Organoid development and applications in gynecological cancers: the new stage of tumor treatment.

Organoids derived from BC tissues have become an essential tool for cancer research due to their ability to preserve the architectural and molecular characteristics of the original tumors. Similar to GC organoids, BC organoids are used to study tumor heterogeneity, genetic mutations, and drug responses, thereby providing insights into the biology of breast tumors that are difficult to capture in conventional 2D cell cultures. Recent studies have shown that BC organoids closely recapitulate the histological features of the original tumors, including receptor expression (e.g., estrogen receptor, progesterone receptor, and HER2), which is crucial for understanding tumor biology and guiding therapeutic decisions in clinical practice [ 102 ]. Moreover, organoid models are increasingly being employed in the development of precision medicine for BC, as they allow for high-throughput drug screening and the testing of personalized treatment regimens. A key advantage of BC organoids, similar to those from gynecological cancers, is their ability to maintain the genomic and transcriptomic features of the primary tumor, making them ideal for the testing of novel drugs and identifying potential biomarkers for targeted therapies [ 103 ]. However, it is important to note several critical differences between BC and GC organoids. While both organoid types generally maintain tumor-specific genetic mutations and molecular signatures, the TME plays a more prominent role in BC research, particularly in the context of stromal interactions and immune microenvironment. BC organoids have been frequently co-cultured with fibroblasts, immune cells, and endothelial cells to study the influence of these components on tumor progression and drug resistance [ 104 ]. In contrast, GC organoids are typically studied in isolation, with fewer studies incorporating the TME components, though this trend is starting to change as co-culture techniques become more widely adopted. In terms of drug screening, BC organoids have been shown to be particularly effective in evaluating responses to chemotherapy, endocrine therapy, and targeted therapies such as PARP inhibitors and CDK4/6 inhibitors, which have emerged as promising treatments for various BC subtypes [ 105 ]. This is similar to the use of GC organoids, where drug screening has also played a significant role in identifying novel therapeutic options for cancers such as OC and EC. Overall, while BC organoids offer significant potential for personalized medicine and drug development, they also highlight some key differences in TME composition and stromal interactions when compared to GC organoids. This comparison underlines the versatility of organoid models across different cancer types and their potential to revolutionize cancer research and treatment strategies.

GC organoids preserve the histological architecture, genetic profiles, and tumor heterogeneity of the original tumors, thus facilitating the development and application of personalized treatment strategies. In the context of understanding the pathogenesis of female reproductive system malignancies, as well as drug screening and efficacy prediction, organoid-based preclinical tumor models enable precise selection of therapeutic approaches. While organoid technology holds significant promise in biomedical research, further optimization of culture protocols is essential. This includes the incorporation of both tumor parenchymal cells and stromal components to more faithfully replicate the in vivo TME. Ultimately, organoid models are poised to establish comprehensive cancer modeling systems, providing an efficient platform for tumor prevention research, personalized treatment design, and patient survival prediction.

Organoids technology is rapidly advancing, with future priorities centered on tumor model establishment, personalized medicine and new drug development [ 22 ]. Organoids simulate the structure and cell interactions of tumor tissues within three-dimensional culture systems, offering significant advantages over traditional animal models and two-dimensional cancer cell lines. This approach facilitates a better understanding of tumor mechanisms and provides more accurate assessments of drug efficacy and safety [ 106 – 108 ]. Organoids have emerged as transformative tools in biology and biomedical sciences, offering unprecedented opportunities to study human physiology and disease (Fig.  7 ). These three-dimensional cell culture systems closely mimic the architecture and function of human organs, making them invaluable for a wide range of applications across various scientific disciplines. Besides, traditional organoid models predominantly replicate the properties of tumor cells, and the tumor microenvironment is largely absent. The influence of the TME is typically studied through co-culture experiments rather than relying solely on organoid cultures themselves [ 109 ]. While organoids are valuable for studying tumor cell biology, they do not fully recreate the complex cellular interactions present in the native tumor environment. For example, without the presence of immune cells or stromal cells, organoids cannot accurately mimic the regulatory effects of the TME on tumor cell behavior. To overcome this limitation, an increasing number of studies have utilized co-culture systems, combining organoids with various cell types, such as immune cells or fibroblasts, to more fully reconstruct the tumor microenvironment and study its impact on cancer progression [ 110 ]. These co-culture models not only enhance the clinical relevance of organoid research but also provide a valuable platform for studying cancer immunotherapy. Fig. 7 The potential application of