1. 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

2. 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

3. 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 - (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.

4. 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

5. 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

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

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

8. 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).

9. 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

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

11. 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

12. 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

13. 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