Paradoxical Increase of Permeability and Lipophilicity with the Increasing Topological Polar Surface Area within a Series of PRMT5 Inhibitors.

An imidazolone → triazolone replacement addressed the limited passive permeability of a series of protein arginine methyl transferase 5 (PRMT5) inhibitors. This increase in passive permeability was unexpected given the increase in the hydrogen bond acceptor (HBA) count and topological polar surface area (TPSA), two descriptors that are typically inversely correlated with permeability. Quantum mechanics (QM) calculations revealed that this unusual effect was due to an electronically driven disconnect between TPSA and 3D-PSA, which manifests in a reduction in overall HBA strength as indicated by the HBA moment descriptor from COSMO-RS (conductor-like screening model for real solvation). HBA moment was subsequently deployed as a design parameter leading to the discovery of inhibitors with not only improved passive permeability but also reduced P-glycoprotein (P-gp) transport. Our case study suggests that hidden polarity as quantified by TPSA-3DPSA can be rationally designed through QM calculations.

SHP2 blockade enhances anti-tumor immunity via tumor cell intrinsic and extrinsic mechanisms.

SHP2 is a ubiquitous tyrosine phosphatase involved in regulating both tumor and immune cell signaling. In this study, we discovered a novel immune modulatory function of SHP2. Targeting this protein with allosteric SHP2 inhibitors promoted anti-tumor immunity, including enhancing T cell cytotoxic function and immune-mediated tumor regression. Knockout of SHP2 using CRISPR/Cas9 gene editing showed that targeting SHP2 in cancer cells contributes to this immune response. Inhibition of SHP2 activity augmented tumor intrinsic IFNγ signaling resulting in enhanced chemoattractant cytokine release and cytotoxic T cell recruitment, as well as increased expression of MHC Class I and PD-L1 on the cancer cell surface. Furthermore, SHP2 inhibition diminished the differentiation and inhibitory function of immune suppressive myeloid cells in the tumor microenvironment. SHP2 inhibition enhanced responses to anti-PD-1 blockade in syngeneic mouse models. Overall, our study reveals novel functions of SHP2 in tumor immunity and proposes that targeting SHP2 is a promising strategy for cancer immunotherapy.

Tumor Intrinsic Efficacy by SHP2 and RTK Inhibitors in KRAS-Mutant Cancers.

KRAS, an oncogene mutated in nearly one third of human cancers, remains a pharmacologic challenge for direct inhibition except for recent advances in selective inhibitors targeting the G12C variant. Here, we report that selective inhibition of the protein tyrosine phosphatase, SHP2, can impair the proliferation of KRAS-mutant cancer cells in vitro and in vivo using cell line xenografts and primary human tumors. In vitro, sensitivity of KRAS-mutant cells toward the allosteric SHP2 inhibitor, SHP099, is not apparent when cells are grown on plastic in 2D monolayer, but is revealed when cells are grown as 3D multicellular spheroids. This antitumor activity is also observed in vivo in mouse models. Interrogation of the MAPK pathway in SHP099-treated KRAS-mutant cancer models demonstrated similar modulation of p-ERK and DUSP6 transcripts in 2D, 3D, and in vivo, suggesting a MAPK pathway-dependent mechanism and possible non-MAPK pathway-dependent mechanisms in tumor cells or tumor microenvironment for the in vivo efficacy. For the KRASG12C MIAPaCa-2 model, we demonstrate that the efficacy is cancer cell intrinsic as there is minimal antiangiogenic activity by SHP099, and the effects of SHP099 is recapitulated by genetic depletion of SHP2 in cancer cells. Furthermore, we demonstrate that SHP099 efficacy in KRAS-mutant models can be recapitulated with RTK inhibitors, suggesting RTK activity is responsible for the SHP2 activation. Taken together, these data reveal that many KRAS-mutant cancers depend on upstream signaling from RTK and SHP2, and provide a new therapeutic framework for treating KRAS-mutant cancers with SHP2 inhibitors.

TRPS1 Is a Lineage-Specific Transcriptional Dependency in Breast Cancer.

