Preclinical 3D model screening reveals digoxin as an effective therapy for a rare and aggressive type of endometrial cancer.

OBJECTIVE: Dedifferentiated endometrial carcinoma (DDEC) characterized by SWItch/Sucrose Non-Fermentable (SWI/SNF) complex inactivation is a highly aggressive type of endometrial cancer without effective systemic therapy options. Its uncommon nature and aggressive disease trajectory pose significant challenges for therapeutic progress. To address this obstacle, we focused on developing preclinical models tailored to this tumor type and established patient tumor-derived three-dimensional (3D) spheroid models of DDEC. METHODS: High-throughput drug repurposing screens were performed on in vitro 3D spheroid models of DDEC cell lines (SMARCA4-inactivated DDEC-1 and ARID1A/ARID1B co-inactivated DDEC-2). The dose-response relationships of the identified candidate drugs were evaluated in vitro, followed by in vivo evaluation using xenograft models of DDEC-1 and DDEC-2. RESULTS: Drug screen in 3D models identified multiple cardiac glycosides including digoxin and digitoxin as candidate drugs in both DDEC-1 and DDEC-2. Subsequent in vitro dose-response analyses confirmed the inhibitory activity of digoxin and digitoxin with both drugs showing lower IC50 in DDEC cells compared to non-DDEC endometrial cancer cells. In in vivo xenograft models, digoxin significantly suppressed the growth of DDEC tumors at clinically relevant serum concentrations. CONCLUSION: Using biologically precise preclinical models of DDEC derived from patient tumor samples, our study identified digoxin as an effective drug in suppressing DDEC tumor growth. These findings provide compelling preclinical evidence for the use of digoxin as systemic therapy for SWI/SNF-inactivated DDEC, which may also be applicable to other SWI/SNF-inactivated tumor types.

Survey of NF1 inactivation by surrogate immunohistochemistry in ovarian carcinomas.

OBJECTIVE: Inhibition of the MAPK pathway by MEK inhibitors (MEKi) is currently a therapeutic standard in several cancer types, including ovarian low-grade serous carcinoma (LGSC). A common MAPK pathway alteration in tubo-ovarian high-grade serous carcinoma (HGSC) is the genomic inactivation of neurofibromin 1 (NF1). The primary objectives of our study were to survey the prevalence of NF1 inactivation in the principal ovarian carcinoma histotype as well as to evaluate its associations with clinico-pathological parameters and key biomarkers including BRCA1/2 status in HGSC. METHODS: A recently commercialized NF1 antibody (clone NFC) was orthogonally validated on an automated immunohistochemistry (IHC) platform and IHC was performed on tissue microarrays containing 2140 ovarian carcinoma cases. Expression was interpreted as loss/inactivated (complete or subclonal) versus normal/retained. RESULTS: Loss of NF1 expression was detected in 250/1429 (17.4%) HGSC including 11% with subclonal loss. Survival of NF1-inactivated HGSC patients was intermediate between favorable BRCA1/2 mutated HGSC and unfavorable CCNE1 high-level amplified HGSC. NF1 inactivation was mutually exclusive with CCNE1 high-level amplifications, co-occurred with RB1 loss and occurred at similar frequencies in BRCA1/2 mutated versus wild-type HGSC. NF1 loss was found in 21/286 (7.3%) endometrioid carcinomas with a favorable prognostic association (p = 0.048), and in 4/64 (5.9%) LGSC, mutually exclusive with other driver events. CONCLUSIONS: NF1 inactivation occurs in a significant subset of BRCA1/2 wild-type HGSC and a subset of LGSC. While the functional effects of NF1 inactivation need to be further characterized, this signifies a potential therapeutic opportunity to explore targeting NF1 inactivation in these tumors.

APOBEC1 cytosine deaminase activity on single-stranded DNA is suppressed by replication protein A.

