A role for the unfolded protein response stress sensor ERN1 in regulating the response to MEK inhibitors in KRAS mutant colon cancers.

BACKGROUND: Mutations in KRAS are frequent in human cancer, yet effective targeted therapeutics for these cancers are still lacking. Attempts to drug the MEK kinases downstream of KRAS have had limited success in clinical trials. Understanding the specific genomic vulnerabilities of KRAS-driven cancers may uncover novel patient-tailored treatment options. METHODS: We first searched for synthetic lethal (SL) genetic interactions with mutant RAS in yeast with the ultimate aim to identify novel cancer-specific targets for therapy. Our method used selective ploidy ablation, which enables replication of cancer-specific gene expression changes in the yeast gene disruption library. Second, we used a genome-wide CRISPR/Cas9-based genetic screen in KRAS mutant human colon cancer cells to understand the mechanistic connection between the synthetic lethal interaction discovered in yeast and downstream RAS signaling in human cells. RESULTS: We identify loss of the endoplasmic reticulum (ER) stress sensor IRE1 as synthetic lethal with activated RAS mutants in yeast. In KRAS mutant colorectal cancer cell lines, genetic ablation of the human ortholog of IRE1, ERN1, does not affect growth but sensitizes to MEK inhibition. However, an ERN1 kinase inhibitor failed to show synergy with MEK inhibition, suggesting that a non-kinase function of ERN1 confers MEK inhibitor resistance. To investigate how ERN1 modulates MEK inhibitor responses, we performed genetic screens in ERN1 knockout KRAS mutant colon cancer cells to identify genes whose inactivation confers resistance to MEK inhibition. This genetic screen identified multiple negative regulators of JUN N-terminal kinase (JNK) /JUN signaling. Consistently, compounds targeting JNK/MAPK8 or TAK1/MAP3K7, which relay signals from ERN1 to JUN, display synergy with MEK inhibition. CONCLUSIONS: We identify the ERN1-JNK-JUN pathway as a novel regulator of MEK inhibitor response in KRAS mutant colon cancer. The notion that multiple signaling pathways can activate JUN may explain why KRAS mutant tumor cells are traditionally seen as highly refractory to MEK inhibitor therapy. Our findings emphasize the need for the development of new therapeutics targeting JUN activating kinases, TAK1 and JNK, to sensitize KRAS mutant cancer cells to MEK inhibitors.

Early-onset torsion dystonia: a novel high-throughput yeast genetic screen for factors modifying protein levels of torsinAΔE.

Dystonia is the third most common movement disorder, but its diagnosis and treatment remain challenging. One of the most severe types of dystonia is early-onset torsion dystonia (EOTD). The best studied and validated EOTD-associated mutation, torsinAΔE, is a deletion of a C-terminal glutamate residue in the AAA+ ATPase torsinA. TorsinA appears to be an endoplasmic reticulum (ER)/nuclear envelope chaperone with multiple roles in the secretory pathway and in determining subcellular architecture. Many functions are disabled in the torsinAΔE variant, and torsinAΔE is also less stable than wild-type torsinA and is a substrate for ER-associated degradation. Nevertheless, the molecular factors involved in the biogenesis and degradation of torsinA and torsinAΔE have not been fully explored. To identify conserved cellular factors that can alter torsinAΔE protein levels, we designed a new high-throughput, automated, genome-wide screen utilizing our validated Saccharomyces cerevisiae torsinA expression system. By analyzing the yeast non-essential gene deletion collection, we identified 365 deletion strains with altered torsinAΔE steady-state levels. One notable hit was EUG1, which encodes a member of the protein disulfide isomerase family (PDIs). PDIs reside in the ER and catalyze the formation of disulfide bonds, mediate protein quality control and aid in nascent protein folding. We validated the role of select human PDIs in torsinA biogenesis in mammalian cells and found that overexpression of PDIs reduced the levels of torsinA and torsinAΔE. Together, our data report the first genome-wide screen to identify cellular factors that alter expression levels of the EOTD-associated protein torsinAΔE. More generally, the identified hits help in dissecting the cellular machinery involved in folding and degrading a torsinA variant, and constitute potential therapeutic factors for EOTD. This screen can also be readily adapted to identify factors impacting the levels of any protein of interest, considerably expanding the applicability of yeast in both basic and applied research.

A Synthetic Dosage Lethal Genetic Interaction Between CKS1B and PLK1 Is Conserved in Yeast and Human Cancer Cells.

