Next Article in Journal
Inter- and Intraobserver Variability in Bowel Preparation Scoring for Colon Capsule Endoscopy: Impact of AI-Assisted Assessment Feasibility Study
Previous Article in Journal
Prognostic Factors in Neuroendocrine Neoplasms of the Rectum
Previous Article in Special Issue
Machine Learning Models for Predicting Gynecological Cancers: Advances, Challenges, and Future Directions
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Conditionally Reprogrammed Cells as Preclinical Model for Rare Cancers

Department of Pathology, Center for Cell Reprogramming, Georgetown University Medical Center, Washington, DC 20057, USA
Cancers 2025, 17(17), 2834; https://doi.org/10.3390/cancers17172834
Submission received: 21 July 2025 / Revised: 25 August 2025 / Accepted: 28 August 2025 / Published: 29 August 2025
(This article belongs to the Special Issue Advancements in Preclinical Models for Solid Cancers)

Simple Summary

Testing new and potential drugs before they are used in patients is an essential part of biomedical science. Assessing their safety and efficiency as well as researching the mechanisms of the disease—including cancer—is performed in preclinical disease models. Advancements in designing new models are especially important for rare cancers: they are difficult to study because of their uncommon occurrence. Conditional cell reprogramming, a relatively new and promising method of culturing cells in vitro, has been already shown useful for modeling various diseases. This article describes the basics of conditionally reprogrammed technology and its applications in rare cancer research.

Abstract

Despite their disadvantages, preclinical models in vitro are still crucial for every area of biomedical science. They remain a necessary basis for biological, biochemical, and mechanistic studies of pathophysiology of human disease, evaluation of diagnostic tests, assessment of vaccines, as well as screening of potential and repurposed drugs before they are adapted to clinical use. In contrast to animal models in vivo, preclinical in vitro models are cost and time effective. They are easier to use, and, in most cases, they are not associated with ethical concerns. Therefore, they are extensively used in cancer research. Conditional cell reprogramming (CCR) has been one of the novel technologies utilized as a preclinical model in vitro for various common cancers and other diseases. It may be even more important for the research related to rare cancers—elusive, difficult to study, and with insufficient number of relevant models available. Applications of this technology for the basic and translational studies of rare cancers are described in this article. Evaluation of the mechanisms of tumorigenicity and metastasis in neuroblastoma, neuroendocrine cervical carcinoma, ependymoma and astrocytoma, as well as screening of potential drugs and other therapeutic approaches for the laryngeal and hypopharyngeal carcinoma and adenoid cystic carcinoma, demonstrate that the CCR technology is a potential reliable model for various aspects of rare cancer research in the future.

1. Introduction

Preclinical disease models are indispensable in every field of biomedical sciences, including cancer research. They are utilized worldwide for testing possible drugs, vaccines, and diagnostic tests before they are used in the clinic, among others. However, preclinical models, especially preclinical models in vitro, are not perfect and they never precisely recapitulate the pathology and pathophysiology of human organisms. Therefore, there is a constant and urgent need to develop new, advanced, and more accurate preclinical disease models [1,2,3,4,5,6,7,8].
The most basic pre-clinical models are two-dimensional (2D) established cell lines [9]. These conventional cell lines are commercially available, can be cultivated in laboratories at a relatively low cost, are easy to use, and usually no ethical concerns (in contrast to the problems associated with experimental animals use [10]) are associated with them (with the notable exception of human embryonal cell lines [11]). Conventional 2D cell lines have been crucial for innumerable inventions in the biomedical field, from assessment of the efficacy and toxicity of new and repurposed drugs, to the study of genetic and biochemical mechanisms of numerous diseases, including various cancers [12,13,14]. Two-dimensional cells enable high-throughput research [15]: the researchers can obtain very large numbers of cells within relatively short periods of time; the cells can be then biobanked [16]; they are widely available at low cost; and their use does not require particularly high experience from the researchers. However, conventional established cell lines suffer from several weaknesses. They are normally used as monolayers in two-dimensional settings; hence, they do not represent the structure of the tissue (or the cancer) they were collected from [17,18]. Regarding the cell type, they are homogenous. Therefore, studies researching the interactions between different cell types within the tissue or the tumor are not possible [19]. Two-dimensional cell lines do not recapitulate the interconnection and interactivity of tumor microenvironment [20] and do not correctly reflect tumor complexity [21]. Importantly, cell lines kept in the laboratories for many passages accumulate various mutations, as well as karyotype and phenotype changes, and they do not resemble (genetically, physiologically, metabolically, etc.) the original cell line/tissue they were collected from anymore [6,22,23,24,25]. There is also limited number of control cell lines, since normal (tumor-corresponding) cells cannot be grown in laboratory settings indefinitely [26]. The biomedical research based on 2D cell lines is further jeopardized by cross-contaminations, misidentification, and mislabeling of cells used in laboratories on a daily basis [27,28,29,30,31,32], and it has to be emphasized that cell lines should be frequently authenticated to make sure that the experiments are performed using the appropriate models.
Nevertheless, conventional cell lines remain important for various areas of cancer research. Especially for common cancers, there is a variety of available cells representing many different types and different cancer stages, even in different populations of patients. In contrast to common cancers though, rare cancers are not very well-represented in the repositories of conventional cell lines [33]. By definition, rare cancers occur infrequently, are unique, and in numerous cases, there is no adequate number of preclinical models of them available to researchers. Thus, designing and developing new disease models, including two-dimensional in vitro models, becomes crucial for rare and unique malignancies [34,35,36,37].

2. Conditional Cell Reprogramming

One of these relatively new preclinical in vitro models is the conditional cell reprogramming (CCR). The technology was developed at Georgetown University in Washington, D.C. by Drs. Richard Schlegel and Xuefeng Liu with their team, first described in 2012 [38], and its detailed protocol was published in 2017 [39]. Deemed a “valuable” model for precision oncology [4], “high-quality laboratory model” [37], “new generation functional diagnostic” [40], and “exciting technological development” [12], the CCR technology became a “major breakthrough system that enables generation of the first inexhaustible patient-specific biobank of primary epithelial cells and cancer cells from the same patient” [41]. Shortly after its development, cell conditional reprogramming emerged as a powerful tool not only in cancer research, but also in other areas of biomedical science [42].
Conditional cell reprogramming is a very efficient cell culture method that allows immortalization of both normal and cancer cells in the laboratory without infecting or transfecting cells with any viral or cellular genes [38,39]. Therefore, the cells’ native genomic composition remains unchanged. Consequently, potential therapy can be tested on a patient’s own cancer cells (with a control of the patient’s own normal cells) [43]. Thus, the CCR method constitutes an important step toward personalized medicine. The conditionally reprogrammed (CR) cells are immortalized not by genetic manipulations, but by application of a cell culture medium containing Y-27632, a Rho-kinase (ROCK) inhibitor [44,45,46], and co-culture with irradiated Swiss-3T3-J2 murine fibroblasts (feeder cells) [47]. Induction of conditional cell reprogramming is very fast; it occurs on average within 2 days. Under CCR conditions, the cells proliferate indefinitely and do not differentiate as long as the conditions are maintained [39,48]. Conditional cell reprogramming is reversible; even following a long, multi-passage cell culture, after withdrawing the CCR culture conditions, cultured cells can be differentiated into the original tissue that they were obtained from [15,38,48]. Conditionally reprogrammed cancer cells form tumors when injected into adequate mouse model [15,38,49,50]. The cells are reprogrammed to the phenotype of adult stem cells [51]. They do not express high levels of embryonic stem cell markers, such as Sox-2, Oct-4, and Nanog, but they express an increased level of α6 and β1 integrins, ΔNp63α, CD44, and hTERT (human telomerase reverse transcriptase) [48]. They also show a decreased Notch signaling and an increased level of nuclear β-catenin [48,52].
Conventional methods used for immortalization of primary cells include introduction of viral genes (SV40 virus large T antigen, HPV E6/E7 oncoproteins), overexpression of hTERT and other genes, and induction of pluripotent stem cells (iPSc) [53,54,55]. In contrast to CCR technology, they require various genetic manipulations to achieve cell immortalization. Subsequently, genomic instability, loss of some genetic and biological properties of immortalized cells, and even tumorigenicity may be observed after the procedures. These methods are usually expensive and time-consuming. For each specific method, disadvantages such as loss of tissue heterogeneity in transformed cell lines or inapplicability of iPSc for a high-throughput drug screening assays are shown Table 1.
In contrast to conventional immortalization methods, CCR technology does not require introduction of exogenous genes, is fast, reversible, and inexpensive [39]. It has to be emphasized, however, that the technology has its weaknesses as well. It allows the growth of both malignant and non-malignant cells from original tissue, and these two cell populations are difficult to distinguish. Additionally, the growth of non-malignant cells is often preferentially promoted in the culture [56,57] and special methods need to be used to successfully isolate cancer cells [15,39,49]. Importantly, tumor-associated fibroblasts and stromal cells are inhibited in the co-culture [39], and conditionally reprogrammed cells do not always recapitulate all properties of differentiated cells of tissue of origin [58]. Moreover, Y-27632 ROCK inhibitor induces cytoskeleton remodeling; therefore, it may interfere with cell morphology and motility [44,59].
The CCR technology has been shown to be applicable mainly to epithelial cells; however, it is possible to optimize cell culture conditions for other cell types [39,59,60]. Conditional cell reprogramming is a very effective and relatively non-expensive technique: within a few days, it is possible to obtain millions of fast-growing cells [39,43]. As shown in Figure 1 and described previously in detail [39], the procedure requires collection of patient tissue, including clinical biopsies [61], patient-derived xenografts (PDXs) [62,63], or liquid tissue samples, such as urine [64]. Clinical samples then undergo enzymatic/mechanic processing as necessary and are co-cultured with irradiated feeder cells in the CCR medium containing Y-27632 ROCK inhibitor. To avoid physical contact between cultured epithelial cells and feeder cells, conditioned medium (CM; medium incubated on irradiated feeder cell, collected and used as a cell culture medium [39]) is utilized. In some cases, the CCR method is optimized, i.e., modified depending on specific in vitro culture requirements of the particular cell line [39,59,60]. Generated cell lines can be cultivated in the laboratory for numerous passages without accumulation of chromosomal [15] or genetic changes [65], subsequently biobanked [15], and used for a variety of applications [42,66] (Figure 1). Conditional reprogramming is most commonly applied to generate human cells [39,43]; however, it has been utilized for animal (e.g., murine, canine, equine) cells as well [67,68,69].
The mechanisms of the conditional cell reprogramming are complex and involve multiple signaling pathways, such as TGF-β/SMAD, NOTCH, Rho/ROCK, and PI3K/AKT. Irradiated feeder cells and Y-27632 ROCK inhibitor stimulate cell proliferation by hTERT gene induction and increasing telomerase activity, as well as by cytoskeleton remodeling and deregulation of p16/Rb (retinoblastoma protein) pathway, respectively [38,42,45,66,70,71]. Importantly, the link between p53 pathway and hTERT activation regulates conditional cell reprogramming in epithelial cells [72]. Y-27632 inhibits apoptosis through Rho/ROCK-I/MLC pathway, immortalizes keratinocytes by cooperating with MYC [44], mitigates cell differentiation and growth arrest via Rho/ROCK and NOTCH pathways, and may prevent cell senescence by perturbing the p16/Rb-signaling pathway [38]. It is also involved in regulating cell differentiation by interference with the TGF-β/SMAD pathway [73]. Irradiated 3T3-J2 mouse fibroblasts activate EGFR, VEGFR, HGF, and HER2 receptors [74], subsequently affecting the STAT, MAPK, and PI3K/AKT signaling pathways [75]. They also stimulate the non-canonical pathway of β-catenin by increasing PP2Ac activity [52]. Moreover, irradiated feeders enable attachment of CR cells by producing extracellular matrix proteins, such as laminins, glycoproteins, and collagen [76].
The combination of both factors, Y-27632 and irradiated feeder cells, seems to be crucial for induction of proliferation and adult stem-like state of conditionally reprogrammed cells [48], as the co-culture with feeder cells is required for the cell immortalization induced by ROCK inhibitor [38,45]. In the absence of feeder cells, Y-27632 increases cell proliferation, but these cells cannot bypass senescence, so they cannot be propagated indefinitely. Feeder cell irradiation is necessary, since it stimulates apoptosis-correlated production of diffusible factors that contribute to cell immortalization [71,77]. The cell culture conditions can be modified, however. Physical contact between feeder cells and conditionally reprogrammed cells is not necessary; therefore, feeder-conditioned medium can be applied [77]. A plethora of secretory factors released by feeder cells are shown by Ligaba et al. These factors (and/or their combinations), including numerous phosphoproteins, can potentially be applied as a new generation of the CCR technique used as a preclinical disease model [71]. Moreover, Jeong and colleagues demonstrated, using three small molecules, Y-27632 (ROCK inhibitor), A83-01 (TGF-β inhibitor), and LDN193189 (BMP, bone morphogenetic protein inhibitor), enabling a long-term culture of salivary gland cells. However, their technique preferentially stimulated the growth of basal ductal progenitor cell population [78]. Crucially, the knockout of ROCK has not the same effect as using the ROCK inhibitor, Y-27632, as the conditionally reprogrammed cell culture. The knockout of a single isoform of ROCK, or even of both isoforms, ROCK1 and ROCK2, does not reprogram epithelial cells and does not promote cell culture propagation. Moreover, other known ROCK inhibitors cannot substitute for Y-27632. It is clear that Y-27632 acts beyond ROCK inhibition, as the drug affects other mechanisms and signaling pathways. Thus, the necessary conditions for conditional cell reprogramming require a collective activity of Y-27632 ROCK inhibitor and irradiated feeder cells [79,80].
Despite its strengths, such as obtaining a large number of proliferating cells within a short period of time, conditional cell reprogramming technology does not completely recapitulate the heterogeneity of a tissue or tumor (Figure 2). Often, feeder cells inhibit the growth of mesenchymal cells, therefore limiting the use of the method as a reliable model of the interactions between tumor cells and stromal cells [39]. However, especially after optimization of cell culture conditions, CCR technique can preserve heterogenous phenotype of a cancer. This phenomenon was observed in conditionally reprogrammed neuroblastoma cells containing two distinct populations, adrenergic and mesenchymal, typical for neuroblastoma tumors in vivo [59]. Moreover, numerous studies demonstrated that the CR cells of various origins preserved their behavioral and transcriptome diversity that could reflect different risk profiles for human breast cancer [61]; CR tongue squamous cell carcinoma cells resembled the morphology and histologic characteristics of the tumor of origin after inoculation into immunodeficient mice [15]; and non-small cell lung cancers cells as well as breast cancer cells generated using CCR technology faithfully maintained the molecular characteristics of original tumors [65,81]. Strengths and weaknesses of conditional cell reprogramming are summarized in Figure 2.
There are studies showing that the ROCK inhibitor, Y-27632, can be applied to the conditionally reprogrammed cell culture conditions even for generating cell lines from cancers that are dependent on ROCK signaling. For example, the Rho/ROCK axis is important for the cytoskeleton regulation and formation of neurites in neuroblastoma cells, although it should be noted that their growth was slower in the culture conditions without Y-27632 [59,82,83]. Further studies, however, are advised for applying CCR technology for the research of malignancies that are Rho/ROCK-dependent.

