Patient-derived organoids for precision oncology in colorectal cancer: from tumor modeling to clinical translation.
4 affiliations
- 1INOC - Istituto Nazionale Oncologico Candiolo; IRCCS, Viale della Ricerca 7, Torino, Candiolo, 10060, Italy.
- 2Department of Oncology, University of Torino, Torino, Candiolo, 10060, Italy.
- 3INOC - Istituto Nazionale Oncologico Candiolo; IRCCS, Viale della Ricerca 7, Torino, Candiolo, 10060, Italy. [email protected].
- 4Department of Oncology, University of Torino, Torino, Candiolo, 10060, Italy. [email protected].
Abstract
Precision oncology in colorectal cancer (CRC) has been profoundly informed by genomic and transcriptomic profiling, yet molecular stratification remains only partially predictive of therapeutic benefit. This reflects a broader challenge: moving from static molecular information to dynamic, adaptive, and time-resolved predictions of drug response for individual patients along their clinical history. In CRC, this challenge is compounded by extensive inter- and intratumoral heterogeneity, clonal evolution, chromosomal instability, phenotypic plasticity and tumor-microenvironment (TME) interactions, all of which reshape therapeutic vulnerabilities over time.Patient-derived organoids (PDOs) have emerged as a functional platform to address this gap, with CRC providing one of the most fertile contexts for their development and application. By preserving key histopathological, molecular, and phenotypic features of parental tumors while remaining experimentally tractable, expandable, and amenable to pharmacological and genetic perturbation, PDOs add a functional layer to precision oncology in CRC. Living organoid biobanks and ex vivo screening studies have shown that PDOs can capture interpatient heterogeneity, uncover mechanisms of sensitivity and resistance, and, in selected contexts, mirror clinical responses to chemotherapy and targeted agents. The same experimental tractability has made these systems powerful tools for investigating tumor initiation and clonal evolution, while enabling exploration of cellular plasticity through the lens of dynamic cellular hierarchies. In parallel, next-generation CRC organoid systems incorporating stromal and immune components may extend functional testing to TME-dependent processes, including response to immunotherapy.In this review, we discuss the conceptual foundations of organoid technology and its emergence as a functional precision oncology platform in CRC. We examine how CRC organoids have advanced understanding of tumor initiation, evolution, chromosomal instability, and phenotypic plasticity; summarize their applications in drug discovery, therapy-response prediction, and resistance modeling; and highlight the development of next-generation multicellular organoid systems incorporating immune and stromal components. Finally, we address the major technical, biological, and clinical challenges that must be overcome to translate PDO-based approaches into robust and clinically actionable tools for precision medicine.
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BibTeX
@article{lupo2026patientderived,
title = {{Patient-derived organoids for precision oncology in colorectal cancer: from tumor modeling to clinical translation.}},
author = {Barbara Lupo and Irene Catalano and Livio Trusolino},
journal = {Molecular cancer},
year = {2026},
month = jul,
doi = {10.1186/s12943-026-02747-x},
url = {https://europepmc.org/article/MED/42897542},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Patient-derived organoids for precision oncology in colorectal cancer: from tumor modeling to clinical translation.
AU - Barbara Lupo
AU - Irene Catalano
AU - Livio Trusolino
PY - 2026
DA - 2026/07/01
JO - Molecular cancer
DO - 10.1186/s12943-026-02747-x
UR - https://europepmc.org/article/MED/42897542
AB - Precision oncology in colorectal cancer (CRC) has been profoundly informed by genomic and transcriptomic profiling, yet molecular stratification remains only partially predictive of therapeutic benefit. This reflects a broader challenge: moving from static molecular information to dynamic, adaptive, and time-resolved predictions of drug response for individual patients along their clinical history. In CRC, this challenge is compounded by extensive inter- and intratumoral heterogeneity, clonal evolution, chromosomal instability, phenotypic plasticity and tumor-microenvironment (TME) interactions, all of which reshape therapeutic vulnerabilities over time.Patient-derived organoids (PDOs) have emerged as a functional platform to address this gap, with CRC providing one of the most fertile contexts for their development and application. By preserving key histopathological, molecular, and phenotypic features of parental tumors while remaining experimentally tractable, expandable, and amenable to pharmacological and genetic perturbation, PDOs add a functional layer to precision oncology in CRC. Living organoid biobanks and ex vivo screening studies have shown that PDOs can capture interpatient heterogeneity, uncover mechanisms of sensitivity and resistance, and, in selected contexts, mirror clinical responses to chemotherapy and targeted agents. The same experimental tractability has made these systems powerful tools for investigating tumor initiation and clonal evolution, while enabling exploration of cellular plasticity through the lens of dynamic cellular hierarchies. In parallel, next-generation CRC organoid systems incorporating stromal and immune components may extend functional testing to TME-dependent processes, including response to immunotherapy.In this review, we discuss the conceptual foundations of organoid technology and its emergence as a functional precision oncology platform in CRC. We examine how CRC organoids have advanced understanding of tumor initiation, evolution, chromosomal instability, and phenotypic plasticity; summarize their applications in drug discovery, therapy-response prediction, and resistance modeling; and highlight the development of next-generation multicellular organoid systems incorporating immune and stromal components. Finally, we address the major technical, biological, and clinical challenges that must be overcome to translate PDO-based approaches into robust and clinically actionable tools for precision medicine.
SN - 1476-4598
ER -