Insights on the differences between two‑ and three‑dimensional culture systems in tumor models (Review)
- Authors:
- Published online on: September 4, 2025 https://doi.org/10.3892/ijmm.2025.5626
- Article Number: 185
-
Copyright: © Zhang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
Abstract
Introduction
Malignant tumors have imposed a notable burden on human society (1). Despite extensive efforts in cancer management (2-4), effective treatments and early diagnosis remain crucial to reducing cancer-related mortality. Advances in novel chemical compounds and neoadjuvant targeted therapies offer promise. Progress in tumor therapy and diagnosis depends on fundamental tumor biology studies, often using in vitro and in vivo models. Tumor cell culture is a fundamental technique with broad applications, including investigations into biological properties and drug screening.
The first human cancer cell line, HeLa, was established from a cervical carcinoma tissue in 1951 (5,6). Subsequently, numerous cancer cell lines have been successfully established, including ovarian (7), breast (8), colorectal (9), pancreatic (10), prostate (11), kidney (12) and bladder (13) carcinoma cell lines. HeLa cells, which are readily available and commonly cultured in two-dimensional (2D) monolayers, serve as vital preclinical models in cancer biology-related research and drug development. However, emerging three-dimensional (3D) culture techniques enable the formation of HeLa spheroids that mimic in vivo tumor characteristics and exhibit distinct behaviors to a greater extent, such as increased drug resistance compared with 2D cell culture (14-18). These differences are attributed to factors such as cytoskeletal reorganization (16), overexpression of specific genes (SLC2A1, ALDOC and PFKFB4) driving drug resistance (17), and the ability to model tumor microenvironment (TME) complexity, such as through co-culture with fibroblasts (18).
Whilst 2D culture systems, valued for their simplicity and low cost, have notably contributed to cancer therapy, the limitations are increasingly recognized. Results from 2D models often fail to predict patient responses due to the lack of cell-cell/cell-matrix interactions and altered metabolism and gene expression when cancer cells are cultured on a plane plastic or glass bottle/dish (19,20). Moreover, 2D models cannot capture the inherent heterogeneity of in vivo tumors, which comprise diverse cell types, such as cancer stem cells (CSCs), differentiated cancer cells, stroma cells, immune cells and fibroblasts (21-23).
Consequently, more representative research models are needed. 3D culture approaches, including a large class of culture methods, also called 'organoid' culture technologies, have been exploited (24-27). Based on a 3D structure formed by Hydrogel or artificial scaffold, cell lines are capable of self-renewal and differentiation, for example embryonic stem cells, induced pluripotent stem cells and cancer cell lines, can be propagated to generate organoids in 3D culture medium with special bioactive proteins (28). 3D organoids can maintain the architectural characteristics, gene expression profiles, signal pathways and drug sensitivities of the primary tissues (24,29-32). Therefore, 3D organoids appear to be more effective research implements for cancer related investigations.
Currently, different types of 3D culture systems are being researched, and there is mounting interest in the field of drug discovery, drug screening and tumor biology research (29,33-36). Patient derived cells, induced pluripotent stem cells, patient derived tissue and commercial cancer cell lines are the main sources of organoid generation (28). Due to the easy propagation and convenient manipulation of cancer cell lines, several research teams have used immortalized cancer cell lines to construct tumor 3D spheroids or organoids for scientific investigations (37-39). Moreover, drastic changes in 3D organoid cells have been reported when comparing the same cell lines cultured in 2D models (40-44).
To improve the understanding of the underlying mechanisms, the present review describes the recent progress in tumor 3D organoid development and systematically evaluates the alterations in gene expression profiles, metabolism and response to chemotherapy during the transition from 2D to 3D culture.
Progress and status of 3D tumor culture
There has been notable progress in 3D tumor organoid technology for cancer research (45). Tumor 3D organoids are in vitro multicellular structures derived from resected tumor tissues or types of cells capable of self-renewing, including immortalized cancer cell lines, induced pluripotent stem cells and CSCs. One of the earliest 3D multicellular spheres was established in 1907 by Wilson (46). Subsequently, 3D-culture technologies have continuously evolved (Fig. 1).
Current 3D organoid generation methods fall into two main categories: Scaffold-free and scaffold-based technologies. Among scaffold-free approaches, the hanging droplet method is widely utilized. This technique relies on gravity to enable suspended cancer cells in culture medium droplets to proliferate, polarize and self-assemble into spheroids (47,48). Its simplicity and replicability make it popular for spheroid formation (49,50). However, scaffold-based systems are increasingly favored, as they are more effective at replicating the critical cell-to-extracellular matrix (ECM) essential for physiological functions. Currently, diverse biomaterials are applied for scaffolds, such as type-I collagen (51,52), polymeric nanofiber (53), hyaluronic acid (54,55), laminin-rich ECM (lrECM) (56,57), gelatin (42,58,59), poly-Caprolactone (60), poly-Hydroxyethyl Methacrylate (poly-HEMA) (61-63) and Matrigel (64,65). A landmark advancement occurred in 2009 with the development of a Matrigel-based 3D intestinal organoid system by Sato et al (66) using LGR5-positive adult intestinal stem cells. When LGR5+ intestinal stem cells were propagated in this Matrigel culture system, certain essential growth factors, such as EGF, FGF, Wnt3a, Noggin, R-spondin 1 and N-acetylcysteine, triggered a number of signal pathways to facilitate cells to proliferate, differentiate, alter the gene expression files and phenotype to form intestinal crypt-villus units. This foundational protocol has since been adapted to generate diverse organoids associated with the liver (67,68), lung (69,70), colorectal (71-73), gastric (74-77), pancreatic (78-80), prostate (81-85), kidney (86,87) and breast (88,89).
Previous research has focused on establishing 3D organoid/spheroid systems; future studies should prioritize developing more physiologically relevant models. Emerging integrated platforms offer promise. The tumor-on-chip, which combines microfluidic chips, integrates dynamic flow, ECM, cancer cells to simulate vascularized microenvironments (90), and enable real-time study of metastasis mechanisms (91), immune-tumor interactions (92), high-throughput drug screening via concentration gradient systems (93). Furthermore, 3D bioprinting enables precise spatial patterning of multicellular components critical for tumor modeling: tumor cells establish core malignancy (94,95); stromal cells-including cancer-associated fibroblasts (96) and adipocytes (97)-reconstruct the TME; and vascular networks facilitate nutrient/immune cell delivery (98). Notably, this technology enhances drug resistance in multicellular models vs. monocultures (94,95). Furthermore, patient-derived bioinks enable personalized drug response prediction (99).
Whilst in vivo testing, particularly patient-derived xenografts (PDXs) in mice, remains a preclinical standard for retaining tumor histology and heterogeneity, it faces limitations. Mouse stromal and immune cells rapidly replace human counterparts in PDX models, creating a microenvironment distinct from human tumors (100). 3D tumor organoids offer a compelling alternative. By simulating tumor heterogeneity, microenvironment components, vascularization and immune interactions, complex human-derived organoid models show notable potential to reduce reliance on animal testing. This aligns with the ethical 3R principles (Replacement, Reduction and Refinement) mandated by regulatory frameworks.
In summary, platform selection must align with research objectives, balancing physiological fidelity against practical constraints (Table I). High-throughput drug screening prioritizes scalability: Scaffold-free systems (such as hanging drop and micropatterned arrays) enable higher throughput than bio-printed models (47-50,93) but simplify microenvironment complexity. TME interaction studies require ECM integration: Matrigel-based organoids (66) or bio-printed co-cultures (94-97) restore cell-matrix signaling yet introduce batch variability (65) or bioink artifacts (101). Immunotherapy or metastasis research demands dynamics: Microfluidic chips with endothelial barriers optimally model immune cell trafficking and shear stress (90-92), despite increased costs compared with static systems. Personalized medicine relies on patient fidelity: Bio-printed patient-derived organoids better preserve human stroma than PDXs (100) but require >4 weeks culture periods, limiting acute clinical utility. Collectively, optimal platform choice necessitates strategic trade-offs among physiological relevance, throughput, cost and timeline.
Distinct biological properties of 3D tumor models
Cancer cells cultured in 3D systems exhibit distinct biological behaviors and morphology compared with 2D systems. A hallmark change is a reduced proliferation rate and cell viability across several cancer types (Table II). For example, 3D spheroids of HCT-116 (a metastatic colorectal carcinoma cell line) have demonstrated downregulated DNA replication/cell cycle genes and reduced Ki-67 expression compared with 2D monolayers (102). Moreover, colorectal (56), breast (103), osteosarcoma (103), Ewing sarcoma (60), hepatocellular carcinoma (104) and neuroblastoma (105) cells consistently demonstrate lower proliferation in several 3D systems. Furthermore, breast cancer cell viability in poly-HEMA 3D scaffolds was reported to be <50% of 2D levels (106). Migration has also been reported to decrease in breast cancer and osteosarcoma cells cultured in 3D conditions (103).
