Abstract
Since the early 20th century, there has been extensive discussion on the intricate relationship between pathogenic infection and tumors. However, most studies on host-pathogen interactions are performed based on the in-vitro culture, immortalized cell lines or animal experiments. A significant challenge lies in accurately establishing a coculture model between tumors and pathogens under the three-dimensional (3D) context. Recently, the hybrid model system that incorporates 3D tumor organoids and two-dimensional cell lines have been gradually used to analyze the intricate relationship between pathogens and tumors, and several coculture techniques for tumor organoids and pathogens have also been developed. Therefore, this study systematically reviewed the preparation and identification of tumor organoids, coculture techniques with pathogens, and their clinical applications, aiming to further understand and simulate the interaction mechanism between the hosts and pathogens.
1 Introduction
Organoids serve as a transitional model between in vitro cancer cell lines and xenografts, offering a unique approach to study cancer biology. Differing from traditional cell culture, the organoid model can preserve cell-cell and cell-matrix interactions by cultivating cancer cells under the three-dimensional (3D) context (Veninga and Voest, 2021; Xu et al., 2022), more closely resembling the characteristics of the original tumor (McCauley and Wells, 2017; Ouchi et al., 2019; ). Organoids are classified based on the cellular source, including pluripotent stem cells (PSCs), adult stem cells (ASCs), and patient-derived tumor organoids (PDTOs) (; Tindle et al., 2021; ) (Table 1), among which the PDTOs are small tissue spheroids and are generated following tumor resection (Walsh et al., 2017; Rosenbluth et al., 2020). The advent of PDTOs has enabled the implementation of patient-specific drug screening, personalized treatment, and identification of prognostic biomarkers and mechanisms of drug resistance (Neal and Kuo, 2016).
Table 1
| Coculture methods | Stem cell-derived organoids | Patient-derived tumor organoids |
|---|---|---|
| Wild-type cell culture | + | + |
| Preinvasive cancer models | + | + |
| Invasive cancer models | + | + |
| Metastatic cancer models | + | + |
| Cost | $$ | $$ |
| Time | +++ | ++ |
| Success rates | Low | Medium |
| Throughput therapies | High | Medium |
Advantages and limitations of the organoid culture methods.
+, denotes 1 month or less; ++, 1–2 month; +++, often more than several months.
The intricate relationship between infectious diseases and cancers has been extensively studied since the early 20th century. In 2012, approximately 2.2 million new cancer cases were attributed to infections, among which helicobacter pylori (H. pylori), human papillomavirus (HPV), hepatitis B virus (HBV), hepatitis C virus (HCV), and Epstein-Barr virus (EBV) play important roles (Qu et al., 2021). Previous studies have confirmed that tumorigenesis is closely associated with a variety of pathogenic microorganisms comprising a heterogeneous assemblage of bacteria, fungi, protozoa, viruses, and phages (; Purcell et al., 2017; Tsoi et al., 2017; ; Tsay et al., 2018; Zhang et al., 2018; ; ; ; Parhi et al., 2020; Valguarnera and Wardenburg, 2020; ; Tsay et al., 2021) (Table 2). Nejman et al. undertook an exhaustive examination of the microbiomes in 1,526 tumors (breast, lung, ovarian, pancreatic, melanoma, bone, and brain tumors) and their corresponding normal tissues across 7 distinct cancer types. The findings revealed that each tumor category exhibited a distinct microbiome profile, with breast cancer demonstrating a notably abundant and varied microbiome (Plummer et al., 2016; Nejman et al., 2020). This indicates that coculturing pathogenic microorganisms with tumor organoids offers a new approach for diagnosis, prognostic prediction, and treatment decision in cancer. Although bacterial therapy has shown a greater promise in cancer treatment over the last decade due to its ability to lyse the tumor cells and deliver therapeutic products, the potential cytotoxicity of bacteria for healthy tissues and their inability to entirely lyse cancerous cells poses challenges for cancer treatment (Sepich-Poore et al., 2021; Soleimani and Javadi, 2022). Hence, the investigation into pathogenic microorganisms is crucial for understanding the mechanisms of tumorigenesis and promoting the development of innovative vaccine technologies.
