Name: High-Definition Spatial Proteomics for Characterizing the Tumor Microenvironment
Start: 2020-09-23T19:00:00Z
End: 2020-09-23T19:00:34.000Z
Location: BrightTALK
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Champions Oncology delivers innovative solutions to oncology drug development, accelerating the journey from the research bench to the clinic – decreasing timelines, lowering costs, and ultimately saving patient lives.  Learn more about Champions Oncology's capabilities, our service platforms and educational topics affecting our industry on our Webinar Channel.

Fibroblasts can play a significant role in resistance to therapy. In the context of cancer cancer-associated fibroblasts (CAFs) in the TME have been associated with resistance to various therapeutic approaches. CAFs can contribute to therapy resistance through multiple mechanisms, including extracellular matrix remodeling, immune modulation, angiogenesis, and paracrine signaling. Understanding the intricate interactions between fibroblasts and cancer cells is crucial for developing more effective therapeutic strategies and overcoming resistance to cancer treatment.

In the pre-clinical stages of therapy testing, the use of clinically and biologically relevant models is essential. However, current preclinical tumor models often lack a comprehensive characterization of the TME. To address this limitation, Champions Oncology utilized transcriptomic data from its exclusive (TumorGraft) PDX models bank and analyzed the data with xCell computational method to identify molecular signatures predictive of fibroblast presence.

In this short AACR Poster QuickTake, we will take a deep dive into a novel gene signature that predicts fibroblast composition in the TME, allowing for an improved selection of PDX models for preclinical studies.

Poster QuickTake: A Novel Gene Signature predicting TME Fibroblast Composition

Acute myeloid leukemia (AML) poses a significant therapeutic challenge, with a rising incidence in recent times. This clonal hematopoietic disorder of progenitor and stem cells exhibits aggressive behavior, and despite initial remission, recurrence is common. The conventional shift from chemotherapy to monoclonal antibodies and antibody-drug conjugates (ADCs) has been hindered by the absence of AML-specific antigens. Notably, CD33, expressed strongly in 80–90% of AML cells, has become a target for gemtuzumab-ozogamicin (Mylotarg), the sole FDA-approved ADC for AML treatment.

While advancements in understanding AML molecular mechanisms have influenced clinical approaches, the lack of clinically representative models hinders therapeutic progress. Existing models, both in vivo and ex vivo, struggle to capture the heterogeneity and complexity of AML. Addressing this, we present our proprietary assay, Champions’ AML VitroScreen, designed for testing therapeutic candidates in primary AML samples. Our diverse bank of deeply characterized AML samples encompasses multiple subtypes, allowing the evaluation of therapeutic responses through cell viability, proliferation, and clonal composition analyses.

In this Poster QuickTake, we take a deep dive into the correlation between gemtuzumab-ozogamicin efficacy and CD33+ expression in AML primary samples using Champions' novel AML VitroScreen.

Poster QuickTake: Mylotarg Efficacy and CD33+ Expression in AML Correlation

Join Champions Oncology for an exclusive live webinar focused on the pivotal role of Receptor Occupancy (RO) assays in clinical trials. 

Key Learning Objectives:
• Deep-Dive into RO Assay Types: Gain a detailed understanding of the different types of RO assays available and learn to select the one that perfectly aligns with your clinical project needs.
• Critical Development Considerations: Uncover the essential considerations that guide the development of a robust RO assay and ensure reliability in a clinical setting.
• Flow Cytometry Validation Mastery: Equip yourself with the necessary skills to validate RO assays for flow cytometry with confidence, enhancing the accuracy and impact of your clinical trials.

By attending this webinar, you're not just accessing information; you're joining a community of expert scientists determined to make a mark in the fight against cancer. Whether you're aiming to refine an existing assay in-house or planning future assays for upcoming clinical trials, this comprehensive guide to RO assays is an indispensable asset.

Receptor Occupancy Assays: A Comprehensive Guide for Clinical Trial Success

Acute Myeloid Leukemia (AML) is a highly heterogeneous disease with a diverse range of abnormal myeloid subpopulations resulting in challenges in clinical diagnosis and treatment. Many methods such as flow cytometry are used to provide precise information for risk stratification and treatment methods. Flow cytometry utilizes the expression patterns of cellular markers to characterize the high diversity in AML subpopulations with high sensitivity and specificity. This coupled with rapid analysis timelines allows for flow cytometry to be an excellent tool for the identification of AML lineage and progression through both phenotypic analysis and difference from normal. As AML lineage and disease progression are predictors of residual disease and relapse, the need for effective and accurate characterization of AML populations is critical.

