Therapy-Induced Evolution of Human Lung Cancer Revealed by Single-Cell RNA Sequencing.

Lung cancer, the leading cause of cancer mortality, exhibits heterogeneity that enables adaptability, limits therapeutic success, and remains incompletely understood. Single-cell RNA sequencing (scRNA-seq) of metastatic lung cancer was performed using 49 clinical biopsies obtained from 30 patients before and during targeted therapy. Over 20,000 cancer and tumor microenvironment (TME) single-cell profiles exposed a rich and dynamic tumor ecosystem. scRNA-seq of cancer cells illuminated targetable oncogenes beyond those detected clinically. Cancer cells surviving therapy as residual disease (RD) expressed an alveolar-regenerative cell signature suggesting a therapy-induced primitive cell-state transition, whereas those present at on-therapy progressive disease (PD) upregulated kynurenine, plasminogen, and gap-junction pathways. Active T-lymphocytes and decreased macrophages were present at RD and immunosuppressive cell states characterized PD. Biological features revealed by scRNA-seq were biomarkers of clinical outcomes in independent cohorts. This study highlights how therapy-induced adaptation of the multi-cellular ecosystem of metastatic cancer shapes clinical outcomes.

UDP-glucose pyrophosphorylase 2, a regulator of glycogen synthesis and glycosylation, is critical for pancreatic cancer growth.

UDP-glucose pyrophosphorylase 2 (UGP2), the enzyme that synthesizes uridine diphosphate (UDP)-glucose, rests at the convergence of multiple metabolic pathways, however, the role of UGP2 in tumor maintenance and cancer metabolism remains unclear. Here, we identify an important role for UGP2 in the maintenance of pancreatic ductal adenocarcinoma (PDAC) growth in both in vitro and in vivo tumor models. We found that transcription of UGP2 is directly regulated by the Yes-associated protein 1 (YAP)-TEA domain transcription factor (TEAD) complex, identifying UGP2 as a bona fide YAP target gene. Loss of UGP2 leads to decreased intracellular glycogen levels and defects in N-glycosylation targets that are important for the survival of PDACs, including the epidermal growth factor receptor (EGFR). These critical roles of UGP2 in cancer maintenance, metabolism, and protein glycosylation may offer insights into therapeutic options for otherwise intractable PDACs.

Global analysis of host-pathogen interactions that regulate early-stage HIV-1 replication.

Human Immunodeficiency Viruses (HIV-1 and HIV-2) rely upon host-encoded proteins to facilitate their replication. Here, we combined genome-wide siRNA analyses with interrogation of human interactome databases to assemble a host-pathogen biochemical network containing 213 confirmed host cellular factors and 11 HIV-1-encoded proteins. Protein complexes that regulate ubiquitin conjugation, proteolysis, DNA-damage response, and RNA splicing were identified as important modulators of early-stage HIV-1 infection. Additionally, over 40 new factors were shown to specifically influence the initiation and/or kinetics of HIV-1 DNA synthesis, including cytoskeletal regulatory proteins, modulators of posttranslational modification, and nucleic acid-binding proteins. Finally, 15 proteins with diverse functional roles, including nuclear transport, prostaglandin synthesis, ubiquitination, and transcription, were found to influence nuclear import or viral DNA integration. Taken together, the multiscale approach described here has uncovered multiprotein virus-host interactions that likely act in concert to facilitate the early steps of HIV-1 infection.

Kinome rewiring reveals AURKA limits PI3K-pathway inhibitor efficacy in breast cancer.

