A novel network-based method identifies a cuproplasia-related pan-cancer gene signature to predict patient outcome.

Copper is a vital micronutrient involved in many biological processes and is an essential component of tumour cell growth and migration. Copper influences tumour growth through a process called cuproplasia, defined as abnormal copper-dependent cell-growth and proliferation. Copper-chelation therapy targeting this process has demonstrated efficacy in several clinical trials against cancer. While the molecular pathways associated with cuproplasia are partially known, genetic heterogeneity across different cancer types has limited the understanding of how cuproplasia impacts patient survival. Utilising RNA-sequencing data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) datasets, we generated gene regulatory networks to identify the critical cuproplasia-related genes across 23 different cancer types. From this, we identified a novel 8-gene cuproplasia-related gene signature associated with pan-cancer survival, and a 6-gene prognostic risk score model in low grade glioma. These findings highlight the use of gene regulatory networks to identify cuproplasia-related gene signatures that could be used to generate risk score models. This can potentially identify patients who could benefit from copper-chelation therapy and identifies novel targeted therapeutic strategies.

Copper chelation suppresses epithelial-mesenchymal transition by inhibition of canonical and non-canonical TGF-ß signaling pathways in cancer.

BACKGROUND: Metastatic cancer cells exploit Epithelial-mesenchymal-transition (EMT) to enhance their migration, invasion, and resistance to treatments. Recent studies highlight that elevated levels of copper are implicated in cancer progression and metastasis. Clinical trials using copper chelators are associated with improved patient survival; however, the molecular mechanisms by which copper depletion inhibits tumor progression and metastasis are poorly understood. This remains a major hurdle to the clinical translation of copper chelators. Here, we propose that copper chelation inhibits metastasis by reducing TGF-ß levels and EMT signaling. Given that many drugs targeting TGF-ß have failed in clinical trials, partly because of severe side effects arising in patients, we hypothesized that copper chelation therapy might be a less toxic alternative to target the TGF-ß/EMT axis. RESULTS: Our cytokine array and RNA-seq data suggested a link between copper homeostasis, TGF-ß and EMT process. To validate this hypothesis, we performed single-cell imaging, protein assays, and in vivo studies. Here, we used the copper chelating agent TEPA to block copper trafficking. Our in vivo study showed a reduction of TGF-ß levels and metastasis to the lung in the TNBC mouse model. Mechanistically, TEPA significantly downregulated canonical (TGF-ß/SMAD2&3) and non-canonical (TGF-ß/PI3K/AKT, TGF-ß/RAS/RAF/MEK/ERK, and TGF-ß/WNT/ß-catenin) TGF-ß signaling pathways. Additionally, EMT markers of MMP-9, MMP-14, Vimentin, ß-catenin, ZEB1, and p-SMAD2 were downregulated, and EMT transcription factors of SNAI1, ZEB1, and p-SMAD2 accumulated in the cytoplasm after treatment. CONCLUSIONS: Our study suggests that copper chelation therapy represents a potentially effective therapeutic approach for targeting TGF-ß and inhibiting EMT in a diverse range of cancers.

Systematic review of antitumour efficacy and mechanism of metformin activity in prostate cancer models.

Metformin, the first line pharmacotherapy for type 2 diabetes has demonstrated favourable effects in prostate cancer (PCa) across a range of studies evaluating PCa patient outcomes amongst metformin users. However, a lack of rigorously conducted prospective studies has stalled clinical use in this setting. Despite multiple studies evaluating the mechanisms underpinning antitumour effects of metformin in PCa, to date, no reviews have compared these findings. This systematic review and meta-analysis consolidates the mechanisms accounting for the antitumour effect of metformin in PCa and evaluates the antitumour efficacy of metformin in preclinical PCa studies. Data were obtained through Medline and EMBASE, extracted by two independent assessors. Risk of bias was assessed using the TOXR tool. Meta-analysis compared in vivo reductions of PCa tumour volume with metformin. In total, 447 articles were identified with 80 duplicates, and 261 articles excluded based on eligibility criteria. The remaining 106 articles were assessed and 71 excluded, with 35 articles included for systematic review, and eight included for meta-analysis. The mechanisms of action of metformin regarding tumour growth, viability, migration, invasion, cell metabolism, and activation of signalling cascades are individually discussed. The mechanisms by which metformin inhibits PCa cell growth are multimodal. Metformin regulates expression of multiple proteins/genes to inhibit cellular proliferation, cell cycle progression, and cellular invasion and migration. Published in vivo studies also conclusively demonstrate that metformin inhibits PCa growth. This highlights the potential of metformin to be repurposed as an anticancer agent, warranting further investigation of metformin in the setting of PCa.