3. Conditional Cell Reprogramming Applications in Cancer Research

The major strengths of the conditional cell reprogramming technology are the easy handling and the ability of culturing large numbers of immortalized, genetically stable cells within a short period of time [15]. The main weakness is that the cell culture setting is two-dimensional; thus, the model does not recapitulate the complex structure of tumor or normal tissue. Importantly, however, the CCR technology can be coupled with other, more complex and precise disease models, e.g., zebrafish in vivo model [84], in vitro 3D cell cultures [82] or PDXs [62], thus still proving a valuable step towards personalized medicine.
Conditionally reprogrammed cells may serve as a source of fast-growing cells that can facilitate and accelerate research using patient derived xenografts. For example, prostate cancer CR cells, in contrast to normal prostate cells, form tumors in SCID mice, thus providing a new functional platform to study prostate cancer [38,49]. Moreover, CCR technology can be used for establishing viable cell lines from PDX tumors (generated from human bladder, lung and ovarian cancers) without negatively affecting the original tissue genetic patterns and biological properties [62,63]. Interestingly, re-implanted CR-PDX cells retain histological and drug response characteristics of the parental PDX tumor [63]. These studies show that the CCR technology can be used to establish a reliable 2D cell culture model that complements in vivo PDX model.
Recently, the usage of CCR technology in cancer research has vastly increased. CR cells have been used in research on breast cancer [61,85,86,87,88,89], prostate cancer [49,58,90,91,92,93,94,95,96,97], head, neck and salivary gland cancers [15,50,98,99], various urological cancers [62,64,100,101,102,103,104], melanoma [105], cervical cancer [106], and lung and respiratory tract cancers [81,107,108,109,110,111], although it has to be noted that the attempts of using CCR technology for lung and pharyngeal cancer samples were not always successful [56,57,112]. Conditionally reprogrammed cells have also been used in digestive system oncology [113], including gastrointestinal cancer [114], colorectal cancer [115,116,117], pancreatic carcinoma [118,119,120], hepatocellular carcinoma, and other liver diseases [121,122,123]. That work demonstrates that CR cells are utilized as models for various cancer diseases, as a platform for drug testing and screening, as well as a valuable tool to study mechanisms of tumorigenesis. Besides cancer research, CR cultures are being used in other areas, such as virology [69,124,125,126,127,128,129,130], airway disorders and functions [131,132,133,134,135,136,137,138], asthma and cystic fibrosis [139,140], reproductive tract functions and diseases [141,142,143,144], kidney injury [145], regenerative medicine [146], studies on cell proliferation [46,47,52,71,147,148], and development of new diagnostic assays and therapies [149].
Conditionally reprogrammed cell models are valuable for commonly occurring cancers. Some excellent reviews on CCR technology in general, or focusing on particular cancer types, were published recently [42,64,85,100,104,150]. The current one specifically focuses on rare cancers and the significance of conditional reprogramming for this group of malignancies. As in vitro models are scarce and clinical samples are difficult to obtain in rare cancer research, new preclinical models are extremely important. Thus, the aim of this review is to present the conditional reprogramming technology in rare cancer research. Rare cancers presented in this review have different origins, develop in different organs, and have different genetic and phenotypic characteristics. Importantly, most of them are of non-epithelial origin, thus showing a new research area in which CCR technology, initially applied mostly to epithelial cells, can be utilized.

4. Conditionally Reprogrammed Cells as Preclinical Model for Rare Cancers

4.1. Neuroblastoma

Neuroblastoma is a rare cancer of autonomic nervous system that occurs mostly in children younger than 5 years. It is an extremely complex malignancy with numerous genetic and biological variations, various signaling pathways regulating pathogenesis, as well as clinical heterogeneity related to the severity of the disease and patterns of drug resistance, and poor survival prognosis. Due to the rarity and the complex nature of the malignancy, therapeutic options are still insufficient for patients’ long-term survival. Currently, chemotherapy, immunotherapy, radiotherapy, surgery, stem cell transplantations and combinational therapies are utilized. Moreover, advanced methods such as targeting exosome signaling via non-coding RNA, targeting cancer stem cells and epithelial-to-mesenchymal transition (EMT), various monoclonal antibodies, a combination of chemotherapeutic agents and developmental retinoids, as well as numerous types of drug delivery strategies constitute new promising therapeutic options [151]. Hence, there is an urgent need for the development of preclinical neuroblastoma models facilitating preclinical evaluations of potential therapies, especially for therapies effective against disease initiation and metastasis [152,153,154].
Murine neuroblastoma cell lines that were generated using CCR technology were described in 2020 for the first time ([59], Figure 3A). Cell culture settings were an optimized conditional reprogramming method: cells were grown in the CR medium supplemented with Y-27632, without feeder cells, at 2% O2 (Table 2). Twenty-one cell lines were obtained from tumors growing in a commonly utilized model of human neuroblastoma, TH-MYCN transgenic mice. All of the cell lines retained typical heterogenous phenotype with two distinctive cell populations: mesenchymal and adrenergic, and they were positive for specific biomarkers of neuroblastoma lineages’, as well as for neuronal markers. Their tumorigenic phenotype was confirmed using migration, invasion, and anchorage-independent growth assays in vitro. Passaged for numerous passages and biobanked, neuroblastoma CR cells were subsequently utilized to discover the role of neuropeptide Y receptor in neuroblastoma cell motility [83], as well as tested for their ability to grow in 3D cell culture settings [82]. The main disadvantage of this neuroblastoma in vitro model is that these cells are not human. However, the plans to obtain and culture neuroblastoma cells collected from patients have been made.
Neuroblastoma is an extremely complex malignancy; therefore, its therapy must be carefully designed and personalized, depending on the disease severity and stage. CCR technology, as a personalized preclinical model, may be useful for screening potential neuroblastoma treatments. It may be particularly successful in testing the therapies that affect EMT, as the CCR technology preserves the heterogenous phenotype of the disease (Figure 3A). Other current approaches in applying preclinical neuroblastoma models for the development of new therapies include identification of residual malignant persister cells in tumor samples using single-nucleus RNA sequencing and bulk whole-genome sequencing [162,163], multiomic detection of cellular and molecular interactions of cells within the neuroblastoma tumor for potential use of immunotherapies [164,165], as well as 3D in vitro models for neuroblastoma microenvironment studies [166].

4.2. Neuroendocrine Cervical Carcinoma

Neuroendocrine cervical cancer is a highly aggressive malignancy. Because of its rare occurrence there are no relevant preclinical models of this disease. Using CCR technology, one unique cell line was generated from aggressive large cell neuroendocrine cervical carcinoma metastatic to liver [60]. The cancer tissue was collected from a 27-year-old patient who passed away 3 months later. The cells grew in 3D spheres initially, then formed a rapidly proliferating monolayer (Figure 3B). They required a modified CR cell culture condition: without feeders but collagen-coated cell culture vessel for their growth (Table 2). Genome of human papillomavirus type 16 was found to be integrated into the cellular genome, adjacent to the Myc gene. However, a 40-fold amplification and overexpression of Myc was the driver of transformation of these cells, rather than the HPV-16 oncogene expression. Interestingly, the generated cell line harbored a p53 mutation, which is uncommon for most cervical cancers. Its transformed phenotype was shown in vitro (invasion and migration assays, anchorage-independent growth in soft agar) and in vivo by tumor formation in immunodeficient mice. One possible explanation is that p53 may have different activities in cervical neuroendocrine cells and in cervical squamous cells. However, the establishment of a reliable cancer model has not been fully achieved, since the paper refers to one study and a single, very unique, cell line only.

4.3. Neuroendocrine Prostate Cancer

In contrast to prostate cancer in general, neuroendocrine prostate cancer is very rare. It is an extremely aggressive disease, with its mechanisms not very well known because of lack of adequate models in vitro [167]. Ci et al. [160] described a series of experiments combining xenografts and CCR technology. Tumor specimens were collected from prostate cancer patients and transplanted into immunodeficient mice. After numerous in vivo passages, prostate adenocarcinoma PDX tumors were harvested and grown using standard CR conditions (Table 2). Notably, it was observed that CR conditions partially mimicked castration in vivo: prostate adenocarcinoma PDX transdifferentiated to prostate neuroendocrine cancer after castration of a mouse host and subsequent tumor regression. When CR-PDX cells were re-transplanted to mice, the resultant tumors appear to be neuroendocrine prostate cancers, different from parental adenocarcinoma tumors. Histological and transcriptomic analyses demonstrated that the cells lost their adenocarcinoma markers, and expressed neuroendocrine ones. Also, neuroendocrine genes were enriched, in contrast to androgen receptor signaling genes. Cell culture conditions used in this study were a combination of CR conditions and PDX samples and, interestingly, a transdifferentiation process occurred in the course of the study. Therefore, more studies aiming at the generating and characterizations of this type of cancer are necessary to claim an establishment of a new fully reliable preclinical cancer model.

