May 23, 2018
Cell Systems

Integration of genome-scale RNAi and CRISPR-Cas9 screens across cancer cell lines with large protein-protein interaction networks revealed novel protein complexes.

May 22, 2018
Nature Communications

Scientists established a panel of patient-derived xenografts (PDXs) from subtypes of T-cell lymphomas (TCL) and cell lines for target validation and drug testing. Stapled peptide ALRN-6924 which blocks interactions between p53, MDM2 and MDMX showed pre-clinical activity against TCL lines and PDXs.

May 14, 2018
Cancer Cell

Researchers performed an integrated analysis of TCGA genomic data and CPTAC proteomic data and demonstrated that A-to-I RNA editing contributes to proteomic diversity in breast cancer.

May 11, 2018
Clinical Cancer Research

CTD2 scientists at Fred Hutchinson showed that the triplet combination of WEE1 tyrosine kinase inhibitor AZD1775, cisplatin, and docetaxel is safe and tolerable in a phase I clinical trial of head and neck cancer.

May 03, 2018

CTD2 scientists at UTSW employed a chemistry-first approach to map the associations between chemicals and genetic lesions in lung cancer. These chemical vulnerabilities may reveal novel druggable targets for lung cancer.

April 25, 2018
Cell Systems

Researchers at the UCSD CTD2 Center created a parsimonious composite network (PCNet), which has high efficiency and performance over any single network.

April 24, 2018

Broad Institute CTD2 scientists developed a bioinformatic approach, RWEN, that predicts the responses of human cancer cell lines to a panel of compounds using the gene-expression profiles.

April 17, 2018
Cell Reports

CTD2 researchers at UCSF-1 present a quantitative map linking the influence of chemotherapeutic agents to tumor genetics. This chemical-genetic interaction map can aid in identifying new factors that dictate responses to chemotherapy and prioritize drug combinations.

April 16, 2018
Nature Communications

Scientists developed metaVIPER to assess protein activity in orphan tissues and single cells by integrative analysis of multiple, non-tissue-matched regulatory models. This approach could help to identify critical dependencies within molecularly heterogeneous sub-populations of cancer tissues.

April 14, 2018

Researchers developed MethylMix 2.0, an algorithm implemented in R that facilitates automated downloading and preprocessing of DNA methylation and gene expression datasets from pan-cancer studies. The tool can be used to identify disease specific hyper and hypomethylated genes and cancer subtyping.