Patient-derived organoids (PDOs) as a promising platform for personalized treatment of colorectal cancer: current applications and future challenges

ABSTRACT

Colorectal cancer is a heterogeneous and molecularly complex cancer that often leads to poor prognosis. The standard treatment includes surgical resection and adjuvant therapies such as chemotherapy, radiotherapy, targeted therapy, and immunotherapy. However, owing to the individual heterogeneity of patients, the effectiveness of these treatments is difficult to achieve consistently and efficiently. Patient-derived organoids (PDOs), by mimicking key genes, physical, and mechanical cues from the tumor microenvironment, simulates tumor heterogeneity, tissue structure, and molecular characteristics, as well as the cellular interactions within the tumor microenvironment. Additionally, it provides a more physiological and relevant environment for anticancer drug screening and predicting patient responses to personalized approaches, bridging the gap between simplified 2D models and animal models. Here, we review the roles of PDOs in customizing CRC treatment, discussing its roles in predicting drug sensitivity, drug screening, studying drug resistance mechanisms, simulating cell-to-cell interactions, and exploring immunotherapy targets to develop personalized therapies.

1. Instruction

Colorectal cancer (CRC) is the third leading cause of cancer-related deaths globally, with over 1.85 million new cases and 850,000 deaths annually.¹ In China, CRC ranks third in incidence and fifth in mortality among cancers.² Despite continuous advancements in treatment methods, CRC continues to pose significant challenges in clinical practice. The current main methods for treating stage II–IV colorectal cancer include surgical resection, complemented by chemotherapy, radiotherapy, chemotherapy, targeted therapy, and immunotherapy.^3,4 Although current detection methods are becoming increasingly precise, they are still unable to overcome the bottleneck of individual differences. The risk of recurrence within five years after treatment remains as high as 40%, meaning that the traditional “one-size-fits-all” treatment model fails to provide satisfactory prognoses for CRC patients.⁵ There is an urgent need to seek more precise, personalized efficacy prediction models.

In recent years, a new establishment preclinical model, patient-derived organoids (PDOs), has gradually become a research focus, opening new prospects for the personalized treatment of CRC patients. In particular, PDOs provide a powerful research tool for the immunotherapy of CRC by more authentically simulating tumor cells and their key factors in the tumor microenvironment, as well as their interactions with surrounding cells and the stroma. In addition, PDOs provide more similar physiological environments for screening anti-cancer drugs and predicting patient responses to clinical treatment, filling the gap between simple two-dimensional (2D) models and unrepresentative animal models. In this article, we reviewed the applications of PDOs in drug specificity testing, drug resistance testing and screening, the establishment of biological libraries, combined organ chip technology, gene editing and cell therapy in CRC patients to introduce the applications of PDOs in personalized treatment for CRC.

PDOs are a type of three-dimensional cell culture system directly obtained from tumor tissue, adjacent tissues, or metastatic lesions of patients, which are expanded through passaging cultures. The expression patterns of protein markers such as pan-cytokeratin, caudal type homeobox 2 (CDX2), cytokeratin 20 (CK20), and Ki67 can be correlated across parent CRC tissues and organoids by immunohistochemistry (IHC) analysis for identification. Pan-CK is a broad-spectrum epithelial marker, CDX2 is expressed in the majority of colorectal adenocarcinomas, and Ki67 is a cell proliferation marker. Since healthy colon organoids generally exhibit higher growth rates than cancerous organoids, this may lead to excessive proliferation of healthy cells, affecting the outcomes of drug response assays in CRC organoids. Therefore, we have further elaborated on this section, for example, when expanding CRC organoids, selective culture media must be used to promote the growth of tumor organoids, thereby overcoming the overgrowth of healthy cells.⁶ After purification, CRC PDOs can replicate the genomic, proteomic, and morphological characteristics of primary tumors.⁷ Additionally, its stem cell property allows it to self-renew and self-organize, maintaining a genotype and phenotype similar to the original tissue, making it highly suitable for studying tumor recurrence, distant metastasis, and drug resistance in CRC.⁸ Sequencing is used to identify mutations and copy number alterations/variations (CNA/CNV) in the genome or exome. By comparing mutations and CNAs in blood, tumor tissue, and PDOs from the same patient, if the organoid fails to replicate the mutations and CNAs observed in the corresponding parental cancer tissue, it should no longer be used.⁹ The 3D culture procedure of CRC patient-derived organoids (PDOs) is presented in Figure 1.

Figure 1.

3D culture procedure of CRC patient-derived organoids (PDOs). After obtaining tumor tissue from surgical or biopsy specimens of CRC patients, it is segmented into small pieces, cultured in growth factor-supplemented medium, and expanded using trypsin digestion for passage. Once organoid structures are formed, they are incorporated into a culture gel along with immune cells, stromal cells, and fibroblasts for 3D culture, mimicking the real human tumor growth environment used for basic and clinical research.