In this Poster QuickTake, we take a deep dive into immunophenotyping using high-complexity flow cytometry in AML.

Poster QuickTake: Immunophenotyping via High Complexity Flow Cytometry in AML

Acute myeloid leukemia (AML) is the most common hematological malignancy found in acute leukemia patients. There is shown to be a strong genetic correlation to mechanisms of drug resistance/ sensitivity in AML. e.g.FMS-like tyrosine kinase 3 gene (FLT3) mutation occurs in about 30% of patients. In 2019, a phase 3 clinical trial suggested that gilteritinib treatment resulted in significantly longer survival than salvage chemotherapy in relapsed or refractory FLT3-mutated AML patients. Targeting FLT3-mutant (mut) in AML has become one of the important therapeutic strategies in this decade. Besides, TP53 mut, TET2 mut, and the overexpression of various drug-resistance genes were also reported as important biomarkers that impact the sensitivity of drug treatments.

Champions Oncology’s hematological VitroScreen platform provides user with a powerful and cost-friendly option to screen the performance of new FLT3 inhibitors or other novel anti-neoplastic test agents. In addition, the Lumin platform integrates Champions’ tumor model multi-omic data and public datasets in one accessible platform for model selection and data interpretation. We can apply the system biological method to categorize and design the test groups and predict the therapeutic outcome.

In this Poster QuickTake, we take a deep dive into the systemic analysis of gene mutations and therapeutic efficacy using the ex vivo hematological VitroScreen platform.

Poster QuickTake: Systematic Analysis of Mutations & Efficacy via VitroScreen

There is a growing need to recreate a relevant tumor immune microenvironment (TIME) that is easily traceable to quickly delineate the effect of fine-tuning the different compartments.

Recent advances in Champions' TumorGraft3D (CTG3D) platform have not only generated robust models for preclinical drug evaluation but also elevated the translational relevance by efficiently mimicking the interactions between cancer organoids and immunocytes. Currently, available analytic approaches for coculture models are limited and are highly reliant on flow cytometry and high-resolution confocal imaging endpoints. These are often slow, cost-inefficient, and cloud computing heavy thereby limiting the bandwidth of studies and decision-making.

Easily traceable tags (e.g. bioluminescent and fluorescent) are attractive options that can aid the establishment of reliable effector (E) cells to the tumors (T) cell conditions, thus enabling the user to test multiple test agents cost-effectively and rapidly.

In this Poster QuickTake, we take a deep dive into the development of a bioluminescent 3D tumor platform with immune cell co-culture that can be utilized for high throughput screening.

Poster QuickTake: Bioluminescent 3D Tumors with Immune Cell Co-culture for HTS

Recent advances with engineered co-culture systems, such as microfluidic organ-on-chips, have overcome some of these limitations to better model cell-cell and cell-extracellular matrix (ECM) interactions. The microfluidic nature of these systems enables longer-term cell culture and allows for continuous effluent collection to monitor byproducts for tissue function and viability. They are also designed to recapitulate organ-level structure, function, and physical forces that mimic in vivo cyclic strain and fluid shear stress. Here, we use the Tumor-on-Chip (TOC) model to develop a complex co-culture system of our previously established TumorGraft3D (CTG3Ds) biobank at Champions Oncology.

In this Poster QuickTake, we take a deep dive into tumor-on-chip co-culture systems and their ability to investigate cancer progression.

Poster QuickTake: Tumor-on-Chip Co-culture System

Organoids are 3D in vitro models that recapitulate the structural and functional complexity of the healthy or diseased tissue of origin. The use of organoids represents a step forward in basic and applied research, as it supports and accelerates the investigation of fundamental mechanistic properties of human tissues, such as development, regeneration, and repair, and provides a groundbreaking tool to support drug discovery and personalized medicine by capturing patient specificity while recapitulating in vivo tissue organization and functions in vitro, overcoming conventional 2D cultures and animal models limitations.  Champions Oncology has leveraged a biobank of 1,500+ TumorGraft patient-derived xenograft (PDX) models and 100+ patient primary samples to generate a versatile 3D platform to enhance drug discovery by coupling the assessment of patients’ heterogeneity with the time and cost-effectiveness of an in vitro assay.

