A general framework for quantifying the effects of DNA repair inhibitors on radiation sensitivity as a function of dose

Purpose. Current methods for quantifying effects of DNA repair modifiers on radiation sensitivity assume a constant effect independent of the radiation dose received. The aim of this study was to develop and evaluate a modelling strategy by which radiation dose dependent effects of DNA repair inhibitors on clonogenic survival might be identified and their significance assessed. Methods. An indicator model that allowed quantification of the Sensitiser Effect on Radiation response as a function of Dose (SERD) was developed. This model was fitted to clonogenic survival data derived from human tumour and rodent fibroblast cell lines irradiated in the presence and absence of chemical inhibitors of poly(ADP-ribose) polymerase (PARP) activity. Results. PARP inhibition affected radiation response in a cell cycle and radiation dose dependent manner, and was also associated with significant radiation-independent effects on clonogenic survival. Application of the SERD method enabled identification of components of the radiation response that were significantly affected by PARP inhibition and indicated the magnitude of the effects on each component. Conclusion. The proposed approach improves on current methods of analysing effects of DNA repair modification on radiation response. Furthermore, it may be generalised to account for other parameters such as proliferation or dose rate to enable its use in the context of fractionated or continuous radiation exposures

A new procedure for determining the genetic basis of a physiological process in a non-model species, illustrated by cold induced angiogenesis in the carp

<p>Abstract</p> <p>Background</p> <p>Physiological processes occur in many species for which there is yet no sequenced genome and for which we would like to identify the genetic basis. For example, some species increase their vascular network to minimise the effects of reduced oxygen diffusion and increased blood viscosity associated with low temperatures. Since many angiogenic and endothelial genes have been discovered in man, functional homolog relationships between carp, zebrafish and human were used to predict the genetic basis of cold-induced angiogenesis in <it>Cyprinus Carpio </it>(carp). In this work, carp sequences were collected and built into contigs. Human-carp functional homolog relationships were derived via zebrafish using a new Conditional Stepped Reciprocal Best Hit (CSRBH) protocol. Data sources including publications, Gene Ontology and cDNA libraries were then used to predict the identity of known or potential angiogenic genes. Finally, re-analyses of cold carp microarray data identified carp genes up-regulated in response to low temperatures in heart and muscle.</p> <p>Results</p> <p>The CSRBH approach outperformed all other methods and attained 8,726 carp to human functional homolog relationships for 16,650 contiguous sequences. This represented 3,762 non-redundant genes and 908 of them were predicted to have a role in angiogenesis. The total number of up-regulated differentially expressed genes was 698 and 171 of them were putatively angiogenic. Of these, 5 genes representing the functional homologs NCL, RHOA, MMP9, GRN and MAPK1 are angiogenesis-related genes expressed in response to low temperature.</p> <p>Conclusion</p> <p>We show that CSRBH functional homologs relationships and re-analyses of gene expression data can be combined in a non-model species to predict genes of biological interest before a genome sequence is fully available. Programs to run these analyses locally are available from <url>http://www.cbrg.ox.ac.uk/~jherbert/</url>.</p

MAGNETO: cell type marker panel generator from single-cell transcriptomic data

Single-cell RNA sequencing experiments produce data useful to identify different cell types, including uncharacterized and rare ones. This enables us to study the specific functional roles of these cells in different microenvironments and contexts. After identifying a (novel) cell type of interest, it is essential to build succinct marker panels, composed of a few genes referring to cell surface proteins and clusters of differentiation molecules, able to discriminate the desired cells from the other cell populations. In this work, we propose a fully-automatic framework called MAGNETO, which can help construct optimal marker panels starting from a single-cell gene expression matrix and a cell type identity for each cell. MAGNETO builds effective marker panels solving a tailored bi-objective optimization problem, where the first objective regards the identification of the genes able to isolate a specific cell type, while the second conflicting objective concerns the minimization of the total number of genes included in the panel. Our results on three public datasets show that MAGNETO can identify marker panels that identify the cell populations of interest better than state-of-the-art approaches. Finally, by fine-tuning MAGNETO, our results demonstrate that it is possible to obtain marker panels with different specificity levels

GeneFEAST: the pivotal, gene-centric step in functional enrichment analysis interpretation

