A Synthetic Lethality Screen Using a Focused siRNA Library to Identify Sensitizers to Dasatinib Therapy for the Treatment of Epithelial Ovarian Cancer

Casein Kinase 2 Inhibitor, CX-4945, Induces Apoptosis and Restores Blood-Brain Barrier Homeostasis in In Vitro and In Vivo Models of Glioblastoma

Background: In oncology, casein kinase 2 (CK2), a serine/threonine kinase, has a dual action, regulating cellular processes and acting as an oncogenic promoter. Methods: This study examined the effect of CX-4945, a selective CK2 inhibitor, in a human U-87 glioblastoma (GBM) cell line, treated with CX-4945 (5, 10, and 15 μM) for 24 h. Similarly, the hCMEC/D3 cell line was used to mimic the blood-brain barrier (BBB), examining the ability of CX-4945 to restore BBB homeostasis, after stimulation with lipopolysaccharide (LPS) and then treated with CX-4945 (5, 10, and 15 μM). Results: We reported that CX-4945 reduced the proliferative activity and modulated the main pathways involved in tumor progression including apoptosis. Furthermore, in confirmation of the in vitro study, performing a xenograft model, we demonstrated that CX-4945 exerted promising antiproliferative effects, also restoring the tight junctions' expression. Conclusions: These new insights into the molecular signaling of CK2 in GBM and BBB demonstrate that CX-4945 could be a promising approach for future GBM therapy, not only in the tumor microenvironment but also at the BBB level.

SLKB: synthetic lethality knowledge base

Emerging CRISPR-Cas9 technology permits synthetic lethality (SL) screening of large number of gene pairs from gene combination double knockout (CDKO) experiments. However, the poor integration and annotation of CDKO SL data in current SL databases limit their utility, and diverse methods of calculating SL scores prohibit their comparison. To overcome these shortcomings, we have developed SL knowledge base (SLKB) that incorporates data of 11 CDKO experiments in 22 cell lines, 16,059 SL gene pairs and 264,424 non-SL gene pairs. Additionally, within SLKB, we have implemented five SL calculation methods: median score with and without background control normalization (Median-B/NB), sgRNA-derived score (sgRNA-B/NB), Horlbeck score, GEMINI score and MAGeCK score. The five scores have demonstrated a mere 1.21% overlap among their top 10% SL gene pairs, reflecting high diversity. Users can browse SL networks and assess the impact of scoring methods using Venn diagrams. The SL network generated from all data in SLKB shows a greater likelihood of SL gene pair connectivity with other SL gene pairs than non-SL pairs. Comparison of SL networks between two cell lines demonstrated greater likelihood to share SL hub genes than SL gene pairs. SLKB website and pipeline can be freely accessed at https://slkb.osubmi.org and https://slkb.docs.osubmi.org/, respectively.

Cdc2-like kinases: structure, biological function, and therapeutic targets for diseases

The CLKs (Cdc2-like kinases) belong to the dual-specificity protein kinase family and play crucial roles in regulating transcript splicing via the phosphorylation of SR proteins (SRSF1-12), catalyzing spliceosome molecular machinery, and modulating the activities or expression of non-splicing proteins. The dysregulation of these processes is linked with various diseases, including neurodegenerative diseases, Duchenne muscular dystrophy, inflammatory diseases, viral replication, and cancer. Thus, CLKs have been considered as potential therapeutic targets, and significant efforts have been exerted to discover potent CLKs inhibitors. In particular, clinical trials aiming to assess the activities of the small molecules Lorecivivint on knee Osteoarthritis patients, and Cirtuvivint and Silmitasertib in different advanced tumors have been investigated for therapeutic usage. In this review, we comprehensively documented the structure and biological functions of CLKs in various human diseases and summarized the significance of related inhibitors in therapeutics. Our discussion highlights the most recent CLKs research, paving the way for the clinical treatment of various human diseases.

