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Report

Teaser, summary, work performed and final results

Periodic Reporting for period 1 - APERIM (APERIM: Advanced bioinformatics platform for PERsonalised cancer IMmunotherapy)

Teaser

Summary

Personalized cancer immunotherapy has tremendous potential to provide an incredible benefit to society. Without doubt, successful immunotherapies will not only reduce health care costs, but will also increase the quality of life of the affected patients. Clinical trials have demonstrated profound tumor regression including complete cure in patients with metastatic cancer after treatment with immunotherapy. Importantly, technological advances in next-generation sequencing (NGS) allow for the first time the development of personalised cancer immunotherapies that target patient specific mutations.
However, clinical application is currently hampered by specific bottlenecks in bioinformatics. The project APERIM aims to accelerate the clinical translation and maximize the accessibility and utility of biomedical data in research and medicine.
The overall objective of APERIM is to develop an advanced bioinformatics platform for personalised cancer immunotherapy, which integrates NGS data, whole tissue slides imaging data, and clinical data, as well as novel analytical software tools.

The tools in this platform will further address the following issues:
ï‚§ Quantification of tumor-infiltrating lymphocytes (TILs) in colorectal cancer patients. This digital sorting tool will be invaluable for future biomedical and clinical research.
ï‚§ Development of an analytical pipeline for NGS-guided personalised cancer vaccines. In the future tumor - specific neo-antigens will be identified as individual vaccine targets.
ï‚§ Development of a novel method to predict T-cell receptor (TCR) specificity. Based on this information adoptive T-cell cancer therapy might be successful in the future.

Within APERIM a transdisciplinary network of leading experts in bioinformatics and cancer immunology is working on practical implementation of immunotherapies targeting unique tumor mutations. Partners will develop user-friendly software modules as well as analytical standard operating procedures for clinical use, and apply the bioinformatics platform in clinical settings.

Work performed

In the reporting period APERIM partners set up first architectures and tools towards the development of novel analytical software tools.
A database (The Cancer Immunome Atlas http://tcia.at.) was developed with contains data of the immunogenomic characterization for 20 solid cancers with >8000 tumor samples of The Cancer Genome Atlas. This database provides for the first time comprehensive view of the cellular composition of the intratumoral immune infiltrates. The database will be further developed on order to integrate images from whole-tissue slides (digital pathology) an thereby enable integrative analyses of NGS data and imaging data. Furthermore, the implementation of a functional prototype for an immunology specific ontology and its use for data integration, data consistency, and analysis of data from heterogeneous data sources was successfully performed.
Other groups worked on the development of a fully automatic image analysis solution to detect tumor infiltrating lymphocytes (TIL) in tissue slides. The developed TIL analyser thereby relies on a fully automatic cell segmentation based on machine learning and subsequent cell classification. The prototype of the TIL analyser will now be tested and improved.
Various models have to be combined to finally develop an analytical pipeline for NGS-guided personalised cancer vaccines. Up to now a module to analyse NGS data (output candidate antigenic mutation-containing sequences) could be developed, the researchers are currently working on the transfer of the software to project partners so that it can be tested externally. Further a pipeline that provides predictors for antigen presentation on the cell surface could be set up. As a third action within this objective multiple strategies have been implemented for the selection of sets of potential neo-epitope targets. The models have been implemented into a software product that is disseminated through the established infrastructure (https://github.com/APERIM-EU/WP3-EpitopeSelector, https://hub.docker.com/r/aperim/epitopeselector/) and uses the output of NGSAnalyser and Immunopredictor.
Research groups in parallel also worked on the objective to establish a novel method to predict TCR specifity. In order to achieve this on the one hand the NGS Analyser software had to be developed and on the other hand big data files comprising e.g. CDR3 or TCR sequences and algorithms were set up which will be integrated in the finale APERIM database.

Final results

Technological advances, especially in next-generation sequencing (NGS) combined with data from different sources (imaging data, clinical data) allow for the first time precision tumor medicine.
Providing the necessary - but still lacking - bioinformatics means to accelerate the implementation of these immunotherapies in the clinical setting.
In APERIM, a network of leading experts in bioinformatics and cancer immunology was assembled to ensure that not only highly relevant problems are addressed but also that the implementation of the developed tools in the clinical setting is guaranteed.
The bioinformatics platform will thus considerably accelerate the clinical translation and maximise the accessibility and utility of biomedical data in research and medicine.