Many APOBEC cytidine deaminase members are known to induce 'off-target' cytidine deaminations in 5'TC motifs in genomic DNA that contribute to cancer evolution. In this report, we characterized APOBEC1, which is a possible cancer related APOBEC since APOBEC1 mRNA is highly expressed in certain types of tumors, such as lung adenocarcinoma. We found a low level of APOBEC1-induced DNA damage, as measured by γH2AX foci, in genomic DNA of a lung cancer cell line that correlated to its inability to compete in vitro with replication protein A (RPA) for ssDNA. This suggests that RPA can act as a defense against off-target deamination for some APOBEC enzymes. Overall, the data support the model that the ability of an APOBEC to compete with RPA can better predict genomic damage than combined analysis of mRNA expression levels in tumors and analysis of mutation signatures.

Differential expression of HNF1A and HNF1A-AS1 in colon cancer cells.

The human hepatocyte nuclear factor 1 homeobox A (HNF1A) gene loci express the protein-coding HNF1A transcript and a long non-coding RNA in the anti-sense (HNF1A-AS1) direction. HNF1A-AS1 is expressed in numerous types of cancers and poor clinical outcomes such as higher mortality rates, greater metastatic capacity, and poor prognosis of the disease are the results of this expression. In this study, we determined the epigenetic features of the HNF1A gene loci, and expression and cellular localization of HNF1A-AS1 RNA, HNF1A RNA, and HNF1A protein in colorectal cancer (HT-29, HTC116, RKO, and SW480) and normal colon epithelial (CCD841) cells. The HT-29 HNF1A gene had active histone marks (H3K4me3, H3K27ac) and DNase 1 accessible sites at the promoter regions of the HNF1A and HNF1A-AS1 genes. These epigenetic marks were not observed in the other colorectal cancer cells or in the normal colon epithelial cells. Consistent with the active gene epigenetic signature of the HNF1A gene in HT-29 cells, HNF1A protein, and HNF1A/HNF1A-AS1 transcripts were detected in HT-29 cells but poorly, if at all observed, in the other cell types. In HT-29 cells, HNF1A-AS1 localized to the nucleus and was found to bind to the enhancer of zeste homolog 2 (EZH2, a member of PRC2 complex) and potentially form RNA-DNA triplexes with DNase 1 accessible sites in the HT-29 genome. These activities of HNF1A-AS1 may contribute to the oncogenic properties of this long non-coding RNA.

Identification of novel genes involved in apoptosis of HIV-infected macrophages using unbiased genome-wide screening.

BACKGROUND: Macrophages, besides resting latently infected CD4+ T cells, constitute the predominant stable, major non-T cell HIV reservoirs. Therefore, it is essential to eliminate both latently infected CD4+ T cells and tissue macrophages to completely eradicate HIV in patients. Until now, most of the research focus is directed towards eliminating latently infected CD4+ T cells. However, few approaches have been directed at killing of HIV-infected macrophages either in vitro or in vivo. HIV infection dysregulates the expression of many host genes essential for the survival of infected cells. We postulated that exploiting this alteration may yield novel targets for the selective killing of infected macrophages. METHODS: We applied a pooled shRNA-based genome-wide approach by employing a lentivirus-based library of shRNAs to screen novel gene targets whose inhibition should selectively induce apoptosis in HIV-infected macrophages. Primary human MDMs were infected with HIV-eGFP and HIV-HSA viruses. Infected MDMs were transfected with siRNAs specific for the promising genes followed by analysis of apoptosis by flow cytometry using labelled Annexin-V in HIV-infected, HIV-exposed but uninfected bystander MDMs and uninfected MDMs. The results were analyzed using student's t-test from at least four independent experiments. RESULTS: We validated 28 top hits in two independent HIV infection models. This culminated in the identification of four target genes, Cox7a2, Znf484, Cstf2t, and Cdk2, whose loss-of-function induced apoptosis preferentially in HIV-infected macrophages. Silencing these single genes killed significantly higher number of HIV-HSA-infected MDMs compared to the HIV-HSA-exposed, uninfected bystander macrophages, indicating the specificity in the killing of HIV-infected macrophages. The mechanism governing Cox7a2-mediated apoptosis of HIV-infected macrophages revealed that targeting respiratory chain complex II and IV genes also selectively induced apoptosis of HIV-infected macrophages possibly through enhanced ROS production. CONCLUSIONS: We have identified above-mentioned novel genes and specifically the respiratory chain complex II and IV genes whose silencing may cause selective elimination of HIV-infected macrophages and eventually the HIV-macrophage reservoirs. The results highlight the potential of the identified genes as targets for eliminating HIV-infected macrophages in physiological environment as part of an HIV cure strategy.