The first successful cultivation of tumor-derived PDOs was first reported in 2011.¹⁰ To date, several PDO biobanks have been established from various healthy and malignant tissues, including primary and metastatic colorectal cancer,^11,12 breast,¹³ esophageal,¹⁴ pancreatic,¹⁵ and ovarian¹⁶ cancer tissues. These PDO biobanks not only exhibit stable histopathological, genetic, and epigenetic characteristics similar to the original tumors,¹⁷ but more importantly, compared to conventional 2D cell lines and xenograft models, PDOs better reflect tumor heterogeneity between patients and within patients' bodies,¹⁸ with application value superior to animal models. As an innovative experimental model, PDOs have played a significant role in studying the mechanisms, genomics, and antitumor drug screening of CRC, providing an important preclinical modeling platform for tumor biology research and personalized therapy.^19,20 The main applications of CRC PDOs in basic and clinical research are presented in Figure 2.

Figure 2.

Schematic representation of the application of CRC PDOs in basic and clinical research. CRC PDOs application in basic and clinical studies. The roles of PDOs in CRC therapy mainly includes predicting adjuvant and targeted drug sensitivity, investigating drug resistance mechanisms, performing drug screening, exploring immunotherapy targets and establishing PDOs biobanks.

2. Application of PDOs in personalized treatment of CRC

2.1. Using PDOs to test drug specificity

2.1.1. Evaluation of the efficacy of adjuvant chemoradiotherapy

Over the past few decades, adjuvant radiochemotherapy has been widely recognized as the primary treatment method to prevent or treat relapse in stage II–IV CRC patients, significantly improving their life expectancy and prognosis to a certain extent.²¹ However, owing to the lack of effective analytical tools to predict the degree of drug‒patient matching, a large number of patients have not benefited from adjuvant radiochemotherapy and instead experienced severe side effects.²²

PDOs are cultured from the primary tissue of CRC patients, which more closely resembles the patient's real tumor microenvironment. This allows for the detection of the cytotoxic effects of various drugs on CRC cells, thereby accurately predicting the patient's response to treatment options and offering personalized drug choices and therapeutic plans.

In a study by Mao et al. a PDOs biobank was established for 50 CRC patients with liver metastasis, and it was confirmed that the sensitivity prediction of PDOs to FOLFOX or FOLFIRI chemotherapy regimens was associated with clinical response and prognosis.²³ Another study by Smabers et al. suggested that the sensitivity of PDOs to 5-fluorouracil, irinotecan, and oxaliplatin was significantly correlated with the actual treatment response rate in CRC patients, with correlation coefficients of 0.58, 0.61, and 0.60, respectively.²⁴ Additionally, patients with PDOs detected as resistant to oxaliplatin chemotherapy showed a significantly shorter progression-free survival in the originating patients compared to sensitive individuals (3.3 months vs. 10.9 months). Some findings further support the clinical application value of PDOs as drug efficacy predictors. A phase II clinical study demonstrated the feasibility of using PDO drug sensitivity testing to guide the treatment of metastatic CRC patients, with a median progression-free survival of 67 d and a median overall survival of 189 d.²⁵ Another clinical study effectively guided the modification of treatment strategies for two patients, highlighting that one patient achieved partial remission after several unsuccessful conventional chemotherapy trials.²⁰ The applications of PDOs in evaluating the efficacy of adjuvant chemoradiotherapy for CRC are summarized in Table 1.

Table 1.

Applications of CRC PDOs in drug specificity testing.

