A molecular signature for the "master" heart cell

The vertebrate heart comprises a variety of cell types, the majority of which are cardiomyocytes, smooth muscle and endothelial cells. Their origin is still an intriguing research topic and the question is whether these cells derive from a common or from multiple distinct progenitor cell(s). Three recent publications not only suggest the existence of a single progenitor cell that can give rise to cardiovascular lineages but additionally uncovered, at least in part, the molecular identity of such a multipotent precursor cell. These findings constitute major progress in the quest for stem-cell therapies for cardiac diseases.     

肾移植术后肾功能延迟恢复的发病分子机制与诊断标志物研究

移植肾功能延迟恢复(DGF)为肾移植患者常见并发症之一,越来越多的研究开始关注肾移植患者术后DGF发生的新病理生理学机制以及潜在的诊断标志物。本研究对GEO数据库中肾脏移植手术患者的基因表达谱数据进行分析,通过差异表达基因分析发现了多个表达异常的转录因子和免疫相关基因,通过基因编码蛋白之间的相互作用网络分析进一步挖掘了疾病进展过程中的核心调控基因。通过结合加权基因共表达网络分析(WGCNA)和机器学习构建了肾移植术后DGF的预测模型。模型XGBoost的准确率能够达到82.4%,其受试者工作特征曲线下面积(AUC)为0.86,马修斯相关系数(MCC)为0.652,灵敏度(Sensitivity)及特异度(Specificity)则分别为0.789和0.867。对这些获得最优预测效能的特征基因进行检索发现,这些高区分度基因与肾功能密切相关。最后通过比对CMap数据库发现了多个潜在可用于疾病治疗的小分子化合物。本研究对肾移植术后DGF的病理生理学机制进行了多角度探索,为相关疾病的诊断和治疗提供了可靠的理论和实验依据。     

A congruent molecular signature of vicariance across multiple plant lineages

Explaining disjunct distributions, or why closely related organisms are often separated by apparently severe barriers such as oceans or deserts, is a great challenge for historical biogeography. Competing explanations are long-distance dispersal across a barrier, and vicariance, in which disjunct taxa are descended from an ancestral population that was split by formation of the barrier. Vicariance explanations are testable by their prediction that near-simultaneous speciation should have occurred across multiple lineages of organisms between the disjunct areas because the origin of a barrier would potentially disrupt gene flow within multiple species. To date, there have been few studies providing evidence for multiple synchronous ancient divergences across a barrier whose origin coincides with the timing of the speciation events. Here, we use relaxed molecular-clock dating to investigate the timing of south-western (SW) versus south-eastern (SE) divergences in 23 pairs of plant lineages in southern Australia. Sixteen of the divergences correlate with the origin, 13-14 million years (Myr) ago, of the arid treeless Nullarbor Plain. The Nullarbor Plain currently forms a substantial barrier to SW-SE migration but during the last 45Myr this region has experienced multiple episodes of marine inundation and subaerial exposure. Thus, there have been multiple events that could have caused either isolation and speciation, or secondary contact, among the taxa of southern Australia. The strong molecular signal of coincident speciation in many diverse lineages during a short period provides the best evidence to date linking synchronous speciation to an ancient vicariance event.     

A 6-gene signature identifies four molecular subgroups of neuroblastoma

Background  

There are currently three postulated genomic subtypes of the childhood tumour neuroblastoma (NB); Type 1, Type 2A, and Type 2B. The most aggressive forms of NB are characterized by amplification of the oncogene MYCN (MNA) and low expression of the favourable marker NTRK1. Recently, mutations or high expression of the familial predisposition gene Anaplastic Lymphoma Kinase (ALK) was associated to unfavourable biology of sporadic NB. Also, various other genes have been linked to NB pathogenesis.     