Cell-based high-throughput screen for small molecule inhibitors of Bax translocation.

Aberrant regulation of programmed cell death (PCD) has been tied to an array of human pathologies ranging from cancers to autoimmune disorders to diverse forms of neurodegeneration. Pharmacologic modulation of PCD signalling is therefore of central interest to a number of clinical and biomedical applications. A key component of PCD signalling involves the modulation of pro- and anti-apoptotic Bcl-2 family members. Among these, Bax translocation represents a critical regulatory phase in PCD. In the present study, we have employed a high-content high-throughput screen to identify small molecules which inhibit the cellular process of Bax re-distribution to the mitochondria following commitment of the cell to die. Screening of 6246 Generally Recognized As Safe compounds from four chemical libraries post-induction of cisplatin-mediated PCD resulted in the identification of 18 compounds which significantly reduced levels of Bax translocation. Further examination revealed protective effects via reduction of executioner caspase activity and enhanced mitochondrial function. Consistent with their effects on Bax translocation, these compounds exhibited significant rescue against in vitro and in vivo cisplatin-induced apoptosis. Altogether, our findings identify a new set of clinically useful small molecules PCD inhibitors and highlight the role which cAMP plays in regulating Bax-mediated PCD.

Estrogen receptor signaling regulates the expression of the breast tumor kinase in breast cancer cells.

BACKGROUND: BRK is, a non-receptor tyrosine kinase, overexpressed in approximately 85% of human invasive ductal breast tumors. It is not clear whether BRK expression correlates with breast cancer subtypes, or the expression has prognostic or diagnostic significance. Herein, we investigated the correlation of BRK with any breast cancer subtypes and clinicopathological significance of BRK expression in breast cancer. METHODS: In this study, we examined BRK expression in 120 breast tumor samples and 29 breast cancer cell lines to explore the positive correlation between BRK and the expression of ERα. We used immunohistochemistry, RT-PCR, and immunoblotting to analyse our experimental samples. RESULT: We demonstrate that estrogen induces BRK gene and protein expression in ER+ breast cancer cells. Over-expression of ERα in the ER-negative breast cancer cell line increased BRK expression, and knock-down of ESR1 in MCF7 cells reduced BRK levels. Further, we provide evidence that BRK is regulated by ERα signaling and the presence of ER antagonists (tamoxifen and fulvestrant) reduce the expression of BRK in ER-positive breast cancer cells. Finally, we demonstrate that the overall survival of ER-positive breast cancer patients is poor when their cancers express high levels of BRK. CONCLUSION: Our data indicate that BRK is a prognostic marker for ER+ breast cancers and provide a strong rationale for targeting BRK to improve patients' survival.

An integrated computational and experimental study uncovers FUT9 as a metabolic driver of colorectal cancer.

Metabolic alterations play an important role in cancer and yet, few metabolic cancer driver genes are known. Here we perform a combined genomic and metabolic modeling analysis searching for metabolic drivers of colorectal cancer. Our analysis predicts FUT9, which catalyzes the biosynthesis of Ley glycolipids, as a driver of advanced-stage colon cancer. Experimental testing reveals FUT9's complex dual role; while its knockdown enhances proliferation and migration in monolayers, it suppresses colon cancer cells expansion in tumorspheres and inhibits tumor development in a mouse xenograft models. These results suggest that FUT9's inhibition may attenuate tumor-initiating cells (TICs) that are known to dominate tumorspheres and early tumor growth, but promote bulk tumor cells. In agreement, we find that FUT9 silencing decreases the expression of the colorectal cancer TIC marker CD44 and the level of the OCT4 transcription factor, which is known to support cancer stemness. Beyond its current application, this work presents a novel genomic and metabolic modeling computational approach that can facilitate the systematic discovery of metabolic driver genes in other types of cancer.

Molecular characterization of breast cancer cell lines through multiple omic approaches.