Functions	Authors	PDOs source of tumor tissue	Sample collection method	Significance	References
Evaluation of the efficacy of adjuvant chemoradiotherapy	Mao et al.	CRC cells	Surgical resection	Sensitivity of PDOs to FOLFOX or FOLFIRI chemotherapy regimens is associated with clinical response and prognosis.	[23]
	Smabers et al.	CRC cells	Surgical resection	PDOs sensitivity to 5-fluorouracil, irinotecan, and oxaliplatin was significantly correlated with the actual treatment response rates in CRC patients.	[24]
	Zhang et al.	CRC cells	Surgical resection	Using cancer tissue-originated spheroids (CTOS) method, organoid-like structures can be established within one week using semi-effective concentration samples, aiming to predict neoadjuvant chemotherapy outcomes in colorectal cancer patients.	[26]
	Jensen et al.	CRC cells, metastatic sites	Surgical resection	Conducted a phase II clinical study and demonstrated the feasibility of PDOs drug sensitivity testing to guide treatment in patients with metastatic CRC with a median progression-free survival of 67 d and a median overall survival of 189 d.	[25]
Evaluate and optimize of the efficacy of targeted therapeutic drugs and their combination therapies	Sophie et al.	CRC cells, liver metastatic tissue	Surgical resection	Dual EGFR pathway blockade in combination with AURKA inhibition may prove effective for second-line treatment of chemo tolerant CRC liver metastases with acquired KRAS mutation and increased AURKA/c-MYC expression.	[27]
	Sander et al.	CRC cells	Surgical resection	Revealed hidden vulnerabilities in phenotypes triggered by treatment.	[28]
	Pensione et al.	CRC cells	Surgical resection	Revealed a mechanism for the effectiveness of EGFR inhibitors in combination therapy for KRAS- and BRAF-mutated CRC patients.	[29]
	Yuan et al.	CRC cells	Surgical resection	Inhibition of JOSD2 by RNA interference or its pharmacological inhibitor promotes the polyubiquitination and proteasomal degradation of KRAS mutants and preferentially impede the growth of KRAS-mutant CRC over that harboring wild-type KRAS.	[30]
Predicting the efficacy of immunotherapy and identifying more effective immunotherapeutic targets	Dijkstra et al.	CRC cells, (Co-cultured with self-derived peripheral blood lymphocytes)	Surgical resection, self-derived peripheral blood	Co-culturing CRC PDOs from individuals with self-derived peripheral blood lymphocytes enhances the presence of tumor-specific T cells, allowing for an assessment of their cytotoxic effects on PDOs, thus forecasting the patient's reaction to cellular immunotherapy.	[31]
	Tristan et al.	CRC cells, (Co-cultured with T and Natural Killer (NK) cells)	Surgical resection, healthy human peripheral blood monocellular cells (PBMCs)	Analyzed heterotypic co-cultures of human CRC PDOs with immune cells and revealed the anti-tumor potential of immunomodulatory antibodies targeting MICA/B and NKG2A.	[28]
	Schnalzger et al.	CRC cells, tumor-adjacent normal colon tissue, (Co-cultured with CAR-NK−92 cells)	Surgical resection	Quantitative assessment of CAR-NK cells' cytotoxic effects on 3D cultured CRC PDOs through luciferase, enabling individualized analysis of CAR therapy's efficacy and tumor precision.	[32]
	Zhao et al.	CRC cells, (Co-cultured with T and dendritic cells)	Surgical resection, healthy human PBMCs	Knockout of miR−424 in extracellular vesicles secreted by CRC cell can amplify the T cell-mediated anti-tumor immune response.	[33]
	Fang et al.	CRC cells, (Co-cultured with tumor-infiltrating lymphocytes (TILs) including monocytes and CD8+T cells)	Surgical resection, self-derived peripheral blood	Indicate that SIRT1 in CRC triggers the movement of tumor-associated macrophages (TAM) via the chemokine C-X-C motif receptor 4/chemokine C-X-C motif ligand 12 (CXCR4/CXCL12) route and suppresses the growth and function of CD8+T cells, thereby accelerating CRC progression.	[34]
	Hutton C et al.	CRC cells and normal colorectal mucosa	Surgical resection	provide a versatile CRC research tool for ex vivo assessment of cell–cell interactions and of long-term responses to therapeutic interventions, potentially in a patient-specific manner.	[35]
	Sheng et al.	CRC cells and liver metastatic tissue derived from colorectal cancer patients	Surgical resection	B7-H3 CAR-T cells effectively controlled tumor growth and metastasis through cytotoxic killing and potential immune regulatory effects.	[36]

In conclusion, the existing evidence has preliminarily suggested that PDOs can effectively predict CRC patients' clinical responses and be used to screen new drugs and optimize current treatment plans, providing more accurate means for accurately evaluating the efficacy of chemotherapy drugs for CRC.

2.1.2. Evaluation and optimization of the efficacy of targeted therapeutic drugs and their combination therapies

Targeted therapy can significantly improve the survival of CRC patients with advanced stage by specifically blocking tumor growth-related molecular pathways. Its application must be based on molecular profiling, emphasizing personalized treatment. Targeted drugs for CRC include epidermal growth factor receptor (EGFR) inhibitors (cetuximab and panitumumab), vascular endothelial growth factor (VEGF) inhibitors (bevacizumab), and human epidermal growth factor receptor 2 (HER2)-targeted therapies (trastuzumab, pertuzumab, or lapatinib), and v-Raf murine sarcoma viral oncogene homolog B (BRAF) inhibitors (encorafenib) for the treatment of CRC patients with various molecular profiles.^37-39