Perturbed epigenomic programs play key roles in tumorigenesis, and chromatin modulators are candidate therapeutic targets in various human cancer types. To define singular and shared dependencies on DNA and histone modifiers and transcription factors in poorly differentiated adult and pediatric cancers, we conducted a targeted shRNA screen across 59 cell lines of 6 cancer types. Here, we describe the TRPS1 transcription factor as a strong breast cancer-specific hit, owing largely to lineage-restricted expression. Knockdown of TRPS1 resulted in perturbed mitosis, apoptosis, and reduced tumor growth. Integrated analysis of TRPS1 transcriptional targets, chromatin binding, and protein interactions revealed that TRPS1 is associated with the NuRD repressor complex. These findings uncover a transcriptional network that is essential for breast cancer cell survival and propagation.

Generation of High-Throughput Three-Dimensional Tumor Spheroids for Drug Screening.

Cancer cells have routinely been cultured in two dimensions (2D) on a plastic surface. This technique, however, lacks the true environment a tumor mass is exposed to in vivo. Solid tumors grow not as a sheet attached to plastic, but instead as a collection of clonal cells in a three-dimensional (3D) space interacting with their neighbors, and with distinct spatial properties such as the disruption of normal cellular polarity. These interactions cause 3D-cultured cells to acquire morphological and cellular characteristics which are more relevant to in vivo tumors. Additionally, a tumor mass is in direct contact with other cell types such as stromal and immune cells, as well as the extracellular matrix from all other cell types. The matrix deposited is comprised of macromolecules such as collagen and fibronectin. In an attempt to increase the translation of research findings in oncology from bench to bedside, many groups have started to investigate the use of 3D model systems in their drug development strategies. These systems are thought to be more physiologically relevant because they attempt to recapitulate the complex and heterogeneous environment of a tumor. These systems, however, can be quite complex, and, although amenable to growth in 96-well formats, and some now even in 384, they offer few choices for large-scale growth and screening. This observed gap has led to the development of the methods described here in detail to culture tumor spheroids in a high-throughput capacity in 1536-well plates. These methods represent a compromise to the highly complex matrix-based systems, which are difficult to screen, and conventional 2D assays. A variety of cancer cell lines harboring different genetic mutations are successfully screened, examining compound efficacy by using a curated library of compounds targeting the Mitogen-Activated Protein Kinase or MAPK pathway. The spheroid culture responses are then compared to the response of cells grown in 2D, and differential activities are reported. These methods provide a unique protocol for testing compound activity in a high-throughput 3D setting.

A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles.

We previously piloted the concept of a Connectivity Map (CMap), whereby genes, drugs, and disease states are connected by virtue of common gene-expression signatures. Here, we report more than a 1,000-fold scale-up of the CMap as part of the NIH LINCS Consortium, made possible by a new, low-cost, high-throughput reduced representation expression profiling method that we term L1000. We show that L1000 is highly reproducible, comparable to RNA sequencing, and suitable for computational inference of the expression levels of 81% of non-measured transcripts. We further show that the expanded CMap can be used to discover mechanism of action of small molecules, functionally annotate genetic variants of disease genes, and inform clinical trials. The 1.3 million L1000 profiles described here, as well as tools for their analysis, are available at https://clue.io.

Project DRIVE: A Compendium of Cancer Dependencies and Synthetic Lethal Relationships Uncovered by Large-Scale, Deep RNAi Screening.

Elucidation of the mutational landscape of human cancer has progressed rapidly and been accompanied by the development of therapeutics targeting mutant oncogenes. However, a comprehensive mapping of cancer dependencies has lagged behind and the discovery of therapeutic targets for counteracting tumor suppressor gene loss is needed. To identify vulnerabilities relevant to specific cancer subtypes, we conducted a large-scale RNAi screen in which viability effects of mRNA knockdown were assessed for 7,837 genes using an average of 20 shRNAs per gene in 398 cancer cell lines. We describe findings of this screen, outlining the classes of cancer dependency genes and their relationships to genetic, expression, and lineage features. In addition, we describe robust gene-interaction networks recapitulating both protein complexes and functional cooperation among complexes and pathways. This dataset along with a web portal is provided to the community to assist in the discovery and translation of new therapeutic approaches for cancer.

An epigenetic mechanism of resistance to targeted therapy in T cell acute lymphoblastic leukemia.