Notably, multiple myeloma (MM) cells have been reported to proliferate faster in 3D tissue-engineered bone marrow models than in 2D (107); however, MM proliferation decreases in Matrigel-based 3D systems (108,109), highlighting model-dependent effects.
3D tumor culture also induces profound cellular structural changes. Breast cancer cells undergo marked chromatin reorganization in Matrigel 3D systems (43). Lung and head and neck carcinoma cell lines exhibit altered morphology, cytoskeletal architecture and increased heterochromatin in 3D compared with in 2D models (110). This is associated with reduced histone H3 acetylation and elevated HP1-α expression. These structural modifications may contribute to enhanced cells survival under stress, such as radiation therapy, by reducing DNA double-strand breaks and lethal chromosomal aberrations.
In summary, transitioning to 3D culture typically reduces cancer cell proliferation and viability. However, MM demonstrates a significant deviation from this trend: within bone-like 3D microenvironments, MM cells display accelerated proliferation-markedly diverging from their inhibited proliferation in Matrigel cultures. This divergence exposes a fundamental constraint: Proliferative outcomes are scaffold-dependent, challenging the dogma that 3D culture intrinsically inhibits growth. Additionally, 3D spatial organization induces chromatin compaction, a structural change that diminishes DNA damage susceptibility and enhances treatment resistance. Although this improved simulation of in vivo stress adaptation is valuable, it introduces a key compromise: 3D systems may disproportionately amplify resistance pathways whose clinical relevance remains uncertain.
Phenotypic alterations in 3D cultured cells
Cell culture conditions markedly influence cellular morphology and phenotype. Unlike 2D systems, 3D spheroids or organoids can more effectively recapitulate the cell-to-cell and cell-to-ECM interactions of parent tissue, enabling cancer cells to maintain morphological and (epi)genetic heterogeneity. Crucially, transitioning cancer cell lines from 2D to 3D culture usually induces a shift towards mesenchymal and stem cell phenotypes (Table III). In colorectal cancer, HT-29 (a P53 gene mutated, K-RAS wild type, microsatellite stable colorectal carcinoma cell line) organoids exhibit elevated αSMA (a mesenchymal marker) and loss of E-cadherin (an epithelial marker) in comparison with their 2D counterparts (53). Additionally, HT-29 and HCT-116 tumor organoids have demonstrated increased expression of Snail, an epithelial-mesenchymal transition (EMT) marker, at both the transcription and protein level in comparison with 2D cultures. HCT-116 organoids display strong N-cadherin (a mesenchymal marker) staining, absent in 2D. Key proteins (ZO1, β-catenin, E-cadherin and vinculin) translocate from membrane interfaces in 2D to cytoplasm/nucleus in 3D, implicating pathways such as WNT/β-catenin in EMT (111). Epithelial ovarian carcinoma spheroids also show loss of E-cadherin and gain of vimentin, confirming EMT (112).
Furthermore, HT-29 tumor organoids express CSC markers including NANOG, OCT4, LGR5 and SOX2. HCT-116 organoids demonstrate increased aldehyde dehydrogenase enzyme activity, which was also a hallmark of CSC, compared with in 2D culture. Additionally, MMP9 (an aggressiveness marker) expression is elevated in HCT-116 3D cultures compared with in 2D, suggesting enhanced invasiveness. Furthermore, epithelial ovarian carcinoma spheroids show increased MMP9 immunofluorescence, indicating greater aggressiveness in 3D (112).
In summary, 3D-culture systems uniquely preserve the heterogeneity of parental tissue, facilitating the expression of clinically relevant phenotypes (EMT, stemness and invasiveness), often absent in 2D. This phenotypic fidelity necessitates careful selection of culture models for research associated with cell phenotype and morphology.
Altered gene and protein expression in 3D cell culture
Cell culture conditions markedly impact gene and protein expression profiles associated with cell function and physiology (Table IV). Notably, 3D systems are more effective at replicating tissue-specific functions. HepG2 or HepaRG cell lines regain hepatocellular functions and metabolic capabilities in 3D systems, showing upregulated gluconeogenesis enzymes (G6Pase and PEPCK2), lipid metabolism genes (apoB, apoE and apoA-I) and phase I/II xenobiotic-metabolizing enzymes (such as CYP3A4, CYP1A2, UGT1A1 and UGT1A6) (42,104,114). Furthermore, the expression of tumor-related genes (for example ALB, AFP, CD133, IL-8 and β-TGF) are enhanced in HepG2 spheroids.
3D culture induces widespread expression shifts. Colorectal carcinoma spheroids generated by HCT-116 cells have been reported to upregulate hypoxia and adhesion genes but downregulate DNA replicate and cell cycle genes compared with in 2D culture (102). Breast cancer spheroids have demonstrated elevated cytochrome p450 enzymes and P-glycoprotein related to drug metabolism (106). Moreover, 3D breast cancer models have been reported to exhibit increased apoptotic markers such as caspase 3/7/9, decreased pErk (viability), yet elevated survival proteins including Akt, pAkt, Erk and EGFR family members (106,113). Hypoxia in spheroid cores also drives HIF-1 induction, activating multi-drug resistance-1 gene (coding P-glycoprotein) and its targets, including PDK1, PGK1 and VEGF (113).
In other cancer type 3D culture research, differential expression of genes has been detected between 2D and 3D cells. For example, oral squamous cell carcinoma cell spheroids have been reported to upregulate interleukin 8 expression (115). Furthermore, in an Ewing sarcoma 3D culture model, IGF-1R, phosphorylated IGF-1R, c-kit and HER2 were notably higher than in the 2D monolayer culture (60). Neuroblastoma 3D spheroids also exhibit an elevated expression of HER4 (105). In addition, a marked transcriptomic and epigenetic divergence has been reported by single cell analysis methods when pancreatic adenocarcinoma cell lines were cultured in 3D conditions (23).
Taken together, 3D culture environments could alter gene/protein expression, enabling cells to recapitulate the functions and physiology of original tissue in vitro. However, these advantages are offset by inherent limitations. A primary concern is the hypoxic core within 3D spheroids, which disproportionately induces HIF-1-mediated drug resistance pathways (for example, MDR-1, PDK1 and VEGF), potentially distorting therapeutic response predictions. Furthermore, attempts to model in vivo complexity can generate model-specific distortions: Breast cancer systems may exhibit conflicting survival signals (simultaneous pro-apoptotic caspase activation and pro-survival Akt/EGFR upregulation), whilst Ewing sarcoma models display amplified IGF-1R/HER2 signaling that could exaggerate perceived target vulnerabilities. Single-cell analyses add another layer of complexity, revealing that 3D-induced transcriptomic and epigenetic heterogeneity can mask critical subpopulation dynamics, complicating interpretation. Consequently, whilst 3D platforms overcome fundamental metabolic limitations of 2D cultures, their variable oxygen gradients and context-driven pathway activation necessitate rigorous context-dependent validation for translational relevance.
Differential signaling pathway in 3D culture
Cell culture surroundings have substantial impact on cell behaviors and functions, largely mediated by alterations in gene expression and signal pathway (44). As depicted in Fig. 2, the alterations in signal pathways are mainly concentrated on the downstream of the EGFR family pathways and WNT/β-catenin pathway.
WNT/β-catenin signaling, one of the most common pathways involved in EMT, is elevated when cancer cell lines are transferred from 2D to 3D culture (44,111,116). In 3D liver-colorectal hybrid carcinoma organoids constructed by Skardal et al (111), WNT/β-catenin pathway activation participated in negatively regulating the viability and proliferation rate of colorectal cancer cells, whilst no such phenomena were detected in the corresponding 2D cultured cells (111). In addition, WNT/β-catenin pathway activation also promoted colorectal cell resistance to 5-FU in 3D liver-tumor organoids. In comparison with 2D cultures, colorectal cancer cells within an ECM-derived hydrogel 3D culture system (117) and breast cancer poly-HEMA spheroids (106,118) presented higher levels of total EGFR and phosphorylated EGFR. By contrast, EGFR signal pathways were suppressed in colorectal cancer cells under 3D lrECM circumstances by decreased levels of EGFR and phosphorylated EGFR (56).