Dysregulation of the PI3K-AKT-mTOR signaling network is a prominent feature of breast cancers. However, clinical responses to drugs targeting this pathway have been modest, possibly because of dynamic changes in cellular signaling that drive resistance and limit drug efficacy. Using a quantitative chemoproteomics approach, we mapped kinome dynamics in response to inhibitors of this pathway and identified signaling changes that correlate with drug sensitivity. Maintenance of AURKA after drug treatment was associated with resistance in breast cancer models. Incomplete inhibition of AURKA was a common source of therapy failure, and combinations of PI3K, AKT or mTOR inhibitors with the AURKA inhibitor MLN8237 were highly synergistic and durably suppressed mTOR signaling, resulting in apoptosis and tumor regression in vivo. This signaling map identifies survival factors whose presence limits the efficacy of targeted therapies and reveals new drug combinations that may unlock the full potential of PI3K-AKT-mTOR pathway inhibitors in breast cancer.

Mapping the molecular determinants of BRAF oncogene dependence in human lung cancer.

Oncogenic mutations in the BRAF kinase occur in 6-8% of nonsmall cell lung cancers (NSCLCs), accounting for more than 90,000 deaths annually worldwide. The biological and clinical relevance of these BRAF mutations in NSCLC is incompletely understood. Here we demonstrate that human NSCLC cells with BRAF(V600E), but not other BRAF mutations, initially are sensitive to BRAF-inhibitor treatment. However, these BRAF(V600E) NSCLC cells rapidly acquire resistance to BRAF inhibition through at least one of two discrete molecular mechanisms: (i) loss of full-length BRAF(V600E) coupled with expression of an aberrant form of BRAF(V600E) that retains RAF pathway dependence or (ii) constitutive autocrine EGF receptor (EGFR) signaling driven by c-Jun-mediated EGFR ligand expression. BRAF(V600E) cells with EGFR-driven resistance are characterized by hyperphosphorylated protein kinase AKT, a biomarker we validated in BRAF inhibitor-resistant NSCLC clinical specimens. These data reveal the multifaceted molecular mechanisms by which NSCLCs establish and regulate BRAF oncogene dependence, provide insights into BRAF-EGFR signaling crosstalk, and uncover mechanism-based strategies to optimize clinical responses to BRAF oncogene inhibition.

Quantitative genetic-interaction mapping in mammalian cells.

Mapping genetic interactions (GIs) by simultaneously perturbing pairs of genes is a powerful tool for understanding complex biological phenomena. Here we describe an experimental platform for generating quantitative GI maps in mammalian cells using a combinatorial RNA interference strategy. We performed ∼11,000 pairwise knockdowns in mouse fibroblasts, focusing on 130 factors involved in chromatin regulation to create a GI map. Comparison of the GI and protein-protein interaction (PPI) data revealed that pairs of genes exhibiting positive GIs and/or similar genetic profiles were predictive of the corresponding proteins being physically associated. The mammalian GI map identified pathways and complexes but also resolved functionally distinct submodules within larger protein complexes. By integrating GI and PPI data, we created a functional map of chromatin complexes in mouse fibroblasts, revealing that the PAF complex is a central player in the mammalian chromatin landscape.

Human host factors required for influenza virus replication.

Influenza A virus is an RNA virus that encodes up to 11 proteins and this small coding capacity demands that the virus use the host cellular machinery for many aspects of its life cycle. Knowledge of these host cell requirements not only informs us of the molecular pathways exploited by the virus but also provides further targets that could be pursued for antiviral drug development. Here we use an integrative systems approach, based on genome-wide RNA interference screening, to identify 295 cellular cofactors required for early-stage influenza virus replication. Within this group, those involved in kinase-regulated signalling, ubiquitination and phosphatase activity are the most highly enriched, and 181 factors assemble into a highly significant host-pathogen interaction network. Moreover, 219 of the 295 factors were confirmed to be required for efficient wild-type influenza virus growth, and further analysis of a subset of genes showed 23 factors necessary for viral entry, including members of the vacuolar ATPase (vATPase) and COPI-protein families, fibroblast growth factor receptor (FGFR) proteins, and glycogen synthase kinase 3 (GSK3)-beta. Furthermore, 10 proteins were confirmed to be involved in post-entry steps of influenza virus replication. These include nuclear import components, proteases, and the calcium/calmodulin-dependent protein kinase (CaM kinase) IIbeta (CAMK2B). Notably, growth of swine-origin H1N1 influenza virus is also dependent on the identified host factors, and we show that small molecule inhibitors of several factors, including vATPase and CAMK2B, antagonize influenza virus replication.

