On dynamic network entropy in cancer

The cellular phenotype is described by a complex network of molecular interactions. Elucidating network properties that distinguish disease from the healthy cellular state is therefore of critical importance for gaining systems-level insights into disease mechanisms and ultimately for developing improved therapies. By integrating gene expression data with a protein interaction network to induce a stochastic dynamics on the network, we here demonstrate that cancer cells are characterised by an increase in the dynamic network entropy, compared to cells of normal physiology. Using a fundamental relation between the macroscopic resilience of a dynamical system and the uncertainty (entropy) in the underlying microscopic processes, we argue that cancer cells will be more robust to random gene perturbations. In addition, we formally demonstrate that gene expression differences between normal and cancer tissue are anticorrelated with local dynamic entropy changes, thus providing a systemic link between gene expression changes at the nodes and their local network dynamics. In particular, we also find that genes which drive cell-proliferation in cancer cells and which often encode oncogenes are associated with reductions in the dynamic network entropy. In summary, our results support the view that the observed increased robustness of cancer cells to perturbation and therapy may be due to an increase in the dynamic network entropy that allows cells to adapt to the new cellular stresses. Conversely, genes that exhibit local flux entropy decreases in cancer may render cancer cells more susceptible to targeted intervention and may therefore represent promising drug targets.Comment: 10 pages, 3 figures, 4 tables. Submitte

Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology

Stain variation is a phenomenon observed when distinct pathology laboratories stain tissue slides that exhibit similar but not identical color appearance. Due to this color shift between laboratories, convolutional neural networks (CNNs) trained with images from one lab often underperform on unseen images from the other lab. Several techniques have been proposed to reduce the generalization error, mainly grouped into two categories: stain color augmentation and stain color normalization. The former simulates a wide variety of realistic stain variations during training, producing stain-invariant CNNs. The latter aims to match training and test color distributions in order to reduce stain variation. For the first time, we compared some of these techniques and quantified their effect on CNN classification performance using a heterogeneous dataset of hematoxylin and eosin histopathology images from 4 organs and 9 pathology laboratories. Additionally, we propose a novel unsupervised method to perform stain color normalization using a neural network. Based on our experimental results, we provide practical guidelines on how to use stain color augmentation and stain color normalization in future computational pathology applications.Comment: Accepted in the Medical Image Analysis journa

Vitamin D-VDR signaling inhibits Wnt/beta-catenin-mediated melanoma progression and promotes anti-tumor immunity

1α,25-dihydroxyvitamin D3 signals via the Vitamin D Receptor (VDR). Higher serum vitamin D is associated with thinner primary melanoma and better outcome, although a causal mechanism has not been established. As melanoma patients commonly avoid sun exposure, and consequent vitamin D deficiency might worsen outcomes, we interrogated 703 primary melanoma transcriptomes to understand the role of vitamin D-VDR signalling and replicated the findings in TCGA metastases. VDR expression was independently protective for melanoma death in both primary and metastatic disease. High tumor VDR expression was associated with upregulation of pathways mediating anti-tumor immunity and correspondingly with higher imputed immune cell scores and histologically detected tumor infiltrating lymphocytes (TILs). High VDR expressing tumors had downregulation of proliferative pathways, notably Wnt/beta-catenin signaling. Deleterious low VDR levels resulted from promoter methylation and gene deletion in metastases. Vitamin D deficiency (< 25 nmol/l ~ 10 ng/ml) shortened survival in primary melanoma in a VDR-dependent manner. In vitro functional validation studies showed that elevated vitamin D-VDR signaling inhibited Wnt/beta-catenin signaling genes. Murine melanoma cells overexpressing VDR produced fewer pulmonary metastases than controls in tail vein metastasis assays. In summary, vitamin D-VDR signaling contributes to controlling pro-proliferative/immunosuppresive Wnt/beta-catenin signaling in melanoma and this is associated with less metastatic disease and stronger host immune responses. This is evidence of the causal relationship between vitamin D-VDR signaling and melanoma survival which should be explored as a therapeutic target in primary resistance to checkpoint blockade

