Lumin Bioinformatics Spotlight: Feature Exploration

Aug 26, 2021 11:00:00 AM / by Champions Oncology

person accessing Lumin platform on a laptop

Champions Oncology is illuminating the cellular dynamics of cancer by providing a tool to accelerate biomarker discovery for all cancer researchers. Champions proprietary PDX (patient-derived xenograft) models have been shown to recapitulate patient response to clinical treatments1. The Lumin Bioinformatics platform incorporates NGS and proteomic data obtained from Champions unique and highly characterized PDX tumor bank as well as publicly available data sets (i.e. TCGA, CPTAC, GEO).

Lumin Bioinformatics is a revolutionary data interpretation software capable of analyzing proteomic, genomic, and transcriptomic datasets in real time, providing scientists with the ability to gain novel insights at their fingertips. The power of Lumin is in the ability to explore and perform analysis on rich and unique datasets assembled from over 25,000 cancer patients, including thousands of clinical treatment responses not available in any public dataset. Champions’ Lumin offers a range of analysis and visualization tools that can be utilized in all stages of drug development. In this blog, we highlight some of the features currently available within Lumin Bioinformatics.

Lumin on laptop

Networks

Within this interactive module, users can build protein-protein interaction maps, which leverage data from the Pathway Commons database. Researchers can select genes of interest to explore known protein interactions and export viewed interactions complete with public references. Within the network viewer, users can color protein nodes based on gene expression, mutational status, quantitative protein expression or include molecular signatures. This tool overlays proteomics data from Champions’ PDX models or the public CPTAC database (additional upgrades required). Users can then evaluate quantitative protein expression and specific phosphorylation status across cancer types or within a defined tumor model.

 

Gene & Molecular Signatures

In our gene signature and molecular signature modules, users can upload datasets to build their own gene signatures or access several preloaded molecular signatures that leverage in vivo response and clinical data from Champions' PDX models, TCGA, Broad Achilles or CPTAC databases.

 

t-SNE Clustering & Clustergrammer

Researchers can leverage Champions' proprietary clustering tools to interrogate Champions’ PDX models and TCGA public data sets using t-SNE and UMAP distributions. Users can also overlay gene expression or agent response data.

T-SNE graph - UMAP Clustering

 

Binarize Datasets

In this module, users can compare gene expression across model cohorts by interrogating existing as well as customized gene signatures of any two variables to perform correlative and causative analyses. Users can input their pharmacological drug study data (%TGI or IC50 values) and run differential analyses to identify genes or mutations that are significantly up- or down-regulated in the context of model sensitivity or resistance.

 

Synergy

This module allows users to upload plate maps and response data from their drug combination studies to calculate synergy, additivity, or antagonism via Loewe, Bliss, ZIP, HSA test. Results are displayed as a table, heat map and 3D volcano surface plot, which allows the researcher to easily visualize drug combination synergy.

 

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.

 

Oncoprint

This tool allows for visualization of genetic alterations in user defined genes across Champions' PDX models.

 

Dependency Mapper

In this module, a machine learning model (gradient boost machine) was trained using the DepMap-CCLE data to predict the survival dependencies of cells on a list of genes. The prediction works based on the transcriptional and mutational profile of cells, and outputs the predicted dependencies for each gene as either a negative or positive value, based upon knockdown of a particular gene and/or disruption of the gene’s function.

 

GSVA Pathways

The Gene Set Enrichment Pathways feature provides a standard ssGSEA (single-sample gene set enrichment analysis) enrichment score for our PDX models.

 

Throughout Lumin, users may easily collect and export their findings either as PNG images or CSV files. In addition to the modules mentioned above, Champions’ Lumin Bioinformatics software offers access to additional tools that perform advanced analytics and apply AI. Lumin Bioinformatics is the ideal software for cancer research in that it is enables scientists to harness the power of computational science in a convenient and sophisticated tool. We invite you to access the power of Lumin Bioinformatics today, through a FREE 14-Day Trial.

 

      Trial Version - Lumin Bioinformatics - Click to Access Lumin Now           Request a Live Demo of Lumin

 

 


1] Izumchenko E, Paz K, Ciznadija D, Sloma I, Katz A, Vasquez-Dunddel D, Ben-Zvi I, et. al. Patient-derived xenografts effectively capture responses to oncology therapy in a heterogeneous cohort of patients with solid tumors. Ann. Oncol. 2017; 28: 2595–2605. https://doi.org/10.1093/annonc/mdx416.

Tags: Lumin Bioinformatics