ACE ImmunoID. ACE ImmunoID. Precision immunogenomics. Precision Genomics for Immuno-Oncology

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1 ACE ImmunoID ACE ImmunoID Precision immunogenomics Precision Genomics for Immuno-Oncology

2 Personalis, Inc. A universal biomarker platform for immuno-oncology Patient response to cancer immunotherapies is currently reported as falling anywhere between 8% and 20% 1,2. Understanding the mechanisms by which tumors can evade the immune response and elucidating the complex dynamics of the tumor and its microenvironment are key to improving this success rate. ACE ImmunoID is designed to meet this need. The ACE ImmunoID Platform integrates augmented exome and transcriptome sequencing from a paired tumor and normal sample to generate comprehensive genomic and transcriptomic data that can be used for neoantigen selection and tumor immunogenomic profiling. The result? A universal platform to support the development of more effective cancer immunotherapies by identifying biomarkers that can be used to stratify patient populations, determining rational therapy combinations, and developing truly personalized therapeutics. Precision immunogenomics You need to answer complex biological questions. This requires precise and accurate genomic data. Our patented Accuracy and Content Enhanced (ACE ) Technology 3 improves processes including nucleic extraction, library creation, sequencing, and analytics, and is the foundational platform powering ACE ImmunoID. By optimizing each step of genomics laboratory and bioinformatics analysis processes, we re ensuring that you get the most complete data from your precious samples. Make the most of your precious samples Patient samples can vary in quality and unlocking genomic insights from these critical samples can be challenging. Our ACE Technology improves sample preparation and nucleic acid extraction processes, even when working with samples which may be archival and/or partially degraded.

3 ACE ImmunoID ACE ImmunoID requires paired tumor and normal (T/N) samples for analysis. Our proprietary sample-sparing approach enables us to extract DNA and RNA from the same tumor sample. DNA is additionally extracted from the normal sample, providing a germline baseline which is used to more precisely identify tumor-specific somatic mutations. Additionally, Personalis has developed protocols to overcome the challenges of working with diverse sample types including formalin-fixed and paraffin-embedded (FFPE), fine-needle aspirates (FNAs), fresh frozen, and peripheral blood mononuclear cells (PBMCs). With respect to cancer studies, FFPE specimens are often the only tumor sample type available. Unfortunately, the fixation process can contribute to the degradation of both DNA and RNA. To accommodate for any variation in sample quality, each sample undergoes robust QC. At Personalis, metrics such as percent of mapped reads, Qmap score, and Qbase score are evaluated when assessing sequencing results. Figure 1 below illustrates QC metrics for a recent project performed at Personalis using our ACE Cancer Exome assay across 130 randomlyselected FFPE samples that varied in terms of quality (amount, age). The metrics below convey that the data quality of the DNA extracted from these challenging samples was high in more than 92% of these samples. Figure 1: Personalis sample quality metrics in a randomly selected cohort of 130 FFPE specimens Footnotes 1. Gay, N. and V. Prasad. Few people actually benefit from breakthrough cancer immunotherapy. Stat. March 8, com/2017/03/08/immunotherapy-cancer-breakthrough/. 2. Lee Ventola, C. Cancer Immunotherapy, Part 2: Efficacy, Safety, and Other Clinical Considerations. Pharmacy and Therapeutics Jul; 42(7): ACE Technology has patent approval world-wide including the United States, Europe, and China. Precision Genomics for Immuno-Oncology

4 Personalis, Inc. We ve taken the same precautions to ensure that RNA data quality is equally high. Whether fresh frozen or fixed specimens are available for your analysis, the ACE approach produces high quality transcriptome sequencing results. Using paired FFPE and matched adjacent fresh frozen tissues, we found high correlation of normalized gene expression (TPM) (Figure 2) across various tumor types. This data demonstrates that the Personalis ACE Cancer Transcriptome is an accurate, reliable method for characterizing gene expression in even the most challenging materials such as FFPE. Figure 2: Correlation plots of log 2 transcripts per million (TPM) between matched FF (x-axis) and FFPE (y-axis) pairs in A-D) colon, E) lung, and F) rectum tumor samples. ACE sequencing improvements The ACE ImmunoID platform combines our ACE Cancer Exome and ACE Cancer Transcriptome assays for more complete genomic and transcriptomic data compared to standard exome assays. Most commercially-available exome assays have significant sequencing coverage gaps due to systematic sequencing biases. Personalis has custom-developed targeted capture with additional optimized chemistry, as part of our ACE Technology, to augment and fix gaps in the exome across more than 8,000 of the ~20,000 genes. This augmented sequencing decreases the risk of missed variants and more precisely captures putative neoantigens.