The identification of activating NOTCH1 mutations in T cell acute lymphoblastic leukemia (T-ALL) led to clinical testing of γ-secretase inhibitors (GSIs) that prevent NOTCH1 activation. However, responses to these inhibitors have been transient, suggesting that resistance limits their clinical efficacy. Here we modeled T-ALL resistance, identifying GSI-tolerant 'persister' cells that expand in the absence of NOTCH1 signaling. Rare persisters are already present in naive T-ALL populations, and the reversibility of their phenotype suggests an epigenetic mechanism. Relative to GSI-sensitive cells, persister cells activate distinct signaling and transcriptional programs and exhibit chromatin compaction. A knockdown screen identified chromatin regulators essential for persister viability, including BRD4. BRD4 binds enhancers near critical T-ALL genes, including MYC and BCL2. The BRD4 inhibitor JQ1 downregulates expression of these targets and induces growth arrest and apoptosis in persister cells, at doses well tolerated by GSI-sensitive cells. Consistently, the GSI-JQ1 combination was found to be effective against primary human leukemias in vivo. Our findings establish a role for epigenetic heterogeneity in leukemia resistance that may be addressed by incorporating epigenetic modulators in combination therapy.

ZFHX4 interacts with the NuRD core member CHD4 and regulates the glioblastoma tumor-initiating cell state.

Glioblastoma (GBM) harbors subpopulations of therapy-resistant tumor-initiating cells (TICs) that are self-renewing and multipotent. To understand the regulation of the TIC state, we performed an image-based screen for genes regulating GBM TIC maintenance and identified ZFHX4, a 397 kDa transcription factor. ZFHX4 is required to maintain TIC-associated and normal human neural precursor cell phenotypes in vitro, suggesting that ZFHX4 regulates differentiation, and its suppression increases glioma-free survival in intracranial xenografts. ZFHX4 interacts with CHD4, a core member of the nucleosome remodeling and deacetylase (NuRD) complex. ZFHX4 and CHD4 bind to overlapping sets of genomic loci and control similar gene expression programs. Using expression data derived from GBM patients, we found that ZFHX4 significantly affects CHD4-mediated gene expression perturbations, which defines ZFHX4 as a master regulator of CHD4. These observations define ZFHX4 as a regulatory factor that links the chromatin-remodeling NuRD complex and the GBM TIC state.

Identification of regulators of polyploidization presents therapeutic targets for treatment of AMKL.

The mechanism by which cells decide to skip mitosis to become polyploid is largely undefined. Here we used a high-content image-based screen to identify small-molecule probes that induce polyploidization of megakaryocytic leukemia cells and serve as perturbagens to help understand this process. Our study implicates five networks of kinases that regulate the switch to polyploidy. Moreover, we find that dimethylfasudil (diMF, H-1152P) selectively increased polyploidization, mature cell-surface marker expression, and apoptosis of malignant megakaryocytes. An integrated target identification approach employing proteomic and shRNA screening revealed that a major target of diMF is Aurora kinase A (AURKA). We further find that MLN8237 (Alisertib), a selective inhibitor of AURKA, induced polyploidization and expression of mature megakaryocyte markers in acute megakaryocytic leukemia (AMKL) blasts and displayed potent anti-AMKL activity in vivo. Our findings provide a rationale to support clinical trials of MLN8237 and other inducers of polyploidization and differentiation in AMKL.

A public genome-scale lentiviral expression library of human ORFs.

Functional characterization of the human genome requires tools for systematically modulating gene expression in both loss-of-function and gain-of-function experiments. We describe the production of a sequence-confirmed, clonal collection of over 16,100 human open-reading frames (ORFs) encoded in a versatile Gateway vector system. Using this ORFeome resource, we created a genome-scale expression collection in a lentiviral vector, thereby enabling both targeted experiments and high-throughput screens in diverse cell types.

The JAK2/STAT3 signaling pathway is required for growth of CD44⁺CD24⁻ stem cell-like breast cancer cells in human tumors.