A genetic interaction map of RNA-processing factors reveals links between Sem1/Dss1-containing complexes and mRNA export and splicing.

We used a quantitative, high-density genetic interaction map, or E-MAP (Epistatic MiniArray Profile), to interrogate the relationships within and between RNA-processing pathways. Due to their complexity and the essential roles of many of the components, these pathways have been difficult to functionally dissect. Here, we report the results for 107,155 individual interactions involving 552 mutations, 166 of which are hypomorphic alleles of essential genes. Our data enabled the discovery of links between components of the mRNA export and splicing machineries and Sem1/Dss1, a component of the 19S proteasome. In particular, we demonstrate that Sem1 has a proteasome-independent role in mRNA export as a functional component of the Sac3-Thp1 complex. Sem1 also interacts with Csn12, a component of the COP9 signalosome. Finally, we show that Csn12 plays a role in pre-mRNA splicing, which is independent of other signalosome components. Thus, Sem1 is involved in three separate and functionally distinct complexes.

An inflamed tumor cell subpopulation promotes chemotherapy resistance in triple negative breast cancer.

Individual cancers are composed of heterogeneous tumor cells with distinct phenotypes and genotypes, with triple negative breast cancers (TNBC) demonstrating the most heterogeneity among breast cancer types. Variability in transcriptional phenotypes could meaningfully limit the efficacy of monotherapies and fuel drug resistance, although to an unknown extent. To determine if transcriptional differences between tumor cells lead to differential drug responses we performed single cell RNA-seq on cell line and PDX models of breast cancer revealing cell subpopulations in states associated with resistance to standard-of-care therapies. We found that TNBC models contained a subpopulation in an inflamed cellular state, often also present in human breast cancer samples. Inflamed cells display evidence of heightened cGAS/STING signaling which we demonstrate is sufficient to cause tumor cell resistance to chemotherapy. Accordingly, inflamed cells were enriched in human tumors taken after neoadjuvant chemotherapy and associated with early recurrence, highlighting the potential for diverse tumor cell states to promote drug resistance.

Focal adhesion kinase-YAP signaling axis drives drug-tolerant persister cells and residual disease in lung cancer.

Targeted therapy is effective in many tumor types including lung cancer, the leading cause of cancer mortality. Paradigm defining examples are targeted therapies directed against non-small cell lung cancer (NSCLC) subtypes with oncogenic alterations in EGFR, ALK and KRAS. The success of targeted therapy is limited by drug-tolerant persister cells (DTPs) which withstand and adapt to treatment and comprise the residual disease state that is typical during treatment with clinical targeted therapies. Here, we integrate studies in patient-derived and immunocompetent lung cancer models and clinical specimens obtained from patients on targeted therapy to uncover a focal adhesion kinase (FAK)-YAP signaling axis that promotes residual disease during oncogenic EGFR-, ALK-, and KRAS-targeted therapies. FAK-YAP signaling inhibition combined with the primary targeted therapy suppressed residual drug-tolerant cells and enhanced tumor responses. This study unveils a FAK-YAP signaling module that promotes residual disease in lung cancer and mechanism-based therapeutic strategies to improve tumor response.

Coevolution within a transcriptional network by compensatory trans and cis mutations.

