Download Gene Expression Measurement of Immuno

Gene Expression Measurement of Immuno-Oncology Targets in a Single FFPE Section Using a Novel Targeted Sequencing Assay
Monica Reinholz, Debrah Thompson, James Cooley, Xiao-Bo Chen, Iris Howlett, John Luecke, Qian Liu, Patrick Roche.
HTG Molecular Diagnostics, Inc. | Tucson, AZ; Abstract 2237
Sample Input Dynamic Range
Abstract
HTG EdgeSeq Immuno-Oncology Assay
HTG EdgeSeq Immuno-Oncology Assay
Background:
The field of immuno-oncology (IO) covers a broad set of research disciplines and presents a highly varied set of experimental
requirements. Experimental challenges include sample types of varying quality and quantity of material (including small fixed
samples and blood products) as well as an expanding multiplicity of targets to assay for immunological response. The
HTG EdgeSeq system combines HTG Molecular Diagnostics’ (HTG) proprietary quantitative nuclease protection assay chemistry
with next-generation sequencing (NGS) to enable semi-quantitative analysis of hundreds to thousands of targeted genes in a
single assay. Biological relevance is presented for two HTG EdgeSeq assays, the HTG EdgeSeq Immuno-Oncology Assay and the
HTG EdgeSeq Lymphoma Panel.
Survival Analysis
Assay Comparison of Gene Expression of Immune Markers
HTG EdgeSeq Lymphoma Panel
CD20 (MS4A1)
Pearson Correlations
Methods:
Assay performance characteristics including sample input titration and reproducibility are presented in brief. Examples of the
biological relevance of this data are provided by qualitative examination of expression from subject samples each profiled using a
single 5 µm FFPE section. Twenty-three FFPE tissue samples from DLBCL patients with progression-free survival (PFS) outcome
data were evaluated using the HTG EdgeSeq Immuno-Oncology Assay and the HTG EdgeSeq Lymphoma Panel. Optimal
cut-points for a set of immune markers (CD68, CD8A, CTLA4, LAG3, CD20, CD56, PDCD1, PDCD1LG2, CD274) were obtained by
maximizing expression using PFS. Kaplan-Meier survival curves are shown for a representative set of these genes. Average
expression for each of the immune genes were tabulated for progressors and non-progressors by assay and further stratified by
ABC/GCB status.
FFPE: 0.78 mm2-12.5 mm2
Cells: 234 cells-7500 cells
uRNA: 0.78 ng-12.5 ng
PAXgene: Neat (32 µl-1:16)
Results:
Correlative expression across the dynamic range was obtained within each of the sample types tested (Pearson correlations
ranging between 0.96 to 0.99 shown for HTG EdgeSeq Immuno-Oncology Assay). High reproducibility was observed across
technical replicates and across platforms (r ≥ 0.94) and days (median r > 0.93; data not shown) for both assays. In two melanoma
tumors, the lymphocyte infiltrates appear to be similar, whereas one tumor appears to be mounting a significant type I interferon
response, which is not as apparent in the other tumor. In the series of DLBCL samples, gene expression distribution was
consistent between the two panels for most of the examined markers. Statistically significant differences in PFS by CD20, CD8,
PD-L1, PD-L2, and CD68 and CTLA4 (not shown) expression were observed using the
HTG EdgeSeq Immuno-Oncology Assay and the HTG EdgeSeq Lymphoma Panel.
Gene Name
A ligand for PD-1. Activated T cells, B cells, and myeloid cells, to modulate activation or
inhibition
CD68
Myeloid cells (macrophages)
CD8; Leu2; MAL; p32
Cytotoxic T cell receptor (TCR). Binds to MHC1 protein.