Other signal pathways involved in regulating cell proliferation, survival and metabolism, are also reported to be differentially activated between cells in 3D and 2D cultures. Reduced PI3K/mTOR signaling in 3D osteosarcoma cells lowers proliferation and motility (103). Conversely, elevated levels of total Akt and phosphorylated Akt were detected, indicating upregulation of PI3K/Akt signal pathways in poly-HEMA 3D cultures established by Breslin and O'Driscoll (106). Protein expression levels of IGF-1R and phosphorylated IGF-1R were also reported to be upregulated in 3D cultured Ewing sarcoma cells compared with in cells in 2D plastic, suggesting augmented IGF-1R/mTOR signaling in 3D scaffolds (60). Additionally, angiogenesis signal pathways, such as VEGF, hepatocyte growth factor and IL-8, could be induced by hypoxia and at a higher level in MM 3D cultures compared with in 2D cultures. Moreover, pathways in which MAPK is involved are found at different levels of activity in cells between 3D and 2D culture conditions. The rates of phosphorylated and total p42/p44 MAPK are elevated in colorectal carcinoma cell lines (HT-29, SW480 and CACO-2) within 3D conditions (56,117). In 3D lrECM, breast cancer cell line AU565 cells have been reported to exhibit activation of MAPK pathway as phosphorylation of MEK1/2 not Akt is detected. By contrast, in 2D cultures, only Akt is phosphorylated. Notably, for the SKBR3 cell line, both PI3K/Akt and RAS/MAPK pathways were reported to be activated in 2D conditions, whereas in 3D lrECM, SKBR3 cells only demonstrated activation of the RAS-MAPK pathway in line with AU565 cells in 3D lrECM. Based on binding with its ligand, HER2 supports cell proliferation and survival by activation of the lower tyrosine kinase through RAS-to-MAPK and PI3K-to-Akt pathways, respectively (119-121). In accordance with the aforementioned results, raised activation of MAPK and attenuated PI3K/Akt signal pathways caused by HER2 homodimerization have been reported in breast cancer cell spheroids compared with in 2D cell culture (118). Furthermore, Weigelt et al (57) reported that culture systems had an impact on PI3K/Akt and RAS/MAPK pathways, even without the participation of HER2. However, the level of phosphorylated HER2 was attenuated in 3D lrECM compared with in 2D cultures.
The transition from 2D to 3D culture significantly alters oncogenic signaling pathways, though scaffold-specific variations complicate mechanistic extrapolation. WNT/β-catenin activation consistently promotes EMT and chemoresistance across 3D models. By contrast, EGFR responses show marked scaffold dependence: Signaling amplifies in hydrogel/poly-HEMA matrices but attenuates in lrECM, directly linking extracellular matrix composition to receptor regulation. Similarly, PI3K/Akt pathway activity varies contextually. It is reduced in osteosarcoma 3D models yet elevated in poly-HEMA breast cancer spheroids and Ewing sarcoma 3D scaffolds. Notably, 3D architectures can uncouple canonical pathway hierarchies, as demonstrated by lrECM-induced MAPK activation concurrent with PI3K/Akt suppression in HER2 positivity breast cancer, independent of HER2 engagement. These observations collectively suggest that pathway rewiring arises from complex ECM-receptor-integrin crosstalk rather than dimensional change alone, highlighting the need for standardized scaffold characterization to enhance translational relevance.
Changes in drug response under 3D culture environment
Drug discovery and screening serve an important role in the fields of personal and precise medicine. Whilst 2D cell culture remains prevalent, its models often exhibit oversensitivity to drug treatment compared with the parental tissue in vivo due to the lack of cell-cell and cell-ECM interaction. This discrepancy drives the adoption of 3D research models, where altered expression of drug metabolism genes, including cytochrome p450 enzymes, p-glycoprotein and EGFR family members, leads to distinct drug responses in 2D models (Fig. 2 and Table V) (42,95,113-115).
In comparison with 2D models, 3D colorectal cancer cell culture generally shows a marked increase in resistance to classes of chemotherapeutic agents, targeting DNA synthesis and repairment, including platinum-based drugs, 5-FU, melphalan and irinotecan (38,102,111,117). Similarly, several types of anticancer drugs, such as platinum-based drugs, monoclonal antibodies, multityrosine kinase inhibitors and other chemical drugs, are often more effective in breast carcinoma cells cultured in 2D plane systems than the 3D counterparts (57,106,113,122,123). Furthermore, other types of cancer, including lung (124-127), liver (42,128), ovarian (112,118), oral (129), bladder (130), endometrial (131), pancreatic carcinoma (132), MM (107), Ewing sarcoma (60) and neuroblastoma (105), are usually more responsive to chemotherapeutics in 3D culture circumstances than in 2D conditions.
Notably, multi-kinase inhibitors targeting downstream VEGFR, FGR and EGFR receptor pathways, such as regorafenib, sorafenib, dabrafenib and trametinib, induce a higher degree of cell death in 3D culture systems than 2D cultures (117). As the expression of HIF-1 is augmented in 3D culture, tirapazamine, which is an inhibitor targeting the HIF-1 downstream pathway, has been reported to have higher efficacy in 3D culture than in 2D (133). Moreover, trastuzumab, a commercial monoclonal antibody against HER-2 downstream pathway, has exhibited higher efficacy against the HER2-amplified cell line AU565 under 3D lrECM than in 2D cultures (57). However, the efficacies of kinase inhibitors, regorafenib, AG148 and AG1478, were reduced in 3D CRC cell system compared with in a 2D model, due to reduced EGFR expression in IrECM (40,56,57). Trastuzumab has also been shown to be ineffective against SKBR3 cells in 3D lrECM due to downregulated HER2 phosphorylation (57).
The drug reaction is associated with the 3D culture matrix. Goudar et al (40) co-cultured HCT-8 colorectal cancer cell line with NIH3T3 fibroblasts to set up 3D chimeric tumor spheroids (CTSs), which were associated with a decline in EGFR expression as fibroblasts can secrete several types of ECM including type-I collagen and laminin (134,135). A further study demonstrated that the CTSs had enhanced resistance to tyrosine kinase inhibitors, in line with the aforementioned results (56). 3D SKBR3 cells in poly-HEMA culture system regain trastuzumab sensitively as 3D poly-HEMA conditions support anchorage-independent cell growth under the absence of an artificial ECM (117). Additionally, acinar polarity, which exists in cells 3D lrECM, is not observed in 3D poly-HEMA culture systems, highlighting the crucial influence of the ECM.
In summary, 3D-culture systems better replicate in vivo drug response profiles than 2D models, particularly for conventional chemotherapeutics where heightened resistance reflects clinical observations across multiple carcinomas. However, significant context-dependent variations exist. Targeted therapeutics exhibit class-specific divergence: Multi-kinase inhibitors (regorafenib/sorafenib) and hypoxia-activated agents (tirapazamine) demonstrate superior efficacy in 3D environments, whereas certain tyrosine kinase inhibitors and monoclonal antibodies show reduced activity due to ECM-mediated receptor modulation. Crucially, ECM biochemistry governs therapeutic outcomes: IrECM suppresses HER2/EGFR signaling and drug sensitivity, whilst scaffold-free poly-HEMA systems preserve target vulnerability. This matrix-driven heterogeneity necessitates rigorous microenvironmental characterization in preclinical studies to ensure accurate interpretation of drug responses. Standardized documentation of scaffold properties would substantially improve translational predictability.
Conclusions and future perspectives
The present review compares key differences in cell phenotypes, behaviors, gene expression profiles, signal pathways and drug sensitivities between 2D and 3D cancer cell cultures. 3D tumor culture systems directly address the fundamental limitations of 2D models-artificial metabolism, loss of tumor heterogeneity and poor clinical predictability-by reconstructing critical TME elements: Cell-matrix interactions, spatial architecture and hypoxia gradients. This transformative advancement evolves from early spheroids to contemporary scaffold-defined organoids, enabling physiologically relevant carcinoma modeling. Crucially, 3D platforms restore malignancy hallmarks absent in 2D systems: Preserved tumor heterogeneity, EMT progression, stemness programs (OCT4/SOX2) and hypoxia-driven resistance (HIF-1/MDR-1). Whilst therapeutic predictability improves significantly for conventional agents such as 5-FU, matrix-dependent efficacy variations in targeted therapies (for example, lrECM-diminished HER2 inhibition) represent persistent modeling challenges that require resolution.
Nevertheless, persistent constraints reintroduce the very biases 3D systems aim to resolve: Microenvironmental artifacts from amplified hypoxia hyperactivate resistance pathways, whilst biomaterial inconsistencies (Matrigel variability, bioink artifacts) compromise reproducibility. The scaffold-response paradox-exemplified by context-dependent proliferation kinetics in MM (bone-mimetic enhancement vs. Matrigel suppression) and opposing EGFR pharmacodynamics-highlights fundamental complexities in tumor modeling. Translational barriers similarly mirror historical gaps: Extended patient-derived organoid maturation (>4 weeks) hinders clinical adoption, whilst multidimensional heterogeneity risks obscuring critical subclones as noted in single-cell analyses.