Table 2
| Tumor types | Pathogen types | Mechanisms |
|---|---|---|
| Colorectal cancer | Bacteroides fragilis | NF-κB-STAT3, IL-17 production (Valguarnera and Wardenburg, 2020); |
| Methylation (; ); | ||
| Activate CEC Wnt signaling, induce c-Myc expression, and amplify CEC proliferation (Valguarnera and Wardenburg, 2020); | ||
| Upregulate CEACAM, and downregulate MUC2 () | ||
| Escherichia coli | DNA inter-strand crosslinks, DNA double-strand breaks, chromosomal aberrances, and cell cycle arrest () | |
| Fusobacterium nucleatum | TLR4-NFκB, Wnt/β-catenin () | |
| Streptococcus gallolyticus | High NF-κB and IL-8 messenger RNA tissue expression (Zhang et al., 2018) | |
| Peptostreptococcus stomatis | Acidity and hypoxia (Purcell et al., 2017) | |
| Peptostreptococcus anaerobius | ROS accumulation promoting bacterial colonization and cellular proliferation respectively (Tsoi et al., 2017) | |
| Gastric cancer | Helicobacter pylori | Produce ROS and nitrogen species, trigger single-strand DNA breaks and/or induce the NF-κB pro-inflammatory pathway that can trigger double-strand DNA breaks () |
| Lung cancer | Veillonella parvula | Upregulate IL-17, PI3K-AKT, MAPK and ERK pathways as well as IL-6/IL-8 (Tsay et al., 2021) |
| Streptococcus | Upregulate the ERK and PI3K pathways (Tsay et al., 2018) | |
| Breast cancer | Fusobacterium nucleatum | Enhanced tumor growth inhibited by antibiotics (Parhi et al., 2020) |
Common mechanisms of pathogen-induced tumorigenesis across tumor types.
Certain bacteria can induce cancers in diverse organs and tissues, including lung, liver, colorectum, kidney, cervix, brain, gastrointestinal tract, etc (Ward et al., 1994; ; ; ; Zhan et al., 2011; ; ; ; ; ; ; ; Oh et al., 2015; ; Zhu et al., 2016; ; ; ; ; Wang et al., 2020; Zhang et al., 2020; ; ; ; ; Wasunan et al., 2022; ; Seelbinder et al., 2023; ; Zhang et al., 2024; ; Peng et al., 2025) (Table 3). These bacteria contribute to tumorigenesis or malignant progression through various mechanisms (Wong and Yu, 2023; ). Here, we systematically reviewed the preparation and identification of tumor organoids, coculture techniques of tumor organoids and pathogenic microorganisms, and their clinical application.
Table 3
| Cancer types | Pathogenic microorganisms |
|---|---|
| Gastric cancer | H. pylori (), Epstein-Barr virus (), Mycobacterium (), Eggerthia catenaformis (Wang et al., 2020) |
| Colorectal cancer | pks+ Escherichia coli (; ), Fusobacterium nucleatum (; ; ), Streptococcus gallolyticus (; ) |
| Cervical cancer | HPV (; ), Prevotella (Zhang et al., 2024; Peng et al., 2025), Lactobacillus crispatus (Oh et al., 2015; ), Chlamydia trachomatis (Zhu et al., 2016; ) |
| Nasopharyngeal Carcinoma | Epstein-Barr virus (Zhang et al., 2020) |
| Hepatocellular Carcinoma | HBV (; ), HCV (; ), Bacillus subtilis (botany) (Wasunan et al., 2022), Escherichia spiralis (genus of bacteria) (Ward et al., 1994) |
| Gallbladder cancer | Salmonella (), H. pylori (; ) |
| Lung cancer | Chlamydia pneumoniae (Zhan et al., 2011; ), Candida (Seelbinder et al., 2023) |
Common pathogenic microorganisms with cancer-related risk.