The CKS1B gene located on chromosome 1q21 is frequently amplified in breast, lung, and liver cancers. CKS1B codes for a conserved regulatory subunit of cyclin-CDK complexes that function at multiple stages of cell cycle progression. We used a high throughput screening protocol to mimic cancer-related overexpression in a library of Saccharomyces cerevisiae mutants to identify genes whose functions become essential only when CKS1 is overexpressed, a synthetic dosage lethal (SDL) interaction. Mutations in multiple genes affecting mitotic entry and mitotic exit are highly enriched in the set of SDL interactions. The interactions between Cks1 and the mitotic entry checkpoint genes require the inhibitory activity of Swe1 on the yeast cyclin-dependent kinase (CDK), Cdc28. In addition, the SDL interactions of overexpressed CKS1 with mutations in the mitotic exit network are suppressed by modulating expression of the CDK inhibitor Sic1. Mutation of the polo-like kinase Cdc5, which functions in both the mitotic entry and mitotic exit pathways, is lethal in combination with overexpressed CKS1 Therefore we investigated the effect of targeting the human Cdc5 ortholog, PLK1, in breast cancers with various expression levels of human CKS1B Growth inhibition by PLK1 knockdown correlates with increased CKS1B expression in published tumor cell data sets, and this correlation was confirmed using shRNAs against PLK1 in tumor cell lines. In addition, we overexpressed CKS1B in multiple cell lines and found increased sensitivity to PLK1 knockdown and PLK1 drug inhibition. Finally, combined inhibition of WEE1 and PLK1 results in less apoptosis than predicted based on an additive model of the individual inhibitors, showing an epistatic interaction and confirming a prediction of the yeast data. Thus, identification of a yeast SDL interaction uncovers conserved genetic interactions that can affect human cancer cell viability.

Physical and genetic-interaction density reveals functional organization and informs significance cutoffs in genome-wide screens.

Genome-wide experiments often measure quantitative differences between treated and untreated cells to identify affected strains. For these studies, statistical models are typically used to determine significance cutoffs. We developed a method termed "CLIK" (Cutoff Linked to Interaction Knowledge) that overlays biological knowledge from the interactome on screen results to derive a cutoff. The method takes advantage of the fact that groups of functionally related interacting genes often respond similarly to experimental conditions and, thus, cluster in a ranked list of screen results. We applied CLIK analysis to five screens of the yeast gene disruption library and found that it defined a significance cutoff that differed from traditional statistics. Importantly, verification experiments revealed that the CLIK cutoff correlated with the position in the rank order where the rate of true positives drops off significantly. In addition, the gene sets defined by CLIK analysis often provide further biological perspectives. For example, applying CLIK analysis retrospectively to a screen for cisplatin sensitivity allowed us to identify the importance of the Hrq1 helicase in DNA crosslink repair. Furthermore, we demonstrate the utility of CLIK to determine optimal treatment conditions by analyzing genome-wide screens at multiple rapamycin concentrations. We show that CLIK is an extremely useful tool for evaluating screen quality, determining screen cutoffs, and comparing results between screens. Furthermore, because CLIK uses previously annotated interaction data to determine biologically informed cutoffs, it provides additional insights into screen results, which supplement traditional statistical approaches.

ScreenTroll: a searchable database to compare genome-wide yeast screens.

Systematic biological screens typically identify many genes or proteins that are implicated in a specific phenotype. However, deriving mechanistic insight from these screens typically involves focusing upon one or a few genes within the set in order to elucidate their precise role in producing the phenotype. To find these critical genes, researchers use a variety of tools to query the set of genes to uncover underlying common genetic or physical interactions or common functional annotations (e.g. gene ontology terms). Not only it is necessary to find previous screens containing genes in common with the new set, but also useful to easily access the individual manuscript or study that classified those genes. Unfortunately, no tool currently exists to facilitate this task. We have developed a web-based tool (ScreenTroll) that queries one or more genes against a database of systematic yeast screens. The software determines which genome-wide yeast screens also identified the queried gene(s) and the resulting screens are listed in an order based on the extent of the overlap between the queried gene(s) and the open reading frames (ORFs) characterized in each individual yeast screen. In a separate list, the corresponding ORFs that are found in both the queried set of genes and each individual genome-wide screen are displayed along with links to the relevant manuscript via NIH's PubMed database. ScreenTroll is useful for comparing a list of ORFs with genes identified in a wide array of published genome-wide screens. This comparison informs users whether any of their queried ORFs overlaps a previous study in the ScreenTroll database. By listing the manuscript of the published screen, users can read more about the phenotype associated with that study. Together, this information provides insight into the function of the queried genes and helps the user focus on a subset of them.