4.4. GIST

Gastrointestinal stromal tumors (GIST) are rare abdominal tumors. Histologically, most of them consist of spindle-shaped, mesenchymal cells [168]. Clinical specimens of the GIST were collected from a patient at the Georgetown University hospital. The tumors were processed and cultured using conditional reprogramming technology (Figure 3C). Cell cultures confirmed that the proliferation and growth of fibroblast/stromal cells is inhibited by J2 feeder cells, as observed before [47,169]. Thus, the cell culture method was optimized for GIST cells [39] (Table 2). One conditionally reprogrammed cell line was generated and biobanked. A long-term growth of the cell line and reproducibility was not assessed; moreover, the single cell line generated was not characterized. The data are promising, but more are necessary for the establishment of the CCR technology-based in vitro model for GIST.

4.5. Gliomas and Other Glioneural Tumors

4.5.1. Ependymoma

Pediatric spinal ependymomas are uncommon cancers of the central nervous system. Because of their rarity, there are no sufficient preclinical models available [170]. A novel preclinical ependymoma model was described in 2017 [155]. The tumor sample was collected from a 12-year-old patient with spinal myxopapillary ependymoma. The cells were grown in optimized conditional reprogramming cell culture (Table 2). Importantly, in comparison to their controls, CR ependymoma cells demonstrated elevated expression of genes encoding High Mobility Group Protein AT-hook 1 (HMGA1), High Mobility Group Protein AT-hook 2 (HMGA2), cMYC, HOXB13, and HOXA10 proteins.
In the second study, two other myxopapillary ependymomas collected from patients above 40 years old were cultured using CCR technology [156]. They were grown in modified CR conditions: CR medium mixed with conditioned medium (CM; CR medium conditioned on irradiated J2 feeder cells [39]) (Table 2). The cell culture method was slightly modified when compared to the one used by the same team before; however, it still did not fully support the growth of CR ependymoma cells. Further optimization of the CCR technology for the establishment of ependymoma in vitro models is necessary.

4.5.2. Pilocytic Astrocytoma

Pilocytic astrocytoma cell line was generated using optimized CCR technology (Table 2) [156]. The tumor was collected from a 14-year-old patient with neurofibromatosis type 1. Conditionally reprogrammed cells were growing rapidly, were genetically stable for numerous passages, and positive for vimentin and neural progenitor markers, nestin, and NG2. These cultured cells were used for drug testing in vitro, as well as characterized in various biological assays. Reduced NF1 expression was confirmed on the mRNA level. BRAF p.V600E mutation was detected by pyrosequencing and PCR analysis. The cells formed tumors in immunodeficient mice, and the patient’s glial cells were observed in the brain and leptomeninges of these mice. In zebrafish xenografts, the cells were migrating along developing zebrafish spinal cord. Senescence induction was evaluated using β-galactosidase staining, and cell cycle proteins (p21, p27) were detected by Western blot analysis. Additionally, two other pilocytic astrocytoma CR cell lines were grown; however, the growth was not as abundant. The results suggest that the studies on the application of conditional reprogramming for viable, fast-growing, and reliable astrocytoma cell lines are needed.

4.5.3. Other Gliomas

The same team was able to grow other gliomas and glioneural tumors using optimized conditional cell reprogramming technology (Table 2). Among them were anaplastic pleomorphic xanthoastrocytoma (this CR cell line forms orthotopic tumors in nude mice); anaplastic gliomas grade III and III/IV; gangliogliomas grade I and III; low grade neuroepithelial tumors; and low-grade gliomas with pilomyxoid and ependymal features [156]. That extensive study confirms that CR technology seems to be a promising method to be used as a preclinical model for drug-screening and mechanistic assays, especially in cases of rare tumors that are difficult to propagate in standard media.

4.6. Ameloblastoma

Six conditionally reprogrammed cells lines from excised ameloblastomas (odontogenic tumors) were generated [145]. They were grown in modified CR cell culture conditions (Table 2) for six to eight passages only. Afterwards, to avoid cellular senescence, cell lines were immortalized with hTERT transduction at early passage. The cell lines expressed amelotin, ameloblast-associated gene, and harbored various ameloblastoma driver mutations in MAPK (mitogen-activated protein kinase) pathway, e.g., KRAS, NRAS, BRAF, FGFR2), and Hedgehog pathway (SMO). Two of them were the first tumor cell lines established that carried SMO mutations. Generated cells were used in drug sensitivity assays and oncogene dependency assays. However, because human ameloblastoma cell lines grew in CR conditions only for a limited number of passages, it has to be emphasized that in this case, a reliable disease model was not established.
Before human ameloblastoma cell lines, the same team successfully generated cells from an analog of human ameloblastoma, namely canine acanthomatous ameloblastoma [158]. Canine ameloblastoma CR cell lines were immortalized in modified CR cell culture conditions (Table 2) and were tested for their sensitivity to drugs. This study shows the potential of establishing CCR technology-dependent in vitro models that can be applicable in veterinary medicine.

4.7. Laryngeal and Hypopharyngeal Carcinoma

Laryngeal and hypopharyngeal carcinoma is a rare type of head-and-neck cancer. Its prognosis is poor due to inefficient treatment; therefore, the development of new potential therapies, including chemotherapies, is of utmost importance [171]. Dong et al. [161] describe establishment of cell lines from patients with a rare type of namely laryngeal and hypopharyngeal squamous cell carcinomas (LHSCC). They generated 28 cell lines (both tumor and corresponding normal control) from 50 clinical specimens, using standard CCR technology (Table 2). The cells were genetically stable, recapitulated genetic changes typical for LHSCCs, and expressed an epithelial cell marker (pan-keratin), as well as a head-and-neck cancer biomarker, CD44 (CD44 expression levels were higher in tumor cell lines, in comparison to normal cells). Generated CR cell lines’ tumorigenicity was evaluated by their potential to form tumors in nude mice. Tumor cells injection resulted in formation of tumors, while normal CR cells did not show that effect. CR LHSCC cells, growing in 2D and 3D settings, as well as xenografts, were used for various drug and radiation sensitivity testing. The authors of the study claim that even though the successful growth rate of the CR cell lines was not the highest, it was still superior to xenograft and organoid 3D growth. Moreover, conditional reprogramming alone and in combination with other preclinical models may be useful for identification of new potential drug targets, as well as for discovery of new therapeutic agents for the laryngeal and hypopharyngeal carcinoma.

4.8. Adenoid Cystic Carcinoma

Adenoid cystic carcinomas are slow-growing but highly lethal tumors, neuroinvasive, recurrent, and often metastatic. The treatment is limited due to the elusive molecular nature of the tumor, as well as the lack of adequate in vitro screening models. Establishment of six ACC conditionally reprogrammed cell lines (1 from primary tumor and 5 from xenografts) has been described [159]. The cells were grown in optimized CR cell culture conditions (Table 2). In contrast to normal salivary gland cells, they expressed ACC markers previously introduced to validate stem cell identity of cultured cells (SOX10, NOTCH1, FABP7, NTRK3/TrkC and PROM1/CD133), and formed spheroids in 3D cultures and tumors in immunodeficient mice, proving to be a useful source for adenoid cystic carcinoma samples for personalized oncology.
Additionally, CR adenoid cystic carcinoma cells collected from xenografts were injected into the zebrafish model, thus establishing a new approach for the preclinical modeling of this malignancy [84]. Two conditionally reprogrammed ACC xenograft cell lines were established, using optimized CCR technology (Table 2). The cells maintained their transformed potential, as shown in in vitro soft agar and invasion assays. They were grown for a limited number of passages and subsequently injected into zebrafish embryos. Conditionally reprogrammed cells, PDXs, and zebrafish models were used for drug sensitivity testing, and the results were similar. The authors concluded that these cultures can be useful as models for basic and translational studies.

5. Conclusions

Preclinical in vitro disease models are indispensable in every area of cancer research. Conditional cell reprogramming is a novel technology that can be used as a 2D in vitro model for cancer and other diseases. Obtaining fast-growing non-differentiated cells that can be reversibly immortalized with cell culture conditions only without any genetic modifications is the strength of this technology. Moreover, both normal and cancer cells collected from the same patients can be grown alongside each other, even in the case of rare cancers. Conditionally reprogrammed cells can also be generated from different stages of tumors. Furthermore, CR cultures preserve tissue heterogeneity to some extent; therefore, they may be applied to studies of cellular interactions in various tumors. However, it needs to be emphasized that CCR technology is still a two-dimensional cell culture system and suffers from the major weaknesses of that kind of setting, including poor representation of tumor/tissue complexity and the lack of adequate representation of the three-dimensional tissue structures (Figure 2). Additionally, attempts to establish viable cell lines without the optimization of the cell culture conditions are not always successful. Notably, in many cases of rare cancers, especially of non-epithelial origin (gliomas, neuroblastoma, neuroendocrine cervical cancer, ameloblastoma) the CCR technology needs to be modified and optimized (Table 2). Consequently, these studies confirm the decades-old discovery that irradiated 3T3-J2 cells inhibit the growth of tissue stromal cells. The necessary modification in most cases was the removal of the feeders from the cell co-culture.
Importantly, conditional cell reprogramming technique cultures can be combined with other, low-throughput, but more complex and precise platforms such as patient-derived xenografts and/or 3D systems (as used for culturing astrocytoma, adenoid cystic carcinoma, laryngeal and hypopharyngeal carcinoma). It suggests that these different types of preclinical models can work in synergy to advance cancer research. They can be utilized in numerous research areas, from evaluation of the malignancy mechanisms and identification of potential therapeutic targets, to high-throughput screening of potential anticancer drugs and the determination of mechanisms of cellular susceptibility to these agents.
The CCR technology (and its combinations with other methods) may be even more important in often neglected rare cancer research area, due to their elusiveness, unique tumorigenicity mechanisms, and infrequent occurrence. The main challenges of the burden of rare cancers are insufficient patient numbers and therefore difficulty in establishment of clinical trials for potential drugs, and, consequently, inadequate numbers of effective therapies and poor disease prognosis for patients [33,36]. There is a notable lack of relevant and reliable models to study these malignancies. Thus, the development of new preclinical models is crucial. This article reviews the conditional cell reprogramming technology as a novel and useful model, demonstrating its strengths and limitations, as well as applications for various rare cancers studies. Alone and in combination with other technologies, it can be used in various aspects of basic and translational cancer research related to rare diseases.

Funding

This research received no external funding. To support the work, internal funds from the Center for Cell Reprogramming at Georgetown University Medical Center were used.

Acknowledgments

All authors have read and agreed to the published version of the manuscript.

Conflicts of Interest

The author declares no conflicts of interest.

