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The molecular mechanisms underlying resistance to therapy in Chronic lymphocytic leukemia (CLL) remain to be explored. Here, the authors perform multi-omics analysis in a mouse model of ibrutinib resistance and suggest proteasome inhibition for overcoming it.

Multi-omics can be used to characterise tumour and immune cell populations. Here the authors use multi-omics to characterise CLL blood and tissue samples and use prediction models for CLL TCR specificity and implicate interactions between galectin-9 and TIM3 as involved in CLL immune escape and propose galectin-9 as a possible immunotherapy target.

Viral pathogen load in cancer genomes is estimated through analysis of sequencing data from 2,656 tumors across 35 cancer types using multiple pathogen-detection pipelines, identifying viruses in 382 genomic and 68 transcriptome datasets.

The mechanisms regulating the balance between proliferation and differentiation in medulloblastomas with extensive nodularity (MBEN) remain poorly understood. Here, single cell multi-omics and spatial analysis characterises the spatial tissue organisation of MBEN in the context of the developmental trajectory.

Analyses of genomes from 914 children, adolescents, and young adults provide a comprehensive resource of genomic alterations across a spectrum of common childhood cancers.

In cancer, associations between mutational signatures and driver mutations have been proposed but not fully explored. Here, the authors develop sigDriver to find associations between mutational signatures and mutation hotspots in order to predict coding and non-coding driver mutations in pan-cancer genomics data.

Chromothripsis (CT) is a type of genome instability which is prevalent in medulloblastoma with germline TP53 mutations (Li-Fraumeni syndrome, LFS). Here the authors combine single-cell genomic and transcriptomic analyses to reveal the clonal heterogeneity and functional consequences of CT in LFS medulloblastoma.

The authors present SVclone, a computational method for inferring the cancer cell fraction of structural variants from whole-genome sequencing data.

Many tumours exhibit hypoxia (low oxygen) and hypoxic tumours often respond poorly to therapy. Here, the authors quantify hypoxia in 1188 tumours from 27 cancer types, showing elevated hypoxia links to increased mutational load, directing evolutionary trajectories.

Analyses of 2,658 whole genomes across 38 types of cancer identify the contribution of non-coding point mutations and structural variants to driving cancer.

With the generation of large pan-cancer whole-exome and whole-genome sequencing projects, a question remains about how comparable these datasets are. Here, using The Cancer Genome Atlas samples analysed as part of the Pan-Cancer Analysis of Whole Genomes project, the authors explore the concordance of mutations called by whole exome sequencing and whole genome sequencing techniques.

Whole-genome sequencing data for 2,778 cancer samples from 2,658 unique donors across 38 cancer types is used to reconstruct the evolutionary history of cancer, revealing that driver mutations can precede diagnosis by several years to decades.

There’s an emerging body of evidence to show how biological sex impacts cancer incidence, treatment and underlying biology. Here, using a large pan-cancer dataset, the authors further highlight how sex differences shape the cancer genome.

The flagship paper of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium describes the generation of the integrative analyses of 2,658 cancer whole genomes and their matching normal tissues across 38 tumour types, the structures for international data sharing and standardized analyses, and the main scientific findings from across the consortium studies.

Integrative analyses of transcriptome and whole-genome sequencing data for 1,188 tumours across 27 types of cancer are used to provide a comprehensive catalogue of RNA-level alterations in cancer.

An analysis of 2,954 genomes from 38 cancer subtypes identified 19,166 retrotransposition events in 35% of samples. Aberrant LINE-1 retrotranspositions can lead to the deletion of tumor-suppressor genes as well as the amplification of oncogenes.

Understanding deregulation of biological pathways in cancer can provide insight into disease etiology and potential therapies. Here, as part of the PanCancer Analysis of Whole Genomes (PCAWG) consortium, the authors present pathway and network analysis of 2583 whole cancer genomes from 27 tumour types.

In somatic cells the mechanisms maintaining the chromosome ends are normally inactivated; however, cancer cells can re-activate these pathways to support continuous growth. Here, the authors characterize the telomeric landscapes across tumour types and identify genomic alterations associated with different telomere maintenance mechanisms.

Analysis of cancer genome sequencing data has enabled the discovery of driver mutations. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium the authors present DriverPower, a software package that identifies coding and non-coding driver mutations within cancer whole genomes via consideration of mutational burden and functional impact evidence.

The characterization of 4,645 whole-genome and 19,184 exome sequences, covering most types of cancer, identifies 81 single-base substitution, doublet-base substitution and small-insertion-and-deletion mutational signatures, providing a systematic overview of the mutational processes that contribute to cancer development.

Whole-genome sequencing data from more than 2,500 cancers of 38 tumour types reveal 16 signatures that can be used to classify somatic structural variants, highlighting the diversity of genomic rearrangements in cancer.

A pan-cancer genomic analysis reports the effects of structural variations on chromatin domains (TADs). Most TAD disruptions do not result in appreciable changes in expression of nearby genes.