Join us for a webinar that provides a thorough analysis of Champions' revolutionary TumorGraft3D platform, an ex vivo multiclonal 3D organ-like tumor culture assay derived from our industry-leading clinically relevant patient-derived xenograft (PDX) models. 

Key Takeaways
Attendees of this webinar will be able to:
• Gain comprehensive insights into the TumorGraft3D platform and its robust capabilities
• Discover specific readouts including cytotoxicity, flow cytometry, high-content imaging, DRUGseq, and luciferase-tagged models for superior research outcomes
• Understand the applications of the platform to refine your preclinical programs

Discover TumorGraft3D: A Technical Deep-Dive for Advancing Oncology Research

Genomic DNA editing is a continuous process that occurs during the entire cell life span. The type and frequency of these modifications can be related to the physiological or pathological activity of intrinsic mechanisms such as DNA surveillance and repair or to extrinsic events that may induce an alteration of DNA sequence by exposure to agents that directly or indirectly induce accumulations of DNA alterations. In the past few years, large-scale analyses have revealed mutational signatures across human cancer types. These signatures can be used as markers of defective internal processes, such as DNA repair deficiency, or external exposures, such as carcinogens, like tobacco, or genotoxic therapies such as radiation and chemotherapy.

In this Poster QuickTake, we take a deep dive into evaluating mutational signatures in PDX models to give a better understanding of drug responses and companion biomarker identification.

Poster QuickTake: Mutational Signatures in PDXs for biomarker identification

By attending this webinar, “Mastering Precision in Clinical Specialty Testing” you will unravel the nuanced effects that Peripheral Blood Mononuclear Cell (PBMC) isolation techniques exert on PBMC phenotypes and recovery, shedding light on pivotal considerations for enhancing the accuracy and effectiveness of your results, ultimately driving success in your clinical trial.

Webinar Key Takeaways: 
• In-Depth Analysis: Gain comprehensive insights into the variety of PBMC Isolation methods, understanding the technical nuances that differentiate each technique.
• Impact Exploration: Discover the detailed effects of these isolation methods on PBMC phenotypes, equipping you with the knowledge to refine your selection process and protocols.
• Timing’s Role: Uncover the critical influence of time - from collection to cryopreservation - on PBMC phenotypes, and how this timeline can significantly impact your research outcomes.

Don’t miss this unparalleled opportunity to enhance your expertise with insights drawn from real-world applications and cutting-edge research. Whether you're refining established studies or embarking on new investigative paths, understanding the influence of PBMC isolation methods on phenotypes and recovery is fundamental to achieving precision and excellence in your assay for clinical specialty testing.

Mastering Precision in Clinical Specialty Testing: The Impact of PBMC Isolation

With an estimated 90% of oncology drugs failing clinical trials, there is a critical need for a more robust approach to preclinical and translational studies in immuno-oncology research.

Advanced approaches to immuno-oncology research are being galvanized with new humanized mouse models and 3D co-culture techniques to better understand therapeutic intervention. However, understanding the best model is critical to building successful IO studies with interpretable readouts.

In this webinar, we will provide insights into immuno-oncology ex vivo assays and in vivo models to help improve the accuracy of preclinical studies.

Autologous Co-culture Models to Humanized Mouse Models: Navigating IO Models

Flow Cytometry can interrogate multiparametric measurements on individual cells and has become a widely used specialty testing platform for clinical trials. In addition to the importance of evaluating single-cell analysis throughout the drug development lifecycle, there are increasingly new flow cytometry instruments being introduced that can enhance the researcher’s ability to produce high-quality patient results. One of the challenges that exist when conducting a global clinical trial is the ability to standardize laboratory flow cytometers across sites while also producing rigorous and comparable results in either an exploratory or critical endpoint analysis.  

Attend this webinar to learn:
• Important considerations when designing and validating cytometry panels for use across multiple sites and instruments.
• Understanding aspects of flow cytometry assessments in either a regulatory or non-regulatory setting.
• Validation of a high-complexity Immuno-Oncology panel to interrogate human patient samples as part of a global clinical trial.

