Evolution: What determines the rate of sequence evolution?

High rates of amino-acid sequence evolution have sometimes been considered to be diagnostic for genes undergoing adaptive change. However, two recent studies have shown that rapid evolution of amino-acid sequence can also be congruent with neutrality.     

What determines the rate of sequence evolution?

High rates of amino-acid sequence evolution have sometimes been considered to be diagnostic for genes undergoing adaptive change. However, two recent studies have shown that rapid evolution of amino-acid sequence can also be congruent with neutrality.     

Survivin study: What is the next wave?

Survivin, a novel member of inhibitor of apoptosis (IAP) protein family, is aberrantly expressed in cancer but undetectable in normal, differentiated adult tissues. Current studies suggest that survivin is implicated in both control of apoptosis and regulation of cell division. However, due to some inconsistent observations on survivin subcellular localization, there is debate about survivin's function in regulating apoptosis, cell division, or both. This review will discuss concepts, experimental methods, and interesting results that unify the different notions about survivin localization and function or point out gaps of knowledge about controversial issues. The author also intends to review various aspects of survivin studies, which were not emphasized or sufficiently discussed in previous reviews on survivin, and update recent developments that may reveal new applications of disease-oriented therapeutics in the coming years.     

Future research in weight bias: What next?

The 2015 Canadian Weight Bias Summit disseminated the newest research advances and brought together 40 experts, stakeholders, and policy makers in various disciplines in health, education, and public policy to identify future research directions in weight bias. In this paper we aim to share the results of the Summit as well as encourage international and interdisciplinary research collaborations in weight bias reduction. Consensus emerged on six research areas that warrant further investigation in weight bias: costs, causes, measurement, qualitative research and lived experience, interventions, and learning from other models of discrimination. These discussions highlighted three key lessons that were informed by the Summit, namely: language matters, the voices of people living with obesity should be incorporated, and interdisciplinary stakeholders should be included.     

Are primary cultures realistic models of prostate cancer?

Primary cultures fill a unique niche among the repertoire of in vitro model systems available to investigate the biology of the normal and malignant human prostate. This review summarizes some of the properties of primary cultures, with special emphasis on two questions: are primary cultures from adenocarcinomas really comprised of cancer rather than normal cells, and do primary cultures faithfully retain characteristics of cells of origin? © 2003 Wiley‐Liss, Inc.     

Fast and reliable prediction of domain–peptide binding affinity using coarse-grained structure models

Domain–peptide recognition and interaction are fundamentally important for eukaryotic signaling and regulatory networks. It is thus essential to quantitatively infer the binding stability and specificity of such interaction based upon large-scale but low-accurate complex structure models which could be readily obtained from sophisticated molecular modeling procedure. In the present study, a new method is described for the fast and reliable prediction of domain–peptide binding affinity with coarse-grained structure models. This method is designed to tolerate strong random noises involved in domain–peptide complex structures and uses statistical modeling approach to eliminate systematic bias associated with a group of investigated samples. As a paradigm, this method was employed to model and predict the binding behavior of various peptides to four evolutionarily unrelated peptide-recognition domains (PRDs), i.e. human amph SH3, human nherf PDZ, yeast syh GYF and yeast bmh 14-3-3, and moreover, we explored the molecular mechanism and biological implication underlying the binding of cognate and noncognate peptide ligands to their domain receptors. It is expected that the newly proposed method could be further used to perform genome-wide inference of domain–peptide binding at three-dimensional structure level.     

MicroRNAs: Oncogenes,tumor suppressors or master regulators of cancer heterogeneity?

The realization that microRNAs are intimately linked to cancer pathogenesis has spawned an explosion of research activity in recent years. Their presence is not merely predictive of tumor origin and behavior, they are causally linked to the emergence and development of cancer by acting as oncogenes or tumor suppressors. The understanding of the functional consequences of altered microRNA expression in cancer is progressing rapidly, even though the prediction of microRNA targets is still a hit and miss process. MicroRNAs may not act primarily by strongly reducing the expression of a few prominent cancer-regulatory genes, but by influencing the properties of the network of which these regulators are a central part. By coordinately regulating many genes, microRNAs are exquisitely suited to act as stabilizers of networks and to prevent extreme variations in phenotype due to intrinsic and extrinsic disturbances. Many advanced tumors show defects in microRNA expression and processing, which could increase phenotypic variability within tumors. This allows small subsets of cells with altered characteristics to emerge, which can have grave consequences as typically a small fraction of tumor cells is responsible for metastasis and treatment resistance, and ultimately treatment failure. Investigating microRNAs from the perspective of master regulators of network stability in cancer calls for new experimental approaches and may help to understand causes of cancer heterogeneity and disease progression.     

Acute myeloid leukaemia: a paradigm for the clonal evolution of cancer?

