142P - Identifying novel immunotherapy targets using machine learning and ex vivo validation

Background

Immunotherapy has transformed the cancer therapy landscape. However, since most patients do not respond, new alternatives are needed. Traditional immune-oncology (IO) target identification uses preclinical models with limited translation between species and an inability to fully recapitulate human tumour complexity. Large-scale multimodal molecular data from patient samples offers utility to discover new generations of targets with higher probability of successful translation into the clinic. Increasing attention is thus focussed on harnessing rich patient molecular data and modern machine learning approaches.

Methods

We profiled tumour-immune relationships to create a rich dataset for IO target discovery. Bulk exome and transcriptome data from n=1,317 immune checkpoint inhibitor-treated patients (Litchfield et al., Cell 2021) were integrated with single cell transcriptomic (scRNAseq) atlases from n=350 samples. We extended this to profile the immunopeptidome of 60 patients. Causal information regarding immune responses to genetic perturbation derived from n=7 genome-wide CRISPR tumour-T cell co-cultures and n=15,442 SNP-phenotype associations. Further biological context was provided by n=6,387 gene-disease, n=147,164 protein-protein and n=265,672 gene-regulatory interactions (Himmelstein et al., eLife 2017).

Results

We developed an ensemble approach comprising XGBoost, random forest, support vector machine and logistic regression models. This framework achieved held-out ROC-AUC>0.75 for classifying gene IO target status (whether a gene was addressed in IO clinical trials), and successfully ranked targets by clinical trial phase (p<0.001), despite being agnostic to these annotations. Interpretability analysis showed strong links between autoimmunity and IO targets. 41 targets were reviewed based on plausibility, tractability and commercial landscape. 4 were selected for immediate ex vivo validation in patient-derived explants and organoid co-cultures, with 5 reserved for potential future work.

Conclusions

Here we will present results from this study in progress and share learnings on the feasibility of using patient data and machine learning to discover new IO drug targets.

Legal entity responsible for the study

UCL.

Funding

Cancer Research UK Cancer Research Horizons.

Disclosure

C. Swanton: Financial Interests, Personal, Invited Speaker, Activity took place in 2016.: Pfizer, Celgene; Financial Interests, Personal, Invited Speaker, October 26th 2020: Novartis; Financial Interests, Personal, Invited Speaker: Roche/Ventana, BMS, AstraZeneca, MSD, Illumina, GSK; Financial Interests, Personal, Advisory Board, AdBoard - November 12th, 2020: Amgen; Financial Interests, Personal, Advisory Board, Current - since 2018: Genentech; Financial Interests, Personal, Advisory Board: Sarah Canon Research Institute; Financial Interests, Personal, Advisory Board, Joined October 2020. Also have stock options: Bicycle Therapeutics; Financial Interests, Personal, Other, Consultancy: Medicxi; Financial Interests, Personal, Advisory Board, Member of the Science Advisory Board. Also had stock options until June 2021: GRAIL; Financial Interests, Personal, Other, Consultancy agreement: Roche Innovation Centre Shanghai; Financial Interests, Personal, Advisory Board, 29 November - 1 December 2022: Novartis; Financial Interests, Personal, Invited Speaker, Oncology Collective - 2nd Nov - 4 Nov 2022 - Atlanta, USA: Roche; Financial Interests, Personal, Advisory Board, ctDNA advisory Board - 24th March 2023: AstraZeneca; Financial Interests, Personal, Invited Speaker, Pfizer Oncology 'Leading the revolution for the future: Pfizer; Financial Interests, Personal, Full or part-time Employment, Chief Clinician since October 2017: Cancer Research UK; Financial Interests, Personal, Ownership Interest, Co-Founder of Achilles Therapeutics. Also, have stock options in this company.: Achilles Therapeutics; Financial Interests, Personal, Stocks/Shares, Stocks owned until June 2021: GRAIL, Apogen Biotechnologies; Financial Interests, Personal, Stocks/Shares: Epic Biosciences, Bicycle Therapeutics; Financial Interests, Institutional, Research Grant, Funded RUBICON grant - October 2018 - April 2021: Bristol Myers Squibb; Financial Interests, Institutional, Research Grant, Collaboration in minimal residual disease sequencing technologies.: Archer Dx Inc; Financial Interests, Institutional, Research Grant: Pfizer, Boehringer Ingelheim; Financial Interests, Institutional, Trial Chair, Chief Investigator for the MeRmaiD 1and 2 clinical trials and chair of the steering committee.: AstraZeneca; Financial Interests, Institutional, Research Grant, Research grant from Oct 2019 - July 2023 - Genetics of CIN and SCNAs for Targeted Discovery (SCEPTRE): Ono Pharmaceutical; Financial Interests, Institutional, Research Grant, Research Grants from 2015: Roche; Financial Interests, Personal, Other, Co-chief investigator: NHS-Galleri Clinical Trial; Financial Interests, Institutional, Research Grant, from October 2022: Personalis; Non-Financial Interests, Personal, Principal Investigator, Chief Investigator for MeRmaiD 1and 2 clinical trials: AstraZeneca; Non-Financial Interests, Personal, Member of Board of Directors, From 2019-2022: AACR; Non-Financial Interests, Personal, Other, Board of Directors: AACR; Non-Financial Interests, Personal, Advisory Role, EACR Advisory Council member: EACR. K.R. Litchfield: Financial Interests, Personal, Invited Speaker: Roche Tissue Diagnostics; Financial Interests, Personal, Other, Consulting work: Kynos Therapeutics, Monopteros Therapeutics, Tempus; Financial Interests, Personal, Invited Speaker, Invited speaker: Ellipses Pharma; Financial Interests, Institutional, Research Grant: Ono/LifeArc; Financial Interests, Institutional, Research Grant, Research funding: Genesis Therapeutics; Non-Financial Interests, Institutional, Proprietary Information, Collaboration on data analysis: Bms. All other authors have declared no conflicts of interest.