organoids in different biology or biomedical sciences. Organoids are valuable for studying metabolomics and nutrient transport in disease and normal conditions. Intestinal organoids can investigate gut-microbiome effects using techniques like microinjection, mixing with Matrigel, or co-culturing in ECM. They also aid in infectious disease research by co-culturing with related viruses. Organoids help understand cell niches and microenvironments through embedding with tumor microenvironment cells, adding factors to culture media, or using air–liquid interface techniques. In drug screening and personalized medicine, patient-derived organoids identify optimal treatments for specific diseases or individual patients, enhancing therapeutic precision and effectiveness The potential application of organoids in different biology or biomedical sciences. Organoids are valuable for studying metabolomics and nutrient transport in disease and normal conditions. Intestinal organoids can investigate gut-microbiome effects using techniques like microinjection, mixing with Matrigel, or co-culturing in ECM. They also aid in infectious disease research by co-culturing with related viruses. Organoids help understand cell niches and microenvironments through embedding with tumor microenvironment cells, adding factors to culture media, or using air–liquid interface techniques. In drug screening and personalized medicine, patient-derived organoids identify optimal treatments for specific diseases or individual patients, enhancing therapeutic precision and effectiveness In GC research, organoids derived from patient tumors—often referred to as tumor organoids—have proven invaluable for studying tumor biology and testing therapeutic interventions. Unlike conventional 2D models, tumor organoids preserve the complex genetic and phenotypic characteristics of the original tumors, which is crucial for understanding tumor heterogeneity, drug resistance, and metastasis. These models are increasingly used in the development of personalized medicine approaches, where different treatment regimens can be tested on patient-specific organoid models to identify the most effective therapies [ 105 ]. This ability to accurately mirror in vivo tumor biology helps researchers better predict treatment outcomes and side effects, providing a more reliable platform for drug testing compared to traditional cancer models. For example, recent studies have utilized EC organoids to investigate the molecular mechanisms underlying tumor growth and metastasis. These models have enabled the identification of novel therapeutic targets and the testing of targeted therapies, contributing to personalized treatment plans [ 111 ]. Additionally, in OC, organoid models derived from patient tumors have been instrumental in exploring the mechanisms of drug resistance, offering new avenues for overcoming therapeutic challenges in treatment-resistant cancers [ 104 ]. Organoids have shown great promise in drug screening, particularly in gynecological cancers. The three-dimensional structure of organoids better replicates the complexity of tumor tissues, including interactions between tumor cells, stromal cells, and the extracellular matrix. This improved mimicry of the tumor microenvironment enhances the predictive power of drug response assays, which is critical for evaluating the efficacy and safety of potential treatments [ 112 ]. For instance, ECOs have been used to screen for compounds that target specific mutations found in patient tumors, helping identify the most promising drugs for individual patients [ 113 ]. In OC, researchers have developed patient-specific organoid models to predict responses to chemotherapeutic agents, improving the accuracy of drug sensitivity testing. These models are not only important for evaluating existing drugs but also for discovering new therapeutic agents. The ability to test multiple drugs in a high-throughput fashion using patient-derived organoids allows for the identification of treatment regimens that could lead to better clinical outcomes with fewer side effects [ 114 ]. The clinical trials of organoids in gynecological cancer were displayed in Table  7 . Table 7 The clinical trials of organoids in gynecological cancers Cancer type Clinical trial Status Enrollment Primary outcome measures Ovarian cancer NCT04555473 Unknown 48 Reliability (yes/no) of HGSOC organoids obtained from PDS+adjuvant Chemotherapy and NACT+IDS cases as a model for the patient's response to treatments. NCT06085404 Recruiting 48 To improve the knowledge of advanced ovarian cancer by developing an Experimental laboratory model NCT05175326 Unknown 64 Prediction of the response to treatment by the patient-derived organoids. NCT05290961 Recruiting 30 Progression-free survival NCT04768270 Recruiting 30 PFS, OS NCT06317610 Recruiting 100 AUC of growth prediction performance using deep learning model Accuracy of growth prediction using deep learning model NCT06229522 Recruiting 150 To assess if the drugs' sensibility tested in the 3D organoids derived from biopsies and ascites fluids could predict the clinical response (PFS and PFI) to therapy Regimen for each individual ovarian cancer patient. NCT05813509 Recruiting 30 Objective remission rate Gynecological tumor NCT06155370 Not yet recruiting 200 Construction of BioBank The clinical trials of organoids in gynecological cancers In addition to the more commonly studied gynecological cancers such as ovarian, cervical, and endometrial cancers, vulvar and vaginal cancers are also significant contributors to the global burden of gynecological malignancies. However, unlike the better-characterized cancers, there is limited research on the development of organoid models for these types of tumors. This lack of detailed models hampers our ability