Summary: GeneFEAST, implemented in Python, is a gene-centric functional enrichment analysis summarisation and visualisation tool that can be applied to large functional enrichment analysis (FEA) results arising from upstream FEA pipelines. It produces a systematic, navigable HTML report, making it easy to identify sets of genes putatively driving multiple enrichments and to explore gene-level quantitative data first used to identify input genes. Further, GeneFEAST can compare FEA results from multiple studies, making it possible, for example, to highlight patterns of gene expression amongst genes commonly differentially expressed in two sets of conditions, and giving rise to shared enrichments under those conditions. GeneFEAST offers a novel, effective way to address the complexities of linking up many overlapping FEA results to their underlying genes and data, advancing gene-centric hypotheses, and providing pivotal information for downstream validation experiments. Availability: GeneFEAST is available at https://github.com/avigailtaylor/GeneFEAST Contact: [email protected]: Main text: 3 pages, 1 figure. Supplementary Information: 16 pages, 3 figures, 2 tables, 4 boxe

A structural characterisation of the mitogen-activated protein kinase network in cancer

Gene regulatory networks represent collections of regulators that interact with each other and with other molecules to govern gene expression. Biological signalling networks model how signals are transmitted and how activities are coordinated in the cell. The study of the structure of such networks in complex diseases such as cancer can provide insights into how they function, and consequently, suggest suitable treatment approaches. Here, we explored such topological characteristics in the example of a mitogen-activated protein kinase (MAPK) signalling network derived from published studies in cancer. We employed well-established techniques to conduct network analyses, and collected information on gene function as obtained from large-scale public databases. This allowed us to map topological and functional relationships, and build hypotheses on this network’s functional consequences. In particular, we find that the topology of this MAPK network is highly non-random, modular and robust. Moreover, analysis of the network’s structure indicates the presence of organisational features of cancer hallmarks, expressed in an asymmetrical manner across communities of the network. Finally, our results indicate that the organisation of this network renders it problematic to use treatment approaches that focus on a single target. Our analysis suggests that multi-target attacks in a well-orchestrated manner are required to alter how the network functions. Overall, we propose that complex network analyses combined with pharmacological insights will help inform on future treatment strategies, exploiting structural vulnerabilities of signalling and regulatory networks in canc

Overexpression of POLQ Confers a Poor Prognosis in Early Breast Cancer Patients

Depletion of POLQ (DNA polymerase theta) has recently been shown to render tumour cells more sensitive to radiotherapy whilst having little or no effect on normal tissues. This finding led us to investigate whether tumours that overexpress POLQ are associated with an adverse outcome. We therefore correlated the clinical outcomes of two retrospective series of patients with early breast cancer with the expression levels of POLQ, as determined by microarray gene expression analysis. We found that a significant number of tumours overexpressed POLQ and that overexpression was correlated with ER negative disease (p=0.047) and high tumour grade (p=0.004), both of which are associated with poor clinical outcomes. POLQ overexpression was associated with poor relapse free survival rates on both univariate (HR 5.80; 95% CI, 2.220 to 15.159; p<0.001) and multivariate analysis (HR 8.086; 95% CI 2.340 to 27.948 p=0.001). Analysis of other published clinical series confirmed that POLQ overexpression is associated with adverse clinical outcomes. The poor prognosis associated with POLQ is independent of other clinical or pathological features. The mechanism that causes this adverse outcome remains to be elucidated but may in part arise from resistance to adjuvant treatment. These findings, combined with the limited normal tissue expression of POLQ, make it a very appealing target for possible clinical exploitation

Genomic alterations underlie a pan-cancer metabolic shift associated with tumour hypoxia

Altered metabolism is a hallmark of cancer. However, the role of genomic changes in metabolic genes driving the tumour metabolic shift remains to be elucidated. Here, we have investigated the genomic and transcriptomic changes underlying this shift across ten different cancer types.A systematic pan-cancer analysis of 6538 tumour/normal samples covering ten major cancer types identified a core metabolic signature of 44 genes that exhibit high frequency somatic copy number gains/amplifications (>20 % cases) associated with increased mRNA expression (ρ > 0.3, q < 10(-3)). Prognostic classifiers using these genes were confirmed in independent datasets for breast and kidney cancers. Interestingly, this signature is strongly associated with hypoxia, with nine out of ten cancer types showing increased expression and five out of ten cancer types showing increased gain/amplification of these genes in hypoxic tumours (P ≤ 0.01). Further validation in breast and colorectal cancer cell lines highlighted squalene epoxidase, an oxygen-requiring enzyme in cholesterol biosynthesis, as a driver of dysregulated metabolism and a key player in maintaining cell survival under hypoxia.This study reveals somatic genomic alterations underlying a pan-cancer metabolic shift and suggests genomic adaptation of these genes as a survival mechanism in hypoxic tumours

Gene expression analysis in human breast cancer associated blood vessels.