References

  1. Krattiger, L.A.; Guex, A.G. Complex in Vitro Model Systems to Understand the Biointerfaces of Dental Implants. Dent. Mater. 2025, 41, 810–826. [Google Scholar] [CrossRef] [PubMed]
  2. Abbot, A. Cell Culture: Biology’s New Dimension. Nature 2003, 424, 870–872. [Google Scholar] [CrossRef] [PubMed]
  3. Aljitawi, O.S.; Li, D.; Xiao, Y.; Zhang, D.; Ramachandran, K.; Stehno-Bittel, L.; Van Veldhuizen, P.; Lin, T.L.; Kambhampati, S.; Garimella, R. A Novel Three-Dimensional Stromal-Based Model for in Vitro Chemotherapy Sensitivity Testing of Leukemia Cells. Leuk. Lymphoma 2014, 55, 378–391. [Google Scholar] [CrossRef]
  4. Senft, D.; Leiserson, M.D.M.; Ruppin, E.; Ronai, Z.A. Precision Oncology: The Road Ahead. Trends Mol. Med. 2017, 23, 874–898. [Google Scholar] [CrossRef]
  5. Novelli, G.; Spitalieri, P.; Murdocca, M.; Centanini, E.; Sangiuolo, F. Organoid Factory: The Recent Role of the Human Induced Pluripotent Stem Cells (HiPSCs) in Precision Medicine. Front. Cell Dev. Biol. 2023, 10, 1059579. [Google Scholar] [CrossRef]
  6. He, Z.; Wilson, A.; Rich, F.; Kenwright, D.; Stevens, A.; Low, Y.S.; Thunders, M. Chromosomal Instability and Its Effect on Cell Lines. Cancer Rep. 2023, 6, e1822. [Google Scholar] [CrossRef]
  7. Krüger, M.; Kopp, S. Tumor Models and Drug Targeting In Vitro—Where Are We Today? Where Do We Go from Here? Cancers 2023, 15, 1768. [Google Scholar] [CrossRef]
  8. Krendl, F.J.; Primavesi, F.; Oberhuber, R.; Neureiter, D.; Ocker, M.; Bekric, D.; Kiesslich, T.; Mayr, C. The Importance of Preclinical Models for Cholangiocarcinoma Drug Discovery. Expert. Opin. Drug Discov. 2025, 20, 205–216. [Google Scholar] [CrossRef]
  9. Movia, D.; Prina-Mello, A. (Eds.) Cancer Cell Culture Methods and Protocols Methods in Molecular Biology; Humana Press: Totowa, NJ, USA, 2023. [Google Scholar]
  10. Festing, S.; Wilkinson, R. The Ethics of Animal Research: Talking Point on the Use of Animals in Scientific Research. EMBO Rep. 2007, 8, 526–530. [Google Scholar] [CrossRef]
  11. Charitos, I.A.; Ballini, A.; Cantore, S.; Boccellino, M.; Di Domenico, M.; Borsani, E.; Nocini, R.; Di Cosola, M.; Santacroce, L.; Bottalico, L. Stem Cells: A Historical Review about Biological, Religious, and Ethical Issues. Stem Cells Int. 2021, 2021, 9978837. [Google Scholar] [CrossRef] [PubMed]
  12. Boehm, J.S.; Golub, T.R. An Ecosystem of Cancer Cell Line Factories to Support a Cancer Dependency Map. Nat. Rev. Genet. 2015, 16, 373–374. [Google Scholar] [CrossRef]
  13. Barretina, J.; Caponigro, G.; Stransky, N.; Venkatesan, K.; Margolin, A.A.; Kim, S.; Wilson, C.J.; Lehár, J.; Kryukov, G.V.; Sonkin, D.; et al. The Cancer Cell Line Encyclopedia Enables Predictive Modelling of Anticancer Drug Sensitivity. Nature 2012, 483, 603–607. [Google Scholar] [CrossRef]
  14. Voskoglou-Nomikos, T.; Pater, J.L.; Seymour, L. Clinical Predictive Value of the in Vitro Cell Line, Human Xenograft, and Mouse Allograft Preclinical Cancer Models. Clin. Cancer Res. 2003, 9, 4227–4239. [Google Scholar] [PubMed]
  15. Palechor-Ceron, N.; Krawczyk, E.; Dakic, A.; Simic, V.; Yuan, H.; Blancato, J.; Wang, W.; Hubbard, F.; Zheng, Y.L.; Dan, H.; et al. Conditional Reprogramming for Patient-Derived Cancer Models and next-Generation Living Biobanks. Cells 2019, 8, 1327. [Google Scholar] [CrossRef] [PubMed]
  16. Coppola, L.; Cianflone, A.; Grimaldi, A.M.; Incoronato, M.; Bevilacqua, P.; Messina, F.; Baselice, S.; Soricelli, A.; Mirabelli, P.; Salvatore, M. Biobanking in Health Care: Evolution and Future Directions. J. Transl. Med. 2019, 17, 172. [Google Scholar] [CrossRef]
  17. Augustine, R.; Kalva, S.N.; Ahmad, R.; Zahid, A.A.; Hasan, S.; Nayeem, A.; McClements, L.; Hasan, A. 3D Bioprinted Cancer Models: Revolutionizing Personalized Cancer Therapy. Transl. Oncol. 2021, 14, 101015. [Google Scholar] [CrossRef] [PubMed]
  18. Grainger, D.W. Cell-Based Drug Testing; This World is Not Flat. Adv. Drug Deliv. Rev. 2014, 69–70, vii–xi. [Google Scholar] [CrossRef]
  19. Bhuker, S.; Sinha, A.K.; Arora, A.; Tuli, H.S.; Datta, S.; Saini, A.K.; Saini, R.V.; Ramniwas, S. Genes and Proteins Expression Profile of 2D vs 3D Cancer Models: A Comparative Analysis for Better Tumor Insights. Cytotechnology 2025, 77, 51. [Google Scholar] [CrossRef]
  20. Bittman-Soto, X.S.; Thomas, E.S.; Ganshert, M.E.; Mendez-Santacruz, L.L.; Harrell, J.C. The Transformative Role of 3D Culture Models in Triple-Negative Breast Cancer Research. Cancers 2024, 16, 1859. [Google Scholar] [CrossRef]
  21. Hickman, J.A.; Graeser, R.; de Hoogt, R.; Vidic, S.; Brito, C.; Gutekunst, M.; van der Kuip, H.; Imi Predect consortium. Three-Dimensional Models of Cancer for Pharmacology and Cancer Cell Biology: Capturing Tumor Complexity in Vitro/Ex Vivo. Biotechnol. J. 2014, 9, 1115–1128. [Google Scholar] [CrossRef]
  22. Kamb, A. What’s Wrong with Our Cancer Models? Nat. Rev. Drug Discov. 2005, 4, 161–165. [Google Scholar] [CrossRef]
  23. Ben-David, U.; Siranosian, B.; Ha, G.; Tang, H.; Oren, Y.; Hinohara, K.; Strathdee, C.A.; Dempster, J.; Lyons, N.J.; Burns, R.; et al. Genetic and Transcriptional Evolution Alters Cancer Cell Line Drug Response. Nature 2018, 560, 325–330. [Google Scholar] [CrossRef] [PubMed]
  24. Santillo, S. Changes in Biophysical Properties of Undifferentiated SH-SY5Y Cells During Long-Term Cultures. Neuroscience 2022, 482, 143–158. [Google Scholar] [CrossRef] [PubMed]
  25. Nestor, C.E.; Ottaviano, R.; Reinhardt, D.; Cruickshanks, H.A.; Mjoseng, H.K.; McPherson, R.C.; Lentini, A.; Thomson, J.P.; Dunican, D.S.; Pennings, S.; et al. Rapid Reprogramming of Epigenetic and Transcriptional Profiles in Mammalian Culture Systems. Genome Biol. 2015, 16, 11. [Google Scholar] [CrossRef] [PubMed]
  26. Shay, J.; Wright, W. Hayflick, His Limit, and Cellular Ageing. Nat. Rev. Mol. Cell Biol. 2000, 1, 72–76. [Google Scholar] [CrossRef]
  27. Drexler, H.G.; Dirks, W.G.; Matsuo, Y.; MacLeod, R.A.F. False Leukemia-Lymphoma Cell Lines: An Update on over 500 Cell Lines. Leukemia 2003, 17, 416–426. [Google Scholar] [CrossRef]
  28. Lacroix, M. Persistent Use of “False” Cell Lines. Int. J. Cancer 2008, 122, 1–4. [Google Scholar] [CrossRef]
  29. Ye, F.; Chen, C.; Qin, J.; Liu, J.; Zheng, A.C. Genetic Profiling Reveals an Alarming Rate of Cross-Contamination among Human Cell Lines Used in China. FASEB J. 2015, 29, 4268–4272. [Google Scholar] [CrossRef]
  30. Weiskirchen, S.; Schröder, S.K.; Buhl, E.M.; Weiskirchen, R. A Beginner’s Guide to Cell Culture: Practical Advice for Preventing Needless Problems. Cells 2023, 12, 682. [Google Scholar] [CrossRef]
  31. Hughes, P.; Marshall, D.; Reid, Y.; Parkes, H.; Gelber, C. The Costs of Using Unauthenticated, over-Passaged Cell Lines: How Much More Data Do We Need? Biotechniques 2007, 43, 575–586. [Google Scholar] [CrossRef]
  32. Alston-Roberts, C.; Barallon, R.; Bauer, S.R.; Butler, J.; Capes-Davis, A.; Dirks, W.G.; Elmore, E.; Furtado, M.; Kerrigan, L.; Kline, M.C.; et al. Cell Line Misidentification: The Beginning of the End. Nat. Rev. Cancer 2010, 10, 441–448. [Google Scholar] [CrossRef]
  33. Boyd, N.; Dancey, J.E.; Gilks, B.; Huntsman, D.G. Rare Cancers: A Sea of Opportunity. Lancet Oncol. 2016, 17, e52–e61. [Google Scholar] [CrossRef]
  34. Beltinger, C.; Debatin, K.M. Murine Models for Experimental Therapy of Pediatric Solid Tumors with Poor Prognosis. Int. J. Cancer 2001, 92, 313–318. [Google Scholar] [CrossRef]
  35. Kawai, A.; Higashi, T.; Shibata, T.; Yoshida, A.; Katoh, Y.; Fujiwara, Y.; Nishida, T. Rare Cancers in Japan: Definition, Clinical Features and Future Perspectives. Jpn. J. Clin. Oncol. 2020, 50, 970–975. [Google Scholar] [CrossRef] [PubMed]
  36. Kondo, T. Current Status and Future Outlook for Patient-Derived Cancer Models from a Rare Cancer Research Perspective. Cancer Sci. 2021, 112, 953–961. [Google Scholar] [CrossRef] [PubMed]
  37. Sharifnia, T.; Hong, A.L.; Painter, C.A.; Boehm, J.S. Emerging Opportunities for Target Discovery in Rare Cancers. Cell Chem. Biol. 2017, 24, 1075–1091. [Google Scholar] [CrossRef]
  38. Liu, X.; Ory, V.; Chapman, S.; Yuan, H.; Albanese, C.; Kallakury, B.; Timofeeva, O.A.; Nealon, C.; Dakic, A.; Simic, V.; et al. ROCK Inhibitor and Feeder Cells Induce the Conditional Reprogramming of Epithelial Cells. Am. J. Pathol. 2012, 180, 599–607. [Google Scholar] [CrossRef]
  39. Liu, X.; Krawczyk, E.; Suprynowicz, F.A.; Palechor-Ceron, N.; Yuan, H.; Dakic, A.; Simic, V.; Zheng, Y.L.; Sripadhan, P.; Chen, C.; et al. Conditional Reprogramming and Long-Term Expansion of Normal and Tumor Cells from Human Biospecimens. Nat. Protoc. 2017, 12, 439–451. [Google Scholar] [CrossRef]
  40. Friedman, A.A.; Letai, A.; Fisher, D.E.; Flaherty, K.T. Precision Medicine for Cancer with Next-Generation Functional Diagnostics. Nat. Rev. Cancer 2015, 15, 747–756. [Google Scholar] [CrossRef]