However, RAS mutations predominate in CRC, accounting for 60%, while patients with metastatic left colon cancer harboring RAS mutations exhibit resistance to EGFR receptor inhibitors, resulting in their exclusion from EGFR-specific therapies.^40,41 Due to the insufficient sample size of patients, the majority of studies are unable to conduct a detailed analysis of RAS mutation-specific subtypes. In fact, there are significant differences in drug response between mutation hotspots, and even between variants of specific codons (such as D, V, and C substitutions at G12 and G13, or between the Q61 variants R, L, and K).³⁰ Currently, certain targeted drugs, including sotorasib and adagrasib, have already been developed for patients with KRAS G12C mutations (1%−3% of CRC patients), but they are still in the clinical trial phase.⁴² Sophie et al. confirmed through drug sensitivity testing and analysis of genes in CRC organoid biological collections from tumor and liver metastases that a therapeutic strategy involving dual EGFR pathway blockade in combination with Aurora kinase A (AURKA) inhibition may prove effective for second-line treatment of chemotolerant CRC liver metastases with acquired KRAS mutation and increased AURKA/c-MYC expression.²⁷ Sander and his team used a repurposed drug library to investigate CRC PDOs, with the goal of revealing hidden vulnerabilities in phenotypes triggered by treatment. The assessment was conducted on 414 prospective anti-cancer drugs to determine their ability to modify the cytostatic phenotype triggered by EGFRi/MEKi into cytotoxicity, revealing the uniform efficacy of vinorelbine in a study involving over 25 distinct CRC PDOs, regardless of the RAS mutation status. Additionally, when combined with EGFR/MEK inhibition, it triggered apoptosis throughout the cell cycle and demonstrated both tolerability and potent anti-cancer effects in vivo, laying the groundwork for a clinical study aimed at treating metastatic RAS-mutant CRC patients.²⁸ In another study, Pensione et al. using CRC PDOs, found that the activation of EGFR upstream activity can improve the signal transduction efficiency of the KRAS or BRAF-mutated mitogen-activated protein kinase (MAPK) pathway, revealing a mechanism for the effectiveness of EGFR inhibitors in combination therapy for patients with KRAS- and BRAF-mutated CRC patients.²⁹ In a recent study, Yuan et al. used patient-derived cells/xenografts/organoids (PDCs/PDXs/PDOs) found that the inhibition of JOSD2 by RNA interference or its pharmacological inhibitor promotes the polyubiquitination and proteasomal degradation of KRAS mutants and preferentially impeded the growth of KRAS-mutant CRC over that harboring wild-type KRAS. This finding may facilitate the treatment of a broad population of CRC patients with KRAS variants across different mutant types.³⁰

CRC PDOs can be used for pre-treatment prediction of targeted drug efficacy based on molecular profiling and are expected to further improve the precision of CRC-targeted therapeutic drugs and their combination therapies, expand the range of patients who benefit, and become a powerful tool for research and clinical translational treatments. This hot topic has already been the subject of some ongoing research. The applications of PDOs in evaluating the efficacy of targeted therapeutic drugs are summarized in Table 1.

2.1.3. Predicting the efficacy of immunotherapy and identifying more effective immunotherapeutic targets

Immunotherapy is a significant milestone in cancer treatment. Existing clinical data strongly suggests that immune checkpoint inhibitors can effectively treat metastatic colorectal cancer (CRC), which is characterized by mismatch repair deficiency (dMMR) or high microsatellite instability (MSI-H). However, unfortunately, a large portion of CRC patients (over 85%) are either proficient in mismatch repair (pMMR) or have microsatellite stability (MSS), meaning that this group of patients does not respond to immunotherapy.⁴³ Furthermore, among MSI-H CRC patients, even if immune checkpoint inhibitors can be used, due to the diversity of individual tumor microenvironments, some patients still experience poor treatment responses.⁴⁴ In other words, the therapeutic benefits of immunotherapy in CRC are far from ideal, and testing treatment efficacy before therapy, as well as exploring immune therapy targets suitable for CRC, are important research directions in CRC immunotherapy.

Organoids can integrate components such as stromal cells, blood vessels, and immune cells to simulate the complex microenvironment of primary CRC tumors, revealing the dynamic interaction between tumors and the immune system. This provides a preclinical foundation for evaluating immune checkpoint blockade therapies and various immunotherapies.^45,46 A research from Dijkstra et al. indicated that co-culturing CRC PDOs from individuals with self-derived peripheral blood lymphocytes enhances the presence of tumor-specific T cells, allowing for an assessment of their cytotoxic effects on PDOs, thus forecasting the patient's reaction to cellular immunotherapy.³¹ In another research, Tristan et al. analyzed heterotypic co-cultures of human CRC PDOs with immune cells from self-peripheral blood to assess the infiltration, activation, and function of T and natural killer (NK) cells in human CRC in vitro and they revealed the anti-tumor potential of immunomodulatory antibodies targeting major histocompatibility complex class I chain-related protein A/B (MICA/B) and NK cell lectin-like receptor subfamily C member 1 (NKG2A).⁴⁷ A study by Schnalzger et al. developed a 3D platform for the quantitative assessment of the cytotoxic effects of chimeric antigen receptor (CAR)-natural killer (NK) cells on CRC PDOs through luciferase, enabling personalized analysis of CAR therapy's efficacy and tumor precision.³² Another study revealed that extracellular vesicles secreted by CRC cells can inhibit the costimulatory pathway of T cells and dendritic cells, leading to immune checkpoint blockade of treatment resistance. Knockout of miR−424 in vesicles can amplify the T cell-mediated anti-tumor immune response.³³ In a recent study, Sheng et al. found that B7-H3 CAR-T cells effectively controlled tumor growth and metastasis through cytotoxic killing and potential immunoregulatory effects by using PDOs from primary CRC tumor and liver metastatic tissue.³⁶