Cytotoxic lanthanum oxide nanoparticles sensitize glioblastoma cells to radiation therapy and temozolomide: an in vitro rationale for translational studies.

Glioblastoma (GBM) is a malignant brain tumour with a dismal prognosis, despite best treatment by surgical resection, radiation therapy (RT) and chemotherapy with temozolomide (TMZ). Nanoparticle (NP) therapy is an emerging consideration due to the ability of NPs to be formulated and cross the blood brain barrier. Lanthanum oxide (La2O3) NPs are therapeutically advantageous due to the unique chemical properties of lanthanum making it cytotoxic to cancers, and able to enhance existing anti-cancer treatments. However, La2O3 NPs have yet to be thoroughly investigated in brain tumors. We show that these NPs can reach the brain after venous injection, penetrate into GBM cells via endocytosis, dissociate to be cytotoxic, and enhance the therapeutic effects of RT and TMZ. The mechanisms of cell death by La2O3 NPs were found to be multifaceted. Increasing NP concentration was correlated to increased intrinsic and extrinsic apoptosis pathway markers in a radical oxygen species (ROS)-dependent manner, as well as involving direct DNA damage and autophagic pathways within GBM patient-derived cell lines. NP interactions to sensitize GBM to RT and TMZ were shown to involve these pathways by enhancing ROS and apoptotic mechanisms. We therefore demonstrate the therapeutic potential of La2O3 NPs to treat GBM cells in vitro, and encourage translational exploration in the future.

Constitutive CHK1 Expression Drives a pSTAT3-CIP2A Circuit that Promotes Glioblastoma Cell Survival and Growth.

High-constitutive activity of the DNA damage response protein checkpoint kinase 1 (CHK1) has been shown in glioblastoma (GBM) cell lines and in tissue sections. However, whether constitutive activation and overexpression of CHK1 in GBM plays a functional role in tumorigenesis or has prognostic significance is not known. We interrogated multiple glioma patient cohorts for expression levels of CHK1 and the oncogene cancerous inhibitor of protein phosphatase 2A (CIP2A), a known target of high-CHK1 activity, and examined the relationship between these two proteins in GBM. Expression levels of CHK1 and CIP2A were independent predictors for reduced overall survival across multiple glioma patient cohorts. Using siRNA and pharmacologic inhibitors we evaluated the impact of their depletion using both in vitro and in vivo models and sought a mechanistic explanation for high CIP2A in the presence of high-CHK1 levels in GBM and show that; (i) CHK1 and pSTAT3 positively regulate CIP2A gene expression; (ii) pSTAT3 and CIP2A form a recursively wired transcriptional circuit; and (iii) perturbing CIP2A expression induces GBM cell senescence and retards tumor growth in vitro and in vivo. Taken together, we have identified an oncogenic transcriptional circuit in GBM that can be destabilized by targeting CIP2A. IMPLICATIONS: High expression of CIP2A in gliomas is maintained by a CHK1-dependent pSTAT3-CIP2A recursive loop; interrupting CIP2A induces cell senescence and slows GBM growth adding impetus to the development of CIP2A as an anticancer drug target.

A case study of a long-term glioblastoma survivor with unmethylated MGMT and hypermutated genotype.