  41. Lisanti, M.P.; Tanowitz, H.B. Translational Discoveries, Personalized Medicine, and Living Biobanks of the Future. Am. J. Pathol. 2012, 180, 1334–1336. [Google Scholar] [CrossRef] [PubMed]
  42. Wu, X.; Wang, S.; Li, M.; Li, J.; Shen, J.; Zhao, Y.; Pang, J.; Wen, Q.; Chen, M.; Wei, B.; et al. Conditional Reprogramming: Next Generation Cell Culture. Acta Pharm. Sin. B 2020, 10, 1360–1381. [Google Scholar] [CrossRef]
  43. Yuan, H.; Myers, S.; Wang, J.; Zhou, D.; Woo, J.A.; Kallakury, B.; Ju, A.; Bazylewicz, M.; Carter, Y.M.; Albanese, C.; et al. Use of Reprogrammed Cells to Identify Therapy for Respiratory Papillomatosis. N. Engl. J. Med. 2012, 367, 1220–1227. [Google Scholar] [CrossRef]
  44. Dakic, A.; Divito, K.; Fang, S.; Suprynowicz, F.; Gaur, A.; Li, X.; Palechor-Ceron, N.; Simic, V.; Choudhury, S.; Yu, S.; et al. ROCK Inhibitor Reduces Myc-Induced Apoptosis and Mediates Immortalization of Human Keratinocytes. Oncotarget 2016, 7, 66740–66753. [Google Scholar] [CrossRef]
  45. Chapman, S.; Liu, X.; Meyers, C.; Schlegel, R.; McBride, A.A. Human Keratinocytes Are Efficiently Immortalized by a Rho Kinase Inhibitor. J. Clin. Investig. 2010, 120, 2619–2626. [Google Scholar] [CrossRef] [PubMed]
  46. Piltti, J.; Varjosalo, M.; Qu, C.; Häyrinen, J.; Lammi, M.J. Rho-Kinase Inhibitor Y-27632 Increases Cellular Proliferation and Migration in Human Foreskin Fibroblast Cells. Proteomics 2015, 15, 2953–2965. [Google Scholar] [CrossRef]
  47. Rheinwald, J.G.; Green, H. Serial Cultivation of Strains of Human Epidermal Keratinocytes: The Formation of Keratinizing Colonies from Single Cells. Cell 1975, 6, 331–343. [Google Scholar] [CrossRef] [PubMed]
  48. Suprynowicz, F.A.; Upadhyay, G.; Krawczyk, E.; Kramer, S.C.; Hebert, J.D.; Liu, X.; Yuan, H.; Cheluvaraju, C.; Clapp, P.W.; Boucher, R.C.; et al. Conditionally Reprogrammed Cells Represent a Stem-like State of Adult Epithelial Cells. Proc. Natl. Acad. Sci. USA 2012, 109, 20035–20040. [Google Scholar] [CrossRef] [PubMed]
  49. Timofeeva, O.A.; Palechor-Ceron, N.; Li, G.; Yuan, H.; Krawczyk, E.; Zhong, X.; Liu, G.; Upadhyay, G.; Dakic, A.; Yu, S.; et al. Conditionally Reprogrammed Normal and Primary Tumor Prostate Epithelial Cells: A Novel Patient-Derived Cell Model for Studies of Human Prostate Cancer. Oncotarget 2017, 8, 22741–22758. [Google Scholar] [CrossRef]
  50. Alamri, A.M.; Liu, X.; Blancato, J.K.; Haddad, B.R.; Wang, W.; Zhong, X.; Choudhary, S.; Krawczyk, E.; Kallakury, B.V.; Davidson, B.J.; et al. Expanding Primary Cells from Mucoepidermoid and Other Salivary Gland Neoplasms for Genetic and Chemosensitivity Testing. DMM Dis. Models Mech. 2018, 11, dmm031716. [Google Scholar] [CrossRef]
  51. Saenz, F.R.; Ory, V.; AlOtaiby, M.; Rosenfield, S.; Furlong, M.; Cavalli, L.R.; Johnson, M.D.; Liu, X.; Schlegel, R.; Wellstein, A.; et al. Conditionally Reprogrammed Normal and Transformed Mouse Mammary Epithelial Cells Display a Progenitor-Cell-like Phenotype. PLoS ONE 2014, 9, e97666. [Google Scholar] [CrossRef]
  52. Suprynowicz, F.A.; Kamonjoh, C.M.; Krawczyk, E.; Agarwal, S.; Wellstein, A.; Agboke, F.A.; Choudhury, S.; Liu, X.; Schlegel, R. Conditional Cell Reprogramming Involves Noncanonical β-Catenin Activation and MTOR-Mediated Inactivation of Akt. PLoS ONE 2017, 12, e0180897. [Google Scholar] [CrossRef]
  53. Chalak, M.; Hesaraki, M.; Mirbahari, S.N.; Yeganeh, M.; Abdi, S.; Rajabi, S.; Hemmatzadeh, F. Cell Immortality: In Vitro Effective Techniques to Achieve and Investigate Its Applications and Challenges. Life 2024, 14, 417. [Google Scholar] [CrossRef] [PubMed]
  54. Cerneckis, J.; Cai, H.; Shi, Y. Induced Pluripotent Stem Cells (IPSCs): Molecular Mechanisms of Induction and Applications. Signal Transduct. Target Ther. 2024, 9, 112. [Google Scholar] [CrossRef]
  55. He, Z.; Cole, K.D.; He, H.J. A Novel Immortalization Method for Immortalizing Human Primary CD8+ T Cells by Inserting a Single Copy of Human Telomerase Reverse Transcriptase via CRISPR/Cas9. Tissue Cell 2025, 95, 102908. [Google Scholar] [CrossRef] [PubMed]
  56. Gao, B.; Huang, C.; Kernstine, K.; Pelekanou, V.; Kluger, Y.; Jiang, T.; Peters-Hall, J.R.; Coquelin, M.; Girard, L.; Zhang, W.; et al. Non-Malignant Respiratory Epithelial Cells Preferentially Proliferate from Resected Non-Small Cell Lung Cancer Specimens Cultured under Conditionally Reprogrammed Conditions. Oncotarget 2017, 8, 1114. [Google Scholar] [CrossRef]
  57. Yu, F.; Lu, Y.; Tao, L.; Jiang, Y.Y.; Lin, D.C.; Wang, L.; Petersson, F.; Yoshiyama, H.; Koeffler, P.H.; Goh, B.C.; et al. Non-Malignant Epithelial Cells Preferentially Proliferate from Nasopharyngeal Carcinoma Biopsy Cultured under Conditionally Reprogrammed Conditions. Sci. Rep. 2017, 7, 17359. [Google Scholar] [CrossRef]
  58. Tricoli, L.; Naeem, A.; Parasido, E.; Mikhaiel, J.P.; Choudhry, M.U.; Berry, D.L.; Abdelgawad, I.A.; Lee, R.J.; Feldman, A.S.; Ihemelandu, C.; et al. Characterization of the Effects of Defined, Multidimensional Culture Conditions on Conditionally Reprogrammed Primary Human Prostate Cells. Oncotarget 2018, 9, 2193. [Google Scholar] [CrossRef]
  59. Krawczyk, E.; Hong, S.H.; Galli, S.; Trinh, E.; Wietlisbach, L.; Misiukiewicz, S.F.; Tilan, J.U.; Chen, Y.S.; Schlegel, R.; Kitlinska, J. Murine Neuroblastoma Cell Lines Developed by Conditional Reprogramming Preserve Heterogeneous Phenotypes Observed in Vivo. Lab. Investig. 2020, 100, 38–51. [Google Scholar] [CrossRef]
  60. Yuan, H.; Krawczyk, E.; Blancato, J.; Albanese, C.; Zhou, D.; Wang, N.; Paul, S.; Alkhilaiwi, F.; Palechor-Ceron, N.; Dakic, A.; et al. HPV Positive Neuroendocrine Cervical Cancer Cells Are Dependent on Myc but Not E6/E7 Viral Oncogenes. Sci. Rep. 2017, 7, 45617. [Google Scholar] [CrossRef]
  61. Alothman, S.J.; Kang, K.; Liu, X.; Krawczyk, E.; Azhar, R.I.; Hu, R.; Goerlitz, D.; Kallakury, B.V.; Furth, P.A. Characterization of Transcriptome Diversity and in Vitro Behavior of Primary Human High-Risk Breast Cells. Sci. Rep. 2022, 12, 6159. [Google Scholar] [CrossRef] [PubMed]
  62. Mondal, A.M.; Ma, A.H.; Li, G.; Krawczyk, E.; Yuan, R.; Lu, J.; Schlegel, R.; Stamatakis, L.; Kowalczyk, K.J.; Philips, G.K.; et al. Fidelity of a PDX-CR Model for Bladder Cancer. Biochem. Biophys. Res. Commun. 2019, 517, 49–56. [Google Scholar] [CrossRef]
  63. Borodovsky, A.; McQuiston, T.J.; Stetson, D.; Ahmed, A.; Whitston, D.; Zhang, J.; Grondine, M.; Lawson, D.; Challberg, S.S.; Zinda, M.; et al. Generation of Stable PDX Derived Cell Lines Using Conditional Reprogramming. Mol. Cancer 2017, 16, 177. [Google Scholar] [CrossRef]
  64. Daneshdoust, D.; Yin, M.; Luo, M.; Sundi, D.; Dang, Y.; Lee, C.; Li, J.; Liu, X. Conditional Reprogramming Modeling of Bladder Cancer for Clinical Translation. Cells 2023, 12, 1714. [Google Scholar] [CrossRef]
  65. Mahajan, A.S.; Sugita, B.M.; Duttargi, A.N.; Saenz, F.; Krawczyk, E.; McCutcheon, J.N.; Fonseca, A.S.; Kallakury, B.; Pohlmann, P.; Gusev, Y.; et al. Genomic Comparison of Early-Passage Conditionally Reprogrammed Breast Cancer Cells to Their Corresponding Primary Tumors. PLoS ONE 2017, 12, e0186190. [Google Scholar] [CrossRef] [PubMed]
  66. Zhong, M.; Fu, L. Culture and Application of Conditionally Reprogrammed Primary Tumor Cells. Gastroenterol. Rep. (Oxf.) 2020, 8, 224–233. [Google Scholar] [CrossRef]
  67. Zhou, X.; Kang, Y.; Chang, Y.; Xia, S.; Wu, M.; Liu, J.; Dong, D.; Zhang, W.; Chen, H.; Li, H. CRC Therapy Identifies Indian Hedgehog Signaling in Mouse Endometrial Epithelial Cells and Inhibition of Ihh-KLF9 as a Novel Strategy for Treating IUA. Cells 2022, 11, 4053. [Google Scholar] [CrossRef]
  68. Alkhilaiwi, F.; Wang, L.; Zhou, D.; Raudsepp, T.; Ghosh, S.; Paul, S.; Palechor-Ceron, N.; Brandt, S.; Luff, J.; Liu, X.; et al. Long-Term Expansion of Primary Equine Keratinocytes That Maintain the Ability to Differentiate into Stratified Epidermis. Stem Cell Res. Ther. 2018, 9, 181. [Google Scholar] [CrossRef]
  69. Zhou, D.; Wang, A.; Maxwell, S.; Schlegel, R.; Yuan, H. Long-Term Culture of Canine Ocular Cells That Maintain Canine Papillomaviruses. Viruses 2022, 14, 2675. [Google Scholar] [CrossRef] [PubMed]
  70. Narumiya, S.; Ishizaki, T.; Uehata, M. Use and Properties of ROCK-Specific Inhibitor Y-27632. Methods Enzymol. 2000, 325, 273–284. [Google Scholar] [PubMed]
  71. Ligaba, S.B.; Khurana, A.; Graham, G.; Krawczyk, E.; Jablonski, S.; Petricoin, E.F.; Glazer, R.I.; Upadhyay, G. Multifactorial Analysis of Conditional Reprogramming of Human Keratinocytes. PLoS ONE 2015, 10, e0116755. [Google Scholar] [CrossRef] [PubMed]
  72. Mondal, A.M.; Zhou, H.; Horikawa, I.; Suprynowicz, F.A.; Li, G.; Dakic, A.; Rosenthal, B.; Ye, L.; Harris, C.C.; Schlegel, R.; et al. Δ133p53α, a Natural P53 Isoform, Contributes to Conditional Reprogramming and Long-Term Proliferation of Primary Epithelial Cells. Cell Death Dis. 2018, 9, 750. [Google Scholar] [CrossRef]