It is also possible to track the migration, invasion pathways, and drug resistance signaling pathways of cancer cells through CRC PDOs, providing a research platform for studying immune therapy resistance mechanisms. Fang et al. established a co-culture system involving monocytes, CD8⁺T cells, and PDOs to study the relationships between immune cells and CRC cells. These results indicate that in CRC, SIRT1 triggers the movement of tumor-associated macrophages TAM via the chemokine C-X-C motif receptor 4/chemokine C-X-C motif ligand 12 (CXCR4/CXCL12) pathway and suppresses the growth and function of CD8⁺ T cells, thereby accelerating CRC progression.³⁴ Moreover, the new “mini-colon” model utilizes optogenetics and other technologies to achieve spatiotemporal control of tumorigenesis, supporting long-term observations of the dynamic evolution of the tumor-immune microenvironment at single-cell resolution.^35,48 By co-culturing CRC PDOs with autologous T cells, it is possible to screen for T cells that specifically kill tumor cells, providing a precise model for adoptive cell therapy.⁴⁹ Based on the immune therapy response data from PDOs, personalized immune combination therapies can be designed to target the tumor heterogeneity of individual patients. The applications of PDOs in predicting the efficacy of immunotherapy and identifying more effective immunotherapeutic targets of CRC are summarized in Table 1.

3. Drug resistance testing and screening with PDOs

3.1. Drug resistance testing and mechanism research

CRC-PDOs can simulate the histological and molecular characteristics of primary tumors, including the genome, transcriptome, and tumor microenvironment, and have become the primary models for detecting CRC drug resistance.⁵⁰ Through the application of the PDOs model, researchers have identified several key genes and pathways that may be involved in CRC drug resistance. For example, abnormal expression of genes such as STMN1, VEGFA, and NDRG1 is associated with oxaliplatin resistance.⁵⁰ In another research, Tung et al. used CRC PDOs to demonstrate that resistant CRC cells undergo significant chromatin changes in response to oxaliplatin treatment.⁵¹ Furthermore, metabolic adaptation, activation of the DNA damage response, cell apoptosis defects, and reduced cell aging are also important mechanisms of drug resistance. A study from Ubink et al. revealed that using both mitomycin C and ATR inhibitors together markedly enhances the effectiveness against peritoneal metastasis.⁵² Ubink et al. also discovered that the CMS4 subtype exhibits distinct resistance to gefitinib and SN-38 and identified MET as a potential target.⁵³ Another study revealed that focusing on the leucine-rich repeat-containing G protein-coupled receptor 4-wingless (LGR4-Wnt) signaling route can amplify cell death caused by chemotherapy, thereby overcoming the development of drug resistance.⁵⁴ A recent study published this year by Huang et al. identified a novel stromal-TME crosstalk mechanism wherein Wnt5a restrains CRC progression via TGF-β/NOTUM/OLFM4 signaling. They also found that the combined efficacy of Wnt5a and 5-FU highlights a promising strategy to overcome chemoresistance in CRC chemotherapy.⁵⁵ A new clinical trial investigating PDO screening of radiotherapy-resistant rectal cancer identified a synergistic regimen of EGFR inhibitors and MEK inhibitors, leading to a 40% increase in the tumor regression rate.⁵⁶ The application of PDOs in CRC drug resistance research has developed into a systematic technological pathway and is increasingly being applied in clinical practice and validation, related published results are summarized in Table 2.

Table 2.

Applications of CRC PDOs in drug resistance testing and screening.