Some cancer patients first present with metastases where the location of the primary is unidentified; these are difficult to treat. In this study, using machine learning, the authors develop a method to determine the tissue of origin of a cancer based on whole sequencing data.

Multi-omics datasets pose major challenges to data interpretation and hypothesis generation owing to their high-dimensional molecular profiles. Here, the authors develop ActivePathways method, which uses data fusion techniques for integrative pathway analysis of multi-omics data and candidate gene discovery.

In this study the authors consider the structural variants (SVs) present within cancer cases of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. They report hundreds of genes, including known cancer-associated genes for which the nearby presence of a SV breakpoint is associated with altered expression.

Cancers evolve as they progress under differing selective pressures. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, the authors present the method TrackSig the estimates evolutionary trajectories of somatic mutational processes from single bulk tumour data.

Medulloblastoma is one of the most prevalent malignant brain tumors in children and has very poor prognosis. In this study, the authors show, using a mouse model of medulloblastoma, that Gfi1 promotes tumor growth by recruiting Lsd1, that this interaction inhibits genes involved in neuronal differentiation, and that Lsd1 may be a therapeutic target in Gfi1-activated tumors.

An online approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups has been developed to help to improve current diagnostic standards.

The molecular genetic landscape of leiomyosarcoma (LMS) is largely unknown. Here, the authors identify frequent DNA copy number alterations, whole-genome duplication, TP53 and RB1 inactivation, alternative telomere lengthening, and genomic imprints of defective DNA repair via homologous recombination as a potential therapeutic target in LMS patients.

Genomic analysis of 491 medulloblastoma samples, including methylation profiling of 1,256 cases, effectively assigns candidate drivers to most tumours across all molecular subgroups.

Burkitt lymphoma (BL) is the most common pediatric B-cell lymphoma. Here, within the International Cancer Genome Consortium, the authors performed whole genome and transcriptome sequencing of 39 sporadic BL, describing the landscape of mutations, structural variants, and mutational processes that underpin this disease how alterations on different cellular levels cooperate in deregulating key pathways and complexes.

Gene transfer is a powerful technique to investigate the mechanistic basis of tumorigenesis. Here Zuckermann et al. adapt CRISPR/Cas9 genome editing to target potential oncogenes somatically in vivo, establishing a fast and convenient system for validating novel genetic candidates.

Focusing on two ill-characterized subtypes of medulloblastoma (group 3 and group 4), this study identifies prevalent genomic structural variants that are restricted to these two subtypes and independently bring together coding regions of GFI1 family proto-oncogenes with active enhancer elements, leading to their mutually exclusive oncogenic activation.

Chromothripsis and chromoanasynthesis lead to locally clustered rearrangements affecting one or a few chromosomes, but their impact on cancer development and progression is unclear. Here the authors analyse the role of DNA repair factors in brain tumors by whole-genome sequencing of tumors from mouse models of medulloblastoma or high grade gliomas.

Stefan Pfister and the ICGC PedBrain Tumor Project report whole-genome sequencing of 96 pilocytic astrocytomas. They identify recurrent activating mutations in FGFR1 and PTPN11 and novel NTRK2 fusion genes.

Recurrent histone mutations are linked to paediatric glioblastoma multiforme, an aggressive type of brain tumour.

Genomic studies of the paediatric brain tumour medulloblastoma have revealed four clinically distinct molecular subgroups; here active gene regulatory elements in 28 primary medulloblastoma tissues are mapped to reveal differentially regulated enhancers across the different subgroups, allowing insights into the transcription factors that characterize subgroup divergence and the cellular origin of the poorly characterized Group 3 and 4 subgroups.

Analysis of whole-genome sequencing data across 2,658 tumors spanning 38 cancer types shows that chromothripsis is pervasive, with a frequency of more than 50% in several cancer types, contributing to oncogene amplification, gene inactivation and cancer genome evolution.

Analysis of mitochondrial genomes (mtDNA) by using whole-genome sequencing data from 2,658 cancer samples across 38 cancer types identifies hypermutated mtDNA cases, frequent somatic nuclear transfer of mtDNA and high variability of mtDNA copy number in many cancers.

Efficient, large-scale genomic analysis is facilitated on the cloud by a computational tool with error-diagnosing and self-healing capabilities.

Medulloblastoma is the most common brain tumour in children; using whole-genome sequencing of tumour samples the authors show that the clinically challenging Group 3 and 4 tumours can be tetraploid, and reveal the expression of the first medulloblastoma fusion genes identified.

Super enhancers regulate oncogenes and other molecular targets in ependymomas, and identification of these genes provides potential therapeutic targets.

Medulloblastoma is a malignant childhood brain tumour presenting major clinical challenges; here, a comprehensive genome-wide DNA methylation data set from human and mouse tumours, coupled with analysis of histone modifications, RNA transcripts and genome sequencing, uncovers a wealth of alterations that provide insights into the epigenetic regulation of transcription and genome organization in medulloblastoma pathogenesis.