Synthetic Lethality Interaction Between Aurora Kinases and CHEK1 Inhibitors in Ovarian Cancer

Aurora Kinase A inhibition enhances DNA damage and tumor cell death with 131I-MIBG therapy in high-risk neuroblastoma

BACKGROUND

Neuroblastoma is the most common extra-cranial pediatric solid tumor. 131I-metaiodobenzylguanidine (MIBG) is a targeted radiopharmaceutical highly specific for neuroblastoma tumors, providing potent radiotherapy to widely metastatic disease. Aurora kinase A (AURKA) plays a role in mitosis and stabilization of the MYCN protein in neuroblastoma. We aimed to study the impact of AURKA inhibitors on DNA damage and tumor cell death in combination with 131I-MIBG therapy in a pre-clinical model of high-risk neuroblastoma.

RESULTS

Using an in vivo model of high-risk neuroblastoma, we demonstrated a marked combinatorial effect of 131I-MIBG and alisertib on tumor growth. In MYCN amplified cell lines, the combination of radiation and an AURKA A inhibitor increased DNA damage and apoptosis and decreased MYCN protein levels.

CONCLUSION

The combination of AURKA inhibition with 131I-MIBG treatment is active in resistant neuroblastoma models.

Leveraging synthetic lethality to uncover potential therapeutic target in gastric cancer

Since trastuzumab was approved in 2012 for the first-line treatment of gastric cancer (GC), no significant advancement in GC targeted therapies has occurred. Synthetic lethality refers to the concept that simultaneous dysfunction of a pair of genes results in a lethal effect on cells, while the loss of an individual gene does not cause this effect. Through exploiting synthetic lethality, novel targeted therapies can be developed for the individualized treatment of GC. In this study, we proposed a computational strategy named Gastric cancer Specific Synthetic Lethality inference (GSSL) to identify synthetic lethal interactions in GC. GSSL analysis was used to infer probable synthetic lethality in GC using four accessible clinical datasets. In addition, prediction results were confirmed by experiments. GSSL analysis identified a total of 34 candidate synthetic lethal pairs, which included 33 unique targets. Among the synthetic lethal gene pairs, TP53-CHEK1 was selected for further experimental validation. Both computational and experimental results indicated that inhibiting CHEK1 could be a potential therapeutic strategy for GC patients with TP53 mutation. Meanwhile, in vitro experimental validation of two novel synthetic lethal pairs TP53-AURKB and ARID1A-EP300 further proved the universality and reliability of GSSL. Collectively, GSSL has been shown to be a reliable and feasible method for comprehensive analysis of inferring synthetic lethal interactions of GC, which may offer novel insight into the precision medicine and individualized treatment of GC.

Aurora Kinase A inhibition enhances DNA damage and tumor cell death with 131I-MIBG therapy in high-risk neuroblastoma

Background

Neuroblastoma is the most common extra-cranial pediatric solid tumor. 131I-metaiodobenzylguanidine (MIBG) is a targeted radiopharmaceutical highly specific for neuroblastoma tumors, providing potent radiotherapy to widely metastatic disease. Aurora kinase A (AURKA) plays a role in mitosis and stabilization of the MYCN protein in neuroblastoma. Here we explore whether AURKA inhibition potentiates a response to MIBG therapy.

Results

Using an in vivo model of high-risk neuroblastoma, we demonstrated a marked combinatorial effect of 131I-MIBG and alisertib on tumor growth. In MYCN amplified cell lines, the combination of radiation and an AURKA A inhibitor increased DNA damage and apoptosis and decreased MYCN protein levels.

Conclusion

The combination of AURKA inhibition with 131I-MIBG treatment is active in resistant neuroblastoma models and is a promising clinical approach in high-risk neuroblastoma.

Recent Updates on Oncogenic Signaling of Aurora Kinases in Chemosensitive, Chemoresistant Cancers: Novel Medicinal Chemistry Approaches for Targeting Aurora Kinases

The Aurora Kinase family (AKI) is composed of serine-threonine protein kinases involved in the modulation of the cell cycle and mitosis. These kinases are required for regulating the adherence of hereditary-related data. Members of this family can be categorized into aurora kinase A (Ark-A), aurora kinase B (Ark-B), and aurora kinase C (Ark-C), consisting of highly conserved threonine protein kinases. These kinases can modulate cell processes such as spindle assembly, checkpoint pathway, and cytokinesis during cell division. The main aim of this review is to explore recent updates on the oncogenic signaling of aurora kinases in chemosensitive/chemoresistant cancers and to explore the various medicinal chemistry approaches to target these kinases. We searched Pubmed, Scopus, NLM, Pubchem, and Relemed to obtain information pertinent to the updated signaling role of aurora kinases and medicinal chemistry approaches and discussed the recently updated roles of each aurora kinases and their downstream signaling cascades in the progression of several chemosensitive/chemoresistant cancers; subsequently, we discussed the natural products (scoulerine, Corynoline, Hesperidin Jadomycin-B, fisetin), and synthetic, medicinal chemistry molecules as aurora kinase inhibitors (AKIs). Several natural products' efficacy was explained as AKIs in chemosensitization and chemoresistant cancers. For instance, novel triazole molecules have been used against gastric cancer, whereas cyanopyridines are used against colorectal cancer and trifluoroacetate derivatives could be used for esophageal cancer. Furthermore, quinolone hydrazine derivatives can be used to target breast cancer and cervical cancer. In contrast, the indole derivatives can be preferred to target oral cancer whereas thiosemicarbazone-indole could be used against prostate cancer, as reported in an earlier investigation against cancerous cells. Moreover, these chemical derivatives can be examined as AKIs through preclinical studies. In addition, the synthesis of novel AKIs through these medicinal chemistry substrates in the laboratory using in silico and synthetic routes could be beneficial to develop prospective novel AKIs to target chemoresistant cancers. This study is beneficial to oncologists, chemists, and medicinal chemists to explore novel chemical moiety synthesis to target specifically the peptide sequences of aurora kinases in several chemoresistant cancer cell types.

Emerging role of competing endogenous RNA in lung cancer drug resistance

Lung cancer remains one of the most common malignant cancers worldwide, and its survival rate is extremely low. Chemotherapy, the mainstay of lung cancer treatment, is not as effective as it could be due to the development of cellular resistance. The molecular mechanisms of drug resistance in lung cancer remain to be elucidated. Accumulating evidence suggests that ceRNAs are involved in various carcinogenesis and development. CeRNA is a transcript that regulates each other through competition with miRNA. However, the relationship between ceRNAs and chemoresistance in lung cancer remains unclear. In this narrative review, we provided a summary of treatment approaches that focus on ceRNA networks to overcome drug resistance.

