Day One
WEDNESDAY, 24TH APRIL 2019
Day Two
Thursday, 25TH APRIL 2019
08.30 Registration
09.15 Chair’s Opening Remarks
Approaches to Improve Neoantigen Predication
09.30 Neoantigen Prediction: Approach & Validation
Synopsis
- Most solid tumour patients could benefit from personalised immunotherapy against private neoantigens – discussing the critical need for neoantigen identification and product manufacturing
- Addressing the significant challenge of neoantigen identification for cancer immunotherapy
- Understanding how tumour immunopeptidomics combined with deep learning provides a powerful approach for neoantigen prediction
- Evaluating Gritstone’s EDGETM prediction model which identifies therapeutically relevant neoantigens
10.00 A Non-Functional Neoepitope Specific CD8+ T-cell Response Induced by Tumour Derived Antigen Exposure In Vivo
Synopsis
- High frequencies of mutation-specific T cells are rarely spontaneously induced. Hence, therapies that broaden the tumour specific T-cell response are of interest
- We analysed neoepitope-specific CD8+ T-cell responses mounted either spontaneously or after immunotherapy regimens, which induce local tumour inflammation and cell death in mice
- Review how all tested treatment regimens were found to induce a single significant CD8+ T-cell response which was not able to recognize and kill tumour cells
- Evaluate the presented data which exemplifies that neo-antigen specific T cells primed by tumor-released antigen exposure might not always be functionally relevant as previously expected
10.30 An Integrated Machine-Learning Approach to Improve the Prediction of Clinically Relevant Neoantigens
Synopsis
- Outlining a high-performing machine learning approach, trained on massspectrometry data, that predicts naturally processed and presented antigens
- Demonstrating how the predictor is integrated with several immune parameters, such as HLA binding, in a deep learning layer to predict bone fide neoantigens
- Illustrating its application to significantly improve the identification of neoantigen targets for personalised cancer immunotherapy
11.00 Speed Networking & Morning Refreshments
Enhancing the Validation of Neoantigens to Ensure Immunogenicity
12.00 Connecting Neoantigens to TCR Recognition
Synopsis
Evaluating how:
- Not all aberrations are equal in the eyes of the immune system
- Only some non-self aberrations are processed and presented
- Only some presented peptides are recognised and impart effective immune response
- TCRs have a defined specificity for recognition
12.30 Obtaining a Fuller Picture of Immunogenicity to Improve Neoantigen Selection
Synopsis
- Reviewing important parameters to consider for neo-epitope selection
- Improving neoantigen prediction for MHC II peptides
- Comparing and contrasting methods for prediction for better T cell epitope discovery
- Balancing high throughput capabilities while selecting all presented and immunogenic MHC ligands
13.30 Lunch & Networking
14.30 ImmunoID NeXT Platform: Improving Neoantigen Prediction, TME Assessment, & ctDNA Detection for Vaccine Development
Synopsis
- Exploring innovative genomics methods for more comprehensive assessment of neoantigens
- Improving neoantigen to MHC binding prediction and ranking
- Assessing TME/TCR and tumour escape mechanisms that may impact vaccine response
15.00 Determinants of Cancer Neoantigen Immunogenicity
15.30 Afternoon Break & Poster Session
16.00 Roundtable Discussion:
Synopsis
Be part of practical and highly interactive breakout roundtables where attendees can crowd-source solutions and
share opinions around pre-assigned topic areas. This is a valuable chance for you to unite with your peers around
hot topics and debate best practice.
