Project description:BACKGROUND:The National Cancer Institute-60 (NCI-60) cell lines are among the most widely used models of human cancer. They provide a platform to integrate DNA sequence information, epigenetic data, RNA and protein expression, and pharmacologic susceptibilities in studies of cancer cell biology. Genome-wide studies of the complete panel have included exome sequencing, karyotyping, and copy number analyses but have not targeted repetitive sequences. Interspersed repeats derived from mobile DNAs are a significant source of heritable genetic variation, and insertions of active elements can occur somatically in malignancy. METHOD:We used Transposon Insertion Profiling by microarray (TIP-chip) to map Long INterspersed Element-1 (LINE-1, L1) and Alu Short INterspersed Element (SINE) insertions in cancer genes in NCI-60 cells. We focused this discovery effort on annotated Cancer Gene Index loci. RESULTS:We catalogued a total of 749 and 2,100 loci corresponding to candidate LINE-1 and Alu insertion sites, respectively. As expected, these numbers encompass previously known insertions, polymorphisms shared in unrelated tumor cell lines, as well as unique, potentially tumor-specific insertions. We also conducted association analyses relating individual insertions to a variety of cellular phenotypes. CONCLUSIONS:These data provide a resource for investigators with interests in specific cancer gene loci or mobile element insertion effects more broadly. Our data underscore that significant genetic variation in cancer genomes is owed to LINE-1 and Alu retrotransposons. Our findings also indicate that as large numbers of cancer genomes become available, it will be possible to associate individual transposable element insertion variants with molecular and phenotypic features of these malignancies.
Project description:The National Cancer Institute-60 (NCI-60) cell lines are among the most widely used models of human cancer. They provide a platform to integrate DNA sequence information, epigenetic data, RNA and protein expression, and pharmacologic susceptibilities in studies of cancer cell biology. Genome-wide studies of the NCI-60 have included exome sequencing, karyotyping, and copy number analyses but have not targeted repetitive sequences. Interspersed repeats are a significant source of heritable genetic variation, and insertions of active elements can occur somatically in malignancy. To approach a functional understanding of these sequences in transformed cells, we used transposon insertion profiling (TIP) to map Long INterspersed Element-1 (LINE-1, L1) and Alu Short INterspersed Element (SINE) insertions in cancer genes in NCI-60 cells. As expected, this identified known insertions, polymorphisms shared in unrelated tumor cell lines, as well as unique, potentially tumor-specific insertions. Here, we report a map of these insertion sites and conduct association analyses relating individual insertions to a variety of cellular phenotypes. Overall design: 60 cell lines representing nine different types of neoplasias were mapped for LINE-1 and Alu transposable elements using a TIP-CHIP microarray tiling known cancer genes Please note that a technique called TIP-Chip was used to discover transposable elements (TE) in the NCI-60 cancer cell lines. The process uses labeled unique 3' DNA amplicons adjacent to these elements to map the TEs in the genome. These 3' amplicons are hybridized to the array and serve as a marker to identify a genomic coordinate. When the array scanner generate .gff output files as raw data output files on which clean-up algorithms and subsequent analysis were performed (resulting in peak files in text format).
Project description:We investigated, in the panel of 60 human tumour cell lines of the National Cancer Institute (NCI-60), whether the R72P polymorphism of TP53 and the T309G polymorphism of MDM2 were associated to the in vitro cytotoxicity of anticancer agents, extracted from the NCI database. For validation, the same study was performed independently on a second panel of tumour cell lines, JFCR-45.Both SNPs were identified in cell DNA using PCR-RFLP techniques confirmed by direct sequencing and by pyrosequencing. For the analysis of the results, the mutational status of p53 was taken into account.In the NCI-60 panel, the TP53 rare-allele frequency was 32% and the MDM2 rare-allele frequency 39%. The MDM2 alleles were distributed according to Hardy-Weinberg equilibrium whereas this was only found, for the TP53 alleles, in p53 non-mutated cell lines. Comparable results were obtained in the JFCR-45 validation set. The TP53 SNP had low impact on anticancer drug cytotoxicity in either panel. In contrast, the MDM2 gene polymorphism had a major impact on anticancer drug cytotoxicity, essentially in p53 non-mutated cell lines. Presence of the rare allele was associated to significantly higher MDM2 protein expression and to increased sensitivity to DNA-interfering drugs. In the JFCR-45 panel, a similar effect of the MDM2 gene polymorphism was observed, but was less dependent on the p53 mutational status.We hypothesised that cell lines harbouring the MDM2 G allele presented a lower availability of p53 for DNA repair, translating into higher sensitivity to DNA-damaging agents.