BACKGROUND: Breast cancer cell lines are frequently used as model systems to study the cellular properties and biology of breast cancer. Our objective was to characterize a large, commonly employed panel of breast cancer cell lines obtained from the American Type Culture Collection (ATCC 30-4500 K) to enable researchers to make more informed decisions in selecting cell lines for specific studies. Information about these cell lines was obtained from a wide variety of sources. In addition, new information about cellular pathways that are activated within each cell line was generated. METHODS: We determined key protein expression data using immunoblot analyses. In addition, two analyses on serum-starved cells were carried out to identify cellular proteins and pathways that are activated in these cells. These analyses were performed using a commercial PathScan array and a novel and more extensive phosphopeptide-based kinome analysis that queries 1290 phosphorylation events in major signaling pathways. Data about this panel of breast cancer cell lines was also accessed from several online sources, compiled and summarized for the following areas: molecular classification, mRNA expression, mutational status of key proteins and other possible cancer-associated mutations, and the tumorigenic and metastatic capacity in mouse xenograft models of breast cancer. RESULTS: The cell lines that were characterized included 10 estrogen receptor (ER)-positive, 12 human epidermal growth factor receptor 2 (HER2)-amplified and 18 triple negative breast cancer cell lines, in addition to 4 non-tumorigenic breast cell lines. Within each subtype, there was significant genetic heterogeneity that could impact both the selection of model cell lines and the interpretation of the results obtained. To capture the net activation of key signaling pathways as a result of these mutational combinations, profiled pathway activation status was examined. This provided further clarity for which cell lines were particularly deregulated in common or unique ways. CONCLUSIONS: These two new kinase or "Kin-OMIC" analyses add another dimension of important data about these frequently used breast cancer cell lines. This will assist researchers in selecting the most appropriate cell lines to use for breast cancer studies and provide context for the interpretation of the emerging results.

Epigenetic silencing of CREB3L1 by DNA methylation is associated with high-grade metastatic breast cancers with poor prognosis and is prevalent in triple negative breast cancers.

BACKGROUND: CREB3L1 (cAMP-responsive element-binding protein 3-like protein 1), a member of the unfolded protein response, has recently been identified as a metastasis suppressor in both breast and bladder cancer. METHODS: Quantitative real time PCR (qPCR) and immunoblotting were used to determine the impact of histone deacetylation and DNA methylation inhibitors on CREB3L1 expression in breast cancer cell lines. Breast cancer cell lines and tumor samples were analyzed similarly, and CREB3L1 gene methylation was determined using sodium bisulfite conversion and DNA sequencing. Immunohistochemistry was used to determine nuclear versus cytoplasmic CREB3L1 protein. Large breast cancer database analyses were carried out to examine relationships between CREB3L1 gene methylation and mRNA expression in addition to CREB3L1 mRNA expression and prognosis. RESULTS: This study demonstrates that the low CREB3L1 expression previously seen in highly metastatic breast cancer cell lines is caused in part by epigenetic silencing. Treatment of several highly metastatic breast cancer cell lines that had low CREB3L1 expression with DNA methyltransferase and histone deacetylase inhibitors induced expression of CREB3L1, both mRNA and protein. In human breast tumors, CREB3L1 mRNA expression was upregulated in low and medium-grade tumors, most frequently of the luminal and HER2 amplified subtypes. In contrast, CREB3L1 expression was repressed in high-grade tumors, and its loss was most frequently associated with triple negative breast cancers (TNBCs). Importantly, bioinformatics analyses of tumor databases support these findings, with methylation of the CREB3L1 gene associated with TNBCs, and strongly negatively correlated with CREB3L1 mRNA expression. Decreased CREB3L1 mRNA expression was associated with increased tumor grade and reduced progression-free survival. An immunohistochemistry analysis revealed that low-grade breast tumors frequently had nuclear CREB3L1 protein, in contrast to the high-grade breast tumors in which CREB3L1 was cytoplasmic, suggesting that differential localization may also regulate CREB3L1 effectiveness in metastasis suppression. CONCLUSIONS: Our data further strengthens the role for CREB3L1 as a metastasis suppressor in breast cancer and demonstrates that epigenetic silencing is a major regulator of the loss of CREB3L1 expression. We also highlight that CREB3L1 expression is frequently altered in many cancer types suggesting that it could have a broader role in cancer progression and metastasis.

