Quantitative proteomics suggests decrease in the secretogranin‐1 cerebrospinal fluid levels during the disease course of multiple sclerosis

Multiple sclerosis (MS) is a chronic inflammatory disease of the CNS with unknown cause. Proteins with different abundance in the cerebrospinal fluid (CSF) from relapsing‐remitting MS (RRMS) patients and neurological controls could give novel insight to the MS pathogenesis and be used to improve diagnosis, predict prognosis and disease course, and guide in therapy decisions. We combined iTRAQ labeling and Orbitrap mass spectrometry to discover proteins with different CSF abundance between six RRMS patients and 18 neurological disease controls. From 777 quantified proteins seven were selected as biomarker candidates, namely chitinase‐3‐like protein 1, secretogranin‐1 (Sg1), cerebellin‐1, neuroserpin, cell surface glycoprotein MUC18, testican‐2 and glutamate receptor 4. An independent sample set of 13 early‐MS patients, 13 RRMS patients and 13 neurological controls was used in a multiple reaction monitoring verification study. We found the intracellular calcium binding protein Sg1 to be increased in early‐MS patients compared to RRMS and neurological controls. Sg1 should be included in further studies to elucidate its role in the early phases of MS pathogenesis and its potential as a biomarker for this disease.     

Bottom up proteomics data analysis strategies to explore protein modifications and genomic variants

The quest to understand biological systems requires further attention of the scientific community to the challenges faced in proteomics. In fact the complexity of the proteome reaches uncountable orders of magnitude. This means that significant technical and data‐analytic innovations will be needed for the full understanding of biology. Current state of art MS is probably our best choice for studying protein complexity and exploring new ways to use MS and MS derived data should be given higher priority. We present here a brief overview of visualization and statistical analysis strategies for quantitative peptide values on an individual protein basis. These analysis strategies can help pinpoint protein modifications, splice, and genomic variants of biological relevance. We demonstrate the application of these data analysis strategies using a bottom‐up proteomics dataset obtained in a drug profiling experiment. Furthermore, we have also observed that the presented methods are useful for studying peptide distributions from clinical samples from a large number of individuals. We expect that the presented data analysis strategy will be useful in the future to define functional protein variants in biological model systems and disease studies. Therefore robust software implementing these strategies is urgently needed.     

Molecular Subtypes in Stage II-III Colon Cancer Defined by Genomic Instability: Early Recurrence-Risk Associated with a High Copy-Number Variation and Loss of RUNX3 and CDKN2A

Objective

We sought to investigate various molecular subtypes defined by genomic instability that may be related to early death and recurrence in colon cancer.

Methods

We sought to investigate various molecular subtypes defined by instability at microsatellites (MSI), changes in methylation patterns (CpG island methylator phenotype, CIMP) or copy number variation (CNV) in 8 genes. Stage II-III colon cancers (n = 64) were investigated by methylation-specific multiplex ligated probe amplification (MS-MLPA). Correlation of CNV, CIMP and MSI, with mutations in KRAS and BRAFV600E were assessed for overlap in molecular subtypes and early recurrence risk by uni- and multivariate regression.

Results

The CIMP phenotype occurred in 34% (22/64) and MSI in 27% (16/60) of the tumors, with noted CIMP/MSI overlap. Among the molecular subtypes, a high CNV phenotype had an associated odds ratio (OR) for recurrence of 3.2 (95% CI 1.1-9.3; P = 0.026). Losses of CACNA1G (OR of 2.9, 95% CI 1.4-6.0; P = 0.001), IGF2 (OR of 4.3, 95% CI 1.1-15.8; P = 0.007), CDKN2A (p16) (OR of 2.0, 95% CI 1.1-3.6; P = 0.024), and RUNX3 (OR of 3.4, 95% CI 1.3-8.7; P = 0.002) were associated with early recurrence, while MSI, CIMP, KRAS or BRAF V600E mutations were not. The CNV was significantly higher in deceased patients (CNV in 6 of 8) compared to survivors (CNV in 3 of 8). Only stage and loss of RUNX3 and CDKN2A were significant in the multivariable risk-model for early recurrence.

Conclusions

A high copy number variation phenotype is a strong predictor of early recurrence and death, and may indicate a dose-dependent relationship between genetic instability and outcome. Loss of tumor suppressors RUNX3 and CDKN2A were related to recurrence-risk and warrants further investigation.     

Analysis of qPCR data by converting exponentially related Ct values into linearly related X0 values

A common method for calculating results from qPCR experiments is the comparative Ct method, also called the 2(-ΔΔCt) method. However, several assumptions are included in the 2(-ΔΔCt) method and standard statistical analyses are not directly applicable. Here, we describe a different method, the X(0) method, for result calculations and statistical analysis from qPCR experiments. The X(0) method differs from the 2(-ΔΔCt) method by introducing a conversion of the exponentially related Ct values into linearly related X(0) values, which represent the amount of starting material in a qPCR experiment. Results calculated by the X(0) method are illustrated for qPCR experiments with technical and biological replicates, including procedures to calculate standard deviations. Incorporation of primer efficiencies in calculations by the X(0) method is also described. Altogether, the X(0) method constitutes a very simple and accurate alternative to the 2(-ΔΔCt) method for result calculations from qPCR data.     