2 Preparation and characterization of tumor organoids
In recent years, PDTOs have been widely used to study various cancer types, including pancreatic cancer (), prostate cancer (), liver cancer (), bladder cancer (), breast cancer (Sachs et al., 2018), ovarian cancer () and gastric cancer (Yan et al., 2018). Cancer is an extremely complex disease, and its heterogeneity is manifested by the fact that the same cancer subtype may vary significantly among the patients, such as the cell shape, size, and gene expression (Figure 1). The quality control of different tumor organoids, especially the stable expression of markers, plays a very important role in identifying successful establishment. The morphology and culture conditions of tumor organoids have been reported in several studies (; Yoshida, 2020; ). To provide a basis for standardized quality control of tumor organoids, we summarized the markers applied in the identification of tumor organoids (; ; van de Wetering et al., 2015; ; ; Sachs et al., 2018; Yan et al., 2018; ; ; ; Tao et al., 2022; Ou et al., 2023; Wang et al., 2023; ) (Table 4).
Figure 1
Table 4
| Cancer types | Tissue source | Markers |
|---|---|---|
| Prostate cancer ( | Prostate luminal cells | Basal prostate markers: p63 and CK5; Basal (outer) layer: CK8 |
| Ovarian cancer ( | Surgical tissue and/or drainage of ascites/pleural effusion | Epithelial markers: CK8, CK18, E-cadherin; High-grade serous ovarian cancer markers: PAX8, p53, CK7 |
| Pancreatic cancer ( | Surgical or biopsy tissue | Duct cell markers: Ki-67, CD68, and CK19 |
| Moderate/highly differentiated hepatocellular carcinoma (HCC) ( | Liver tissue (of donor origin) from patients undergoing surgery | AFP and GPC3 |
| Cholangiocarcinoma (CC) ( | Liver tissue (of donor origin) obtained from patients undergoing surgery | EPCAM, KRT19 or S100A11 |
| Combined HCC/CC ( | Liver tissue (of donor origin) from patients undergoing surgery | Markers that express both HCC and CC |
| Bladder cancer ( | Surgical tissue | Urinary tract epithelial cell markers: CK7; basal epithelial markers: CK5; Luminal epithelial markers: CK8 |
| Breast cancer (Sachs et al., 2018) | Surgical tissue | ERα, PR, and HER2 |
| Gastric cancer (Yan et al., 2018) | Surgical tissue | Gastric markers: MUC5AC, PGC, SST, MUC6, TFF1, TFF2 |
| Cervical cancer ( | Healthy endocervical and extracervical tissues dissected from the cervical canal in women undergoing total hysterectomy | Endocervical tissues and organoids: secretory cell transcriptional marker PAX8; Ectocervical organoids: KRT14-positive basal-like cells and differentiated KRT13-positive layers; Markers to confirm the origin of endocervical lining and to determine the extent of disease: PAX8 and MKI67 |
| Lung adenocarcinoma (Wang et al., 2023) | Biopsy or surgical excision of primary or metastatic lesions to obtain fresh tissue and collection of malignant fluid samples using sterile drainage bags | CK7, TTF-1 and Napsin A |
| Squamous cell carcinoma (Wang et al., 2023) | Biopsy or surgical excision of primary or metastatic lesions to obtain fresh tissue and collection of malignant fluid samples using sterile drainage bags | P40, P63 and CK5/6 |
| Small cell lung cancer (Wang et al., 2023) | Biopsy or surgical excision of primary or metastatic lesions to obtain fresh tissue and collection of malignant fluid samples using sterile drainage bags | Neuroendocrine markers: CD56, synaptophysin, CgA and TTF-1 |
| Colorectal cancer (van de Wetering et al., 2015) | Surgical tissue | KI67, OLFM4, KRT20 and Alcian blue |
| Melanoma (Ou et al., 2023) | Obtained from patients receiving treatment | HMB-45, α-SMA, vimentin and ICAM-1 |
| Glioblastoma ( | Surgically resected fresh glioblastoma tissue | Glial cell markers: GFAP and S100B; Mature neuron marker DCX and neural progenitor and glioma stem cell markers NESTIN, BLBP, HOPX, SOX2 and OLIG2 |
Identification of tumor organoid markers.
