Sparse deconvolution in one and two dimensions: applications in endocrinology and single-molecule fluorescence imaging.

Deconvolution of noisy signals is an important task in analytical chemistry, examples being spectral deconvolution or deconvolution in microscopy. When the number of spectral peaks or single emitters in imaging is limited, the solution of the deconvolution is required to be sparse, and desirable results are obtained using a penalized estimation techniques. We impose sparseness by using penalized regression with a penalty based on the L0-norm, as discussed in earlier work. Several extensions to this approach are presented. Results are demonstrated on pulse identification in endocrine data where the aim is to model the secretion pattern as a sparse series of spikes. An application in single-molecule fluorescence imaging demonstrates the algorithm when applied to two-dimensional data.

Molecular subtypes of glioma identified by genome-wide methylation profiling.

Recent studies have indicated a prognostic role for genome-wide methylation in gliomas: Tumors that show an overall increase in DNA methylation at CpG sites (CIMP+; CpG island methylator phenotype) have a more favorable prognosis than CIMP- gliomas. Here, we have determined whether methylation profiling can identify more and clinically relevant molecular subtypes of glioma by performing genome-wide methylation profiling on 138 glial brain tumors of all histological diagnosis. Hopach (Hierarchical ordered partitioning and collapsing hybrid) clustering using the 1,000 most variable CpGs identified three distinct glioma subtypes (C+(1p19q), C+(wt), and C-) and one adult brain subtype. All "C+(1p19q) " and "C+(wt)" tumors were CIMP+ whereas most (50/54) "C-" tumors were CIMP-. The C- subtype gliomas contained many glioblastomas and all pilocytic astrocytomas. 1p19q LOH was frequent in the C+(1p19q) subtype. Other genetic changes (IDH1 mutation and EGFR amplification) and gene-expression based molecular subtypes also segregated in distinct methylation subtypes, demonstrating that these subtypes are also genetically distinct. Each subtype was associated with its own prognosis: median survival for C-, C+(1p19q), and C+(wt) tumors was 1.18, 5.00, and 2.62 years, respectively. The prognostic value of these methylation subtypes was validated on an external dataset from the TCGA. Analysis of recurrences of 14 primary tumors samples indicates that shifts between some C+(wt) and C+(1p/19q) tumors can occur between the primary and recurrent tumor, but CIMP status remained stable. Our data demonstrate that methylation profiling identifies at least three prognostically relevant subtypes of glioma that can aid diagnosis and potentially guide treatment for patients.

Spatially Regularized Shape Analysis of the Hippocampus Using P-Spline Based Shape Regression.

Shape analysis is increasingly becoming important to study changes in brain structures in relation to clinical neurological outcomes. This is a challenging task due to the high dimensionality of shape representations and the often limited number of available shapes. Current techniques counter the poor ratio between dimensions and sample size by using regularization in shape space, but do not take into account the spatial relations within the shapes. This can lead to models that are biologically implausible and difficult to interpret. We propose to use P-spline based regression, which combines a generalized linear model (GLM) with the coefficients described as B-splines and a penalty term that constrains the regression coefficients to be spatially smooth. Owing to the GLM, this method can naturally predict both continuous and discrete outcomes and can include non-spatial covariates without penalization. We evaluated our method on hippocampus shapes extracted from magnetic resonance (MR) images of 510 non-demented, elderly people. We related the hippocampal shape to age, memory score, and sex. The proposed method retained the good performance of current techniques, such as ridge regression, but produced smoother coefficient fields that are easier to interpret.

Sparse deconvolution of high-density super-resolution images.

In wide-field super-resolution microscopy, investigating the nanoscale structure of cellular processes, and resolving fast dynamics and morphological changes in cells requires algorithms capable of working with a high-density of emissive fluorophores. Current deconvolution algorithms estimate fluorophore density by using representations of the signal that promote sparsity of the super-resolution images via an L1-norm penalty. This penalty imposes a restriction on the sum of absolute values of the estimates of emitter brightness. By implementing an L0-norm penalty--on the number of fluorophores rather than on their overall brightness--we present a penalized regression approach that can work at high-density and allows fast super-resolution imaging. We validated our approach on simulated images with densities up to 15 emitters per µm(-2) and investigated total internal reflection fluorescence (TIRF) data of mitochondria in a HEK293-T cell labeled with DAKAP-Dronpa. We demonstrated super-resolution imaging of the dynamics with a resolution down to 55 nm and a 0.5 s time sampling.

The prognostic value of extraocular extension in relation to monosomy 3 and gain of chromosome 8q in uveal melanoma.

PURPOSE: To identify the prognostic value of extraocular extension in enucleated uveal melanoma (UM) patients and to correlate extraocular extension to chromosomal aberrations, metastasis-free survival (MFS), and clinico-histopathological risk factors. METHODS: Retrospective study of patients with UM treated with enucleation between 1987 and 2011. Melanoma-related metastasis and death were recorded. Statistical analysis (log-rank test or Cox regression analysis) was performed to correlate MFS with tumor characteristics, extraocular extension, episcleral diameter of the extraocular extension, cell type, extracellular matrix patterns, inflammation, loss of chromosome 3, and gain of chromosome 8q. RESULTS: In 43 (12%) of 357 patients, extraocular extension was observed. In this subset of patients, we noted a reduced survival of 70 months (105.5 months, P = 0.010) compared with patients without extraocular extension (175.8 months). Patients with gain of chromosomal region 8q in UM with extraocular extension had an increased risk of metastatic disease (P < 0.001). In multivariate Cox proportional hazard analysis, largest basal tumor diameter (P = 0.001), extracellular matrix patterns (P = 0.009), episcleral diameter of the extraocular extension (P = 0.016), loss of chromosome 3 (P < 0.001), and gain of 8q (P < 0.001) were independent predictors for MFS. CONCLUSIONS: Larger episcleral diameter of the extraocular extension and additional gain of chromosome 8q in extraocular extension UM correlates to a worse prognosis. MFS is significantly reduced in UM with a large basal tumor diameter, extracellular matrix patterns, loss of chromosome 3, and gain of chromosome 8q.