Addressing these challenges necessitates: i) Standardization via synthetic ECM and quantitative material registries (mechanical/ligand/degradation metrics) to resolve biomaterial limitations; ii) Dynamic integration of vascularized microfluidics-bioprinting hybrids mitigating hypoxia artifacts, combined with immunocompetent interfaces for immunotherapy screening; iii) Clinical translation acceleration employing automation to compress workflows to <2 weeks, validated by spatial multi-omics. This interdisciplinary convergence will ultimately deliver on 3D modeling's original promise articulated in the introduction: Bridging the translational gap through quantifiable, patient-specific therapeutic platforms that transform precision oncology.
Availability of data and materials
Not applicable.
Authors' contributions
GJZ, QDL and YSW designed the review. GJZ and QDL collected the citations and drafted the manuscript. YFW mainly helped to revise the manuscript. YSW revised the manuscript. All authors read and approved the final version of the manuscript. Data authentication in not applicable.
Ethics approval and consent to participate
Not applicable.
Patient consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Acknowledgments
Not applicable.
Funding
The present study was supported by the Sichuan Science and Technology Program (grant nos. 2025ZNSFSC0578 and 2025ZNSFSC0601).
References
|
Kratzer TB, Jemal A, Miller KD, Nash S, Wiggins C, Redwood D, Smith R and Siegel RL: Cancer statistics for American Indian and Alaska Native individuals, 2022: Including increasing disparities in early onset colorectal cancer. CA Cancer J Clin. 73:120–146. 2023. | |
|
Kuderer NM, Desai A, Lustberg MB and Lyman GH: Mitigating acute chemotherapy-associated adverse events in patients with cancer. Nat Rev Clin Oncol. 19:681–697. 2022. View Article : Google Scholar : PubMed/NCBI | |
|
Ruffin AT, Li H, Vujanovic L, Zandberg DP, Ferris RL and Bruno TC: Improving head and neck cancer therapies by immunomodulation of the tumour microenvironment. Nat Rev Cancer. 23:173–188. 2023. View Article : Google Scholar : | |
|
Kist de Ruijter L, van de Donk PP, Hooiveld-Noeken JS, Giesen D, Elias SG, Lub-de Hooge MN, Oosting SF, Jalving M, Timens W, Brouwers AH, et al: Whole-body CD8+ T cell visualization before and during cancer immunotherapy: A phase 1/2 trial. Nat Med. 28:2601–2610. 2022. View Article : Google Scholar : PubMed/NCBI | |
|
Adey A, Burton JN, Kitzman JO, Hiatt JB, Lewis AP, Martin BK, Qiu R, Lee C and Shendure J: The haplotype-resolved genome and epigenome of the aneuploid HeLa cancer cell line. Nature. 500:207–211. 2013. View Article : Google Scholar : PubMed/NCBI | |
|
Gey GO, Coffman WD and Kubicek MT: Tissue culture studies of the proliferative capacity of cervical carcinoma and normal epithelium. Cancer Res. 12:264–265. 1952. | |
|
Sekiya S, Kaiho T, Shirotake S, Iwasawa H, Inaba N, Kawata M, Higaki K, Ishige H, Takamizawa H, Minamihisamatsu M and Kuwata T: Establishment and properties of a human choriocarcinoma cell line of ovarian origin. In Vitro. 19:489–494. 1983. View Article : Google Scholar : PubMed/NCBI | |
|
Keydar I, Chen L, Karby S, Weiss FR, Delarea J, Radu M, Chaitcik S and Brenner HJ: Establishment and characterization of a cell line of human breast carcinoma origin. Eur J Cancer (1965). 15:659–670. 1979. View Article : Google Scholar : PubMed/NCBI | |
|
Machida S, Ishioka T, Takashima K, Fukushima M, Ishikawa Y and Kudo H: Establishment of a human rectal cancer cell line producing carcinoembryonic antigen. Gan. 68:775–780. 1977.PubMed/NCBI | |
|
Akagi T and Kimoto T: Establishment and characteristics of a human pancreatic cancer cell line (HCG-25). Acta Pathol Jpn. 27:51–58. 1977.PubMed/NCBI | |
|
Koochekpour S, Maresh GA, Katner A, Parker-Johnson K, Lee TJ, Hebert FE, Kao YS, Skinner J and Rayford W: Establishment and characterization of a primary androgen-responsive African-American prostate cancer cell line, E006AA. Prostate. 60:141–152. 2004. View Article : Google Scholar : PubMed/NCBI | |
|
Weber KL, Pathak S, Multani AS and Price JE: Characterization of a renal cell carcinoma cell line derived from a human bone metastasis and establishment of an experimental nude mouse model. J Urol. 168:774–779. 2002. View Article : Google Scholar : PubMed/NCBI | |
|
Russell PJ, Jelbart M, Wills E, Singh S, Wass J, Wotherspoon J and Raghavan D: Establishment and characterization of a new human bladder cancer cell line showing features of squamous and glandular differentiation. Int J Cancer. 41:74–82. 1988. View Article : Google Scholar : PubMed/NCBI | |
|
Jakubowicz-Gil J, Paduch R, Gawron A and Kandefer-Szerszeń M: The effect of heat shock, cisplatin, etoposide and quercetin on Hsp27 expression in human normal and tumour cells. Folia Histochem Cytobiol. 40:31–35. 2002.PubMed/NCBI | |
|
Pai JH, Xu W, Sims CE and Allbritton NL: Microtable arrays for culture and isolation of cell colonies. Anal Bioanal Chem. 398:2595–2604. 2010. View Article : Google Scholar : PubMed/NCBI | |
|
Ho VHB, Müller KH, Barcza A, Chen R and Slater NKH: Generation and manipulation of magnetic multicellular spheroids. Biomaterials. 31:3095–3102. 2010. View Article : Google Scholar | |
|
Wang T, Wang X, Zheng X, Guo Z, Mohsin A, Zhuang Y and Wang G: Overexpression of SLC2A1, ALDOC, and PFKFB4 in the glycolysis pathway drives strong drug resistance in 3D HeLa tumor cell spheroids. Biotechnol J. 19:e24001632024. View Article : Google Scholar : PubMed/NCBI | |
|
Chen T, Wen Y, Song X, Zhang Z, Zhu J, Tian X, Zeng S and Li J: Rationally designed β-cyclodextrin-crosslinked polyacrylamide hydrogels for cell spheroid formation and 3D tumor model construction. Carbohydr Polym. 339:1222532024. View Article : Google Scholar | |
|
Schuth S, Le Blanc S, Krieger TG, Jabs J, Schenk M, Giese NA, Büchler MW, Eils R, Conrad C and Strobel O: Patient-specific modeling of stroma-mediated chemoresistance of pancreatic cancer using a three-dimensional organoid-fibroblast co-culture system. J Exp Clin Cancer Res. 41:3122022. View Article : Google Scholar : PubMed/NCBI | |
|
Brancato V, Oliveira JM, Correlo VM, Reis RL and Kundu SC: Could 3D models of cancer enhance drug screening? Biomaterials. 232:1197442020. View Article : Google Scholar : PubMed/NCBI | |
|
Liebs S, Eder T, Klauschen F, Schütte M, Yaspo ML, Keilholz U, Tinhofer I, Kidess-Sigal E and Braunholz D: Applicability of liquid biopsies to represent the mutational profile of tumor tissue from different cancer entities. Oncogene. 40:5204–5212. 2021. View Article : Google Scholar : PubMed/NCBI | |
|
Contartese D, Salamanna F, Veronesi F and Fini M: Relevance of humanized three-dimensional tumor tissue models: A descriptive systematic literature review. Cell Mol Life Sci. 77:3913–3944. 2020. View Article : Google Scholar : PubMed/NCBI | |
|
Kallinowski F, Zander R, Hoeckel M and Vaupel P: Tumor tissue oxygenation as evaluated by computerized-pO2-histography. Int J Radiat Oncol Biol Phys. 19:953–961. 1990. View Article : Google Scholar : PubMed/NCBI | |
|
Shi R, Radulovich N, Ng C, Liu N, Notsuda H, Cabanero M, Martins-Filho SN, Raghavan V, Li Q, Mer AS, et al: Organoid cultures as preclinical models of non-small cell lung cancer. Clin Cancer Res. 26:1162–1174. 2020. View Article : Google Scholar | |