Genome-wide siRNA screens identify RBBP9 function as a potential target in Fanconi anaemia-deficient head-and-neck squamous cell carcinoma

Fanconi anaemia (FA) is a rare chromosomal-instability syndrome caused by mutations of any of the 22 known FA DNA-repair genes. FA individuals have an increased risk of head-and-neck squamous-cell-carcinomas (HNSCC), often fatal. Systemic intolerance to standard cisplatin-based protocols due to somatic-cell hypersensitivity underscores the urgent need to develop novel therapies. Here, we performed unbiased siRNA screens to unveil genetic interactions synthetic-lethal with FA-pathway deficiency in FA-patient HNSCC cell lines. We identified based on differential-lethality scores between FA-deficient and FA-proficient cells, next to common-essential genes such as PSMC1, PSMB2, and LAMTOR2, the otherwise non-essential RBBP9 gene. Accordingly, low dose of the FDA-approved RBBP9-targeting drug Emetine kills FA-HNSCC. Importantly both RBBP9-silencing as well as Emetine spared non-tumour FA cells. This study provides a minable genome-wide analyses of vulnerabilities to address treatment challenges in FA-HNSCC. Our investigation divulges a DNA-cross-link-repair independent lead, RBBP9, for targeted treatment of FA-HNSCCs without systemic toxicity.

Fusogenic peptide delivery of bioactive siRNAs targeting CSNK2A1 for treatment of ovarian cancer

Ovarian cancer has shown little improvement in survival among advanced-stage patients over the past decade. Current treatment strategies have been largely unsuccessful in treating advanced disease, with many patients experiencing systemic toxicity and drug-resistant metastatic cancer. This study evaluates novel fusogenic peptide carriers delivering short interfering RNA (siRNA) targeting casein kinase II, CSNK2A1, for reducing the aggressiveness of ovarian cancer. The peptides were designed to address two significant barriers to siRNA delivery: insufficient cellular uptake and endosomal entrapment. The three peptide variants developed, DIVA3, DIV3H, and DIV3W, were able to form monodisperse nanoparticle complexes with siRNA and protect siRNAs from serum and RNase degradation. Furthermore, DIV3W demonstrated optimal delivery of bioactive siRNAs into ovarian cancer cells with high cellular uptake efficiency and mediated up to 94% knockdown of CSNK2A1 mRNA compared with non-targeting siRNAs, resulting in decreased cell migration and recolonization in vitro. Intratumoral delivery of DIV3W-siCSNK2A1 complexes to subcutaneous ovarian tumors resulted in reduced CSNK2A1 mRNA and CK2α protein expression after 48 h and reduced tumor growth and migration in a 2-week multi-dosing regimen. These results demonstrate the potential of the DIV3W peptide to deliver bioactive siRNAs and confirms the role of CSNK2A1 in cell-cell communication and proliferation in ovarian cancer.

Synthetic lethal gene pairs: Experimental approaches and predictive models

Synthetic lethality (SL) refers to a genetic interaction in which the simultaneous perturbation of two genes leads to cell or organism death, whereas viability is maintained when only one of the pair is altered. The experimental exploration of these pairs and predictive modeling in computational biology contribute to our understanding of cancer biology and the development of cancer therapies. We extensively reviewed experimental technologies, public data sources, and predictive models in the study of synthetic lethal gene pairs and herein detail biological assumptions, experimental data, statistical models, and computational schemes of various predictive models, speculate regarding their influence on individual sample- and population-based synthetic lethal interactions, discuss the pros and cons of existing SL data and models, and highlight potential research directions in SL discovery.

A fragment-based approach leading to the discovery of inhibitors of CK2α with a novel mechanism of action

Development of a novel CK2α inhibitor from a fragment-based screen with a proposed novel mechanism of action.

Targeting CK2 in cancer: a valuable strategy or a waste of time?

CK2 is a protein kinase involved in several human diseases (ranging from neurological and cardiovascular diseases to autoimmune disorders, diabetes, and infections, including COVID-19), but its best-known implications are in cancer, where it is considered a pharmacological target. Several CK2 inhibitors are available and clinical trials are underway in different cancer types. Recently, the suitability of CK2 as a broad anticancer target has been questioned by the finding that a newly developed compound, named SGC-CK2-1, which is more selective than any other known CK2 inhibitor, is poorly effective in reducing cell growth in different cancer lines, prompting the conclusion that the anticancer efficacy of CX-4945, the commonly used clinical-grade CK2 inhibitor, is to be attributed to its off-target effects. Here we perform a detailed scrutiny of published studies on CK2 targeting and a more in-depth analysis of the available data on SGC-CK2-1 vs. CX-4945 efficacy, providing a different perspective about the actual reliance of cancer cells on CK2. Collectively taken, our arguments would indicate that the pretended dispensability of CK2 in cancer is far from having been proved and warn against premature conclusions, which could discourage ongoing investigations on a potentially valuable drug target.