Comprehensively analyzing the genetic alterations, and identifying key genes in ovarian cancer

Though significant improvements have been made in the treatment methods for ovarian cancer (OC), the prognosis for OC patients is still poor. Exploring hub genes associated with the development of OC and utilizing them as appropriate potential biomarkers or therapeutic targets is highly valuable. In this study, the differentially expressed genes (DEGs) were identified from an independent GSE69428 Gene Expression Omnibus (GEO) dataset between OC and control samples. The DEGs were processed to construct the protein-protein interaction (PPI) network using STRING. Later, hub genes were identified through Cytohubba analysis of the Cytoscape. Expression and survival profiling of the hub genes were validated using GEPIA, OncoDB, and GENT2. For exploring promoter methylation levels and genetic alterations in hub genes, MEXPRESS and cBioPortal were utilized, respectively. Moreover, DAVID, HPA, TIMER, CancerSEA, ENCORI, DrugBank, and GSCAlite were used for gene enrichment analysis, subcellular localization analysis, immune cell infiltration analysis, exploring correlations between hub genes and different diverse states, lncRNA-miRNA-mRNA co-regulatory network analysis, predicting hub gene-associated drugs, and conducting drug sensitivity analysis, respectively. In total, 8947 DEGs were found between OC and normal samples in GSE69428. After STRING and Cytohubba analysis, 4 hub genes including TTK (TTK Protein Kinase), (BUB1 mitotic checkpoint serine/threonine kinase B) BUB1B, (Nucleolar and spindle-associated protein 1) NUSAP1, and (ZW10 interacting kinetochore protein) ZWINT were selected as the hub genes. Further, it was validated that these 4 hub genes were significantly up-regulated in OC samples compared to normal controls, but overexpression of these genes was not associated with overall survival (OS). However, genetic alterations in those genes were found to be linked with OS and disease-free (DFS) survival. Moreover, this study also revealed some novel links between TTK, BUB1B, NUSAP1, and ZWINT overexpression and promoter methylation status, immune cell infiltration, miRNAs, gene enrichment terms, and various chemotherapeutic drugs. Four hub genes, including TTK, BUB1B, NUSAP1, and ZWINT, were revealed as tumor-promotive factors in OC, having the potential to be utilized as novel biomarkers and therapeutic targets for OC management.

The involvement of Aurora-A and p53 in oxaliplatin-resistant colon cancer cells

Resistance to chemotherapy is the deadlock in cancer treatment. In this study, we used wild-type LOVO (LOVO^WT ), a human colon cancer cell line, and the oxaliplatin-resistant sub-clone LOVO^OR cells to investigate the molecular mechanisms of the development of drug resistance in colon cancer. Compared with LOVO^WT cells, LOVO^OR cells had a high proliferation capacity and a high percentage on the G2/M phase. The expression and activation of Aurora-A, a critical kinase in G2/M phase, were higher in LOVO^OR cells than in LOVO^WT cells. The results from immunofluorescence indicated an irregular distribution of Aurora-A in LOVO^OR cells. To evaluate the importance of Aurora-A in oxaliplatin-resistant property of LOVO^OR cells, overexpression of Aurora-A in LOVO^WT cells and otherwise knockdown of Aurora-A in LOVO^OR cells were performed and followed by administration of oxaliplatin. The results indicated that Aurora-A might contribute to the resistance of LOVO^OR cells to oxaliplatin treatment by depressing p53 signaling. The specific findings in this study provide a possibility that targeting Aurora-A might be a solution for patients who have failed oxaliplatin treatment.

TP-0903 Is Active in Preclinical Models of Acute Myeloid Leukemia with TP53 Mutation/Deletion

Acute myeloid leukemia (AML) with mutations in the tumor suppressor gene TP53 confers a dismal prognosis with 3-year overall survival of <5%. While inhibition of kinases involved in cell cycle regulation induces synthetic lethality in a variety of TP53 mutant cancers, this strategy has not been evaluated in mutant TP53 AML. Previously, we demonstrated that TP-0903 is a novel multikinase inhibitor with low nM activity against AURKA/B, Chk1/2, and other cell cycle regulators. Here, we evaluated the preclinical activity of TP-0903 in TP53 mutant AML cell lines, including a single-cell clone of MV4-11 containing a TP53 mutation (R248W), Kasumi-1 (R248Q), and HL-60 (TP 53 null). TP-0903 inhibited cell viability (IC50, 12−32 nM) and induced apoptosis at 50 nM. By immunoblot, 50 nM TP-0903 upregulated pChk1/2 and pH2AX, suggesting induction of DNA damage. The combination of TP-0903 and decitabine was additive in vitro, and in vivo significantly prolonged median survival compared to single-agent treatments in mice xenografted with HL-60 (vehicle, 46 days; decitabine, 55 days; TP-0903, 63 days; combination, 75 days) or MV4-11 (R248W) (51 days; 62 days; 81 days; 89 days) (p < 0.001). Together, these results provide scientific premise for the clinical evaluation of TP-0903 in combination with decitabine in TP53 mutant AML.

Comprehensive bioinformatics analysis confirms RBMS3 as the central candidate biological target for ovarian cancer

Ovarian cancer (OC) is one of the most lethal malignancies in the female reproductive system. To find genes related to cancer progression targeting specific biological factors for targeted therapy, bioinformatics technology has been widely used. To screen the prognostic gene markers of OC by bioinformatics and explore their potential molecular biological mechanisms. Two data sets related to OC, GSE54388, and GSE119056, were rooted in the open comprehensive gene expression database (GEO). To correct the background of the data, standardize and screen differentially expressed genes (DEGs) using the R software limma package. The selected DEGs were enriched by Gene Ontology (GO) and through DAVID online database. Kyoto Encyclopedia of Genes and Genomes (KEGG) signal pathway analysis and protein-protein interaction network (PPI-network) map were constructed by STRING online database and Cytoscape software. Combined with the TCGA database, univariate and multivariate COX regression were used to screen prognostic genes. QRT-PCR was used to verify DEGs in clinical tissue samples. Eventually, the function of RBMS3 on the viability, migration, invasion, and apoptosis of OC cells was tested through functional experiments in vitro. 352 common DEGs were screened from GSE54388 and GSE119056 data sets. Survival analysis showed that MEIS2, TSTA3, CNTN1, RBMS3, and TRA2A were considered to be connected with the prognosis of OC. We discover that the expression level of RBMS3 was positively connected with the overall survival (OS) rate of sufferers with OC. The level of RBMS3 in OC tissues was markedly lower than that in neighboring structures and the outcomes of the GEPIA database were consistent with those of the qRT-PCR experiment. Through gene transfection technology it was found that overexpression of RBMS3 in OC cells substantially suppressed the vitality, migration, and invasion of OC cells and raised the rates of apoptosis in the OC cells. In this experiment, we distinguish 5 genes that may participate in the prognosis of OC and showed the key genes and pathways related to OC. It is speculated that RBMS3, a tumor suppressor gene, can be applied as a potential biological marker for the treatment of OC, gene expression summary, and prognosis.

Targeting Histone Epigenetic Modifications and DNA Damage Responses in Synthetic Lethality Strategies in Cancer?

Synthetic lethality strategies are likely to be integrated in effective and specific cancer treatments. These strategies combine different specific targets, either in similar or cooperating pathways. Chromatin remodeling underlies, directly or indirectly, all processes of tumor biology. In this context, the combined targeting of proteins associated with different aspects of chromatin remodeling can be exploited to find new alternative targets or to improve treatment for specific individual tumors or patients. There are two major types of proteins, epigenetic modifiers of histones and nuclear or chromatin kinases, all of which are druggable targets. Among epigenetic enzymes, there are four major families: histones acetylases, deacetylases, methylases and demethylases. All these enzymes are druggable. Among chromatin kinases are those associated with DNA damage responses, such as Aurora A/B, Haspin, ATM, ATR, DNA-PK and VRK1-a nucleosomal histone kinase. All these proteins converge on the dynamic regulation chromatin organization, and its functions condition the tumor cell viability. Therefore, the combined targeting of these epigenetic enzymes, in synthetic lethality strategies, can sensitize tumor cells to toxic DNA-damage-based treatments, reducing their toxicity and the selective pressure for tumor resistance and increasing their immunogenicity, which will lead to an improvement in disease-free survival and quality of life.

