Abstract 294: ChemoINTEL: A high-throughput, multi-parametric compound screening platform for intelligent lead compound and therapeutic combination identification

Pierian Biosciences has developed the ChemoINTEL platform for high-throughput, semi-automated quantification of cellular responses to chemotherapeutics. ChemoINTEL relies on a microscopy-based process that captures and analyzes single cell behavior to reflect responses within a population. The platform is customizable to a variety of small molecule panels, either specific to certain tumor types or for titration screening of small molecules in development. Automated imaging of each well of a 384-well plate over time provides real-time kinetic response data under a variety of treatment conditions. Brightfield and fluorescent images are used to determine quantitative changes in morphology and molecular metrics reflecting induced apoptosis and cell death. Unique to ChemoINTEL as a drug screening platform is the quantification of intensity values, at the single cell level versus whole well fluorescence, for each fluorescent probe at each timepoint through a high-throughput analysis routine. These data are further processed through an internally developed algorithm to compare a treated population’s response relative to an untreated control and reports a sensitivity score. By combining different treatment conditions, the platform provides intelligent design of single agent or combination treatment approaches. By analyzing individual cells in the population, ChemoINTEL aids in better understanding response of tumor cell sub-populations to different chemotherapeutic agents. As a compound library screening tool or potential clinical diagnostic, Pierian Biosciences’ quality-controlled processes ensure all its equipment, reagents and processes follow ISO17025 guidelines to ensure the quality of all data generated. Each assay is internally controlled to include a standard cell line, whose response is monitored for accuracy of the reported results. In collaboration with several biorepositories and through the development of a standardized dissociation approach resulting in purification of viable primary tumor cells, the ChemoINTEL platform is also under development to assess chemotherapeutic response within patient populations. In conjunction with the ChemoINTEL platform, Pierian Biosciences has also developed a sophisticated multi-color flow cytometry platform (ImmunoINTEL) that when used in conjunction with ChemoINTEL provides information on the purity of isolated primary tumor cells prior to plating, as well as information on the cell populations present within the tumor microenvironment. These two platforms can be further complexed to evaluate immunotherapies in combination with front-line therapies. In summary, Pierian Biosciences has developed a high-throughput, multi-parametric platform for both drug development and diagnostic applications.

Note: This abstract was not presented at the meeting.

Citation Format: Kellye C. Kirkbride, Kevin J. Polach, Samantha J. Braxton, Megan D. Hoeksema, Dustin C. Rogers, Patricia Ladd-Ward, Durdica Vojnic Zelic, Santosh Putta, Matt Westfall, Norman Purvis. ChemoINTEL: A high-throughput, multi-parametric compound screening platform for intelligent lead compound and therapeutic combination identification [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 294.

Automated flow cytometric profiling of tumor heterogeneity, tumor-infiltrating leukocyte (TIL) exhaustion, and coexpression of checkpoint receptors/ligands in patient-derived carcinomas

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Background: Clinical benefits of immune checkpoint receptor (ICP-R) blockade in cancer patients can be predicted using various biomarkers such as Immune Index. However, traditional IHC approaches are lacking in sensitivity and in addressing the heterogeneity of the tumor microenvironment (TME), TIL functional status, expression of targetable ICP-R and their ligands (ICP-L), and detection of rare immune subsets within the TME. Methods: We developed a flow cytometry platform (ImmunoINTEL™) that delivers quantitative, clinically relevant information by merging these aspects of tumor biology into a single automated HTP assay comprised of multi-parameter Ab panels and automated sample/data processing procedures for immunophenotyping of blood and tissue specimens from patients with lung, breast, renal, and colorectal carcinomas. Results: Analysis of tumor specimens revealed distinct immune profiles characterized by variations in TIL makeup, differential expression of ICP-R and ICP-L (PD1/PDL1, TIGIT/CD112&CD155, Tim-3/Galectin-9, SIRPa/CD47), and changes in the functional/exhaustion status of TILs. We observed several discrete carcinoma profiles characterized by (1) an elevated Treg : CD8+GZMB+ T cell ratio, (2) high expression of ICP-L on epithelial cells and myeloid TILs, (3) enrichment for M1 macrophages (Mφ), M2 Mφ, and mixed M1/M2 phenotype Mφ (4) elevated levels of myeloid cells with suppressive phenotypes (MDSCs), (5) significant presence of myeloid and plasmacytoid dendritic cells, and (6) enrichment for mesenchymal cells. The elevated expression of several ICP-Ls on TILs and ICPs on epithelial cells suggested tumor- and TIL-intrinsic mechanisms modulating checkpoint interactions. Conclusions: The heterogeneity of TILs and ICP-R/ICP-L expression profiles across cell and tumor types can be explored in proof-of-mechanism studies and clinical trials to provide a rational for targeting distinct ICP-R/ICP-L interactions and TIL exhaustion mechanisms with immunotherapeutics, and for more refined selection of potential responders to ICP inhibitors.

