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Integrated genomic DNA and RNA profiling to predict
cancer immunotherapy response
Jianjun Yu, Zhixin Zhao, Pan Du, Xiaohong Wang, Huiquan Wang, Shidong Jia
Predicine Inc, Hayward, CA 94545, USA
Methods and Materials
Response to cytokine
Regulation
T-Cell Functions
Chemokines
Cytokines
Cell Functions
Interleukins
B-Cell Functions
TNF Superfamily
Adhesion
NK Cell Functions
Pathogen Defense
Antigen Processing
Cytotoxicity
80
51
38
34
25
22
14
12
9
9
8
7
6
6
Transporter Functions
Leukocyte Functions
5
3
Association of Expression of Tumor Stroma Genes
with OS in Patients with anti−PD1 treatment
1.0
Primary Annotations # of Genes
Eosinophils
10
Th1 cell
9
Cytotoxic cell
7
B-cell
6
DC
6
CD4+ T-cell
6
Neutrophils
6
CD8+ T-cell
5
Macrophages
3
Mast cell
3
Tem
3
TFH
3
aDC
2
iDC
2
Th17 cell
2
Th2 cell
2
# of Genes
Low Score
High Score
0.8
Categories
Survival probability
Table 2. Cell Type Summary
0.2
In this study we report the development of PrediSeq-CI (Cancer
Immunotherapy) panel for comprehensive expression profiling of
genes associated with cancer immunotherapy response. DNAbased methylation data and ddPCR gene expression data are also
shown.
Table 1. Immune Response Category
Fig. 2: Stratification of immune cells and prediction of PD1
response by PrediSeq-CI panel.
Log-rank P = 0.029
0.0
Immunotherapy response varies widely, making it difficult for
physicians to know whether immunotherapy will be effective for a
given patient. Recent studies have reported that patients with high
PD-L1 gene expression are likely to respond to checkpoint blocking
drugs, but there are still many patients whose tumor test for the PDL1 protein are negative and can respond to the drugs. In addition to
the potential link between mismatch repair (MMR) gene mutations
and clinical response to anti-PD1 immunotherapy drug, recent
findings show that tumor mutation burden and microsatellite
instability (MSI) are good indicators of the cancer immunotherapy
responses.
0
6
Fig. 1: Method development for Methyl-Seq and PrediSeq-CI.
cfDNA+cfRNA
1a. Stratification of immune cells by
PrediSeq-CI genes
PrediSeq-CI
PD-L1 ddPCR
24
30
36
1b. Tumor stroma gene set (within
panel) is associated with anti-PD1
response in melanoma.
Fig. 3: PD-L1 DNA Methylation predicts gene expression
Regions Analyzed
221 genes (212 targeted genes, and 9
housekeeping genes)
Sequencing
Illumina NGS
Bioinformatics
in-house pipeline
Turn Around Time
2-4 weeks
Sample Requirement
Liquid Biopsy or Tissue Biopsy
Liquid Biopsy Requirement
5ml plasma or 10ml Whole Blood
Tissue Biopsy Requirement
200mg, or 3 FFPE slides
3a. DNA methylation is associated
with gene expression
3b. Detection of PD-L1 DNA
methylation using Methyl-Seq
Fig. 4: PD-L1 gene expression in clinical samples by ddPCR
dscDNA
MSP
18
OS (months)
Conclusions
Methyl-Seq
12
PrediSeq-CI: Panel Analysis Metrics & Sample Requirement
Nucleic acids were extracted from tissue and/or plasma
samples and tested for PrediSeq-Cancer Immunotherapy gene
expression panel, methylation DNA NGS panel, and PD-L1
digital PCR test.
Bisulfite conversion
Results
PrediSeq-CI Cancer Immunotherapy Panel
0.6
Background
0.4
Poster#: 429
•
PrediSeq-CI, PD-L1 ddPCR and methylation tests have been developed to support cancer immunotherapy clinical studies.
[email protected], www.predicine.com
© 2017
Predicine, Inc. 3555 Arden Rd, Hayward, CA 94545