Nusinow D, Szpyt J, Ghandi M, Rose C, McDonald R, Kalocsay M, Jané-Valbuena J, Gelfand E, Schweppe D, Jedrychowski M, et al. Quantitative Proteomics of the Cancer Cell Line Encyclopedia. Cell. 2020;180(2):387-402.e16.
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.


Ghandi M, Huang F, Jané-Valbuena J, Kryukov G, Lo C, McDonald R, Barretina J, Gelfand E, Bielski C, Li H, et al. Next-generation characterization of the Cancer Cell Line Encyclopedia. Nature. 2019;569(7757):503-508.
Large panels of comprehensively characterized human cancer models, including the Cancer Cell Line Encyclopedia (CCLE), have provided a rigorous framework with which to study genetic variants, candidate targets, and small-molecule and biological therapeutics and to identify new marker-driven cancer dependencies. To improve our understanding of the molecular features that contribute to cancer phenotypes, including drug responses, here we have expanded the characterizations of cancer cell lines to include genetic, RNA splicing, DNA methylation, histone H3 modification, microRNA expression and reverse-phase protein array data for 1,072 cell lines from individuals of various lineages and ethnicities. Integration of these data with functional characterizations such as drug-sensitivity, short hairpin RNA knockdown and CRISPR-Cas9 knockout data reveals potential targets for cancer drugs and associated biomarkers. Together, this dataset and an accompanying public data portal provide a resource for the acceleration of cancer research using model cancer cell lines.
Li H, Ning S, Ghandi M, Kryukov G, Gopal S, Deik A, Souza A, Pierce K, Keskula P, Hernandez D, et al. The landscape of cancer cell line metabolism. Nat Med. 2019;25(5):850-860.
Despite considerable efforts to identify cancer metabolic alterations that might unveil druggable vulnerabilities, systematic characterizations of metabolism as it relates to functional genomic features and associated dependencies remain uncommon. To further understand the metabolic diversity of cancer, we profiled 225 metabolites in 928 cell lines from more than 20 cancer types in the Cancer Cell Line Encyclopedia (CCLE) using liquid chromatography-mass spectrometry (LC-MS). This resource enables unbiased association analysis linking the cancer metabolome to genetic alterations, epigenetic features and gene dependencies. Additionally, by screening barcoded cell lines, we demonstrated that aberrant ASNS hypermethylation sensitizes subsets of gastric and hepatic cancers to asparaginase therapy. Finally, our analysis revealed distinct synthesis and secretion patterns of kynurenine, an immune-suppressive metabolite, in model cancer cell lines. Together, these findings and related methodology provide comprehensive resources that will help clarify the landscape of cancer metabolism.


Cancer Cell Line Encyclopedia Consortium, Genomics of Drug Sensitivity in Cancer Consortium. Pharmacogenomic agreement between two cancer cell line data sets. Nature. 2015;528(7580):84-7.
Large cancer cell line collections broadly capture the genomic diversity of human cancers and provide valuable insight into anti-cancer drug response. Here we show substantial agreement and biological consilience between drug sensitivity measurements and their associated genomic predictors from two publicly available large-scale pharmacogenomics resources: The Cancer Cell Line Encyclopedia and the Genomics of Drug Sensitivity in Cancer databases.


Jaffe J, Wang Y, Chan HM, Zhang J, Huether R, Kryukov G, Bhang H-eun, Taylor J, Hu M, Englund N, et al. Global chromatin profiling reveals NSD2 mutations in pediatric acute lymphoblastic leukemia. Nat Genet. 2013;45(11):1386-91.
Epigenetic dysregulation is an emerging hallmark of cancers. We developed a high-information-content mass spectrometry approach to profile global histone modifications in human cancers. When applied to 115 lines from the Cancer Cell Line Encyclopedia, this approach identified distinct molecular chromatin signatures. One signature was characterized by increased histone 3 lysine 36 (H3K36) dimethylation, exhibited by several lines harboring translocations in NSD2, which encodes a methyltransferase. A previously unknown NSD2 p.Glu1099Lys (p.E1099K) variant was identified in nontranslocated acute lymphoblastic leukemia (ALL) cell lines sharing this signature. Ectopic expression of the variant induced a chromatin signature characteristic of NSD2 hyperactivation and promoted transformation. NSD2 knockdown selectively inhibited the proliferation of NSD2-mutant lines and impaired the in vivo growth of an NSD2-mutant ALL xenograft. Sequencing analysis of >1,000 pediatric cancer genomes identified the NSD2 p.E1099K alteration in 14% of t(12;21) ETV6-RUNX1-containing ALLs. These findings identify NSD2 as a potential therapeutic target for pediatric ALL and provide a general framework for the functional annotation of cancer epigenomes.


Barretina J, Caponigro G, Stransky N, Venkatesan K, Margolin A, Kim S, Wilson C, Lehár J, Kryukov G, Sonkin D, et al. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature. 2012;483(7391):603-7.
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.


Solit D, Garraway L, Pratilas C, Sawai A, Getz G, Basso A, Ye Q, Lobo J, She Y, Osman I, et al. BRAF mutation predicts sensitivity to MEK inhibition. Nature. 2006;439(7074):358-62.
The kinase pathway comprising RAS, RAF, mitogen-activated protein kinase kinase (MEK) and extracellular signal regulated kinase (ERK) is activated in most human tumours, often through gain-of-function mutations of RAS and RAF family members. Using small-molecule inhibitors of MEK and an integrated genetic and pharmacologic analysis, we find that mutation of BRAF is associated with enhanced and selective sensitivity to MEK inhibition when compared to either 'wild-type' cells or cells harbouring a RAS mutation. This MEK dependency was observed in BRAF mutant cells regardless of tissue lineage, and correlated with both downregulation of cyclin D1 protein expression and the induction of G1 arrest. Pharmacological MEK inhibition completely abrogated tumour growth in BRAF mutant xenografts, whereas RAS mutant tumours were only partially inhibited. These data suggest an exquisite dependency on MEK activity in BRAF mutant tumours, and offer a rational therapeutic strategy for this genetically defined tumour subtype.


Garraway L, Widlund H, Rubin M, Getz G, Berger A, Ramaswamy S, Beroukhim R, Milner D, Granter S, Du J, et al. Integrative genomic analyses identify MITF as a lineage survival oncogene amplified in malignant melanoma. Nature. 2005;436(7047):117-22.
Systematic analyses of cancer genomes promise to unveil patterns of genetic alterations linked to the genesis and spread of human cancers. High-density single-nucleotide polymorphism (SNP) arrays enable detailed and genome-wide identification of both loss-of-heterozygosity events and copy-number alterations in cancer. Here, by integrating SNP array-based genetic maps with gene expression signatures derived from NCI60 cell lines, we identified the melanocyte master regulator MITF (microphthalmia-associated transcription factor) as the target of a novel melanoma amplification. We found that MITF amplification was more prevalent in metastatic disease and correlated with decreased overall patient survival. BRAF mutation and p16 inactivation accompanied MITF amplification in melanoma cell lines. Ectopic MITF expression in conjunction with the BRAF(V600E) mutant transformed primary human melanocytes, and thus MITF can function as a melanoma oncogene. Reduction of MITF activity sensitizes melanoma cells to chemotherapeutic agents. Targeting MITF in combination with BRAF or cyclin-dependent kinase inhibitors may offer a rational therapeutic avenue into melanoma, a highly chemotherapy-resistant neoplasm. Together, these data suggest that MITF represents a distinct class of 'lineage survival' or 'lineage addiction' oncogenes required for both tissue-specific cancer development and tumour progression.