 227 Hellmann MD et al, (Paz-Ares L) New Eng J Med 2018

30 Non-Small-Cell Lung Cancer Predictive biomarkers of checkpoint inhibitors efficacy: PD-L1, TMB Challenges for implementation of TMB calculation in clinical practice Our project

31 How to measure TMB Targeted panels genes 1 2 Mb Whole exome sequencing WES exons 1% human genome - 38 Mb Whole genome sequencing WGS genes 3, Mb per haploid genome (x2) The Cancer Genome Atlas (TCGA) project and several other studies have used WES to measure TMB across cancer types and found a wide distribution of TMB across ~20 30 cancer types Chalmers et al. Genome Medicine (2017)

32 Challenges for the implementation of TMB determination in the clinical practice Cost Sequencing equipment / reference hospitals Germline sequencing (tumour-normal pairing) Data analysis - Algorithm Bioinformatitians Servers, storage capacity, optimal computers Liquid biopsy Turnaround time!!

33 The Standard of practice: Foundation One Medicine Comprehensive genomic profiling assay 315 genes 1.1 Mb of coding genome Correlation to WES: Exome: 38Mb FoM cutoffs: TMB low 1-5 mut/mb TMB med 5-10 mut/mb TMB high >10 mut/mb Chalmers ZR et al, Genome Med 2017

34 Available NGS panels for TMB calculation Panel TruSight Tumour TST170 AmpliSeq Comprehensive Cancer Panel Foundation One CDx CGP+ Sureselect ST Caris Molecular Int Brand Illumina Thermo Fisher FDA approved for diagnostic use No No Technology Hybrid capture (DNA+RNA) Amplicons (DNA) Genes Horizontal coverage 170 0,524 Mb 409 1,7 Mb Roche Yes Hybrid capture 324 1,1 Mb Agilent No Hybrid capture 592 1,4 Mb MSK-IMPACT MSKCC Yes Hybrid capture 468 1,22 Mb TruSight Oncology TSO500 Oncomine Tumour Mutation Load Ilumina No Hybrid capture 523 1,95 Mb Thermo Fisher No Amplicons (DNA) 409 1,7 Mb Bibliography Goodman AM, Mole Canc Ther 2017 Hellmann MD NEJM 2018 Gatalica Z EJC 2018 Vandervalde A Cancer Med 2018 Rizvi H et al, JCO 2018 For Research Use Only. Not for use in diagnostic procedures.

35 NGS strategies that I have tried: pros and cons Ion Ampliseq Comprehensive Cancer Panel TruSight Tumor 170 Qiaseq Comprehensive Cancer Panel Genes, Input sample and Technology 409 genes DNA RNA Amplicon-based 170 genes DNA RNA Hybridization capture-based 275 genes DNA RNA Hybridizationextension-based Detected alterations SNVs, CNVs, small InDels DNA: SNVs, CNVs, Indels RNA: Fusions, Splice Variants SNVs, CNVs, small Indels Horizontal coverage 1,75 Mb Mutational burden 0,52 Mb Mutational burden? 0,83 Mb Mutational burden? Data analysis Ion Reporter Software More artefacts Base Space Sequence Hub Software Data Less artefacts Insight Software Less artefacts (UMIs) Thermo Illumina Qiagen For Research Use Only. Not for use in diagnostic procedures.

36 Comparison study of technologies using Foundation One as gold standard Patient # TMB MS Mutations Found VUS Total Tissue origin Type of tumour Illumina TST170 AmpliSeq CCP QiaSeq D00/MCBM Med 7/Mb Stable STK11, MYC, KEAP1, TP53 ATR, BRIP1, CEBPA, EP300, FAM123B, IRS2, SDHA, TGFBR2, WT1 13 Brain Unknown primary adenocarcinoma D01/MEER High 62/Mb Stable ERBB2, NF1, STK11, ERRFI1, MYC, ASXL1, CDKN2A, SMARCA4, TET2, TP Soft tissue Unknown primary adenocarcinoma D02/ERR D03/MPCR D04/ARA Low 2/Mb Low 1/Mb Low 4/Mb Stable MAP2K1, ARID1A, CDKN2A/B, KDM5C, KDM6A BRCA2, STAT2, MAP3K1, SYK, TNFAIP3, MLL2, NSD1 12 Soft tissue Stable BCOR, MYB AKT1, AR, CTNNA1, FAT1 6 Lung Stable MLL3 FANCA, WISP 3 Lung Unknown primary squamous cell carcinoma Lung adenoid cystic carcinoma Lung adenoid cystic carcinoma D08/MTLC Med 15/Mb Stable STK11, CDKN2A/B, KEAP1, TP Lung Lung adenocarcinoma D10/MARP Low 4/Mb Stable KRAS, PIK3CA, APC, ARID1A, FAM1234B, TP53 BRIP1, SMAD2, MAP3K1, SMAD3, NOTCH1, ZNF703, POLE, PTCH1, ROS1 15 Peritoneum Unknown primary adenocarcinoma For Research Use Only. Not for use in diagnostic procedures.

37 Parameters that accelerate the implementation of TMB into routine clinical practice Manpower Expertise (pathology, DNA extraction, library prep, sequencing, data analysis) Bioinformatitians Open algorithms Standardization/Harmonization studies Availability of sequencers of high capacity Data storage with encrypted data Collaboration pathology/oncology/molecular biology

38 One step beyond: TMB in liquid biopsy Siravegna G et al, Nat Rev in Clin Oncol 2017

39 Non-Small-Cell Lung Cancer Predictive biomarkers of checkpoint inhibitors efficacy: PD-L1, TMB Challenges for implementation of TMB calculation in clinical practice Our project

40 Integrating tumour molecular profiling and immune landscape in NSCLC

41 Acknowledgements Luis Paz-Ares, MD, PhD Eva Garrido, PhD Irene Ferrer, PhD Santiago Ponce, MD Laura Ojeda Angela Marrugal Patricia Yagüe Javier Ramos Santiago Garcia Angel Nuñez Rocio Suarez Laura Garcia Maria Jose Duran Nuria Carrizo Mirella Gallego Estrella Lopez Dr. Ana Belen Enguita Anatomía Patológica Hospital 12 de Octubre Dr. Ivan Martinez Cirugía Torácica Hospital 12 de Octubre Dra. Alicia Maroto Biobanco Hospital 12 de Octubre Rocio Garcia-Carbonero, MD, PhD Beatriz Soldevilla, PhD Carlos Carretero Cristina Ojeda Beatriz Gil Dr. Daniel Rueda David Gomez Tumores Hereditarios Hospital 12 de Octubre Dr. Luis Alvarez-Vallina Inmunoterapia del Cancer Hospital 12 de Octubre Dra. Lola Martinez Citometria de flujo CNIO

42 Which genomic aberrations do we detect in gdna and which do we detect in cdna? Type of aberration gdna cdna/rna frameshift SNV CNV Small InDels Large InDels amplification rearrangements