Enabling Truly Personalized Medicine

The first step in the development of personalized cancer therapeutics is the identification of immunogenic, tumor-specific neoantigens. With the ImmunoID NeXT Platform, our partners can utilize our leading methods for predicting which peptides are the most likely to produce an efficacious therapy. 

ImmunoID NeXT delivers high quality, exome-scale analysis of both DNA and RNA to enable the development of both personalized cancer vaccines (PCVs) and personalized adoptive cellular therapies (PACTs), supporting our partners through all phases of drug development from preclinical 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 provides the deep interrogation of DNA and RNA across all ~20,000 genes in a tumor and matched normal sample configuration in order to distinguish between somatic and germline mutations. The following features are incorporated into the ImmunoID NeXT approach 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.


Figure 1: Gene-wide analysis of SYN1 (Panel B) shows the sequencing coverage provided by a standard assay (blue regions) as well as the ACE-enabled augmented coverage (green regions). ImmunoID NeXT encompasses both the standard blue and the augmented green regions. Positional analysis of peptide mutations and HLA-binding potential across the SYN1 genes (Panel A, highlighted region) indicates the number of predicted binding peptides that are captured in the augmented green region only — peptides that would have been missed with a standard offering.

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 select Class II loci.
HLA LociNumber of CallsNumber in AgreementConcordance
All Class I11211199.1%
All Class II22220994.1%
All Class I + Class II33432095.8%

Figure 2: We performed an HLA typing validation study using 18 samples from the International Histocompatibility Working Group (IHWG) in addition to the NA12878 cell line from Centre d’Etude du Polymorphism Humain (CEPH) pedigree. Of the 334 total calls, 320 were in agreement with the gold standard.

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

The NeoantigenID analytic module processes the raw DNA and RNA data to provide an extensive evaluation of candidate neoantigens derived from SNVs, indels, and/or fusions. Significantly, both in-frame and out-of-frame events are accurately considered by transcript, ensuring that a potentially-rich source of putative neoantigens are captured.

Figure 2: Workflow of the NeoantigenID Analytics Engine

The NeoantigenID deliverables used to prioritize neoantigen targets for PCV and/or PACT development are as follows:

  • Identification and ranking of neoantigens based on information such as HLA typing, MHC-binding prediction, similarity-to-self, similarity-to-known antigens, and immunogenicity
  • Allelic fraction and gene- and variant-level expression
  • Phasing for allele-specific expression determination
Gene SymbolPeptideHLAVariant Source TypeExpressedAF DNAAF RNAMinimum Binding Affinity (nM)PredictorBinding Pocket SequenceImmuno-genicity

C11orf63

FVYHINTHR

HLA-A6801

SNV

Y

0.09

*

3.55

NetMHCpan

FVYHINTHR

0.20

CARD11

EVSKYFLPY

HLA-A2601

Fusion

Y

0.15

0.30

5.51

NetMHC

EVSKYFLPY

-0.17

Table 1: Example of the information delivered via NeoantigenID for each of the potentially immunogenic neoantigens identified.

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

  • Personalis’ Symphony Genomics Management System links LIMS, pipelines, databases, and other systems for real-time project status and sample-level tracking
  • This allows your PM to ensure your project stays on-track

Locked Down Assays and Pipeline Versions

  • Symphony also locks down assays and analysis pipeline versions for the life of your study
  • If required, Symphony can globally accommodate re-analysis on updated pipelines, even after a study has closed