to understand the molecular mechanisms driving vulvar and vaginal cancers, as well as to explore targeted treatment options for these rare and often aggressive cancers. One of the challenges in studying these cancers using organoid models is the relative scarcity of patient-derived tissues, which makes it difficult to establish comprehensive organoid biobanks. Further efforts are needed to develop organoid models for vulvar and vaginal cancers to better understand their unique biological characteristics and improve treatment options. This represents a notable gap in the current landscape of gynecological cancer research, and addressing this issue could significantly enhance the applicability of organoid technology for these underserved cancer types. Despite their potential, the use of organoids in gynecological malignancy research faces several challenges. One key issue is the limited recapitulation of the full complexity of the tumor microenvironment in organoid models. Organoids typically lack a complete stromal component and immune cell interactions, which limits their capacity to fully mimic the immune response to treatment [ 115 ]. While co-culture systems are being developed to address this gap, these models are still in the early stages of optimization. Additionally, organoids derived from extended passages may develop a monoclonal population of cells, potentially losing the heterogeneity present in the original tumors. This loss of diversity could affect the accuracy of drug sensitivity assays and reduce the reliability of these models for predicting treatment outcomes in patients [ 105 ]. Standardization of culture protocols and drug testing procedures is needed to overcome this challenge and ensure the reproducibility of results across different research groups and clinical settings. Ethical concerns also arise with the use of organoids, particularly those derived from human tissues and stem cells. Issues related to the ownership of biological samples, the use of gene editing technologies, and the potential for exploitation of patient data must be carefully addressed through clear legal and ethical guidelines. These concerns are particularly pertinent in gynecological research, where the use of sensitive patient data and tissues for organoid generation requires strict oversight to ensure ethical compliance [ 116 ]. Despite the significant advancements in the use of organoids for gynecological cancer research, several limitations should be acknowledged. First, while organoid models replicate the genetic and phenotypic characteristics of primary tumors, they do not fully mimic the complexity of theTME, particularly the interactions with stromal components and immune cells. This limits their ability to capture the multifactorial nature of tumor progression and response to therapies, especially in the context of immunotherapy. Additionally, organoids often lack the full representation of pharmacokinetic and pharmacodynamic processes, such as drug absorption, distribution, metabolism, and excretion, which are essential for predicting drug efficacy and safety in vivo. The limited availability of patient-derived tissue, especially for rarer cancers like vulvar and vaginal cancers, further restricts the development of comprehensive organoid models for these malignancies. Furthermore, prolonged culture and passaging of organoids can lead to the loss of tumor heterogeneity, affecting their ability to represent diverse tumor subpopulations and influencing the accuracy of drug sensitivity assays. There are also challenges in maintaining the stability of genetic and phenotypic traits over time, which may impact the long-term relevance of organoid models. Lastly, the lack of an integrated immune system in organoid models hinders the study of immune-tumor interactions, which are crucial for the development of effective immunotherapies. Addressing these limitations through advanced co-culture systems, improved tissue procurement, and better standardization of protocols will be essential for enhancing the applicability and predictive power of organoids in gynecological cancer research. Looking forward, organoid technology holds great promise for advancing research and treatment in gynecological malignancies. As these models continue to evolve, they will provide more accurate representations of the TME, offering unprecedented opportunities to study the molecular mechanisms driving cancer initiation, progression, and metastasis in GCs [ 117 ]. Moreover, by identifying critical signaling pathways within these models, researchers can discover novel therapeutic targets that could lead to the development of targeted therapies specifically tailored to gynecological cancers. Personalized treatment strategies will be a key focus, with patient-specific organoid models providing insights into the most effective drug regimens. For example, by developing organoid models from ovarian cancer patients, researchers can screen multiple treatment options and identify regimens that are most likely to improve clinical outcomes and minimize adverse side effects [ 104 ]. Additionally, organoid-based research will continue to improve our understanding of chemoresistance, particularly in cancers like endometrial and ovarian cancer, where resistance to standard therapies is a major challenge. Overall, while organoid technology has already proven to be a valuable tool in the study of gynecological malignancies, continued innovation in culture techniques, drug screening, and genetic engineering will further enhance its clinical utility. Overcoming current limitations and addressing ethical concerns will be essential for fully realizing the potential of organoids in personalized medicine and improving treatment outcomes for patients with gynecological cancers.