Sec24p and Sec16p cooperate to regulate the GTP cycle of the COPII coat.

Vesicle budding from the endoplasmic reticulum (ER) employs a cycle of GTP binding and hydrolysis to regulate assembly of the COPII coat. We have identified a novel mutation (sec24-m11) in the cargo-binding subunit, Sec24p, that specifically impacts the GTP-dependent generation of vesicles in vitro. Using a high-throughput approach, we defined genetic interactions between sec24-m11 and a variety of trafficking components of the early secretory pathway, including the candidate COPII regulators, Sed4p and Sec16p. We defined a fragment of Sec16p that markedly inhibits the Sec23p- and Sec31p-stimulated GTPase activity of Sar1p, and demonstrated that the Sec24p-m11 mutation diminished this inhibitory activity, likely by perturbing the interaction of Sec24p with Sec16p. The consequence of the heightened GTPase activity when Sec24p-m11 is present is the generation of smaller vesicles, leading to accumulation of ER membranes and more stable ER exit sites. We propose that association of Sec24p with Sec16p creates a novel regulatory complex that retards the GTPase activity of the COPII coat to prevent premature vesicle scission, pointing to a fundamental role for GTP hydrolysis in vesicle release rather than in coat assembly/disassembly.

Srs2 overexpression reveals a helicase-independent role at replication forks that requires diverse cell functions.

Srs2 is a 3'-5' DNA helicase that regulates many aspects of DNA metabolism in Saccharomyces cerevisiae. It is best known for its ability to counteract homologous recombination by dismantling Rad51 filaments, but is also involved in checkpoint activation, adaptation and recovery, and in resolution of late recombination intermediates. To further address its biological roles and uncover new genetic interactions, we examined the consequences of overexpressing SRS2 as well as two helicase-dead mutants, srs2-K41A and srs2-K41R, in the collection of 4827 yeast haploid deletion mutants. We identified 274 genes affecting a large variety of cellular functions that are required for cell growth when SRS2 or its mutants are overexpressed. Further analysis of these interactions reveals that Srs2 acts independently of its helicase function at replication forks likely through its recruitment by the sumoylated PCNA replication clamp. This helicase-independent function is responsible for the negative interactions with DNA metabolism genes and for the toxicity of SRS2 overexpression in many of the diverse cellular pathways revealed in our screens.

Long telomeres are preferentially extended during recombination-mediated telomere maintenance.

Most human somatic cells do not express telomerase. Consequently, with each cell division their telomeres progressively shorten until replicative senescence is induced. Around 15% of human cancers maintain their telomeres using telomerase-independent, recombination-based mechanisms that are collectively termed 'alternative lengthening of telomeres' (ALT). In the yeast Saccharomyces cerevisiae, ALT cells are referred to as 'survivors'. One type of survivor (type II) resembles human ALT cells in that both are defined by the amplification of telomeric repeats. We analyzed recombination-mediated telomere extension events at individual telomeres in telomerase-negative yeast during the formation of type II survivors and found that long telomeres were preferentially extended. Furthermore, senescent cells with long telomeres were more efficient at bypassing senescence by the type II pathway. We speculate that telomere length may be important in determining whether cancer cells use telomerase or ALT to bypass replicative senescence.

ScreenMill: a freely available software suite for growth measurement, analysis and visualization of high-throughput screen data.

BACKGROUND: Many high-throughput genomic experiments, such as Synthetic Genetic Array and yeast two-hybrid, use colony growth on solid media as a screen metric. These experiments routinely generate over 100,000 data points, making data analysis a time consuming and painstaking process. Here we describe ScreenMill, a new software suite that automates image analysis and simplifies data review and analysis for high-throughput biological experiments. RESULTS: The ScreenMill, software suite includes three software tools or "engines": an open source Colony Measurement Engine (CM Engine) to quantitate colony growth data from plate images, a web-based Data Review Engine (DR Engine) to validate and analyze quantitative screen data, and a web-based Statistics Visualization Engine (SV Engine) to visualize screen data with statistical information overlaid. The methods and software described here can be applied to any screen in which growth is measured by colony size. In addition, the DR Engine and SV Engine can be used to visualize and analyze other types of quantitative high-throughput data. CONCLUSIONS: ScreenMill automates quantification, analysis and visualization of high-throughput screen data. The algorithms implemented in ScreenMill are transparent allowing users to be confident about the results ScreenMill produces. Taken together, the tools of ScreenMill offer biologists a simple and flexible way of analyzing their data, without requiring programming skills.