|
Cattaneo CM, Dijkstra KK, Fanchi LF, Kelderman S, Kaing S, van Rooij N, van den Brink S, Schumacher TN and Voest EE: Tumor organoid-T-cell coculture systems. Nat Protoc. 15:15–39. 2020. View Article : Google Scholar | |
|
Xu H, Lyu X, Yi M, Zhao W, Song Y and Wu K: Organoid technology and applications in cancer research. J Hematol Oncol. 11:1162018. View Article : Google Scholar : PubMed/NCBI | |
|
van de Wetering M, Francies HE, Francis JM, Bounova G, Iorio F, Pronk A, van Houdt W, van Gorp J, Taylor-Weiner A, Kester L, et al: Prospective derivation of a living organoid biobank of colorectal cancer patients. Cell. 161:933–945. 2015. View Article : Google Scholar : PubMed/NCBI | |
|
Drost J and Clevers H: Organoids in cancer research. Nat Rev Cancer. 18:407–418. 2018. View Article : Google Scholar : PubMed/NCBI | |
|
Zhang Y, Houchen CW and Li M: Patient-derived organoid pharmacotyping guides precision medicine for pancreatic cancer. Clin Cancer Res. 28:3176–3178. 2022. View Article : Google Scholar : PubMed/NCBI | |
|
Wang R, Mao Y, Wang W, Zhou X, Wang W, Gao S, Li J, Wen L, Fu W and Tang F: Systematic evaluation of colorectal cancer organoid system by single-cell RNA-Seq analysis. Genome Biol. 23:1062022. View Article : Google Scholar : PubMed/NCBI | |
|
Kim SC, Park JW, Seo HY, Kim M, Park JH, Kim GH, Lee JO, Shin YK, Bae JM, Koo BK, et al: Multifocal organoid capturing of colon cancer reveals pervasive intratumoral heterogenous drug responses. Adv Sci (Weinh). 9:e21033602022. View Article : Google Scholar | |
|
Chen G, Gong T, Wang Z, Wang Z, Lin X, Chen S, Sun C, Zhao W, Kong Y, Ai H, et al: Colorectal cancer organoid models uncover oxaliplatin-resistant mechanisms at single cell resolution. Cell Oncol (Dordr). 45:1155–1167. 2022.PubMed/NCBI | |
|
Zeng Y, Yin L, Zhou J, Zeng R, Xiao Y, Black AR, Hu T, Singh PK, Yin F, Batra SK, et al: MARK2 regulates chemotherapeutic responses through class IIa HDAC-YAP axis in pancreatic cancer. Oncogene. 41:3859–3875. 2022. View Article : Google Scholar : PubMed/NCBI | |
|
Toshimitsu K, Takano A, Fujii M, Togasaki K, Matano M, Takahashi S, Kanai T and Sato T: Organoid screening reveals epigenetic vulnerabilities in human colorectal cancer. Nat Chem Biol. 18:605–614. 2022. View Article : Google Scholar : PubMed/NCBI | |
|
Tong Y, Cheng PSW, Or CS, Yue SSK, Siu HC, Ho SL, Law SYK, Tsui WY, Chan D, Ma S, et al: Escape from cell-cell and cell-matrix adhesion dependence underscores disease progression in gastric cancer organoid models. Gut. 72:242–255. 2023. View Article : Google Scholar | |
|
Grossman JE, Muthuswamy L, Huang L, Akshinthala D, Perea S, Gonzalez RS, Tsai LL, Cohen J, Bockorny B, Bullock AJ, et al: Organoid sensitivity correlates with therapeutic response in patients with pancreatic cancer. Clin Cancer Res. 28:708–718. 2022. View Article : Google Scholar : | |
|
Kawai S, Nakano K, Tamai K, Fujii E, Yamada M, Komoda H, Sakumoto H, Natori O and Suzuki M: Generation of a lung squamous cell carcinoma three-dimensional culture model with keratinizing structures. Sci Rep. 11:243052021. View Article : Google Scholar : PubMed/NCBI | |
|
Ramamoorthy P, Thomas SM, Kaushik G, Subramaniam D, Chastain KM, Dhar A, Tawfik O, Kasi A, Sun W, Ramalingam S, et al: Metastatic tumor-in-a-dish, a novel multicellular organoid to study lung colonization and predict therapeutic response. Cancer Res. 79:1681–1695. 2019. View Article : Google Scholar : PubMed/NCBI | |
|
Kawasaki K, Toshimitsu K, Matano M, Fujita M, Fujii M, Togasaki K, Ebisudani T, Shimokawa M, Takano A, Takahashi S, et al: An organoid biobank of neuroendocrine neoplasms enables genotype-phenotype mapping. Cell. 183:1420–1435.e21. 2020. View Article : Google Scholar : PubMed/NCBI | |
|
Goudar VS, Koduri MP, Ta YN, Chen Y, Chu LA, Lu LS and Tseng FG: Impact of a desmoplastic tumor microenvironment for colon cancer drug sensitivity: A study with 3D chimeric tumor spheroids. ACS Appl Mater Interfaces. 13:48478–48491. 2021. View Article : Google Scholar : PubMed/NCBI | |
|
Tran E, Shi T, Li X, Chowdhury AY, Jiang D, Liu Y, Wang H, Yan C, Wallace WD, Lu R, et al: Development of human alveolar epithelial cell models to study distal lung biology and disease. iScience. 25:1037802022. View Article : Google Scholar : PubMed/NCBI | |
|
Sun L, Yang H, Wang Y, Zhang X, Jin B, Xie F, Jin Y, Pang Y, Zhao H, Lu X, et al: Application of a 3D bioprinted hepatocellular carcinoma cell model in antitumor drug research. Front Oncol. 10:8782020. View Article : Google Scholar : PubMed/NCBI | |
|
Li J, Fang K, Choppavarapu L, Yang K, Yang Y, Wang J, Cao R, Jatoi I and Jin VX: Hi-C profiling of cancer spheroids identifies 3D-growth-specific chromatin interactions in breast cancer endocrine resistance. Clin Epigenetics. 13:1752021. View Article : Google Scholar : PubMed/NCBI | |
|
Monberg ME, Geiger H, Lee JJ, Sharma R, Semaan A, Bernard V, Wong J, Wang F, Liang S, Swartzlander DB, et al: Occult polyclonality of preclinical pancreatic cancer models drives in vitro evolution. Nat Commun. 13:36522022. View Article : Google Scholar : PubMed/NCBI | |
|
Xu H, Jiao D, Liu A and Wu K: Tumor organoids: Applications in cancer modeling and potentials in precision medicine. J Hematol Oncol. 15:582022. View Article : Google Scholar : PubMed/NCBI | |
|
Wilson HV: A new method by which sponges may be artificially reared. Science. 25:912–915. 1907. View Article : Google Scholar : PubMed/NCBI | |
|
Raghavan S, Mehta P, Xie Y, Lei YL and Mehta G: Ovarian cancer stem cells and macrophages reciprocally interact through the WNT pathway to promote pro-tumoral and malignant phenotypes in 3D engineered microenvironments. J Immunother Cancer. 7:1902019. View Article : Google Scholar : PubMed/NCBI | |
|
Wolint P, Bopp A, Woloszyk A, Tian Y, Evrova O, Hilbe M, Giovanoli P, Calcagni M, Hoerstrup SP, Buschmann J and Emmert MY: Cellular self-assembly into 3D microtissues enhances the angiogenic activity and functional neovascularization capacity of human cardiopoietic stem cells. Angiogenesis. 22:37–52. 2019. View Article : Google Scholar | |
|
Thakur G, Bok EY, Kim SB, Jo CH, Oh SJ, Baek JC, Park JE, Kang YH, Lee SL, Kumar R and Rho GJ: Scaffold-free 3D culturing enhance pluripotency, immunomodulatory factors, and differentiation potential of Wharton's jelly-mesenchymal stem cells. Eur J Cell Biol. 101:1512452022. View Article : Google Scholar : PubMed/NCBI | |
|
Cho CY, Chiang TH, Hsieh LH, Yang WY, Hsu HH, Yeh CK, Huang CC and Huang JH: Development of a novel hanging drop platform for engineering controllable 3D microenvironments. Front Cell Dev Biol. 8:3272020. View Article : Google Scholar : PubMed/NCBI | |
|
Guan Z, Jia S, Zhu Z, Zhang M and Yang CJ: Facile and rapid generation of large-scale microcollagen gel array for long-term single-cell 3D culture and cell proliferation heterogeneity analysis. Anal Chem. 86:2789–2797. 2014. View Article : Google Scholar : PubMed/NCBI | |
|
Pageau SC, Sazonova OV, Wong JY, Soto AM and Sonnenschein C: The effect of stromal components on the modulation of the phenotype of human bronchial epithelial cells in 3D culture. Biomaterials. 32:7169–7180. 2011. View Article : Google Scholar : PubMed/NCBI | |
|
