Pan-cancer subclonal mutation analysis of 7,827 tumors predicts clinical outcome.

Intra-tumor heterogeneity is an important driver of tumor evolution and therapy response. Advances in precision cancer treatment will require understanding of mutation clonality and subclonal architecture. Currently the slow computational speed of subclonal reconstruction hinders large cohort studies.

Accelerated somatic mutation calling for whole-genome and whole-exome sequencing data from heterogenous tumor samples.

Accurate detection of somatic mutations in DNA sequencing data is a fundamental prerequisite for cancer research. Previous analytical challenges were overcome by consensus mutation calling from four to five popular callers. This, however, increases the already nontrivial computing time from individual callers.

DeMixSC: a deconvolution framework that uses single-cell sequencing plus a small benchmark dataset for improved analysis of cell-type ratios in complex tissue samples.

Bulk deconvolution with single-cell/nucleus RNA-seq data is critical for understanding heterogeneity in complex biological samples, yet the technological discrepancy across sequencing platforms limits deconvolution accuracy. To address this, we introduce an experimental design to match inter-platform biological signals, hence revealing the technological discrepancy, and then develop a deconvolution framework called DeMixSC using the better-matched, i.e.

Accelerated somatic mutation calling for whole-genome and whole-exome sequencing data from heterogenous tumor samples.

Accurate detection of somatic mutations in DNA sequencing data is a fundamental prerequisite for cancer research. Previous analytical challenge was overcome by consensus mutation calling from four to five popular callers. This, however, increases the already nontrivial computing time from individual callers.

MuSE: A Novel Approach to Mutation Calling with Sample-Specific Error Modeling.

Accurate detection of somatic mutations in genetically heterogeneous tumor cell populations using next-generation sequencing remains challenging. We have developed MuSE, Mutation calling using a Markov Substitution model for Evolution, a novel approach for modeling the evolution of the allelic composition of tumor and normal tissue at each reference base. It adopts a sample-specific error model to depict inter-tumor heterogeneity, which greatly improves the overall accuracy.

Estimation of tumor cell total mRNA expression in 15 cancer types predicts disease progression.

Single-cell RNA sequencing studies have suggested that total mRNA content correlates with tumor phenotypes. Technical and analytical challenges, however, have so far impeded at-scale pan-cancer examination of total mRNA content. Here we present a method to quantify tumor-specific total mRNA expression (TmS) from bulk sequencing data, taking into account tumor transcript proportion, purity and ploidy, which are estimated through transcriptomic/genomic deconvolution.

Novel Anaplastic Thyroid Cancer PDXs and Cell Lines: Expanding Preclinical Models of Genetic Diversity.

Context: Anaplastic thyroid cancer (ATC) is a rare, aggressive, and deadly disease. Robust preclinical thyroid cancer models are needed to adequately develop and study novel therapeutic agents. Patient-derived xenograft (PDX) models may resemble patient tumors by recapitulating key genetic alterations and gene expression patterns, making them excellent preclinical models for drug response evaluation.

Structure of SPH (self-incompatibility protein homologue) proteins: a widespread family of small, highly stable, secreted proteins.

SPH (self-incompatibility protein homologue) proteins are a large family of small, disulfide-bonded, secreted proteins, initially found in the self-incompatibility response in the field poppy (), but now known to be widely distributed in plants, many containing multiple members of this protein family. Using the Origami strain of , we expressed one member of this family, SPH15 from , as a folded thioredoxin fusion protein and purified it from the cytosol. The fusion protein was cleaved and characterised by analytical ultracentrifugation, circular dichroism and nuclear magnetic resonance (NMR) spectroscopy.

DeepCDpred: Inter-residue distance and contact prediction for improved prediction of protein structure.

Rapid, accurate prediction of protein structure from amino acid sequence would accelerate fields as diverse as drug discovery, synthetic biology and disease diagnosis. Massively improved prediction of protein structures has been driven by improving the prediction of the amino acid residues that contact in their 3D structure. For an average globular protein, around 92% of all residue pairs are non-contacting, therefore accurate prediction of only a small percentage of inter-amino acid distances could increase the number of constraints to guide structure determination.

Kissing and nanotunneling mediate intermitochondrial communication in the heart.

Mitochondria in many types of cells are dynamically interconnected through constant fusion and fission, allowing for exchange of mitochondrial contents and repair of damaged mitochondria. However, constrained by the myofibril lattice, the ∼6,000 mitochondria in the adult mammalian cardiomyocyte display little motility, and it is unclear how, if at all, they communicate with each other. By means of target-expressing photoactivatable green fluorescent protein (PAGFP) in the mitochondrial matrix or on the outer mitochondrial membrane, we demonstrated that the local PAGFP signal propagated over the entire population of mitochondria in cardiomyocytes on a time scale of ∼10 h.

Turbo fast three-dimensional carotid artery black-blood MRI by combining three-dimensional MERGE sequence with compressed sensing.

Purpose: In this study, we sought to investigate the feasibility of turbo fast three-dimensional (3D) black-blood imaging by combining a 3D motion-sensitizing driven equilibrium rapid gradient echo sequence with compressed sensing.

Methods: A pseudo-centric phase encoding order was developed for compressed sensing-3D motion-sensitizing driven equilibrium rapid gradient echo to suppress flow signal in undersampled 3D k-space. Nine healthy volunteers were recruited for this study.

Automatic segmentation of white matter hyperintensities by an extended FitzHugh & Nagumo reaction diffusion model.

Purpose: To evaluate the efficiency and reproducibility of the extended FitzHugh & Nagumo (FHN) reaction-diffusion model proposed in this study for white matter hyperintensities (WMH) segmentation.

Materials And Methods: Five types of magnetic resonance T2-weighted fluid-attenuated inversion-recovery (T2FLAIR) images of 127 patients with different scanning parameters from five clinical scanner systems were selected for this study. After skull and scalp removal and denoise, the T2FLAIR images were processed by the proposed extended FHN model to obtain WMH.