Simultaneous Characterization and Quantification of Immune ...
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Background Methods Tools to Characterize Rare Immune Cell Populations CD4/CD8/Ki-67 in Lung Disease Patients Changes in CD4/CD8/Ki-67 with PD-L1 inhibitor Tx Conclusions • Expression of PD-L1 on tumor, and immune markers in tumor tissue, are associated with improved response to PD-1 and PD-L1 checkpoint inhibitors. However, each alone has limited predictive utility. • Multimodal characterization of both the tumor and host immune system is an unmet medical need for the improved prediction of response to immunotherapy. • Metastatic lesions are likely to be under-sampled and require a liquid biopsy, given tumor heterogeneity and evolution and temporal changes in the host immune system. • We sought to examine expression of PD-L1 on CTCs as well as characterize rare immune cell populations with a non-invasive liquid biopsy. Examining dynamic biomarker changes in longitudinal samples could enable the development of novel diagnostic tools for response prediction and pharmacodynamics studies related to immunotherapy. Simultaneous Characterization and Quantification of Immune Cell Subpopulations and PD-L1 Expressing CTCs in Peripheral Blood of Cancer Patients Rachel Krupa, Robin Richardson, Adam Jendrisak, David Lu, Angel Rodriguez, Mike Malchiodi, Nadia Ebrahim, Sean Nisperos, Aaron Oh, Ryon Graf, Jiyun Byun, Yipeng Wang, Mark Landers, Ryan Dittamore Epic Sciences, 9381 Judicial Dr., Suite 200, San Diego, CA 92121 epicsciences.com Blood samples were drawn from 3 healthy donors, 5 non-cancerous lung disease patients, and 4 metastatic cancer patients (prior to and on-therapy with checkpoint inhibitor), and sent to Epic Sciences for processing with Epic Sciences’ CTC and immune cell assays. 4) SINGLE CELL DIGITAL PATHOLOGY 1) SLIDE PREPARATION 2) CELL STAINING 3) SCANNING Nuclear Features Cytoplasmic Features Cell Features Nuclear Area Cytoplasmic Area AR Expression Nuc. Convex Area Cyto Convex Area CK Expression Nuc Major Axis Cyto Major Axis N/C Ratio Nuclear Minor Axis Cyto Minor Axis Nuclear Circularity Cyto Circularity Nuclear Solidity Cyto Solidity Nuclear Entropy Cyto Entropy Nuclear Speckling Cyto Speckling Nucleoli Presence Cyto Presence CK, CD45, DAPI, PD-L1, etc. CK Morphology CD45 Immune Cell Characterization: • Activated T Cells • Regulatory T Cells • Exhausted T Cells • MDSCs • NK cells CTC Phenotypic Analysis: • PD-L1 protein • Calreticulin • Tumor Cell Heterogeneity Archivable Biobank CTC analysis Immune Cell Analysis CTC Genomic Analysis: • Genomic Instability • Mutational Burden PD-L1 expression is detectable in two distinct cell populations in the peripheral blood of lung cancer patients and is associated with worse survival 1 . PD-L1 expression was detected within peripheral circulating cells associated with malignancy (CCAM) in 26/112(23%) non-small cell lung cancer patients. Two distinct populations of nucleated, non-hematolymphoid, PD-L1 expressing cells were identified; A) cytokeratin positive (CK+, PD-L1+, CD45-) and B) cytokeratin negative (CK-, PDL1+, CD45-). PD- L1+ CCAMs are prognostic for overall survival in lung cancer patients. C) Kaplan–Meier estimates of overall survival of patients stratified by those with >1.1 PD-L1(+) CCAM (gray line) or ≤1.1 PD-L1(+) CCAM (black line). 1 Boffa D. J. Cellular Expression of PD-L1 in the Peripheral Blood of Lung Cancer Patients is Associated with Worse Survival. Cancer Epidemiology, Biomarkers & Prevention. 2017; 26(7):1139- 1145. A B PD-L1(+) Peripheral Circulating Cells in Lung Cancer CD4 CD8 Ki67 DAPI composite DAPI CK CD45 PD-L1 Cell Ratios (CD4:CD8) Detecting large scale immune cell changes with the CD4, CD8 Assay. Contrived samples were prepared with immunomagnetically purified CD4 and CD8 cells plated in ratios of approximately 3:1, 1:1, and 1:3. Table shows measured cell counts as a percentage of total cells (approximately 1 million total cells per slide). • Multimodal characterization of both the tumor and host immune system is an unmet medical need for the improved prediction of response to immunotherapy. • Detection of PD-L1 in circulating cells from NSCLC liquid biopsy samples was associated with worse overall survival, highlighting the potential utility of minimally invasive liquid biopsies for tumor profiling. • Epic Sciences has developed tools to simultaneously detect, characterize, and quantify CTCs and rare