Quarni W, Dutta R, Green R, Katiri S, Patel B, Mohapatra SS and Mohapatra S: Mithramycin A inhibits colorectal cancer growth by targeting cancer stem cells. Sci Rep. 9:152022019. View Article : Google Scholar : PubMed/NCBI | |
|
Xiao W, Wang S, Zhang R, Sohrabi A, Yu Q, Liu S, Ehsanipour A, Liang J, Bierman RD, Nathanson DA and Seidlits SK: Bioengineered scaffolds for 3D culture demonstrate extracellular matrix-mediated mechanisms of chemotherapy resistance in glioblastoma. Matrix Biol. 85-86:128–146. 2020. View Article : Google Scholar | |
|
Xu J, Shamul JG, Staten NA, White AM, Jiang B and He X: Bioinspired 3D culture in nanoliter hyaluronic acid-rich core-shell hydrogel microcapsules isolates highly pluripotent human iPSCs. Small. 17:e21022192021. View Article : Google Scholar : PubMed/NCBI | |
|
Luca AC, Mersch S, Deenen R, Schmidt S, Messner I, Schäfer KL, Baldus SE, Huckenbeck W, Piekorz RP, Knoefel WT, et al: Impact of the 3D microenvironment on phenotype, gene expression, and EGFR inhibition of colorectal cancer cell lines. PLoS One. 8:e596892013. View Article : Google Scholar : PubMed/NCBI | |
|
Weigelt B, Lo AT, Park CC, Gray JW and Bissell MJ: HER2 signaling pathway activation and response of breast cancer cells to HER2-targeting agents is dependent strongly on the 3D microenvironment. Breast Cancer Res Treat. 122:35–43. 2010. View Article : Google Scholar : | |
|
Yao H, Li T, Wu Z, Tao Q, Shi J, Liu L and Zhao Y: Superlarge living hyaline cartilage graft contributed by the scale-changed porous 3D culture system for joint defect repair. Biomed Mater. 17:0641012022. View Article : Google Scholar | |
|
Xu X, Feng Q, Ma X, Deng Y, Zhang K, Ooi HS, Yang B, Zhang ZY, Feng B and Bian L: Dynamic gelatin-based hydrogels promote the proliferation and self-renewal of embryonic stem cells in long-term 3D culture. Biomaterials. 289:1218022022. View Article : Google Scholar : PubMed/NCBI | |
|
Fong EL, Lamhamedi-Cherradi SE, Burdett E, Ramamoorthy V, Lazar AJ, Kasper FK, Farach-Carson MC, Vishwamitra D, Demicco EG, Menegaz BA, et al: Modeling Ewing sarcoma tumors in vitro with 3D scaffolds. Proc Natl Acad Sci USA. 110:6500–6505. 2013. View Article : Google Scholar : PubMed/NCBI | |
|
Keate RL, Tropp J, Collins CP, Ware HOT, Petty AJ II, Ameer GA, Sun C and Rivnay J: 3D-printed electroactive hydrogel architectures with Sub-100 µm resolution promote myoblast viability. Macromol Biosci. 22:e22001032022. View Article : Google Scholar | |
|
Nishimura SN, Hokazono N, Taki Y, Motoda H, Morita Y, Yamamoto K, Higashi N and Koga T: Photocleavable peptide-poly(2-hydroxyethyl methacrylate) hybrid graft copolymer via postpolymerization modification by click chemistry to modulate the cell affinities of 2D and 3D materials. ACS Appl Mater Interfaces. 11:24577–24587. 2019. View Article : Google Scholar : PubMed/NCBI | |
|
Svozilová H, Plichta Z, Proks V, Studená R, Baloun J, Doubek M, Pospíšilová Š and Horák D: RGDS-modified superporous poly(2-hydroxyethyl methacrylate)-based scaffolds as 3D in vitro leukemia model. Int J Mol Sci. 22:23762021. View Article : Google Scholar : PubMed/NCBI | |
|
Jiang X, Li X, Fei X, Shen J, Chen J, Guo M and Li Y: Endometrial membrane organoids from human embryonic stem cell combined with the 3D Matrigel for endometrium regeneration in asherman syndrome. Bioact Mater. 6:3935–3946. 2021.PubMed/NCBI | |
|
Zhang Z, Gao S, Hu YN, Chen X, Cheng C, Fu XL, Zhang SS, Wang XL, Che YW, Zhang C and Chai RJ: Ti3 C2 Tx MXene composite 3D hydrogel potentiates mTOR signaling to promote the generation of functional hair cells in cochlea organoids. Adv Sci (Weinh). 9:e22035572022. View Article : Google Scholar | |
|
Sato T, Vries RG, Snippert HJ, van de Wetering M, Barker N, Stange DE, van Es JH, Abo A, Kujala P, Peters PJ and Clevers H: Single Lgr5 stem cells build crypt-villus structures in vitro without a mesenchymal niche. Nature. 459:262–265. 2009. View Article : Google Scholar : PubMed/NCBI | |
|
Soto-Gutierrez A, Navarro-Alvarez N, Yagi H, Nahmias Y, Yarmush ML and Kobayashi N: Engineering of an hepatic organoid to develop liver assist devices. Cell Transplant. 19:815–822. 2010. View Article : Google Scholar : PubMed/NCBI | |
|
Ramachandran SD, Schirmer K, Münst B, Heinz S, Ghafoory S, Wölfl S, Simon-Keller K, Marx A, Øie CI, Ebert MP, et al: In vitro generation of functional liver organoid-like structures using adult human cells. PLoS One. 10:e01393452015. View Article : Google Scholar : PubMed/NCBI | |
|
Magro-Lopez E, Palmer C, Manso J, Liste I and Zambrano A: Effects of lung and airway epithelial maturation cocktail on the structure of lung bud organoids. Stem Cell Res Ther. 9:1862018. View Article : Google Scholar : PubMed/NCBI | |
|
Chen YW, Huang SX, de Carvalho ALRT, Ho SH, Islam MN, Volpi S, Notarangelo LD, Ciancanelli M, Casanova JL, Bhattacharya J, et al: A three-dimensional model of human lung development and disease from pluripotent stem cells. Nat Cell Biol. 19:542–549. 2017. View Article : Google Scholar | |
|
Jung YH, Choi DH, Park K, Lee SB, Kim J, Kim H, Jeong HW, Yang JH, Kim JA, Chung S and Min BS: Drug screening by uniform patient derived colorectal cancer hydro-organoids. Biomaterials. 276:1210042021. View Article : Google Scholar : PubMed/NCBI | |
|
Xie BY and Wu AW: Organoid culture of isolated cells from patient-derived tissues with colorectal cancer. Chin Med J (Engl). 129:2469–2475. 2016. View Article : Google Scholar : PubMed/NCBI | |
|
Zeng L, Liao Q, Zhao Q, Jiang S, Yang X, Tang H, He Q, Yang X, Fang S, He J, et al: Raltitrexed as a synergistic hyperthermia chemotherapy drug screened in patient-derived colorectal cancer organoids. Cancer Biol Med. 18:750–762. 2021. View Article : Google Scholar : PubMed/NCBI | |
|
Miao X, Wang C, Chai C, Tang H, Hu J, Zhao Z, Luo W, Zhang H, Zhu K, Zhou W and Xu H: Establishment of gastric cancer organoid and its application in individualized therapy. Oncol Lett. 24:4472022. View Article : Google Scholar : PubMed/NCBI | |
|
Schlaermann P, Toelle B, Berger H, Schmidt SC, Glanemann M, Ordemann J, Bartfeld S, Mollenkopf HJ and Meyer TF: A novel human gastric primary cell culture system for modelling Helicobacter pylori infection in vitro. Gut. 65:202–213. 2016. View Article : Google Scholar | |
|
Cherne MD, Sidar B, Sebrell TA, Sanchez HS, Heaton K, Kassama FJ, Roe MM, Gentry AB, Chang CB, Walk ST, et al: A synthetic hydrogel, vitroGel® ORGANOID-3, improves immune cell-epithelial interactions in a tissue chip co-culture model of human gastric organoids and dendritic cells. Front Pharmacol. 12:7078912021. View Article : Google Scholar | |
|
Noguchi TK and Kurisaki A: Formation of stomach tissue by organoid culture using mouse embryonic stem cells. Methods Mol Biol. 1597:217–228. 2017. View Article : Google Scholar : PubMed/NCBI | |
|
Wedeken L, Luo A, Tremblay JR, Rawson J, Jin L, Gao D, Quijano J and Ku HT: Adult murine pancreatic progenitors require epidermal growth factor and nicotinamide for self-renewal and differentiation in a serum- and conditioned medium-free culture. Stem Cells Dev. 26:599–607. 2017. View Article : Google Scholar : PubMed/NCBI | |
|
