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A combination of high-resolution spatial imaging, spatial proteomics and transcriptional data reveals sparse and heterogeneous bacterial signals in gliomas and brain metastases.

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.

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.

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.

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.

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.

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.

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.

MorphLink is a computational framework that links tissue morphology changes to molecular alterations using spatial omics data, providing intuitive visualisations of cellular behaviours from both structural and molecular perspectives.

Standard mass spectrometry analyses often miss key targets required for phospho-signalling reconstruction. Here, authors present an intelligent data acquisition strategy that combines discovery and targeted analysis in one run and apply it to maximize the information from single spheroids drug screenings.

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.

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.

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.

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.

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.

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.

MISO (MultI-modal Spatial Omics) integrates two or more spatial omics modalities, despite differences in data quality and spatial resolution for improved feature extraction and clustering to reveal biologically meaningful tissue organization.

VCP/p97 is identified as a co-factor to the fusion oncoprotein ASPSCR1::TFE3. They co-localize on chromatin, co-dependent for enhancer looping and transcriptional regulation in alveolar soft part sarcomas and Xp11- rearranged renal cell carcinomas.

Integrating tissue histology with spatial transcriptomics (ST) can significantly enhance the analysis of tumor heterogeneity and the tumor microenvironment (TME). Here, the authors present METI, a computational framework to analyze cancer cells and the complex TME by integrating ST with histology imaging.

Anal mucosal melanoma is a disorder with limited treatment options and is associated with a poor prognosis. The authors describe the case of a 79-year-old man who was diagnosed with stage IV anal mucosal melanoma expressing the KIT Val560Asp mutation, and was treated with surgery, radiotherapy, and a combination of sorafenib and temozolomide therapy. The authors discuss the potential therapeutic use of sorafenib in anal mucosal melanoma patients with specific mutations such as the KIT Val560Asp mutation.

Comprehensive molecular profiles are required to understand and treat sarcomas, which comprise more than 70 different subtypes. Here, the authors profile the genomic landscape of 7494 sarcomas across 44 histologies using targeted panel sequencing and identify potential therapeutic targets.

A prospective analysis of gut microbiome signatures in patients treated with neoadjuvant immunocheckpoint blockade for high risk resectable metastatic melanoma identifies new links between microbiota signatures, dietary intake and systemic inflammation in shaping the response and toxicity to immunotherapy.

Preliminary evidence from two cases suggests that fecal microbiota transplantation may provide a viable treatment option for a severe adverse effect of immune checkpoint blockade therapy in patients with cancer.

The authors summarize the data produced by phase III of the Encyclopedia of DNA Elements (ENCODE) project, a resource for better understanding of the human and mouse genomes.

Immune profiling of the tumour microenvironment of soft-tissue sarcoma identifies a group of patients with high levels of B-cell infiltration and tertiary lymphoid structures that have improved survival and a high response rate to immune checkpoint blockade therapy.

Roland et al. report the results of a randomized, non-comparative phase 2 trial of neoadjuvant nivolumab or a combination of nivolumab and ipilimumab in patients with resectable retroperitoneal dedifferentiated liposarcoma and extremity/truncal undifferentiated pleomorphic sarcoma.

The efficacy of immune checkpoint inhibitors (ICI) in osteosarcoma has been limited. Here, the authors investigate the immunogenomic landscape of osteosarcoma, and integrated analyses highlight features related to a suppressed immune microenvironment.

Anti-cancer treatment often results in a subset of the clonal cell population developing resistance to therapy, with resistant cells displaying a diversity of fate types resulting from the intrinsic variability among the clonal population before treatment.

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.

Treatment with neoadjuvant BRAF/MEK-targeted therapy results in higher rates of major pathological response in female compared with male patients with melanoma, and pharmacological inhibition of androgen receptor signalling improved the responses of male and female mice to BRAF/MEK-targeted therapy.

Androgen receptor can promote tumour progression in desmoplastic small round cell tumour (DSRCT), an aggressive paediatric malignancy that predominantly affects young males. Here, the authors show that DSRCT is an AR-driven malignancy and sensitive to androgen deprivation therapy

The regulation of the distinct intrinsic phenotypic states in melanoma remain poorly characterised. Here, multi-omics analysis for a panel of 68 early passage melanoma cell lines reveals that cancer cell intrinsic transcriptomic programs are associated with distinct immune features.

Quantum neural networks could help analysing the output of quantum computers and quantum simulators of growing complexity. Here, the authors use a 7-qubit superconducting quantum processor to show how a quantum convolutional neural network can correctly recognise the phase of a quantum many-body state.

Analysis of more than 150 Phase 3 oncology clinical trials supports parametric statistical analysis, significantly increasing the precision of small early-phase trials and relating deviations from the Cox proportional hazards model to trial duration.

A cosmological simulation shows that low-mass galaxies can form with far less dark matter than expected, with results matching some observed characteristics. Roughly one-third of massive central galaxies may host at least one such dark-matter-deficient satellite.