Subgroup-specific gene expression profiles and mixed epistasis in chronic lymphocytic leukemia.

Understanding the molecular and phenotypic heterogeneity of cancer is a prerequisite for effective treatment. For chronic lymphocytic leukemia (CLL), recurrent genetic driver events have been extensively cataloged, but this does not suffice to explain the disease's diverse course. Here, we performed RNA sequencing on 184 CLL patient samples. Unsupervised analysis revealed two major, orthogonal axes of gene expression variation: the first one represented the mutational status of the immunoglobulin heavy variable (IGHV) genes, and concomitantly, the three-group stratification of CLL by global DNA methylation. The second axis aligned with trisomy 12 status and affected chemokine, MAPK and mTOR signaling. We discovered non-additive effects (epistasis) of IGHV mutation status and trisomy 12 on multiple phenotypes, including the expression of 893 genes. Multiple types of epistasis were observed, including synergy, buffering, suppression and inversion, suggesting that molecular understanding of disease heterogeneity requires studying such genetic events not only individually but in combination. We detected strong differentially expressed gene signatures associated with major gene mutations and copy number aberrations including SF3B1, BRAF and TP53, as well as del(17)(p13), del(13)(q14) and del(11)(q22.3) beyond dosage effect. Our study reveals previously underappreciated gene expression signatures for the major molecular subtypes in CLL and the presence of epistasis between them.

nNOS-derived NO modulates force production and iNO-derived NO the excitability in C2C12-derived 3D tissue engineering skeletal muscle via different NO signaling pathways.

Nitric oxide (NO) is a bioactive gas produced by one of the three NO synthases: neuronal NOS (nNOS), inducible (iNOS), and endothelial NOS (eNOS). NO has a relevant modulatory role in muscle contraction; this takes place through two major signaling pathways: (i) activation of soluble guanylate cyclase and, thus, protein kinase G or (ii) nitrosylation of sulfur groups of cysteine. Although it has been suggested that nNOS-derived NO is the responsible isoform in muscle contraction, the roles of eNOS and iNOS and their signaling pathways have not yet been clarified. To elucidate the action of each pathway, we optimized the generation of myooids, an engineered skeletal muscle tissue based on the C2C12 cell line. In comparison with diaphragm strips from wild-type mice, 180 myooids were analyzed, which expressed all relevant excitation-contraction coupling proteins and both nNOS and iNOS isoforms. Along with the biochemical results, myooids treated with NO donor (SNAP) and unspecific NOS blocker (L-NAME) revealed a comparable NO modulatory effect on force production as was observed in the diaphragm strips. Under the effects of pharmacological tools, we analyzed the myooids in response to electrical stimulation of two possible signaling pathways and NO sources. The nNOS-derived NO exerted its negative effect on force production via the sGG-PKG pathway, while iNOS-derived NO increased the excitability in response to sub-threshold electrical stimulation. These results strengthen the hypotheses of previous reports on the mechanism of action of NO during force production, showed a novel function of iNOS-derived NO, and establish the myooid as a novel and robust alternative model for pathophysiological skeletal muscle research.

Multi-omics reveals clinically relevant proliferative drive associated with mTOR-MYC-OXPHOS activity in chronic lymphocytic leukemia.

Chronic Lymphocytic Leukemia (CLL) has a complex pattern of driver mutations and much of its clinical diversity remains unexplained. We devised a method for simultaneous subgroup discovery across multiple data types and applied it to genomic, transcriptomic, DNA methylation and ex-vivo drug response data from 217 Chronic Lymphocytic Leukemia (CLL) cases. We uncovered a biological axis of heterogeneity strongly associated with clinical behavior and orthogonal to the known biomarkers. We validated its presence and clinical relevance in four independent cohorts (n=547 patients). We find that this axis captures the proliferative drive (PD) of CLL cells, as it associates with lymphocyte doubling rate, global hypomethylation, accumulation of driver aberrations and response to pro-proliferative stimuli. CLL-PD was linked to the activation of mTOR-MYC-oxidative phosphorylation (OXPHOS) through transcriptomic, proteomic and single cell resolution analysis. CLL-PD is a key determinant of disease outcome in CLL. Our multi-table integration approach may be applicable to other tumors whose inter-individual differences are currently unexplained.

CellMixS: quantifying and visualizing batch effects in single-cell RNA-seq data.

A key challenge in single-cell RNA-sequencing (scRNA-seq) data analysis is batch effects that can obscure the biological signal of interest. Although there are various tools and methods to correct for batch effects, their performance can vary. Therefore, it is important to understand how batch effects manifest to adjust for them. Here, we systematically explore batch effects across various scRNA-seq datasets according to magnitude, cell type specificity, and complexity. We developed a cell-specific mixing score (cms) that quantifies mixing of cells from multiple batches. By considering distance distributions, the score is able to detect local batch bias as well as differentiate between unbalanced batches and systematic differences between cells of the same cell type. We compare metrics in scRNA-seq data using real and synthetic datasets and whereas these metrics target the same question and are used interchangeably, we find differences in scalability, sensitivity, and ability to handle differentially abundant cell types. We find that cell-specific metrics outperform cell type-specific and global metrics and recommend them for both method benchmarks and batch exploration.