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The integration of spatial, imaging, and sequencing information enables the mapping of cellular dynamics within a tissue. Here, authors show three algorithms in stLearn software to accurately reveal spatial trajectory, detect cell-cell interactions, and impute missing 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.

Parity induces an accumulation of CD8⁺ T cells, including cells with a tissue-resident-memory-like phenotype within human normal breast tissue, offering long-term protection against triple-negative breast 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 of tumours from 560 breast cancer cases provides a comprehensive genome-wide view of recurrent somatic mutations and mutation frequencies across both protein coding and non-coding regions; several mutational signatures in these cancer genomes are associated with BRCA1 or BRCA2 function and defective homologous-recombination-based DNA repair.

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.

Stig Bojesen, Georgia Chenevix-Trench, Alison Dunning and colleagues report common variants at the TERT-CLPTM1L locus associated with mean telomere length measured in whole blood. They also identify associations at this locus to breast or ovarian cancer susceptibility and report functional studies in breast and ovarian cancer tissue and cell lines.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

The association between obesity and breast cancer biology remains understudied in humans. Here, using a large retrospective data collection, the authors identify obesity associated changes in the genomic, transcriptomic profile, and the tumor microenvironment of primary untreated breast tumors.

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.

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.

Fine-mapping of causal variants and integration of epigenetic and chromatin conformation data identify likely target genes for 150 breast cancer risk regions.

Mutational signatures provide evidence of the mechanism of action of a given mutagen and are found in cancer cells. Here, using 560 breast cancer genomes, the authors demonstrate that mutational signatures are frequently associated with genomic architecture including nucleosome positioning and replication timing.

An analysis of mutations from over 7,000 cancers of diverse origins reveals the diversity of mutational processes underlying the development of cancer; more than 20 distinct mutational signatures are described, some of which are present in many cancer types, notably a signature attributed to the APOBEC family of cytidine deaminases, whereas others are specific to individual tumour types.

Recent studies using in depth DNA sequencing techniques led to the identification of cancer driver genes but mainly focused on the effect on their expression. Here, the authors analyse 266 cases of breast cancer and report gene expression signatures associated with the number and character of signature mutations.

Basal-like breast cancer is a heterogeneous disease with poor prognosis; however, its cellular origins and aetiology are poorly understood. Here the authors provide evidence that ID4 is a key controller of mammary stem/progenitor cell self-renewal, acting upstream of Notch signalling to repress luminal fate commitment.

Microarray analysis can be used to differentiate gene expression patterns between various types of tumors, including breast tumors caused by BRCA1 and BRCA2 mutations. But what must be done before this technology can be used in the clinic?

Association analysis identifies 65 new breast cancer risk loci, predicts target genes for known risk loci and demonstrates a strong overlap with somatic driver genes in breast tumours.

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

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.

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.

Previous work has identified several genes where mutations lead to breast cancer, but other genetic and environmental factors must still be accounted for. A large study of genetic association with breast cancer points to four novel genes and many more genetic markers that should be pursued for their link to cancer susceptibility.

Germline pseudogenes have an important role in human evolution. Here, the authors analyse sequencing data from 660 cancer samples and find evidence for the formation of somatically acquired pseudogenes, a new class of mutation, which may contribute to cancer development.

A study of breast cancers shows that the number of somatic mutations in each varies markedly and is strongly correlated with age at diagnosis and cancer histological grade.

Whole-genome sequencing of normal blood cells sampled from 241 adults is used to infer mosaic point mutations that are likely to have arisen during early embryogenesis, providing insight into how early cellular dynamics may affect adult tissues.