Hedgehog beyond medulloblastoma and basal cell carcinoma

The Hedgehog (Hh) signaling pathway is of central importance during embryo development in metazoans and governs a diverse array of processes including cell proliferation, differentiation, and tissue patterning. In normal adult physiology, the pathway is implicated in stem cell maintenance, tissue repair and regeneration. However, the pathway's darker side is its involvement in several types of human cancer, to which it confers growth promoting and/or survival capabilities to the cancer cell to varying degrees, and by different mechanisms. The Hh pathway is firmly linked to the etiology of basal cell carcinoma and to at least a subset of medulloblastoma. There is increasing evidence that other sporadic cancers, including those in pancreas, prostate, lung, and breast, could also be dependent on Hh pathway activity. In this review, we provide an overview of the pathway's role in various tumor types, where much of the framework for Hh-dependent malignancies has been elucidated in experimental mouse models. We discuss three different signal transduction models for the pathway's involvement in cancer: i) ligand-independent signaling, ii) ligand-dependent autocrine/juxtacrine signaling, and iii) ligand-dependent paracrine signaling. These different modes of signaling may have implications for future therapeutic interventions aimed at inhibiting the pathway during disease. In addition, crosstalk with other pathways, and indications of non-canonical Hh signaling in cancer cells may further cause complications, or perhaps possibilities, in the treatment regimen. Finally, we review the rapid progress and promising results in the development of small-molecule inhibitors of the Hh pathway.     

Identification of species by multiplex analysis of variable-length sequences

The quest for a universal and efficient method of identifying species has been a longstanding challenge in biology. Here, we show that accurate identification of species in all domains of life can be accomplished by multiplex analysis of variable-length sequences containing multiple insertion/deletion variants. The new method, called SPInDel, is able to discriminate 93.3% of eukaryotic species from 18 taxonomic groups. We also demonstrate that the identification of prokaryotic and viral species with numeric profiles of fragment lengths is generally straightforward. A computational platform is presented to facilitate the planning of projects and includes a large data set with nearly 1800 numeric profiles for species in all domains of life (1556 for eukaryotes, 105 for prokaryotes and 130 for viruses). Finally, a SPInDel profiling kit for discrimination of 10 mammalian species was successfully validated on highly processed food products with species mixtures and proved to be easily adaptable to multiple screening procedures routinely used in molecular biology laboratories. These results suggest that SPInDel is a reliable and cost-effective method for broad-spectrum species identification that is appropriate for use in suboptimal samples and is amenable to different high-throughput genotyping platforms without the need for DNA sequencing.     

Canards and mixed-mode oscillations in a forest pest model

We consider a three-variable forest pest model, proposed by Rinaldi & Muratori (1992) [Rinaldi, S., Muratori, S., 1992. Limit cycles in slow–fast forest–pest models. Theor. Popul. Biol. 41, 26–43]. The model allows relaxation oscillations where long pest-free periods are interspersed with outbreaks of high pest concentration. For small values of the timescale of the young trees, the model can be reduced to a two-dimensional model. By a geometrical analysis we identify a canard explosion in the reduced model, that is, a change over a narrow parameter interval from outbreak dynamics to small oscillations around an endemic state. For larger values of the timescale of the young trees the two-dimensional approximation breaks down, and a broader parameter interval with mixed-mode oscillations appear, replacing the simple canard explosion. The analysis only relies on simple and generic properties of the model, and is expected to be applicable in a larger class of multiple timescale dynamical models.     

Increased effect of the ApoE gene on survival at advanced age in healthy and long‐lived Danes: two nationwide cohort studies

Studies of Nordic twins suggest an increased genetic influence on mortality with age. Contrary to this, the heterogeneity hypothesis predicts that the mortality of individuals carrying a ‘frail’ or ‘risky’ genotype in a population will approach that of noncarriers with age because of selection pressure. The ApoE ε4 allele is associated with an increased mortality risk, and its effect has been suggested to decrease with age. Here, we investigated the effect of ApoE ε4 allele on survival in a sample of the healthiest and long‐lived Danes. The study population comprised Danes born in 1905 and a replicate sample of the 1895 cohort. For the 1905 cohort, a total of 350 carriers and 1256 noncarriers of the ApoE ε4 allele were followed from 1998 until death or end of follow‐up. Cox regression models were used for the analysis. Of the 1606 persons with known ApoE ε4 status in 1998, 1546 had died at the end of the 10‐year follow‐up. Carriers of the ApoE ε4 allele had an increased mortality compared to noncarriers, and the influence of ApoE status on mortality increased in the age interval 92–103. For the covariates sex and independency status, the difference in relative risk of death between groups decreased with advancing age. Our findings of increasing influence of ApoE ε4 allele on mortality with age do not support previous findings of decreased influence ApoE ε4 allele on mortality with age, and alternative models such as the multifactorial threshold models should be considered for understanding the genetic effects on mortality at advanced age.