Enabling Truly Personalized Neoantigen-Based Cancer Therapies

The first step of developing personalized cancer therapeutics is the identification of patient-specific neoantigens. With ImmunoID NeXT, our partners can utilize our leading methods for predicting which neoantigens are more likely to elicit an immune response.

ImmunoID NeXT™ delivers high quality, exome-scale analysis of both DNA and RNA to guide the development of personalized cancer vaccines (PCVs) and personalized adoptive cellular therapies (PACTs). The entire workflow is optimized to ensure that expedited turnaround timelines are routinely met for personalized cancer therapy development. The added regulatory support and quality assurance processes aid in sample compliance and facilitate the implementation of the platform in all phases of drug development from translational research, clinical trials, and, when applicable, post-approval and beyond.

Accurate and comprehensive neoantigen detection and characterization requires the use of an exome-scale assay since neoantigens can arise from somatic alterations occurring in any gene of the genome (Garofalo et al., 2016). In addition, because only expressed neoantigens are potential candidates for personalized cancer therapy development, it is imperative to analyze not only the DNA of a tumor sample, but also the RNA.

ImmunoID NeXT is a broad immunogenomics platform that combines Personalis’ augmented and analytically-validated NeXT Exome and NeXT Transcriptome, with uniquely enhanced features that are key for the development of personalized cancer therapies.

The following features are incorporated into the ImmunoID NeXT for optimal neoantigen identification:

Augmented Coverage

Personalis’ proprietary Accuracy and Content Enhanced (ACE) Technology augments coverage of complex and difficult-to-sequence regions (e.g. areas of high-GC content) across all ~20,000 genes that are typically poorly covered or completely missed with conventional approaches.

Ultra-High Sensitivity

The ~300X and ~150X mean coverage for the tumor and normal, respectively, enables the highly-sensitive and specific detection of single nucleotide variants (SNVs), insertions/deletions (indels), and gene fusions, any of which may produce potentially-immunogenic neoantigens.

High-Quality HLA

HLA typing is an essential component of the neoantigen prediction process. Leveraging the DNA data derived from the NeXT assay, ImmunoID NeXT utilizes in silico typing of both HLA Class I and Class II loci. Our HLA typing validation study demonstrates that ImmunoID NeXT produces robust and accurate HLA typing.

Advanced Analytics

Integration of both proprietary and publicly-available advanced analytical algorithms and tools to generate high quality and informative analytical reports.

Optimized Extraction

The dual extraction of DNA and RNA from formalin-fixed paraffin-embedded (FFPE) tumor samples maximizes the data generated from each.

NeoantigenID, a suite of advanced analytics, is available via ImmunoID NeXT for the accurate identification of tumor-specific somatic mutations (Figure 1). These mutations are a rich source of putative neoantigens. Current computational neoantigen prediction algorithms suffer from limited training datasets and poor performance. To overcome these challenges, Personalis has developed the Systematic HLA Epitope Ranking Pan Algorithm (SHERPA™) leveraging one of the largest sets of mass spectrometry-based immunopeptidomics training data for accurate neoantigen prediction (Figure 2). SHERPA is integrated into the NeoantigenID analytics engine for comprehensive characterization of putative neoantigens.

Figure 1: Workflow of the NeoantigenID Analytics Engine
Figure 2: Overview of SHERPA machine learning algorithm

The advanced computational pipeline configurations produce data-rich analytics:

  • Accurate identification of SNVs, indels and fusions, which are an abundant source of potentially-immunogenic neoantigens
  • Robust and accurate HLA typing of Class I and Class II MHC loci followed by somatic mutation and allele-specific loss of heterozygosity (LOH) detection in the HLA genes
  •  Comprehensive characterization of each putative neoantigen by combining tumor-specific small variants and fusions with the patient-specific HLA types and predicting neoantigens using our pan-allelic machine learning algorithm, SHERPA™
    – SHERPA relies upon a proprietary, high quality and unambiguous training dataset generated by performing immunopeptidomics on ~70 MHC Class I alleles using monoallelic cell lines. The scale and scope of SHERPA was further expanded by using a large, systematically reprocessed and curated repository of publicly available mono- and multi-allelic immunopeptidomics datasets, as well as publicly available binding affinity data. This combined approach resulted in one of the largest training datasets consisting of 180 unique human alleles. Integrating data from diverse cell line and tissue types improved the generalizability of SHERPA, a critically important aspect when applying it to patient samples.
    – SHERPA incorporates peptide and binding pocket information, expression level of the source protein, proteasomal cleavage, and features representing genes and regions propensities to comprehensively capture all aspects of epitope presentation.
  • Additional immunogenomics analytics to capture the full tumor biology and the complexity of the tumor microenvironment
  • Determination of neoantigen burden as well as the generation of the Personalis Composite Neoantigen Presentation Score (NEOPS) which has the potential to improve the predictive and/or prognostic utility of neoantigen burden-based biomarkers for precision oncology and immunotherapy applications.
Processes and systems to ensure your project is delivered on time:

Expedited Turnaround

Optimized processes ensure that you’ll receive your data no later than 14 calendar days from sample submission

Single Point of Contact

  • Dedicated project manager (PM) is your one point-of-contact for status updates and communication to Personalis
  • PMs are PhD-level scientists with deep scientific and laboratory experience

Real-Time Project and Sample Status

  • Symphony Genomics Management System links LIMS, pipelines, databases, and other internal systems for real-time project status and sample-level tracking with our PM team
  • Symphony enables visibility to the process through automated QC alerts for key milestones and delivery of data with an expedited turnaround time

Locked Down Assays and Pipeline Versions

  • Symphony allows lock down of the platform and analytical pipeline versions for the life of your study
  • Customization in reporting to meet the needs of client’s downstream process and pipelines