Regulated cell death (RCD) in cancer: key pathways and targeted therapies

Regulated cell death (RCD), also well-known as programmed cell death (PCD), refers to the form of cell death that can be regulated by a variety of biomacromolecules, which is distinctive from accidental cell death (ACD). Accumulating evidence has revealed that RCD subroutines are the key features of tumorigenesis, which may ultimately lead to the establishment of different potential therapeutic strategies. Hitherto, targeting the subroutines of RCD with pharmacological small-molecule compounds has been emerging as a promising therapeutic avenue, which has rapidly progressed in many types of human cancers. Thus, in this review, we focus on summarizing not only the key apoptotic and autophagy-dependent cell death signaling pathways, but the crucial pathways of other RCD subroutines, including necroptosis, pyroptosis, ferroptosis, parthanatos, entosis, NETosis and lysosome-dependent cell death (LCD) in cancer. Moreover, we further discuss the current situation of several small-molecule compounds targeting the different RCD subroutines to improve cancer treatment, such as single-target, dual or multiple-target small-molecule compounds, drug combinations, and some new emerging therapeutic strategies that would together shed new light on future directions to attack cancer cell vulnerabilities with small-molecule drugs targeting RCD for therapeutic purposes.

AURKB as a Promising Prognostic Biomarker in Hepatocellular Carcinoma

The Aurora kinases form a family of 3 genes encoding serine/threonine kinases and are involved in the regulation of cell division during the mitosis. This study was designed to investigate the prognostic role of Aurora kinases in hepatocellular carcinoma (HCC). In this study, we analyzed the expression, overall survival (OS) data, promoter methylation level, and relationship with immunoinhibitors of Aurora kinases in patients with HCC from GEPIA2, UALCAN, OncoLnc, and TISIDB databases. Protein-protein interaction (PPI) network, gene ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome pathway analysis were performed using the STRING database and Cytoscape software. We found that the mRNA expression, stages of HCC, and OS of AURKA and AURKB in HCC tissues were significantly different from control tissues, but there were significant inconsistencies in promoter methylation level and relationship with immunoinhibitors for AURKA and AURKB. None of the above items were significantly different for AURKC. Furthermore, a hub module including AURKA, AURKB, and AURKC was identified within the PPI network constructed with the Molecular Complex Detection (MCODE) plug-in in Cytoscape software. Our results show that AURKB could be a potential biomarker for HCC prognosis.

Identification of Key Biomarkers and Pathways in Small-Cell Lung Cancer Using Biological Analysis

Background

Small-cell lung cancer (SCLC) is a major cause of carcinoma-related deaths worldwide. The aim of this study was to identify the key biomarkers and pathways in SCLC using biological analysis.

Methods

Key genes involved in the development of SCLC were identified by downloading three datasets from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened using the GEO2R online analyzer; for the functional annotation and pathway enrichment analysis of genes, Funrich software was used. Construction of protein-to-protein interaction (PPI) networks was accomplished using the Search Tool for the Retrieval of Interacting Genes (STRING), and network visualization and module identification were performed using Cytoscape.

Results

A total of 268 DEGs were ultimately obtained. The enriched functions and pathways of the upregulated DEGs included cell cycle, mitotic, and DNA replication, and the downregulated DEGs were enriched in epithelial-to-mesenchymal transition, serotonin degradation, and noradrenaline. Analysis of significant modules demonstrated that the upregulated genes are primarily concentrated in functions related to cell cycle and DNA replication. Kaplan-Meier analysis of hub genes revealed that they may promote the carcinogenesis and progression of SCLC. The result of ONCOMINE demonstrated that these 10 hub genes were significantly overexpressed in SCLC compared with normal samples.

Conclusion

Identification of the molecular functions and signaling pathways of participating DEGs can deepen the current understanding of the molecular mechanisms of SCLC. The knowledge gained from this work may contribute to the development of treatment options and improve the prognosis of SCLC in the future.

Aurora kinases in ovarian cancer

Aurora kinases (AURK) are key regulators of the mitotic spindle formation. AURK is frequently overexpressed in ovarian cancer and this overexpression has been frequently associated with prognosis in these tumours. Interestingly, AURK have been shown to interact with DNA repair mechanisms and other cell cycle regulators. These functions have brought light to Aurora family as a potential target for anticancer therapy. In the last years, two clinical trials with different AURK inhibitors have shown activity in epithelial and clear-cell ovarian cancer. Although there is a lack of predictive factors of AURK inhibition activity, recent trials have identified some candidates. This review will focus in the functions of the AURK family, its role as prognostic factor in epithelial ovarian cancer and potential clinical implications.

The landscape of gene co-expression modules correlating with prognostic genetic abnormalities in AML

Background

The heterogenous cytogenetic and molecular variations were harbored by AML patients, some of which are related with AML pathogenesis and clinical outcomes. We aimed to uncover the intrinsic expression profiles correlating with prognostic genetic abnormalities by WGCNA.

Methods

We downloaded the clinical and expression dataset from BeatAML, TCGA and GEO database. Using R (version 4.0.2) and ‘WGCNA’ package, the co-expression modules correlating with the ELN2017 prognostic markers were identified (R² ≥ 0.4, p < 0.01). ORA detected the enriched pathways for the key co-expression modules. The patients in TCGA cohort were randomly assigned into the training set (50%) and testing set (50%). The LASSO penalized regression analysis was employed to build the prediction model, fitting OS to the expression level of hub genes by ‘glmnet’ package. Then the testing and 2 independent validation sets (GSE12417 and GSE37642) were used to validate the diagnostic utility and accuracy of the model.

Results

A total of 37 gene co-expression modules and 973 hub genes were identified for the BeatAML cohort. We found that 3 modules were significantly correlated with genetic markers (the ‘lightyellow’ module for NPM1 mutation, the ‘saddlebrown’ module for RUNX1 mutation, the ‘lightgreen’ module for TP53 mutation). ORA revealed that the ‘lightyellow’ module was mainly enriched in DNA-binding transcription factor activity and activation of HOX genes. The ‘saddlebrown’ module was enriched in immune response process. And the ‘lightgreen’ module was predominantly enriched in mitosis cell cycle process. The LASSO- regression analysis identified 6 genes (NFKB2, NEK9, HOXA7, APRC5L, FAM30A and LOC105371592) with non-zero coefficients. The risk score generated from the 6-gene model, was associated with ELN2017 risk stratification, relapsed disease, and prior MDS history. The 5-year AUC for the model was 0.822 and 0.824 in the training and testing sets, respectively. Moreover, the diagnostic utility of the model was robust when it was employed in 2 validation sets (5-year AUC 0.743–0.79).

Conclusions

We established the co-expression network signature correlated with the ELN2017 recommended prognostic genetic abnormalities in AML. The 6-gene prediction model for AML survival was developed and validated by multiple datasets.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-02914-2.

Aurora kinase A, a synthetic lethal target for precision cancer medicine

Recent advances in high-throughput sequencing technologies and data science have facilitated the development of precision medicine to treat cancer patients. Synthetic lethality is one of the core methodologies employed in precision cancer medicine. Synthetic lethality describes the phenomenon of the interplay between two genes in which deficiency of a single gene does not abolish cell viability but combined deficiency of two genes leads to cell death. In cancer treatment, synthetic lethality is leveraged to exploit the dependency of cancer cells on a pathway that is essential for cell survival when a tumor suppressor is mutated. This approach enables pharmacological targeting of mutant tumor suppressors that are theoretically undruggable. Successful clinical introduction of BRCA-PARP synthetic lethality in cancer treatment led to additional discoveries of novel synthetic lethal partners of other tumor suppressors, including p53, PTEN, and RB1, using high-throughput screening. Recent work has highlighted aurora kinase A (AURKA) as a synthetic lethal partner of multiple tumor suppressors. AURKA is a serine/threonine kinase involved in a number of central biological processes, such as the G2/M transition, mitotic spindle assembly, and DNA replication. This review introduces synthetic lethal interactions between AURKA and its tumor suppressor partners and discusses the potential of AURKA inhibitors in precision cancer medicine.

