Background Lung neuroendocrine tumours (NETs, also known as carcinoids) are rapidly rising in incidence worldwide but have unknown aetiology and limited therapeutic options beyond surgery. The current...

Nutrient-starved tumour cells cooperate by secreting aminopeptidases that digest oligopeptides in the microenvironment, creating a shared pool of free amino acids.

Human cancers are heterogeneous. Their genomes evolve from genetically diverse germlines in complex and dynamic environments, including exposure to potential carcinogens. This heterogeneity of humans,...

AbstractSummary. Doublets are usually considered an unwanted artifact of single-cell RNA-sequencing (scRNA-seq) and are only identified in datasets for the

Benchmarking of tumor subclonal reconstruction algorithms finds that interalgorithm variability overwhelms intertumor variability and identifies key quality metrics.

The advent of droplet-based single-cell RNA-sequencing (scRNA-seq) has dramatically increased data throughput, enabling the release of a diverse array of tissue cell atlases to the public. However, we...

Ionizing radiation (IR) is known to be DNA damaging and mutagenic, however less is known about which mutational footprints result from exposures of human cells to different types of IR. We were interested in the mutagenic effects of particle radiation exposures on genomes of various human cell types, in order to gauge the genotoxic risks of space travel, and of certain types of tumor radiotherapy. To this end, we exposed cultured cell lines from the blood, breast and lung to intermittent proton and alpha particle (helium nuclei) beams at doses sufficient to affect cell survival. Whole-genome sequencing revealed that mutation rates were not overall markedly increased upon proton and alpha exposures. However, there were changes in mutation spectra and distributions, such as the increases in clustered mutations and of certain types of indels and structural variants. The spectrum of mutagenic effects of particle beams may often be cell-type and/or genetic background specific. Overall, the mutational effects of recurrent exposures to proton and alpha radiation on human cells appear subtle, however further work is warranted to understand effects of chronic, long-term exposures on various human tissues. ### Competing Interest Statement The authors have declared no competing interest.

Malignant Pleural Mesothelioma (MPM) is an aggressive cancer with rising incidence and challenging clinical management. Using the largest series of whole-genome sequencing data integrated with transcriptomic and epigenomic data using multi-omic factor analysis, we demonstrate that MPM heterogeneity arises from four sources of variation: tumor cell morphology, ploidy, adaptive immune response, and CpG island methylator phenotype. Previous genomic studies focused on describing only the tumor cell morphology factor, although we robustly find the three other sources in all publicly available cohorts. We prove how these sources of variation explain the biological functions performed by the cancer cells, and how genomic events shape MPM molecular profiles. We show how these new sources of variation help understand the heterogeneity of the clinical behavior of MPM and drug responses measured in cell lines. These findings unearth the interplay between MPM functional biology and its genomic history, and ultimately, inform classification, prognostication and treatment. ![Figure][1]</img> ### Competing Interest Statement Where authors are identified as personnel of the International Agency for Research on Cancer/World Health Organisation, the authors alone are responsible for the views expressed in this article and they do not necessarily represent the decisions, policy or views of the International Agency for Research on Cancer/World Health Organisation. Where authors are identified as personnel of the Centre de Recherche en Cancerologie de Lyon (CRCL), the authors declare no conflict of interests. A.S. participated in expert boards and clinical trials with Astra-Zeneca, BMS, MSD, Roche. N.G. declares consultancy, research support from BMS, Astra-Zeneca, Roche, and MSD. All the other authors declare no conflict of interests. [1]: pending:yes

Abstract. The integration of multiple omics datasets measured on the same samples is a challenging task: data come from heterogeneous sources and vary in s

Whole-genome sequencing of liver microdissections from five healthy individuals and nine with cirrhosis demonstrates the effects of liver disease on the genome, including increased rates of mutation, complex structural variation and different mutational signatures.

Genome sequencing of hundreds of normal colonic crypts from 42 individuals sheds light on mutational processes and driver mutations in normal colorectal epithelial cells.

A recent study on human structural variation indicates insufficiencies and errors in the human reference genome, GRCh38, and argues for the construction of a human pan-genome.

The emergence of Next-Generation Sequencing (NGS) has revolutionized the way of reaching a genome sequence, with the promise of potentially providing a comprehensive characterization of DNA variations. Nevertheless, detecting somatic mutations is still a difficult problem, in particular when trying to identify low abundance mutations such as subclonal mutations, tumour-derived alterations in body fluids or somatic mutations from histological normal tissue. The main challenge is to precisely distinguish between sequencing artefacts and true mutations, particularly when the latter are so rare they reach similar abundance levels as artefacts. Here, we present needlestack, a highly sensitive variant caller, which directly learns from the data the level of systematic sequencing errors to accurately call mutations. Needlestack is based on the idea that the sequencing error rate can be dynamically estimated from analyzing multiple samples together. We show that the sequencing error rate varies across alterations, illustrating the need to precisely estimate it. We evaluate the performance of needlestack for various types of variations, and we show that needlestack is robust among positions and outperforms existing state-of-the-art method for low abundance mutations. Needlestack, along with its source code is freely available on the GitHub plateform: <https://github.com/IARCbioinfo/needlestack>.