Effective treatments that extend survival of malignant brain tumor glioblastoma (GBM) have not changed in more than a decade; however, there exists a minority patient group (<5%) whose survival is longer than 3 yr. We herein present a case report of a long-term surviving 51-yr-old female diagnosed with a MGMT unmethylated GBM. The patient was progression-free for 23 mo. Fresh primary and recurrent tumor samples were collected and processed for patient-derived model development. Whole-genome sequencing (WGS) was performed concurrently with additional standard of care diagnostics. WGS revealed a hypermutated genotype in the germline tissue and in both the primary and recurrent tumor samples. Specific to the matched tumors, an average of 30 cancer driver genes were mutated. Noteworthy was the identification of a nonsynonymous mutation in the POLE gene. As a possible instigator of the hypermutational genotype observed in the tumors, we identified nonsynonymous germline mutations within the mismatch repair genes, MLH1 and PMS2 Mutations within these genes are often indicative of the pan-cancer phenotype known as Lynch syndrome; however, their pathogenicity remains unreported. We performed a drug screen of 165 compounds, which identified one compound, YM155, an experimental survivin inhibitor, that showed effectivity to the patient-derived cell lines of both tumors. Treatment selection based on a patient's genome to individualize treatment for GBM patients could potentially be useful in the clinic. This is a promising avenue for further translational research, with larger databases and integrated platforms to increase the efficiency of analyzing and interpreting the individual genomic data of GBM.

A systematic review and meta-analysis of topoisomerase inhibition in pre-clinical glioma models.

Malignant glioma is a devastating disease affecting both adults and children with limited treatment strategies. Pre-clinical animal studies are critical to the development and planning of novel treatment designs for human clinical trials. Topoisomerases has been a target of interest in the treatment of high grade gliomas, such as glioblastoma, in the past years. Here we assess pre-clinical glioma literature with the aim to identify predictive variables that favour treatment outcomes from topoisomerase inhibition. Data was extracted from 90 experimental comparisons, this was divided based on available survival (n = 61) and tumor volume (n = 29) data. The meta-analysis revealed that the overall effect of topoisomerase inhibition prolonged survival by a factor of 1.33 (95% CI: 1.23-1.43) and reduced tumor growth by a factor of 3.21 (95% CI: 1.99-5.88), with considerable between-study heterogeneity. Multivariable meta-regression identified glioma model, type of control, route of drug administration and drug of choice to be predictive of improved survival outcome. Publication bias assessment by contour-enhanced funnel plots, Egger's regression test and trim and fill analysis showed evidence of publication bias in all studies. This study identified multiple study design factors that should be taken into consideration to improve the translation of pre-clinical investigation of topoisomerase inhibition into clinical use.

Veliparib in combination with radiotherapy for the treatment of MGMT unmethylated glioblastoma.

BACKGROUND: The O 6 -methylguanine methyltransferase (MGMT) gene is frequently unmethylated in patients with glioblastoma (GBM), rendering them non-responsive to the standard treatment regime of surgery followed by concurrent radiotherapy (RT) and temozolomide. Here, we investigate the efficacy of adding a PARP inhibitor, veliparib, to radiotherapy to treat MGMT unmethylated GBM. METHODS: The inhibition of PARP with veliparib (ABT-888), a potent and orally bioavailable inhibitor in combination with RT was tested on a panel of patient derived cell lines (PDCLs) and patient-derived xenografts (PDX) models generated from GBM patients with MGMT unmethylated tumors. RESULTS: The combination of veliparib and RT inhibited colony formation in the majority of PDCLs tested. The PDCL, RN1 showed significantly reduced levels of the homologous repair protein, Mre11 and a heightened response to PARP inhibition measured by increased apoptosis and decreased colony formation. The oral administration of veliparib (12.5 mg/kg, twice daily for 5 days in a 28-day treatment cycle) in combination with whole brain RT (4 Gy) induced apoptosis (Tunel staining) and decreased cell proliferation (Ki67 staining) in a PDX of MGMT unmethylated GBM. Significantly longer survival times of the PDX treated with the combination treatment were recorded compared to RT only or veliparib only. CONCLUSIONS: Our results demonstrate preclinical efficacy of targeting PARP at multiple levels and provide a new approach for the treatment of MGMT unmethylated GBM.

