MorphoITH: a framework for deconvolving intra-tumor heterogeneity using tissue morphology

Abstract Background Tumor evolution, driven by the emergence of genetically and epigenetically distinct subclones, enables cancers to adapt to selective pressures and become more aggressive, posing a major challenge in oncology. Multi-regional sequencing has been the primary means of studying tumor...

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Hlavní autoři:	Aleksandra Weronika Nielsen, Hafez Eslami Manoochehri, Hua Zhong, Vandana Panwar, Vipul Jarmale, Jay Jasti, Mehrdad Nourani, Dinesh Rakheja, James Brugarolas, Payal Kapur, Satwik Rajaram
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	BMC 2025-09-01
Edice:	Genome Medicine
Témata:	Deep learning Artificial intelligence Kidney cancer CcRCC Tumor morphology Tumor evolution
On-line přístup:	https://doi.org/10.1186/s13073-025-01504-x
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