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Datasets Discovered: New Cell Lines & PDX Datasets in Lumin Bioinformatics

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Importance of the Dataset

Champions’ PDX models across several indications, including AML (acute myeloid leukemia), H&N (head and neck cancer), NSCLC (non-small cell lung cancer), lymphoma, ovarian, prostate, and melanoma, 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. All of these model cohorts have been recently added to our revolutionary data analysis and visualization platform, Lumin Bioinformatics, and include diverse molecular features, next generation sequencing (NGS), proteomics and phospho-proteomics.

In addition, NGS data from 93 human cancer cell lines are now available spanning across many cancer types (Figure 1) and can be interrogated in numerous visualization modules within Lumin.

Lumin Datasets Discovered

Experimental Design

Each PDX model included in these cohorts was characterized by NGS (WES and RNA-seq), proteomics and phospho-proteomics analyses. Our NGS workflow is a multi-step procedure; specifically, a PDX tumor sample undergoes preparation by thawing and subsequent extraction of gDNA and RNA. A library is then prepared and NGS is performed using Illumina Nextseq2000. Subsequently, raw data is collected and processed into a FASTQ file, which is sent to a bioinformatician for data analysis. Throughout the NGS workflow, stringent quality standards are applied, ensuring the generation of high-quality sequencing data. Finally, data is uploaded and stored in the user’s unique Lumin instance, where it can be visualized and further analyzed in various modules.


Champions has partnered with BGI Genomics to obtain proteomics and phospho-proteomics data; specifically, proteins are extracted from cells and/or tissues to obtain a protein mixture, which are broken down by digestion enzymes to yield a peptide mixture. This peptide mixture undergoes phospho-peptide enrichment to give a phospho-peptide mixture, which is then analyzed by LC/MS, using label-free data-independent acquisition (DIA) for data quantification.


Applications of the Dataset

All model cohort datasets listed above have been integrated into our revolutionary visualization and data analytics software, Lumin Bioinformatics, and is available with subscription access. Several analysis and visualization modules within Lumin are available to interrogate these newly added datasets.

  • Network Viewer: Within the network viewer, users can color protein nodes based on gene expression, mutational status, kinase activity, quantitative protein expression or include molecular signatures. This tool overlays proteomics data from Champions’ PDX models or the public CPTAC database.
  • Mutation Mapper: Researchers can visualize protein amino acid domains and identify mutations within Champions' PDX models. Through Champions’ phospho-proteomic sequencing, phosphorylation sites identified within our tumor bank were detected, and are aligned within the context of protein amino acid domains. Users can also visualize phosphorylation sites detected within the public CPTAC database as well as those predicted by PhosphositePlus.
  • Clustergrammer: Researchers can leverage Champions' clustering tools to interrogate Champions’ PDX gene expression, proteomics, phospho-proteomics, kinases and public data sets using a clustering heatmap. Users can also overlay mutation and agent response data.
  • Molecular Graphing (NEW): Users can use the molecular graphing tool to create box plots for Champions’ PDX models and display either gene expression or proteomics data. Users can also visualize gene expression of their target gene in Champions’ cell line dataset.
  • Lumin Workspaces: Users can analyze rich multi-omic data in our secure, collaborative cloud-based computing environment by writing 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).

Lumin Bioinformatics is the ideal software for cancer research, as it enables scientists to harness the power of computational science in a convenient and sophisticated tool. We invite you discover these new datasets, explore these modules and more by accessing the power of Lumin Bioinformatics today.

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