The EACR’s ‘Highlights in Cancer Research’ is a regular summary of the most interesting and impactful recent papers in cancer research. Previously known as our Top 10 Cancer Research Publications, it is curated by the Board of the European Association for Cancer Research (EACR).
The list below appears in no particular order, and the summary information has been provided by the authors unless otherwise indicated.
Use the dropdown menu or ‘Previous’ and ‘Next’ buttons to navigate the list.
Erickson, A., He, M., Berglund, E. et al. Nature 608, 360–367 (2022).
doi: 10.1038/s41586-022-05023-2.
Summary of the findings
Defining the transition from benign to malignant tissue by molecular principles will be fundamental to improving the early diagnosis of cancer. In the paper by Erickson A. et al., we describe the first step to generate a view of the genome integrity in situ using spatial transcriptomics. Spatial transcriptomics provides a high-resolution map of the entire transcriptome over thousands of areas (spots), enabling us to infer gains and losses of genomic information at unprecedented spatial resolution. Our approach provided comprehensive insights into clonal relationships focused on prostate cancer. Excitingly, we reveal using spatial genome-wide copy number variation (CNVs) analysis that distinct clonal patterns exist not only within tumors, but also in nearby healthy tissue. This allowed us to establish evolutionary clone trees from healthy benign tissue, via altered benign to multiclonal tumors. Importantly the phylogenetic tree could be overlayed on tissue architecture. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. The study also demonstrated the spatial landscape of CNVs in breast, brain, and skin cancer.
Future impact
We highlight the power of an unsupervised approach to capture molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms. Our spatially resolved analysis of clonal dynamics overcomes many of the shortcomings of previous ‘bulk’ sequencing analyses of tissue specimens, with particular applications in the diagnostic space. When linked to metastatic disease, we believe this holds the power to predict at near cellular resolution which clones have the potential to spread, thereby informing prognosis and treatment selection, for example with selection of regions for targeting with focal therapies, or monitoring with MRI imaging.