Cell signaling-based classifier predicts response to induction therapy in elderly patients with acute myeloid leukemia

Single-cell network profiling (SCNP) data generated from multi-parametric flow cytometry analysis of bone marrow (BM) and peripheral blood (PB) samples collected from patients >55 years old with non-M3 AML were used to train and validate a diagnostic classifier (DX_SCNP) for predicting response to standard induction chemotherapy (complete response [CR] or CR with incomplete hematologic recovery [CRi] versus resistant disease [RD]). SCNP-evaluable patients from four SWOG AML trials were randomized between Training (N = 74 patients with CR, CRi or RD; BM set = 43; PB set = 57) and Validation Analysis Sets (N = 71; BM set = 42, PB set = 53). Cell survival, differentiation, and apoptosis pathway signaling were used as potential inputs for DX_SCNP. Five DX_SCNP classifiers were developed on the SWOG Training set and tested for prediction accuracy in an independent BM verification sample set (N = 24) from ECOG AML trials to select the final classifier, which was a significant predictor of CR/CRi (area under the receiver operating characteristic curve AUROC = 0.76, p = 0.01). The selected classifier was then validated in the SWOG BM Validation Set (AUROC = 0.72, p = 0.02). Importantly, a classifier developed using only clinical and molecular inputs from the same sample set (DX_CLINICAL2) lacked prediction accuracy: AUROC = 0.61 (p = 0.18) in the BM Verification Set and 0.53 (p = 0.38) in the BM Validation Set. Notably, the DX_SCNP classifier was still significant in predicting response in the BM Validation Analysis Set after controlling for DX_CLINICAL2 (p = 0.03), showing that DX_SCNP provides information that is independent from that provided by currently used prognostic markers. Taken together, these data show that the proteomic classifier may provide prognostic information relevant to treatment planning beyond genetic mutations and traditional prognostic factors in elderly AML.

Validation of cell-based fluorescence assays: practice guidelines from the ICSH and ICCS - part III - analytical issues

Clinical diagnostic assays, may be classified as quantitative, quasi-quantitative or qualitative. The assay's description should state what the assay needs to accomplish (intended use or purpose) and what it is not intended to achieve. The type(s) of samples (whole blood, peripheral blood mononuclear cells (PBMC), bone marrow, bone marrow mononuclear cells (BMMC), tissue, fine needle aspirate, fluid, etc.), instrument platform for use and anticoagulant restrictions should be fully validated for stability requirements and specified. When applicable, assay sensitivity and specificity should be fully validated and reported; these performance criteria will dictate the number and complexity of specimen samples required for validation. Assay processing and staining conditions (lyse/wash/fix/perm, stain pre or post, time and temperature, sample stability, etc.) should be described in detail and fully validated.

Development and validation of a single-cell network profiling assay-based classifier to predict response to induction therapy in paediatric patients with de novo acute myeloid leukaemia: a report from the Children's Oncology Group

Single cell network profiling (SCNP) is a multi-parameter flow cytometry technique for simultaneous interrogation of intracellular signalling pathways. Diagnostic paediatric acute myeloid leukaemia (AML) bone marrow samples were used to develop a classifier for response to induction therapy in 53 samples and validated in an independent set of 68 samples. The area under the curve of a receiver operating characteristic curve (AUC(ROC)) was calculated to be 0·85 in the training set and after exclusion of induction deaths, the AUC(ROC) of the classifier was 0·70 (P = 0·02) and 0·67 (P = 0·04) in the validation set when induction deaths (intent to treat) were included. The highest predictive accuracy was noted in the cytogenetic intermediate risk patients (AUC(ROC) 0·88, P = 0·002), a subgroup that lacks prognostic/predictive biomarkers for induction response. Only white blood cell count and cytogenetic risk were associated with response to induction therapy in the validation set. After controlling for these variables, the SCNP classifier score was associated with complete remission (P = 0·017), indicating that the classifier provides information independent of other clinical variables that were jointly associated with response. This is the first validation of an SCNP classifier to predict response to induction chemotherapy. Herein we demonstrate the usefulness of quantitative SCNP under modulated conditions to provide independent information on AML disease biology and induction response.

National biosecurity approaches, plans and programmes in response to diseases in farmed aquatic animals: evolution, effectiveness and the way forward

The rapid increase in aquaculture production and trade, and increased attention to the negative effects of disease, are becoming stimuli for developing national biosecurity strategies for farmed fisheries, for which the World Organisation for Animal Health (OIE) Aquatic Animal Health Code and Manual of Diagnostic Tests for Aquatic Animals serve as an excellent framework. Using examples from a few countries and selected diseases, this paper provides a general overview of the development of approaches to implementing biosecurity strategies, including those emerging in the national legislation and regulations of some countries, and those being initiated by industries themselves. The determination of disease status in different epidemiological units (from a farm to a nation), appropriate approaches for preventing the introduction of disease and developing contingencies for disease control and eradication are also discussed. Important to the effectiveness of such strategies are provision of financial, personnel and other resources to implement them, including incentives such as indemnification or compensation in eradication programmes, and practical linkage to regulatory or government policy initiatives.

Multi-platform, multi-site instrumentation and reagent standardization

As flow cytometry laboratories involve themselves in more multi-site domestic and international clinical trial and research studies, it becomes imperative that they develop and adopt qualitative and quantitative standardization. This standardization does not need to be at the instrument-design level but it may evolve from a general consensus on instrument setup, internationally accepted standardized procedures, and quantitative fluorescence intensity units. Instrument condition, age, and setup as well as model and manufacturer all affect the overall instrument performance and quantitative characteristics. Therefore, when working with multiple instruments, platforms, or sites, a standard window of analysis is essential. Furthermore, we should strive to characterize instrument performance and quantitative indices so that data can be compared directly. The same thoughts and ideals hold true for standardizing procedures and reagents. Clones, conjugation, incubation times, pH, temperature, and other environmental conditions all combine to affect the qualitative and quantitative cellular indices that we are attempting to measure. Data are presented that illustrates why standardization is needed and how we have attempted to achieve it in our laboratories.