Improving the dictionary lookup approach for disease normalization using enhanced dictionary and query expansion.

The rapidly increasing biomedical literature calls for the need of an automatic approach in the recognition and normalization of disease mentions in order to increase the precision and effectivity of disease based information retrieval. A variety of methods have been proposed to deal with the problem of disease named entity recognition and normalization. Among all the proposed methods, conditional random fields (CRFs) and dictionary lookup method are widely used for named entity recognition and normalization respectively. We herein developed a CRF-based model to allow automated recognition of disease mentions, and studied the effect of various techniques in improving the normalization results based on the dictionary lookup approach. The dataset from the BioCreative V CDR track was used to report the performance of the developed normalization methods and compare with other existing dictionary lookup based normalization methods. The best configuration achieved an F-measure of 0.77 for the disease normalization, which outperformed the best dictionary lookup based baseline method studied in this work by an F-measure of 0.13.Database URL: https://github.com/TCRNBioinformatics/DiseaseExtract.

Integration and Analysis of Heterogeneous Colorectal Cancer Data for Translational Research.

Cancer is the number one cause of death in Australia with colorectal cancer being the second most common cancer type. The translation of cancer research into clinical practice is hindered by the lack of integration of heterogeneous and autonomous data from various data sources. Integration of heterogeneous data can offer researchers a comprehensive source for biospecimen identification, hypothesis formulation, hypothesis validation, cohort discovery and biomarker discovery. Alongside the increasing prominence of big data, various translational research tools such as tranSMART have emerged that can converge and analyse different types of data. In this study, we show the integration of different data types from a significant Australian colorectal cancer cohort. Additionally, colorectal cancer datasets from The Cancer Genome Atlas were also integrated for comparison. These integrated data are accessible via http://www.tcrn.unsw.edu.au/transmart. The use of translational research tools for data integration can provide a cost-effective and rapid approach to translational cancer research.

The challenges associated with molecular targeted therapies for glioblastoma.

Glioblastoma (GBM) is the most aggressive malignant brain tumor in adults. Improvements in the treatment of GBM have remained static since the advent of the standard therapy which includes radiation with concurrent and adjuvant temozolomide treatment. Developing treatment and diagnostic or companion biomarker combinations is transforming the way we treat numerous cancers. However, can this emerging paradigm be also effective for GBM? Can GBM be treated the same way as other cancers? Here we review the challenges for a personalized molecular targeted therapeutic approach in GBM. The specific challenges for establishing a personalized molecular targeted medicine program for GBM patients include overcoming the blood brain barrier, unravelling the intra- and inter-heterogeneity that exists and the importance of developing more relevant animal models that recapitulate a patient's GBM tumor.

Incorporation of biomarkers in phase II studies of recurrent glioblastoma.

The survival trends for glioblastoma (GBM) patients have remained largely static, reflecting a lack of improvement in the therapeutic options for patients. Less than 5 % of newly diagnosed GBM survives more than 5 years. Tumor relapse is nearly universal and the majority of patients do not respond to further systemic therapy. The results from phase II studies conducted with recurrent GBM patients have not translated to successful confirmatory studies and thus we have reached a significant roadblock in the development of new treatments for patients with recurrent GBM. The development of new, active, and potentially targeted drugs for the treatment of recurrent GBM represents a major unmet need. The incorporation of diagnostic/companion biomarker combinations into the phase II studies and appropriate stratification of the patients is lagging significantly behind other larger cancer groups such as breast, non-small cell lung cancer, and melanoma. We herein carried out a systematic review of the phase II clinical studies conducted in patients with recurrent GBM (2010-2013 inclusive) to assess the degree of biomarker incorporation within the clinical trial design.