Prioritization of Neoantigens without Predictions: Comprehensive T cell Screening using ATLAS

Transcription

1 Prioritization of Neoantigens without Predictions: Comprehensive T cell Screening using ATLAS Jessica Baker Flechtner, PhD CSO, Genocea Biosciences 15 November

2 Safe Harbor Statement This presentation contains forward-looking statements that are within the meaning of federal securities laws and are based on our management s beliefs and assumptions and on information currently available to management. Forward-looking statements include information concerning our possible or assumed future results of operations, business strategies, financing plans, competitive position, industry environment, potential growth opportunities, potential market opportunities and the effects of competition. Forward-looking statements include all statements that are not historical facts and can be identified by terms such as anticipates, believes, could, seeks, estimates, intends, may, plans, potential, predicts, projects, should, will, would or similar expressions and the negatives of those terms. Forwardlooking statements represent our management s beliefs and assumptions only as of the date of this presentation. Our operations involve risks and uncertainties, many of which are outside our control, and any one of which, or combination of which, could materially affect our results of operations and whether the forward-looking statements ultimately prove to be correct. Factors that may materially affect our results of operations include, among other things, those listed in our Annual Report on Form 10-K, our Quarterly Report for the third quarter of 2015 on Form 10-Q and other filings with the Securities and Exchange Commission ( SEC ). Except as required by law, we assume no obligation to update these forward-looking statements publicly, or to update the reasons actual results could differ materially from those anticipated in the forward-looking statements, even if new information becomes available in the future. You may get copies of our Annual Report on Form 10-K, Quarterly Report on Form 10-Q and our other SEC filings for free by visiting EDGAR on the SEC website at 2

3 Introduction to Genocea We are a vaccine company Our ATLAS T cell antigen discovery platform is clinically validated GEN the first subunit vaccine to impact a chronic viral infection Expected to enter Phase 3 in 2017 We have a comprehensive cancer vaccine solution: High-throughput ex vivo antigen selection for both CD4 + & CD8 + T cells Ability to discriminate between responders and non-responders Optimized vaccine delivery system includes adjuvant and manufacturing/production expertise Advisors: a world class team of oncology and vaccine experts We plan to file an IND with a personalized cancer vaccine in

4 Why is ATLAS Important for Neoantigen Vaccines? On average, algorithms have a ~20% success rate at predicting neoepitopes to which T cells respond 4

5 Why is ATLAS Important for Neoantigen Vaccines? On average, algorithms have a Finding the ~20% success rate at RIGHT TARGETS predicting neoepitopes to matters which T cells respond 5

6 ATLAS Provides a Panoramic Perspective on Patient T cell Responses to Identify True Neoantigens Both CD4 + and CD8 + T cell antigens High throughput and rapid ATLAS: actual, not predicted, neoantigens Biological relevance All putative antigens All HLA types 6

7 The Core Invention: Accurate Identification of T cell Antigens in vitro For Any Person Identifying responses by both CD8 + T cells (shown below) and CD4 + T cells Accurately recalls T cell responses in vitro For any person, in any indication Flexible readout Cytoplasmic form of listeriolysin O (cllo) modified so that it can no longer be secreted. E. coli expressing cllo can deliver co-expressed protein to the cytosol of antigen presenting cells. 7

8 ATLAS Optimized as a Highly Industrialized Platform Monocytes: + IL-4, + GM-CSF Bead purification Monocyte-derived DC (APC) Putative Cancer neoantigens Effector T cells Human Subjects Ficoll gradient Protein processing & presentation Whole blood Human immune system in a plate APC Antigen plasmid library T cell Cytokine readout Identify priority T cell targets T cell Response Profile Antigen expression library in E. coli 8

9 Establishing ATLAS Potential for Tumor Antigen Profiling Proof of Concept Study Question: Can ATLAS discern differential patterns of response to tumor-associated antigens in melanoma? Antigen frequency Breadth of response CD4 + and CD8 + T cell responses DFCI collaboration* Retrospective analysis of 20 checkpoint inhibitor recipient subjects T cell responses to 23 pre-selected TAAs Ten cytokine readout *funded by Ludwig Trust, collaboration between DFCI (Hodi/Dranoff), HMS (Higgins/Grubaugh), Genocea 9

10 Profiling Response vs. Non-Response to Checkpoint Inhibitor Therapy (Melanoma) Tumor Regression Tumor Regression Tumor Progression Antigen Tumor Progression 10

11 N u m b e r o f T c e ll A n tig e n s N u m b e r o f T c e ll A n tig e n s ATLAS Discriminates Responder versus Non-Responder C D P< P< P< P ro g re s s o r R e s p o n d e r P< IF N -g a m m a IL -1 2 p 7 0 IL -2 T N F a lp h a IL -1 b e ta C y to k in e IL -4 IL -6 IL -8 IL -1 0 C D 8 IL P< IF N -g a m m a IL -1 2 p 7 0 IL -2 T N F a lp h a IL -1 b e ta IL -4 IL -6 IL -8 IL -1 0 IL -1 3 C y to k in e 11