MZ1 co-operates with trastuzumab in HER2 positive breast cancer

BACKGROUND

Although the anti-HER2 antibody trastuzumab augments patient survival in HER2+ breast cancer, a relevant number of patients progress to this treatment. In this context, novel drug combinations are needed to increase its antitumor activity. In this work, we have evaluated the efficacy of proteolysis targeting chimera (PROTAC) compounds based on BET inhibitors (BETi) to augment the activity of trastuzumab in HER2+ breast cancer models.

METHODS

BT474 and SKBR3 HER2+ breast cancer cell lines were used. The effects of trastuzumab and the BET-PROTAC MZ1 either alone or in combination, were evaluated using MTT proliferation assays, three-dimensional invasion and adhesion cultures, flow cytometry, qPCR and Western blot. In vivo studies were carried out in a xenografted model in mice. Finally, a Clariom_S_Human transcriptomic array was applied to identify deregulated genes after treatments.

RESULTS

MZ1 induced a higher antiproliferative effect compared to the BETi JQ1. The combination of MZ1 and -trastuzumab significantly decreased cell proliferation, the formation of three-dimensional structures and cellular invasion compared to either of the drugs alone. Evaluation of apoptosis resulted in an increase of cell death following treatment with the combination, and biochemical studies displayed modifications of apoptosis and DNA damage components. In vivo administration of agents alone or combined, to tumors orthotopically xenografted in mice, resulted in a decrease of the tumor volume only after MZ1-Trastuzumab combination treatment. Results from a transcriptomic array indicated a series of newly described transcription factors including HOXB7, MEIS2, TCERG1, and DNAJC2, that were associated to poor outcome in HER2+ breast cancer subtype and downregulated by the MZ1-trastuzumab combination.

CONCLUSIONS

We describe an active novel combination that includes the BET-PROTAC MZ1 and trastuzumab, in HER2+ tumors. Further studies should be performed to confirm these findings and pave the way for their future clinical development.

Knockdown of AURKA sensitizes the efficacy of radiation in human colorectal cancer

AIMS

Abnormally amplified expression of AURKA (aurora kinase A) is closely related to chemo-resistance in human colorectal cancer, lung cancer and leukemia. However, the biological role of AURKA in response to radio-sensitivity in human colorectal cancer is still unknown. Therefore, we evaluated the radio-sensitize ability of perturbation AURKA in human colorectal cancer.

MAIN METHODS

The knockdown effect of shAURKA was determined by western blot and qRT-PCR, respectively. Cell growth was determined by CCK-8 and clonogenic assay. Cell migration and metastasis was measured by wound healing assay and transwell invasive assay, respectively. Cell cycle and apoptosis was analyzed by flow cytometry. The alteration of down-stream targets was determined by western blot analysis.

KEY FINDINGS

We observed that high-level of AURKA expression is associated with poor prognosis in CRC patients receiving radiotherapy. Knockdown of AURKA significantly sensitizes the efficacy of radiation on the proliferation of HCT116 and HT-29 cells. The combination of AURKA inhibition and radiation could effectively suppress the ability of cell migration and metastasis, but also synergistically induce cellular apoptosis and arrest cell cycle at G2/M phase. Further studies demonstrated that knockdown AURKA markedly enhanced the efficacy of radiation through elevated PARP cleavage and induced AURKA-mediated pro-apoptosis factor BIM. Meanwhile, knockdown of AURKA in combination with radiation synergistically suppressed the regulator in blockage of G2/M phase, CDK2.

SIGNIFICANCE

Taken together, our results provide the evidence that targeted inhibition of AURKA could be a promising strategy for enhancing the efficacy of radiation for the treatment of human colorectal cancer.

Identification of the Hub Genes Associated with the Prognosis of Ovarian Cancer Patients via Integrated Bioinformatics Analysis and Experimental Validation

Background

This study aimed to identify the hub genes associated with prognosis of patients with ovarian cancer by using integrated bioinformatics analysis and experimental validation.

Methods

Four microarray datasets (GSE12470, GSE14407, GSE18521 and GSE46169) were analyzed by the GEO2R tool to screen common differentially expressed genes (DEGs). Gene Ontology, the Kyoto Encyclopedia of Genes and Genomes, the (KEGG) pathway and Reactome pathway enrichment analysis, protein–protein interaction (PPI) construction, and the identification of hub genes were performed. Furthermore, we performed the survival and expression analysis of the hub genes. In vitro functional assays were performed to assess the effects of hub genes on ovarian cancer cell proliferation, caspase-3/7 activity and invasion.

Results

A total of 89 common DEGs were identified among these four datasets. The KEGG and Reactome pathway results showed that the DEGs were mainly associated with cell cycle, mitotic and p53 signaling pathway. A total of 20 hub genes were identified from the PPI network by using sub-module analysis. The survival analysis revealed that high expression of six hub genes (AURKA, BUB1B, CENPF, KIF11, KIF23 and TOP2A) were significantly correlated with shorter overall survival and progression-free survival of patients with ovarian cancer. Furthermore, the expression of the six hub genes were validated by the GEPIA database and Human Protein Atlas, and functional studies revealed that knockdown of KIF11 and KIF23 suppressed the SKOV3 cell proliferation, increased caspase-3/7 activity and attenuated invasive potentials of SKOV3 cells. In addition, knockdown of KIF11 and KIF23 up-regulated E-cadherin mRNA expression but down-regulated N-cadherin and vimentin mRNA expression in SKOV3 cells.

Conclusion

Our results showed that six hub genes were up-regulated in ovarian cancer tissues and may predict poor prognosis of patients with ovarian cancer. KIF11 and KIF23 may play oncogenic roles in ovarian cancer cell progression via promoting ovarian cancer cell proliferation and invasion.

CRISPR/Cas9 screening identifies a kinetochore-microtubule dependent mechanism for Aurora-A inhibitor resistance in breast cancer

Background

Overexpression of Aurora‐A (AURKA) is a feature of breast cancer and associates with adverse prognosis. The selective Aurora‐A inhibitor alisertib (MLN8237) has recently demonstrated promising antitumor responses as a single agent in various cancer types but its phase III clinical trial was reported as a failure since MLN8237 did not show an apparent effect in prolonging the survival of patients. Thus, identification of potential targets that could enhance the activity of MLN8237 would provide a rationale for drug combination to achieve better therapeutic outcome.

Methods

Here, we conducted a systematic synthetic lethality CRISPR/Cas9 screening of 507 kinases using MLN8237 in breast cancer cells and identified a number of targetable kinases that displayed synthetic lethality interactions with MLN8237. Then, we performed competitive growth assays, colony formation assays, cell viability assays, apoptosis assays, and xenograft murine model to evaluate the synergistic therapeutic effects of Haspin (GSG2) depletion or inhibition with MLN8237. For mechanistic studies, immunofluorescence was used to detect the state of microtubules and the localization of Aurora‐B and mitotic centromere‐associated kinesin (MCAK).

