Champions Oncology is illuminating the cellular dynamics of cancer by providing a tool to accelerate biomarker discovery for all researchers in both academia and industry. Champions was founded on the premise that our PDX (patient derived xenograft) models recapitulate actual patient responses. Our own proprietary PDX bank data, in conjunction with public data sets (i.e. TCGA, CPTAC, GEO), are incorporated into our bioinformatics platform, Lumin.

We recently added Lumin Workspaces to our existing suite of Lumin Bioinformatics products. Building upon our Lumin Bioinformatics platform, Lumin Workspaces allows users to use custom code in any programming language (i.e. R, Python, Julia) within Jupyter notebooks to interrogate and analyze Champions’ bioinformatics datasets (RNA-seq, WES, proteomics, TGI, clinical data) and public access datasets (TCGA, CPTAC) in a secure, collaborative environment.

Bioluminescent imaging (BLI) is non-invasive method that allows for real-time imaging of cells or tissues in living organisms. Mice have become the primary model used for BLI, and the field of preclinical oncology has made great strides in basic research and drug screening with BLI-based murine tumor models. Here we highlight how BLI-based tumor models can be used to quantify tumor burden over time and how this application is particularly well-suited to drug and biologic screening.

Clinical flow cytometry is now a standard tool used by clinical researchers in numerous fields, especially immuno-oncology. Consider these “Do’s & Don’ts” of clinical flow cytometry as you decide to use this tool for clinical research.

Humanized immune system (HIS) mice are valuable models for preclinical oncology research because they can tolerate tumor xenografts and can be used to assess responses to novel drugs, biologics, or adaptive cell therapies. Cell-line derived xenografts (CDX) are commonly used in HIS mice for these preclinical studies because they have defined properties and genomic sequences and are ideal for screening targeted therapies. Here we highlight features of HIS models that use CDX and compare this approach with patient-derived xenografts (PDX).

RNA and DNA analysis methods have improved dramatically in the last decade, and one of the most widely used methods across disciplines is RNA sequencing (RNA-seq), which detects and quantifies messenger RNAs (mRNAs) in either pooled tissue or cell samples. Single cell RNA sequencing (scRNA-seq) measures mRNAs present in individual cells and is now one of the most widely used techniques for characterizing cellular responses^[1]. scRNA-seq is especially useful for preclinical oncology studies that compare transcriptomic differences between normal and malignant tissue or is used to analyze intratumoral heterogeneity^[2].

Acute myeloid leukemia (AML) is an aggressive hematological malignancy that has been treated in the same way for the last several decades and typically includes standard chemotherapy protocols as well as bone marrow (BM) transplantation.  Despite advances in the field of immunotherapy, AML has been challenging to treat with immune checkpoint inhibitors that target Programmed Death (PD) - 1/PD-Ligand (L) 1 inhibitors.

Importance of the Dataset

Champions’ PDX and Hematological models are well-characterized and include patient clinical attributes, disease status, treatment history and in vivo drug responses to a range of Standard of Care therapies. New NGS datasets spanning across various indications, have been recently added to our software platform, Lumin Bioinformatics, specifically 114 model datasets of RNA-Seq and 148 model datasets of WES. Below, we illustrate the model disease types that have been added to Lumin Bioinformatics that have both RNA-Seq and WES datasets.

Lung cancer remains one of the leading causes of cancer-related deaths, and non-small cell lung cancer (NSCLC) is the most common form of lung cancer and is typically diagnosed at advanced stages^[1]. Extensive genomic studies of NSCLC have been essential to identifying mutations that drive oncogenesis and has been critical to the development of targeted therapies. Here we highlight progress in NSCLC treatment and identify areas of ongoing research.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most common and aggressive forms of pancreatic cancer that has remained difficult to diagnose early and treat successfully. PDAC has a five-year survival rate below 10% and is one of the leading causes of cancer death. Complete surgical resection is one of the few curative treatment modalities, and chemotherapy protocols have limited efficacy^[1].

Mouse models have been the workhorses of preclinical immuno-oncology (IO) research, and advances in mouse model development have expanded to applications for nearly all types of solid tumors and hematological malignancies. Preclinical evaluation of experimental immunotherapies has been advanced by syngeneic and humanized mouse models. Syngeneic mice are one of the most established types of models used in cancer research, whereas humanized mice are contemporary mouse model that has been critical to the screening of immunotherapeutic agents. Here we highlight features of syngeneic and humanized mouse models and define which models are most relevant to different phases of preclinical IO research.