3 Development of organoid coculture techniques with pathogens
Coculture techniques play pivotal roles in the examination of host-pathogen interactions and the simplification of in vivo systems. The predictive capacity of cell culture-based assays is constrained by their inability to replicate the intricate organ complexity and inter-tissue communication present in vivo (
There are several methods for cocultures, such as direct coculture of viruses with organoids and injection of microorganisms into the organoid lumen. In the study of Nie et al., the HBV-containing supernatant of HepG2.2.15.7 cells, a HepG2.2.15 clone producing a higher level of HBV, was utilized to coculture with human induced pluripotent stem cell (hiPSC)-liver organoids, hiPSCs-hepatic-like cells, HepG2-tet-Na+-taurocholate cotransporting polypeptide organoids, and primary human hepatocytes in 24-well plates at a specific ratio (Figure 2A) (Nie et al., 2018). The harvested cells were then subjected to HBV covalent closed circular DNA (cccDNA) assay after infection for 10–20 days. This study successfully developed a stable HBV infection model through direct coculture of pathogens and PSCs-induced organoids. However, the coculture period is long, and organoids for passage and clonal growth following exposure to pathogens were limited after long-term culture.
Figure 2

Coculture models of organoids with pathogenic microorganisms. (A) A schematic diagram of direct infection of HepG2.2.15.7 cells with HBV stock solution (detailed procedure can be found in reference (Nie et al., 2018). (B) Organoid microinjections (detailed procedure can be found in reference (Puschhof et al., 2021). (C) Human gastric mucosal columnar epithelium was regenerated using the air-liquid interface culture method (detailed procedure can be found in reference (
With the development of modern biotechnology, the microinjection of microorganisms into the organoid lumen has further enhanced the efficacy of coculture techniques (Figure 2B). The utility of microinjection lies in its capacity to accurately regulate the specific physiological localization of bacteria, although it is not conducive to conducting extensive infection studies. Furthermore, the adoption of transwell-based cell culture methods for investigating bacterial interactions with physiological tissue barriers is steadily increasing (Figure 2C). This method offers the benefit of ensuring consistent exposure of individual cells to microorganisms, but the absence of spatial and environmental protection in bacterial compartments results in reduced viability of specialized anaerobes or unregulated proliferation of other bacterial strains (
Microfluidic organoids-on-a-chip, derived from host tissue cells, offers a valuable tool for in vitro organ mimicry. This allows researchers to manipulate various cellular, molecular, chemical, and biophysical parameters in a controlled manner, either individually or in combination, to study their impact on the development and progression of human cancers, as well as the efficacy of therapeutic interventions (
4 Application of tumor organoids cocultured with pathogenic microorganisms
Coculture techniques have been widely utilized in the field of biology to investigate interactions between various cell populations, or cells and pathogenic microorganisms (
4.1 Brain tumor organoids and viral infections
Gliomas are the most common and lethal primary malignant adult brain tumors, in which glioblastomas are the most common (Zavala-Vega et al., 2019). EBV, a member of the herpesviridae family, was the first oncolytic virus to be described. Since then, several viruses associated with cancer have been identified (
In 2013, Lancaster and Knoblich developed a methodology for culturing brain organoids comprising multiple brain regions. As the organoid develops, cerebrospinal fluid similar to that in the lateral ventricles is found within the neuroepithelial buds. Concurrently, the neuroepithelial cells undergo additional differentiation and migration towards the outer layers, culminating in the formation of brain organoid cultures with various brain regions, including the forebrain, choroid plexus, hippocampal region, and prefrontal lobe (
The human brain is frequently susceptible to viral infections, and numerous viral families contain neurotropic viruses (Ruiz-Guillen et al., 2017; Tavcar et al., 2021). Neurological infections can cause central nervous system disorders, consequently leading to fatality or long-term consequences (