Functions	Authors	PDOs source of tumor tissue	Sample collection method	Significance	References
Drug resistance testing	Chen et al.	CRC cells	Surgical resection	Found that abnormal expression of genes such as STMN1, VEGFA, and NDRG1are associated with oxaliplatin resistance.	[50]
	Tung et al.	CRC cells	Surgical resection	Demonstrate that resistant CRC cells undergo significant chromatin changes in response to oxaliplatin treatment.	[51]
	Ubink et al.	Malignant ascites, peritoneal metastases of CRC patient	Surgical resection	Found that using both mitomycin C and ATR inhibitors together markedly enhances the effectiveness against peritoneal metastases.	[52]
	Ubink et al.	CRC cells	Surgical resection	Discovered that the CMS4 subtype of CRC exhibits distinct resistance to gefitinib and SN−38 and identified MET as a potential target.	[53]
	Zheng et al.	CRC cells	Surgical resection	Discovered that focusing on the LGR4-Wnt signaling route can amplify cell death caused by chemotherapy, thereby overcoming the development of drug resistance.	[54]
	Huang et al.	CRC cells	Surgical resection	Identified a novel stromal-TME crosstalk mechanism wherein Wnt5a restrains CRC progression via TGF-β/NOTUM/OLFM4 signaling, and also found that the combinatorial efficacy of Wnt5a and 5-FU highlights a promising strategy to overcome chemoresistance in CRC chemotherapy.	[55]
Drug screening and response prediction	Jung et al.	CRC cells, normal colorectal mucosa	Surgical resection, endoscopy biopsy	PDOs can accurately predict the treatment response of over 80% of metastatic CRC patients receiving irinotecan-based chemotherapy.	[57]
	Kong et al.	CRC cells, normal colorectal mucosa	Surgical resection	Used web-based machine learning methods to identify biomarkers that can accurately predict 114 CRC patients' response to 5-fluorouracil treatment.	[58]
	Chen et al.	CRC cells	Surgical resection	Utilized a point-of-care testing system called acoustically bioprinted patient-derived microtissues (PDMs) to identify biomarkers that can predict patient responses to 5-fluorouracil and cisplatin from pharmacogenomic data of PDOs.	[59]
	Brandenberg et al.	CRC cells, normal colorectal mucosa	Surgical resection	Adopted automated cultivation and analysis techniques, further improved the throughput and consistency of drug screening in the tumor microenvironment.	[60]

3.2. Drug screening and response prediction

PDOs have shown great potential in CRC drug screening and accurate prediction of individual treatment responses.²⁴ A prospective study revealed that PDOs can accurately predict the treatment response of more than 80% of metastatic CRC patients receiving irinotecan-based chemotherapy.⁵⁷ This provides a basis for developing personalized treatment plans, which are expected to improve the clinical benefits of patients. A study used web-based machine learning methods to identify biomarkers that can accurately predict 114 CRC patients' response to 5-fluorouracil treatment and 77 bladder cancer patients' response to cisplatin treatment from the pharmaceutical genomics data of 3D CRC PDOs.⁵⁸ Another study utilized a point-of-care testing system called acoustically bioprinted PDOs that can model cancer invasion and predict treatment response in individual CRC patients to identify biomarkers that can predict patient responses to 5-fluorouracil and cisplatin from the pharmacogenomic data of PDOs. The study also established a correlation between the invasion rate of PDOs and the tumor spread rate of paired patients, providing quantitative indicators for physicians to make decisions on whether to perform anal preservation surgery.⁵⁹ Moreover, by combining with drug libraries or computer prediction, PDOs can also be used for high-throughput drug screening, rapidly evaluating the effects of a large number of drugs on tumor cells, and accelerating the development process of new drugs.^23,57,61,60 In addition, some studies have also adopted automated cultivation and analysis techniques, further improving the throughput and consistency of drug screening in the tumor microenvironment.⁶⁰ In summary, PDOs have advantages in CRC drug screening, but there are still some challenges that need to be addressed, such as the need to further reduce the impact of PDO heterogeneity in drug screening, related published results are summarized in Table 2.

4. Establishment of biological sample library and genetic heterogeneity research

The heterogeneous character of CRC, which involves a range of genomic and epigenetic alterations, is one of the main reasons for unsatisfactory treatment results. In 2015, the CRC consensus molecular subtype (CMS) classification was proposed, which defines four subtypes (CM1–CMS4) based on gene expression patterns. The CMS1 subtype is composed primarily of tumors with high levels of microsatellite instability (MSI) and expression patterns reflecting immune cell infiltration. CMS2 represents a typical subtype with high WNT activity. CMS3 is characterized by abnormal activation of metabolic signaling pathways. Finally, the mesenchymal subtype CMS4 is characterized by high stromal content and poor prognosis.⁶² The establishment of a an PDOs library of CRC patients that can be used to analyze the molecular characteristics of tumors, detect different therapeutic approaches, and investigate potential pathogenic molecules and anticancer therapies¹² has implications for the treatment of CRC. Multiple studies have reported the establishment of PDO biobanks in CRC patients and proposed new findings. Van de et al. established a "live biological sample library" of 20 CRC patients, including organoids from tumor and normal tissue sources, and found that the profile of genetic variation in the biobank was consistent with previous large-scale CRC mutation analysis results.¹² Luo et al. established a large library of intestinal organoids from high-risk colorectal adenoma patients and based on the biobank conducted a series of high-throughput and high-content drug screens to identify four potential drug candidates, namely, metformin, BMS754807, panobinostat and AT9283.⁶³ Linnekamp et al. established an organoid-stroma biobank of a CRC cell line consisting of 30 patients to provide a resource for context dependency in CRC.⁵³ Ubink et al. successfully constructed a biobank of 50 liver metastasis samples and identified several rare molecular phenotypes, such as the PTPRK-RSPO3 fusion gene.¹⁸ A study by Vlachogiannis et al. also indicated that PDOs can replicate patient responses in a clinical setting and can be used for personalized therapies.¹⁴ Existing evidence suggests that PDO biobanks have clinical value in predicting treatment outcomes for individual patients,^14,20 and related published results are summarized in Table 3.

