Alterations In Cancer Cell Lines Research Articles

Cancercelllines.org-a novel resource for genomic variants in cancer cell lines.

Cancer cell lines are an important component in biological and medical research, enabling studies of cellular mechanisms as well as the development and testing of pharmaceuticals. Genomic alterations in cancer cell lines are widely studied as models for oncogenetic events and are represented in a wide range of primary resources. We have created a comprehensive, curated knowledge resource-cancercelllines.org-with the aim to enable easy access to genomic profiling data in cancer cell lines, curated from a variety of resources and integrating both copy number and single nucleotide variants data. We have gathered over 5600 copy number profiles as well as single nucleotide variant annotations for 16 000 cell lines and provide these data with mappings to the GRCh38 reference genome. Both genomic variations and associated curated metadata can be queried through the GA4GH Beacon v2 Application Programming Interface (API) and a graphical user interface with extensive data retrieval enabled using GA4GH data schemas under a permissive licensing scheme. Database URL: https://cancercelllines.org.

Targeted Genomic Screen Reveals Focal Long Non-Coding RNA Copy Number Alterations in Cancer Cell Lines.

The landscape of somatic copy-number alterations (SCNAs) affecting long non-coding RNAs (lncRNAs) in human cancers remains largely unexplored. While the majority of lncRNAs remain to be functionally characterized, several have been implicated in cancer development and metastasis. Considering the plethora of lncRNAs genes that have been currently reported, it is conceivable that many more lncRNAs might function as oncogenes or tumor suppressor genes. We devised a strategy to detect focal lncRNA SCNAs using a custom DNA microarray platform probing 10,519 lncRNA genes. By screening a panel of 80 cancer cell lines, we detected numerous focal aberrations targeting one or multiple lncRNAs without affecting neighboring protein-coding genes. These focal aberrations are highly suggestive for a tumor suppressive or oncogenic role of the targeted lncRNA gene. Although functional validation remains an essential step in the further characterization of the involved candidate cancer lncRNAs, our results provide a direct way of prioritizing candidate lncRNAs that are involved in cancer pathogenesis.

PO-376 SWI/SNF alterations as markers for prognosis and specific treatments in human cancer

Introduction The mutational landscape of cancer has been robustly analysed using next generation sequencing (NGS) allowing the identification of somatic mutations in several SWI/SNF chromatin remodelling complex subunits such as SMARCA4 , SMARCA2 , ARID1A , ARID1B , ARID2 and PBRM1 in different tumour types. SWI/SNF complex play a key role in modulating DNA transcription and repair mechanisms that could offer potential explanations of this role in cancer. We hypothesised that other chromatin remodelling genes, not described until now, could also play an important role in cancer develoment. Material and methods We have performed target sequencing of 736 samples, including 178 lung tumours and 88 matched normal tissue, using custom probes designed against the coding sequence of 250 genes including chromatin regulators such as ATP-dependent remodelling complexes, histone modifiers and as well as recurrently mutated cancer genes. Validation of the potential mutations found in the screening was assessed using high-coverage amplicon sequencing. Finally, proliferation, migration and invasion studies in vitro and in vivo were performed to validate the functional impact of chromatin remodeler alterations in cancer cell lines. Results and discussions This comprehensive genomic analysis identified 4900 somatic mutations among all the samples studied. More than 800 of these mutations are located in the genes of the components of the four main ATP-dependent chromatin remodelling complexes (SWI/SNF, ISWI, CHD and INO80). We have seen that SWI/SNF seems to play a more prominent role in cancer development that the other complexes. Additionally, we have identified new members of the complex that could play an important role in cancer development or in different cancer sub-types to the ones already described. Finally, we have performed functional studies that supports this role and opens new therapeutic opportunities to exploit SWI/SNF defects. Conclusion Our results are in agreement with the notion that chromatin structure plays an important role in tumour progression and that some genes coding for components of ATP-dependent chromatin remodelling complexes are bona fide cancer genes essential for tumour development in specific malignancies. Additionally, we show that these deficiencies can be exploited as markers for prognosis and specific therapy.

Association analysis of the perturbation of interactions in biological pathways and anticancer drug activity

Understanding how different genomic mutational landscapes in patients with cancer lead to different responses to anticancer drugs is an important challenge for realizing precision medicine for cancer. Many studies have analyzed the comprehensive anticancer drug-response profiles and genomic profiles of cancer cell lines to identify the relationship between the anticancer drug response and genomic alternations. However, few studies have focused on interpreting these profiles with a network perspective. In this work, we analyzed genomic alterations in cancer cell lines by considering which interactions in the signaling pathway were perturbed by mutations. With our interaction-centric approach, we identified novel interaction/drug response associations for two drugs (afatinib and ixabepilone) for which no gene-centric association could be found. When we compared the performance of classifiers for predicting the responses to 164 drugs, the classifiers trained with interaction-centric features outperformed the classifiers trained with gene-centric features, despite the smaller number of features (p-value = 2.0 × 10−3). By incorporating the interaction information from signaling pathways, we revealed associations between genomic alterations and drug responses that could be missed when using a gene-centric approach.