Overcoming resistance to BRAFV600E inhibition in melanoma by deciphering and targeting personalized protein network alterations

BRAFV600E melanoma patients, despite initially responding to the clinically prescribed anti-BRAFV600E therapy, often relapse, and their tumors develop drug resistance. While it is widely accepted that these tumors are originally driven by the BRAFV600E mutation, they often eventually diverge and become supported by various signaling networks. Therefore, patient-specific altered signaling signatures should be deciphered and treated individually. In this study, we design individualized melanoma combination treatments based on personalized network alterations. Using an information-theoretic approach, we compute high-resolution patient-specific altered signaling signatures. These altered signaling signatures each consist of several co-expressed subnetworks, which should all be targeted to optimally inhibit the entire altered signaling flux. Based on these data, we design smart, personalized drug combinations, often consisting of FDA-approved drugs. We validate our approach in vitro and in vivo showing that individualized drug combinations that are rationally based on patient-specific altered signaling signatures are more efficient than the clinically used anti-BRAFV600E or BRAFV600E/MEK targeted therapy. Furthermore, these drug combinations are highly selective, as a drug combination efficient for one BRAFV600E tumor is significantly less efficient for another, and vice versa. The approach presented herein can be broadly applicable to aid clinicians to rationally design patient-specific anti-melanoma drug combinations.

Role of CK2 inhibitor CX-4945 in anti-cancer combination therapy - potential clinical relevance

BACKGROUND

Protein kinase CK2 inhibition has long been considered as an attractive anti-cancer strategy based on the following considerations: CK2 is a pro-survival kinase, it is frequently over-expressed in human tumours and its over-expression correlates with a worse prognosis. Preclinical evidence strongly supports the feasibility of this target and, although dozens of CK2 inhibitors have been described in the literature so far, CX-4945 (silmitasertib) was the first that entered into clinical trials for the treatment of both human haematological and solid tumours. However, kinase inhibitor monotherapies turned out to be effective only in a limited number of malignancies, probably due to the multifaceted causes that underlie them, supporting the emerging view that multi-targeted approaches to treat human tumours could be more effective.

CONCLUSIONS

In this review, we will address combined anti-cancer therapeutic strategies described so far which involve the use of CX-4945. Data from preclinical studies clearly show the ability of CX-4945 to synergistically cooperate with different classes of anti-neoplastic agents, thereby contributing to an orchestrated anti-tumour action against multiple targets. Overall, these promising outcomes support the translation of CX-4945 combined therapies into clinical anti-cancer applications.

Lassa-VSV chimeric virus targets and destroys human and mouse ovarian cancer by direct oncolytic action and by initiating an anti-tumor response

Ovarian cancer is the third most common female cancer, with poor survival in later stages of metastatic spread. We test a chimeric virus consisting of genes from Lassa and vesicular stomatitis viruses, LASV-VSV; the native VSV glycoprotein is replaced by the Lassa glycoprotein, greatly reducing neurotropism. Human ovarian cancer cells in immunocompromised nude mice were lethal in controls. Chemotherapeutic paclitaxel and cisplatin showed modest cancer inhibition and survival extension. In contrast, a single intraperitoneal injection of LASV-VSV selectively infected and killed ovarian cancer cells, generating long-term survival. Mice with human ovarian cancer cells in brain showed rapid deterioration; LASV-VSV microinjection into brain blocked cancer growth, and generated long-term survival. Treatment of immunocompetent mice with infected mouse ovarian cancer cells blocked growth of non-infected ovarian cancer cells peritoneally and in brain. These results suggest LASV-VSV is a viable candidate for further study and may be of use in the treatment of ovarian cancer.