Organoids have emerged as a transformative tool in the screening of drugs for gynecologic tumors. These three-dimensional cell culture systems closely mimic the architecture and functionality of human tissues, providing a more accurate model for drug testing compared to traditional cell lines. By using patient-derived organoids from ovarian, endometrial, and cervical cancers, researchers can evaluate the efficacy and toxicity of potential therapeutic agents in a personalized manner. This approach enhances the prediction of clinical responses, facilitates the identification of effective treatments, and reduces the risk of adverse effects, ultimately improving patient outcomes in gynecologic oncology. Gynecological malignancis-derived organoids for drug screening was showed in Table  6 . Table 6 Gynecological malignancis-derived organoids for drug screening Cancer Source of tissue Original tumor type Similarity of original tumor Sensitive drugs Resistant drugs References BOT Surgical resection BOT patients Genetic characteristics, biomarker, and structural functions Bractoppin / [ 79 ] UCS Surgical resection / Histological heterogeneity, pathological characteristics and molecular phenotype Gemcitabine, Gemcitabine+Carboplatin/Paclitaxel Ifosfamide, Carboplatin+Paclitaxel [ 80 ] Surgical resection; Ascitic fluid; Uterine brush UCS/APAM Genetic and histological characteristics Lapatinib Standard chemotherapy drugs [ 81 ] CC Biopsy sample cCCC Histology, immunostaining profile, and genomic features Paclitaxel, cisplatin, gemcitabine, and MET inhibitors / [ 82 ] Surgical resection; Biopsy sample SqCa, AdCa, NECC, VGA Genetic mutation spectrum and copy number variation features Bortezomib, MLN2238, MLN9708, Carfilzomib, Panobinostat, Romidepsin, Homoharringtonine / [ 83 ] Surgical resection / Genetic characteristics and tissue structure Trabectedin, Trabectedin+Propranolol / [ 84 ] Surgical resection; Biopsy sample HSIL, SqCa Histological, biomarker, chromosomal, and molecular characteristics Gemcitabine, Paclitaxel, Platinum-based drugs Cisplatin, Carboplatin [ 129 ] EC Surgical resection / Histological characteristics and gene mutation MI-136 / [ 84 ] Surgical resection / Morphological and molecular characteristics FGFR inhibitor (Infigratinib/Pemigatinib) / [ 86 ] Surgical resection EC, EAC, LNM Histological and immunophenotypic characteristics Napabucasin, Fulvestrant / [ 87 ] Surgical resection EC(REME9、REME11 and REME16) Morphological, gene expression, and in vivo biological characteristics paclitaxel, carboplatin, and mitoxantrone / [ 88 ] OC Ascitic fluid OS Histological, genomic characteristics, increased p53 expression Bleomycin, Belinostat, Bleomycin+Belinostat, AZD1775 Bevacizumab, Olaparib [ 89 ] Biopsy sample HGSOC Molecular and cellular phenotypes Paclitaxel, Carboplatin, Doxorubicin, Gemcitabine / [ 90 ] Ascitic fluid HGSOC Morphological and molecular characteristics APR-246, CB-5083, MK-1775, Sorafenib Paclitaxel, Carboplatin [ 91 ] Surgical resection HGSOC Morphology, proliferative activity, and biomarker PARPi / [ 92 ] Surgical resection HGSOC / Etoposide / [ 93 ] Surgical resection; Ascitic fluid HGSOC, LGSOC, HGAC, SBT, MAC, CCC, ENDC Genomic features HGSOC: Carboplatin, Paclitaxel LGSOC: carboplatin, paclitaxel [ 94 ] Surgical resection CCC, HGSOC(HGSOC-1/HGSOC-2), EMC Histological features, gene mutations, heterogeneity HGSOC-1: Olaparib, Cisplatin; HGSOC-2: Trabectedin HGSOC-2: most resistance; CCC: Cisplatin, Carboplatin, Olaparib [ 95 ] Surgical resection HGSOC Genetic mutation spectrum and gene expression patterns / 1 in 6 PDOs: Carboplatin [ 96 ] Surgical resection; Ascitic fluid HGSOC Histological characteristics and therapeutic responses Carboplatin, paclitaxel, doxorubicin, and atraleukin / [ 97 ] Surgical resection LGSOC Histological and biological characteristics, somatic genomic variation spectrum Gemcitabine, ibrutinib Paclitaxel, oxaliplatin [ 98 ] Surgical resection HGSOC Histology, genetic characteristics, biological behavior, and therapeutic response Topotecan, niraparib / [ 99 ] Surgical resection LGSOC Genetic characteristics, whole-genome characteristics and treatment history  Tucatinib, Lapatinib, Trastuzumab emtansine, Neratinib Everolimus, Crizotinib, Enzalutamide [ 100 ] Surgical resection HGSOC Histological characteristics, genomic characteristics Carboplatin, THZ531 Olaparib [ 101 ] Gynecological malignancis-derived organoids for drug screening HGSOC-1: Olaparib, Cisplatin; HGSOC-2: Trabectedin HGSOC-2: most resistance; CCC: Cisplatin, Carboplatin, Olaparib Borderline ovarian tumors represent approximately 15% of all ovarian tumors. Cheng et al. developed 13 PDO models from BOTs, which can be stably cultured in vitro for over three months while accurately replicating the genetic and morphological characteristics of the primary tumors. Bractoppin, a BRCA1 C-terminal domain inhibitor, effectively suppresses the growth of BOT-derived PDOs and induces apoptosis. Its mechanism of action includes the inhibition of cell cycle progression, impairment of DNA repair processes, and promotion of apoptosis. Furthermore, Bractoppin exhibits anti-tumor activity in OC cell lines by inhibiting homologous recombination and non-homologous end joining repair pathways. This study underscores the utility of BOT-derived PDOs in assessing targeted therapies and validates Bractoppin's potential as a therapeutic agent [ 79 ]. The Dahl research team established PDO models from tumor samples of a patient with uterine carcinosarcoma and performed comprehensive phenotypic analyses. The PDOs expressed both epithelial and mesenchymal markers, such as E-cadherin and N-cadherin, and displayed a range of morphologies, including columnar and squamous epithelium. The study evaluated the effects of six