immune cell subpopulations from a single blood draw. • Examining dynamic biomarker changes with minimally invasive liquid biopsies in longitudinal samples could enable the development of novel diagnostic tools for response prediction and pharmacodynamics studies related to immunotherapy. Detecting small scale immune cell changes: quantitation and linearity of the CD8 assay. CD8 + cells were spiked into healthy donor leukocytes at target ratios of approximately 1 - 9%. After staining and quantification of CD8 + cells, percentages of detected spiked CD8 + cells for three technical replicates (Percent CD8 + Measured) were plotted against target percentages (Percent CD8+ Target). Bars show mean and standard error of the mean. Schematic of Epic’s CTC platform: CTC enumeration, leukocyte classification, morphology and protein analyses 1) Nucleated cells from a 10 mL blood draw are plated onto 10-12 slides (approximately 3 million cells/slide) 2) Slides are stained with 4',6-diamidino-2-phenylindole (DAPI) and a combination of one or more additional markers, including cytokeratin (CK), CD45, PD-L1, CD3, CD4, CD8, CD14, Ki-67, PD-1, Lag-3, and Tim-3 3) Slides are scanned using a rapid fluorescent scanning method, which images each nucleated cell 4) All cells are analyzed with a multi-parametric digital pathology algorithm for morphological features and protein expression Schematic of Epic Single Cell Tools for Immune Monitoring 1) A single blood draw is used to make slides for CTC and immune cell analysis. Extra slides are archived for staining at a later date 2) Slides can be used for CTC and immune cell characterization as well as downstream genomic analysis C CD45 PD-L1 DAPI CD3 DAPI Representative images of immune cell staining in control cell lines and healthy donor or patient leukocytes. Cells were plated and stained with DAPI and one or more immune cell markers including CD4, CD8, Ki-67, CD3, PD-L1, CD45, PD-1, Tim-3, Lag-3, and CD14. CD45 Tim-3 DAPI CD4/CD8/Ki-67 CD3 PD-L1/CD45 PD-1 Tim-3 Lag-3 CD14 Lag-3 DAPI CD14 DAPI PD-1 DAPI 0.9 1.8 2.7 3.6 4.5 5.4 6.3 7.2 8.1 9.1 0 1 2 3 4 5 6 7 8 Percent CD8+ (Target) Percent CD8+ (Measured) Quantification of CD4 and CD8 positive populations. Leukocytes from five lung disease patients and two healthy donors were plated and stained with CD4, CD8, Ki-67, and DAPI. CD4 + :CD8 + ratios (A) and cell counts per mL of blood (B) were quantified. Quantification of double positive populations. Scatter plots comparing CD4 + Ki-67 + and CD8 + Ki-67 + double positive populations in healthy donor and lung disease patient samples (C). CD4 + Ki-67 + (D) and CD8 + Ki-67 + (E) leukocytes were quantified in healthy donor and patient samples and graphed as a percentage of total leukocytes. CD4 + Ki-67 + and CD8 + Ki-67 + double positive values were also graphed as a percentage of total CD4 + (F) or total CD8 + (G) leukocytes, respectively. Representative scatter plots demonstrating CD4, CD8, and Ki-67 threshold determination in a healthy donor sample. Healthy donor leukocytes were plated and stained with CD4, CD8, Ki-67, and DAPI. Mean fluorescent intensity (MFI) was plotted for approximately 3 million cells to generate histograms and determine positivity thresholds for each marker, and to quantify CD4 + and CD8 + cell counts. Thresholds were applied to scatter plots for quantification of double positive values for CD4 + Ki67 + and CD8 + Ki-67 + . A B C F D E G Changes in CD4, CD8, and Ki-67 positive populations were detected in metastatic cancer patient samples upon treatment with PD-L1 inhibitor. Baseline and cycle 3 samples were collected for four metastatic cancer patients undergoing PD-L1 inhibitor therapy. Percent change was calculated for CD4 + Ki-67 + and CD8 + Ki-67 + populations between baseline and cycle 3 samples (A and B). CD4 + Ki-67 + and CD8 + Ki-67 + percentages were quantified per total CD4 + and CD8 + cells, respectively. Six replicates from a single healthy donor were stained along with patient samples to serve as controls. For percent change analyses, replicates were analyzed as pairs to mimic baseline and on-therapy samples. CD4 + :CD8 + ratios were determined for patients and healthy donor samples (C). Percent change between baseline and on-therapy was calculated for patient samples and healthy donor replicates were analyzed as pairs (D). composite DAPI CK CD45 PD-L1 A B C D
Transcript of Simultaneous Characterization and Quantification of Immune ...