The HMGB1-2 Ovarian Cancer Interactome. The Role of HMGB Proteins and Their Interacting Partners MIEN1 and NOP53 in Ovary Cancer and Drug-Response

High mobility group box B (HMGB) proteins are overexpressed in different types of cancers such as epithelial ovarian cancers (EOC). We have determined the first interactome of HMGB1 and HMGB2 in epithelial ovarian cancer (the EOC-HMGB interactome). Libraries from the SKOV-3 cell line and a primary transitional cell carcinoma (TCC) ovarian tumor were tested by the Yeast Two Hybrid (Y2H) approach. The interactome reveals proteins that are related to cancer hallmarks and their expression is altered in EOC. Moreover, some of these proteins have been associated to survival and prognosis of patients. The interaction of MIEN1 and NOP53 with HMGB2 has been validated by co-immunoprecipitation in SKOV-3 and PEO1 cell lines. SKOV-3 cells were treated with different anti-tumoral drugs to evaluate changes in HMGB1, HMGB2, MIEN1 and NOP53 gene expression. Results show that combined treatment of paclitaxel and carboplatin induces a stronger down-regulation of these genes in comparison to individual treatments. Individual treatment with paclitaxel or olaparib up-regulates NOP53, which is expressed at lower levels in EOC than in non-cancerous cells. On the other hand, bevacizumab diminishes the expression of HMGB2 and NOP53. This study also shows that silencing of these genes affects cell-viability after drug exposure. HMGB1 silencing causes loss of response to paclitaxel, whereas silencing of HMGB2 slightly increases sensitivity to olaparib. Silencing of either HMGB1 or HMGB2 increases sensitivity to carboplatin. Lastly, a moderate loss of response to bevacizumab is observed when NOP53 is silenced.

QuaDMutNetEx: a method for detecting cancer driver genes with low mutation frequency

BACKGROUND

Cancer is caused by genetic mutations, but not all somatic mutations in human DNA drive the emergence or growth of cancers. While many frequently-mutated cancer driver genes have already been identified and are being utilized for diagnostic, prognostic, or therapeutic purposes, identifying driver genes that harbor mutations occurring with low frequency in human cancers is an ongoing endeavor. Typically, mutations that do not confer growth advantage to tumors - passenger mutations - dominate the mutation landscape of tumor cell genome, making identification of low-frequency driver mutations a challenge. The leading approach for discovering new putative driver genes involves analyzing patterns of mutations in large cohorts of patients and using statistical methods to discriminate driver from passenger mutations.

RESULTS

We propose a novel cancer driver gene detection method, QuaDMutNetEx. QuaDMutNetEx discovers cancer drivers with low mutation frequency by giving preference to genes encoding proteins that are connected in human protein-protein interaction networks, and that at the same time show low deviation from the mutual exclusivity pattern that characterizes driver mutations occurring in the same pathway or functional gene group across a cohort of cancer samples.

CONCLUSIONS

Evaluation of QuaDMutNetEx on four different tumor sample datasets show that the proposed method finds biologically-connected sets of low-frequency driver genes, including many genes that are not found if the network connectivity information is not considered. Improved quality and interpretability of the discovered putative driver gene sets compared to existing methods shows that QuaDMutNetEx is a valuable new tool for detecting driver genes. QuaDMutNetEx is available for download from https://github.com/bokhariy/QuaDMutNetExunder the GNU GPLv3 license.

An Ensemble Strategy to Predict Prognosis in Ovarian Cancer Based on Gene Modules

Due to the high heterogeneity and complexity of cancer, it is still a challenge to predict the prognosis of cancer patients. In this work, we used a clustering algorithm to divide patients into different subtypes in order to reduce the heterogeneity of the cancer patients in each subtype. Based on the hypothesis that the gene co-expression network may reveal relationships among genes, some communities in the network could influence the prognosis of cancer patients and all the prognosis-related communities could fully reveal the prognosis of cancer patients. To predict the prognosis for cancer patients in each subtype, we adopted an ensemble classifier based on the gene co-expression network of the corresponding subtype. Using the gene expression data of ovarian cancer patients in TCGA (The Cancer Genome Atlas), three subtypes were identified. Survival analysis showed that patients in different subtypes had different survival risks. Three ensemble classifiers were constructed for each subtype. Leave-one-out and independent validation showed that our method outperformed control and literature methods. Furthermore, the function annotation of the communities in each subtype showed that some communities were cancer-related. Finally, we found that the current drug targets can partially support our method.

Protein Kinase CK2, a Potential Therapeutic Target in Carcinoma Management

The Protein kinase CK2 (formerly known as casein kinase 2) is a highly conserved serine/ threonine kinase overexpressed in various human carcinomas and its high expression often correlates with poor prognosis. CK2 protein is localized in the nucleus of many tumor cells and correlates with clinical features in many cases. Increased expression of CK2 in mice results in the development of various types of carcinomas (both solids and blood related tumors, such as (breast carcinoma, lymphoma, etc), which reveals its carcinogenic properties. CK2 plays essential roles in many key biological processes related to carcinoma, including cell apoptosis, DNA damage responses and cell cycle regulation. CK2 has become a potential anti-carcinoma target. Various CK2 inhibitors have been developed with anti-neoplastic properties against a variety of carcinomas. Some CK2 inhibitors have showed good results in in vitro and pre-clinical models, and have even entered in clinical trials. This article will review effects of CK2 and its inhibitors on common carcinomas in in vitro and pre-clinical studies.