single-agent treatments and nine combination therapies, finding that gemcitabine, both as a monotherapy and in combination with carboplatin or paclitaxel, significantly induced apoptosis, surpassing the efficacy of the carboplatin + paclitaxel regimen [ 80 ]. Hippo et al. established three PDOs from late-stage uterine carcinosarcoma patients, sourced from surgical tumor resection, peritoneal lavage fluid, and endometrial curettage. The three PDOs exhibited variations in morphology, proliferation rates, and genetic characteristics, reflecting tumor heterogeneity, and showed differing sensitivities to HER2 inhibitors and standard cytotoxic drugs. These variations were consistent with the heterogeneous expression of HER2 within the tumors. Multiple PDOs more accurately represent spatial tumor heterogeneity, offering valuable resources for uterine carcinosarcoma research. However, the sensitivity of PDOs to drugs may not always align with in vivo treatment responses, potentially due to non-cell-autonomous factors influencing in vivo conditions [ 81 ]. Cervical clear cell carcinoma (cCCC) is a rare subtype of CC, and its pathogenesis remains largely unexplored due to the scarcity of cell lines and preclinical models. Researchers established cell lines from biopsy samples of cCCC patients and developed organoids that were cultured for over six months. Genomic analysis of these organoids provided new insights, revealing their sensitivity to major chemotherapeutic agents and MET inhibitors, thereby indicating their potential as novel preclinical models for studying cCCC [ 82 ]. Nam et al. generated organoid models from four patients with various types of CC, accurately replicating the primary features of the original tumors, such as DNA copy number and mutation profiles. They identified KMT2C gene mutations across all types of CC PDOs, which may represent potential therapeutic targets. Screening of 171 FDA-approved drugs identified seven that had growth-inhibitory effects on CC organoids. The study observed differential responses of CC PDOs to drugs and radiation therapy; specifically, adenocarcinoma and large cell neuroendocrine carcinoma were resistant to radiation, whereas squamous cell carcinoma and papillary adenocarcinoma exhibited greater sensitivity [ 83 ]. Another study employed PDOs derived from surgical specimens of three CC patients to assess the antitumor effects of Trabectedin alone and in combination with the β-blocker Propranolol. Trabectedin inhibited the proliferation of CC cell lines and patient-derived CC tumor organoids by inducing DNA double-strand breaks and S-phase cell cycle arrest. Propranolol augmented the efficacy of Trabectedin through mechanisms involving mitochondrial involvement, ERK1/2 activation, and increased COX-2 expression, thereby counteracting Trabectedin resistance caused by β-adrenergic receptor activation [ 84 ]. Liao et al. developed a long-term 3D organ culture system, establishing HSIL and SqCa organoid libraries. These models preserved the genomic, transcriptomic, and HPV characteristics of the original tissues and demonstrated variable responses to chemotherapeutic agents and mouse xenograft assays. Co-culturing the organoids with immune cells stimulated by HPV antigens elicited virus-specific T cell responses, supporting their utility in HPV vaccine screening [ 84 ]. Researchers have developed a primary mouse model of EC driven by mutations in the Trp53, Pten, and Pik3r1 genes and subsequently cultured EC organoids. Screening of a small molecule compound library targeting epigenetic factors revealed that MI-136, an inhibitor of the Menin-MLL complex, significantly inhibited organoid growth, potentially through modulation of the HIF pathway, thereby proposing MI-136 as a novel therapeutic strategy for EC [ 85 ]. Pollock et al. established 16 PDX organoids from various EC subtypes, demonstrating the morphological and molecular characteristics of the primary tumors. PDX organoids with high or medium FGFR2 expression were significantly sensitive to the FGFR inhibitor BGJ398. In vivo experiments showed that PDXs with high or medium FGFR2 expression exhibited substantial tumor growth inhibition and prolonged survival when treated with FGFR inhibitors. In PDX models with abnormal p53, Pemigatinib in combination with cisplatin demonstrated notable efficacy [ 86 ]. Smith et al. created PDOs from tissues of 15 EC patients, including both primary EC and lymph node metastasis (LNM) PDOs. They found that the STAT3 inhibitor BBI608 strongly inhibited PDO growth, emphasizing the importance of stem cell characteristics. Additionally, various tyrosine kinase inhibitors were effective in inhibiting the growth of certain PDOs, highlighting variability in growth factor signaling pathways among PDOs. Notably, four PDOs were sensitive to anti-E2 drugs, underscoring the significance of E2 receptor signaling [ 87 ]. Researchers also established 53 Fukushima organoids from different tumor tissues and conducted detailed analyses on three EC-derived Fukushima organoids (REME9, 11, and 16). These Fukushima organoids were capable of long-term culture, preserving morphological and gene expression characteristics similar to the original tumor tissues. Transplantation of these three Fukushima organoids into mice confirmed their tumorigenic capabilities, though with varying growth rates. High-throughput screening using REME9 and 11 assessed the efficacy of various antitumor drugs, revealing notable resistance to certain drugs such as paclitaxel and carboplatin. This study provides valuable research tools for personalized tumor treatment [ 88 ]. Leslie et al. established organoid models from OC cells isolated from the ascites of patients with advanced ovarian sarcoma and identified a rare N131 