4.2 Lung organoids and viruses
Lung cancer stands as the leading cause of cancer-related death worldwide (
Recently, lung organoids have shown their suitability as the models for studying respiratory viruses. In a previous study, respiratory syncytial virus (RSV) and human parainfluenza virus (HPIV) were found to successfully infect human airway organoids (Porotto et al., 2019), which might serve as a versatile model for studying hereditary, malignant, and infectious pulmonary diseases (Sachs et al., 2019). There are also studies that use differentiated airway organoids to predict the infectivity of emerging respiratory viruses, including human and avian influenza viruses and zoonotic coronaviruses (
Regarding respiratory infectious diseases, virologists are trying to use organoid models as platforms to understand the mechanisms of viral infection, cell deregulation and drug screening, but there is still much to do in bacterial and parasitic infections (
4.3 Nasopharyngeal carcinoma organoids and EBV
Nasopharyngeal carcinoma (NPC) is a highly aggressive malignant tumor. Its etiology is multifactorial, in which EBV infection may be a major pathogenic factor (
4.4 Gastric cancer organoids and H. pylori
H. pylori is an organism related to ulcer disease and gastric cancer, and its oncogenic actions fully reflect the intricate interplay between human cells, microorganisms, and the environment (Wroblewski et al., 2010). H. pylori infection can cause chronic inflammation of the gastric mucosa, resulting in gastric mucosal cell changes and atrophy to promote development of precancerous lesions and cancer.
Over a decade ago, human gastric organoids (hGOs) were successfully established utilizing gastric cancer tissue, cancerous site tissue, and induced PSCs (
The timeline from H. pylori infection to gastric atrophy, intestinal metaplasia and intraepithelial neoplasia may be months to years long (Piazuelo et al., 2021). During this period, the loss of acid-secreting parietal cells makes the stomach in a relatively hypochlorous environment, promoting changes in the composition of the gastric microbiota (
4.5 Hepatocellular cancer organoids and HBV
HBV infection is the primary etiological factor for chronic cirrhosis and HCC (
In 2021, a research team successfully cultured a liver organoid-derived primary in vitro HBV infection model from a healthy donor (
4.6 Cervical cancer organoids and HPV
Over 90% of cervical cancer patients are attributed to high-risk HPV infection, particularly HPV-16 and HPV-18. High-risk HPV is known to cause cervical cancer through the expression of its E6/E7 proto-oncoproteins (Pal and Kundu, 2020). The squamocolumnar junction (SCJ) is the primary site of HPV infection (Rajendra and Sharma, 2019). Nevertheless, the absence of human-derived in vitro models for the SCJ has hindered the research on precancerous lesions and HPV-related cancers.
In 2020, researchers successfully generated organoids derived from the normal SCJ region using stromal gel 3D culture technology. These SCJ organoids primarily consisted of squamous cells in a compact structure, with some mucin-secreting uterine cervical canal cells present alongside the squamous cell population. Transcriptome analysis revealed elevated expression levels of SCJ marker genes in these organoids compared to immortalized cervical cell lines originating from non-SCJ regions (Maru et al., 2020). As a predominant subtype of cervical cancer, squamous cell carcinoma (SqCa) (Sahasrabuddhe et al., 2012) comprises 70% of all cases and typically follows a progression from HPV infection to low-grade squamous intraepithelial lesion (LSIL), then to high-grade squamous intraepithelial lesion (HSIL), with a process that may span over a decade (
Small cell carcinoma of the cervix (scCC) is also a rare and highly aggressive cancer associated with HPV. In a previous study, the organoids from a patient with HPV18-positive scCC were generated. Through whole exome sequencing and RNA-seq, therapeutic targets specific to HPV-derived scCC were identified. Additionally, utilizing organoids and organoid-derived mouse xenograft models, drug sensitivity testing was conducted. The findings all suggest the potential of tumor organoids in uncovering targets for rare cancers (
5 Conclusions and prospects
Pathogenic infection may appear in various anatomical locations within the host, which is usually considered to be an inducement for diseases (
Figure 3

A schematic diagram of organoids to study diverse links of the chain of infection model.