Harnessing synthetic lethality to predict the response to cancer treatment

While synthetic lethality (SL) holds promise in developing effective cancer therapies, SL candidates found via experimental screens often have limited translational value. Here we present a data-driven approach, ISLE (identification of clinically relevant synthetic lethality), that mines TCGA cohort to identify the most likely clinically relevant SL interactions (cSLi) from a given candidate set of lab-screened SLi. We first validate ISLE via a benchmark of large-scale drug response screens and by predicting drug efficacy in mouse xenograft models. We then experimentally test a select set of predicted cSLi via new screening experiments, validating their predicted context-specific sensitivity in hypoxic vs normoxic conditions and demonstrating cSLi's utility in predicting synergistic drug combinations. We show that cSLi can successfully predict patients' drug treatment response and provide patient stratification signatures. ISLE thus complements existing actionable mutation-based methods for precision cancer therapy, offering an opportunity to expand its scope to the whole genome.

Conceptual frameworks of synthetic lethality in clear cell carcinoma of the ovary

Targeting non-oncogenes may result in the selective death of cancer cells. Clear cell carcinoma of the ovary (CCC) may exhibit resistance against conventional chemotherapy and is associated with poor prognosis. The aim of the present report was to review synthetic lethality-based therapies for CCC. Previous English-language studies were reviewed to accumulate preclinical and clinical data on targeting synthetic lethal partners. Synthetic lethal interactions have a variety of types, involving components of a backup or parallel pathway with overlapping functions, components encoded by paralogous pairs, subunit components that form heteromeric complexes and components that are arranged in a single linear pathway. A set of candidate gene targets potentially resulting in synthetic lethality have been previously identified. HNF class homeobox, AT-rich interaction domain 1A, ATR serine/threonine kinase, ATM serine/threonine kinase, checkpoint kinase 1 and phosphatase and tensin homolog may be the key partner genes. A variety of loss of function genes in CCC are driver or passenger events and may function as synthetic lethal pairs under replication stress conditions. Further clinical studies will be required to investigate the safety and therapeutic effect of synthetic lethality pairs in CCC tumor types with replication stress.

Licofelone Enhances the Efficacy of Paclitaxel in Ovarian Cancer by Reversing Drug Resistance and Tumor Stem-like Properties

Drug development for first-line treatment of epithelial ovarian cancer (EOC) has been stagnant for almost three decades. Traditional cell culture methods for primary drug screening do not always accurately reflect clinical disease. To overcome this barrier, we grew a panel of EOC cell lines in three-dimensional (3D) cell cultures to form multicellular tumor spheroids (MCTS). We characterized these MCTS for molecular and cellular features of EOC and performed a comparative screen with cells grown using two-dimensional (2D) cell culture to identify previously unappreciated anticancer drugs. MCTS exhibited greater resistance to chemotherapeutic agents, showed signs of senescence and hypoxia, and expressed a number of stem cell-associated transcripts including ALDH1A and CD133, also known as PROM1 Using a library of clinically repurposed drugs, we identified candidates with preferential activity in MCTS over 2D cultured cells. One of the lead compounds, the dual COX/LOX inhibitor licofelone, reversed the stem-like properties of ovarian MCTS. Licofelone also synergized with paclitaxel in ovarian MCTS models and in a patient-derived tumor xenograft model. Importantly, the combination of licofelone with paclitaxel prolonged the median survival of mice (>141 days) relative to paclitaxel (115 days), licofelone (37 days), or vehicle (30 days). Increased efficacy was confirmed by Mantel-Haenszel HR compared with vehicle (HR = 0.037) and paclitaxel (HR = 0.017). These results identify for the first time an unappreciated, anti-inflammatory drug that can reverse chemotherapeutic resistance in ovarian cancer, highlighting the need to clinically evaluate licofelone in combination with first-line chemotherapy in primary and chemotherapy-refractory EOC.Significance: This study highlights the use of an in vitro spheroid 3D drug screening model to identify new therapeutic approaches to reverse chemotherapy resistance in ovarian cancer. Cancer Res; 78(15); 4370-85. ©2018 AACR.