  73. Ji, H.; Tang, H.; Lin, H.; Mao, J.; Gao, L.; Liu, J.; Wu, T. Rho/Rock Cross-Talks with Transforming Growth Factor-β/Smad Pathway Participates in Lung Fibroblast-Myofibroblast Differentiation. Biomed. Rep. 2014, 2, 787–792. [Google Scholar] [CrossRef] [PubMed]
  74. Hynds, R.E.; Gowers, K.H.C.; Nigro, E.; Butler, C.R.; Bonfanti, P.; Giangreco, A.; Prêle, C.M.; Janes, S.M. Cross-Talk between Human Airway Epithelial Cells and 3T3-J2 Feeder Cells Involves Partial Activation of Human MET by Murine HGF. PLoS ONE 2018, 13, e0197129. [Google Scholar] [CrossRef]
  75. Calautti, E.; Li, J.; Saoncella, S.; Brissette, J.L.; Goetinck, P.F. Phosphoinositide 3-Kinase Signaling to Akt Promotes Keratinocyte Differentiation versus Death. J. Biol. Chem. 2005, 280, 32856–32865. [Google Scholar] [CrossRef]
  76. Alitalo, K.; Kuismanen, E.; Myllyl, R.; Kiistala, U.; Asko-Seljavaara, S.; Vaheri, A. Extracellular Matrix Proteins of Human Epidermal Keratinocytes and Feeder 3T3 Cells. J. Cell Biol. 1982, 94, 497–505. [Google Scholar] [CrossRef]
  77. Palechor-Ceron, N.; Suprynowicz, F.A.; Upadhyay, G.; Dakic, A.; Minas, T.; Simic, V.; Johnson, M.; Albanese, C.; Schlegel, R.; Liu, X. Radiation Induces Diffusible Feeder Cell Factor(s) That Cooperate with ROCK Inhibitor to Conditionally Reprogram and Immortalize Epithelial Cells. Am. J. Pathol. 2013, 183, 1862–1870. [Google Scholar] [CrossRef] [PubMed]
  78. Jeong, Y.J.; Hong, Y.; Yoon, Y.-J.; Sim, N.S.; Hong, S.-M.; Lim, J.-Y. Chemical Reprogramming Culture for the Expansion of Salivary Gland Epithelial Basal Progenitor Cells. Stem Cell Res. Ther. 2025, 16, 187. [Google Scholar] [CrossRef]
  79. Witkowski, T.A.; Li, B.; Andersen, J.G.; Kumar, B.; Mroz, E.A.; Rocco, J.W. Y-27632 Acts beyond ROCK Inhibition to Maintain Epidermal Stem-like-Cells in Culture. J. Cell Sci. 2023, 136, jcs260990. [Google Scholar] [CrossRef]
  80. Yugawa, T.; Nishino, K.; Ohno, S.; Nakahara, T.; Fujita, M.; Goshima, N.; Umezawa, A.; Kiyono, T. Noncanonical NOTCH Signaling Limits Self-Renewal of Human Epithelial and Induced Pluripotent Stem Cells through ROCK Activation. Mol. Cell Biol. 2013, 33, 4434–4447. [Google Scholar] [CrossRef] [PubMed]
  81. Correa, B.R.S.; Hu, J.; Penalva, L.O.F.; Schlegel, R.; Rimm, D.L.; Galante, P.A.F.; Agarwal, S. Patient-Derived Conditionally Reprogrammed Cells Maintain Intra-Tumor Genetic Heterogeneity. Sci. Rep. 2018, 8, 1327. [Google Scholar] [CrossRef]
  82. Krawczyk, E.; Kitlinska, J. Preclinical Models of Neuroblastoma—Current Status and Perspectives. Cancers 2023, 15, 3314. [Google Scholar] [CrossRef]
  83. Abualsaud, N.; Caprio, L.; Galli, S.; Krawczyk, E.; Alamri, L.; Zhu, S.; Gallicano, G.I.; Kitlinska, J. Neuropeptide Y/Y5 Receptor Pathway Stimulates Neuroblastoma Cell Motility Through RhoA Activation. Front. Cell Dev. Biol. 2021, 8, 627090. [Google Scholar] [CrossRef]
  84. Chen, C.; Choudhury, S.; Wangsa, D.; Lescott, C.J.; Wilkins, D.J.; Sripadhan, P.; Liu, X.; Wangsa, D.; Ried, T.; Moskaluk, C.; et al. A Multiplex Preclinical Model for Adenoid Cystic Carcinoma of the Salivary Gland Identifies Regorafenib as a Potential Therapeutic Drug. Sci. Rep. 2017, 7, 11410. [Google Scholar] [CrossRef]
  85. Daneshdoust, D.; Luo, M.; Li, Z.; Mo, X.; Alothman, S.; Kallakury, B.; Schlegel, R.; Zhang, J.; Guo, D.; Furth, P.A.; et al. Unlocking Translational Potential: Conditionally Reprogrammed Cells in Advancing Breast Cancer Research. Cells 2023, 12, 2388. [Google Scholar] [CrossRef]
  86. Vaclova, T.; Maguire, S.; Pugh, M.; Barry, P.; Orr, N. Abstract 816: Molecular and Genomic Characterization of a Newly Established Male Breast Cancer Cell Line. Cancer Res. 2017, 77, 816. [Google Scholar] [CrossRef]
  87. Jeong, Y.J.; Park, S.H.; Jeon, C.H. Detection of Circulating Tumor Cells in Patients with Breast Cancer Using the Conditionally Reprogrammed Cell Culture Method and Reverse Transcription-PCR of Htert and Mage A1-6. Oncol. Lett. 2020, 20, 78. [Google Scholar] [CrossRef] [PubMed]
  88. Brown, D.D.; Dabbs, D.J.; Lee, A.V.; McGuire, K.P.; Ahrendt, G.M.; Bhargava, R.; Davidson, N.E.; Brufsky, A.M.; Johnson, R.R.; Oesterreich, S.; et al. Developing in Vitro Models of Human Ductal Carcinoma in Situ from Primary Tissue Explants. Breast Cancer Res. Treat. 2015, 153, 311–321. [Google Scholar] [CrossRef]
  89. Alamri, A.M.; Kang, K.; Groeneveld, S.; Wang, W.; Zhong, X.; Kallakury, B.; Hennighausen, L.; Liu, X.; Furth, P.A. Primary Cancer Cell Culture: Mammary-Optimized vs Conditional Reprogramming. Endocr. Relat. Cancer 2016, 23, 535–554. [Google Scholar] [CrossRef]
  90. Jung, M.; Kowalczyk, K.; Hankins, R.; Bandi, G.; Kallakury, B.; Carrasquilla, M.A.; Banerjee, P.P.; Grindrod, S.; Dritschilo, A. Novel Paired Normal Prostate and Prostate Cancer Model Cell Systems Derived from African American Patients. Cancer Res. Commun. 2022, 2, 1617–1625. [Google Scholar] [CrossRef] [PubMed]
  91. Naeem, A.; Dakshanamurthy, S.; Walthieu, H.; Parasido, E.; Avantaggiati, M.; Tricoli, L.; Kumar, D.; Lee, R.J.; Feldman, A.; Noon, M.S.; et al. Predicting New Drug Indications for Prostate Cancer: The Integration of an in Silico Proteochemometric Network Pharmacology Platform with Patient-Derived Primary Prostate Cells. Prostate 2020, 80, 1233–1243. [Google Scholar] [CrossRef]
  92. Elbialy, A.; Kappala, D.; Desai, D.; Wang, P.; Fadiel, A.; Wang, S.J.; Makary, M.S.; Lenobel, S.; Sood, A.; Gong, M.; et al. Patient-Derived Conditionally Reprogrammed Cells in Prostate Cancer Research. Cells 2024, 13, 1005. [Google Scholar] [CrossRef]
  93. Stover, E.H.; Oh, C.; Keskula, P.; Choudhury, A.D.; Tseng, Y.Y.; Adalsteinsson, V.A.; Lohr, J.G.; Thorner, A.R.; Ducar, M.; Kryukov, G.V.; et al. Implementation of a Prostate Cancer-Specific Targeted Sequencing Panel for Credentialing of Patient-Derived Cell Lines and Genomic Characterization of Patient Samples. Prostate 2022, 82, 584–597. [Google Scholar] [CrossRef]
  94. Cao, J.; Chan, W.C.; Chow, M.S.S. Use of Conditional Reprogramming Cell, Patient Derived Xenograft and Organoid for Drug Screening for Individualized Prostate Cancer Therapy: Current and Future Perspectives (Review). Int. J. Oncol. 2022, 60, 52. [Google Scholar] [CrossRef]
  95. Saeed, K.; Rahkama, V.; Eldfors, S.; Bychkov, D.; Mpindi, J.P.; Yadav, B.; Paavolainen, L.; Aittokallio, T.; Heckman, C.; Wennerberg, K.; et al. Comprehensive Drug Testing of Patient-Derived Conditionally Reprogrammed Cells from Castration-Resistant Prostate Cancer. Eur. Urol. 2017, 71, 319–327. [Google Scholar] [CrossRef]
  96. Choudhary, S.; Ramasundaram, P.; Dziopa, E.; Mannion, C.; Kissin, Y.; Tricoli, L.; Albanese, C.; Lee, W.; Zilberberg, J. Human Ex Vivo 3D Bone Model Recapitulates Osteocyte Response to Metastatic Prostate Cancer. Sci. Rep. 2018, 8, 17975. [Google Scholar] [CrossRef]
  97. Ringer, L.; Sirajuddin, P.; Tricoli, L.; Waye, S.; Choudhry, M.U.; Parasido, E.; Sivakumar, A.; Heckler, M.; Naeem, A.; Abdelgawad, I.; et al. The Induction of the P53 Tumor Suppressor Protein Bridges the Apoptotic and Autophagic Signaling Pathways to Regulate Cell Death in Prostate Cancer Cells. Oncotarget 2014, 5, 10678–10691. [Google Scholar] [CrossRef] [PubMed]
  98. Ow, T.J.; Mehta, V.; Li, D.; Thomas, C.; Shrivastava, N.; Kawachi, N.; Gersten, A.J.; Zhu, J.; Schiff, B.A.; Smith, R.V.; et al. Characterization of a Diverse Set of Conditionally Reprogrammed Head and Neck Cancer Cell Cultures. Laryngoscope 2024, 134, 2748–2756. [Google Scholar] [CrossRef]
  99. Li, D.; Thomas, C.; Shrivastava, N.; Gersten, A.; Gadsden, N.; Schlecht, N.; Kawachi, N.; Schiff, B.A.; Smith, R.V.; Rosenblatt, G.; et al. Establishment of a Diverse Head and Neck Squamous Cancer Cell Bank Using Conditional Reprogramming Culture Methods. J. Med. Virol. 2023, 95, e28388. [Google Scholar] [CrossRef] [PubMed]
  100. Miyamoto, H. Conditional Reprogramming Technology: A New Tool for Personalized Medicine in Bladder Cancer? Transl. Cancer Res. 2019, 8, S636–S638. [Google Scholar] [CrossRef] [PubMed]
  101. Wang, W.; Shan, D.; Wang, G.; Mao, X.; You, W.; Wang, X.; Wang, Z. Elafibranor Emerged as a Potential Chemotherapeutic Drug for Non-Muscle Invasive Bladder Cancer. Cell Insight 2024, 3, 100149. [Google Scholar] [CrossRef]
  102. Kettunen, K.; Boström, P.J.; Lamminen, T.; Heinosalo, T.; West, G.; Saarinen, I.; Kaipio, K.; Rantala, J.; Albanese, C.; Poutanen, M.; et al. Personalized Drug Sensitivity Screening for Bladder Cancer Using Conditionally Reprogrammed Patient-Derived Cells. Eur. Urol. 2019, 76, 430–434. [Google Scholar] [CrossRef] [PubMed]
  103. Ge, Q.; Wang, P.; Wang, S.; Sood, A.; Meng, L.; Lee, C.; Parwani, A.V.; Li, J.; Liu, X. Urine PD-L1 as a Non-Invasive Biomarker for Immune Checkpoint Inhibitor (ICI) Therapy in Bladder Cancer. Adv. Biomark. Sci. Technol. 2025, 7, 172–179. [Google Scholar] [CrossRef]
