Claire Grills

Gene Expression Meta-Analysis Identifies VDAC1 as a Predictor of Poor Outcome in Early Stage Non-Small Cell Lung Cancer

BACKGROUND The bioenergetic status of non-small cell lung cancer correlates with tumour aggressiveness. The voltage dependent anion channel type 1 (VDAC1) is a component of the mitochondrial permeability transition pore, regulates mitochondrial ATP/ADP exchange suggesting that its over-expression could be associated with energy dependent processes including increased proliferation and invasiveness. To test this hypothesis, we conducted an in vivo gene-expression meta-analysis of surgically resected non-small cell lung cancer (NSCLC) using 602 individual expression profiles, to examine the impact of VDAC1 on survival. METHODOLOGY/PRINCIPAL FINDINGS High VDAC1 expression was associated with shorter overall survival with hazard ratio (HR) = 0.6639 (95% confidence interval (CI) 0.4528 to 0.9721), p = 0.035352 corresponding to 52 versus 101 months. VDAC1 predicted shorter time to recurrence and was shown to be an independent prognostic factor compared with histology, gender, age, nodal stage and tumour stage in a Cox multivariate analysis. Supervised analysis of all the datasets identified a 6-gene signature comprising HNRNPC, HSPA4, HSPA9, UBE2D2, CSNK1A1 and G3BP1 with overlapping functions involving regulation of protein turnover, RAS-RAF-MEK pathway and transcription. VDAC1 predicted survival in breast cancer and myeloma and an unsupervised analysis revealed enrichment of the VDAC1 signature in specific subsets. CONCLUSIONS In summary, gene expression analysis identifies VDAC1 gene expression as a predictor of poor outcome in NSCLC and other cancers and is associated with dysregulation of a conserved set of biological pathways, which may be causally associated with aggressive tumour behaviour.

Polyomavirus enhancer activator 3 protein promotes breast cancer metastatic progression through Snail-induced epithelial-mesenchymal transition.

Polyomavirus enhancer activator 3 protein (Pea3), also known as ETV4, is a member of the Ets‐transcription factor family, which promotes metastatic progression in various types of solid cancer. Pea3‐driven epithelial‐mesenchymal transition (EMT) has been described in lung and ovarian cancers. The mechanisms of Pea3‐induced EMT, however, are largely unknown. Here we show that Pea3 overexpression promotes EMT in human breast epithelial cells through transactivation of Snail (SNAI1), an activator of EMT. Pea3 binds to the human Snail promoter through the two proximal Pea3 binding sites and enhances Snail expression. In addition, knockdown of Pea3 in invasive breast cancer cells results in down‐regulation of Snail, partial reversal of EMT, and reduced invasiveness in vitro. Moreover, knockdown of Snail partially rescues the phenotype induced by Pea3 overexpression, suggesting that Snail is one of the mediators bridging Pea3 and EMT, and thereby metastatic progression of the cancer cells. In four breast cancer patient cohorts whose microarray and survival data were obtained from the Gene Expression Omnibus database, Pea3 and Snail expression are significantly correlated with each other and with overall survival of breast cancer patients. We further demonstrate that nuclear localization of Pea3 is associated with Snail expression in breast cancer cell lines and is an independent predictor of overall survival in a Chinese breast cancer patient cohort. In conclusion, our results suggest that Pea3 may be an important prognostic marker and a therapeutic target for metastatic progression of human breast cancer. Copyright

Dynamical systems analysis of mitochondrial BAK activation kinetics predicts resistance to BH3 domains.

Introduction The molecular mechanism underlying mitochondrial BAK activation during apoptosis remains highly controversial. Two seemingly conflicting models have been proposed. In one, BAK requires so-called activating BH3 only proteins (aBH3) to initiate its conformation change. In the other, displacement from inhibitory pro-survival BCL-2 proteins (PBPs) and monomerization of BAK by PBP selective dissociator BH3-only proteins (dBH3) is sufficient. Methodology/Principal Findings To better understand the kinetic implications of these conflicting but highly evidence-based models, we have conducted a deterministic, dynamical systems analysis to explore the kinetics underlying the first step of BAK activation, as a non-linear reaction system. We show that dBH3 induced BAK activation is efficient, even in the absence of aBH3s, provided constitutive interaction of PBPs with open conformation BAK occurs in an adenoviral E1B 19K-like manner. The pattern of PBP expression robustly predicts the efficacy of dBH3s. Conclusion Our findings accommodate the prevailing BAK activation models as potentially coexisting mechanisms capable of initiating BAK activation, and supports a model based approach for predicting resistance to therapeutically relevant small molecule BH3 mimetics.

A TMA De-Arraying Method for High Throughput Biomarker Discovery in Tissue Research

Background Tissue MicroArrays (TMAs) represent a potential high-throughput platform for the analysis and discovery of tissue biomarkers. As TMA slides are produced manually and subject to processing and sectioning artefacts, the layout of TMA cores on the final slide and subsequent digital scan (TMA digital slide) is often disturbed making it difficult to associate cores with their original position in the planned TMA map. Additionally, the individual cores can be greatly altered and contain numerous irregularities such as missing cores, grid rotation and stretching. These factors demand the development of a robust method for de-arraying TMAs which identifies each TMA core, and assigns them to their appropriate coordinates on the constructed TMA slide. Methodology This study presents a robust TMA de-arraying method consisting of three functional phases: TMA core segmentation, gridding and mapping. The segmentation of TMA cores uses a set of morphological operations to identify each TMA core. Gridding then utilises a Delaunay Triangulation based method to find the row and column indices of each TMA core. Finally, mapping correlates each TMA core from a high resolution TMA whole slide image with its name within a TMAMap. Conclusion This study describes a genuine robust TMA de-arraying algorithm for the rapid identification of TMA cores from digital slides. The result of this de-arraying algorithm allows the easy partition of each TMA core for further processing. Based on a test group of 19 TMA slides (3129 cores), 99.84% of cores were segmented successfully, 99.81% of cores were gridded correctly and 99.96% of cores were mapped with their correct names via TMAMaps. The gridding of TMA cores were also extensively tested using a set of 113 pseudo slide (13,536 cores) with a variety of irregular grid layouts including missing cores, rotation and stretching. 100% of the cores were gridded correctly.