Transcriptional networks have been shown to evolve very rapidly, prompting questions as to how such changes arise and are tolerated. Recent comparisons of transcriptional networks across species have implicated variations in the cis-acting DNA sequences near genes as the main cause of divergence. What is less clear is how these changes interact with trans-acting changes occurring elsewhere in the genetic circuit. Here, we report the discovery of a system of compensatory trans and cis mutations in the yeast AP-1 transcriptional network that allows for conserved transcriptional regulation despite continued genetic change. We pinpoint a single species, the fungal pathogen Candida glabrata, in which a trans mutation has occurred very recently in a single AP-1 family member, distinguishing it from its Saccharomyces ortholog. Comparison of chromatin immunoprecipitation profiles between Candida and Saccharomyces shows that, despite their different DNA-binding domains, the AP-1 orthologs regulate a conserved block of genes. This conservation is enabled by concomitant changes in the cis-regulatory motifs upstream of each gene. Thus, both trans and cis mutations have perturbed the yeast AP-1 regulatory system in such a way as to compensate for one another. This demonstrates an example of "coevolution" between a DNA-binding transcription factor and its cis-regulatory site, reminiscent of the coevolution of protein binding partners.

A human MAP kinase interactome.

Mitogen-activated protein kinase (MAPK) pathways form the backbone of signal transduction in the mammalian cell. Here we applied a systematic experimental and computational approach to map 2,269 interactions between human MAPK-related proteins and other cellular machinery and to assemble these data into functional modules. Multiple lines of evidence including conservation with yeast supported a core network of 641 interactions. Using small interfering RNA knockdowns, we observed that approximately one-third of MAPK-interacting proteins modulated MAPK-mediated signaling. We uncovered the Na-H exchanger NHE1 as a potential MAPK scaffold, found links between HSP90 chaperones and MAPK pathways and identified MUC12 as the human analog to the yeast signaling mucin Msb2. This study makes available a large resource of MAPK interactions and clone libraries, and it illustrates a methodology for probing signaling networks based on functional refinement of experimentally derived protein-interaction maps.

A bi-steric mTORC1-selective inhibitor overcomes drug resistance in breast cancer.

Activation of the PI3K-mTOR pathway is central to breast cancer pathogenesis including resistance to many targeted therapies. The mTOR kinase forms two distinct complexes, mTORC1 and mTORC2, and understanding which is required for the survival of malignant cells has been limited by tools to selectively and completely impair either subcomplex. To address this, we used RMC-6272, a bi-steric molecule with a rapamycin-like moiety linked to an mTOR active-site inhibitor that displays >25-fold selectivity for mTORC1 over mTORC2 substrates. Complete suppression of mTORC1 by RMC-6272 causes apoptosis in ER+/HER2- breast cancer cell lines, particularly in those that harbor mutations in PIK3CA or PTEN, due to inhibition of the rapamycin resistant, mTORC1 substrate 4EBP1 and reduction of the pro-survival protein MCL1. RMC-6272 reduced translation of ribosomal mRNAs, MYC target genes, and components of the CDK4/6 pathway, suggesting enhanced impairment of oncogenic pathways compared to the partial mTORC1 inhibitor everolimus. RMC-6272 maintained efficacy in hormone therapy-resistant acquired cell lines and patient-derived xenografts (PDX), showed increased efficacy in CDK4/6 inhibitor treated acquired resistant cell lines versus their parental counterparts, and was efficacious in a PDX from a patient experiencing resistance to CDK4/6 inhibition. Bi-steric mTORC1-selective inhibition may be effective in overcoming multiple forms of therapy-resistance in ER+ breast cancers.

Computational drug repositioning for the identification of new agents to sensitize drug-resistant breast tumors across treatments and receptor subtypes.