Notwithstanding these challenges, the coculture system of tumor organoids with pathogenic microorganisms is significant in comprehending and simulating the status of human viral infection, in vivo homeostasis, and disease progression. Outside the gastrointestinal tract, the microbiota can affect the immune function by regulating the balance of Treg cells, γδT cells, and cytokine production. The brain interacts with the gastrointestinal system through a vast network described as the gut-brain axis, which may be expanded to include the gut microbiota, thus labeling the gut-microbiota-brain axis (Patterson et al., 2019). The existing preclinical data show that head injury can cause structural and functional damage to the digestive tract, but there is no experimental model that directly reflects this research (Sundman et al., 2017). Despite this gap, the coculture method proposed in this study may be used as a reference.
In the future, efforts will be made to gradually overcome the constraints above. The utilization of tumor organoid-based coculture models holds promise for enhancing patient-derived disease models, drug screening and stem cell research, as well as elucidating the interactions between pathogen-induced infection and tumor mechanisms, which paves the way for translational research and personalized treatment.
Statements
Author contributions
XZ: Writing – original draft, Investigation, Conceptualization, Writing – review & editing, Supervision. SS: Supervision, Writing – review & editing, Conceptualization, Investigation, Writing – original draft. SC: Formal analysis, Writing – original draft, Investigation, Data curation, Writing – review & editing. JD: Data curation, Investigation, Formal analysis, Writing – review & editing, Writing – original draft. FD: Resources, Writing – review & editing, Writing – original draft, Methodology, Investigation. JW: Writing – original draft, Resources, Writing – review & editing, Investigation, Methodology. DW: Writing – original draft, Methodology, Resources, Investigation, Writing – review & editing. YY: Supervision, Writing – original draft, Writing – review & editing, Conceptualization. YL: Funding acquisition, Writing – original draft, Supervision, Writing – review & editing, Conceptualization.
Funding
The author(s) declare that financial support was received for the research and/or publication of this article. This work was supported by the Key Laboratory of Precision Medicine for Malignancies in Liaoning Province (No.: k2229).
Conflict of interest
Authors FD and JW were employed by the company Kingbio Medical Co., Ltd.
The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declare that no Generative AI was used in the creation of this manuscript.
Publisher’s note
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Summary
Keywords
tumor organoids, microorganisms, pathogenic infection, coculture, interactions
Citation
Zhang X, Sun S, Cheng S, Dai J, Du F, Wang J, Wei D, Yan Y and Liu Y (2025) Coculture of tumor organoids with pathogenic microorganisms: a novel system to mimic in vivo pathogenic infection. Front. Cell. Infect. Microbiol. 15:1601688. doi: 10.3389/fcimb.2025.1601688
Received
28 March 2025
Accepted
11 June 2025
Published
30 June 2025
Volume
15 - 2025
Edited by
Tania Wong, Rutgers University, Newark, United States
Reviewed by
Cristina Giogha, Hudson Institute of Medical Research, Australia
Upasana Das Adhikari, Massachusetts General Hospital and Harvard Medical School, United States
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Copyright
© 2025 Zhang, Sun, Cheng, Dai, Du, Wang, Wei, Yan and Liu.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Yefu Liu, 97902153@cmu.edu.cn; Yichao Yan, yanyichao@pkuih.edu.cn
†These authors share first authorship
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