Plasma lipid biomarker signatures in squamous carcinoma and adenocarcinoma lung cancer patients

There is a clinical need for reliable biomarkers for lung cancer that permit early diagnosis of the disease and provide prediction of histological phenotype. A prospective study design was used with a study population of patients with suspected lung cancer. Blood samples were collected from 17 patients with histologically confirmed squamous cell lung carcinoma, 17 individuals with adenocarcinoma, and 17 control individuals who did not subsequently have a diagnosis of lung cancer or any other cancer. Blood plasma samples were analysed for their lipid profiles using liquid chromatography coupled with high resolution mass spectrometry. Data were analysed using multivariate statistical methods. There was good separation between histological subtypes and control groups and also between individuals with a subsequent diagnosis of adenocarcinoma and squamous cell carcinoma (sensitivity 80 %, specificity 83 %, Q2 = 0.70). Alterations in the levels of different classes of lipids including triglycerides (TGs), phosphatidylinositols (PIs), phosphatidylcholines (PCs), phosphatidylethanolamines (PEs), free fatty acids, lysophospholipids and sphingolipids were observed in squamous carcinoma and adenocarcinoma lung cancer patients when compared with control patients. In conclusion, this study has identified candidate lipid biomarkers of non-small cell lung cancer patients which may be helpful to indicate the tumour subtype and to differentiate them from patients who do not have lung cancer. Measuring these biomarkers has the potential to improve diagnosis in patients with suspected lung cancer and risk stratification in screening

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Mass spectrometry and multivariate analysis to classify cervical intraepithelial neoplasia from blood plasma: an untargeted lipidomic study

Cervical cancer is still an important issue of public health since it is the fourth most frequent type of cancer in women worldwide. Much effort has been dedicated to combating this cancer, in particular by the early detection of cervical pre-cancerous lesions. For this purpose, this paper reports the use of mass spectrometry coupled with multivariate analysis as an untargeted lipidomic approach to classifying 76 blood plasma samples into negative for intraepithelial lesion or malignancy (NILM, n = 42) and squamous intraepithelial lesion (SIL, n = 34). The crude lipid extract was directly analyzed with mass spectrometry for untargeted lipidomics, followed by multivariate analysis based on the principal component analysis (PCA) and genetic algorithm (GA) with support vector machines (SVM), linear (LDA) and quadratic (QDA) discriminant analysis. PCA-SVM models outperformed LDA and QDA results, achieving sensitivity and specificity values of 80.0% and 83.3%, respectively. Five types of lipids contributing to the distinction between NILM and SIL classes were identified, including prostaglandins, phospholipids, and sphingolipids for the former condition and Tetranor-PGFM and hydroperoxide lipid for the latter. These findings highlight the potentiality of using mass spectrometry associated with chemometrics to discriminate between healthy women and those suffering from cervical pre-cancerous lesions

A Systems Biology Approach Reveals the Role of a Novel Methyltransferase in Response to Chemical Stress and Lipid Homeostasis

Using small molecule probes to understand gene function is an attractive approach that allows functional characterization of genes that are dispensable in standard laboratory conditions and provides insight into the mode of action of these compounds. Using chemogenomic assays we previously identified yeast Crg1, an uncharacterized SAM-dependent methyltransferase, as a novel interactor of the protein phosphatase inhibitor cantharidin. In this study we used a combinatorial approach that exploits contemporary high-throughput techniques available in Saccharomyces cerevisiae combined with rigorous biological follow-up to characterize the interaction of Crg1 with cantharidin. Biochemical analysis of this enzyme followed by a systematic analysis of the interactome and lipidome of CRG1 mutants revealed that Crg1, a stress-responsive SAM-dependent methyltransferase, methylates cantharidin in vitro. Chemogenomic assays uncovered that lipid-related processes are essential for cantharidin resistance in cells sensitized by deletion of the CRG1 gene. Lipidome-wide analysis of mutants further showed that cantharidin induces alterations in glycerophospholipid and sphingolipid abundance in a Crg1-dependent manner. We propose that Crg1 is a small molecule methyltransferase important for maintaining lipid homeostasis in response to drug perturbation. This approach demonstrates the value of combining chemical genomics with other systems-based methods for characterizing proteins and elucidating previously unknown mechanisms of action of small molecule inhibitors

Nociceptors: a phylogenetic view

The ability to react to environmental change is crucial for the survival of an organism and an essential prerequisite is the capacity to detect and respond to aversive stimuli. The importance of having an inbuilt “detect and protect” system is illustrated by the fact that most animals have dedicated sensory afferents which respond to noxious stimuli called nociceptors. Should injury occur there is often sensitization, whereby increased nociceptor sensitivity and/or plasticity of nociceptor-related neural circuits acts as a protection mechanism for the afflicted body part. Studying nociception and nociceptors in different model organisms has demonstrated that there are similarities from invertebrates right through to humans. The development of technology to genetically manipulate organisms, especially mice, has led to an understanding of some of the key molecular players in nociceptor function. This review will focus on what is known about nociceptors throughout the Animalia kingdom and what similarities exist across phyla; especially at the molecular level of ion channels

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

A neuroscientist's guide to lipidomics

Nerve cells mould the lipid fabric of their membranes to ease vesicle fusion, regulate ion fluxes and create specialized microenvironments that contribute to cellular communication. The chemical diversity of membrane lipids controls protein traffic, facilitates recognition between cells and leads to the production of hundreds of molecules that carry information both within and across cells. With so many roles, it is no wonder that lipids make up half of the human brain in dry weight. The objective of neural lipidomics is to understand how these molecules work together; this difficult task will greatly benefit from technical advances that might enable the testing of emerging hypotheses