BackgroundSingle-cell RNA sequencing is fast becoming one the standard method for gene expression measurement, providing unique insights into cellular processes. A number of methods, based on general dimensionality reduction techniques, have been suggested to help infer and visualise the underlying structure of cell populations from single-cell expression levels, yet their models generally lack proper biological grounding and struggle at identifying complex differentiation paths.ResultsHere we introduce cellTree: an R/Bioconductor package that uses a novel statistical approach, based on document analysis techniques, to produce tree structures outlining the hierarchical relationship between single-cell samples, while identifying latent groups of genes that can provide biological insights.ConclusionsWith cellTree, we provide experimentalists with an easy-to-use tool, based on statistically and biologically-sound algorithms, to efficiently explore and visualise single-cell RNA data. The cellTree package is publicly available in the online Bionconductor repository at: http://bioconductor.org/packages/cellTree/.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1175-6) contains supplementary material, which is available to authorized users.

Biomarkers are vital to detect diseases in various clinical stages. A variety of cancer serum biomarkers are already known, while for more accurate cancer-type detection, there required more rigorous evaluation manners, especially computational evaluation measures, for biomarkers. In this review, we first show three typical pitfalls in finding biomarkers and their examples, after briefly presenting standard five clinical biomarker screening phases by National Cancer Institute. We then introduce current computational biomarker evaluation measures, including current, standard methods with their intrinsic features. We further show an up-to-date list of existing cancer serum biomarkers, pointing out several issues, being caused by the limitations of current biomarker evaluation approaches. Finally we discuss the current attempts to develop new, statistically robust, computational serum-based biomarker measures in terms of specificity to each of various cancer types.

Recent advancements in cell-based therapies for the treatment of cardiovascular disease (CVD) show continuing promise for the use of transplanted stem and cardiac progenitor cells (CPCs) to promote cardiac restitution. However, a detailed understanding of the molecular mechanisms that control the development of these cells remains incomplete and is critical for optimizing their use in such therapy. Long non-coding (lnc) RNA has recently emerged as a crucial class of regulatory molecules involved in directing a variety of critical biological processes including development, homeostasis and disease. As such, a rising body of evidence suggests that they also play key regulatory roles in CPC development, though many questions remain regarding the expression landscape and specific identity of lncRNA involved in this process. To address this, we performed whole transcriptome sequencing of two murine CPC populations-Nkx2-5 EmGFP reporter-sorted embryonic stem (ES) cell-derived and ex vivo, cardiosphere-derived-in an effort to characterize their lncRNA profiles and potentially identify novel CPC regulators. The resulting sequencing data revealed an enrichment in both CPC populations for a panel of previously-identified lncRNA genes associated with cardiac differentiation. Additionally, a total of 1,678 differentially expressed and as-of-yet unannotated, putative lncRNA genes were found to be enriched for in the two CPC populations relative to undifferentiated ES cells.

Lung cancer is the leading cause of cancer death for both men and women in the United States, and similar trends are seen world wide. The lack of early diagnosis is one of the primary reasons for the high mortality rate. A number of biomarkers have been evaluated in lung cancer patients, however, their specificity and early stage diagnostic values are limited. Using traditional protein chemistry and proteomics tool we have demonstrated higher serum haptoglobin levels in small cell lung cancer (SCLC). Similar findings have been reported for other cancers including ovarian cancer and glioblastoma. Haptoglobin is an acute phase protein with at least six possible phenotypes. The six phenotypes, in combination with two post translational modifications, glycosylation and deamidation, lead to large numbers of possible haptoglobin isoforms. Recent studies indicate a possible correlation between specific haptoglobin glycosylation and particular disease conditions. In our current study, we have fractionated control and SCLC patient serum by 2-D gel electrophoresis to identify differentially expressed haptoglobin isoforms in SCLC serum samples.

Introduction Ixekizumab has demonstrated rapid onset of action, high levels of skin clearance, and improvements in quality of life in patients with moderate-to-severe psoriasis, including plaque, erythrodermic, or generalized pustular psoriasis. Methods This was a post hoc analysis of UNCOVER-J, a phase 3, multicenter, single-arm, open-label study of ixekizumab for treatment of Japanese patients with psoriasis. The objective was to assess the proportion of patients who achieved Dermatology Life Quality Index (DLQI) (0,1) and Itch Numeric Rating Scale (NRS) (0) at weeks 4 and 12 according to Psoriasis Area and Severity Index (PASI) percentage improvement levels. All intent-to-treat patients with plaque, erythrodermic, or generalized pustular psoriasis were analyzed. Results A total of 91 patients were treated with ixekizumab and included in the analysis. Rapid improvements in PASI at weeks 4 and 12 were associated with improvements in DLQI (0,1) response at week 4 and at week 12. Complete skin clearance (PASI 100) achieved either at week 4 or week 12 was associated with a higher Itch NRS (0) response at week 12. Conclusions Patients with rapid improvement in clinical symptoms of psoriasis had better patient outcomes than those with slower responses. These findings highlight the clinical importance of achieving a fast response in patients with psoriasis, which may lead to better treatment outcomes. Trial Registration ClinicalTrials.gov identifier, NCT01624233. Graphic Abstract Electronic supplementary material The online version of this article (10.1007/s13555-020-00441-4) contains supplementary material, which is available to authorized users.