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This study explores the relationship between telomere length and clonal hematopoiesis. Splicing factor and PPM1D gene mutations are more frequent in people with genetically predicted shorter telomere lengths, suggesting that these mutations protect against the consequences of telomere attrition.

Explosive growth is attributed to the BCR::ABL1 gene 3–14 years before diagnosis of chronic myeloid leukaemia, highlighting the oncogenic potency of gene fusion and the slow and sequential trajectories of most other cancers.

Isolating and studying haematopoietic stem cells in young and aged mice demonstrates evolutionary processes related to blood production and provides a framework for interpreting future work using laboratory mice to study stem cell ageing.

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Prostate cancer (PrCa) involves a large heritable genetic component. Here, the authors perform multivariate fine-mapping of known PrCa GWAS loci, identifying variants enriched for biological function, explaining more familial relative risk, and with potential application in clinical risk profiling.

A large meta-analysis combining genome-wide and custom high-density genotyping array data identifies 63 new susceptibility loci for prostate cancer, enhancing fine-mapping efforts and providing insights into the underlying biology.

Rosalind Eeles and colleagues report meta-analysis of genome-wide association studies for prostate cancer and genotyping on the custom iCOGS array in 25,074 cases and 24,272 controls from 32 studies available in the PRACTICAL Consortium. They identify 23 new prostate cancer susceptibility loci, 20 of which are associated with both aggressive and non-aggressive disease.

Sequencing of individual human lymphocyte clones shows that they are highly prone to mutations, with higher burdens in memory cells than in naive cells arising from mutational processes associated with differentiation and tissue residency.

Douglas Easton and colleagues report a comprehensive analysis of SNP associations to prostate cancer across the 8q24 region. They report 8 SNPs in 5 blocks independently associated to prostate cancer risk.

Joint analysis of new and previously published sequencing data for primary and metastatic prostate cancers identifies new candidate driver mutations and provides insights into disease progression and potential drug targets.

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.

Whole-genome sequencing analysis of somatic mutations in liver samples from patients with chronic liver disease identifies driver mutations in metabolism-related genes such as FOXO1, and shows that these variants frequently exhibit convergent evolution.

Mutational signature analysis provides important information about the mutational processes underpinning different stages of tumorigenesis. Here, the authors compare publicly available signature extraction tools and suggest a framework for the generation of accurate and reproducible signature data.

The authors report the mutational landscape of 29 cell types from microdissected biopsies from 19 organs and explore the mechanisms underlying mutation rates in normal tissues.

The factors that are associated with myeloma precursor condition progression are not well understood. Here the authors find that monoclonal gammopathies of undetermined significance and smoldering myelomas that did not progress to multiple myelomas have a distinct genomic profile and emerge later in the patient’s life.

Whole-genome sequencing of normal human endometrial glands shows that most are clonal cell populations and frequently carry cancer driver mutations that occur early in life, and that parity has a protective effect.

Classification and risk-stratification for Acute Myeloid Leukemia (AML) at diagnosis are primarily based on cytogenetics and only a few gene mutations. Here, the authors study the genomic landscape of 3653 AML patients and characterize 16 non-overlapping molecular subgroups of clinical relevance for disease classification and risk prognostication.

The molecular characterisation of germ cell tumours (GCT) is necessary to understand their development and histological diversification. Here, the authors use whole-genome and transcriptome sequencing of GCTs across distinct histologies to reveal their somatic evolution and clonal diversification, as well as identify several putative biomarkers for treatment stratification.

Multiple myeloma evolves continuously. Here the authors chronologically reconstruct driver events in multiple myeloma, noting a limited repertoire of initiating driver events that shape the evolutionary trajectory of the disease.

The initial mutational processes and how these lead to progression in multiple myeloma (MM) are unclear. Here, the authors identify mutational signatures that occur over time in a large cohort of MM patients and suggest features that may help in early diagnosis.

Rosalind Eeles, Christopher Haiman and colleagues report genome-wide association and meta-analyses of prostate cancer in populations of European, African, Japanese and Latino ancestry. They identify 23 new susceptibility loci, including one associated with early-onset prostate cancer.