Angiogenesis is essential for solid tumour growth, whilst the molecular profiles of tumour blood vessels have been reported to be different between cancer types. Although presently available anti-angiogenic strategies are providing some promise for the treatment of some cancers it is perhaps not surprisingly that, none of the anti-angiogenic agents available work on all tumours. Thus, the discovery of novel anti-angiogenic targets, relevant to individual cancer types, is required. Using Affymetrix microarray analysis of laser-captured, CD31-positive blood vessels we have identified 63 genes that are upregulated significantly (5-72 fold) in angiogenic blood vessels associated with human invasive ductal carcinoma (IDC) of the breast as compared with blood vessels in normal human breast. We tested the angiogenic capacity of a subset of these genes. Genes were selected based on either their known cellular functions, their enriched expression in endothelial cells and/or their sensitivity to anti-VEGF treatment; all features implicating their involvement in angiogenesis. For example, RRM2, a ribonucleotide reductase involved in DNA synthesis, was upregulated 32-fold in IDC-associated blood vessels; ATF1, a nuclear activating transcription factor involved in cellular growth and survival was upregulated 23-fold in IDC-associated blood vessels and HEX-B, a hexosaminidase involved in the breakdown of GM2 gangliosides, was upregulated 8-fold in IDC-associated blood vessels. Furthermore, in silico analysis confirmed that AFT1 and HEX-B also were enriched in endothelial cells when compared with non-endothelial cells. None of these genes have been reported previously to be involved in neovascularisation. However, our data establish that siRNA depletion of Rrm2, Atf1 or Hex-B had significant anti-angiogenic effects in VEGF-stimulated ex vivo mouse aortic ring assays. Overall, our results provide proof-of-principle that our approach can identify a cohort of potentially novel anti-angiogenic targets that are likley to be, but not exclusivley, relevant to breast cancer

Disruption of hypoxia-inducible fatty acid binding protein 7 induces beige fat-like differentiation and thermogenesis in breast cancer cells

Background Humans produce heat through non-shivering thermogenesis, a metabolic process that occurs in inducible beige adipocytes expressing uncoupling protein 1 (UCP1). UCP1 dissipates the proton gradient of the mitochondrial inner membrane and converts that energy into heat. It is unclear whether cancer cells can exhibit autonomous thermogenesis. Previously, we found that the knockdown of hypoxia-inducible fatty acid binding protein 7 (FABP7) increased reactive oxygen species (ROS) in breast cancer cells. ROS are known to induce beige adipocyte differentiation. Methods We investigated the association of tumor hypoxia, FABP7, and UCP1 across breast cancer patients using METABRIC and TCGA data sets. Furthermore, using a breast cancer cell line, HCC1806, we tested the effect of FABP7 knockdown on cellular physiology including thermogenesis. Results We found a strong mutual exclusivity of FABP7 and UCP1 expression both in METABRIC and in TCGA, indicating major metabolic phenotypic differences. FABP7 was preferentially distributed in poorly differentiated-, estrogen receptor (ER) negative tumors. In contrast, UCP1 was highly expressed in normal ducts and well-differentiated-, ER positive-, less hypoxic tumors. In the cell line-based experiments, UCP1 and its transcriptional regulators were upregulated upon FABP7 knockdown. UCP1 was induced in about 20% of cancer cells, and the effect was increased further in hypoxia. UCP1 depolarized mitochondrial membranes at the site of expression. UCP1 induction was associated with the increase in proton leak, glycolysis, and maximal respiration, mimicking the typical energy profile of beige adipocytes. Most importantly, UCP1 induction elevated cancer cell temperature associated with increased vulnerability to hypoxia and gamma-irradiation. Conclusions We demonstrated that breast cancer cells can undergo thermogenesis through UCP1 induction. Disrupting FABP7-mediated fatty acid metabolism can unlock UCP1-mediated thermogenesis, potentially making it possible to develop therapies to target thermogenesis. Further study would be warranted to investigate the effect of rise in temperature of cancer cells on patients' outcomes and the relationship to other metabolic pathways

Hypoxia-induced SETX links replication stress with the unfolded protein response.

Tumour hypoxia is associated with poor patient prognosis and therapy resistance. A unique transcriptional response is initiated by hypoxia which includes the rapid activation of numerous transcription factors in a background of reduced global transcription. Here, we show that the biological response to hypoxia includes the accumulation of R-loops and the induction of the RNA/DNA helicase SETX. In the absence of hypoxia-induced SETX, R-loop levels increase, DNA damage accumulates, and DNA replication rates decrease. Therefore, suggesting that, SETX plays a role in protecting cells from DNA damage induced during transcription in hypoxia. Importantly, we propose that the mechanism of SETX induction in hypoxia is reliant on the PERK/ATF4 arm of the unfolded protein response. These data not only highlight the unique cellular response to hypoxia, which includes both a replication stress-dependent DNA damage response and an unfolded protein response but uncover a novel link between these two distinct pathways