Replication data for: The spatial landscape of Cancer Hallmarks reveals patterns of tumor ecology and drug sensitivity

No description.This dataset contains spatial transcriptomics data used to analyze the spatial distribution of biological processes associated with cancer hallmarks in human tumor samples. The data come from untreated primary tumors from multiple cancer types and allow the study of gene expression ac...

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Detalles Bibliográficos
Autores: Porta-Pardo, Eduard, Esteller, Manel, Grases Mendoza, Daniela, Musulen, Eva, Sibai, Mustafa
Tipo de recurso: conjunto de datos
Fecha de publicación:2026
País:España
Institución:Consorci de Serveis Universitaris de Catalunya (CSUC)
Repositorio:CORA.Repositori de Dades de Recerca
OAI Identifier:oai:dnet:cora.rdr____::97d45044f8b484fda0e9061cfab48c2a
Acceso en línea:https://doi.org/10.34810/DATA3067
Access Level:acceso abierto
Palabra clave:Medicine, Health and Life Sciences
CP
cancer
cancer hallmarks
drug sensitivity
ecosystem
intratumoral heterogeneity
spatial transcriptomics
tumor microenvironment
Descripción
Sumario:No description.This dataset contains spatial transcriptomics data used to analyze the spatial distribution of biological processes associated with cancer hallmarks in human tumor samples. The data come from untreated primary tumors from multiple cancer types and allow the study of gene expression activity across different regions of the tumor and its surrounding microenvironment. The dataset includes gene expression matrices, spatial coordinates associated with each measurement point, and sample metadata. These data enable the identification of spatial patterns of molecular activity, comparison of functional organization across tumors, and exploration of the relationship between tumor heterogeneity and characteristics of the tumor microenvironment. The dataset may be useful for researchers in bioinformatics, cancer biology, and spatial transcriptomics who aim to study the molecular organization of tumors, develop spatial analysis methods, or investigate relationships between tumor biological processes and treatment response.