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The dynamics of breast tissue aging are characterized by imaging mass cytometry of over 500 reduction mammoplasties, revealing nonlinear loss of cellularity and a compositional shift favoring inflammation.

Integrative analysis of copy number and gene expression in 2,000 primary breast tumours with long-term clinical follow-up revealed putative cis-acting driver genes, novel subgroups and trans-acting aberration hotspots that modulate subgroup-specific gene networks.

Single-cell DNA sequencing identifies recurrent copy number changes in healthy breast tissue from women with wild-type or germline BRCA1 or BRCA2 mutations.

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

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.

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.

Sohrab Shah, Samuel Aparicio and colleagues analyze whole genomes and single cells from ovarian cancers in the peritoneal cavity to establish patterns of disease spread. They determine the clonal relationships between multiple tumor sites and characterize the migratory potential of genomically diverse clones.

A single-cell sequencing study using more than 30,000 tumour genomes from human ovarian cancers shows that whole-genome doubling is an ongoing mutational process that drives tumour evolution and disrupts immunity.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

In single-cell RNA-seq analyses, it would be critical to measure the relationships between genes. Here, the authors develop a framework for single-cell dimensionality reduction that incorporates gene-specific relationships - GeneVector -, and use it for tasks such as annotating cell types and analysing pathway variation after treatment.

Primary triple-negative breast cancers are shown to vary widely and continuously in the degree of clonal evolution and mutational content at the time of diagnosis, with implications for future studies of the disease.

G-quadruplex stabilizers, including CX-5461, exhibit synthetic lethality with loss of BRCA1/2 in preclinical models. Here the authors report the results of a phase I study of CX-5461 in patients with solid tumors enriched for DNA-repair deficiencies.

Here the authors develop a probabilistic model for single-cell DNA sequencing of aneuploid tumors that infers clone-specific replication timing and S-phase fractions, unveiling their relationships with copy number evolution and clonal fitness.

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

Bodenmiller and colleagues pair imaging mass cytometry with data from the METABRIC cohort to define single-cell phenotypic and genomic features of breast cancer with spatial context, finding associations with breast cancer subtypes and prognosis.

Esophageal adenocarcinoma is characterised by frequent amplifications in oncogenes. Here, the authors use short- and long-read sequencing approaches to analyze primary tumor samples and tumour-derived organoids and to investigate the mechanisms underlying complex amplifications.

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.

Much effort has recently been devoted to understanding the genomics of breast cancer. In this study, the authors integrate somatic mutation data with previously published copy number aberration and gene expression information for nearly 2,500 breast cancer samples.

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.

Whole-genome sequencing of human cancer cells in patient-derived mouse xenograft models indicates a key role for TP53 in determining the fitness landscape of polyclonal cancer cell populations.

The phosphorylation of serine/arginine-rich proteins by CDC-like kinase is a central regulatory mechanism for RNA splicing reactions. Here, the authors synthesize a novel small molecule CLK inhibitor and map CLK-responsive alternative splicing events and discover an effect on conjoined gene transcription.

Single-cell whole-genome sequencing shows that 'foreground' cell-to-cell structural variation and alterations in copy number are associated with genomic diversity and evolution in triple-negative breast and high-grade serous ovarian cancers.

Understanding the molecular mechanisms underlying DNA methylation in cancer and its clinical relevance remains crucial. Here, the authors study RRBS-based profiles of 1538 breast tumours and 244 normal breast tissues from the METABRIC cohort and report epigenomic instability and cis-regulatory effects.

Meta-analysis of genome-wide association studies on Alzheimer’s disease and related dementias identifies new loci and enables generation of a new genetic risk score associated with the risk of future Alzheimer’s disease and dementia.

The functional changes of individual clones in single cell RNA sequencing (scRNA-seq) data remain elusive. Here, the authors develop PhylEx that integrates bulk genomics data with co-occurrences of mutations revealed by scRNA-seq data and apply it to high-grade serous ovarian cancer cell line and breast cancer datasets.

Single-cell Proliferation Rate Inference in Non-homogeneous Tumors through Evolutionary Routes (SPRINTER) allows users to infer proliferation rates of individual clones within a tumor from single-cell DNA sequencing data. Applying SPRINTER to human tumor datasets highlighted a link between proliferation and metastatic potential.

Gene fitness and essentiality analyses using in vivo cancer models are challenging due to multiple confounders. Here, the authors develop a quantitative approach to study CRISPR-transduced patient-derived xenografts, which they use to analyse in vivo gene fitness in breast cancers and the biological features that influence uncertainty in fitness estimation.

Stabilization of DNA quadruplex structures (G4) is lethal for cells with a compromised DNA repair pathway. Here, the authors show that CX-5461, a small molecule in clinical trials as RNA polymerase inhibitor, has G4-stablization properties and can be repurposed to target DNA repair-defective cancers cells.

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.