Results

Among the hits, we observed that Haspin depletion or inhibition marginally inhibited breast cancer cell growth but could substantially enhance the killing effects of MLN8237. Mechanistic studies showed that co‐treatment with Aurora‐A and Haspin inhibitors abolished the recruitment of Aurora‐B and mitotic centromere‐associated kinesin (MCAK) to centromeres which were associated with excessive microtubule depolymerization, kinetochore‐microtubule (KT‐MT) attachment failure, and severe mitotic catastrophe. We further showed that the combination of MLN8237 and the Haspin inhibitor CHR‐6494 synergistically reduced breast cancer cell viability and significantly inhibited both in vitro and in vivo tumor growth.

Conclusions

These findings establish Haspin as a synthetic lethal target and demonstrate CHR‐6494 as a potential combinational drug for promoting the therapeutic effects of MLN8237 on breast cancer.

Targeting AURKA in Cancer: molecular mechanisms and opportunities for Cancer therapy

Aurora kinase A (AURKA) belongs to the family of serine/threonine kinases, whose activation is necessary for cell division processes via regulation of mitosis. AURKA shows significantly higher expression in cancer tissues than in normal control tissues for multiple tumor types according to the TCGA database. Activation of AURKA has been demonstrated to play an important role in a wide range of cancers, and numerous AURKA substrates have been identified. AURKA-mediated phosphorylation can regulate the functions of AURKA substrates, some of which are mitosis regulators, tumor suppressors or oncogenes. In addition, enrichment of AURKA-interacting proteins with KEGG pathway and GO analysis have demonstrated that these proteins are involved in classic oncogenic pathways. All of this evidence favors the idea of AURKA as a target for cancer therapy, and some small molecules targeting AURKA have been discovered. These AURKA inhibitors (AKIs) have been tested in preclinical studies, and some of them have been subjected to clinical trials as monotherapies or in combination with classic chemotherapy or other targeted therapies.

Exploration of predictive and prognostic alternative splicing signatures in lung adenocarcinoma using machine learning methods

Background

Alternative splicing (AS) plays critical roles in generating protein diversity and complexity. Dysregulation of AS underlies the initiation and progression of tumors. Machine learning approaches have emerged as efficient tools to identify promising biomarkers. It is meaningful to explore pivotal AS events (ASEs) to deepen understanding and improve prognostic assessments of lung adenocarcinoma (LUAD) via machine learning algorithms.

Method

RNA sequencing data and AS data were extracted from The Cancer Genome Atlas (TCGA) database and TCGA SpliceSeq database. Using several machine learning methods, we identified 24 pairs of LUAD-related ASEs implicated in splicing switches and a random forest-based classifiers for identifying lymph node metastasis (LNM) consisting of 12 ASEs. Furthermore, we identified key prognosis-related ASEs and established a 16-ASE-based prognostic model to predict overall survival for LUAD patients using Cox regression model, random survival forest analysis, and forward selection model. Bioinformatics analyses were also applied to identify underlying mechanisms and associated upstream splicing factors (SFs).

Results

Each pair of ASEs was spliced from the same parent gene, and exhibited perfect inverse intrapair correlation (correlation coefficient = − 1). The 12-ASE-based classifier showed robust ability to evaluate LNM status of LUAD patients with the area under the receiver operating characteristic (ROC) curve (AUC) more than 0.7 in fivefold cross-validation. The prognostic model performed well at 1, 3, 5, and 10 years in both the training cohort and internal test cohort. Univariate and multivariate Cox regression indicated the prognostic model could be used as an independent prognostic factor for patients with LUAD. Further analysis revealed correlations between the prognostic model and American Joint Committee on Cancer stage, T stage, N stage, and living status. The splicing network constructed of survival-related SFs and ASEs depicts regulatory relationships between them.

Conclusion

In summary, our study provides insight into LUAD researches and managements based on these AS biomarkers.

Further Understanding of High-Grade Serous Ovarian Carcinogenesis: Potential Therapeutic Targets

High-grade serous ovarian carcinoma (HGSOC) is the most common type of ovarian cancer and the most lethal gynecologic malignancy due to advanced stage at presentation. Recent years have witnessed progress in the therapy of HGSOC with the introduction of PARP (poly-adenosine diphosphate ribose polymerase) inhibitors and the anti-angiogenic monoclonal antibody bevacizumab to the backbone of chemotherapy or as maintenance therapy after chemotherapy. The improved molecular understanding of ovarian cancer pathogenesis, which has brought these therapies into the clinic, aspires to extend the boundaries of therapies through elucidation of other molecular aspects of ovarian carcinogenesis. This accumulating knowledge has started to be translated to additional targeted therapies that are in various stages of development. These include inhibitors of the function of other proteins involved in homologous recombination deficiency (HRD), such as WEE1 kinase, ATM/ATR kinases and CDK12 inhibitors. Despite disappointing results with immune checkpoint inhibitors monotherapy, harnessing the immune system in HGSOC with combination therapies that promote antigen production and immune cell activation is an avenue being explored. This paper examines arising HGSOC therapies based on molecular understanding of pathogenesis.

Targeting DNA Repair, Cell Cycle, and Tumor Microenvironment in B Cell Lymphoma

The DNA double-strand break (DSB) is the most cytotoxic lesion and compromises genome stability. In an attempt to efficiently repair DSBs, cells activate ATM kinase, which orchestrates the DNA damage response (DDR) by activating cell cycle checkpoints and initiating DSB repair pathways. In physiological B cell development, however, programmed DSBs are generated as intermediates for effective immune responses and the maintenance of genomic integrity. Disturbances of these pathways are at the heart of B cell lymphomagenesis. Here, we review the role of DNA repair and cell cycle control on B cell development and lymphomagenesis. In addition, we highlight the intricate relationship between the DDR and the tumor microenvironment (TME). Lastly, we provide a clinical perspective by highlighting treatment possibilities of defective DDR signaling and the TME in mantle cell lymphoma, which serves as a blueprint for B cell lymphomas.

Inhibition of miR-1193 leads to synthetic lethality in glioblastoma multiforme cells deficient of DNA-PKcs

Glioblastoma multiforme (GBM) is the most malignant primary brain tumor and has the highest mortality rate among cancers and high resistance to radiation and cytotoxic chemotherapy. Although some targeted therapies can partially inhibit oncogenic mutation-driven proliferation of GBM cells, therapies harnessing synthetic lethality are ‘coincidental’ treatments with high effectiveness in cancers with gene mutations, such as GBM, which frequently exhibits DNA-PKcs mutation. By implementing a highly efficient high-throughput screening (HTS) platform using an in-house-constructed genome-wide human microRNA inhibitor library, we demonstrated that miR-1193 inhibition sensitized GBM tumor cells with DNA-PKcs deficiency. Furthermore, we found that miR-1193 directly targets YY1AP1, leading to subsequent inhibition of FEN1, an important factor in DNA damage repair. Inhibition of miR-1193 resulted in accumulation of DNA double-strand breaks and thus increased genomic instability. RPA-coated ssDNA structures enhanced ATR checkpoint kinase activity, subsequently activating the CHK1/p53/apoptosis axis. These data provide a preclinical theory for the application of miR-1193 inhibition as a potential synthetic lethal approach targeting GBM cancer cells with DNA-PKcs deficiency.