Soltanian A, Ghezelayagh Z, Mazidi Z, Halvaei M, Mardpour S, Ashtiani MK, Hajizadeh-Saffar E, Tahamtani Y and Baharvand H: Generation of functional human pancreatic organoids by transplants of embryonic stem cell derivatives in a 3D-printed tissue trapper. J Cell Physiol. 234:9564–9576. 2019. View Article : Google Scholar | |
|
Molnár R, Madácsy T, Varga Á, Németh M, Katona X, Görög M, Molnár B, Fanczal J, Rakonczay Z Jr, Hegyi P, et al: Mouse pancreatic ductal organoid culture as a relevant model to study exocrine pancreatic ion secretion. Lab Invest. 100:84–97. 2020. View Article : Google Scholar | |
|
Calderon-Gierszal EL and Prins GS: Directed differentiation of human embryonic stem cells into prostate organoids in vitro and its perturbation by low-dose bisphenol A exposure. PLoS One. 10:e01332382015. View Article : Google Scholar : PubMed/NCBI | |
|
Cheaito K, Bahmad HF, Hadadeh O, Msheik H, Monzer A, Ballout F, Dagher C, Telvizian T, Saheb N, Tawil A, et al: Establishment and characterization of prostate organoids from treatment-naïve patients with prostate cancer. Oncol Lett. 23:62022. View Article : Google Scholar | |
|
Choo N, Ramm S, Luu J, Winter JM, Selth LA, Dwyer AR, Frydenberg M, Grummet J, Sandhu S, Hickey TE, et al: High-throughput imaging assay for drug screening of 3D prostate cancer organoids. SLAS Discov. 26:1107–1124. 2021. View Article : Google Scholar : PubMed/NCBI | |
|
Van Hemelryk A, Mout L, Erkens-Schulze S, French PJ, van Weerden WM and van Royen ME: Modeling prostate cancer treatment responses in the organoid era: 3D environment impacts drug testing. Biomolecules. 11:15722021. View Article : Google Scholar : PubMed/NCBI | |
|
Ma L, Li J, Nie Q, Zhang Q, Liu S, Ge D and You Z: Organoid culture of human prostate cancer cell lines LNCaP and C4-2B. Am J Clin Exp Urol. 5:25–33. 2017.PubMed/NCBI | |
|
Facioli R, Lojudice FH, Anauate AC, Maquigussa E, Nishiura JL, Heilberg IP, Sogayar MC and Boim MA: Kidney organoids generated from erythroid progenitors cells of patients with autosomal dominant polycystic kidney disease. PLoS One. 16:e02521562021. View Article : Google Scholar : PubMed/NCBI | |
|
Velagapudi C, Nilsson RP, Lee MJ, Burns HS, Ricono JM, Arar M, Barnes VL, Abboud HE and Barnes JL: Reciprocal induction of simple organogenesis by mouse kidney progenitor cells in three-dimensional co-culture. Am J Pathol. 180:819–830. 2012. View Article : Google Scholar : | |
|
Wang X, Sun L, Maffini MV, Soto A, Sonnenschein C and Kaplan DL: A complex 3D human tissue culture system based on mammary stromal cells and silk scaffolds for modeling breast morphogenesis and function. Biomaterials. 31:3920–3929. 2010. View Article : Google Scholar : PubMed/NCBI | |
|
Polo ML, Arnoni MV, Riggio M, Wargon V, Lanari C and Novaro V: Responsiveness to PI3K and MEK inhibitors in breast cancer. Use of a 3D culture system to study pathways related to hormone independence in mice. PLoS One. 5:e107862010. View Article : Google Scholar : PubMed/NCBI | |
|
Hachey SJ, Hatch CJ, Gaebler D, Forsythe AG, Ewald ML, Chopra AL, Chen Z, Thapa K, Hodanu M, Fang JS and Hughes CCW: Methods for processing and analyzing images of vascularized micro-organ and tumor systems. Front Bioeng Biotechnol. 13:15850032025. View Article : Google Scholar : PubMed/NCBI | |
|
Schmid KF, Zeinali S, Moser SK, Dubey C, Schneider S, Deng H, Haefliger S, Marti TM and Guenat OT: Assessing the metastatic potential of circulating tumor cells using an organ-on-chip model. Front Bioeng Biotechnol. 12:14578842024. View Article : Google Scholar : PubMed/NCBI | |
|
Maulana TI, Teufel C, Cipriano M, Roosz J, Lazarevski L, van den Hil FE, Scheller L, Orlova V, Koch A, Hudecek M, et al: Breast cancer-on-chip for patient-specific efficacy and safety testing of CAR-T cells. Cell Stem Cell. 31:989–1002.e9. 2024. View Article : Google Scholar : PubMed/NCBI | |
|
Zhou G, Lin X, Li H, Sun W, Li W, Zhang Q, Bian F and Lin J: Assessment of drug treatment response using primary human colon cancer cell spheroids cultivated in a microfluidic mixer chip. Biosens Bioelectron. 269:1169442025. View Article : Google Scholar | |
|
Huang B, Wei X, Chen K, Wang L and Xu M: Bioprinting of hydrogel beads to engineer pancreatic tumor-stroma microtissues for drug screening. Int J Bioprint. 9:6762023. View Article : Google Scholar : PubMed/NCBI | |
|
Wang P, Sun L, Li C, Jin B, Yang H, Wu B and Mao Y: Study on drug screening multicellular model for colorectal cancer constructed by three-dimensional bioprinting technology. Int J Bioprint. 9:6942023. View Article : Google Scholar : PubMed/NCBI | |
|
Mazzaglia C, Sheng Y, Rodrigues LN, Lei IM, Shields JD and Huang YYS: Deployable extrusion bioprinting of compartmental tumoroids with cancer associated fibroblasts for immune cell interactions. Biofabrication. 15:0250052023. View Article : Google Scholar | |
|
Horder H, Böhringer D, Endrizzi N, Hildebrand LS, Cianciosi A, Stecher S, Dusi F, Schweinitzer S, Watzling M, Groll J, et al: Cancer cell migration depends on adjacent ASC and adipose spheroids in a 3D bioprinted breast cancer model. Biofabrication. 16:0350312024. View Article : Google Scholar | |
|
Ning L, Shim J, Tomov ML, Liu R, Mehta R, Mingee A, Hwang B, Jin L, Mantalaris A, Xu C, et al: A 3D bioprinted in vitro model of neuroblastoma recapitulates dynamic tumor-endothelial cell interactions contributing to solid tumor aggressive behavior. Adv Sci (Weinh). 9:e22002442022. View Article : Google Scholar : PubMed/NCBI | |
|
Choi YM, Na D, Yoon G, Kim J, Min S, Yi HG, Cho SJ, Cho JH, Lee C and Jang J: Prediction of patient drug response via 3d bioprinted gastric cancer model utilized patient-derived tissue laden tissue-specific bioink. Adv Sci (Weinh). 12:e24117692025. View Article : Google Scholar : PubMed/NCBI | |
|
Barbosa MAG, Xavier CPR, Pereira RF, Petrikaitė V and Vasconcelos MH: 3D cell culture models as recapitulators of the tumor microenvironment for the screening of anti-cancer drugs. Cancers. 14:1902021. View Article : Google Scholar | |
|
Geevarghese R, Somasekharan LT, Bhatt A, Kasoju N and Nair RP: Development and evaluation of a multicomponent bioink consisting of alginate, gelatin, diethylaminoethyl cellulose and collagen peptide for 3D bioprinting of tissue construct for drug screening application. Int J Biol Macromol. 207:278–288. 2022. View Article : Google Scholar : PubMed/NCBI | |
|
Karlsson H, Fryknäs M, Larsson R and Nygren P: Loss of cancer drug activity in colon cancer HCT-116 cells during spheroid formation in a new 3-D spheroid cell culture system. Exp Cell Res. 318:1577–1585. 2012. View Article : Google Scholar : PubMed/NCBI | |
|
Fallica B, Maffei JS, Villa S, Makin G and Zaman M: Alteration of cellular behavior and response to PI3K pathway inhibition by culture in 3D collagen gels. PLoS One. 7:e480242012. View Article : Google Scholar : PubMed/NCBI | |
|
Ramaiahgari SC, den Braver MW, Herpers B, Terpstra V, Commandeur JN, van de Water B and Price LS: A 3D in vitro model of differentiated HepG2 cell spheroids with improved liver-like properties for repeated dose high-throughput toxicity studies. Arch Toxicol. 88:1083–1095. 2014.PubMed/NCBI | |
|
Hua Y, Gorshkov K, Yang Y, Wang W, Zhang N and Hughes DP: Slow down to stay alive: HER4 protects against cellular stress and confers chemoresistance in neuroblastoma. Cancer. 118:5140–5154. 2012. View Article : Google Scholar : PubMed/NCBI | |
|
