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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.

Rapid and affordable tumor molecular profiling has led to an explosion of clinical and genomic data poised to enhance the diagnosis, prognostication and treatment of cancer. A critical point has now been reached at which the analysis and storage of annotated clinical and genomic information in unconnected silos will stall the advancement of precision cancer care. Information systems must be harmonized to overcome the multiple technical and logistical barriers to data sharing. Against this backdrop, the Global Alliance for Genomic Health (GA4GH) was established in 2013 to create a common framework that enables responsible, voluntary and secure sharing of clinical and genomic data. This Perspective from the GA4GH Clinical Working Group Cancer Task Team highlights the data-aggregation challenges faced by the field, suggests potential collaborative solutions and describes how GA4GH can catalyze a harmonized data-sharing culture.

Profiling candidate therapeutics with limited cancer models during preclinical development hinders predictions of clinical efficacy and identifying factors that underlie heterogeneous patient responses for patient-selection strategies. We established ∼1,000 patient-derived tumor xenograft models (PDXs) with a diverse set of driver mutations. With these PDXs, we performed in vivo compound screens using a 1 × 1 × 1 experimental design (PDX clinical trial or PCT) to assess the population responses to 62 treatments across six indications. We demonstrate both the reproducibility and the clinical translatability of this approach by identifying associations between a genotype and drug response, and established mechanisms of resistance. In addition, our results suggest that PCTs may represent a more accurate approach than cell line models for assessing the clinical potential of some therapeutic modalities. We therefore propose that this experimental paradigm could potentially improve preclinical evaluation of treatment modalities and enhance our ability to predict clinical trial responses.

Resistance to cancer therapies presents a significant clinical challenge. Recent studies have revealed intratumoral heterogeneity as a source of therapeutic resistance. However, it is unclear whether resistance is driven predominantly by pre-existing or de novo alterations, in part because of the resolution limits of next-generation sequencing. To address this, we developed a high-complexity barcode library, ClonTracer, which enables the high-resolution tracking of more than 1 million cancer cells under drug treatment. In two clinically relevant models, ClonTracer studies showed that the majority of resistant clones were part of small, pre-existing subpopulations that selectively escaped under therapeutic challenge. Moreover, the ClonTracer approach enabled quantitative assessment of the ability of combination treatments to suppress resistant clones. These findings suggest that resistant clones are present before treatment, which would make up-front therapeutic combinations that target non-overlapping resistance a preferred approach. Thus, ClonTracer barcoding may be a valuable tool for optimizing therapeutic regimens with the goal of curative combination therapies for cancer.

Mantle cell lymphoma (MCL) is an aggressive malignancy that is characterized by poor prognosis. Large-scale pharmacological profiling across more than 100 hematological cell line models identified a subset of MCL cell lines that are highly sensitive to the B cell receptor (BCR) signaling inhibitors ibrutinib and sotrastaurin. Sensitive MCL models exhibited chronic activation of the BCR-driven classical nuclear factor-κB (NF-κB) pathway, whereas insensitive cell lines displayed activation of the alternative NF-κB pathway. Transcriptome sequencing revealed genetic lesions in alternative NF-κB pathway signaling components in ibrutinib-insensitive cell lines, and sequencing of 165 samples from patients with MCL identified recurrent mutations in TRAF2 or BIRC3 in 15% of these individuals. Although they are associated with insensitivity to ibrutinib, lesions in the alternative NF-κB pathway conferred dependence on the protein kinase NIK (also called mitogen-activated protein 3 kinase 14 or MAP3K14) both in vitro and in vivo. Thus, NIK is a new therapeutic target for MCL treatment, particularly for lymphomas that are refractory to BCR pathway inhibitors. Our findings reveal a pattern of mutually exclusive activation of the BCR-NF-κB or NIK-NF-κB pathways in MCL and provide critical insights into patient stratification strategies for NF-κB pathway-targeted agents.

Aberrant activation of the Hedgehog (Hh) pathway can drive tumorigenesis. To investigate the mechanism by which glioma-associated oncogene family zinc finger-1 (GLI1), a crucial effector of Hh signaling, regulates Hh pathway activation, we searched for GLI1-interacting proteins. We report that the chromatin remodeling protein SNF5 (encoded by SMARCB1, hereafter called SNF5), which is inactivated in human malignant rhabdoid tumors (MRTs), interacts with GLI1. We show that Snf5 localizes to Gli1-regulated promoters and that loss of Snf5 leads to activation of the Hh-Gli pathway. Conversely, re-expression of SNF5 in MRT cells represses GLI1. Consistent with this, we show the presence of a Hh-Gli-activated gene expression profile in primary MRTs and show that GLI1 drives the growth of SNF5-deficient MRT cells in vitro and in vivo. Therefore, our studies reveal that SNF5 is a key mediator of Hh signaling and that aberrant activation of GLI1 is a previously undescribed targetable mechanism contributing to the growth of MRT cells.

The sensitivity of conventional DNA sequencing in tumor biopsies is limited by stromal contamination and by genetic heterogeneity within the cancer. Here, we show that microreactor-based pyrosequencing can detect rare cancer-associated sequence variations by independent and parallel sampling of multiple representatives of a given DNA fragment. This technology can thereby facilitate accurate molecular diagnosis of heterogeneous cancer specimens and enable patient selection for targeted cancer therapies.

Loss of PTEN function leads to activation of phosphoinositide 3-kinase (PI3K) signaling and Akt. Clinical trials are now testing whether mammalian target of rapamycin (mTOR) inhibition is useful in treating PTEN-null cancers. Here, we report that mTOR inhibition induced apoptosis of epithelial cells and the complete reversal of a neoplastic phenotype in the prostate of mice expressing human AKT1 in the ventral prostate. Induction of cell death required the mitochondrial pathway, as prostate-specific coexpression of BCL2 blocked apoptosis. Thus, there is an mTOR-dependent survival signal required downstream of Akt. Bcl2 expression, however, only partially restored intraluminal cell growth in the setting of mTOR inhibition. Expression profiling showed that Hif-1 alpha targets, including genes encoding most glycolytic enzymes, constituted the dominant transcriptional response to AKT activation and mTOR inhibition. These data suggest that the expansion of AKT-driven prostate epithelial cells requires mTOR-dependent survival signaling and activation of HIF-1 alpha, and that clinical resistance to mTOR inhibitors may emerge through BCL2 expression and/or upregulation of HIF-1 alpha activity.