Acute myeloid leukaemia (AML) is an uncontrolled clonal proliferation of abnormal myeloid progenitor cells in the bone marrow and blood. Advances in cancer genomics have revealed the spectrum of somatic mutations that give rise to human AML and drawn our attention to its molecular evolution and clonal architecture. It is now evident that most AML genomes harbour small numbers of mutations, which are acquired in a stepwise manner. This characteristic, combined with our ability to identify mutations in individual leukaemic cells and our detailed understanding of normal human and murine haematopoiesis, makes AML an excellent model for understanding the principles of cancer evolution. Furthermore, a better understanding of how AML evolves can help us devise strategies to improve the therapy and prognosis of AML patients. Here, we draw from recent advances in genomics, clinical studies and experimental models to describe the current knowledge of the clonal evolution of AML and its implications for the biology and treatment of leukaemias and other cancers.KEY WORDS: Acute myeloid leukaemia, Cancer, Clonal evolution, In vivo models of leukaemia, Mutation     

Genetic biasing through cultural transmission: Do simple Bayesian models of language evolution generalise?

The recent Bayesian approaches to language evolution and change seem to suggest that genetic biases can impact on the characteristics of language, but, at the same time, that its cultural transmission can partially free it from these same genetic constraints. One of the current debates centres on the striking differences between sampling and a posteriori maximising Bayesian learners, with the first converging on the prior bias while the latter allows a certain freedom to language evolution. The present paper shows that this difference disappears if populations more complex than a single teacher and a single learner are considered, with the resulting behaviours more similar to the sampler. This suggests that generalisations based on the language produced by Bayesian agents in such homogeneous single agent chains are not warranted. It is not clear which of the assumptions in such models are responsible, but these findings seem to support the rising concerns on the validity of the “acquisitionist” assumption, whereby the locus of language change and evolution is taken to be the first language acquirers (children) as opposed to the competent language users (the adults).     

Dendritic cell–tumor cell hybrids and immunotherapy: what's next?

Dendritic cells (DC) are professional antigen-presenting cells currently being used as a cellular adjuvant in cancer immunotherapy strategies. Unfortunately, DC-based vaccines have not demonstrated spectacular clinical results. DC loading with tumor antigens and DC differentiation and activation still require optimization. An alternative technique for providing antigens to DC consists of the direct fusion of dendritic cells with tumor cells. These resulting hybrid cells may express both major histocompatibility complex (MHC) class I and II molecules associated with tumor antigens and the appropriate co-stimulatory molecules required for T-cell activation. Initially tested in animal models, this approach has now been evaluated in clinical trials, although with limited success. We summarize and discuss the results from the animal studies and first clinical trials. We also present a new approach to inducing hybrid formation by expression of viral fusogenic membrane glycoproteins.     

Radiomic models for lymph node metastasis prediction in cervical cancer: can we think beyond sentinel lymph node?

Liu and colleagues performed a retrospective study to validate a computed tomography (CT) scan-based radiomic model to detect lymph node metastasis in cervical cancer. The proposed model incorporating the arterial and venous phase CT-scan features represented a non-invasive method exhibiting high sensitivity in the prediction of lymph node metastasis. It is well established that lymph node metastasis is one of the most significant prognostic factors in cervical cancer. For this reason, management of cervical cancer is strictly related to lymph node status, with international guidelines recommending definitive chemo-radiation in case of metastatic lymph node. More and more evidence supports the use of sentinel lymph node in early-stage cervical cancer but its frozen section analysis may result in false negative results; in locally-advanced stages staging para-aortic lymphadenectomy is proposed by many Authors to tailor chemoradiotherapy treatment, with potential intra-and post-operative related complications. The use of a validated radiomic model able to predict lymph node metastases in radiologically normal lymph nodes may represent an essential tool to possibly spare lympadenectomy related morbidity.     

Validation of three-dimensional conduction models using experimental mapping: are we getting closer?

The anisotropic material properties, irregular geometry, and specialized conduction system of the heart all affect the three-dimensional (3D) spread of electrical activation. A limited number of research groups have tried accounting for these features in 3D conduction models to investigate more thoroughly their observations of cardiac electrical activity in 3D experimental preparations. The full potential of these large scale conduction models, however, has not been realized because of a lack of quantitative validation with experiment. Such validation is critical in order to use the models to predict the electrical response of the myocardium to drugs or electrical stimulation. In this paper, a quantitative, experimental validation of paced activation in a 3D conduction model of a 3 cm × 3 cm × 1 cm section of the ventricular wall is presented. Epicardial and intramural pacing stimuli were applied in the center of a 528 channel electrode plaque sutured to the left ventricle in dogs. Unipolar electrograms were recorded at 2 kHz during and after pacing. Fiber directions within the tissue below the electrodes were estimated histologically and from pace-mapping. Simulated epicardial electrograms were computed for surface paced beats using our 3D bidomain model of the mapped tissue volume incorporating the measured fiber directions. Extracellular potentials and isochronal maps resulting from paced activations in both model and experiment were directly compared. Preliminary results demonstrate that our 3D model reproduces qualitatively such key features of the experimental data as electrogram morphologies and epicardial conduction velocities. Though quantitative agreement between model and experiment was only moderate, the validation approach described herein is an essential first step in assessing the predictive capability of present day conduction models.