Cotargeting CHK1 and PI3K Synergistically Suppresses Tumor Growth of Oral Cavity Squamous Cell Carcinoma in Patient-Derived Xenografts

Oral cavity squamous cell carcinomas (OSCCs) are aggressive tumors, and their recurrence leads to poor prognosis and reduced survival rates. This study aimed to identify therapeutic targets and to evaluate the efficacy of targeted inhibitors in OSCC patient-derived xenograft (PDX) models. Herein, we reported that OSCC PDXs recapitulated the genomic signatures of their paired primary tumors and the expression of CHEK1, PIK3CA, and PIK3CD was significantly upregulated in OSCC. The antitumor efficacy of CHK1 inhibitors (PF477736, AZD7762, LY2606368) and PI3K inhibitors (BYL719, GDC0941, GSK1059615) was investigated in OSCC cell lines and PDX models. Targeting either CHK1 or PI3K effectively inhibited cell proliferation and colony formation by inducing cell cycle arrest and apoptosis in in vitro cell-based assays. Cisplatin-based chemotherapy combined with CHK1 inhibitor treatment synergistically inhibited cell proliferation by suppressing CHK1 phosphorylation and inducing PARP cleavage. Furthermore, compared with monotherapy, cotreatment with CHK1 and PI3K inhibitors exerted synergistic anticancer effects by suppressing CHK1, AKT, and 4E-BP1 phosphorylation. In summary, our study identified CHK1 and PI3K as promising targets, especially in a dual treatment strategy combining a CHK1 inhibitor with cisplatin or a PI3K inhibitor as a novel therapeutic approach for OSCC patients with aberrant cell cycle regulation and PI3K signaling activation.

An Overview of Candidate Therapeutic Target Genes in Ovarian Cancer

Ovarian cancer (OC) shows the highest mortality rate among gynecological malignancies and, because of the absence of specific symptoms, it is frequently diagnosed at an advanced stage, mainly due to the lack of specific and early biomarkers, such as those based on cancer molecular signature identification. Indeed, although significant progress has been made toward improving the clinical outcome of other cancers, rates of mortality for OC are essentially unchanged since 1980, suggesting the need of new approaches to identify and characterize the molecular mechanisms underlying pathogenesis and progression of these malignancies. In addition, due to the low response rate and the high frequency of resistance to current treatments, emerging therapeutic strategies against OC focus on targeting single factors and pathways specifically involved in tumor growth and metastasis. To date, loss-of-function screenings are extensively applied to identify key drug targets in cancer, seeking for more effective, disease-tailored treatments to overcome lack of response or resistance to current therapies. We review here the information relative to essential genes and functional pathways recently discovered in OC, often strictly interconnected with each other and representing promising biomarkers and molecular targets to treat these malignancies.

Construction of a Competitive Endogenous RNA Network for Pancreatic Adenocarcinoma Based on Weighted Gene Co-expression Network Analysis and a Prognosis Model

Pancreatic adenocarcinoma (PAAD) is a pancreatic disease with considerable mortality worldwide. Because of a lack of obvious symptoms at the early stage, most PAAD patients are diagnosed at the terminal stage and prognosis is usually poor. In this study, we firstly obtained RNA sequencing data of 181 patients with PAAD from The Cancer Genome Atlas (TCGA) database to identify early diagnostic biomarkers for PAAD. Survival-related mRNAs were identified using a weighted gene co-expression network analysis (WGCNA), and then a linear prognostic model of seven long non-coding RNAs (lncRNAs) was established using univariate and multivariate Cox proportional hazards regression analyses, which is verified using a time-dependent receiver operating characteristic (ROC) curve analysis. Finally, according to the survival analysis, we constructed a survival-related competing endogenous RNA (ceRNA) network. Our results showed that: (1) The upregulated genes related to cell cycle-related pathway (including homologous recombination, DNA replication and mismatch repair) in PAAD can increase the proliferation ability of cancer cells; (2) The 7-lncRNA signature can predict the overall survival (OS) of PAAD patients; and (3) The key mRNAs and lncRNAs are involved in mutual regulation in the ceRNA network.

Emerging serine-threonine kinase inhibitors for treating ovarian cancer

Introduction: Ovarian cancer is the leading cause of gynecologic cancer death, owing to high rates of incurable, recurrent disease after initial treatment. Serine threonine kinases (STKs) have been proposed as potential therapeutic targets in ovarian cancer because of their role in the initiation and progression of cancers. Experience in non-ovarian cancers suggests that STK inhibitors are active against tumors with specific molecular alterations.Areas covered: This review discusses STK inhibitors in active development in phase II/III clinical trials for ovarian cancer. PubMed and ClinicalTrials.gov were systematically searched to identify STK inhibitor trials for ovarian cancer; active development was confirmed via Pharmaprojects. Available data regarding the efficacy and safety of these compounds are explored.Expert opinion: STK inhibitors currently in development have modest activity as single agents and are unlikely to achieve approval as monotherapy for unselected ovarian cancer patients. Combination trials of STK inhibitors with chemotherapy and/or targeted therapies have suggested an acceptable efficacy/toxicity ratio for certain combinations but confirmatory studies are needed. Carefully designed trials, especially those including somatic molecular analysis, may help identify the subsets of patients most likely to benefit from these therapeutic strategies and determine the role of STK inhibitors in the evolving landscape of precision oncology.

Wise Management of Ovarian Cancer: On the Cutting Edge

Epithelial ovarian cancer (EOC) is the fifth leading cause of cancer mortality among women. Two-thirds of patients present at advanced stage at diagnosis, and the estimated 5 year survival rate is 20-40%. This heterogeneous group of malignancies has distinguishable etiology and molecular biology. Initially, single-gene sequencing was performed to identify germline DNA variations associated with EOC. However, hereditary EOC syndrome can be explained by germline pathogenic variants (gPVs) in several genes. In this regard, next-generation sequencing (NGS) changed clinical diagnostic testing, allowing assessment of multiple genes simultaneously in a faster and cheaper manner than sequential single gene analysis. As we move into the era of personalized medicine, there is evidence that poly (ADP-ribose) polymerase (PARP) inhibitors exploit homologous recombination (HR) deficiency, especially in breast cancer gene 1 and 2 (BRCA1/2) mutation carriers. Furthermore, extensive preclinical data supported the development of aurora kinase (AURK) inhibitors in specific tumor types, including EOC. Their efficacy may be optimized in combination with chemotherapeutic or other molecular agents. The efficacy of metformin in ovarian cancer prevention is under investigation. Certain mutations, such as ARID1A mutations, and alterations in the phosphatidylinositol 3-kinase (PI3K)/AKT/mTOR pathway, which are specific in ovarian clear cell carcinoma (OCCC) and endometrioid ovarian carcinoma (EnOC), may offer additional therapeutic targets in these clinical entities. Malignant ovarian germ cell tumors (MOGCTs) are rare and randomized trials are extremely challenging for the improvement of the existing management and development of novel strategies. This review attempts to offer an overview of the main aspects of ovarian cancer, catapulted from the molecular mechanisms to therapeutic considerations.

mRNAsi Index: Machine Learning in Mining Lung Adenocarcinoma Stem Cell Biomarkers