Intratumor heterogeneity is a major clinical problem because tumor cell subtypes display variable sensitivity to therapeutics and may play different roles in progression. We previously characterized 2 cell populations in human breast tumors with distinct properties: CD44+CD24- cells that have stem cell-like characteristics, and CD44-CD24+ cells that resemble more differentiated breast cancer cells. Here we identified 15 genes required for cell growth or proliferation in CD44+CD24- human breast cancer cells in a large-scale loss-of-function screen and found that inhibition of several of these (IL6, PTGIS, HAS1, CXCL3, and PFKFB3) reduced Stat3 activation. We found that the IL-6/JAK2/Stat3 pathway was preferentially active in CD44+CD24- breast cancer cells compared with other tumor cell types, and inhibition of JAK2 decreased their number and blocked growth of xenografts. Our results highlight the differences between distinct breast cancer cell types and identify targets such as JAK2 and Stat3 that may lead to more specific and effective breast cancer therapies.

Subtype-specific genomic alterations define new targets for soft-tissue sarcoma therapy.

Soft-tissue sarcomas, which result in approximately 10,700 diagnoses and 3,800 deaths per year in the United States, show remarkable histologic diversity, with more than 50 recognized subtypes. However, knowledge of their genomic alterations is limited. We describe an integrative analysis of DNA sequence, copy number and mRNA expression in 207 samples encompassing seven major subtypes. Frequently mutated genes included TP53 (17% of pleomorphic liposarcomas), NF1 (10.5% of myxofibrosarcomas and 8% of pleomorphic liposarcomas) and PIK3CA (18% of myxoid/round-cell liposarcomas, or MRCs). PIK3CA mutations in MRCs were associated with Akt activation and poor clinical outcomes. In myxofibrosarcomas and pleomorphic liposarcomas, we found both point mutations and genomic deletions affecting the tumor suppressor NF1. Finally, we found that short hairpin RNA (shRNA)-based knockdown of several genes amplified in dedifferentiated liposarcoma, including CDK4 and YEATS4, decreased cell proliferation. Our study yields a detailed map of molecular alterations across diverse sarcoma subtypes and suggests potential subtype-specific targets for therapy.

CK1epsilon is required for breast cancers dependent on beta-catenin activity.

BACKGROUND: Aberrant beta-catenin signaling plays a key role in several cancer types, notably colon, liver and breast cancer. However approaches to modulate beta-catenin activity for therapeutic purposes have proven elusive to date. METHODOLOGY: To uncover genetic dependencies in breast cancer cells that harbor active beta-catenin signaling, we performed RNAi-based loss-of-function screens in breast cancer cell lines in which we had characterized beta-catenin activity. Here we identify CSNK1E, the gene encoding casein kinase 1 epsilon (CK1epsilon) as required specifically for the proliferation of breast cancer cells with activated beta-catenin and confirm its role as a positive regulator of beta-catenin-driven transcription. Furthermore, we demonstrate that breast cancer cells that harbor activated beta-catenin activity exhibit enhanced sensitivity to pharmacological blockade of Wnt/beta-catenin signaling. We also find that expression of CK1epsilon is able to promote oncogenic transformation of human cells in a beta-catenin-dependent manner. CONCLUSIONS/SIGNIFICANCE: These studies identify CK1epsilon as a critical contributor to activated beta-catenin signaling in cancer and suggest it may provide a potential therapeutic target for cancers that harbor active beta-catenin. More generally, these observations delineate an approach that can be used to identify druggable synthetic lethal interactions with signaling pathways that are frequently activated in cancer but are difficult to target with the currently available small molecule inhibitors.

Proteomic and genetic approaches identify Syk as an AML target.

Cell-based screening can facilitate the rapid identification of compounds inducing complex cellular phenotypes. Advancing a compound toward the clinic, however, generally requires the identification of precise mechanisms of action. We previously found that epidermal growth factor receptor (EGFR) inhibitors induce acute myeloid leukemia (AML) differentiation via a non-EGFR mechanism. In this report, we integrated proteomic and RNAi-based strategies to identify their off-target, anti-AML mechanism. These orthogonal approaches identified Syk as a target in AML. Genetic and pharmacological inactivation of Syk with a drug in clinical trial for other indications promoted differentiation of AML cells and attenuated leukemia growth in vivo. These results demonstrate the power of integrating diverse chemical, proteomic, and genomic screening approaches to identify therapeutic strategies for cancer.

Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1.

