Publications

517 Publications Available
January 01, 2019
Nature Medicine

UCSF (1) CTD2 researchers identified a synthetic lethal interaction between EGFR tyrosine kinase inhibitors and Aurora kinase inhibitors in acquired resistant cells. This study suggests combinatorial treatment to prevent treatment resistance with the monotherapies.

December 26, 2018
Cell Systems

Bioinformatic approach, Similarity Weighted Nonnegative Embedding (SWNE), enables visualization of single-cell gene expression data into biologically relevant factors.

December 24, 2018
OncoImmunology

UCSD study suggests that the combination of APOBEC-related mutagenesis and tumor mutation burden may be used as a biomarker of response to immunotherapy.

December 21, 2018
Nature Communications

Researchers at DFCI analyzed genome-scale loss-of-function datasets and identified adenosine deaminase acting on RNA as a gene dependency in subsets of lung cancer.

December 21, 2018
Cancers

Analysis of next generation sequencing of patients with hematologic malignancies showed that patients had alterations that could be targeted with gene or immune-targeted therapies.

December 17, 2018
Cold Spring Harbor Molecular Case Studies

Scientists report that two myeloid leukemia cases with FMS-like tyrosine kinase (FLT3) fusions demonstrate mixed features of myelodysplastic and myeloproliferative syndromes; showed sensitivity to FLT3 inhibitors in ex vivo drug screening assays.

December 13, 2018
Cell

CTD2 scientists at Stanford University demonstrated that air-liquid interface patient-derived tumor organoid models retain the original tumor immune cells, enabling testing for personalized immunotherapy in cancer.

November 29, 2018
Journal of Molecular Cell Biology

CTD2 researchers at Emory University identify novel role for large tumor suppressor 2, LATS2, as a regulator of the ASK1-mediated stress response pathway which may lead to new strategies to control cellular response to stress in normal cells and diseases.

November 28, 2018
Cell Systems

UCSF scientists developed a bioinformatic approach, MAGNETIC, which integrates multi-omic data from cancer patients with pharmacogenomic data from cell lines into a small set of pathway-enriched gene modules. These modules connect tumor and cell line biomarkers and may inform therapeutic targets.

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