Cancer stem cells (CSCs), characterized by self-renewal and unlimited proliferation, lead to therapeutic resistance in lung cancer. In this study, we aimed to investigate the expressions of stem cell-related genes in lung adenocarcinoma (LUAD). The stemness index based on mRNA expression (mRNAsi) was utilized to analyze LUAD cases in the Cancer Genome Atlas (TCGA). First, mRNAsi was analyzed with differential expressions, survival analysis, clinical stages, and gender in LUADs. Then, the weighted gene co-expression network analysis was performed to discover modules of stemness and key genes. The interplay among the key genes was explored at the transcription and protein levels. The enrichment analysis was performed to annotate the function and pathways of the key genes. The expression levels of key genes were validated in a pan-cancer scale. The pathological stage associated gene expression level and survival probability were also validated. The Gene Expression Omnibus (GEO) database was additionally used for validation. The mRNAsi was significantly upregulated in cancer cases. In general, the mRNAsi score increases according to clinical stages and differs in gender significantly. Lower mRNAsi groups had a better overall survival in major LUADs, within five years. The distinguished modules and key genes were selected according to the correlations to the mRNAsi. Thirteen key genes (CCNB1, BUB1, BUB1B, CDC20, PLK1, TTK, CDC45, ESPL1, CCNA2, MCM6, ORC1, MCM2, and CHEK1) were enriched from the cell cycle Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, relating to cell proliferation Gene Ontology (GO) terms, as well. Eight of the thirteen genes have been reported to be associated with the CSC characteristics. However, all of them have been previously ignored in LUADs. Their expression increased according to the pathological stages of LUAD, and these genes were clearly upregulated in pan-cancers. In the GEO database, only the tumor necrosis factor receptor associated factor-interacting protein (TRAIP) from the blue module was matched with the stemness microarray data. These key genes were found to have strong correlations as a whole, and could be used as therapeutic targets in the treatment of LUAD, by inhibiting the stemness features.

Identification and validation of key genes with prognostic value in non-small-cell lung cancer via integrated bioinformatics analysis

Background

Lung cancer is the most common cause of cancer‐related death among all human cancers and the five‐year survival rates are only 23%. The precise molecular mechanisms of non‐small cell lung cancer (NSCLC) are still unknown. The aim of this study was to identify and validate the key genes with prognostic value in lung tumorigenesis.

Methods

Four GEO datasets were obtained from the Gene Expression Omnibus (GEO) database. Common differentially expressed genes (DEGs) were selected for Kyoto Encyclopedia of Genes and Genomes pathway analysis and Gene Ontology enrichment analysis. Protein‐protein interaction (PPI) networks were constructed using the STRING database and visualized by Cytoscape software and Molecular Complex Detection (MCODE) were utilized to PPI network to pick out meaningful DEGs. Hub genes, filtered from the CytoHubba, were validated using the Gene Expression Profiling Interactive Analysis database. The expressions and prognostic values of hub genes were carried out through Gene Expression Profiling Interactive Analysis (GEPIA) and Kaplan‐Meier plotter. Finally, quantitative PCR and the Oncomine database were used to verify the differences in the expression of hub genes in lung cancer cells and tissues.

Results

A total of 121 DEGs (49 upregulated and 72 downregulated) were identified from four datasets. The PPI network was established with 121 nodes and 588 protein pairs. Finally, AURKA, KIAA0101, CDC20, MKI67, CHEK1, HJURP, and OIP5 were selected by Cytohubba, and they all correlated with worse overall survival (OS) in NSCLC.

Conclusion

The results showed that AURKA, KIAA0101, CDC20, MKI67, CHEK1, HJURP, and OIP5 may be critical genes in the development and prognosis of NSCLC.

Key points

Our results indicated that AURKA, KIAA0101, CDC20, MKI67, CHEK1, HJURP, and OIP5 may be critical genes in the development and prognosis of NSCLC. Our methods showed a new way to explore the key genes in cancer development.

Identification of Target Associations for Polypharmacology from Analysis of Crystallographic Ligands of the Protein Data Bank

The design of a chemical entity that potently and selectively binds to a biological target of therapeutic relevance has dominated the scene of drug discovery so far. However, recent findings suggest that multitarget ligands may be endowed with superior efficacy and be less prone to drug resistance. The Protein Data Bank (PDB) provides experimentally validated structural information about targets and bound ligands. Therefore, it represents a valuable source of information to help identifying active sites, understanding pharmacophore requirements, designing novel ligands, and inferring structure-activity relationships. In this study, we performed a large-scale analysis of the PDB by integrating different ligand-based and structure-based approaches, with the aim of identifying promising target associations for polypharmacology based on reported crystal structure information. First, the 2D and 3D similarity profiles of the crystallographic ligands were evaluated using different ligand-based methods. Then, activity data of pairs of similar ligands binding to different targets were inspected by comparing structural information with bioactivity annotations reported in the ChEMBL, BindingDB, BindingMOAD, and PDBbind databases. Afterward, extensive docking screenings of ligands in the identified cross-targets were made in order to validate and refine the ligand-based results. Finally, the therapeutic relevance of the identified target combinations for polypharmacology was evaluated from comparison with information on therapeutic targets reported in the Therapeutic Target Database (TTD). The results led to the identification of several target associations with high therapeutic potential for polypharmacology.

ALDH1A1-related stemness in high-grade serous ovarian cancer is a negative prognostic indicator but potentially targetable by EGFR/mTOR-PI3K/aurora kinase inhibitors

Poor chemotherapy response remains a major treatment challenge for high-grade serous ovarian cancer (HGSC). Cancer stem cells are the major contributors to relapse and treatment failure as they can survive conventional therapy. Our objectives were to characterise stemness features in primary patient-derived cell lines, correlate stemness markers with clinical outcome and test the response of our cells to both conventional and exploratory drugs. Tissue and ascites samples, treatment-naive and/or after neoadjuvant chemotherapy, were prospectively collected. Primary cancer cells, cultured under conditions favouring either adherent or spheroid growth, were tested for stemness markers; the same markers were analysed in tissue and correlated with chemotherapy response and survival. Drug sensitivity and resistance testing was performed with 306 oncology compounds. Spheroid growth condition HGSC cells showed increased stemness marker expression (including aldehyde dehydrogenase isoform I; ALDH1A1) as compared with adherent growth condition cells, and increased resistance to platinum and taxane. A set of eight stemness markers separated treatment-naive tumours into two clusters and identified a distinct subgroup of HGSC with enriched stemness features. Expression of ALDH1A1, but not most other stemness markers, was increased after neoadjuvant chemotherapy and its expression in treatment-naive tumours correlated with chemoresistance and reduced survival. In drug sensitivity and resistance testing, five compounds, including two PI3K-mTOR inhibitors, demonstrated significant activity in both cell culture conditions. Thirteen compounds, including EGFR, PI3K-mTOR and aurora kinase inhibitors, were more toxic to spheroid cells than adherent cells. Our results identify stemness markers in HGSC that are associated with a decreased response to conventional chemotherapy and reduced survival if expressed by treatment-naive tumours. EGFR, mTOR-PI3K and aurora kinase inhibitors are candidates for targeting this cell population. © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Silencing Long Non-coding RNA LINC01224 Inhibits Hepatocellular Carcinoma Progression via MicroRNA-330-5p-Induced Inhibition of CHEK1

Hepatocellular carcinoma (HCC) accounts for approximately 85%–90% of primary liver cancers. Based on in silico analysis, differentially expressed long non-coding RNA (lncRNA) LINC01224 in HCC, the downstream microRNA (miRNA) miR-330-5p, and its target gene checkpoint kinase 1 (CHEK1) were selected as research subjects. Herein, this study was designed to evaluate their interaction effects on the malignant phenotypes of HCC cells. LINC01224 and CHEK1 were upregulated and miR-330-5p was downregulated in HCC cells. miR-330-5p shared negative correlations with LINC01224 and CHEK1, and LINC01224 shared a positive correlation with CHEK1. Notably, LINC01224 could specifically bind to miR-330-5p, and CHEK1 was identified as a target gene of miR-330-5p. When LINC01224 was silenced or miR-330-5p was elevated, the sphere and colony formation abilities and proliferative, migrative, and invasive potentials of HCC cells were diminished, while cell cycle arrest and apoptosis were enhanced. Moreover, LINC01224 induced HCC progression in vitro and accelerated tumor formation in nude mice by increasing CHEK1 expression. The key findings of the present study demonstrated that silencing LINC01224 could downregulate the expression of CHEK1 by competitively binding to miR-330-5p, thus inhibiting HCC progression. This result highlights the LINC01224/miR-330-5p/CHEK1 axis as a novel molecular mechanism involved in the pathology of HCC.

