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Lineage tracing in mice identifies a subpopulation of basal cells that express Tmprss2 and Nkx3 as the origin of ERG-driven prostate cancer. Upon expansion, these cells show an enrichment for STAT3 chromatin binding and elevated expression of KMT2A and DOT1L as dependencies for ERG oncogenicity.

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

Similarities in cancers can be studied to interrogate their etiology. Here, the authors use genome-wide association study summary statistics from six cancer types based on 296,215 cases and 301,319 controls of European ancestry, showing that solid tumours arising from different tissues share a degree of common germline genetic basis.

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

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.

Breast cancer risk for BRCA1/BRCA2 mutation carriers varies depending on other genetic factors. Here, the authors perform a case-only genome-wide association study and highlight novel loci associated with breast cancer risk for BRCA1/BRCA2 mutation carriers.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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 principal mid-visible light-harvesting system in cyanobacteria is the phycobilisome. Now, using broadband multidimensional spectroscopy, delocalized vibronic excitations and sub-picosecond excitation transfer pathways have been observed in the rods of intact phycobilisomes. An observed kinetic bottleneck in the phycobilisome’s core arises from the intramolecular charge-transfer character of the bilin chromophores, enabling photoregulatory processes to operate on the >10-ps timescale.

Over 170 susceptibility loci have been identified by genome-wide association studies in breast cancer. Here, the authors interrogated the role of risk-associated variants from non-breast tissue, and using expression quantitative trait loci, identify potential target genes of known breast cancer susceptibility variants, as well as 11 regions not previously known to be associated with breast cancer risk.

An integrated transcriptome, genome, methylome and proteome analysis of over 200 lung adenocarcinomas reveals high rates of somatic mutations, 18 statistically significantly mutated genes including RIT1 and MGA, splicing changes, and alterations in MAPK and PI(3)K pathway activity.

PPM1D is a known mediator of p53 signalling, and has been linked to treatment resistance in glioma. In this work, the authors utilise genomics, proteomics, and mouse models to determine the role of PPM1D in the development of diffuse midline glioma.

Paul Pharoah and colleagues report the results of a large genome-wide association study of ovarian cancer. They identify new susceptibility loci for different epithelial ovarian cancer histotypes and use integrated analyses of genes and regulatory features at each locus to predict candidate susceptibility genes, including OBFC1.

The Cancer Genome Atlas Research Network reports an integrative analysis of more than 400 samples of clear cell renal cell carcinoma based on genomic, DNA methylation, RNA and proteomic characterisation; frequent mutations were identified in the PI(3)K/AKT pathway, suggesting this pathway might be a potential therapeutic target, among the findings is also a demonstration of metabolic remodelling which correlates with tumour stage and severity.

Christopher Haiman and colleagues report a genome-wide association study for estrogen receptor (ER)-negative breast cancer in women of African and European ancestry. They identify a variant at the TERT-CLPTM1L locus on 5p15 as associated with ER-negative and triple-negative breast cancer. This locus also harbors multiple variants associated with a range of other cancers.

Comprehensive analyses of 178 lung squamous cell carcinomas by The Cancer Genome Atlas project show that the tumour type is characterized by complex genomic alterations, with statistically recurrent mutations in 11 genes, including TP53 in nearly all samples; a potential therapeutic target is identified in most of the samples studied.

A region on chromosome 19p13 is associated with the risk of developing ovarian and breast cancer. Here, the authors genotyped SNPs in this region in thousands of breast and ovarian cancer patients and identified SNPs associated with three genes, which were analysed with functional studies.

Although activated Notch receptors have been associated with chemoresistance in cancer, the role of specific Notch ligands remain elusive. Here, the authors show that in breast cells the Notch ligand DLL1 is expressed in cells with a cancer stem cell phenotype and promote doxorubicin resistance in part through NF-kB, as well as metastasis.

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.

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.

The mechanism by which PTEN mutation is melanomagenic is complicated by different PTEN functions in different cellular locations. Here, the authors identify an alternative to membrane PI3K–AKT signalling, a caveolin-1-dependent PTEN pathway that induces nuclear localization and activation of β-catenin.

Faster, higher throughput antibody engineering methods are needed. Here the authors present CeVICA, a cell-free nanobody engineering platform using ribosome display and computational clustering analysis for in vitro selection; they use this to develop nanobodies against the RBD of SARS-CoV-2 spike protein.

In breast cancer the contribution of different genetic variants to disease heritability is complex and not fully understood. Here, the authors present a network-based analysis in 84,567 patients studying ~7.3 million variants, identifying gene modules associated with breast cancer survival.

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.

Genome-wide analysis identifies 32 loci associated with breast cancer susceptibility, accounting for estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade.

Roger Milne and colleagues conduct a genome-wide association study for estrogen receptor (ER)-negative breast cancer combined with BRCA1 mutation carriers in a large cohort. They identify ten new risk variants and find high genetic correlation between breast cancer risk for BRCA1 mutation carriers and risk of ER-negative breast cancer in the general population.

Montserrat Garcia-Closas and colleagues report a meta-analysis of three genome-wide association studies for estrogen receptor (ER)-negative breast cancer, including 4,193 ER-negative breast cancer cases and 35,194 controls, with replication using the iCOGS custom genotyping array in 40 studies, including 6,514 cases and 41,455 controls. They identify four loci associated with ER-negative but not ER-positive breast cancer.

This analysis provides 108 noncoding CRISPR screens collated by the ENCODE4 consortium and establishes experimental guidelines for future CRISPRi screens characterizing functional cis-regulatory elements.