The Power of Global Standardization: Unlock High Quality Flow Cytometry Results

There is a significant need for better understanding of an oncology therapeutic’s mechanism of action while in preclinical studies, to then translate into clinic development. Identification of a companion biomarker to identify patients who will benefit from a given treatment can enable the success of clinical trials. Recent advances in high-throughput multiomics are revolutionizing our understanding of tumor biology.

This webinar will focus on Champions’ multiomics oncology datasets, including genomics, proteomics and phospho-proteomics, and will show how proprietary algorithms are used to reveal mechanisms of action and potential companion biomarkers as part of a preclinical oncology strategy. 

Webinar topics will include:
• Molecular, pharmacological, and phenotypical characterization to develop in-depth multiomic datasets
• Identification of suitable models for drug validation 
• Identification of mechanisms of action
• Identification of predictive biomarkers

About the Presenter:
A molecular biologist by training with PhD in human genetics, Stefano has a strong background in Translational Research in Oncology, with a specific focus on solid tumors and on pediatric oncology. Prior to joining Champions Oncology, Stefano led several collaborative research projects which led to the identification and validation of new therapeutic targets, cancer pathways and gene signatures used to stratify patient population.

Gilad is a systems biologist and a bioinformatician, with PhD in human molecular genetics. Focusing on the holistic perspective of molecular interactions, Gilad has developed algorithms and workflows, which are used for addressing disease and treatment MoA, biomarker and target identification, and sub-classification of patient groups.

Identify MOA and Companion Biomarkers in Oncology using Multi-Omic Analyses

Determining an effective treatment for AML has been challenging due to the heterogeneity of the disease and the diverse subpopulations that drive the disease in each patient. Also, a better understanding of the role of the immune system in AML has created new interest in developing effective therapies for the treatment of patients. Flow Cytometry is used not only for clinical diagnosis of the disease but also for interrogation of the diverse subpopulations that exist within AML to explore more treatments that could lead to a cure.  

Attend this webinar to learn:
• Important considerations when designing cytometry-based assays for hematological malignancy indications.
• The design and development of cytometry-based assays for preclinical and clinical applications.
• Validation of a high complexity 18-color panel to interrogate AML patient samples.

Preclinical & Clinical Immunophenotyping Innovation in Acute Myeloid Leukemia

With an estimated 90% of oncology drugs failing clinical trials, there is a critical need for a more robust approach to preclinical and translational studies. Recent advances in high-throughput proteomics and multiomic analysis are revolutionizing our understanding of tumour biology. In this webinar we’ll discuss how Champions’ multiomics datasets, including proteomics and phospho-proteomics, and proprietary algorithms are used to improve model selection for ex vivo and in vivo studies and to reveal mechanisms of drug sensitivity and resistance. 

Webinar topics will include:
- How to incorporate highly translational cancer models such as PDX, primary models and organoids into an effective preclinical research plan
- Beyond RNASeq: systematic analysis of PDX proteome reveals indication-specific lack of correlation with RNA expression
- Improving the selection of preclinical models with predictive kinase activity and pathway activation scoring
- Using Champions’ Pharmaco-Pheno-MultiOmic (PPMOTM) analysis tools to discover new biomarkers of drug resistance/sensitivity: primary AML (Cytarabine) and Ovarian PDX (Olaparib) case study examples

About the Presenter:
Molecular biologist by training with PhD in human genetics, Stefano has a strong background in Translational Research in Oncology, with a specific focus on solid tumor cancer. Prior to joining Champions Oncology, Stefano supervised XenTech's PDX platform development in collaboration with several clinical centers. Stefano led several collaborative research projects which led to the identification and validation of new therapeutic targets, cancer pathways and gene signatures used to stratify patient population.

Improving Preclinical Study Accuracy Using PDX with Next-Gen Multiomic Datasets

The era of leveraging genomics and transcriptomics has yielded a deeper understanding of the molecular underpinnings of neoplastic transformation and the vulnerabilities within. However, the use of genomics and transcriptomics provides a mere superficial view of the molecular nature of a cell. 