Developing a genetic signature to predict drug response in ovarian cancer

There is a lack of personalized treatment options for women with recurrent platinum-resistant ovarian cancer. Outside of bevacizumab and a group of poly ADP-ribose polymerase inhibitors, few options are available to women that relapse. We propose that efficacious drug combinations can be determined via molecular characterization of ovarian tumors along with pre-established pharmacogenomic profiles of repurposed compounds. To that end, we selectively performed multiple two-drug combination treatments in ovarian cancer cell lines that included reactive oxygen species inducers and HSP90 inhibitors. This allowed us to select cell lines that exhibit disparate phenotypes of proliferative inhibition to a specific drug combination of auranofin and AUY922. We profiled altered mechanistic responses from these agents in both reactive oxygen species and HSP90 pathways, as well as investigated PRKCI and lncRNA expression in ovarian cancer cell line models. Generation of dual multi-gene panels implicated in resistance or sensitivity to this drug combination was produced using RNA sequencing data and the validity of the resistant signature was examined using high-density RT-qPCR. Finally, data mining for the prevalence of these signatures in a large-scale clinical study alluded to the prevalence of resistant genes in ovarian tumor biology. Our results demonstrate that high-throughput viability screens paired with reliable in silico data can promote the discovery of effective, personalized therapeutic options for a currently untreatable disease.

Aurora A kinase regulates non-homologous end-joining and poly(ADP-ribose) polymerase function in ovarian carcinoma cells

Ovarian cancer is usually diagnosed at late stages when cancer has spread beyond the ovary and patients ultimately succumb to the development of drug-resistant disease. There is an urgent and unmet need to develop therapeutic strategies that effectively treat ovarian cancer and this requires a better understanding of signaling pathways important for ovarian cancer progression. Aurora A kinase (AURKA) plays an important role in ovarian cancer progression by mediating mitosis and chromosomal instability. In the current study, we investigated the role of AURKA in regulating the DNA damage response and DNA repair in ovarian carcinoma cells. We discovered that AURKA modulated the expression and activity of PARP, a crucial mediator of DNA repair that is a target of therapeutic interest for the treatment of ovarian and other cancers. Further, specific inhibition of AURKA activity with the small molecule inhibitor, alisertib, stimulated the non-homologous end-joining (NHEJ) repair pathway by elevating DNA-PKcs activity, a catalytic subunit required for double-strand break (DSB) repair, as well as decreased the expression of PARP and BRCA1/2, which are required for high-fidelity homologous recombination-based DNA repair. Further, AURKA inhibition stimulates error-prone NHEJ repair of DNA double-strand breaks with incompatible ends. Consistent with in vitro findings, alisertib treatment increased phosphorylated DNA-PKcs(pDNA-PKcsT2609) and decreased PARP levels in vivo. Collectively, these results reveal new non-mitotic functions for AURKA in the regulation of DNA repair, which may inform of new therapeutic targets and strategies for treating ovarian cancer.

CK2 in Cancer: Cellular and Biochemical Mechanisms and Potential Therapeutic Target

CK2 genes are overexpressed in many human cancers, and most often overexpression is associated with worse prognosis. Site-specific expression in mice leads to cancer development (e.g., breast, lymphoma) indicating the oncogenic nature of CK2. CK2 is involved in many key aspects of cancer including inhibition of apoptosis, modulation of signaling pathways, DNA damage response, and cell cycle regulation. A number of CK2 inhibitors are now available and have been shown to have activity against various cancers in vitro and in pre-clinical models. Some of these inhibitors are now undergoing exploration in clinical trials as well. In this review, we will examine some of the major cancers in which CK2 inhibition has promise based on in vitro and pre-clinical studies, the proposed cellular and signaling mechanisms of anti-cancer activity by CK2 inhibitors, and the current or recent clinical trials using CK2 inhibitors.

