Multi‐omics studies promise the improved characterization of biological processes across molecular layers. However, methods for the unsupervised integration of the resulting heterogeneous data sets are lacking. We present Multi‐Omics Factor Analysis (MOFA), a computational method for discovering the principal sources of variation in multi‐omics data sets. MOFA infers a set of (hidden) factors that capture biological and technical sources of variability. It disentangles axes of heterogeneity that are shared across multiple modalities and those specific to individual data modalities. The learnt factors enable a variety of downstream analyses, including identification of sample subgroups, data imputation and the detection of outlier samples. We applied MOFA to a cohort of 200 patient samples of chronic lymphocytic leukaemia, profiled for somatic mutations, RNA expression, DNA methylation and ex vivo drug responses. MOFA identified major dimensions of disease heterogeneity, including immunoglobulin heavy‐chain variable region status, trisomy of chromosome 12 and previously underappreciated drivers, such as response to oxidative stress. In a second application, we used MOFA to analyse single‐cell multi‐omics data, identifying coordinated transcriptional and epigenetic changes along cell differentiation.

SummaryThe ability of a bacterial cell to monitor and adaptively respond to its environment is crucial for survival.

The purpose of this prospective multicenter phase 2 trial was to investigate the long-term outcome of reduced-intensity conditioning allogeneic stem cell transplantation (alloSCT) in patients with poor-risk chronic lymphocytic leukemia. Conditioning was fludarabine/ cyclophosphamide-based. Longitudinal quantitative monitoring of minimal residual disease (MRD) was performed centrally by MRD-flow or real-time quantitative polymerase chain reaction. One hundred eligible patients were enrolled, and 90 patients proceeded to alloSCT.With a median follow-up of 46 months (7-102 months), 4-year nonrelapse mortality, event-free survival (EFS) and overall survival (OS) were 23%, 42%, and 65%, respectively. Of 52 patients with MRD monitoring available, 27 (52%) were alive and MRD negative at 12 months after transplant. Four-year EFS of this subset was 89% with all event-free patients except for 2 being MRD negative at the most recent assessment. EFS was similar for all genetic subsets, including 17p deletion (17p؊). In multivariate analyses, uncontrolled disease at alloSCT and in vivo T-cell depletion with alemtuzumab, but not 17p؊, previous purine analogue refractoriness, or donor source (human leukocyte antigen-identical siblings or unrelated donors) had an adverse impact on EFS and OS. In conclusion, alloSCT for poor-risk chronic lymphocytic leukemia can result in long-term MRD-negative survival in up to one-half of the patients independent of the underlying genomic risk profile. This trial is registered at

MET receptor tyrosine kinase and its ligand hepatocyte growth factor (HGF) regulate a variety of cellular functions, many of which can be dysregulated in human cancers. Activated MET signaling can lead to cell motility and scattering, angiogenesis, proliferation, branching morphogenesis, invasion, and eventual metastasis. We performed systematic analysis of the expression of the MET receptor and its ligand HGF in tumor tissue microarrays (TMA) from human solid cancers. Standard immunohistochemistry and a computerized automated scoring system were used. DNA sequencing for MET mutations in both non-kinase and kinase domains was also performed. MET was differentially overexpressed in human solid cancers. The ligand HGF was widely expressed in both tumor, primarily intra-tumoral, and non-malignant tissues. The MET/HGF likely is functional and may be activated in autocrine fashion in vivo. MET and SCF were found to be positively stained in the bronchioalevolar junctions of lung tumors. A number of novel mutations of MET were identified, particularly in the extracellular semaphorin domain and the juxtamembrane domain. MET-HGF pathway can be assayed in TMAs and is often overexpressed in a wide variety of human solid cancers. MET can be activated through overexpression, mutation, or autocrine signaling in malignant cells. Mutations in the non-kinase regions of MET might play important role in tumorigenesis and tumor progression. MET would be an important therapeutic anti-tumor target to be inhibited, and in lung cancer, MET may represent a cancer early progenitor cell marker.