5 ACE ImmunoID ACE Cancer Exome When used as a component of the ACE ImmunoID Platform, the ACE Cancer Exome is available as a paired tumor and normal configuration and is sequenced at a guaranteed average depth of 200x for the tumor and 70x for the normal. Our assay outperforms conventional exome assays by augmenting coverage again made possible using our ACE technology across more than 8,000 genes which are poorly covered by conventional approaches. This superior coverage puts our customers at a competitive advantage especially when it comes to identifying putative neoantigens, as well as identifying novel biomarker signatures. Neoantigens can arise from any gene in the genome, therefore, accuracy in calculating neoantigen load or comprehensively identifying neoantigens is contingent on having uniform coverage across the whole exome. The ACE Cancer Exome identifies candidate neoantigens that would have otherwise been missed by a standard exome. Positional analysis of the peptide mutations and binding potential across the SYN1 gene (Figure 3, Panel A), shows the number of predicted binding peptides that are captured in the augmented green region only (ACE supplementation) these peptides would have been completely missed by a conventional offering. The colors indicate the various Class I HLA alleles interrogated. Gene-wide sequencing of the SYN1 gene (Figure 3., Panel B) illustrates the coverage provided by a standard exome assay (blue region) and the gaps filled in by ACE augmentation (green region). Personalis provides both the blue (standard) and green (ACE) regions. A Figure 3: Neoantigens detected through ACE augmentation which would have otherwise been missed using standard exome assays, as demonstrated for the SYN1 gene. B Precision Genomics for Immuno-Oncology

6 Personalis, Inc. ACE Cancer Transcriptome Comprehensive characterization of tumor gene expression is an important overlay for interpreting somatic mutations, identifying neoantigens, assessing expression of immune checkpoint genes, and identifying prognostic expression signatures. The ACE Cancer Transcriptome, as part of ACE ImmunoID, sequences the tumor specimen at 100 million total reads. The same augmented, high accuracy coverage described for the ACE Cancer Exome is also available through our ACE Cancer Transcriptome enrichment protocol. Our enrichment protocol directly selects for transcripts using the optimized ACE capture probes, eliminating background and focusing the sequencing on regions of interest. When compared to a standard exome enrichment protocol, the ACE Cancer Transcriptome shows more uniform and deeper coverage across the entire gene (Figure 4). In addition, because we use the most current gene definitions, the ACE Cancer Transcriptome covers exons that are missing in standard annotation and other exon capture methods (Figure 5). A B Figure 4: Samples were prepared both with a standard exome capture method (panel A) and with the ACE Cancer Transcriptome Protocol (panel B). Five exomes of the BCR gene are shown. The ACE Cancer Transcriptome Protocol shows deeper and more even coverage across all give exome regions. A B Figure 5: Samples were prepared with both the standard exome capture method (panel A) and the ACE Cancer Trancriptome (panel B). Two exomes of the AFF3 gene are shown. The standard exome capture method misses the second exon while the ACE Cancer Transcriptome protocol shows deeper and more even coverage of both.

7 ACE ImmunoID Bioinformatics and reporting High quality genomic and transcriptomic data from ACE ImmunoID is run through our robust somatic pipeline to comprehensively profile the tumor including single nucleotide variants (SNVs), insertions and deletions (indels), fusions, and expression data. We provide both raw data files and reporting for DNA and RNA through our somatic pipelines. A summary of our standard deliverables is shown below: For DNA Analysis For RNA Analysis Raw data files: FASTQ, BAM Somatic variant (SNV, indel) analysis and report: VCF file Somatic variant annotation: VAR file Filtering and annotation of variants by cancer relevance and frequency Quality control report and statistical summary report Raw data files: FASTQ, BAM Variant (SNV, indel) analysis and report: VCF file Gene-associated variant analysis with additional filtering by cancer relevance Fusion gene analysis and report Gene-based expression results Quality control report and statistical summary report Precision Genomics for Immuno-Oncology

