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Whole-genome analysis of oestrogen-receptor-positive tumours in patients treated with aromatase inhibitors show that distinct phenotypes are associated with specific patterns of somatic mutations; however, most recurrent mutations are relatively infrequent so prospective clinical trials will require comprehensive sequencing and large study populations.

A multi-omic analysis of pancreatic cancer identifies spatially resolved, heterogeneous cell populations including transitional cell types. Analysis of primary samples identifies treatment-related changes in cross-talk between tumor and stromal cells.

The sequencing of AML genomes of eight patients before and after relapse reveals two major patterns of clonal evolution, with chemotherapy appearing to have a role in both patterns.

Clonal evolution in multiple myeloma (MM) needs to be understood in both the tumor and its microenvironment. Here the authors perform single-cell multi-omics profiling of samples from MM patients at different stages, finding transitions in the immune cell composition throughout progression.

Analysing the regulatory consequences of mutations and splice variants at large scale in cancer requires efficient computational tools. Here, the authors develop RegTools, a software package that can identify splice-associated variants from large-scale genomics and transcriptomics data with efficiency and flexibility.

Massively parallel DNA sequencing allows entire genomes to be screened for genetic changes associated with tumour progression. Here, the genomes of four DNA samples from a 44-year-old African-American patient with basal-like breast cancer were analysed. The samples came from peripheral blood, the primary tumour, a brain metastasis and a xenograft derived from the primary tumour. The findings indicate that cells with a distinct subset of the primary tumour mutation might be selected during metastasis and xenografting.

Published sequencing data sets of cancer samples could be used to identify genetic variants associated with the risk of developing cancer. Here, Luet al. analyse over 4,000 tumour-normal pairs to reveal variable frequencies of inherited susceptibilities across 12 cancer types and find enrichment of functionally validated missense variants of unknown significance.

As part of The Cancer Genome Atlas Pan-Cancer effort, data analysis for point mutations and small indels from 3,281 tumours and 12 tumour types is presented; among the findings are 127 significantly mutated genes from cellular processes with both established and emerging links in cancer, and an indication that the number of driver mutations required for oncogenesis is relatively small.

Ovarian cancer is one of the most common cancers in women and has an average 5-year survival of only 43%. Here, Kanchi et al.describe the germline and somatic mutation spectrum in ovarian cancer patients and identify potential risk variants associated with the disease.

As guidelines, therapies and literature on cancer variants expand, the lack of consensus variant interpretations impedes clinical applications. CIViC is a public-domain, crowd-sourced and adaptable knowledgebase of evidence for the clinical interpretation of variants in cancer, designed to reduce barriers to knowledge sharing and alleviate the variant-interpretation bottleneck.

The Cancer Genome Atlas Network describe their multifaceted analyses of primary breast cancers, shedding light on breast cancer heterogeneity; although only three genes (TP53, PIK3CA and GATA3) are mutated at a frequency greater than 10% across all breast cancers, numerous subtype-associated and novel mutations were identified.

The field of cancer genomics has been transformed by recent advances in sequencing and the development of new computational methods. This Review outlines the available cancer genomics software and describes recent insights gained from the application of these tools.

The authors develop a new method to mine genomic cancer data to uncover complex indels. These simultaneous deletions and insertions have been over-looked by previous sequencing data analysis methods, and the Pindel-C algorithm uncovers new information about their potential contribution to tumorigenesis.

Systematic analysis of cancer-associated mutations in the blood cells of healthy individuals.

Current clinical practice is organized according to tissue or organ of origin of tumors. Now, The Cancer Genome Atlas (TCGA) Research Network has started to identify genomic and other molecular commonalities among a dozen different types of cancer. Emerging similarities and contrasts will form the basis for targeted therapies of the future and for repurposing existing therapies by molecular rather than histological similarities of the diseases.

The Human Pangenome Reference Consortium aims to offer the highest quality and most complete human pangenome reference that provides diverse genomic representation across human populations.

The imminent release of tissue atlases combining multichannel microscopy with single-cell sequencing and other omics data from normal and diseased specimens creates an urgent need for data and metadata standards to guide data deposition, curation and release. We describe a Minimum Information about Highly Multiplexed Tissue Imaging (MITI) standard that applies best practices developed for genomics and for other microscopy data to highly multiplexed tissue images and traditional histology.