  104. Liu, W.; Ju, L.; Cheng, S.; Wang, G.; Qian, K.; Liu, X.; Xiao, Y.; Wang, X. Conditional Reprogramming: Modeling Urological Cancer and Translation to Clinics. Clin. Transl. Med. 2020, 10, e95. [Google Scholar] [CrossRef]
  105. Simbulan-Rosenthal, C.M.; Dougherty, R.; Vakili, S.; Ferraro, A.M.; Kuo, L.W.; Alobaidi, R.; Aljehane, L.; Gaur, A.; Sykora, P.; Glasgow, E.; et al. CRISPR-Cas9 Knockdown and Induced Expression of CD133 Reveal Essential Roles in Melanoma Invasion and Metastasis. Cancers 2019, 11, 1490. [Google Scholar] [CrossRef]
  106. Xing, B.; Pu, C.; Chen, Y.; Sheng, Y.; Zhang, B.; Cui, J.; Wu, G.; Zhao, Y. Insights into the Characteristics of Primary Radioresistant Cervical Cancer Using Single-Cell Transcriptomics. Hum. Cell 2023, 36, 1135–1146. [Google Scholar] [CrossRef]
  107. Hynds, R.E.; Ben Aissa, A.; Gowers, K.H.C.; Watkins, T.B.K.; Bosshard-Carter, L.; Rowan, A.J.; Veeriah, S.; Wilson, G.A.; Quezada, S.A.; Swanton, C.; et al. Expansion of Airway Basal Epithelial Cells from Primary Human Non-Small Cell Lung Cancer Tumors. Int. J. Cancer 2018, 143, 160–166. [Google Scholar] [CrossRef]
  108. Wu, G.D.; Xiao, Y.G.; Fang, F.Y.; Yao, D.; Liu, J.; Cao, Y.H.; Mao, Y.; Yu, B.; Yao, T.R.; Wu, Y.M.; et al. Monitoring of Lung Malignant Epithelial Cells by Gene Methylation Analysis in the Conditionally Reprogrammed Cell Cultures. Neoplasma 2020, 67, 692–699. [Google Scholar] [CrossRef] [PubMed]
  109. Wu, M.; Hong, G.; Chen, Y.; Ye, L.; Zhang, K.; Cai, K.; Yang, H.; Long, X.; Gao, W.; Li, H. Personalized Drug Testing in a Patient with Non-Small-Cell Lung Cancer Using Cultured Cancer Cells from Pleural Effusion. J. Int. Med. Res. 2020, 48, 300060520955058. [Google Scholar] [CrossRef] [PubMed]
  110. Kodack, D.P.; Farago, A.F.; Dastur, A.; Held, M.A.; Dardaei, L.; Friboulet, L.; von Flotow, F.; Damon, L.J.; Lee, D.; Parks, M.; et al. Primary Patient-Derived Cancer Cells and Their Potential for Personalized Cancer Patient Care. Cell Rep. 2017, 21, 3298–3309. [Google Scholar] [CrossRef]
  111. Zhao, Z.; Feng, X.; Wu, H.; Chen, S.; Ma, C.; Guan, Z.; Lei, L.; Tang, K.; Chen, X.; Dong, Y.; et al. Construction of a Lung Cancer 3D Culture Model Based on Alginate/Gelatin Micro-Beads for Drug Evaluation. Transl. Lung Cancer Res. 2024, 13, 2698–2712. [Google Scholar] [CrossRef] [PubMed]
  112. Sette, G.; Salvati, V.; Giordani, I.; Pilozzi, E.; Quacquarini, D.; Duranti, E.; De Nicola, F.; Pallocca, M.; Fanciulli, M.; Falchi, M.; et al. Conditionally Reprogrammed Cells (CRC) Methodology Does Not Allow the in Vitro Expansion of Patient-Derived Primary and Metastatic Lung Cancer Cells. Int. J. Cancer 2018, 143, 88–99. [Google Scholar] [CrossRef] [PubMed]
  113. Zhao, R.; Li, R.; An, T.; Liu, X. Conditional Cell Reprogramming in Modeling Digestive System Diseases. Front. Cell Dev. Biol. 2021, 9, 669756. [Google Scholar] [CrossRef] [PubMed]
  114. Yang, C.S.; Kim, I.H.; Chae, H.D.; Kim, D.D.; Jeon, C.H. Detection of Circulating Gastrointestinal Cancer Cells in Conditionally Reprogrammed Cell Culture. In Vivo 2021, 35, 1515–1520. [Google Scholar] [CrossRef] [PubMed]
  115. Li, Y.; Guo, D.; Zhang, Y.; Wang, L.; Sun, T.; Li, Z.; Zhang, X.; Wang, S.; Chen, Y.; Wu, A. Rapid Screening for Individualized Chemotherapy Optimization of Colorectal Cancer: A Novel Conditional Reprogramming Technology-Based Functional Diagnostic Assay. Transl. Oncol. 2021, 14, 100935. [Google Scholar] [CrossRef]
  116. Wang, Y.; Liao, H.; Zheng, T.; Wang, J.; Guo, D.; Lu, Z.; Li, Z.; Chen, Y.; Shen, L.; Zhang, Y.; et al. Conditionally Reprogrammed Colorectal Cancer Cells Combined with Mouse Avatars Identify Synergy between EGFR and MEK or CDK4/6 Inhibitors. Am. J. Cancer Res. 2020, 10, 249–262. [Google Scholar]
  117. Kim, B.K.; Nam, S.W.; Min, B.S.; Ban, H.S.; Paik, S.; Lee, K.; Im, J.Y.; Lee, Y.; Park, J.T.; Kim, S.Y.; et al. Bcl-2-Dependent Synthetic Lethal Interaction of the IDF-11774 with the V0 Subunit C of Vacuolar ATPase (ATP6V0C) in Colorectal Cancer. Br. J. Cancer 2018, 119, 1347–1357. [Google Scholar] [CrossRef]
  118. Parasido, E.; Avetian, G.S.; Naeem, A.; Graham, G.; Pishvaian, M.; Glasgow, E.; Mudambi, S.; Lee, Y.; Ihemelandu, C.; Choudhry, M.; et al. The Sustained Induction of C-MYC Drives Nab-Paclitaxel Resistance in Primary Pancreatic Ductal Carcinoma Cells. Mol. Cancer Res. 2019, 17, 1815–1827. [Google Scholar] [CrossRef]
  119. Beglyarova, N.; Banina, E.; Zhou, Y.; Mukhamadeeva, R.; Andrianov, G.; Bobrov, E.; Lysenko, E.; Skobeleva, N.; Gabitova, L.; Restifo, D.; et al. Screening of Conditionally Reprogrammed Patient-Derived Carcinoma Cells Identifies ERCC3-MYC Interactions as a Target in Pancreatic Cancer. Clin. Cancer Res. 2016, 22, 6153–6163. [Google Scholar] [CrossRef]
  120. Hollevoet, K.; Mason-Osann, E.; Liu, X.F.; Imhof-Jung, S.; Niederfellner, G.; Pastan, I. In Vitro and in Vivo Activity of the Low-Immunogenic Antimesothelin Immunotoxin RG7787 in Pancreatic Cancer. Mol. Cancer Ther. 2014, 13, 2040–2049. [Google Scholar] [CrossRef]
  121. Su, S.; Di Poto, C.; Roy, R.; Liu, X.; Cui, W.; Kroemer, A.; Ressom, H.W. Long-Term Culture and Characterization of Patient-Derived Primary Hepatocytes Using Conditional Reprogramming. Exp. Biol. Med. 2019, 244, 857–864. [Google Scholar] [CrossRef]
  122. Su, S.; Di Poto, C.; Kroemer, A.H.; Cui, W.; Roy, R.; Liu, X.; Ressom, H.W. Establishment of Ornithine Transcarbamylase Deficiency-Derived Primary Human Hepatocyte with Hepatic Functions. Exp. Cell Res. 2019, 384, 111621. [Google Scholar] [CrossRef]
  123. Wang, Z.; Bi, B.; Song, H.; Liu, L.; Zheng, H.; Wang, S.; Shen, Z. Proliferation of Human Hepatocellular Carcinoma Cells from Surgically Resected Specimens under Conditionally Reprogrammed Culture. Mol. Med. Rep. 2019, 19, 4623–4630. [Google Scholar] [CrossRef]
  124. Liu, X.; Mondal, A.M. Conditional Cell Reprogramming for Modeling Host-Virus Interactions and Human Viral Diseases. J. Med. Virol. 2020, 92, 2440–2452. [Google Scholar] [CrossRef] [PubMed]
  125. Liu, X.; Wu, Y.; Rong, L. Conditionally Reprogrammed Human Normal Airway Epithelial Cells at ALI: A Physiological Model for Emerging Viruses. Virol. Sin. 2020, 35, 280–289. [Google Scholar] [CrossRef]
  126. Matsumoto, N.; Ueha, S.; Ueha, R.; Koyama, M.; Yamakawa, K.; Sato, T.; Goto, T.; Kono, T.; Shichino, S.; Matsushima, K.; et al. Induced Gene Expression Signature in Recurrent Respiratory Papillomatosis. Laryngoscope 2025. [Google Scholar] [CrossRef]
  127. Rani, A.Q.; Nurmemet, D.; Liffick, J.; Khan, A.; Mitchell, D.; Li, J.; Zhao, B.; Liu, X. Conditional Cell Reprogramming and Air–Liquid Interface Modeling Life Cycle of Oncogenic Viruses (HPV and EBV) in Epithelial Cells and Virus-Associated Human Carcinomas. Viruses 2023, 15, 1388. [Google Scholar] [CrossRef] [PubMed]
  128. Roberts, N.; Al Mubarak, R.; Francisco, D.; Kraft, M.; Chu, H.W. Comparison of Paired Human Nasal and Bronchial Airway Epithelial Cell Responses to Rhinovirus Infection and IL-13 Treatment. Clin. Transl. Med. 2018, 7, 13. [Google Scholar] [CrossRef] [PubMed]
  129. Schmidt, H.; Guthjahr, L.; Sauter, A.; Zech, F.; Nchioua, R.; Stenger, S.; Frick, M.; Kirchhoff, F.; Dietl, P.; Wittekindt, O.H. Serially Passaged, Conditionally Reprogrammed Nasal Epithelial Cells as a Model to Study Epithelial Functions and SARS-CoV-2 Infection. Am. J. Physiol. Cell Physiol. 2022, 322, C591–C604. [Google Scholar] [CrossRef]
  130. Xiao, Y.; Wang, L.; Li, S.; Fang, S.; Luo, F.; Chen, S.; Zou, X.; Ye, L.; Hou, W. Conditional Reprogrammed Human Limbal Epithelial Cell Model for Anti-SARS-CoV-2 Drug Screening. Heliyon 2024, 10, e30044. [Google Scholar] [CrossRef]
  131. Bukowy-Bieryłło, Z. Long-Term Differentiating Primary Human Airway Epithelial Cell Cultures: How Far Are We? Cell Communication and Signaling. Cell Commun. Signal. 2021, 19, 63. [Google Scholar] [CrossRef]
  132. Kaneko, Y.; Konno, T.; Kohno, T.; Kakuki, T.; Miyata, R.; Ohkuni, T.; Kakiuchi, A.; Yajima, R.; Ohwada, K.; Kurose, M.; et al. Induction of Airway Progenitor Cells via P63 and KLF11 by Rho-Kinase Inhibitor Y27632 in HTERT-Human Nasal Epithelial Cells. Am. J. Transl. Res. 2019, 11, 599–611. [Google Scholar]
  133. Kelly, N.A.; Shontz, K.M.; Bergman, M.; Manning, A.M.; Reynolds, S.D.; Chiang, T. Biobanked Tracheal Basal Cells Retain the Capacity to Differentiate. Laryngoscope Investig. Otolaryngol. 2022, 7, 2119–2125. [Google Scholar] [CrossRef]
  134. Kurokawa, A.; Kondo, M.; Honda, N.; Orimo, M.; Miyoshi, A.; Kobayashi, F.; Abe, K.; Akaba, T.; Tsuji, M.; Arimura, K.; et al. Analysis of the Diagnosis of Japanese Patients with Primary Ciliary Dyskinesia Using a Conditional Reprogramming Culture. Respir. Investig. 2022, 60, 407–417. [Google Scholar] [CrossRef]
