Next-generation characterization of the Cancer Cell Line Encyclopedia.
Ontology highlight
ABSTRACT:
SUBMITTER: Ghandi M
PROVIDER: S-EPMC6697103 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Proteins are essential agents of biological processes. To date, large-scale profiling of cell line collections including the Cancer Cell Line Encyclopedia (CCLE) has focused primarily on genetic information whereas deep interrogation of the proteome has remained out of reach. Here, we expand the CCLE through quantitative profiling of thousands of proteins by mass spectrometry across 375 cell lines from diverse lineages to reveal information undiscovered by DNA and RNA methods. We observe unexpected correlations within and between pathways that are largely absent from RNA. An analysis of microsatellite instable (MSI) cell lines reveals the dysregulation of specific protein complexes associated with surveillance of mutation and translation. These and other protein complexes were associated with sensitivity to knockdown of several different genes. These data in conjunction with the wider CCLE are a broad resource to explore cellular behavior and facilitate cancer research.
| S-EPMC7339254 | biostudies-literature
Project description:Tumor suppressors play a major role in the etiology of human cancer, and typically achieve a tumor-promoting effect upon complete functional inactivation. Bi-allelic inactivation of tumor suppressors may occur through genetic mechanisms (such as loss of function mutation, copy number (CN) loss, or loss of heterozygosity (LOH)), epigenetic mechanisms (such as promoter methylation or histone modification), or a combination of the two. We report systematically derived status of 69 known or putative tumor suppressors, across 799 samples of the Cancer Cell Line Encyclopedia. In order to generate such resource we constructed a novel comprehensive computational framework for the assessment of tumor suppressor functional "status". This approach utilizes several orthogonal genomic data types, including mutation data, copy number, LOH and expression. Through correlation with additional data types (compound sensitivity and gene set activity) we show that this integrative method provides a more accurate assessment of tumor suppressor status than can be inferred by expression, copy number, or mutation alone. This approach has the potential for a more realistic assessment of tumor suppressor genes for both basic and translational oncology research.
| S-EPMC3729735 | biostudies-literature
Project description:The Cancer Cell Line Encyclopedia (CCLE) project is a collaboration between the Broad Institute, the Novartis Institutes for Biomedical Research and the Genomics Novartis Foundation to conduct a detailed genetic and pharmacologic characterization of a large panel of human cancer models It consists of a compilation of gene expression, chromosomal copy number, and massively parallel sequencing data from nearly 1,000 human cancer cell lines. All raw and processed data are available through an integrated portal on www.broadinstitute.org/ccle The final cell line collection spans 36 cancer types. Representation of cell lines for each cancer type was mainly driven by cancer mortality in the United States, as a surrogate of unmet medical need, as well as availability.
| S-ECPF-GEOD-36133 | biostudies-other
Project description:The systematic translation of cancer genomic data into knowledge of tumour biology and therapeutic possibilities remains challenging. Such efforts should be greatly aided by robust preclinical model systems that reflect the genomic diversity of human cancers and for which detailed genetic and pharmacological annotation is available. Here we describe the Cancer Cell Line Encyclopedia (CCLE): a compilation of gene expression, chromosomal copy number and massively parallel sequencing data from 947 human cancer cell lines. When coupled with pharmacological profiles for 24 anticancer drugs across 479 of the cell lines, this collection allowed identification of genetic, lineage, and gene-expression-based predictors of drug sensitivity. In addition to known predictors, we found that plasma cell lineage correlated with sensitivity to IGF1 receptor inhibitors; AHR expression was associated with MEK inhibitor efficacy in NRAS-mutant lines; and SLFN11 expression predicted sensitivity to topoisomerase inhibitors. Together, our results indicate that large, annotated cell-line collections may help to enable preclinical stratification schemata for anticancer agents. The generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of 'personalized' therapeutic regimens.
| S-EPMC3320027 | biostudies-literature
Project description:928 cancer cell lines from 20 major cancer types were cultured in vitro for metabolomic profiling of 124 polar and 101 lipid species. Extracted polar and lipid metabolites were analyzed using hydrophilic interaction
2019-02-25 | ST001142 | MetabolomicsWorkbench
Project description:Genetic alterations initiate tumors and enable the evolution of drug resistance. The pro-cancer view of mutations is however incomplete, and several studies show that mutational load can reduce tumor fitness. Given its negative effect, genetic load should make tumors more sensitive to anticancer drugs. Here, we test this hypothesis across all major types of cancer from the Cancer Cell Line Encyclopedia, which provides genetic and expression data of 496 cell lines together with their response to 24 common anticancer drugs. We found that the efficacy of 9 out of 24 drugs showed significant association with genetic load in a pan-cancer analysis. The associations for some tissue-drug combinations were remarkably strong, with genetic load explaining up to 83% of the variance in the drug response. Overall, the role of genetic load depended on both the drug and the tissue type with 10 tissues being particularly vulnerable to genetic load. We also identified changes in gene expression associated with increased genetic load, which included cell-cycle checkpoints, DNA damage and apoptosis. Our results show that genetic load is an important component of tumor fitness and can predict drug sensitivity. Beyond being a biomarker, genetic load might be a new, unexplored vulnerability of cancer.