Background
MethodsTools to Characterize Rare Immune Cell Populations
CD4/CD8/Ki-67 in Lung Disease Patients
Changes in CD4/CD8/Ki-67 with PD-L1 inhibitor Tx
Conclusions
• Expression of PD-L1 on tumor, and immune markers in tumor tissue, are associatedwith improved response to PD-1 and PD-L1 checkpoint inhibitors. However, each alonehas limited predictive utility.
• Multimodal characterization of both the tumor and host immune system is an unmetmedical need for the improved prediction of response to immunotherapy.
• Metastatic lesions are likely to be under-sampled and require a liquid biopsy, giventumor heterogeneity and evolution and temporal changes in the host immune system.
• We sought to examine expression of PD-L1 on CTCs as well as characterize rareimmune cell populations with a non-invasive liquid biopsy. Examining dynamicbiomarker changes in longitudinal samples could enable the development of noveldiagnostic tools for response prediction and pharmacodynamics studies related toimmunotherapy.
Simultaneous Characterization and Quantification of Immune Cell Subpopulations andPD-L1 Expressing CTCs in Peripheral Blood of Cancer PatientsRachel Krupa, Robin Richardson, Adam Jendrisak, David Lu, Angel Rodriguez, Mike Malchiodi, Nadia Ebrahim, Sean Nisperos, Aaron Oh, Ryon Graf, Jiyun Byun, Yipeng Wang, Mark Landers, Ryan Dittamore
Epic Sciences, 9381 Judicial Dr., Suite 200, San Diego, CA 92121 epicsciences.com
Blood samples were drawn from 3 healthy donors, 5 non-cancerous lung disease patients, and4 metastatic cancer patients (prior to and on-therapy with checkpoint inhibitor), and sent toEpic Sciences for processing with Epic Sciences’ CTC and immune cell assays.
4) SINGLE CELL DIGITAL PATHOLOGY
1) SLIDE PREPARATION 2) CELL STAINING 3) SCANNING
Nuclear Features Cytoplasmic Features Cell Features
Nuclear Area Cytoplasmic Area AR Expression
Nuc. Convex Area Cyto Convex Area CK Expression
Nuc Major Axis Cyto Major Axis N/C Ratio
Nuclear Minor Axis Cyto Minor Axis
Nuclear Circularity Cyto Circularity
Nuclear Solidity Cyto Solidity
Nuclear Entropy Cyto Entropy
Nuclear Speckling Cyto Speckling
Nucleoli Presence Cyto Presence
CK, CD45, DAPI, PD-L1, etc.
CK Morphology
CD45
Immune Cell Characterization:• Activated T Cells • Regulatory T Cells • Exhausted T Cells• MDSCs• NK cells
CTC Phenotypic Analysis:• PD-L1 protein• Calreticulin• Tumor Cell
Heterogeneity
ArchivableBiobank
CTC analysis
Immune Cell Analysis
CTC Genomic Analysis:• Genomic Instability • Mutational Burden
PD-L1 expression is detectable in two distinct cell populations in the peripheralblood of lung cancer patients and is associated with worse survival1. PD-L1expression was detected within peripheral circulating cells associated with malignancy(CCAM) in 26/112(23%) non-small cell lung cancer patients. Two distinct populations ofnucleated, non-hematolymphoid, PD-L1 expressing cells were identified; A) cytokeratinpositive (CK+, PD-L1+, CD45-) and B) cytokeratin negative (CK-, PDL1+, CD45-). PD-L1+ CCAMs are prognostic for overall survival in lung cancer patients. C) Kaplan–Meierestimates of overall survival of patients stratified by those with >1.1 PD-L1(+) CCAM(gray line) or ≤1.1 PD-L1(+) CCAM (black line).
1Boffa D. J. Cellular Expression of PD-L1 in the Peripheral Blood of Lung Cancer Patients isAssociated with Worse Survival. Cancer Epidemiology, Biomarkers & Prevention. 2017; 26(7):1139-1145.
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PD-L1(+) Peripheral Circulating Cells in Lung Cancer
CD4CD8Ki67DAPI
composite DAPI CK CD45 PD-L1
Cell Ratios (CD4:CD8)
Detecting large scale immune cell changes with the CD4, CD8 Assay. Contrived sampleswere prepared with immunomagnetically purified CD4 and CD8 cells plated in ratios ofapproximately 3:1, 1:1, and 1:3. Table shows measured cell counts as a percentage of totalcells (approximately 1 million total cells per slide).
• Multimodal characterization of both the tumor and host immune system is anunmet medical need for the improved prediction of response to immunotherapy.