Breslin S and O'Driscoll L: The relevance of using 3D cell cultures, in addition to 2D monolayer cultures, when evaluating breast cancer drug sensitivity and resistance. Oncotarget. 7:45745–45756. 2016. View Article : Google Scholar : PubMed/NCBI | |
|
de la Puente P, Muz B, Gilson RC, Azab F, Luderer M, King J, Achilefu S, Vij R and Azab AK: 3D tissue-engineered bone marrow as a novel model to study pathophysiology and drug resistance in multiple myeloma. Biomaterials. 73:70–84. 2015. View Article : Google Scholar : PubMed/NCBI | |
|
Lamanuzzi A, Saltarella I, Frassanito MA, Ribatti D, Melaccio A, Desantis V, Solimando AG, Ria R and Vacca A: Thrombopoietin promotes angiogenesis and disease progression in patients with multiple myeloma. Am J Pathol. 191:748–758. 2021. View Article : Google Scholar : PubMed/NCBI | |
|
Cucè M, Gallo Cantafio ME, Siciliano MA, Riillo C, Caracciolo D, Scionti F, Staropoli N, Zuccalà V, Maltese L, Di Vito A, et al: Trabectedin triggers direct and NK-mediated cytotoxicity in multiple myeloma. J Hematol Oncol. 12:322019. View Article : Google Scholar : PubMed/NCBI | |
|
Storch K, Eke I, Borgmann K, Krause M, Richter C, Becker K, Schröck E and Cordes N: Three-dimensional cell growth confers radioresistance by chromatin density modification. Cancer Res. 70:3925–3934. 2010. View Article : Google Scholar : PubMed/NCBI | |
|
Skardal A, Devarasetty M, Rodman C, Atala A and Soker S: Liver-tumor hybrid organoids for modeling tumor growth and drug response in vitro. Ann Biomed Eng. 43:2361–2373. 2015. View Article : Google Scholar : PubMed/NCBI | |
|
Loessner D, Stok KS, Lutolf MP, Hutmacher DW, Clements JA and Rizzi SC: Bioengineered 3D platform to explore cell-ECM interactions and drug resistance of epithelial ovarian cancer cells. Biomaterials. 31:8494–8506. 2010. View Article : Google Scholar : PubMed/NCBI | |
|
Doublier S, Belisario DC, Polimeni M, Annaratone L, Riganti C, Allia E, Ghigo D, Bosia A and Sapino A: HIF-1 activation induces doxorubicin resistance in MCF7 3-D spheroids via P-glycoprotein expression: A potential model of the chemo-resistance of invasive micropapillary carcinoma of the breast. BMC Cancer. 12:42012. View Article : Google Scholar : PubMed/NCBI | |
|
Takahashi Y, Hori Y, Yamamoto T, Urashima T, Ohara Y and Tanaka H: 3D spheroid cultures improve the metabolic gene expression profiles of HepaRG cells. Biosci Rep. 35:e002082015. View Article : Google Scholar : PubMed/NCBI | |
|
Fischbach C, Kong HJ, Hsiong SX, Evangelista MB, Yuen W and Mooney DJ: Cancer cell angiogenic capability is regulated by 3D culture and integrin engagement. Proc Natl Acad Sci USA. 106:399–404. 2009. View Article : Google Scholar : PubMed/NCBI | |
|
Tanaka C, Furihata K, Naganuma S, Ogasawara M, Yoshioka R, Taniguchi H, Furihata M and Taniuchi K: Establishment of a mouse model of pancreatic cancer using human pancreatic cancer cell line S2-013-derived organoid. Hum Cell. 35:735–744. 2022. View Article : Google Scholar : PubMed/NCBI | |
|
Forsythe S, Mehta N, Devarasetty M, Sivakumar H, Gmeiner W, Soker S, Votanopoulos K and Skardal A: Development of a colorectal cancer 3D micro-tumor construct platform from cell lines and patient tumor biospecimens for standard-of-care and experimental drug screening. Ann Biomed Eng. 48:940–952. 2020. View Article : Google Scholar | |
|
Pickl M and Ries CH: Comparison of 3D and 2D tumor models reveals enhanced HER2 activation in 3D associated with an increased response to trastuzumab. Oncogene. 28:461–468. 2009. View Article : Google Scholar | |
|
Swain SM, Shastry M and Hamilton E: Targeting HER2-positive breast cancer: Advances and future directions. Nat Rev Drug Discov. 22:101–126. 2023. View Article : Google Scholar | |
|
Rubin I and Yarden Y: The basic biology of HER2. Ann Oncol. 12(Suppl 1): S3–S8. 2001. View Article : Google Scholar : PubMed/NCBI | |
|
Yarden Y and Sliwkowski MX: Untangling the ErbB signalling network. Nat Rev Mol Cell Biol. 2:127–137. 2001. View Article : Google Scholar : PubMed/NCBI | |
|
Lovitt CJ, Shelper TB and Avery VM: Evaluation of chemotherapeutics in a three-dimensional breast cancer model. J Cancer Res Clin Oncol. 141:951–959. 2015. View Article : Google Scholar : PubMed/NCBI | |
|
Dhiman HK, Ray AR and Panda AK: Three-dimensional chitosan scaffold-based MCF-7 cell culture for the determination of the cytotoxicity of tamoxifen. Biomaterials. 26:979–986. 2005. View Article : Google Scholar | |
|
Choi JW, Lee SY and Lee DW: A cancer spheroid array chip for selecting effective drug. Micromachines (Basel). 10:6882019. View Article : Google Scholar : PubMed/NCBI | |
|
Mazzocchi A, Dominijanni A and Soker S: Pleural effusion aspirate for use in 3D lung cancer modeling and chemotherapy screening. Methods Mol Biol. 2394:471–483. 2022. View Article : Google Scholar : PubMed/NCBI | |
|
Wu Q, Wei X, Pan Y, Zou Y, Hu N and Wang P: Bionic 3D spheroids biosensor chips for high-throughput and dynamic drug screening. Biomed Microdevices. 20:822018. View Article : Google Scholar : PubMed/NCBI | |
|
Li YF, Gao Y, Liang BW, Cao XQ, Sun ZJ, Yu JH, Liu ZD and Han Y: Patient-derived organoids of non-small cells lung cancer and their application for drug screening. Neoplasma. 67:430–437. 2020. View Article : Google Scholar : PubMed/NCBI | |
|
Takai A, Fako V, Dang H, Forgues M, Yu Z, Budhu A and Wang XW: Three-dimensional organotypic culture models of human hepatocellular carcinoma. Sci Rep. 6:211742016. View Article : Google Scholar : PubMed/NCBI | |
|
Vincent-Chong VK and Seshadri M: Development and radiation response assessment in A novel syngeneic mouse model of tongue cancer: 2D culture, 3D organoids and orthotopic allografts. Cancers (Basel). 12:5792020. View Article : Google Scholar : PubMed/NCBI | |
|
Wei Y, Amend B, Todenhöfer T, Lipke N, Aicher WK, Fend F, Stenzl A and Harland N: Urinary tract tumor organoids reveal eminent differences in drug sensitivities when compared to 2-dimensional culture systems. Int J Mol Sci. 23:63052022. View Article : Google Scholar : PubMed/NCBI | |
|
Chitcholtan K, Sykes PH and Evans JJ: The resistance of intracellular mediators to doxorubicin and cisplatin are distinct in 3D and 2D endometrial cancer. J Transl Med. 10:382012. View Article : Google Scholar : PubMed/NCBI | |
|
Wen Z, Liao Q, Hu Y, You L, Zhou L and Zhao Y: A spheroid-based 3-D culture model for pancreatic cancer drug testing, using the acid phosphatase assay. Braz J Med Biol Res. 46:634–642. 2013. View Article : Google Scholar : PubMed/NCBI | |
|
Phan NLC, Pham KD, Le Minh P, Nguyen MTT, Kim NP, Truong KD and Van Pham P: Hopea odorata extract can efficiently kill breast cancer cells and cancer stem-like cells in three-dimensional culture more than in monolayer cell culture. Adv Exp Med Biol. 1292:145–155. 2020. View Article : Google Scholar : PubMed/NCBI | |
|
Sahai E, Astsaturov I, Cukierman E, DeNardo DG, Egeblad M, Evans RM, Fearon D, Greten FR, Hingorani SR, Hunter T, et al: A framework for advancing our understanding of cancer-associated fibroblasts. Nat Rev Cancer. 20:174–186. 2020. View Article : Google Scholar : PubMed/NCBI | |
|
Park D, Sahai E and Rullan A: SnapShot: Cancer-associated fibroblasts. Cell. 181:486–486.e1. 2020. View Article : Google Scholar : PubMed/NCBI |