Table 3.

Applications of CRC PDOs in genetic heterogeneity research, gene editing and cell therapy.

Functions	Authors	PDOs source of tumor tissue	Sample collection method	Significance	References
Establishment of biological sample library and genetic heterogeneity research	Van de et al.	CRC cells	Surgical resection, endoscopy biopsy	Established a "live biological sample library" of 20 CRC patients, including organoid from tumor and normal tissue sources, and found that the profile of genetic variation in the biobank was consistent with previous large-scale CRC mutation analysis results.	[12]
	Luo et al.	Normal colorectal mucosa, adenoma tissues	Surgical resection, endoscopy biopsy	Established a large library of intestinal organoids from high-risk colorectal adenoma patients and based on the biobank conducted a series of high-throughput and high-content drug screens to identify four potential drug candidates including metformin, BMS754807, panobinostat and AT9283.	[63]
	Farin et al.	CRC cells, tumor-adjacent normal mucosa	Surgical resection	Established a stromal cell biobank of a CRC cell line consisting of 30 patients to provides a resource for context dependency in CRC.	[53]
	Ubink et al.	CRC cells, liver metastasis	Surgical resection	Constructed a biobank of 50 liver metastases samples and identified several rare molecular phenotypes such as the PTPRK-RSPO3 fusion gene.	[18]
	Vlachogiannis et al.	CRC cells, liver metastasis	Surgical resection	Indicated that PDOs can replicate patient responses in a clinical setting and can be used for personalized therapies	[14]
Gene editing and cell therapy	Roper et al.	CRC cells, liver metastasis	Surgical resection	Presented in vivo characterization of tumor-associated genes and reproduce the entire spectrum of CRC progression and metastasis.	[64]
	Drost et al.	Human intestinal stem cells	Surgical resection	Finding that by editing common oncogenes such as APC and P53 in normal intestinal organ samples, spontaneous tumor formation can be induced	[65]

However, the high cost and enormous workload of establishing and maintaining PDO biobanks are challenges that need to be overcome, especially given the long cultivation times and relatively high failure rates. To overcome these limitations, Zhang et al. used the cancer tissue-originated spheroid (CTOS) method to establish organoids from a heterogeneous population of colorectal cancer specimens. They used half effective concentration gradients to classify CTOS as sensitive or resistant to chemotherapy regimens within a week for predicting neoadjuvant treatment outcomes for colorectal cancer patients, which indicated better practical efficiency.²⁶

5. Construction of disease models and organ chip technology for mechanism research

PDOs can be combined with organ chip technology to mimic "dialogue" between the immune system and tissues, providing a new platform for studying CRC initiation, development, and therapeutic response.^66,67 Compared with traditional in vitro models, organ chips can more accurately control local cellular, molecular, chemical, and biophysical parameters and more flexibly simulate the human CRC microenvironment.⁶⁷ Combining organ chips with PDOs not only replicates the characteristics of the CRC tissue itself but also mimics interactions between CRC cells and stromal cells or other organs to construct more complex and optimized model systems.⁶⁸ For example, one study explored the application prospects of tumor chips in combination with small tissue or organ samples.⁶⁹ In addition, organ chip technology could be used to evaluate the effectiveness of new anti-cancer drugs. By precisely controlling the microenvironmental conditions, organ chips can be used to analyze the effects of various parameters on tumor cell behavior and treatment response.⁶⁷ Some studies have explored the combination of organ chip technology and PDOs for evaluating the effectiveness of new anti-cancer therapies. Meanwhile, the development of biosensors and data analysis tools will promote the application of these models in drug screening and personalized therapy,⁷⁰ and related published results are summarized in Table 3.

At present, the combination of organ chips and PDOs still faces some challenges in CRC research. For example, complex model systems with vascularization and multiorgan functions have been established, and the role of the immune system in tumor occurrence and development has been simulated.^71-73 In the future, by combining with other emerging technologies such as gene editing and 3D bioprinting, it is expected to better simulate the occurrence and development process of CRC,⁷⁴ providing innovative tools for basic research and clinical translation of CRC, and accelerating the development of new drugs and personalized treatment.