| S-EPMC5434051 | biostudies-literature
Project description:Cell lines are indispensable models for modern biomedical research. A large part of their usefulness derives from the ability of a cell line to proliferate over multiple passages (often indefinitely), allowing multiple experiments to be performed. However, over time, cell line identity and purity can be compromised by human errors. Cross-contamination from other cell lines and complete misidentification are both possible. Routine cell line authentication is a necessary preventive measure and has become a requirement for many funding applications and publications. Short tandem repeat (STR) profiling is the most common method for cell line authentication and is usually carried out using standard polymerase chain reaction-capillary electrophoresis analysis (STR-CE). Here, we evaluated next-generation sequencing (NGS)-based STR profiling of human and mouse cell lines at 18 and 15 loci, respectively, in a high-throughput format. Using the Python program STRight, we demonstrate that NGS-based analysis (STR-NGS) is superior to standard STR-CE in terms of the ability to report the sequence context of repeat motifs, sensitivity and flexible multiplexing capability. STR-NGS is thus a valuable alternative for cell line authentication.
| S-EPMC10618599 | biostudies-literature
Project description:Molecular characterization of advanced non-small-cell lung cancer (NSCLC) is mandatory before any treatment decision making. Next-generation sequencing (NGS) approaches represent the best strategy in this context. The turnaround time for NGS methodologies and the related costs are becoming more and more adaptable for their use in clinical practice. In our study, we analyzed a case series of young (under 65 years old) NSCLC patients with a wide NGS gene panel assay. The most frequent altered genes were TP53 (64.55%), followed by KRAS (44.1%), STK11 (26.9%), CDKN2A (21.5%), CDKN2B (14.0%), EGFR (16.1%), and RB1 (10.8%). Tumor mutational burden (TMB) was also evaluated. Considering the cut-off of 10 mut/Mb, 62 (68.9%) patients showed a TMB < 10 mut/Mb, whereas 28 (31.1%) showed a TMB ≥ 10 mut/Mb. STK11 and KRAS mutations were significantly associated with a higher TMB (p = 0.019 and p = 0.004, respectively). Conversely, EGFR and EML4-ALK alterations were more frequently found in tumors with low TMB (p = 0.019 and p < 0.001, respectively). We compared results obtained from this approach with those obtained from a single or few genes approach, observing perfect concordance of the results.
| S-EPMC9139648 | biostudies-literature
Project description:Using high-throughput RNA sequencing data from 50 common lymphoma cell culture models from the Cancer Cell Line Encyclopedia project, we performed an unbiased global interrogation for the presence of a panel of 740 viruses and strains known to infect human and other mammalian cells. This led to the findings of previously identified infections by Epstein-Barr virus (EBV), Kaposi's sarcoma herpesvirus (KSHV), and human T-lymphotropic virus type 1 (HTLV-1). In addition, we also found a previously unreported infection of one cell line (DEL) with a murine leukemia virus. High expression of murine leukemia virus (MuLV) transcripts was observed in DEL cells, and we identified four transcriptionally active integration sites, one being in the TNFRSF6B gene. We also found low levels of MuLV reads in a number of other cell lines and provided evidence suggesting cross-contamination during sequencing. Analysis of HTLV-1 integrations in two cell lines, HuT 102 and MJ, identified 14 and 66 transcriptionally active integration sites with potentially activating integrations in immune regulatory genes, including interleukin-15 (IL-15), IL-6ST, STAT5B, HIVEP1, and IL-9R. Although KSHV and EBV do not typically integrate into the genome, we investigated a previously identified integration of EBV into the BACH2 locus in Raji cells. This analysis identified a BACH2 disruption mechanism involving splice donor sequestration. Through viral gene expression analysis, we detected expression of stable intronic RNAs from the EBV BamHI W repeats that may be part of long transcripts spanning the repeat region. We also observed transcripts at the EBV vIL-10 locus exclusively in the Hodgkin's lymphoma cell line, Hs 611.T, the expression of which were uncoupled from other lytic genes. Assessment of the KSHV viral transcriptome in BCP-1 cells showed expression of the viral immune regulators, K2/vIL-6, K4/vIL-8-like vCCL1, and K5/E2-ubiquitin ligase 1 that was significantly higher than expression of the latency-associated nuclear antigen. Together, this investigation sheds light into the virus composition across these lymphoma model systems and provides insights into common viral mechanistic principles.Viruses cause cancer in humans. In lymphomas the Epstein-Barr virus (EBV), Kaposi's sarcoma herpesvirus (KSHV) and human T-lymphotropic virus type 1 are major contributors to oncogenesis. We assessed virus-host interactions using a high throughput sequencing method that facilitates the discovery of new virus-host associations and the investigation into how the viruses alter their host environment. We found a previously unknown murine leukemia virus infection in one cell line. We identified cellular genes, including cytokine regulators, that are disrupted by virus integration, and we determined mechanisms through which virus integration causes deregulation of cellular gene expression. Investigation into the KSHV transcriptome in the BCP-1 cell line revealed high-level expression of immune signaling genes. EBV transcriptome analysis showed expression of vIL-10 transcripts in a Hodgkin's lymphoma that was uncoupled from lytic genes. These findings illustrate unique mechanisms of viral gene regulation and to the importance of virus-mediated host immune signaling in lymphomas.
| S-EPMC4301145 | biostudies-literature
Project description:The Cancer Cell Line Encyclopedia (CCLE) project is a collaboration between the Broad Institute, the Novartis Institutes for Biomedical Research and the Genomics Novartis Foundation to conduct a detailed genetic and pharmacologic characterization of a large panel of human cancer models It consists of a compilation of gene expression, chromosomal copy number, and massively parallel sequencing data from nearly 1,000 human cancer cell lines. All raw and processed data are available through an integrated portal on www.broadinstitute.org/ccle
2012-03-20 | GSE36133 | GEO