deletion mutation in the tumor suppressor gene TP53. The cultured organoid models exhibited overexpression of the p53 protein, and computational modeling suggested that this residue is crucial for maintaining protein conformation. Drug screening revealed that a combination of protease inhibitors and histone deacetylase inhibitors was particularly effective against these organoid models, highlighting the potential of PDOs in cancer modeling and therapeutic evaluation [ 89 ]. Researchers created OC organoid models from HGSOC patient tissues and tested various culture medium components. The addition of neuregulin-1 significantly increased both the number and expandability of organoids, which exhibited morphologies and characteristics akin to the patient's tumors, replicating markers and mutation profiles of the primary tumors and showing tumor-specific sensitivity to clinical chemotherapy drugs [ 90 ]. Smith et al. utilized multicellular spheres from malignant effusions of HGSOC patients to construct short-term organoid models. RNA sequencing analysis revealed significant upregulation of genes related to proliferation, epithelial-mesenchymal transition, and KRAS signaling pathways within six days of culture, identifying several potential therapeutic drugs for HGSOC [ 91 ]. Han et al. cultured OC-derived PDOs and treated them with the PARP inhibitor olaparib, which significantly inhibited organoid growth and reduced the proportion of Ki67-positive cells. However, some cells survived at high PARP inhibitor concentrations, indicating resistance. Gene expression analysis provided insights into the mechanisms of PARP inhibitor resistance, affecting several key genes, including some previously unreported ones [ 92 ]. A quantitative study using γH2AX markers investigated the response of four OC organoid models to etoposide, finding that one organoid model was unresponsive, confirming its resistance. This imaging and analysis method can be applied to other 3D organoid and spheroid models for high-throughput screening, offering new tools for TT research [ 93 ]. Stelloo et al. evaluated the use of OC PDOs as preclinical models by constructing 36 PDOs from 23 patients and conducting whole-genome sequencing. Results demonstrated that PDOs retained the genomic characteristics of the original tumors. Drug responses of PDOs were significantly correlated with clinical responses, with PDO responses to carboplatin and paclitaxel aligning with patients' clinical response scores, CA-125 levels, and RECIST criteria. PDOs exhibited inter- and intra-patient heterogeneity in drug responses, with most showing poor responses to carboplatin and paclitaxel but better responses to gemcitabine; LGSOC-derived PDOs often exhibited resistance to carboplatin and paclitaxel [ 94 ]. In another study, researchers successfully established OC organoids from HGSOC, cCCC, and EC with an 80% success rate and a culture period of within three weeks. organoids retained the genomic features of the primary tumors, with 59.5% of gene mutations consistent with those in the primary tumors, and replicated copy number variations. HGSOC organoids with pathogenic BRCA1 mutations were more sensitive to PARP inhibitors and platinum-based drugs, whereas cCCC organoids showed resistance to conventional drugs [ 95 ]. Kolesar et al. established six HGSOC organoids from debulking surgery tissues, finding that UK1254 was resistant to carboplatin. Gene expression analysis indicated an association with the NF-κB signaling pathway, cell differentiation, and B cell receptor signaling and PI3K-Akt pathways [ 96 ]. Rizzolio et al. developed a passive microfluidic platform for culturing 3D cancer organoids from HGSOC patients. This platform improved organoid growth, reduced cell death, and enhanced drug penetration and efficacy. Testing standard chemotherapy drugs (carboplatin, paclitaxel, doxorubicin) and targeted drugs on the platform showed lower IC50 values, demonstrating its potential for simulating treatment and personalizing therapy [ 97 ]. Several cases have highlighted the significant responses of serous OC patients to targeted therapies. One patient with low-grade serous OC responded exceptionally well to ibrutinib despite previous ineffective standard chemotherapy and two surgeries, with drug sensitivity testing showing high efficacy of ibrutinib and resulting in notable clinical improvement with monotherapy [ 98 ]. Another 59-year-old female patient with recurrent HGSOC relapsed after surgery and chemotherapy; tumor models established from ascites demonstrated the effectiveness of topotecan and niraparib, with topotecan treatment significantly lowering CA-125 levels and alleviating symptoms [ 99 ]. Additionally, a stage IV low-grade serous OC patient, after failing multiple lines of treatment, responded effectively to a combination of fulvestrant and everolimus through in vitro drug sensitivity testing, stabilizing the disease for seven months [ 100 ]. These cases underscore the potential value of in vitro drug sensitivity testing for personalized treatment. Sette et al. confirmed the strong anticancer activity of CDK12/13 inhibitors using HGSOC cell lines and PDO models. High-throughput RNA sequencing revealed that CDK12/13 inhibition induced extensive transcriptome reprogramming, including intron retention and premature transcriptional termination, affecting DNA repair genes, EGFR, and mTORC1 regulatory proteins. Combining CDK12/13 inhibitors with EGFR inhibitors, mTORC1 inhibitors, paclitaxel, PARP inhibitors, and ATR/CHK1 inhibitors significantly enhanced sensitivity in HGSOC cells and PDOs, showing clinical relevance. CDK12/13 inhibition can improve the efficacy of existing drugs, with PDO models providing an important platform for personalized medicine [ 101 ].

