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Tumor heterogeneity: preclinical models, emerging technologies, and future applications.
Proietto, Marco; Crippa, Martina; Damiani, Chiara; Pasquale, Valentina; Sacco, Elena; Vanoni, Marco; Gilardi, Mara.
Affiliation
  • Proietto M; Next Generation Sequencing Core, The Salk Institute for Biological Studies, La Jolla, CA, United States.
  • Crippa M; Gene Expression Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, United States.
  • Damiani C; NOMIS Center for Immunobiology and Microbial Pathogenesis, The Salk Institute for Biological Studies, La Jolla, CA, United States.
  • Pasquale V; Vita-Salute San Raffaele University, Milan, Italy.
  • Sacco E; Experimental Imaging Center, Istituti di Ricovero e Cura a Carattere Scientifico (IRCCS) Ospedale San Raffaele, Milan, Italy.
  • Vanoni M; Infrastructure Systems Biology Europe /Centre of Systems Biology (ISBE/SYSBIO) Centre of Systems Biology, Milan, Italy.
  • Gilardi M; Department of Biotechnology and Biosciences, School of Sciences, University of Milano-Bicocca, Milan, Italy.
Front Oncol ; 13: 1164535, 2023.
Article in En | MEDLINE | ID: mdl-37188201
ABSTRACT
Heterogeneity describes the differences among cancer cells within and between tumors. It refers to cancer cells describing variations in morphology, transcriptional profiles, metabolism, and metastatic potential. More recently, the field has included the characterization of the tumor immune microenvironment and the depiction of the dynamics underlying the cellular interactions promoting the tumor ecosystem evolution. Heterogeneity has been found in most tumors representing one of the most challenging behaviors in cancer ecosystems. As one of the critical factors impairing the long-term efficacy of solid tumor therapy, heterogeneity leads to tumor resistance, more aggressive metastasizing, and recurrence. We review the role of the main models and the emerging single-cell and spatial genomic technologies in our understanding of tumor heterogeneity, its contribution to lethal cancer outcomes, and the physiological challenges to consider in designing cancer therapies. We highlight how tumor cells dynamically evolve because of the interactions within the tumor immune microenvironment and how to leverage this to unleash immune recognition through immunotherapy. A multidisciplinary approach grounded in novel bioinformatic and computational tools will allow reaching the integrated, multilayered knowledge of tumor heterogeneity required to implement personalized, more efficient therapies urgently required for cancer patients.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Front Oncol Year: 2023 Document type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Front Oncol Year: 2023 Document type: Article Affiliation country: United States
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