Abstract IA1: Cancer dependencies defined by genomic alterations and targeted by small molecules

Abstract The ability to sequence cancer genomes coupled with advances in small-molecule science provides a new foundation for creating safe and effective cancer therapeutics – ones delivered to patients based on the specific genomic alterations present in their cancer. Several examples now exist of small-molecule cancer drugs targeting protein kinases encoded by both wild-type and oncogenic alleles, and yielding high clinical response rates in patients with specific genetic features. However, these drugs target only a narrow range of proteins, benefit <1% of patients suffering today from cancer, and provide therapeutic benefits that are not always durable. All current genetically matched drugs target the driver oncogene or its wild-type allele directly (“oncogene dependencies”). It is unknown whether similar clinical responses will result from drugs targeting non-oncogenes working in cooperation with oncogenes in patients with cancers having the relevant genetic features (“non-oncogene co-dependencies”). To accelerate the discovery of genetically matched therapies, systematic approaches are needed to identify: 1) the direct and indirect dependencies cancers acquire as a consequence of their specific mutations, translocations, and copy number alterations, and 2) small-molecule drugs that target the dependencies. Genomic cancer cell line profiling has been used to reveal patterns of small-molecule sensitivities across diverse cancer cell lines (CCLs). These efforts initially focused on relating sensitivity to the lineage of CCLs (ref NCI-60 and others), but now increasingly focus on relating sensitivity to genetic and epigenetic features of the cell lines. But these are still early days of genomic CCL profiling – there are many issues to iron out. Nevertheless, there are also signs that this approach will eventually be fruitful and impacting. For example, there are no examples of targeted cancer therapeutics today that were not predicted by genomic CCL profiling. In my lecture, I will describe an Interactive Resource to analyze and visualize a rich body of quantitative CCL sensitivity measurements with the aim of identifying novel candidate cancer dependencies targeted by small molecules. To enable the Resource, we measured the sensitivity of 243 genetically characterized CCLs to 355 small-molecule probes and drugs (the ‘Informer Set’) at eight concentrations in duplicate. The CCLs are part of a 949-member Cancer Cell Line Encyclopedia (CCLE) whose extensive genomic characterization includes the mutational status of >1,600 genes, global assessment of DNA copy number, and global gene expression analysis. These characterizations are also available freely via an interactive web portal (broadinstitute.org/ccle). The compounds included in the Informer Set are known to have selective interactions with their target, and collectively target many distinct nodes in cancer cell circuitry, including but not limited to pathways modulating apoptosis, oxidative stress, chromatin signaling, mitotic stress, hypoxic stress, proteotoxic stress, and metabolism. Using robust analytical methods including cell-line and compound filtering, we correlated the sensitivity measurements with genomic alterations in cancer cell lines to identify dependencies conferred by specific genotypes. I will describe the current content of the Resource and provide multiple illustrations of its use, including the use of additional analytical tools not included in the Resource but readily and freely accessible elsewhere. Citation Format: Stuart L. Schreiber. Cancer dependencies defined by genomic alterations and targeted by small molecules [abstract]. In: Proceedings of the AACR Special Conference on Chemical Systems Biology: Assembling and Interrogating Computational Models of the Cancer Cell by Chemical Perturbations; 2012 Jun 27-30; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2012;72(13 Suppl):Abstract nr IA1.

DNA fingerprinting of glioma cell lines and considerations on similarity measurements

Glioma cell lines are an important tool for research in basic and translational neuro-oncology. Documentation of their genetic identity has become a requirement for scientific journals and grant applications to exclude cross-contamination and misidentification that lead to misinterpretation of results. Here, we report the standard 16 marker short tandem repeat (STR) DNA fingerprints for a panel of 39 widely used glioma cell lines as reference. Comparison of the fingerprints among themselves and with the large DSMZ database comprising 9 marker STRs for 2278 cell lines uncovered 3 misidentified cell lines and confirmed previously known cross-contaminations. Furthermore, 2 glioma cell lines exhibited identity scores of 0.8, which is proposed as the cutoff for detecting cross-contamination. Additional characteristics, comprising lack of a B-raf mutation in one line and a similarity score of 1 with the original tumor tissue in the other, excluded a cross-contamination. Subsequent simulation procedures suggested that, when using DNA fingerprints comprising only 9 STR markers, the commonly used similarity score of 0.8 is not sufficiently stringent to unambiguously differentiate the origin. DNA fingerprints are confounded by frequent genetic alterations in cancer cell lines, particularly loss of heterozygosity, that reduce the informativeness of STR markers and, thereby, the overall power for distinction. The similarity score depends on the number of markers measured; thus, more markers or additional cell line characteristics, such as information on specific mutations, may be necessary to clarify the origin.

Identification of possible genetic alterations in the breast cancer cell line MCF-7 using high-density SNP genotyping microarray

Context:Cancer cell lines are used extensively in various research. Knowledge of genetic alterations in these lines is important for understanding mechanisms underlying their biology. However, since paired normal tissues are usually unavailable for comparison, precisely determining genetic alterations in cancer cell lines is difficult. To address this issue, a highly efficient and reliable method is developed. Aims: Establishing a highly efficient and reliable experimental system for genetic profiling of cell lines.Materials and Methods:A widely used breast cancer cell line, MCF-7, was genetically profiled with 4,396 single nucleotide polymorphisms (SNPs) spanning 11 whole chromosomes and two other small regions using a newly developed high-throughput multiplex genotyping approach.Results:The fractions of homozygous SNPs in MCF-7 (13.3%) were significantly lower than those in the control cell line and in 24 normal human individuals (25.1% and 27.4%, respectively). Homozygous SNPs in MCF-7 were found in clusters. The sizes of these clusters were significantly larger than the expected based on random allelic combination. Fourteen such regions were found on chromosomes 1p, 1q, 2q, 6q, 13, 15q, 16q, 17q and 18p in MCF-7 and two in the small regions.Conclusions:These results are generally concordant with those obtained using different approaches but are better in defining their chromosomal positions. The used approach provides a reliable way to detecting possible genetic alterations in cancer cell lines without paired normal tissues.