Recent revelations and future directions using single-cell technologies in chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) is a clinically and biologically heterogeneous disease with varying outcomes. In the last decade, the application of next-generation sequencing technologies has allowed extensive mapping of disease-specific genomic, epigenomic, immunogenetic, and transcriptomic signatures linked to CLL pathogenesis. These technologies have improved our understanding of the impact of tumor heterogeneity and evolution on disease outcome, although they have mostly been performed on bulk preparations of nucleic acids. As a further development, new technologies have emerged in recent years that allow high-resolution mapping at the single-cell level. These include single-cell RNA sequencing for assessment of the transcriptome, both of leukemic and non-malignant cells in the tumor microenvironment; immunogenetic profiling of B and T cell receptor rearrangements; single-cell sequencing methods for investigation of methylation and chromatin accessibility across the genome; and targeted single-cell DNA sequencing for analysis of copy-number alterations and single nucleotide variants. In addition, concomitant profiling of cellular subpopulations, based on protein expression, can also be obtained by various antibody-based approaches. In this review, we discuss different single-cell sequencing technologies and how they have been applied so far to study CLL onset and progression, also in response to treatment. This latter aspect is particularly relevant considering that we are moving away from chemoimmunotherapy to targeted therapies, with a potentially distinct impact on clonal dynamics. We also discuss new possibilities, such as integrative multi-omics analysis, as well as inherent limitations of the different single-cell technologies, from sample preparation to data interpretation using available bioinformatic pipelines. Finally, we discuss future directions in this rapidly evolving field.</p

Recent revelations and future directions using single-cell technologies in chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) is a clinically and biologically heterogeneous disease with varying outcomes. In the last decade, the application of next-generation sequencing technologies has allowed extensive mapping of disease-specific genomic, epigenomic, immunogenetic, and transcriptomic signatures linked to CLL pathogenesis. These technologies have improved our understanding of the impact of tumor heterogeneity and evolution on disease outcome, although they have mostly been performed on bulk preparations of nucleic acids. As a further development, new technologies have emerged in recent years that allow high-resolution mapping at the single-cell level. These include single-cell RNA sequencing for assessment of the transcriptome, both of leukemic and non-malignant cells in the tumor microenvironment; immunogenetic profiling of B and T cell receptor rearrangements; single-cell sequencing methods for investigation of methylation and chromatin accessibility across the genome; and targeted single-cell DNA sequencing for analysis of copy-number alterations and single nucleotide variants. In addition, concomitant profiling of cellular subpopulations, based on protein expression, can also be obtained by various antibody-based approaches. In this review, we discuss different single-cell sequencing technologies and how they have been applied so far to study CLL onset and progression, also in response to treatment. This latter aspect is particularly relevant considering that we are moving away from chemoimmunotherapy to targeted therapies, with a potentially distinct impact on clonal dynamics. We also discuss new possibilities, such as integrative multi-omics analysis, as well as inherent limitations of the different single-cell technologies, from sample preparation to data interpretation using available bioinformatic pipelines. Finally, we discuss future directions in this rapidly evolving field

Low Temperature Physics

Contains research objectives

Comparative assessment of clinical rating scales in Wilson’s disease

Background: Wilson’s disease (WD) is an autosomal recessive disorder of copper metabolism resulting in multifaceted neurological, hepatic, and psychiatric symptoms. The objective of the study was to comparatively assess two clinical rating scales for WD, the Unified Wilson’s Disease Rating Scale (UWDRS) and the Global Assessment Scale for Wilson’s disease (GAS for WD), and to test the feasibility of the patient reported part of the UWDRS neurological subscale (termed the “minimal UWDRS”). Methods: In this prospective, monocentric, cross-sectional study, 65 patients (median age 35 [range: 15–62] years; 33 female, 32 male) with treated WD were scored according to the two rating scales. Results: The UWDRS neurological subscore correlated with the GAS for WD Tier 2 score (r = 0.80; p < 0.001). Correlations of the UWDRS hepatic subscore and the GAS for WD Tier 1 score with both the Model for End Stage Liver Disease (MELD) score (r = 0.44/r = 0.28; p < 0.001/p = 0.027) and the Child-Pugh score (r = 0.32/r = 0.12; p = 0.015/p = 0.376) were weak. The “minimal UWDRS” score significantly correlated with the UWDRS total score (r = 0.86), the UWDRS neurological subscore (r = 0.89), and the GAS for WD Tier 2 score (r = 0.86). Conclusions: The UWDRS neurological and psychiatric subscales and the GAS for WD Tier 2 score are valuable tools for the clinical assessment of WD patients. The “minimal UWDRS” is a practical prescreening tool outside scientific trials

Optimizing Preprocessing and Analysis Pipelines for Single-Subject fMRI: 2. Interactions with ICA, PCA, Task Contrast and Inter-Subject Heterogeneity

A variety of preprocessing techniques are available to correct subject-dependant artifacts in fMRI, caused by head motion and physiological noise. Although it has been established that the chosen preprocessing steps (or “pipeline”) may significantly affect fMRI results, it is not well understood how preprocessing choices interact with other parts of the fMRI experimental design. In this study, we examine how two experimental factors interact with preprocessing: between-subject heterogeneity, and strength of task contrast. Two levels of cognitive contrast were examined in an fMRI adaptation of the Trail-Making Test, with data from young, healthy adults. The importance of standard preprocessing with motion correction, physiological noise correction, motion parameter regression and temporal detrending were examined for the two task contrasts. We also tested subspace estimation using Principal Component Analysis (PCA), and Independent Component Analysis (ICA). Results were obtained for Penalized Discriminant Analysis, and model performance quantified with reproducibility (R) and prediction metrics (P). Simulation methods were also used to test for potential biases from individual-subject optimization. Our results demonstrate that (1) individual pipeline optimization is not significantly more biased than fixed preprocessing. In addition, (2) when applying a fixed pipeline across all subjects, the task contrast significantly affects pipeline performance; in particular, the effects of PCA and ICA models vary with contrast, and are not by themselves optimal preprocessing steps. Also, (3) selecting the optimal pipeline for each subject improves within-subject (P,R) and between-subject overlap, with the weaker cognitive contrast being more sensitive to pipeline optimization. These results demonstrate that sensitivity of fMRI results is influenced not only by preprocessing choices, but also by interactions with other experimental design factors. This paper outlines a quantitative procedure to denoise data that would otherwise be discarded due to artifact; this is particularly relevant for weak signal contrasts in single-subject, small-sample and clinical datasets

Angular distributions in the decay B -> K*l(+)l(-)

We use a sample of 384 million BBbar events collected with the Babar detector at the PEP-II e+e- collider to study angular distributions in the rare decays B -> K* l+l-, where l+l- is either e+e- or mu+mu-. For low dilepton invariant masses, m(l+l-)3.2$ GeV/c^2, we measure AFB=0.76 (+0.52,-0.32) +/- 0.07 FL=0.71 (+0.20,-0.22) +/- 0.04.We are grateful for the excellent luminosity and machine conditions provided by our PEP-II colleagues, and for the substantial dedicated effort from the computing organizations that support BABAR. The collaborating institutions wish to thank SLAC for its support and kind hospitality. This work is supported by DOE and NSF (USA), NSERC (Canada), CEA and CNRS-IN2P3 (France), BMBF and DFG (Germany), INFN (Italy), FOM (The Netherlands), NFR (Norway), MES (Russia), MEC (Spain), and STFC (United Kingdom). Individuals have received support from the Marie Curie EIF (European Union) and the A. P. Sloan Foundation.Peer reviewe