Subcellular tissue proteomics of hepatocellular carcinoma for molecular signature discovery

Hepatocellular carcinoma (HCC) is one of the leading causes of mortality from solid organ malignancy worldwide. Because of the complexity of proteins within liver cells and tissues, the discovery of therapeutic targets of HCC has been difficult. To investigate strategies for decreasing the complexity of tissue samples for detecting meaningful protein mediators of HCC, we employed subcellular fractionation combined with 1D-gel electrophoresis and liquid chromatography-tandem mass spectrometry analysis. Moreover, we utilized a statistical method, namely, the Power Law Global Error Model (PLGEM), to distinguish differentially expressed proteins in a duplicate proteomic data set. Mass spectrometric analysis identified 3045 proteins in nontumor and HCC from cytosolic, membrane, nuclear, and cytoskeletal fractions. The final lists of highly differentiated proteins from the targeted fractions were searched for potentially translocated proteins in HCC from soluble compartments to the nuclear or cytoskeletal compartments. This analysis refined our targets of interest to include 21 potential targets of HCC from these fractions. Furthermore, we validated the potential molecular targets of HCC, MATR3, LETM1, ILF2, and IQGAP2 by Western blotting, immunohistochemisty, and immunofluorescent microscopy. Here we demonstrate an efficient strategy of subcellular tissue proteomics toward molecular target discovery of one of the most complicated human disease, HCC.     

Cdc42 and Tks5: A minimal and universal molecular signature for functional invadosomes

Invadosomes are actin-based structures involved in extracellular-matrix degradation. Invadosomes, either known as podosomes or invadopodia, are found in an increasing number of cell types. Moreover, their overall organization and molecular composition may vary from one cell type to the other. Some are constitutive such as podosomes in hematopoietic cells whereas others are inducible. However, they share the same feature, their ability to interact and to degrade the extracellular matrix. Based on the literature and our own experiments, the aim of this study was to establish a minimal molecular definition of active invadosomes. We first highlighted that Cdc42 is the key RhoGTPase involved in invadosome formation in all described models. Using different cellular models, such as NIH-3T3, HeLa, and endothelial cells, we demonstrated that overexpression of an active form of Cdc42 is sufficient to form invadosome actin cores. Therefore, active Cdc42 must be considered not only as an inducer of filopodia, but also as an inducer of invadosomes. Depending on the expression level of Tks5, these Cdc42-dependent actin cores were endowed or not with a proteolytic activity. In fact, Tks5 overexpression rescued this activity in Tks5 low expressing cells. We thus described the adaptor protein Tks5 as a major actor of the invadosome degradation function. Surprisingly, we found that Src kinases are not always required for invadosome formation and function. These data suggest that even if Src family members are the principal kinases involved in the majority of invadosomes, it cannot be considered as a common element for all invadosome structures. We thus define a minimal and universal molecular signature of invadosome that includes Cdc42 activity and Tks5 presence in order to drive the actin machinery and the proteolytic activity of these invasive structures.     

The molecular phylogenetic signature of clades in decline

Molecular phylogenies have been used to study the diversification of many clades. However, current methods for inferring diversification dynamics from molecular phylogenies ignore the possibility that clades may be decreasing in diversity, despite the fact that the fossil record shows this to be the case for many groups. Here we investigate the molecular phylogenetic signature of decreasing diversity using the most widely used statistic for inferring diversity dynamics from molecular phylogenies, the γ statistic. We show that if a clade is in decline its molecular phylogeny may show evidence of the decrease in the diversification rate that occurred between its diversification and decline phases. The ability to detect the change in diversification rate depends largely on the ratio of the speciation rates of the diversification and decline phases, the higher the ratio the stronger the signal of the change in diversification rate. Consequently, molecular phylogenies of clades in relative rapid decline do not carry a signature of their decreasing diversification. Further, the signal of the change in diversification rate, if present, declines as the diversity drop. Unfortunately, the molecular signature of clades in decline is the same as the signature produced by diversity dependent diversification. Given this similarity, and the inability of current methods to detect declining diversity, it is likely that some of the extant clades that show a decrease in diversification rate, currently interpreted as evidence for diversity dependent diversification, are in fact in decline. Unless methods can be developed that can discriminate between the different modes of diversification, specifically diversity dependent diversification and declining diversity, we will need the fossil record, or data from some other source, to distinguish between these very different diversity trajectories.     

The prognostic value of the furosemide stress test in predicting delayed graft function following deceased donor kidney transplantation

Objectives and methods: The Furosemide Stress Test (FST) is a novel dynamic assessment of tubular function that has been shown in preliminary studies to predict patients who will progress to advanced stage acute kidney injury, including those who receive renal replacement therapy (RRT). The aim of this study is to investigate if the urinary response to a single intraoperative dose of intravenous furosemide predicts delayed graft function (DGF) in patients undergoing deceased donor kidney transplant.