Long non-coding RNA LINC00485 acts as a microRNA-195 sponge to regulate the chemotherapy sensitivity of lung adenocarcinoma cells to cisplatin by regulating CHEK1

Background

Long non-coding RNAs (lncRNAs) are a family of non-protein-coding RNAs, which have the ability to influence the chemo-resistance of lung adenocarcinoma (LAC). In this study, we explored the mechanism by which LINC00485 competitively binds to microRNA-195 (miR-195) in the regulation of the chemotherapy sensitivity in LAC by regulating checkpoint kinase 1 (CHEK1).

Methods

Microarray analysis was used to screen out LAC related genes, and interaction between CHEK1 and miR-195, as well as that between miR-195 and LINC00485, was further confirmed by RNA-pull down and RIP. LINC00485 expression in LAC cells (A549 and H1299) was determined. The cells were then introduced with miR-195, anta-miR-195, LINC00485 or si-LINC00485 to identify the role of miR-195 and LINC00485 in LAC through evaluating the expression of CHEK1, CHEK1, Bax, Bcl-2, VEGF and HIF-1α in LAC cells by either RT-qPCR or Western blot analysis. After being treated with different concentration of cisplatin, cell proliferation, colony formation and apoptosis were assessed.

Results

LINC00485 acted as a competitive endogenous RNA against miR-195, and miR-195 directly targeted CHEK1. The expression of LINC00485 was higher in LAC cells. The down-regulation of LINC00485 or the up-regulation of miR-195 decreased the expression of CHEK1, Bcl-2, VEGF and HIF-1α, while also increasing the expression of Bax. Moreover, the over-expression of miR-195, or the silencing of LINC00485 enhanced the sensitivity of LAC cells to cisplatin, thereby promoting the apoptosis of LAC cells while suppressing the proliferation.

Conclusion

LINC00485 competitively binds to miR-195 to elevate CHEK1 expression in LAC cells, suggesting that LINC00485 is a novel direction for therapeutic strategies of LAC.

Inhibition of the Replication Stress Response Is a Synthetic Vulnerability in SCLC That Acts Synergistically in Combination with Cisplatin

Small cell lung cancer (SCLC) is generally regarded as very difficult to treat, mostly due to the development of metastases early in the disease and a quick relapse with resistant disease. SCLC patients initially show a good response to treatment with the DNA damaging agents cisplatin and etoposide. This is, however, quickly followed by the development of resistant disease, which urges the development of novel therapies for this type of cancer. In this study, we set out to compile a comprehensive overview of the vulnerabilities of SCLC. A functional genome-wide screen where all individual genes were knocked out was performed to identify novel vulnerabilities of SCLC. By analysis of the knockouts that were lethal to these cancer cells, we identified several processes to be synthetic vulnerabilities in SCLC. We were able to validate the vulnerability to inhibition of the replication stress response machinery by use of Chk1 and ATR inhibitors. Strikingly, SCLC cells were more sensitive to these inhibitors than nontransformed cells. In addition, these inhibitors work synergistically with either etoposide and cisplatin, where the interaction is largest with the latter. ATR inhibition by VE-822 treatment in combination with cisplatin also outperforms the combination of cisplatin with etoposide in vivo Altogether, our study uncovered a critical dependence of SCLC on the replication stress response and urges the validation of ATR inhibitors in combination with cisplatin in a clinical setting.

TPX2/Aurora kinase A signaling as a potential therapeutic target in genomically unstable cancer cells

Genomic instability is a hallmark feature of cancer cells, and can be caused by defective DNA repair, for instance due to inactivation of BRCA2. Paradoxically, loss of Brca2 in mice results in embryonic lethality, whereas cancer cells can tolerate BRCA2 loss. This holds true for multiple DNA repair genes, and suggests that cancer cells are molecularly "rewired" to cope with defective DNA repair and the resulting high levels of genomic instability. In this study, we aim to identify genes that genomically unstable cancer cells rely on for their survival. Using functional genomic mRNA (FGmRNA) profiling, 16,172 cancer samples were previously ranked based on their degree of genomic instability. We analyzed the top 250 genes that showed a positive correlation between FGmRNA levels and the degree of genomic instability, in a co-functionality network. Within this co-functionality network, a strong cluster of 11 cell cycle-related genes was identified, including TPX2. We then assessed the dependency on these 11 genes in the context of survival of genomically unstable cancer cells, induced by BRCA2 inactivation. Depletion of TPX2 or its associated kinase Aurora-A preferentially reduced cell viability in a panel of BRCA2-deficient cancer cells. In line with these findings, BRCA2-depleted and BRCA2-mutant human cell lines, or tumor cell lines derived from Brca2-/-;p53-/- mice showed increased sensitivity to the Aurora-A kinase inhibitor alisertib, with delayed mitotic progression and frequent mitotic failure. Our findings reveal that BRCA2-deficient cancer cells show enhanced sensitivity to inactivation of TPX2 or its partner Aurora-A, which points at an actionable dependency of genomically unstable cancers.

A phase 1, first-in-human study of AMG 900, an orally administered pan-Aurora kinase inhibitor, in adult patients with advanced solid tumors

Background Aurora kinase overexpression or amplifications are associated with high proliferation, poor prognosis, and therapeutic resistance in human tumors. AMG 900 is an investigational, oral, selective pan-Aurora kinase inhibitor. Methods This first-in-human trial included dose-escalation and dose-expansion phases ( ClinicalTrials.gov : NCT00858377). Dose escalation evaluated the safety, tolerability, and pharmacokinetics of AMG 900 in advanced solid tumors and determined the maximum tolerated dose (MTD) with/without granulocyte colony-stimulating factor (G-CSF) prophylaxis. Dose expansion evaluated clinical activity in three tumor types: taxane- and platinum-resistant ovarian cancer, taxane-resistant triple-negative breast cancer (TNBC), and castration-resistant and taxane- or cisplatin/etoposide-resistant prostate cancer (CRPC). AMG 900 was administered 4 days on/10 days off at 1-50 mg/day during escalation and at the MTD with G-CSF during expansion. Results AMG 900 showed rapid absorption with fast clearance, supporting once-daily dosing. The MTD was 25 mg/day, increasing to 40 mg/day with G-CSF. Grade ≥ 3 treatment-related adverse events included neutropenia (37%), anemia (23%), leukopenia (14%), and thrombocytopenia (12%). During dose expansion, 3/29 (10.3%, 95% CI: 2.0%-28.0%) evaluable patients with ovarian cancer experienced partial response by central imaging per RECIST 1.1; median duration of response was 24.1 weeks (95% CI: 16.1-34.1). Seven patients (24.1%, 95% CI: 10.3%-43.5%) experienced partial response per Gynecologic Cancer InterGroup criteria; 5/9 patients positive for p53 expression responded to treatment. No objective responses were observed in patients with TNBC or CRPC per RECIST 1.1. Conclusions AMG 900 40 mg/day with G-CSF had manageable toxicity and demonstrated single-agent activity in patients with heavily pretreated, chemotherapy-resistant ovarian cancer.