A negative genetic interaction map in isogenic cancer cell lines reveals cancer cell vulnerabilities.

Improved efforts are necessary to define the functional product of cancer mutations currently being revealed through large-scale sequencing efforts. Using genome-scale pooled shRNA screening technology, we mapped negative genetic interactions across a set of isogenic cancer cell lines and confirmed hundreds of these interactions in orthogonal co-culture competition assays to generate a high-confidence genetic interaction network of differentially essential or differential essentiality (DiE) genes. The network uncovered examples of conserved genetic interactions, densely connected functional modules derived from comparative genomics with model systems data, functions for uncharacterized genes in the human genome and targetable vulnerabilities. Finally, we demonstrate a general applicability of DiE gene signatures in determining genetic dependencies of other non-isogenic cancer cell lines. For example, the PTEN(-/-) DiE genes reveal a signature that can preferentially classify PTEN-dependent genotypes across a series of non-isogenic cell lines derived from the breast, pancreas and ovarian cancers. Our reference network suggests that many cancer vulnerabilities remain to be discovered through systematic derivation of a network of differentially essential genes in an isogenic cancer cell model.

PhenoM: a database of morphological phenotypes caused by mutation of essential genes in Saccharomyces cerevisiae.

About one-fifth of the genes in the budding yeast are essential for haploid viability and cannot be functionally assessed using standard genetic approaches such as gene deletion. To facilitate genetic analysis of essential genes, we and others have assembled collections of yeast strains expressing temperature-sensitive (ts) alleles of essential genes. To explore the phenotypes caused by essential gene mutation we used a panel of genetically engineered fluorescent markers to explore the morphology of cells in the ts strain collection using high-throughput microscopy. Here, we describe the design and implementation of an online database, PhenoM (Phenomics of yeast Mutants), for storing, retrieving, visualizing and data mining the quantitative single-cell measurements extracted from micrographs of the ts mutant cells. PhenoM allows users to rapidly search and retrieve raw images and their quantified morphological data for genes of interest. The database also provides several data-mining tools, including a PhenoBlast module for phenotypic comparison between mutant strains and a Gene Ontology module for functional enrichment analysis of gene sets showing similar morphological alterations. The current PhenoM version 1.0 contains 78,194 morphological images and 1,909,914 cells covering six subcellular compartments or structures for 775 ts alleles spanning 491 essential genes. PhenoM is freely available at http://phenom.ccbr.utoronto.ca/.

Systematic Comparison of CRISPR and shRNA Screens to Identify Essential Genes Using a Graph-Based Unsupervised Learning Model.

Generally, essential genes identified using shRNA and CRISPR are not always the same, raising questions about the choice between these two screening platforms. To address this, we systematically compared the performance of CRISPR and shRNA to identify essential genes across different gene expression levels in 254 cell lines. As both platforms have a notable false positive rate, to correct this confounding factor, we first developed a graph-based unsupervised machine learning model to predict common essential genes. Furthermore, to maintain the unique characteristics of individual cell lines, we intersect essential genes derived from the biological experiment with the predicted common essential genes. Finally, we employed statistical methods to compare the ability of these two screening platforms to identify essential genes that exhibit differential expression across various cell lines. Our analysis yielded several noteworthy findings: (1) shRNA outperforms CRISPR in the identification of lowly expressed essential genes; (2) both screening methodologies demonstrate strong performance in identifying highly expressed essential genes but with limited overlap, so we suggest using a combination of these two platforms for highly expressed essential genes; (3) notably, we did not observe a single gene that becomes universally essential across all cancer cell lines.

hnRNP A1 dysfunction alters RNA splicing and drives neurodegeneration in multiple sclerosis (MS).

