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Advances in sequencing and genomic technologies are rapidly expanding our understanding of cancer and in turn the role of genomics in clinical oncology. Nature Cancer presents a Series of commissioned Reviews covering the current impact of genomics in guiding cancer diagnosis and treatment, the potential role of emerging technologies, and efforts toward translating new discoveries to the clinic. This collection also includes related primary research articles and News and Views on the topic published by Nature Cancer.
The field of cancer genomics has been advancing at a rapid pace, opening up a wealth of possibilities for translational applications. In this issue, we are excited to launch a Series of commissioned articles that explore the role of genomics in cancer research and oncology, from current achievements to future directions.
Evaluation of circulating tumor DNA in blood has emerged as a powerful technology for oncology research. Lillian Siu and colleagues review the potential applications of liquid biopsy, highlighting clinical-trial designs to establish its clinical utility.
Garnett and colleagues review principles that underpin the pre-clinical development of genomics-guided cancer medicines, challenges that limit their impact, and new opportunities, such as CRISPR-based screening, for refining and extending their use.
Molecular characterization of tumors informs clinical cancer care. Here, Taylor and colleagues review the progress, opportunities, and challenges of scientific and translational discovery that leverages prospective data from clinical genomic screening.
Zhang and Meyerson review exciting advances in methodologies, models and datasets to study noncoding alterations in cancer, new insights into their roles in disease and potential translational implications.
Discerning and analyzing the mutational patterns that arise in the cancer genome can provide essential information on the process of tumorigenesis. An analytical framework and web-based tool now aim to aid in mutational signature assignment for improved tumor stratification.
Tumor heterogeneity remains an obstacle to effective clinical management of breast cancer. Two new studies use high-dimensional imaging of single-cell protein expression in situ in clinical samples to link genomic alterations to multi-cellular features of the tumor microenvironment and reveal breast-cancer phenotypes associated with clinical outcome.
A new suite of studies from the Pan Cancer Analysis of Whole Genomes (PCAWG) Consortium provides the most detailed resolution of cancer genomes to date, extending our knowledge of driver genes, mutational features, structural alterations and more. Kreisberg, Ideker, Mills and Meric-Bernstam discuss the foundational and translational insights gained from this project.
Despite recent advances in cancer treatment, metastasis and therapy resistance remain among the major causes of cancer-related deaths worldwide. A recent pan-cancer study provides a comprehensive molecular profile of advanced and post-therapy tumors, integrating whole-genome and transcriptomic analysis with clinical outcomes.
Anagnostou et al. present an improved predictor of response to immune checkpoint blockade that integrates estimates of tumor mutational burden corrected for tumor purity, RTK genomic alterations, a smoking-related mutational signature and HLA status.
Autry et al. combine genome-wide genomic, epigenetic and transcriptomic analyses in an integrated polygenomic approach to identify mechanisms of glucocorticoid resistance in acute lymphoblastic leukemia.
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.
Diehn and colleagues report that assaying circulating DNA in patients receiving chemoradiation therapy for non-small-cell lung cancer could identify the patients most likely to benefit from consolidation immunotherapy.
Degasperi et al. introduce a practical framework and Signal, an online tool, to analyze mutational signatures. They find evidence of tissue-specific variability in mutational signatures, which may impact tumor classification and clinical application.
Iacobuzio-Donahue and colleagues use integrated transcriptomic, histologic and mutational data to analyze squamous features of pancreatic ductal adenocarcinoma (PDAC), further refining the understanding of heterogeneity and evolution in PDAC.
Aparicio and colleagues identify gene expression changes in breast cancer datasets putatively associated with age-related endocrine effects, suggesting that patient age may influence the prognostic potential of certain biomarkers.