Increased expression of protein kinase CK2α correlates with poor patient prognosis in epithelial ovarian cancer

Epithelial ovarian cancer (EOC) is one of the deadly gynecological malignancies. The function of protein kinase CK2α (CK2α) in EOC is still unknown. Our study aimed to investigate the relationship between the protein expression of CK2α and the tumor progression, the prognosis of human EOC. In this study, we analyzed the expression levels of CK2α through Western blot, using EOC cell lines like A2780, HO8910, COV644, OVCAR3, SKOV3, and the primary normal ovarian surface epithelial (NOSE) cells. Furthermore, OVCAR3 and SKOV3 EOC cells were employed as a cellular model to study the role of CK2α on cell growth, migration, invasion, apoptosis, and cell cycle distribution. In addition, we investigated CK2α protein expression in tumor tissues from patients with EOC by immunohistochemistry and analyzed the association between CK2α expression and clinicopathologic parameters and prognosis of EOC patients. And we found that compared with NOSE cells, CK2α protein expression was increased in A2780, HO8910, OVCAR3, and SKOV3 ovarian cancer cell lines. Decreased CK2α expression suppressed OVCAR3 and SKOV3 cell growth and induced more apoptosis. CK2α knockdown using specific siRNAs inhibited migration and invasion ability of OVCAR3 and SKOV3 cells. In addition, high CK2α protein expression was found in 68.4% (80/117) of EOC patients. Increased CK2α expression of was significantly correlated with FIGO staging and peritoneal cytology. Patients with higher CK2α expression had a significantly poorer overall survival compared with those with lower CK2α expression. Multi-variate Cox regression analysis proved that increased CK2α expression was an independent prognostic marker for EOC. Taken together, our data displayed that CK2α may play a role in tumor aggressive behavior of EOC and could be used as a marker for predicting prognosis of EOC patient. High CK2α expression might predict poor patient survival.

Specific inhibition of CK2α from an anchor outside the active site

The development of selective inhibitors of protein kinases is challenging because of the significant conservation of the ATP binding site. Here, we describe a new mechanism by which the protein kinase CK2α can be selectively inhibited using features outside the ATP site. We have identified a new binding site for small molecules on CK2α adjacent to the ATP site and behind the αD loop, termed the αD pocket. An elaborated fragment anchored in this site has been linked with a low affinity fragment binding in the ATP site, creating a novel and selective inhibitor (CAM4066) that binds CK2α with a Kd of 320 nM and shows significantly improved selectivity compared to other CK2α inhibitors. CAM4066 shows target engagement in several cell lines and similar potency to clinical trial candidate CX4945. Our data demonstrate that targeting a poorly conserved, cryptic pocket allows inhibition of CK2α via a novel mechanism, enabling the development of a new generation of selective CK2α inhibitors.

Combination of Imatinib Mesylate and AKT Inhibitor Provides Synergistic Effects in Preclinical Study of Gastrointestinal Stromal Tumor

PURPOSE

Gastrointestinal stromal tumors (GIST) generally harbor activating mutations in the receptor tyrosine kinase KIT or in the related platelet-derived growth factor receptor alpha (PDGFRA). GIST treated with imatinib mesylate or second-line therapies that target mutant forms of these receptors generally escape disease control and progress over time. Inhibiting additional molecular targets may provide more substantial disease control. Recent studies have implicated the PI3K/AKT pathway in the survival of imatinib mesylate-resistant GIST cell lines and tumors.

EXPERIMENTAL DESIGN

Here, we performed in vitro and in vivo studies evaluating the novel combination of imatinib mesylate with the AKT inhibitor MK-2206 in GIST. Whole-transcriptome sequencing (WTS) of xenografts was performed to explore the molecular aspects of tumor response to this novel combination and to potentially identify additional therapeutic targets in GIST.

RESULTS

This drug combination demonstrated significant synergistic effects in a panel of imatinib mesylate-sensitive and -resistant GIST cell lines. Furthermore, combination therapy provided significantly greater efficacy, as measured by tumor response and animal survival, in imatinib mesylate-sensitive GIST xenografts as compared with treatment with imatinib mesylate or MK-2206 alone. WTS implicated two neural genes, brain expressed X-linked 1 and neuronal pentraxin I, whose expression was significantly upregulated in combination-treated tumors compared with tumors treated with the two monotherapies.

CONCLUSIONS

These studies provide strong preclinical justification for combining imatinib mesylate with an AKT inhibitor as a front-line therapy in GIST. In addition, the WTS implicated the BCL-2/BAX/BAD apoptotic pathway as a potential mechanism for this enhanced combination effect. Clin Cancer Res; 23(1); 171-80. ©2016 AACR.