HLA class I and II genotype of the NCI-60 cell lines

Sixty cancer cell lines have been extensively characterized and used by the National Cancer Institute's Developmental Therapeutics Program (NCI-60) since the early 90's as screening tools for anti-cancer drug development. An extensive database has been accumulated that could be used to select individual cells lines for specific experimental designs based on their global genetic and biological profile. However, information on the human leukocyte antigen (HLA) genotype of these cell lines is scant and mostly antiquated since it was derived from serological typing. We, therefore, re-typed the NCI-60 panel of cell lines by high-resolution sequence-based typing. This information may be used to: 1) identify and verify the identity of the same cell lines at various institutions; 2) check for possible contaminant cell lines in culture; 3) adopt individual cell lines for experiments in which knowledge of HLA molecule expression is relevant. Since genome-based typing does not guarantee actual surface protein expression, further characterization of relevant cell lines should be entertained to verify surface expression in experiments requiring correct antigen presentation

Physical Analyses of E. coli Heteroduplex Recombination Products In Vivo: On the Prevalence of 5′ and 3′ Patches

BACKGROUND: Homologous recombination in Escherichia coli creates patches (non-crossovers) or splices (half crossovers), each of which may have associated heteroduplex DNA. Heteroduplex patches have recombinant DNA in one strand of the duplex, with parental flanking markers. Which DNA strand is exchanged in heteroduplex patches reflects the molecular mechanism of recombination. Several models for the mechanism of E. coli RecBCD-mediated recombinational double-strand-end (DSE) repair specify that only the 3'-ending strand invades the homologous DNA, forming heteroduplex in that strand. There is, however, in vivo evidence that patches are found in both strands. METHODOLOGY/PRINCIPLE FINDINGS: This paper re-examines heteroduplex-patch-strand polarity using phage lambda and the lambdadv plasmid as DNA substrates recombined via the E. coli RecBCD system in vivo. These DNAs are mutant for lambda recombination functions, including orf and rap, which were functional in previous studies. Heteroduplexes are isolated, separated on polyacrylamide gels, and quantified using Southern blots for heteroduplex analysis. This method reveals that heteroduplexes are still found in either 5' or 3' DNA strands in approximately equal amounts, even in the absence of orf and rap. Also observed is an independence of the RuvC Holliday-junction endonuclease on patch formation, and a slight but statistically significant alteration of patch polarity by recD mutation. CONCLUSIONS/SIGNIFICANCE: These results indicate that orf and rap did not contribute to the presence of patches, and imply that patches occurring in both DNA strands reflects the molecular mechanism of recombination in E. coli. Most importantly, the lack of a requirement for RuvC implies that endonucleolytic resolution of Holliday junctions is not necessary for heteroduplex-patch formation, contrary to predictions of all of the major previous models. This implies that patches are not an alternative resolution of the same intermediate that produces splices, and do not bear on models for splice formation. We consider two mechanisms that use DNA replication instead of endonucleolytic resolution for formation of heteroduplex patches in either DNA strand: synthesis-dependent-strand annealing and a strand-assimilation mechanism

Predicting tumor cell line response to drug pairs with deep learning

Abstract Background The National Cancer Institute drug pair screening effort against 60 well-characterized human tumor cell lines (NCI-60) presents an unprecedented resource for modeling combinational drug activity. Results We present a computational model for predicting cell line response to a subset of drug pairs in the NCI-ALMANAC database. Based on residual neural networks for encoding features as well as predicting tumor growth, our model explains 94% of the response variance. While our best result is achieved with a combination of molecular feature types (gene expression, microRNA and proteome), we show that most of the predictive power comes from drug descriptors. To further demonstrate value in detecting anticancer therapy, we rank the drug pairs for each cell line based on model predicted combination effect and recover 80% of the top pairs with enhanced activity. Conclusions We present promising results in applying deep learning to predicting combinational drug response. Our feature analysis indicates screening data involving more cell lines are needed for the models to make better use of molecular features

Phosphorylated fraction of H2AX as a measurement for DNA damage in cancer cells and potential applications of a novel assay

<div><p>Phosphorylated H2AX (γ-H2AX) is a sensitive marker for DNA double-strand breaks (DSBs), but the variability of H2AX expression in different cell and tissue types makes it difficult to interpret the meaning of the γ-H2AX level. Furthermore, the assays commonly used for γ-H2AX detection utilize laborious and low-throughput microscopy-based methods. We describe here an ELISA assay that measures both phosphorylated H2AX and total H2AX absolute amounts to determine the percentage of γ-H2AX, providing a normalized value representative of the amount of DNA damage. We demonstrate the utility of the assay to measure DSBs introduced by either ionizing radiation or DNA-damaging agents in cultured cells and in xenograft models. Furthermore, utilizing the NCI-60 cancer cell line panel, we show a correlation between the basal fraction of γ-H2AX and cellular mutation levels. This additional application highlights the ability of the assay to measure γ-H2AX levels in many extracts at once, making it possible to correlate findings with other cellular characteristics. Overall, the γ-H2AX ELISA represents a novel approach to quantifying DNA damage, which may lead to a better understanding of mutagenic pathways in cancer and provide a useful biomarker for monitoring the effectiveness of DNA-damaging anticancer agents.</p></div

Studies of the NCI-60 cell databank using the combined % γ-H2AX ELISA.

<p><b>(A)</b> Cell lines from the NCI-60 cell bank aligned in order of increasing total H2AX amounts per cell (left). The basal % γ-H2AX in unstressed cells for each cell line is shown on the right. Data from normal human fibroblasts (NHFs) is boxed. <b>(B)</b> Selected lines were arranged according to their basal % γ-H2AX values (red bars). Light gray, dark gray, and black bars represent the fold change in % γ-H2AX after 0.5, 2, and 5 Gy radiation, respectively, relative to the basal value (purple bars).</p