Introduction: Drug resistance is a major obstacle in cancer treatment and can involve a variety of different factors. Identifying effective therapies for drug resistant tumors is integral for improving patient outcomes. Methods: In this study, we applied a computational drug repositioning approach to identify potential agents to sensitize primary drug resistant breast cancers. We extracted drug resistance profiles from the I-SPY 2 TRIAL, a neoadjuvant trial for early stage breast cancer, by comparing gene expression profiles of responder and non-responder patients stratified into treatments within HR/HER2 receptor subtypes, yielding 17 treatment-subtype pairs. We then used a rank-based pattern-matching strategy to identify compounds in the Connectivity Map, a database of cell line derived drug perturbation profiles, that can reverse these signatures in a breast cancer cell line. We hypothesize that reversing these drug resistance signatures will sensitize tumors to treatment and prolong survival. Results: We found that few individual genes are shared among the drug resistance profiles of different agents. At the pathway level, however, we found enrichment of immune pathways in the responders in 8 treatments within the HR+HER2+, HR+HER2-, and HR-HER2- receptor subtypes. We also found enrichment of estrogen response pathways in the non-responders in 10 treatments primarily within the hormone receptor positive subtypes. Although most of our drug predictions are unique to treatment arms and receptor subtypes, our drug repositioning pipeline identified the estrogen receptor antagonist fulvestrant as a compound that can potentially reverse resistance across 13/17 of the treatments and receptor subtypes including HR+ and triple negative. While fulvestrant showed limited efficacy when tested in a panel of 5 paclitaxel resistant breast cancer cell lines, it did increase drug response in combination with paclitaxel in HCC-1937, a triple negative breast cancer cell line. Conclusion: We applied a computational drug repurposing approach to identify potential agents to sensitize drug resistant breast cancers in the I-SPY 2 TRIAL. We identified fulvestrant as a potential drug hit and showed that it increased response in a paclitaxel-resistant triple negative breast cancer cell line, HCC-1937, when treated in combination with paclitaxel.

Novel Regulators of Macropinocytosis-Dependent Growth Revealed by Informer Set Library Screening in Pancreatic Cancer Cells.

Cancer cells utilize multiple nutrient scavenging mechanisms to support growth and survival in nutrient-poor, hypoxic tumor microenvironments. Among these mechanisms, macropinocytosis has emerged as an important pathway of extracellular nutrient acquisition in cancer cells, particularly in tumors with activated RAS signaling, such as pancreatic cancer. However, the absence of a clinically available inhibitor, as well as the gap of knowledge in macropinocytosis regulation, remain a hurdle for its use for cancer therapy. Here, we use the Informer set library to identify novel regulators of macropinocytosis-dependent growth in pancreatic cancer cells. Understanding how these regulators function will allow us to provide novel opportunities for therapeutic intervention.

Trans-channel fluorescence learning improves high-content screening for Alzheimer's disease therapeutics.

In microscopy-based drug screens, fluorescent markers carry critical information on how compounds affect different biological processes. However, practical considerations, such as the labor and preparation formats needed to produce different image channels, hinders the use of certain fluorescent markers. Consequently, completed screens may lack biologically informative but experimentally impractical markers. Here, we present a deep learning method for overcoming these limitations. We accurately generated predicted fluorescent signals from other related markers and validated this new machine learning (ML) method on two biologically distinct datasets. We used the ML method to improve the selection of biologically active compounds for Alzheimer's disease (AD) from a completed high-content high-throughput screen (HCS) that had only contained the original markers. The ML method identified novel compounds that effectively blocked tau aggregation, which had been missed by traditional screening approaches unguided by ML. The method improved triaging efficiency of compound rankings over conventional rankings by raw image channels. We reproduced this ML pipeline on a biologically independent cancer-based dataset, demonstrating its generalizability. The approach is disease-agnostic and applicable across diverse fluorescence microscopy datasets.

Host cell factors in HIV replication: meta-analysis of genome-wide studies.

We have analyzed host cell genes linked to HIV replication that were identified in nine genome-wide studies, including three independent siRNA screens. Overlaps among the siRNA screens were very modest (<7% for any pairwise combination), and similarly, only modest overlaps were seen in pairwise comparisons with other types of genome-wide studies. Combining all genes from the genome-wide studies together with genes reported in the literature to affect HIV yields 2,410 protein-coding genes, or fully 9.5% of all human genes (though of course some of these are false positive calls). Here we report an "encyclopedia" of all overlaps between studies (available at http://www.hostpathogen.org), which yielded a more extensively corroborated set of host factors assisting HIV replication. We used these genes to calculate refined networks that specify cellular subsystems recruited by HIV to assist in replication, and present additional analysis specifying host cell genes that are attractive as potential therapeutic targets.