Mixture models for two-dimensional baseline correction, applied to artifact elimination in time-resolved spectroscopy.

Baseline correction and artifact removal are important pre-processing steps in analytical chemistry. We propose a correction algorithm using a mixture model in combination with penalized regression. The model is an extension of a method recently introduced for baseline estimation in the case of one-dimensional data. The data are modeled as a smooth surface using tensor product P-splines. The weights of the P-splines regression model are computed from a mixture model where a datapoint is either allocated to the noise around the baseline, or to the artifact component. The method is broadly applicable for anisotropic smoothing of two-way data such as two-dimensional gel electrophoresis and two-dimensional chromatography data. We focus here on the application of the approach in femtosecond time-resolved spectroscopy, to eliminate strong artifact signals from the solvent.

Foramen magnum size and involvement of its intraoccipital synchondroses in Crouzon syndrome.

BACKGROUND: Cranial sutures and synchondroses tend to close prematurely in patients with Crouzon syndrome. This influences their skull vault and skull base development and may involve in common disturbances such as increased intracranial pressure and cerebellar tonsillar herniation. The authors' hypothesis was that Crouzon patients patients have a smaller foramen magnum than controls because of premature fusion of the intraoccipital synchondroses, putting them at risk for cerebellar tonsillar herniation. Therefore, foramen magnum size and time of intraoccipital synchondroses closure were evaluated and were related to the presence and degree of cerebellar tonsillar herniation. METHODS: The foramen magnum surface area and anteroposterior diameter were measured on three-dimensional computed tomographic scans of 27 Crouzon patients and 27 age-matched controls. Scans had a slice-thickness between 0.75 and 1.25 mm and were aligned in a three-dimensional reformatting platform. The t test was used to study size differences. Synchondroses were graded as described by Madeline and Elster and studied with ordinal logistic regression analysis. RESULTS: Crouzon patients had a smaller foramen magnum surface area (602 mm versus 767 mm, p < 0.001) and anteroposterior diameter (31 mm versus 35 mm, p < 0.001) compared with controls. Differences stayed constant over time. Intraoccipital synchondroses closed 3 to 9 months earlier in Crouzon patients than in controls (p < 0.05). CONCLUSIONS: Since intraoccipital synchondroses close earlier in Crouzon patients, from early life on their foramen magnum is smaller compared with controls. Within Crouzon patients, the presence of cerebellar tonsillar herniation could not be related to foramen magnum size. CLINICAL QUESTION/LEVEL OF EVIDENCE: Risk, II.

Integrated transcript and genome analyses reveal NKX2-1 and MEF2C as potential oncogenes in T cell acute lymphoblastic leukemia.

To identify oncogenic pathways in T cell acute lymphoblastic leukemia (T-ALL), we combined expression profiling of 117 pediatric patient samples and detailed molecular-cytogenetic analyses including the Chromosome Conformation Capture on Chip (4C) method. Two T-ALL subtypes were identified that lacked rearrangements of known oncogenes. One subtype associated with cortical arrest, expression of cell cycle genes, and ectopic NKX2-1 or NKX2-2 expression for which rearrangements were identified. The second subtype associated with immature T cell development and high expression of the MEF2C transcription factor as consequence of rearrangements of MEF2C, transcription factors that target MEF2C, or MEF2C-associated cofactors. We propose NKX2-1, NKX2-2, and MEF2C as T-ALL oncogenes that are activated by various rearrangements.

Intrinsic gene expression profiles of gliomas are a better predictor of survival than histology.

Gliomas are the most common primary brain tumors with heterogeneous morphology and variable prognosis. Treatment decisions in patients rely mainly on histologic classification and clinical parameters. However, differences between histologic subclasses and grades are subtle, and classifying gliomas is subject to a large interobserver variability. To improve current classification standards, we have performed gene expression profiling on a large cohort of glioma samples of all histologic subtypes and grades. We identified seven distinct molecular subgroups that correlate with survival. These include two favorable prognostic subgroups (median survival, >4.7 years), two with intermediate prognosis (median survival, 1-4 years), two with poor prognosis (median survival, <1 year), and one control group. The intrinsic molecular subtypes of glioma are different from histologic subgroups and correlate better to patient survival. The prognostic value of molecular subgroups was validated on five independent sample cohorts (The Cancer Genome Atlas, Repository for Molecular Brain Neoplasia Data, GSE12907, GSE4271, and Li and colleagues). The power of intrinsic subtyping is shown by its ability to identify a subset of prognostically favorable tumors within an external data set that contains only histologically confirmed glioblastomas (GBM). Specific genetic changes (epidermal growth factor receptor amplification, IDH1 mutation, and 1p/19q loss of heterozygosity) segregate in distinct molecular subgroups. We identified a subgroup with molecular features associated with secondary GBM, suggesting that different genetic changes drive gene expression profiles. Finally, we assessed response to treatment in molecular subgroups. Our data provide compelling evidence that expression profiling is a more accurate and objective method to classify gliomas than histologic classification. Molecular classification therefore may aid diagnosis and can guide clinical decision making.