A Robust Co-Localisation Measurement Utilising Z-Stack Image Intensity Similarities for Biological Studies

Background Co-localisation is a widely used measurement in immunohistochemical analysis to determine if fluorescently labelled biological entities, such as cells, proteins or molecules share a same location. However the measurement of co-localisation is challenging due to the complex nature of such fluorescent images, especially when multiple focal planes are captured. The current state-of-art co-localisation measurements of 3-dimensional (3D) image stacks are biased by noise and cross-overs from non-consecutive planes. Method In this study, we have developed Co-localisation Intensity Coefficients (CICs) and Co-localisation Binary Coefficients (CBCs), which uses rich z-stack data from neighbouring focal planes to identify similarities between image intensities of two and potentially more fluorescently-labelled biological entities. This was developed using z-stack images from murine organotypic slice cultures from central nervous system tissue, and two sets of pseudo-data. A large amount of non-specific cross-over situations are excluded using this method. This proposed method is also proven to be robust in recognising co-localisations even when images are polluted with a range of noises. Results The proposed CBCs and CICs produce robust co-localisation measurements which are easy to interpret, resilient to noise and capable of removing a large amount of false positivity, such as non-specific cross-overs. Performance of this method of measurement is significantly more accurate than existing measurements, as determined statistically using pseudo datasets of known values. This method provides an important and reliable tool for fluorescent 3D neurobiological studies, and will benefit other biological studies which measure fluorescence co-localisation in 3D.

The Rab27A effector MYRIP as a regulator of survival in non-small cell lung cancer cells.

e13537 Background: Personalising therapy for non-small cell lung cancer has been validated as an effective treatment paradigm. Somatic gene alterations confer sensitivity to inhibition of growth survival pathways irrespective of underlying resistance to chemotherapeutic agents, and enables efficient activation of BCL-2 family-dependent pro-apoptotic signalling. In platinum resistant cancers this signalling is blocked, however the intrinsic pathway remains sensitive to exogenous BH3 death signals. METHODS Microarray profiling coupled to focused RNAi screening was used to reveal those resistance genes involved in derepression of proapoptotic BCL-2 family proteins. Analysis of the effect of MYRIP expression on survival was generated from studying 6 NSCLC datasets from Gene Expression Omnibus which were paired with survival time and status information. The toxic effect of MYRIP depletion on NSCLC and non-cancerous lung cells was determined by cell viability and clonogenic assays. Apoptotic induction was examined by caspase and PARP cleavage experiments, and fractionation of mitochondrial proteins. FACS analysis was used to examine effects on cell cycle. RESULTS MYRIP/Slac2c, a gene hitherto associated with vesicle trafficking but not apoptosis, was overexpressed in platinum resistant NSCLC cells. In particular, cisplatin resistant cells expressed a heavier protein isoform of MYRIP which appeared to be associated with the mitochondria. Silencing of MYRIP induced BIM and BAX/BAK-dependent mitochondrial apoptosis which was selective for NSCLC, but not non-cancerous lung cells. In addition, loss of MYRIP induced S-phase arrest. CONCLUSIONS Overexpression of MYRIP is an independent, poor prognostic factor suggesting that targeting these genes may be therapeutically relevant. In summary, MYRIP exhibits a previously unknown survival function associated with suppression of pro-apoptotic BCL-2 family proteins and maintenance of cancer cell proliferation and survival.

Evaluation of machine learning versus Cox regression in identification of factors predicting recurrence following resection of non-small cell lung cancer.

1599 Background: To capture the influence of multiple clinicopathological factors on NSCLC recurrence following surgical resection, machine learning methods (MLMs) can provide clear stratification between subgroups of patients. In this study a clinical signature associated with recurrence-free survival is considered, comparing the performance of MLMs against Cox regression analysis (CRA). Methods: Recurrences 60 months from surgery were filtered, yielding 846 patients with full data comprising 14 clinicopathological factors. Neural Network classification was applied with correlation feature selection and discretisation, using the target values of recurrence and survival status. Ten-fold cross-validation was used, ranked by AUC values. Likewise, Decision Trees were applied, with Kaplan-Meier analysis (KMA) based on time to recurrence (TTR) or last follow-up. Initial results led to the removal of non-recurring patients with < 60 months follow-up time, leaving 477 patients. Results: CRA identified p...

Deterministic Modelling of BAK Activation Kinetics

The molecular mechanism underlying mitochondrial BAK activation during apoptosis remains highly controversial. Two seemingly conflicting models have been proposed. In the activation model, BAK requires so‐called activating BH3 only proteins (aBH3) to initiate its conformation change. In the other, displacement from inhibitory pro‐survival BCL‐2 proteins (PBPs) and monomerization of BAK by PBP restricted dissociator BH3‐only proteins (dBH3) is sufficient. To better understand the kinetic implications of these models and reconcile these conflicting but highly evidence‐based models, we have employed dynamical systems analysis to explore the kinetics underlying BAK activation as a non‐linear reaction system. Our findings accommodate both pure agonism and dissociation as mutually exclusive mechanisms capable of initiating BAK activation. In addition we find our work supports a modelling based approach for predicting resistance to therapeutically relevant small molecules BH3 mimetics.