• Detection of PD-L1 in circulating cells from NSCLC liquid biopsy samples wasassociated with worse overall survival, highlighting the potential utility of minimallyinvasive liquid biopsies for tumor profiling.
• Epic Sciences has developed tools to simultaneously detect, characterize, andquantify CTCs and rare immune cell subpopulations from a single blood draw.
• Examining dynamic biomarker changes with minimally invasive liquid biopsies inlongitudinal samples could enable the development of novel diagnostic tools forresponse prediction and pharmacodynamics studies related to immunotherapy.
Detecting small scale immune cell changes:quantitation and linearity of the CD8 assay. CD8+ cellswere spiked into healthy donor leukocytes at targetratios of approximately 1 - 9%. After staining andquantification of CD8+ cells, percentages of detectedspiked CD8+ cells for three technical replicates (PercentCD8+ Measured) were plotted against targetpercentages (Percent CD8+ Target). Bars show meanand standard error of the mean.
Schematic of Epic’s CTC platform: CTC enumeration, leukocyte classification, morphology andprotein analyses
1) Nucleated cells from a 10 mL blood draw are plated onto 10-12 slides (approximately 3 million cells/slide)2) Slides are stained with 4',6-diamidino-2-phenylindole (DAPI) and a combination of one or more additional markers, including cytokeratin (CK),
CD45, PD-L1, CD3, CD4, CD8, CD14, Ki-67, PD-1, Lag-3, and Tim-33) Slides are scanned using a rapid fluorescent scanning method, which images each nucleated cell4) All cells are analyzed with a multi-parametric digital pathology algorithm for morphological features and protein expression
Schematic of Epic Single Cell Tools for Immune Monitoring1) A single blood draw is used to make slides for CTC and immune cell analysis. Extra slides are archived for staining at a later date2) Slides can be used for CTC and immune cell characterization as well as downstream genomic analysis
C
CD45PD-L1DAPI
CD3DAPI
Representative images of immune cell staining in control cell lines and healthy donor or patient leukocytes. Cells were plated and stained with DAPIand one or more immune cell markers including CD4, CD8, Ki-67, CD3, PD-L1, CD45, PD-1, Tim-3, Lag-3, and CD14.
CD45Tim-3DAPI
CD4/CD8/Ki-67 CD3 PD-L1/CD45 PD-1 Tim-3 Lag-3 CD14
Lag-3DAPI
CD14DAPI
PD-1DAPI
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P e r c e n t C D 8 + (T a rg e t )
Pe
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CD
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red
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Quantification of CD4 and CD8 positive populations.Leukocytes from five lung disease patients and two healthydonors were plated and stained with CD4, CD8, Ki-67, andDAPI. CD4+ :CD8+ ratios (A) and cell counts per mL of blood(B) were quantified.
Quantification of double positive populations. Scatter plots comparingCD4+Ki-67+ and CD8+Ki-67+ double positive populations in healthy donor andlung disease patient samples (C). CD4+Ki-67+ (D) and CD8+Ki-67+ (E)leukocytes were quantified in healthy donor and patient samples and graphedas a percentage of total leukocytes. CD4+Ki-67+ and CD8+Ki-67+ double positivevalues were also graphed as a percentage of total CD4+ (F) or total CD8+ (G)leukocytes, respectively.
Representative scatter plotsdemonstrating CD4, CD8, andKi-67 threshold determinationin a healthy donor sample.Healthy donor leukocytes wereplated and stained with CD4,CD8, Ki-67, and DAPI. Meanfluorescent intensity (MFI) wasplotted for approximately 3million cells to generatehistograms and determinepositivity thresholds for eachmarker, and to quantify CD4+
and CD8 + cell counts.Thresholds were applied toscatter plots for quantificationof double positive values forCD4+Ki67+ and CD8+Ki-67+.
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Changes in CD4, CD8, and Ki-67 positive populations were detected in metastatic cancer patient samples upon treatment with PD-L1 inhibitor.Baseline and cycle 3 samples were collected for four metastatic cancer patients undergoing PD-L1 inhibitor therapy. Percent change was calculatedfor CD4+Ki-67+ and CD8+Ki-67+ populations between baseline and cycle 3 samples (A and B). CD4+Ki-67+ and CD8+Ki-67+ percentages werequantified per total CD4+ and CD8+ cells, respectively. Six replicates from a single healthy donor were stained along with patient samples to serve ascontrols. For percent change analyses, replicates were analyzed as pairs to mimic baseline and on-therapy samples. CD4+:CD8+ ratios weredetermined for patients and healthy donor samples (C). Percent change between baseline and on-therapy was calculated for patient samples andhealthy donor replicates were analyzed as pairs (D).
composite DAPI CK CD45 PD-L1
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