Independent component analysis (ICA) applied to ultrasound image processing and tissue characterization

As a complicated ubiquitous phenomenon encountered in ultrasound imaging, speckle can be treated as either annoying noise that needs to be reduced or the source from which diagnostic information can be extracted to reveal the underlying properties of tissue. In this study, the application of Independent Component Analysis (ICA), a relatively new statistical signal processing tool appeared in recent years, to both the speckle texture analysis and despeckling problems of B-mode ultrasound images was investigated. It is believed that higher order statistics may provide extra information about the speckle texture beyond the information provided by first and second order statistics only. However, the higher order statistics of speckle texture is still not clearly understood and very difficult to model analytically. Any direct dealing with high order statistics is computationally forbidding. On the one hand, many conventional ultrasound speckle texture analysis algorithms use only first or second order statistics. On the other hand, many multichannel filtering approaches use pre-defined analytical filters which are not adaptive to the data. In this study, an ICA-based multichannel filtering texture analysis algorithm, which considers both higher order statistics and data adaptation, was proposed and tested on the numerically simulated homogeneous speckle textures. The ICA filters were learned directly from the training images. Histogram regularization was conducted to make the speckle images quasi-stationary in the wide sense so as to be adaptive to an ICA algorithm. Both Principal Component Analysis (PCA) and a greedy algorithm were used to reduce the dimension of feature space. Finally, Support Vector Machines (SVM) with Radial Basis Function (RBF) kernel were chosen as the classifier for achieving best classification accuracy. Several representative conventional methods, including both low and high order statistics based methods, and both filtering and non-filtering methods, have been chosen for comparison study. The numerical experiments have shown that the proposed ICA-based algorithm in many cases outperforms other algorithms for comparison. Two-component texture segmentation experiments were conducted and the proposed algorithm showed strong capability of segmenting two visually very similar yet different texture regions with rather fuzzy boundaries and almost the same mean and variance. Through simulating speckle with first order statistics approaching gradually to the Rayleigh model from different non-Rayleigh models, the experiments to some extent reveal how the behavior of higher order statistics changes with the underlying property of tissues. It has been demonstrated that when the speckle approaches the Rayleigh model, both the second and higher order statistics lose the texture differentiation capability. However, when the speckles tend to some non-Rayleigh models, methods based on higher order statistics show strong advantage over those solely based on first or second order statistics. The proposed algorithm may potentially find clinical application in the early detection of soft tissue disease, and also be helpful for better understanding ultrasound speckle phenomenon in the perspective of higher order statistics. For the despeckling problem, an algorithm was proposed which adapted the ICA Sparse Code Shrinkage (ICA-SCS) method for the ultrasound B-mode image despeckling problem by applying an appropriate preprocessing step proposed by other researchers. The preprocessing step makes the speckle noise much closer to the real white Gaussian noise (WGN) hence more amenable to a denoising algorithm such as ICS-SCS that has been strictly designed for additive WGN. A discussion is given on how to obtain the noise-free training image samples in various ways. The experimental results have shown that the proposed method outperforms several classical methods chosen for comparison, including first or second order statistics based methods (such as Wiener filter) and multichannel filtering methods (such as wavelet shrinkage), in the capability of both speckle reduction and edge preservation

Phenology and the Response to Disturbance of the Fucoid, Stephanocystis osmundacea