Gynecological cancers (GCs) include ovarian cancer (OC), cervical cancer (CC), endometrial cancer (EC), vulvar and vaginal cancers, and fallopian tube cancer [ 1 ]. Among these, OC, CC, and EC are the most common malignancies of the female reproductive system, posing significant threats to women's lives and health and representing a global public health concern [ 2 – 4 ]. Particularly, OC is difficult to diagnose early due to its hidden location, with over half of patients presenting with distant metastasis at diagnosis [ 5 – 8 ]. While early detection techniques have improved cure rates for EC and CC, treatment options remain limited for cases of recurrence and metastasis [ 9 – 11 ]. Currently, the treatment of GCs primarily involves a comprehensive approach, including surgery, radiotherapy, chemotherapy, and targeted therapy [ 12 , 13 ]. However, due to the unique anatomical relationships of GCs, complete surgical resection is challenging, leading to high recurrence rates and often impacting patients' quality of life post-surgery. Radiotherapy mainly utilizes intracavitary brachytherapy, but its effectiveness is compromised in cases of poor anatomical conditions, retroperitoneal lymph node metastasis, or extensive pelvic adhesions, resulting in incomplete target coverage and uneven dose distribution [ 1 , 14 ]. Additionally, traditional animal models and two-dimensional (2D) cell culture systems have significant limitations in simulating tumor biology and drug responsiveness, failing to fully replicate the complex microenvironment of human tumors. Therefore, finding more precise and effective treatment methods is urgent. For example, three-dimensional cell culture technology and organoid models can better mimic the biological characteristics and microenvironment of tumors to some extent, providing new means for drug screeningand personalized treatment [ 15 , 16 ]. Simultaneously, the application of immunotherapy and gene editing technologies brings new hope for the treatment of GCs. In summary, the main challenge in gynecologic tumor research is to overcome the limitations of existing technologies and find more precise and effective treatment methods. Organoids are three-dimensional (3D) culture systems derived from stem cells, which replicate the architecture and function of human organs. They retain stem cell properties like continuous division and differentiation, enabling them to closely resemble the original tissues in terms of spatial structure, genetics, and function. Organoids can be derived from various stem cell sources, including adult stem cells, induced pluripotent stem cells (iPSCs), and embryonic stem cells (ESCs), each offering unique advantages for cancer research [ 17 ] (Fig.  1 ). In cancer studies, organoids derived from adult stem cells are valuable for precision oncology because they retain the genomic integrity and tumor microenvironment (TME) of the original tumor. However, most organoid platforms primarily focus on epithelial (tumor) cells and lack the other critical cell types typically found in the TME, which limits their ability to fully replicate the complexity of cancer biology. These patient-specific models are ideal for studying drug resistance and pharmacodynamics [ 18 ]. In contrast, iPSC and ESC-derived organoids can be genetically engineered to mimic oncogenic mutations, making them versatile tools for investigating cancer mechanisms, screening drugs, and conducting functional genomics studies [ 19 ]. The integration of organoids with the TME, through both reconstituted and holistic native models, further enhances their ability to model tumor-immune interactions, immune evasion, and therapy responses [ 20 ] (Fig.  2 ). The summary of organoid types and their applications in cancer research was showed in Table  1 , while TME models and their applications were displayed in Table  2 . Overall, organoid models offer a robust and innovative approach to understanding tumor biology and developing personalized cancer therapies [ 21 ]. Fig. 1 Organoids for cancer modeling. Cancer organoid models derived from adult stem cells (ASCs) and pluripotent stem cells (PSCs) represent significant advancements in cancer research. ASCs are harvested directly from patient tumors, preserving the genetic and phenotypic characteristics of the original cancer, making them ideal for personalized medicine studies. PSCs, on the other hand, can differentiate into any cell type, enabling the creation of diverse cancer models. These organoid models are used for drug screening, understanding cancer progression, and studying tumor microenvironment interactions. Their application accelerates the development of targeted therapies and improves treatment strategies across various cancer types Fig. 2 The tumor immune microenvironment can be generated in organoids. The tumor immune microenvironment (TME) can be effectively replicated in organoids through two main approaches: reconstituted models and holistic native TME models. Reconstituted models