DNA data development for cancer cell lines and patients

Division Of Basic Sciences - Nci

Investigators

Linked publications, trials & patents

Abstract

Cancer arises in a multi-factorial manner, employing a combination of genetic, transcript of epigenetic alterations to become increasingly undifferentiated, proliferative, invasive and metastatic. Both individual genes and molecular networks advantageous to these changes are altered in this process. Our contention is that to both gain understanding of the disease progression and be able to choose more targeted and efficacious cancer treatments, one needs to be able to place the existing changes in a networked, systems-level context. For anti-cancer drugs, there is knowledge regarding their mechanism of action and biological effects. However, even with this information as exists for FDA-approved and in-clinical-trial drugs, there are generally poorly understood off-target effects. Our approach is to use compound activity and genomic profiling data over well-characterized cell line panels to improve understanding and attempt computational prediction of molecular drug response determinants. In our CellMiner suite of web-applications we provide the functionality to make comparisons between DNA parameters and drug activities as well as other molecular and phenotypic data. We also allow database downloads for the more bioinformatically inclined. In the last year, we have added i) mutational data for a set of 18 triple negative breast cancer PDXs (PMID 39932272), ii) nuclear size analysis, mitochondrial fragmentation, gene knockout and gene knock-in analysis for triple negative breast cancer cell lines (PMID 39041239), iii) DNA methylation, mutation, translocations and DNA copy number for our sarcoma specific web-application, Sarcoma_CellMinerCDB (https://discover.nci.nih.gov/SarcomaCellMinerCDB/), iv) the association of the POL1 inhibitors, BHM-21 and BOB-42 with DNA mutations, copy number and promoter methylation (PMID 40553690) and v) the effect of body methylation on the expression of MGMT and its modulation of response to DNA-alkylating agents in glioblastoma (PMID 40464417).