Project description:The panel of 60 human cancer cell lines (the NCI-60) assembled by the National Cancer Institute for anticancer drug discovery is a widely used resource. The NCI-60 has been characterized pharmacologically and at the molecular level more extensively than any other set of cell lines. However, no systematic mutation analysis of genes causally implicated in oncogenesis has been reported. This study reports the sequence analysis of 24 known cancer genes in the NCI-60 and an assessment of 4 of the 24 genes for homozygous deletions. One hundred thirty-seven oncogenic mutations were identified in 14 (APC, BRAF, CDKN2, CTNNB1, HRAS, KRAS, NRAS, SMAD4, PIK3CA, PTEN, RB1, STK11, TP53, and VHL) of the 24 genes. All lines have at least one mutation among the cancer genes examined, with most lines (73%) having more than one. Identification of those cancer genes mutated in the NCI-60, in combination with pharmacologic and molecular profiles of the cells, will allow for more informed interpretation of anticancer agent screening and will enhance the use of the NCI-60 cell lines for molecularly targeted screens.
Project description:The U.S. National Cancer Institute has used a panel of 60 diverse human cancer cell lines (the NCI-60) to screen >100,000 chemical compounds for anticancer activity. However, not all important cancer types are included in the panel, nor are drug responses of the panel predictive of clinical efficacy in patients. We asked, therefore, whether it would be possible to extrapolate from that rich database (or analogous ones from other drug screens) to predict activity in cell types not included or, for that matter, clinical responses in patients with tumors. We address that challenge by developing and applying an algorithm we term "coexpression extrapolation" (COXEN). COXEN uses expression microarray data as a Rosetta Stone for translating from drug activities in the NCI-60 to drug activities in any other cell panel or set of clinical tumors. Here, we show that COXEN can accurately predict drug sensitivity of bladder cancer cell lines and clinical responses of breast cancer patients treated with commonly used chemotherapeutic drugs. Furthermore, we used COXEN for in silico screening of 45,545 compounds and identify an agent with activity against human bladder cancer.
Project description:The NCI-60 panel of 60 human cancer cell-lines of nine different tissues of origin has been extensively characterized in biological, molecular and pharmacological studies. Analyses of data from such studies have provided valuable information for understanding cellular processes and developing strategies for the diagnosis and treatment of cancer. Here, Affymetrix® GeneChip™ miRNA version 1 oligonucleotide microarrays were used to quantify 847 microRNAs to generate an expression dataset of 495 (58.4%) microRNAs that were identified as expressed in at least one cell-line of the NCI-60 panel. Accuracy of the microRNA measurements was partly confirmed by reverse transcription and polymerase chain reaction assays. Similar to that seen among the four existing NCI-60 microRNA datasets, the concordance of the new expression dataset with the other four was modest, with mean Pearson correlation coefficients of 0.37-0.54. In spite of this, comparable results with different datasets were noted in clustering of the cell-lines by their microRNA expression, differential expression of microRNAs by the lines' tissue of origin, and correlation of specific microRNAs with the doubling-time of cells or their radiation sensitivity. Mutation status of the cell-lines for the TP53, PTEN and BRAF but not CDKN2A or KRAS cancer-related genes was found to be associated with changes in expression of specific microRNAs. The microRNA dataset generated here should be valuable to those working in the field of microRNAs as well as in integromic studies of the NCI-60 panel.