Results: On an adjusted multiple logistic regression, a single 100?mg dose of intraoperative furosemide after the anastomosis of the renal vessels (FST) predicted the need for RRT at 2 and 6?h post kidney transplantation (KT). Recipient urinary output was measured at 2 and 6?h post furosemide administration. In receiver-operating characteristic (ROC) analysis, the FST predicted DGF with an area-under-the curve of 0.85 at an optimal urinary output cut-off of <600 mls at 6?h with a sensitivity of and a specificity of 83% and 74%, respectively.

Conclusions: The FST is a predictor of DGF post kidney transplant and has the potential to identify patients requiring RRT early after KT.     

A novel epithelial-mesenchymal transition molecular signature predicts the oncological outcomes in colorectal cancer

Epithelial-mesenchymal transition (EMT), a biological process involving the transformation of epithelial cells into mesenchymal cells, promotes tumour initiation and metastasis. The aim of this study was to construct an EMT molecular signature for predicting colorectal cancer (CRC) prognosis and evaluate the efficacy of the model. The risk scoring system, constructed by log-rank test and multivariate Cox regression analysis according to EMT-related gene expression in CRC patients from TCGA database, demonstrated the highest correlation with prognosis compared with other parameters in CRC patients. The risk scores were significantly correlated with more lymph node metastasis, distal metastasis and advanced clinical stage of CRC. The model was further successfully validated in two independent external cohorts from GEO database. Furthermore, we developed a nomogram to integrate the EMT signature with the pathological stage of CRC, which was found to perform well in predicting the overall survival. Additionally, this risk scoring model was found to be associated with immune cell infiltration, implying a potential role of EMT involved in immunity regulation in tumour microenvironment. Taken together, our novel EMT molecular model may be useful in identifying high-risk patients who need an intensive follow-up and more aggressive therapy, finally contributing to more precise individualized therapeutic strategies.     

Identification of a 5-protein biomarker molecular signature for predicting Alzheimer's disease

Background

Alzheimer''s disease (AD) is a progressive brain disease with a huge cost to human lives. The impact of the disease is also a growing concern for the governments of developing countries, in particular due to the increasingly high number of elderly citizens at risk. Alzheimer''s is the most common form of dementia, a common term for memory loss and other cognitive impairments. There is no current cure for AD, but there are drug and non-drug based approaches for its treatment. In general the drug-treatments are directed at slowing the progression of symptoms. They have proved to be effective in a large group of patients but success is directly correlated with identifying the disease carriers at its early stages. This justifies the need for timely and accurate forms of diagnosis via molecular means. We report here a 5-protein biomarker molecular signature that achieves, on average, a 96% total accuracy in predicting clinical AD. The signature is composed of the abundances of IL-1α, IL-3, EGF, TNF-α and G-CSF.

Methodology/Principal Findings

Our results are based on a recent molecular dataset that has attracted worldwide attention. Our paper illustrates that improved results can be obtained with the abundance of only five proteins. Our methodology consisted of the application of an integrative data analysis method. This four step process included: a) abundance quantization, b) feature selection, c) literature analysis, d) selection of a classifier algorithm which is independent of the feature selection process. These steps were performed without using any sample of the test datasets. For the first two steps, we used the application of Fayyad and Irani''s discretization algorithm for selection and quantization, which in turn creates an instance of the (alpha-beta)-k-Feature Set problem; a numerical solution of this problem led to the selection of only 10 proteins.

Conclusions/Significance

the previous study has provided an extremely useful dataset for the identification of AD biomarkers. However, our subsequent analysis also revealed several important facts worth reporting:1. A 5-protein signature (which is a subset of the 18-protein signature of Ray et al.) has the same overall performance (when using the same classifier).2. Using more than 20 different classifiers available in the widely-used Weka software package, our 5-protein signature has, on average, a smaller prediction error indicating the independence of the classifier and the robustness of this set of biomarkers (i.e. 96% accuracy when predicting AD against non-demented control).3. Using very simple classifiers, like Simple Logistic or Logistic Model Trees, we have achieved the following results on 92 samples: 100 percent success to predict Alzheimer''s Disease and 92 percent to predict Non Demented Control on the AD dataset.