involve incorporating specific immune cell types into the organoid culture, enabling targeted studies on cell–cell interactions and immune responses. In contrast, holistic native TME models maintain the complete microenvironment from the original tumor, preserving the complex interactions between cancer cells, stromal cells, and immune components. These advanced organoid models offer invaluable insights into the dynamics of the TME, facilitating the development of immunotherapies and personalized cancer treatments Table 1 Summary of organoid types and their applications in cancer research Organoid type Source Key features Applications References ASC-derived organoids Patient-specific tumor biopsies Preserves genomic integrity and tumor microenvironment Precision oncology, drug resistance, pharmacodynamics, personalized therapy [ 118 ] iPSC-derived organoids Induced pluripotent stem cells Genetically malleable, ideal for genetic manipulation Oncogenesis, high-throughput drug screening, functional genomics [ 119 ] ESC-derived organoids Embryonic stem cells Can be engineered to express oncogenic mutations Cancer modeling, drug screening, developmental biology [ 120 ] Reconstituted TME models Organoids with immune cell integration Study immune-cell interactions in cancer Immune evasion, immunotherapy efficacy, drug testing [ 121 ] Holistic native TME models Organoids cultured with stromal and immune components Preserves complex tumor-immune interactions in vivo Tumor-immune dynamics, personalized therapies, in-depth mechanistic studies [ 122 ] Table 2 Tumor microenvironment (TME) models and their applications Model type Description Advantages Applications PMID Reconstituted TME Models Immune cells (T cells, macrophages, NK cells) are added to organoid cultures to mimic tumor-immune interactions Flexibility, ideal for targeted studies and drug screening Immune response, immune evasion, immunotherapy testing [ 123 ] Holistic Native TME Models Tumor organoids cultured with native stromal and immune components Accurate, in vivo-like representation of TME interactions Tumor progression, immune dynamics, personalized therapies [ 124 ] Organoids for cancer modeling. Cancer organoid models derived from adult stem cells (ASCs) and pluripotent stem cells (PSCs) represent significant advancements in cancer research. ASCs are harvested directly from patient tumors, preserving the genetic and phenotypic characteristics of the original cancer, making them ideal for personalized medicine studies. PSCs, on the other hand, can differentiate into any cell type, enabling the creation of diverse cancer models. These organoid models are used for drug screening, understanding cancer progression, and studying tumor microenvironment interactions. Their application accelerates the development of targeted therapies and improves treatment strategies across various cancer types The tumor immune microenvironment can be generated in organoids. The tumor immune microenvironment (TME) can be effectively replicated in organoids through two main approaches: reconstituted models and holistic native TME models. Reconstituted models involve incorporating specific immune cell types into the organoid culture, enabling targeted studies on cell–cell interactions and immune responses. In contrast, holistic native TME models maintain the complete microenvironment from the original tumor, preserving the complex interactions between cancer cells, stromal cells, and immune components. These advanced organoid models offer invaluable insights into the dynamics of the TME, facilitating the development of immunotherapies and personalized cancer treatments Summary of organoid types and their applications in cancer research Tumor microenvironment (TME) models and their applications In GCs research, organoid technology has shown substantial potential for application. For instance, by culturing human-derived OC tumor cells under appropriate conditions within a three-dimensional cell culture system, individualized OC organoids models can be generated [ 16 ]. These OC organoids preserve the histomorphology, genomics, and transcriptomics characteristics of their source tumors. Research indicates that the in vitro drug sensitivity test results of OC organoids align with patient treatment responses, providing a valuable platform for investigating the origin, progression, and resistance mechanisms of OC [ 22 ]. Moreover, individualized OC organoids models facilitate the screening of personalized treatment plans, offering considerable clinical translational value [ 23 , 24 ]. In summary, organoids technology offers promising prospects for both fundamental research and clinical applications in gynecologic malignancies. By further refining organoids culture techniques and application strategies, it is anticipated that more effective treatment methods for gynecologic tumor patients will be developed, thereby enhancing patient prognosis, improving quality of life, and ultimately advancing precision medicine for GCs.