CTLA4
CD152
Expressed on the surface of Helper T cells and transmits an inhibitory signal to T cells
LAG3
CD223
A cell surface molecule with diverse biologic effects on T cell function
CD20
Expressed on B-cells; enables optimal B-cell immune response against T-independent
antigens
NCAM
Neural Cell Adhesion Marker
CD56
A homophilic binding glycoprotein expressed on the surface of neurons, glia, skeletal
muscle and natural killer cells
PDCD1
PD-1
CD279
A cell surface receptor that belongs to the immunoglobulin superfamily and is expressed on
T cells and pro-B cells
PD-L2; CD273
A second ligand for PD-1 and inhibits T cell activation
CD68
CD8A
Conclusions:
The HTG EdgeSeq Immuno-Oncology Assay and the HTG EdgeSeq Lymphoma Panel provide valuable tools for researchers
exploring the host immune response to tumors across a wide variety of tissue types. Combining highly reproducible results with
very small sample input allows the assays to be utilized for the limited specimens available to researchers.
MS4A1
HTG EdgeSeq System Workflow
mm2-12.5
mm2
FFPE: 0.39
Cells: 234 cells-7500 cells
CD8
Function
PD-L1
CD274
HTG EdgeSeq Lymphoma Panel
Immune Marker
PDCD1L2
PD-L1 (CD274)
Gene Expression Cutoff
mm 2 : 0.39
cells: 250
0.78
500
1.56
1000
3.13
2000
6.25
4000
12.5
8000
log2cpm
Reproducibility
HTG EdgeSeq Immuno-Oncology Assay
Extraction-free method
Proprietary lysis buffer
Amenable to small FFPE and blood samples
Nuclease protection chemistry
Minimal hands-on time
Rapid sequencing library preparation methods
Coupled with NGS
Intra-run
Inter-processor
uRNA
Equivalent to size of 1.5 mm
diameter TMA core
Methods
HTG EdgeSeq Immuno-Oncology Assay:
§ 549 genes
§ Sample input evaluated through a 5-point titration curve using Pearson Correlation
§ Reproducibility for intra-run, inter-day/run, and inter-processor evaluated using SUDHL6 cell line and universal RNA
(uRNA) through Pearson Correlation
HTG EdgeSeq Immuno-Oncology Assay
HTG EdgeSeq Lymphoma Panel
Marker
cut-off
N High
N Low
cut-off
N High
N Low
CD274
8.45
20
3
9.51
18
4
CD68
10.87
20
3
12.17
18
4
CD8A
10.45
9
14
10.68
14
8
CTLA4
6.54
20
3
6.96
20
2
LAG3
9.02
19
4
11.66
11
11
MS4A1
9.92
9
14
14.81
11
11
NCAM1
8.27
5
18
9.48
4
18
PDCD1
8.27
14
9
8.69
16
6
PDCD1LG2
7.44
19
4
8.07
18
4
PD-1 (PDCD1)
Example of Cutoff Determination: MS4A1, PFS
HTG EdgeSeq Immuno-Oncology Assay
HTG EdgeSeq Lymphoma Panel
HTG EdgeSeq Lymphoma Panel
LAG3
HTG EdgeSeq Lymphoma Panel:
§ 93 genes
§ Linearity evaluated through a 5-point titration curve using R2
§ Reproducibility intra-run, inter-day/run, and inter-processor evaluated using SUDHL6 cell line through Pearson
Correlation
Biological Significance:
§ Optimal cut-points for a set of immune markers (CD68, CD8A, CTLA4, LAG3, CD20, CD56, PDCD1, PDCD1LG2, CD274)
obtained by maximizing expression using PFS (log-rank statistic) from 23 patients with DLBCL
§ Kaplan-Meier survival curves
§ Average expression for each of the immune genes tabulated for progressors and non-progressors by assays and
further stratified by ABC/GCB status
Differential Gene Expression of Immune Markers in Melanoma Samples
(HTG EdgeSeq Immuno-Oncology Assay)
Similar immune cell compositions evaluating traditional markers
3500
3000
10000
NK cells
8000
CPMs
CPMs
2500
Interferon-like
response
6000
1500
4000
1000
500
0
Helper
T-cell
Cytotoxic
T-cells
CD3D
Interleukin Melanoma
13
antigen
2000
Broad
T-cell
B cells
0
CD4
CD8A
Melanoma 1
CD68
Menanoma 2
CD79A
FCGR3A
(CD16)
HTG EdgeSeq Immuno-Oncology Assay
Tissue inhibitor
metalloproteinase
12000
IFNA2
IFNAFamily
IFI27
Melanoma 1
IL13RA2
Menanoma 2
MAGEC1
TIMP1
Conclusions
HTG EdgeSeq Immuno-Oncology Assay and HTG EdgeSeq Lymphoma Panel:
Different tumor immune response seen evaluating novel markers
Myeloid cells
(macrophages)
2000
Mean (Standard Deviation) Expression By ABC/GCB and Progression and Assay
ABC
HTG EdgeSeq Lymphoma Panel
GCB
ABC
§ Do not require RNA extraction from samples tested.
