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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.

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.

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.

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.

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.

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.

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.

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 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.

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.

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.

Chaib et al. find that therapy-induced senescent cells have high programmed cell death 1 ligand 2 (PD-L2), contributing to recurrence. They show that PD-L2 blocking combined with chemotherapy is therapeutically beneficial because it reduces senescent cells and immunosuppressive cell recruitment.

Disease comorbidity is attracting increasing attention, but the involvement of molecular factors in forecasting risk of a disease in the presence of other diseases is poorly understood. Here the authors build a disease interaction network based on gene expression profile and discover new comorbidity relationships in patient subgroups.

The Pan-Cancer Analysis of Whole Genomes project generated a vast array of data. In this article, the authors describe five different online resources to enable readers to explore and visualize the data.

Defining minimal standards for data collection is key to creating interoperative, searchable genomic and clinical databases. We highlight here the 1+Million Genomes Minimal Dataset for Cancer, encompassing 140 items in 8 domains to foster the collection of cancer data, inform transnational cooperation and advance precision cancer medicine.

The molecular mechanisms underlying metastasis in pheochromocytoma/paraganglioma (mPPGL) remain to be explored. Here, the authors perform genomic and immunogenomic profiling of mPPGL tumors and suggest potential biomarkers for risk of metastasis and immunotherapy response.

Fasting has been reported to protect from chemotherapy-associated toxicity. Here, the authors show that fatty acid profiles in erythrocyte membranes and gene expression from peripheral blood mononuclear cells are associated to the fasting-mediated benefits during cancer treatment in mice and patients.

Tumor-secreted midkine modulates immune tolerance in the melanoma tumor microenvironment and determines resistance to immune checkpoint blockade.

A new mouse model is developed in which haematopoietic malignancies are caused by genetic changes in the microenvironment of blood cells. Deletion in bone progenitor cells of Dicer1, a gene involved in microRNA processing, leads to a myelodysplastic syndrome-like phenotype which can progress to leukaemia. Deregulation of Sbds, which is mutated in human Schwachman–Bodian–Diamond syndrome, may be involved in this process.

The authors uncover a new role for the RNA-binding protein Msi2 in the regulation of hematopoietic stem cell homeostasis and leukemogenesis. Msi2 is required for the maintenance of the balance between progenitor renewal and differentiation, and its overexpression cooperates with oncogenic events to induce aggressive leukemia. Msi2 expression is also elevated in human myeloid leukemias and may be a new prognostic marker and therapeutic target in acute myeloid leukemia.

Gold-standard cancer data management is pivotal to enable precision medicine for European citizens. Achieving this goal relies on key elements: adopting standardized data formats, ensuring robust data privacy, educating professionals about the infrastructure’s benefits and leveraging cutting-edge technologies to transform cancer care.

Triple-negative breast cancer (TNBC) lacks prognostic and predictive markers. Here, the authors use phosphoproteomics to define kinases with distinct activity profiles in TNBC, demonstrating their prognostic value as well as their utility for simplifying TNBC classification and designing drug regimens.

High-throughput screening systems that better mimic the physiological complexity of diseased tissues may aid the discovery of more efficacious compounds. A co-culture system that mimics the microenvironment of leukemia stem cells (LSCs) in bone marrow enables the discovery of compounds, including lovastatin, that selectively kill LSCs.

Michael Kharas and colleagues characterize the MSI2 protein interactome in leukemia cells and subsequently perform a functional screen identifying 24 genes required for leukemia in vivo. They focus on the RNA-binding protein SYNCRIP, showing that it regulates Hoxa9 and other transcripts involved in a myeloid leukemia stem cell program.

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.