Abstract 1334: A diagnostic platform for precision cancer therapy enabling composite biomarkers by combining tumor and immune features from an enhanced exome and transcriptome
Authors: Power Robert Peter , Bartha Gabor , Harris Jason , Boyle Sean M. , Levy Eric , Milani Pamela , Tandon Prateek , McNitt Paul , Lee Mandy , Morra Massimo , Desai Sejal , Salvidar Sebastian , Clark Michael J. , Haudenschild Christian , Jang Sekwon , West John , Chen Richard 
Published: September 2020

There is an increasing need for more advanced, composite biomarkers that can model the complex systems biology driving response and resistance to cancer therapy. However, many cancer diagnostic platforms to date, with their focus on mutational changes in a relatively small panel of genes, provide limited data to support integrative, multidimensional biomarkers that can better predict immunotherapy response.

To enable the identification of composite biomarkers that combine tumor- and immune-related information from both DNA and RNA, we have developed ImmunoID NeXT, an enhanced exome/transcriptome-based diagnostic platform that can simultaneously profile the tumor and immune system from a single FFPE sample, across all of the approximately 20,000 genes. By co-optimizing assay and analytics design, we enable sensitive evaluation of clinically-relevant cancer biomarkers from &gt;=25ng of co-extracted DNA/RNA, while also providing a broader evaluation of neoantigens, HLA typing and LOH, antigen processing machinery (APM), TCR/BCR repertoire, immune expression signatures, tumor-infiltrating lymphocytes (TILs), oncoviruses, and germline variants. Leveraging this expansive feature set, we developed methods that combine individual analytes to construct composite biomarker scores that correlate with immunotherapy response.

Validation of ImmunoID NeXT demonstrated high sensitivity and specificity to somatic and structural variants across ~20,000 genes at allelic fractions as low as 5%, with clinical diagnostic reporting on actionable mutations (SNVs, indels, CNAs, fusions) in 248 cancer-driver genes that have been boosted further for higher sensitivity, as well as reporting on TMB and MSI status. For neoantigen prediction, immuno-peptidomic data from monoallelic HLA-transfected cell lines were used to train neural networks to predict pMHC binding with higher precision than public tools. For TCRα/β analysis in FFPE tumor samples, strong correlation with targeted TCR kit results was shown (R^2&gt;0.9 and &gt;0.94). For TILs, we developed signatures for eight immune cell types, demonstrating concordance with orthogonal immunofluorescence methods. We achieved genotyping accuracy of 99.1% for HLA Class I, and 95% for HLA Class II, and have developed and verified the performance of a tool for HLA LOH detection. In a cohort of 55 late-stage melanoma patients, the integration of neoantigen burden, HLA LOH, and APM mutational data formed a composite neoantigen score that more accurately predicted response to checkpoint blockade than other markers such as TMB.

With ImmunoID NeXT, we have developed a broad diagnostic platform that can be leveraged for the development of advanced composite biomarkers (and novel resistance mechanisms) that combine both tumor and immune features from DNA and RNA; enabling more accurate stratification of patient response to immunotherapy. The platform has been validated and optimized for use with limited FFPE tissue samples, making it ideal for both research and clinical applications.

Citation Format: Robert Peter Power, Gabor Bartha, Jason Harris, Sean M. Boyle, Eric Levy, Pamela Milani, Prateek Tandon, Paul McNitt, Mandy Lee, Massimo Morra, Sejal Desai, Sebastian Salvidar, Michael J. Clark, Christian Haudenschild, Sekwon Jang, John West, Richard Chen. A diagnostic platform for precision cancer therapy enabling composite biomarkers by combining tumor and immune features from an enhanced exome and transcriptome [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1334.