Nearshore rocky ecosystems along exposed shorelines experience frequent disturbances due to turbulent swells and wave action. These disturbances directly affect subtidal algal communities that provide biogenic habitat along the coast. This habitat shapes faunal communities by providing refuge through structural complexity. In central California, kelps are the most notable providers of biogenic habitat, but, seasonally, a prolific fucoid, Stephanocystis osmundacea, adds a considerable amount of habitat into the environment. While diminutive and bushy during the winter, this alga produces canopy-forming reproductive fronds during the spring and summer months that add to the biogenic refuge. The purpose behind this study was to understand how the frequency and timing of disturbances affect the physiology of Stephanocystis. This was accomplished by performing manipulations on the reproductive and vegetative tissues of the alga, including: full reproductive removal (-R), haphazard vegetative blade damage (-V), no removal (C), and damage of both reproductive and vegetative structures (-All). By using measurements of changes in total length (cm) as a proxy for biomass we provided an in situ assessment of the response to disturbance by the alga. This external growth response was coupled with stable isotope analysis of changes in carbon and nitrogen isotopes as a bioindication of fitness. Removal of reproductive fronds during spring elicited a dormancy response, while damage to the vegetative tissue reduced growth, possibly by limiting overall photosynthetic capacity. These results suggest that spring frond growth is important to reproductive fitness and removal can stimulate a life history trade-off between reproduction and survival. Winter manipulations elicited no response due to the dormancy period of this species. Enrichment values for ∂13C and ∂15N were consistent with reported values for growth in other brown algal species but, because of the timing of extraction, the internal chemistry of the individuals rebounded and the ability to detect a response was lost. Both the natural and manipulated populations had similar ∂13C and ∂15N values when separated by tissue and time of year, which indicates that while the alga may be impacted from an external perspective, it will recover internally and stay as a viable part of the reproductive population. Understanding how these seaweeds respond to biomass loss provides a better perspective of disturbance effects on this species and the ecosystem it helps support

Genomic evaluation of multiparametric magnetic resonance imaging-visible and -nonvisible lesions in clinically localised prostate cancer

Background: The prostate cancer (PCa) diagnostic pathway is undergoing a radical change with the introduction of multiparametric magnetic resonance imaging (mpMRI), genomic testing, and different prostate biopsy techniques. It has been proposed that these tests should be used in a sequential manner to optimise risk stratification. Objective: To characterise the genomic, epigenomic, and transcriptomic features of mpMRI-visible and -nonvisible PCa in clinically localised disease. Design, setting, and participants: Multicore analysis of fresh prostate tissue sampled immediately after radical prostatectomy was performed for intermediate- to high-risk PCa. Intervention: Low-pass whole-genome, exome, methylation, and transcriptome profiling of patient tissue cores taken from microscopically benign and cancerous areas in the same prostate. Circulating free and germline DNA was assessed from the blood of five patients. Outcome measurement and statistical analysis: Correlations between preoperative mpMRI and genomic characteristics of tumour and benign prostate samples were assessed. Gene profiles for individual tumour cores were correlated with existing genomic classifiers currently used for prognostication. Results and limitations: A total of 43 prostate cores (22 tumour and 21 benign) were profiled from six whole prostate glands. Of the 22 tumour cores, 16 were tumours visible and six were tumours nonvisible on mpMRI. Intratumour genomic, epigenomic, and transcriptomic heterogeneity was found within mpMRI-visible lesions. This could potentially lead to misclassification of patients using signatures based on copy number or RNA expression. Moreover, three of the six cores obtained from mpMRI-nonvisible tumours harboured one or more genetic alterations commonly observed in metastatic castration-resistant PCa. No circulating free DNA alterations were found. Limitations include the small cohort size and lack of follow-up. Conclusions: Our study supports the continued use of systematic prostate sampling in addition to mpMRI, as avoidance of systematic biopsies in patients with negative mpMRI may mean that clinically significant tumours harbouring genetic alterations commonly seen in metastatic PCa are missed. Furthermore, there is inconsistency in individual genomics when genomic classifiers are applied. Patient summary: Our study shows that tumour heterogeneity within prostate tumours visible on multiparametric magnetic resonance imaging (mpMRI) can lead to misclassification of patients if only one core is used for genomic analysis. In addition, some cancers that were missed by mpMRI had genomic aberrations that are commonly seen in advanced metastatic prostate cancer. Avoiding biopsies in mpMRI-negative cases may mean that such potentially lethal cancers are missed