Evolutionarily conserved herpesviral protein interaction networks.

Herpesviruses constitute a family of large DNA viruses widely spread in vertebrates and causing a variety of different diseases. They possess dsDNA genomes ranging from 120 to 240 kbp encoding between 70 to 170 open reading frames. We previously reported the protein interaction networks of two herpesviruses, varicella-zoster virus (VZV) and Kaposi's sarcoma-associated herpesvirus (KSHV). In this study, we systematically tested three additional herpesvirus species, herpes simplex virus 1 (HSV-1), murine cytomegalovirus and Epstein-Barr virus, for protein interactions in order to be able to perform a comparative analysis of all three herpesvirus subfamilies. We identified 735 interactions by genome-wide yeast-two-hybrid screens (Y2H), and, together with the interactomes of VZV and KSHV, included a total of 1,007 intraviral protein interactions in the analysis. Whereas a large number of interactions have not been reported previously, we were able to identify a core set of highly conserved protein interactions, like the interaction between HSV-1 UL33 with the nuclear egress proteins UL31/UL34. Interactions were conserved between orthologous proteins despite generally low sequence similarity, suggesting that function may be more conserved than sequence. By combining interactomes of different species we were able to systematically address the low coverage of the Y2H system and to extract biologically relevant interactions which were not evident from single species.

Cutaneous T-Cell Lymphoma PDX Drug Screening Platform Identifies Cooperation between Inhibitions of PI3Kα/δ and HDAC.

Cutaneous T-cell lymphoma is a form of non-Hodgkin lymphoma that manifests initially in the skin and disseminates systemically as the disease progresses. Mycosis fungoides and Sézary syndrome are the most common subtypes of cutaneous T-cell lymphoma. Advanced mycosis fungoides and Sézary syndrome are life threatening with few treatment options. We searched for new agents by high-throughput screening of selected targeted compounds and identified high-value targets, including phosphatidylinositol 3-kinase (PI3K) and cyclin-dependent kinases. To validate these hits from the screen, we developed patient-derived xenograft mouse models that recapitulated the cardinal features of mycosis fungoides and Sézary syndrome and maintained histologic and molecular characteristics of their clinical counterparts. Importantly, we established a blood-based biomarker assay using tumor cell-free DNA to measure systemic tumor burden longitudinally in living mice during drug therapy. A PI3K inhibitor, BKM120, was tested in our patient-derived xenograft model leading to disease attenuation and prolonged survival. Isoform-specific small interfering RNA knockdowns and isoform-selective PI3K inhibitors identified PI3K-δ as required for tumor proliferation. Additional studies showed a synergistic combination of PI3K-α/δ inhibitors with histone deacetylase inhibitors. The strong preclinical efficacy of this potent combination against multiple patient-derived xenograft models makes it an excellent candidate for further clinical development.

Integration of multiple biological contexts reveals principles of synthetic lethality that affect reproducibility.

Synthetic lethal screens have the potential to identify new vulnerabilities incurred by specific cancer mutations but have been hindered by lack of agreement between studies. In the case of KRAS, we identify that published synthetic lethal screen hits significantly overlap at the pathway rather than gene level. Analysis of pathways encoded as protein networks could identify synthetic lethal candidates that are more reproducible than those previously reported. Lack of overlap likely stems from biological rather than technical limitations as most synthetic lethal phenotypes are strongly modulated by changes in cellular conditions or genetic context, the latter determined using a pairwise genetic interaction map that identifies numerous interactions that suppress synthetic lethal effects. Accounting for pathway, cellular and genetic context nominates a DNA repair dependency in KRAS-mutant cells, mediated by a network containing BRCA1. We provide evidence for why most reported synthetic lethals are not reproducible which is addressable using a multi-faceted testing framework.