Given the wide array of post transcriptional and post translational regulatory processes that govern cellular dynamics, additional omics types (quantitative proteomics, phosphorylation proteomics, epigenomics, metabolomics, etc.) are needed to capture a more comprehensive understanding of the molecular landscape of a tumor. The deep analyses enabled by such a dataset has the power to reveal unimaginable insight around cellular dynamics and improve the prospects of effective precision medicine. 

Here, we present a deep dive into an analysis module termed Pharmaco-Pheno-Multi Omic (PPMO®) integration used for novel target and comprehensive biomarker discovery. We will feature:

• Details on the analytic scripts, models, and datasets required for building an efficient PPMO® model
• Case Studies highlighting the power of this multiomic workflow

The Omic Revolution: Leveraging Multiomic Integration...

Day 3:  Using Lumin Bioinformatics to Interrogate your Biomarker Hypothesis

Learn more about these topics by registering for this webinar:
• Computational investigation of specific biomarkers within your PPMO model  
• Deriving in-depth biological significance of biomarkers within the PPMO model
• Prioritizing biomarkers from your PPMO model as potential therapeutic targets

Using the Lumin Platform to Build Prediction Models of Olaparib Sensitivity Day3

Day 2:  Enriching your Multi-omic Dataset and Building Highly Predictive Models of Response Sensitivity

Learn more about these topics by registering for this webinar:
• Using PPMO to build highly accurate biomarker prediction models of Olaparib sensitivity in Ovarian Cancer
• Testing a PPMO model on prospective tumor samples to predict sensitivity 
• Utilize pre-built templates and custom code to create multi-omic analyses that will propel your research

Using the Lumin Platform to Build Prediction Models of Olaparib Sensitivity Day2

LUMIN: Harnessing the Power of Pharmaco-omics to Illuminate Tumor Cell Biology

Novel applications for Ex-vivo PDX models of the Tumor Microenvironment

Embracing variation: a multi-batch study delivers robust estimates of efficacy

Fast-tracking C010DS-Zn: PARP1-agonist targeting cancer and M2-like macrophages

Selective Ablation of Malignant Cells using Apoptotic Gene Therapy

Evaluation of Acute Myeloid Leukemia by high parameter flow cytometry

Targeting IDH mutations in Cancer

Human-derived IO preclinical systems—from in vitro to in vivo and back

Tipifarnib as a Precision Therapy for HRAS-Mutant Head and Neck SCCs

Models for evaluating cancerous stem cell-targeting therapeutics

Constrained bicyclic peptide delivery of toxin & immune agonists to solid tumors

Targeting Notch Altered Patient Derived Xenografts (PDX) with AL101

Cell cycle intervention beyond Palbociclib; discovery of a CDK2/4/6 inhibitor

Champions Oncology’s Translational Oncology Summit

The complexity of the TME with variable cellular composition and organization has driven the development of experimental techniques capable of tracking large numbers of biomarkers in tissue with sub-cellular resolution. This webinar will provide an overview of how high-definition spatial proteomics, enabled by Multiplexed Ion Beam Imaging (MIBI), can be used to explore the tumor microenvironment (TME) of tumor biopsy samples with unprecedented depth. MIBI leverages the high resolution of a rastered primaryion beam and the sensitivity of time-of-flight secondary ion mass spectrometry (ToF-SIMS) to image standard frozen or formalin fixed paraffin embedded (FFPE) tissue sections that have been stained with up to 40 different antibodies labeled with metal isotope tags. Masses of detected species are assigned to target biomolecules given the unique label of each antibody. Multi-step processing and segmentation utilizing highly expressed nuclear, membrane, and cytoplasmic markers are then performed to accurately determine cell boundaries. Cell classification is performed to phenotypically characterize the tissue environments and quantify marker expression. Dr. Jason Ptacek, Associate Director of Research Services at IONpath, Inc., will share examples of quantitative single-cell phenotype mapping in tissue analysis applications and review the data analysis methods used to generate actionable insights from this highly multiplexed, spatial proteomic data.

Learn how MIBI provides:
●  Comprehensive, quantitative single-cell phenotyping across tumor samples
●  Characterization of the spatial organization of cell populations of the TME
●  Sensitivity to quantify the expression of markers associated with immune suppression

High-Definition Spatial Proteomics for Characterizing the Tumor Microenvironment

immunohistoche mistry

proteomics

Oncology

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High-Definition Spatial Proteomics for Characterizing the Tumor Microenvironment

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