Cancer/testis antigens and gametogenesis: a review and "brain-storming" session

Genes expressed both in normal testis and in malignancies (Cancer/ Testis associated genes – CTA) have become the most extensively studied antigen group in the field of tumour immunology. Despite this, many fundamentally important questions remain unanswered: what is the connection between germ-cell specific genes and tumours? Is the expression of these genes yet another proof for the importance of genome destabilisation in the process of tumorigenesis?, or maybe activation of these genes is not quite random but instead related to some programme giving tumours a survival advantage? This review collates most of the recent information available about CTAs expression, function, and regulation. The data suggests a programme related to ontogenesis, mostly to gametogenesis. In the "brain-storming" part, facts in conflict with the hypothesis of random CTA gene activation are discussed. We propose a programme borrowed from organisms phylogenetically much older than humans, which existed before the differentiation of sexes. It is a programme that has served as a life cycle with prominent ploidy changes, and from which, as we know, the germ-cell ploidy cycle – meiosis – has evolved. Further work may show whether this hypothesis can lead to a novel anti-tumour strategy

Validation of Reference Genes for Robust qRT-PCR Gene Expression Analysis in the Rice Blast Fungus Magnaporthe oryzae

This is the final version of the article. Available from Public Library of Science via the DOI in this record.The rice blast fungus causes significant annual harvest losses. It also serves as a genetically-tractable model to study fungal ingress. Whilst pathogenicity determinants have been unmasked and changes in global gene expression described, we know little about Magnaporthe oryzae cell wall remodelling. Our interests, in wall remodelling genes expressed during infection, vegetative growth and under exogenous wall stress, demand robust choice of reference genes for quantitative Real Time-PCR (qRT-PCR) data normalisation. We describe the expression stability of nine candidate reference genes profiled by qRT-PCR with cDNAs derived during asexual germling development, from sexual stage perithecia and from vegetative mycelium grown under various exogenous stressors. Our Minimum Information for Publication of qRT-PCR Experiments (MIQE) compliant analysis reveals a set of robust reference genes used to track changes in the expression of the cell wall remodelling gene MGG_Crh2 (MGG_00592). We ranked nine candidate reference genes by their expression stability (M) and report the best gene combination needed for reliable gene expression normalisation, when assayed in three tissue groups (Infective, Vegetative, and Global) frequently used in M. oryzae expression studies. We found that MGG_Actin (MGG_03982) and the 40S 27a ribosomal subunit MGG_40s (MGG_02872) proved to be robust reference genes for the Infection group and MGG_40s and MGG_Ef1 (Elongation Factor1-α) for both Vegetative and Global groups. Using the above validated reference genes, M. oryzae MGG_Crh2 expression was found to be significantly (p<0.05) elevated three-fold during vegetative growth as compared with dormant spores and two fold higher under cell wall stress (Congo Red) compared to growth under optimal conditions. We recommend the combinatorial use of two reference genes, belonging to the cytoskeleton and ribosomal synthesis functional groups, MGG_Actin, MGG_40s, MGG_S8 (Ribosomal subunit 40S S8) or MGG_Ef1, which demonstrated low M values across heterogeneous tissues. By contrast, metabolic pathway genes MGG_Fad (FAD binding domain-containing protein) and MGG_Gapdh (Glyceraldehyde-3-phosphate dehydrogenase) performed poorly, due to their lack of expression stability across samples.We acknowledge funding from Khazanah Foundation in support of SCO, BBSRC grant BB/J008923/1 awarded to SG and we thank Eleanor Jaskowska for her assistance in tissue preparation. Neither funder played a role in study design, data collection, analysis, decision to publish or manuscript preparation