8 Personalis, Inc. Informing biomarker discovery and personalized therapy development NeoantigenID and ImmunogenomicsID, advanced analytical components of ACE ImmunoID, go a step beyond our standard bioinformatics reporting to provide summarized analytics on key areas of cancer biology in an easy-to-interpret format. NeoantigenID While tumor mutational burden (TMB) has been found to have some correlation with immunotherapy success 4, studies comparing the predictive utility of TMB and neoantigen load suggest that there is an even higher predicted clinical benefit in patients with higher neoantigen loads 5. Neoantigens are derived from tumor-specific somatic mutations and are therefore present only on the surface of cancer cells and not in healthy tissue. As a result, neoantigens can be used to train the immune system to distinguish healthy tissue from tumor tissue, making these tumor-specific peptides promising targets for personalized cancer vaccines and adoptive cell therapies. Powered by our Neoantigen Pipeline (Figure 6), NeoantigenID provides both TMB and neoantigen load, and also comprehensively identifies all potentially immunogenic neoantigens. Additionally, NeoantigenID includes metrics which may help guide candidate neoantigen selection such as HLA Class I and Class II typing, similarity-to-self, similarity-to-known-antigens, and an immunogenicity score 6. A list of top ten neoantigens, ranked based on MHC-binding prediction, is also provided.

9 ACE ImmunoID Neoantigen Analytics Engine Figure 6: Personalis Neoantigen Analytics Engine consists of several modules that inform neoantigen selection. Precision Genomics for Immuno-Oncology

10 Personalis, Inc. ImmunogenomicsID ImmunogenomicsID complements NeoantigenID to further elucidate the tumor and its microenvironment, providing genomic characterization of genes associated with key immunooncology areas such as antigen processing machinery (APM), immune modulation, adaptive and innate immune response, tumor-associated antigens (TAAs), amongst others. Metrics provided include tumor mutational burden (TMB) and reporting on gene-level expression (TPM), variant type (SNVs, indels, fusions), variant expression, DNA and RNA allelic fraction (>5%), HLA Class I somatic mutation variant calls, as well as population database searches. HLA HLA Class I somatic variants Antigen Presentation Machinery e.g. HLA, B2M, TAP, proteasome, ERAP1 Cytokines & Chemokines e.g. Interleukens, CXCL1,9,10,12, CXCR3 Analytics Immune Modulators e.g. OX40, LAG-3, TIM3, KIR, PD-L1, CTLA-4, ICOS Cytotoxicity e.g. GNLY, GZMA, GZMB, GAMH, PRF1 Immunogenomics and Neoantigen Discovery Adaptive & Innate Immune Response e.g. AIF1, IL2, IRF1, STA1, VCAM1 TAAs e.g. PRAME, MAGE, SSX-2, MUC1, CTAG1B (NY-ESO-1) Repair & Replication e.g. MMR, POL-E, MLH-1, BRCA1, BRCA2 Footnotes 4. Goodman, AM et al. Tumor Mutational Burden as an Independent Predictor of Response to Immunotherapy in Diverse Cancers. Mol Cancer Ther Nov; 16(11): Laus, M. et al. Mutational and putative neoantigen load predict clinical benefit of adoptive t-cell therapy in melanoma. Nature Communications. 2017Nov; 8: Our immunogenicity score is based on internal algorithms derived from Callis et al. PLoS Comput Biol Oct:9(10):e

11 ACE ImmunoID An all-in-one immunogenomics solution By integrating high quality, comprehensive genomic and transcriptomic data, the ACE ImmunoID Platform not only supports a range of novel therapies including neoantigen-based cancer vaccines and adoptive cell therapies, it also supports biomarker discovery for checkpoint modulators. Further, this platform can be used to evaluate the efficacy of multi-modal treatments spanning immunotherapy, targeted therapy, and chemotherapy. Get In Touch To learn more about how our platform can transform your biomarker discovery and clinical development programs, contact us at info@personalis.com. Precision Genomics for Immuno-Oncology

12 Sales Contact United States Europe Other Countries Personalis, Inc O Brien Drive, Menlo Park, CA GENOME4 ( ) Personalis, Inc. All rights reserved. Personalis, ACE, ACE ImmunoID and ACE Cancer Transcriptome are registered trademarks of Personalis, Inc., ( Personalis ) in the United States and/or other countries A