Project description:Advances in the understanding of cancer cell biology and response to drug treatment have benefited from new molecular technologies and methods for integrating information from multiple sources. The NCI-60, a panel of 60 diverse human cancer cell lines, has been used by the National Cancer Institute to screen >100,000 chemical compounds and natural product extracts for anticancer activity. The NCI-60 has also been profiled for mRNA and protein expression, mutational status, chromosomal aberrations, and DNA copy number, generating an unparalleled public resource for integrated chemogenomic studies. Recently, microRNAs have been shown to target particular sets of mRNAs, thereby preventing translation or accelerating mRNA turnover. To complement the existing NCI-60 datasets, we have measured expression levels of microRNAs in the NCI-60.
Project description:The National Cancer Institute's NCI-60 cell line panel, the most extensively characterized set of cells in existence and a public resource, is frequently used as a screening tool for drug discovery. Because many laboratories around the world rely on data from the NCI-60 cells, confirmation of their genetic identities represents an essential step in validating results from them. Given the consequences of cell line contamination or misidentification, quality control measures should routinely include DNA fingerprinting. We have, therefore, used standard DNA microsatellite short tandem repeats to profile the NCI-60, and the resulting DNA fingerprints are provided here as a reference. Consistent with previous reports, the fingerprints suggest that several NCI-60 lines have common origins: the melanoma lines MDA-MB-435, MDA-N, and M14; the central nervous system lines U251 and SNB-19; the ovarian lines OVCAR-8 and OVCAR-8/ADR (also called NCI/ADR); and the prostate lines DU-145, DU-145 (ATCC), and RC0.1. Those lines also show that the ability to connect two fingerprints to the same origin is not affected by stable transfection or by the development of multidrug resistance. As expected, DNA fingerprints were not able to distinguish different tissues-of-origin. The fingerprints serve principally as a barcodes.
Project description:The NCI-60 is a panel of 60 diverse human cancer cell lines used by the U.S. National Cancer Institute to screen compounds for anticancer activity. We recently clustered genes based on correlation of expression profiles across the NCI-60. Many of the resulting clusters were characterized by cancer-associated biological functions. The set of curated glioblastoma (GBM) gene expression data from the Cancer Genome Atlas (TCGA) initiative has recently become available. Thus, we are now able to determine which of the processes are robustly shared by both the immortalized cell lines and clinical cancers.Our central observation is that some sets of highly correlated genes in the NCI-60 expression data are also highly correlated in the GBM expression data. Furthermore, a "double fishing" strategy identified many sets of genes that show Pearson correlation ?0.60 in both the NCI-60 and the GBM data sets relative to a given "bait" gene. The number of such gene sets far exceeds the number expected by chance.Many of the gene-gene correlations found in the NCI-60 do not reflect just the conditions of cell lines in culture; rather, they reflect processes and gene networks that also function in vivo. A number of gene network correlations co-occur in the NCI-60 and GBM data sets, but there are others that occur only in NCI-60 or only in GBM. In sum, this analysis provides an additional perspective on both the utility and the limitations of the NCI-60 in furthering our understanding of cancers in vivo.
Project description:DNA-damaging agents (DDAs) constitute the backbone of treatment for most human tumors. Here we used the National Cancer Institute Antitumor Cell Line Panel (the NCI-60) to identify predictors of cancer cell response to topoisomerase I (Top1) inhibitors, a widely used class of DDAs. We assessed the NCI-60 transcriptome using Affymetrix Human Exon 1.0 ST microarrays and correlated the in vitro activity of four Top1 inhibitors with gene expression in the 60 cell lines. A single gene, Schlafen-11 (SLFN11), showed an extremely significant positive correlation with the response not only to Top1 inhibitors, but also to Top2 inhibitors, alkylating agents, and DNA synthesis inhibitors. Using cells with endogenously high and low SLFN11 expression and siRNA-mediated silencing, we show that SLFN11 is causative in determining cell death and cell cycle arrest in response to DDAs in cancer cells from different tissues of origin. We next analyzed SLFN11 expression in ovarian and colorectal cancers and normal corresponding tissues from The Cancer Genome Atlas database and observed that SLFN11 has a wide expression range. We also observed that high SLFN11 expression independently predicts overall survival in a group of ovarian cancer patients treated with cisplatin-containing regimens. We conclude that SLFN11 expression is causally associated with the activity of DDAs in cancer cells, has a broad expression range in colon and ovarian adenocarcinomas, and may behave as a biomarker for prediction of response to DDAs in the clinical setting.