Artificial intelligence (AI) methods have multiplied our capabilities to extract quantitative
information from digital histopathology images. AI is expected to reduce workload for human …

The natural history of cancers can be understood through the lens of evolution given that
the driving forces of cancer development are mutation and selection of fitter clones. Cancer …

Cancer is a somatic evolutionary process characterized by the accumulation of mutations,
which contribute to tumor growth, clinical progression, immune escape, and drug resistance …

Background Recent studies have provided a detailed census of genes that are mutated in
acute myeloid leukemia (AML). Our next challenge is to understand how this genetic diversity …

We analysed whole-genome sequences of 560 breast cancers to advance understanding of
the driver mutations conferring clonal advantage and the mutational processes generating …

Myelodysplastic syndromes (MDS) are a heterogeneous group of chronic hematological
malignancies characterized by dysplasia, ineffective hematopoiesis and a variable risk of …

How somatic mutations accumulate in normal cells is central to understanding cancer
development but is poorly understood. We performed ultradeep sequencing of 74 cancer genes in …

Spatial transcriptomic technologies promise to resolve cellular wiring diagrams of tissues in
health and disease, but comprehensive mapping of cell types in situ remains a challenge. …

Cancer develops as a result of somatic mutation and clonal selection, but quantitative
measures of selection in cancer evolution are lacking. We adapted methods from molecular …

… For visual comparison, the number of mutations was scaled to the effective genome size,
defined as the 1/mean(m i /C i ), in which m i is the estimated number of allelic copies of each …