014 - Evaluation of Immunosignature Profile in Medulloblastoma 013 - Gene Expression Analysis Platform Evaluation for FFPE Specimen Material-Based Studies 014 - Evaluation of Immunosignature Profile in Medulloblastoma Mateusz Koptyra, PhD Center for Data-Driven Discovery in Biomedicine (D3b) Children’s Hospital of Philadelphia

Gene Expression Analysis Platform Evaluation for FFPE Specimen Material-Based Studies for data generation The overwhelming majority of archival samples of cancer tissue are formalin-fixed, paraffin-embedded (FFPE) Archived FFPE specimens present potential for transcriptomic/genomic data generation especially for rare cancers Fixative selection as well as storage conditions can compromise nucleic acid quality. We identified the need to evaluate and establish the system for FFPE material derived transcriptomic/genomic data generation

The Evaluation Demonstrate directional correlation between mRNA analysis form RNAseq and HTG, and NanoString pipelines. Cases: 5 high-grade gliomas (HGG) and primitive neuro-ectodermal tumors (PNET) FFPE specimens Frozen tissue total RNA RNAseq - BGI@CHOP (data obtained from CBTTC) FFPE HTG EdgeSeq analysis – mRNA oncology biomarker panel (OBP) for mRNA gene expression including 2560 genes. NanoString nCounter® PanCancer Pathways panel for mRNA gene expression including 770 genes.

HTG EdgeSeq technology overview Bind target RNA to protection probe Eliminate excess protection probes and RNA with S1 nuclease Eliminate target RNA with heat and base Add sequencing adaptors and tags Quantitate, pool, and sequence

NanoString nCounter technology overview Individual reporter and capture probe for each analyzed transcript Solution based mRNA hybridization Reporter and capture probe complexes surface binding Surface imaging and reporter probes decoding Fortina, P. & Surrey, S., 2008 Nature Biotechnology

Distribution of correlation coefficient The correlation coefficient calculated for each gene using the normalized data from all 5 samples measured by two different platforms.

The distribution of gene expression measurements from 3 platforms. Average expression distribution The distribution of gene expression measurements from 3 platforms.

Average expression correlation Comparison of the average expression measurements from 5 samples between 3 platforms. The data was adjusted, the medians of the means of all 3 data sets are the same. Highlighted (red) genes present the lowest correlation coefficient  (< 0.2).

Currently ongoing and future plans: Establishing within platform correlations Single target gene expression validation studies miRNA whole transcriptome analysis for all analyzed platforms Additional platforms considered – (TaqMan® Gene Expression array / RT2 Profiler PCR Array) Bouin fixative specimen transcriptomic analysis

ImmunoSignature Assay Johnson, Stephen A., TRILOGY STEM Group 2012

ImmunoSignature Assay recognizes brain tumor immuno-pattern in serum The heat-map presents peptides that differentiated glioblastoma patients from healthy persons obtained from two independent cohorts. The colored bars on the right indicate clusters that define groups of peptides. Hughes A. 2012, PLOS One

Immunosignature assay for Medulloblastoma Subtyping 10 plasma specimens from medulloblastoma tumor cases 28 whole blood specimen from medulloblastoma tumor cases Specimen type based evaluation (frozen whole blood vs plasma) analysis Clinical medulloblastoma subtyping RNAseq medulloblastoma subtyping

Phillip B. Storm, MD Adam Resnick, PhD Jena Lilly, MS Angela Waanders, MD, MPH Robert Wechsler-Reya, PhD Dustin Hatefi, MD, MPH Zhe (Jim) Zhang, PhD Namrata Choudhari, MS Yaunkun Zhu,BS Mariarita Santi, MD, PhD Bo Zhang, BS Elizabeth Ampert, BS Phillip Stafford, PhD Stephen Albert Johnston, PhD