Supplementary Methods, Figures 1 - 7 from Modeling RAS Phenotype in Colorectal Cancer Uncovers Novel Molecular Traits of RAS Dependency and Improves Prediction of Response to Targeted Agents in Patients
Year: 2023
Type: supplementary-materials
Abstract: PDF file - 219K, Supplemental Figure 1. A We evaluated 4 "RAS" signatures across 4 CRC data sets to assess their ability to discriminate KRAS mutant samples from KRAS wild-type. Supplemental Figure 2. The lower observed RIS of KRAS codon 13 mutated samples relative to KRAS codon 12 mutated samples may be a result of the imbalanced distribution of these mutations in the training data. Supplemental Figure 3. RIS distribution by mutation of KRAS, BRAF, NRAS mutations, and wild-type. Supplemental Figure 4. RAS index score (RIS) for PIK3CA mutant samples by exon in the TCGA CRC cohort. Supplemental Figure 5. Distribution of RIS for the subset of colorectal samples (n=19) within the Cancer Cell Line Encylopedia (CCLE), separated by KRAS codon, BRAF V600E, PIK3CA (KRAS/BRAF wild-type), or wild-type (no KRAS/BRAF/PIK3CA) mutation. Supplemental Figure 6. In the mouse early passage cohort (n=26), our RAS model outperforms the KRAS/BRAF mutation model (p=0.06 vs p > .1, respectively). Supplemental Figure 7. Association of RIS and cetuximab response for metastatic colorectal patients (Khambata-Ford, et al.) Patients annotated according to treatment response: Progressive Disease (PD), Stable Disease (SD) and Partial Response (PR) as well as KRAS mutation status.
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
OpenAlex ID: W4362394785