GCB
No Progression
Progression
No Progression
Progression
No Progression
Progression
No Progression
Progression
CD68
12.45(0.73)
11.84(0.82)
11.84(0.46)
11.72(0.95)
14.01(1.12)
13.48(0.85)
13.3(0.48)
12.68(1.58)
CD8A
11.14(0.51)
9.74(0.92)
10.19(0.65)
9.58(1.23)
12.71(0.65)
10.76(1.05)
11.25(0.61)
10.91(1.94)
CTLA4
8.3(0.69)
7.9(1.91)
8.53(1.02)
7.97(1.53)
10.03(0.67)
9.25(1.8)
10.17(1.06)
9.2(2.79)
LAG3
10.74(0.41)
10.55(1.66)
9.96(0.42)
9.26(1.69)
12.43(0.58)
12.37(1.49)
11.41(0.72)
10.53(2.23)
MS4A1
9.29(0.9)
8.34(1.34)
10.74(0.74)
9.47(0.38)
14.86(0.83)
14.52(0.64)
15.82(0.71)
14.1(0.48)
NCAM1
6.75(1.43)
7.04(2.58)
7.12(1.34)
7.46(0.61)
7.93(1.82)
6.56(4.47)
8.63(2.42)
8.64(1.29)
PDCD1
9.51(0.34)
7.92(1.28)
9.06(0.79)
7.77(1.89)
10.51(0.85)
8.88(1.05)
9.86(0.68)
8.28(2.52)
PDCD1LG2
8.38(0.59)
8.25(0.71)
8.3(0.51)
7.26(1.26)
9.93(0.56)
9.28(1.16)
9.13(0.37)
8.49(2.22)
CD274
9.57(0.33)
8.93(0.92)
9.33(0.92)
9.28(1.04)
11.12(0.53)
9.68(1.59)
10.65(0.73)
10.38(1.65)
§ Are amenable to small clinical specimens – requires very little sample input (~1-2 mm2 FFPE tissue).
§ Detect expression of several hundreds of genes in different sample types tested.
§ Have excellent technical and instrument to instrument reproducibility (r > 0.93).
§ Are linear over wide range of sample inputs.
§ Display similar biological results (e.g., PFS outcome correlation) while measuring genes with different assays.
§ Identify differential gene expression within tumor types.
§ Identify differential gene expression between progressors and non-progressors.
HTG Molecular Diagnostics, Inc. | 3430 E. Global Loop | Tucson, AZ 85706 | (877) 289-2615 | htgmolecular.com | Presented at AACR Annual Meeting 2016
For Research Use Only. Not for use in diagnostic procedures.
HTG EdgeSeq, HTG Edge and qNPA are trademarks of HTG Molecular Diagnostics,
Inc. Any other trademarks or trade names used herein are the intellectual property
of their respective owners.
Work supported by NIH grants R44HG005949 and R43HG005949