Neurodegeneration is the primary driver of disease progression in multiple sclerosis (MS) resulting in permanent disability, creating an urgent need to discover its underlying mechanisms. Herein, we establish that dysfunction of the RNA binding protein heterogeneous nuclear ribonucleoprotein A1 (hnRNP A1) results in differential of binding to RNA targets causing alternative RNA splicing, which contributes to neurodegeneration in MS and its models. Using RNAseq of MS brains, we discovered differential expression and aberrant splicing of hnRNP A1 target RNAs involved in neuronal function and RNA homeostasis. We confirmed this in vivo in experimental autoimmune encephalomyelitis employing CLIPseq specific for hnRNP A1, where hnRNP A1 differentially binds and regulates RNA, including aberrantly spliced targets identified in human samples. Additionally, dysfunctional hnRNP A1 expression in neurons caused neurite loss and identical changes in splicing, corroborating hnRNP A1 dysfunction as a cause of neurodegeneration. Collectively, these data indicate hnRNP A1 dysfunction causes altered neuronal RNA splicing, resulting in neurodegeneration in MS.

MEMO1 binds iron and modulates iron homeostasis in cancer cells.

Mediator of ERBB2-driven cell motility 1 (MEMO1) is an evolutionary conserved protein implicated in many biological processes; however, its primary molecular function remains unknown. Importantly, MEMO1 is overexpressed in many types of cancer and was shown to modulate breast cancer metastasis through altered cell motility. To better understand the function of MEMO1 in cancer cells, we analyzed genetic interactions of MEMO1 using gene essentiality data from 1028 cancer cell lines and found multiple iron-related genes exhibiting genetic relationships with MEMO1. We experimentally confirmed several interactions between MEMO1 and iron-related proteins in living cells, most notably, transferrin receptor 2 (TFR2), mitoferrin-2 (SLC25A28), and the global iron response regulator IRP1 (ACO1). These interactions indicate that cells with high-MEMO1 expression levels are hypersensitive to the disruptions in iron distribution. Our data also indicate that MEMO1 is involved in ferroptosis and is linked to iron supply to mitochondria. We have found that purified MEMO1 binds iron with high affinity under redox conditions mimicking intracellular environment and solved MEMO1 structures in complex with iron and copper. Our work reveals that the iron coordination mode in MEMO1 is very similar to that of iron-containing extradiol dioxygenases, which also display a similar structural fold. We conclude that MEMO1 is an iron-binding protein that modulates iron homeostasis in cancer cells.

A CRISPR Platform for Targeted In Vivo Screens.

Large-scale genetic screens are becoming increasingly used as powerful tools to query the genome to identify therapeutic targets in cancer. The advent of the CRISPR technology has revolutionized the effectiveness of these screens and has made it possible to carry out loss-of-function screens to identify cancer-specific genetic interactions. Such loss-of-function screens can be performed in silico, in vitro, and in vivo, depending on the scale of the screen, as well as research questions to be answered. Performing screens in vivo has its challenges but also advantages, providing opportunities to study the tumor microenvironment and cancer immunity. In this chapter, we present a procedural framework and associated notes for conducting in vivo CRISPR knockout screens in cancer models to study cancer biology, anti-tumor immune responses, tumor microenvironment, and predicting treatment responses.

Integration of cancer-related genetic landscape of Eph receptors and ephrins with proteomics identifies a crosstalk between EPHB6 and EGFR.

Eph receptors and their ephrin ligands are viewed as promising targets for cancer treatment; however, targeting them is hindered by their context-dependent functionalities. To circumvent this, we explore molecular landscapes underlying their pro- and anti-malignant activities. Using unbiased bioinformatics approaches, we construct a cancer-related network of genetic interactions (GIs) of all Ephs and ephrins to assist in their therapeutic manipulation. We also apply genetic screening and BioID proteomics and integrate them with machine learning approaches to select the most relevant GIs of one Eph receptor, EPHB6. This identifies a crosstalk between EPHB6 and EGFR, and further experiments confirm the ability of EPHB6 to modulate EGFR signaling, enhancing the proliferation of cancer cells and tumor development. Taken together, our observations show EPHB6 involvement in EGFR action, suggesting its targeting might be beneficial in EGFR-dependent tumors, and confirm that the Eph family genetic interactome presented here can be effectively exploited in developing cancer treatment approaches.

A Multipronged Unbiased Strategy Guides the Development of an Anti-EGFR/EPHA2-Bispecific Antibody for Combination Cancer Therapy.