The proto-oncogene KRAS is mutated in a wide array of human cancers, most of which are aggressive and respond poorly to standard therapies. Although the identification of specific oncogenes has led to the development of clinically effective, molecularly targeted therapies in some cases, KRAS has remained refractory to this approach. A complementary strategy for targeting KRAS is to identify gene products that, when inhibited, result in cell death only in the presence of an oncogenic allele. Here we have used systematic RNA interference to detect synthetic lethal partners of oncogenic KRAS and found that the non-canonical IkappaB kinase TBK1 was selectively essential in cells that contain mutant KRAS. Suppression of TBK1 induced apoptosis specifically in human cancer cell lines that depend on oncogenic KRAS expression. In these cells, TBK1 activated NF-kappaB anti-apoptotic signals involving c-Rel and BCL-XL (also known as BCL2L1) that were essential for survival, providing mechanistic insights into this synthetic lethal interaction. These observations indicate that TBK1 and NF-kappaB signalling are essential in KRAS mutant tumours, and establish a general approach for the rational identification of co-dependent pathways in cancer.

AKT-independent signaling downstream of oncogenic PIK3CA mutations in human cancer.

Dysregulation of the phosphatidylinositol 3-kinase (PI3K) signaling pathway occurs frequently in human cancer. PTEN tumor suppressor or PIK3CA oncogene mutations both direct PI3K-dependent tumorigenesis largely through activation of the AKT/PKB kinase. However, here we show through phosphoprotein profiling and functional genomic studies that many PIK3CA mutant cancer cell lines and human breast tumors exhibit only minimal AKT activation and a diminished reliance on AKT for anchorage-independent growth. Instead, these cells retain robust PDK1 activation and membrane localization and exhibit dependency on the PDK1 substrate SGK3. SGK3 undergoes PI3K- and PDK1-dependent activation in PIK3CA mutant cancer cells. Thus, PI3K may promote cancer through both AKT-dependent and AKT-independent mechanisms. Knowledge of differential PI3K/PDK1 signaling could inform rational therapeutics in cancers harboring PIK3CA mutations.

Synthetic lethal interaction between oncogenic KRAS dependency and STK33 suppression in human cancer cells.

An alternative to therapeutic targeting of oncogenes is to perform "synthetic lethality" screens for genes that are essential only in the context of specific cancer-causing mutations. We used high-throughput RNA interference (RNAi) to identify synthetic lethal interactions in cancer cells harboring mutant KRAS, the most commonly mutated human oncogene. We find that cells that are dependent on mutant KRAS exhibit sensitivity to suppression of the serine/threonine kinase STK33 irrespective of tissue origin, whereas STK33 is not required by KRAS-independent cells. STK33 promotes cancer cell viability in a kinase activity-dependent manner by regulating the suppression of mitochondrial apoptosis mediated through S6K1-induced inactivation of the death agonist BAD selectively in mutant KRAS-dependent cells. These observations identify STK33 as a target for treatment of mutant KRAS-driven cancers and demonstrate the potential of RNAi screens for discovering functional dependencies created by oncogenic mutations that may enable therapeutic intervention for cancers with "undruggable" genetic alterations.

Scoring diverse cellular morphologies in image-based screens with iterative feedback and machine learning.

Many biological pathways were first uncovered by identifying mutants with visible phenotypes and by scoring every sample in a screen via tedious and subjective visual inspection. Now, automated image analysis can effectively score many phenotypes. In practical application, customizing an image-analysis algorithm or finding a sufficient number of example cells to train a machine learning algorithm can be infeasible, particularly when positive control samples are not available and the phenotype of interest is rare. Here we present a supervised machine learning approach that uses iterative feedback to readily score multiple subtle and complex morphological phenotypes in high-throughput, image-based screens. First, automated cytological profiling extracts hundreds of numerical descriptors for every cell in every image. Next, the researcher generates a rule (i.e., classifier) to recognize cells with a phenotype of interest during a short, interactive training session using iterative feedback. Finally, all of the cells in the experiment are automatically classified and each sample is scored based on the presence of cells displaying the phenotype. By using this approach, we successfully scored images in RNA interference screens in 2 organisms for the prevalence of 15 diverse cellular morphologies, some of which were previously intractable.