12 Response Response The Application of ATLAS to Neoantigen Prioritization Immune memory cell Autologous APC and T cells Tumor immune Antigen Neoantigen library Use antigen prioritization criteria defined through ongoing retrospective analysis of CPI-treated subjects 12

13 Construction and Screening of Personalized Neoantigen Expression Libraries Identify tumor-specific somatic mutations Clone DNA sequences encoding ~100 aa spanning each mutation into ATLAS expression construct Shine-Dalgarno T7 Promoter 6 x His attr1 ATLAS TM Expression construct Neoantigen SIINFEKL attr2 T7 terminator Ampicillin Validate expression using a high-throughput surrogate T cell assay Derive DC from monocytes and sort and expand CD4 + and CD8 + T cell subsets from blood, recombine with ATLAS library Measure T cell responses through meso scale discovery 13

14 Clones Arrayed Randomly and Screened in Duplicate add Confidence to Data Analysis Example patient data from a NSCLC patient who was treated with pembrolizumab 14

15 IF N p g /m L IF N p g /m L Robust Platform for Identification of Neoantigens for CD8 + T cells C D 8 T c e ll R e s p o n s e s P r e -T r e a tm e n t Ag pre-treatment Ag post-treatment Inhibitory Ag Negative controls M e a n + 3 * S D C D 8 T c e ll R e s p o n s e s P o s t-t r e a tm e n t M e a n + 3 * S D

16 p g /m L IF N p g /m L IF N Robust Platform for Identification of Neoantigens for CD4 + T cells C D 4 + T c e ll R e s p o n s e s P r e -T r e a tm e n t Ag pre-treatment Ag post-treatment Inhibitory Ag Negative controls M e a n + 4 * S D C D 4 + T c e ll R e s p o n s e s P o s t-t r e a tm e n t M e a n + 4 * S D

17 Stringent Assay Identifies Truly Immunogenic T cell Targets CD8 + T cell Responses Number of mutations identified as neoantigens (IFNγ) Pre-treatment: 13 (6%) Post-treatment: 20 (10%) Both pre- and post-treatment: 6 (3%) CD4 + T cell Responses Number of mutations identified neoantigens (IFNγ) Pre-treatment: 16 (8%) Post-treatment: 38 (19%) Both pre- and post-treatment: 9 (5%) Number of inhibitory neoantigens increases posttreatment Number of inhibitory neoantigens declines posttreatment 15 neoantigens were positive both pre- and post-treatment for either cell type, one for both cell types Six neoantigens were identified by both subsets at any time point 17

18 Comparison of Results with in silico Predictions 64 of 77 (83%) of neoag predicted by algorithms show no detectable response with ATLAS 8 of 77 (10%) of neoag were predicted by both algorithms and ATLAS 5 of 77 (6.5%) of neoag were missed by all three algorithms but found by ATLAS 3 of 13 (23%) of neoag detected by ATLAS were predicted by all three algorithms ATLAS increases useful NeoAg found by 38% and eliminated 83% of false positives predicted by algorithms 18

19 Summary of the ATLAS Potential in Neoantigen Discovery Identifies the majority of neoantigens in any patient Every mutation from a tumor separately screened to identify true neoantigens CD4+ and CD8+ T cell antigens can be separately identified, those that stimulate both may be valuable Multiple cytokines measured simultaneously Inhibitory neoantigens can be identified 19

20 Our Working Hypotheses for Successful Neoantigen Vaccination It is a lower bar to boost pre-existing responses than create de novo responses Re-educate the immune system by delivering an antigen with a strong adjuvant Proof of concept established in our GEN-003 chronic virus immunotherapy With the right adjuvant and ATLAS-prioritized antigens, an IND is anticipated in

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22 Biologically Verified Antigens are Worth It ATLAS adds ~2 weeks to personalized vaccine development The value added: Certainty that T cell responses exist and are not deleterious Confidence that targets are cancer antigens in the individual Likelihood that T cell responses can be boosted with the right vaccine Potential to redirect mis-educated T cells to be productive 22

23 Acknowledgements Memorial Sloan Kettering Cancer Center Timothy Chan Jedd Wolchok Jonathan Havel Vladimir Makarov Taha Merghoub Matthew Hellman Dana-Farber Cancer Institute F. Stephen Hodi [Glenn Dranoff] Harvard Medical School Darren Higgins Daniel Grubaugh Genocea Biosciences Lila Ghamsari Emilio Flano Judy Jacques Biao Liu Wendy Broom Zheng Yan Christine Kelley Aula Alami LeeAnn Blalock Jean-Luc Bodmer Ning Wu Funding Ludwig Trust (TAA study) 23