PURPOSE: Accumulating analyses of pro-oncogenic molecular mechanisms triggered a rapid development of targeted cancer therapies. Although many of these treatments produce impressive initial responses, eventual resistance onset is practically unavoidable. One of the main approaches for preventing this refractory condition relies on the implementation of combination therapies. This includes dual-specificity reagents that affect both of their targets with a high level of selectivity. Unfortunately, selection of target combinations for these treatments is often confounded by limitations in our understanding of tumor biology. Here, we describe and validate a multipronged unbiased strategy for predicting optimal co-targets for bispecific therapeutics. EXPERIMENTAL DESIGN: Our strategy integrates ex vivo genome-wide loss-of-function screening, BioID interactome profiling, and gene expression analysis of patient data to identify the best fit co-targets. Final validation of selected target combinations is done in tumorsphere cultures and xenograft models. RESULTS: Integration of our experimental approaches unambiguously pointed toward EGFR and EPHA2 tyrosine kinase receptors as molecules of choice for co-targeting in multiple tumor types. Following this lead, we generated a human bispecific anti-EGFR/EPHA2 antibody that, as predicted, very effectively suppresses tumor growth compared with its prototype anti-EGFR therapeutic antibody, cetuximab. CONCLUSIONS: Our work not only presents a new bispecific antibody with a high potential for being developed into clinically relevant biologics, but more importantly, successfully validates a novel unbiased strategy for selecting biologically optimal target combinations. This is of a significant translational relevance, as such multifaceted unbiased approaches are likely to augment the development of effective combination therapies for cancer treatment. See related commentary by Kumar, p. 2570.

Homoharringtonine demonstrates a cytotoxic effect against triple-negative breast cancer cell lines and acts synergistically with paclitaxel.

The lack of targeted therapies for triple-negative breast cancer (TNBC) contributes to their high mortality rates and high risk of relapse compared to other subtypes of breast cancer. Most TNBCs (75%) have downregulated the expression of CREB3L1 (cAMP-responsive element binding protein 3 like 1), a transcription factor and metastasis suppressor that represses genes that promote cancer progression and metastasis. In this report, we screened an FDA-approved drug library and identified four drugs that were highly cytotoxic towards HCC1806 CREB3L1-deficient TNBC cells. These four drugs were: (1) palbociclib isethionate, a CDK4/6 inhibitor, (2) lanatocide C (also named isolanid), a Na+/K+-ATPase inhibitor, (3) cladribine, a nucleoside analog, and (4) homoharringtonine (also named omacetaxine mepesuccinate), a protein translation inhibitor. Homoharringtonine consistently showed the most cytotoxicity towards an additional six TNBC cell lines (BT549, HCC1395, HCC38, Hs578T, MDA-MB-157, MDA-MB-436), and several luminal A breast cancer cell lines (HCC1428, MCF7, T47D, ZR-75-1). All four drugs were then separately evaluated for possible synergy with the chemotherapy agents, doxorubicin (an anthracycline) and paclitaxel (a microtubule stabilizing agent). A strong synergy was observed using the combination of homoharringtonine and paclitaxel, with high cytotoxicity towards TNBC cells at lower concentrations than when each was used separately.

Synthetic lethal interactions of DEAD/H-box helicases as targets for cancer therapy.

DEAD/H-box helicases are implicated in virtually every aspect of RNA metabolism, including transcription, pre-mRNA splicing, ribosomes biogenesis, nuclear export, translation initiation, RNA degradation, and mRNA editing. Most of these helicases are upregulated in various cancers and mutations in some of them are associated with several malignancies. Lately, synthetic lethality (SL) and synthetic dosage lethality (SDL) approaches, where genetic interactions of cancer-related genes are exploited as therapeutic targets, are emerging as a leading area of cancer research. Several DEAD/H-box helicases, including DDX3, DDX9 (Dbp9), DDX10 (Dbp4), DDX11 (ChlR1), and DDX41 (Sacy-1), have been subjected to SL analyses in humans and different model organisms. It remains to be explored whether SDL can be utilized to identity druggable targets in DEAD/H-box helicase overexpressing cancers. In this review, we analyze gene expression data of a subset of DEAD/H-box helicases in multiple cancer types and discuss how their SL/SDL interactions can be used for therapeutic purposes. We also summarize the latest developments in clinical applications, apart from discussing some of the challenges in drug discovery in the context of targeting DEAD/H-box helicases.