6. Gene editing and cell therapy

Multiple studies have shown that using gene editing techniques such as CRISPR/Cas9 to manipulate tumor organoids can reproduce key molecular events related to the occurrence and development of CRC.^64,65,75 For example, spontaneous tumor formation can be induced by editing common oncogenes such as APC and P53 in normal intestinal organ samples.^64,65 This method not only identifies genes associated with cancer but also reproduces the entire process of tumor progression and metastasis. In addition, gene editing technology combined with PDOs can also be used to investigate key tumor biology, such as the clonal dynamics of tumor stem cells and microsatellite instability.^64,75

The current PDOs culture system cannot fully mimic immune cells in the tumor microenvironment,⁷¹ which somewhat limits its application in immunotherapy studies. The existing CRC PDOs are derived mainly from early- to mid-stage patients, while there is a relative lack of research on models for recurrent or metastatic tumors.⁶⁴ Therefore, it is necessary to establish more PDOs systems from metastatic or drug-resistant tumors in the future, combined with gene editing techniques, to more accurately study the molecular mechanisms of the later stages of tumor progression.⁷⁶ The applications of PDOs in gene editing and cell therapy for CRC are summarized in Table 3.

In conclusion, combining gene editing and cell therapy, PDOs provide a promising model platform for precision medicine in CRC. Further progress in this area is expected through sustained technological innovation and model optimization.

7. Conclusions

CRC is a major health issue worldwide, and metastasis, drug resistance, and a lack of immunotherapy have always been obstacles to improving the prognosis of clinical patients. For a long time, owing to the lack of good in vitro research tools, the above problems have not been resolved. PDOs have emerged as a new strategy to improve the predictive value of preclinical research and ultimately contribute to accomplish precise decisions during personalized medicine, saving time and resources. The ability of PDOs to improve important issues, such as the screening of anti-tumoral drug activity, toxicity/therapeutic plans, and the personalized sensitivity to chemotherapy and radiotherapy, is highly desirable. However, PDOs also have several limitations, such as being expensive and time-consuming, and it also have weaknesses in simulating the complexity of the tumor microenvironment, such as the lack of interactions between tumor cells and human immune cells and stromal cells. Future research can focus on the following aspects: 1. Establish a composite organ model containing immune cells to study the relationship between the immune system and CRC; 2. Combining single-cell multi omics techniques to deeply analyze various cellular subpopulations and their molecular mechanisms; 3. Develop standardized and automated organoid culture platforms to improve experimental consistency and reproducibility; 4. Verify the ability of PDOs to predict patient treatment response in larger clinical studies. In conclusion, PDOs holds vast prospects in the personalized treatment of CRC, enabling researchers not only to better understand the biological characteristics of tumors but also to offer patients more precise and personalized treatment plans. However, further in-depth research is still needed to fully tap into its potential in basic and translational research.

Funding Statement

This review was supported by the Noncommunicable Chronic Diseases-National Science and Technology Major Project (No. 2024ZD0531000).

Acknowledgments

We appreciate the help of https://app.biorender.com in figures production. The licenses for publication are provided.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Author contributions

The first draft of the manuscript was written by Xinlu Liu, Yan Liu, Yao Zhang, Ran Zhang, and Chengzhao Zhang. All the authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Data availability statement

The authors declare that all data and materials are included in the references.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Abbreviations

CRC

Colorectal cancer

PDOs

Patient-derived organoids

5-FU

5-fluorouracil

EGFR

Epidermal growth factor receptor

VEGF

Vascular endothelial growth factor

dMMR

Mismatch repair deficiency

pMMR

Mismatch repair proficient

MSI-H

High microsatellite instability

MSS

Microsatellite stable

CTOS

Cancer tissue-originated spheroids

CRISPR Cas9

Clustered regular interval short palindromic repeat related protein 9

DCs

Dendritic cells

MEK

Mitogen-activated protein kinase

MAPK

Mutated mitogen-activated protein kinase

BRAF

v-Raf Murine Sarcoma Viral Oncogene Homolog B

KRAS

Kirsten rats arcomaviral oncogene homolog

MICA/B

Major histocompatibility complex class Ⅰ chain-related protein A/B

NKG2A

NK cell lectin-like receptor subfamily C member 1

ATR

Ataxia telangiectasia and Rad3-related protein

LGR4-Wnt

Leucine-rich repeat-containing G protein-coupled receptor 4-wingless

3D

Three-dimensional

2D

Two-dimensional

NK cells

Natural Killer cells

TAM

Tumor-associated macrophages

CXCR4/CXCL12

Chemokine C-X-C motif receptor 4/chemokine C-X-C motif ligand 12

AURKA

Aurora kinase A