  135. Peters-Hall, J.R.; Min, J.; Tedone, E.; Sho, S.; Siteni, S.; Mender, I.; Shay, J.W. Proliferation of Adult Human Bronchial Epithelial Cells without a Telomere Maintenance Mechanism for over 200 Population Doublings. FASEB J. 2020, 34, 386–398. [Google Scholar] [CrossRef]
  136. Peters-Hall, J.R.; Coquelin, M.L.; Torres, M.J.; Laranger, R.; Alabi, B.R.; Sho, S.; Calva-Moreno, J.F.; Thomas, P.J.; Shay, J.W. Long-Term Culture and Cloning of Primary Human Bronchial Basal Cells That Maintain Multipotent Differentiation Capacity and CFTR Channel Function. Am. J. Physiol. Lung Cell Mol. Physiol. 2018, 315, L313–L327. [Google Scholar] [CrossRef]
  137. Zhang, Z.; Bai, Q.; Chen, Y.; Ye, L.; Wu, X.; Long, X.; Ye, L.; Liu, J.; Li, H. Conditionally Reprogrammed Human Normal Bronchial Epithelial Cells Express Comparable Levels of Cytochromes P450 and Are Sensitive to BaP Induction. Biochem. Biophys. Res. Commun. 2018, 503, 2132–2138. [Google Scholar] [CrossRef] [PubMed]
  138. Veerati, P.C.; Nichol, K.S.; Read, J.M.; Bartlett, N.W.; Wark, P.A.B.; Knight, D.A.; Grainge, C.L.; Reid, A.T. Conditionally Reprogrammed Asthmatic Bronchial Epithelial Cells Express Lower FOXJ1 at Terminal Differentiation and Lower IFNs Following RV-A1 Infection. Am. J. Physiol. Lung Cell Mol. Physiol. 2022, 323, L495–L502. [Google Scholar] [CrossRef] [PubMed]
  139. Gentzsch, M.; Boyles, S.E.; Cheluvaraju, C.; Chaudhry, I.G.; Quinney, N.L.; Cho, C.; Dang, H.; Liu, X.; Schlegel, R.; Randell, S.H. Pharmacological Rescue of Conditionally Reprogrammed Cystic Fibrosis Bronchial Epithelial Cells. Am. J. Respir. Cell Mol. Biol. 2017, 56, 568–574. [Google Scholar] [CrossRef] [PubMed]
  140. Martinovich, K.M.; Iosifidis, T.; Buckley, A.G.; Looi, K.; Ling, K.M.; Sutanto, E.N.; Kicic-Starcevich, E.; Garratt, L.W.; Shaw, N.C.; Montgomery, S.; et al. Conditionally Reprogrammed Primary Airway Epithelial Cells Maintain Morphology, Lineage and Disease Specific Functional Characteristics. Sci. Rep. 2017, 7, 17971. [Google Scholar] [CrossRef]
  141. Kabbesh, H.; Riaz, M.A.; Jensen, A.D.; Scheiner-Bobis, G.; Konrad, L. Long-Term Maintenance of Viable Adult Rat Sertoli Cells Able to Establish Testis Barrier Components and Function in Response to Androgens. Cells 2021, 10, 2405. [Google Scholar] [CrossRef]
  142. Park, D.; Reddy, A.P.; Wilmarth, P.A.; Jensen, J.T.; Han, L. Mucus Secretions from a Conditionally Reprogrammed Primary Endocervical Cell Culture. F S Sci. 2022, 3, 159–165. [Google Scholar] [CrossRef]
  143. Wu, M.; Zhang, X.; Kang, Y.; Zhu, Y.; Su, Z.; Liu, J.; Zhang, W.; Chen, H.; Li, H. The First Human Vulvar Intraepithelial Neoplasia Cell Line with Naturally Infected Episomal HPV18 Genome. Viruses 2022, 14, 2054. [Google Scholar] [CrossRef]
  144. Looney, R.J.; Roberts, M.; Markovetz, M.; Godiah, R.; Yao, S.; Golgotiu, K.; Wei, S.; Cellucci, C.; Han, L. In Vitro Inhibition of the CFTR Ion Channel in the Macaca mulatta Cervix Thickens Cervical Mucus. Biol. Reprod. 2025, ioaf103. [Google Scholar] [CrossRef] [PubMed]
  145. Xia, S.; Wu, M.; Chen, S.; Zhang, T.; Ye, L.; Liu, J.; Li, H. Long Term Culture of Human Kidney Proximal Tubule Epithelial Cells Maintains Lineage Functions and Serves as an Ex Vivo Model for Coronavirus Associated Kidney Injury. Virol. Sin. 2020, 35, 311–320. [Google Scholar] [CrossRef] [PubMed]
  146. Jensen, T.J.; Foster, C.; Sayej, W.; Finck, C.M. Conditional Reprogramming of Pediatric Human Esophageal Epithelial Cells for Use in Tissue Engineering and Disease Investigation. J. Vis. Exp. 2017, 121, 55243. [Google Scholar] [CrossRef]
  147. Liu, L.; Mondal, A.M.; Liu, X. Crosstalk of Moderate ROS and PARP-1 Contributes to Sustainable Proliferation of Conditionally Reprogrammed Keratinocytes. J. Biochem. Mol. Toxicol. 2023, 37, e23262. [Google Scholar] [CrossRef] [PubMed]
  148. Jin, L.; Qu, Y.; Gomez, L.J.; Chung, S.; Han, B.; Gao, B.; Yue, Y.; Gong, Y.; Liu, X.; Amersi, F.; et al. Characterization of Primary Human Mammary Epithelial Cells Isolated and Propagated by Conditional Reprogrammed Cell Culture. Oncotarget 2018, 9, 11503–11514. [Google Scholar] [CrossRef]
  149. Sayej, W.N.; Foster, C.; Jensen, T.; Chatfield, S.; Finck, C. Expanding and Characterizing Esophageal Epithelial Cells Obtained from Children with Eosinophilic Esophagitis. Pediatr. Res. 2018, 84, 306–313. [Google Scholar] [CrossRef]
  150. Daneshdoust, D.; He, K.; Wang, Q.E.; Li, J.; Liu, X. Modeling Respiratory Tract Diseases for Clinical Translation Employing Conditionally Reprogrammed Cells. Cell Insight 2024, 3, 100201. [Google Scholar] [CrossRef]
  151. Katta, S.S.; Nagati, V.; Paturi, A.S.V.; Murakonda, S.P.; Murakonda, A.B.; Pandey, M.K.; Gupta, S.C.; Pasupulati, A.K.; Challagundla, K.B. Neuroblastoma: Emerging Trends in Pathogenesis, Diagnosis, and Therapeutic Targets. J. Control. Release 2023, 357, 444–459. [Google Scholar] [CrossRef]
  152. Ornell, K.J.; Coburn, J.M. Developing Preclinical Models of Neuroblastoma: Driving Therapeutic Testing. BMC Biomed. Eng. 2019, 1, 33. [Google Scholar] [CrossRef] [PubMed]
  153. Kolb, E.A.; Houghton, P.J.; Kurmasheva, R.T.; Mosse, Y.P.; Maris, J.M.; Erickson, S.W.; Guo, Y.; Teicher, B.A.; Smith, M.A.; Gorlick, R. Preclinical Evaluation of the Combination of AZD1775 and Irinotecan against Selected Pediatric Solid Tumors: A Pediatric Preclinical Testing Consortium Report. Pediatr. Blood Cancer 2020, 67, e28098. [Google Scholar] [CrossRef] [PubMed]
  154. Tian, X.; Zhou, D.; Chen, L.; Tian, Y.; Zhong, B.; Cao, Y.; Dong, Q.; Zhou, M.; Yan, J.; Wang, Y.; et al. Polo-like Kinase 4 Mediates Epithelial-Mesenchymal Transition in Neuroblastoma via PI3K/Akt Signaling Pathway Article. Cell Death Dis. 2018, 9, 54. [Google Scholar] [CrossRef] [PubMed]
  155. Luo, L.; Krawczyk, E.; Lourdusamy, A.; Storer, L.C.; Xian, L.; Cohen, K.J.; Schlegel, R.; Grundy, R.; Resar, L. Abstract LB-224: A. Novel Model of Pediatric Spinal Ependymoma Using Conditionally Reprogrammed Cells from a Primary Tumor Demonstrates Aberrant Expression of HMGA, HOX, MYC and Other Wnt Target Genes. Cancer Res. 2017, 77 (Suppl. 13), LB-224. [Google Scholar] [CrossRef]
  156. Yuan, M.; White, D.; Resar, L.; Bar, E.; Groves, M.; Cohen, A.; Jackson, E.; Bynum, J.; Rubens, J.; Mumm, J.; et al. Conditional Reprogramming Culture Conditions Facilitate Growth of Lower-Grade Glioma Models. Neuro Oncol. 2021, 23, 770–782. [Google Scholar] [CrossRef]
  157. Nguyen, J.; Saffari, P.S.; Pollack, A.S.; Vennam, S.; Gong, X.; West, R.B.; Pollack, J.R. New Ameloblastoma Cell Lines Enable Preclinical Study of Targeted Therapies. J. Dent. Res. 2022, 101, 1517–1525. [Google Scholar] [CrossRef]
  158. Saffari, P.S.; Vapniarsky, N.; Pollack, A.S.; Gong, X.; Vennam, S.; Pollack, A.J.; Verstraete, F.J.M.; West, R.B.; Arzi, B.; Pollack, J.R. Most Canine Ameloblastomas Harbor HRAS Mutations, Providing a Novel Large-Animal Model of RAS-Driven Cancer. Oncogenesis 2019, 8, 11. [Google Scholar] [CrossRef] [PubMed]
  159. Panaccione, A.; Chang, M.T.; Carbone, B.E.; Guo, Y.; Moskaluk, C.A.; Virk, R.K.; Chiriboga, L.; Prasad, M.L.; Judson, B.; Mehra, S.; et al. NOTCH1 and SOX10 Are Essential for Proliferation and Radiation Resistance of Cancer Stem-like Cells in Adenoid Cystic Carcinoma. Clin. Cancer Res. 2016, 22, 2083–2095. [Google Scholar] [CrossRef]
  160. Ci, X.; Hao, J.; Dong, X.; Xue, H.; Wu, R.; Choi, S.Y.C.; Haegert, A.M.; Collins, C.C.; Liu, X.; Lin, D.; et al. Conditionally Reprogrammed Cells from Patient-Derived Xenograft to Model Neuroendocrine Prostate Cancer Development. Cells 2020, 9, 1398. [Google Scholar] [CrossRef]
  161. Dong, Y.; Wang, J.; Ji, W.; Zheng, M.; Wang, P.; Liu, L.; Li, S. Preclinical Application of Conditional Reprogramming Culture System for Laryngeal and Hypopharyngeal Carcinoma. Front. Cell Dev. Biol. 2021, 9, 744969. [Google Scholar] [CrossRef] [PubMed]
  162. Grossmann, L.D.; Chen, C.-H.; Uzun, Y.; Thadi, A.; Wolpaw, A.J.; Louault, K.; Goldstein, Y.; Surrey, L.F.; Martinez, D.; Calafatti, M.; et al. Identification and Characterization of Chemotherapy Resistant High-Risk Neuroblastoma Persister Cells. Cancer Discov. 2024, 12, 2387–2406. [Google Scholar] [CrossRef] [PubMed]
  163. Wolf, A.B.; Reynolds, C.P.; Barbieri, E. Characterization of Persister Cells Provides Insights into Mechanisms of Therapy Resistance in Neuroblastoma. Cancer Discov. 2024, 14, 2308–2311. [Google Scholar] [CrossRef]
  164. Polychronopoulos, P.A.; Bedoya-Reina, O.C.; Johnsen, J.I. The Neuroblastoma Microenvironment, Heterogeneity and Immunotherapeutic Approaches. Cancers 2024, 16, 1863. [Google Scholar] [CrossRef]
  165. Yu, W.; Biyik-Sit, R.; Uzun, Y.; Chen, C.-H.; Thadi, A.; Sussman, J.H.; Pang, M.; Wu, C.-Y.; Grossmann, L.D.; Gao, P.; et al. Longitudinal Single-Cell Multiomic Atlas of High-Risk Neuroblastoma Reveals Chemotherapy-Induced Tumor Microenvironment Rewiring. Nat. Genet. 2025, 1–13. [Google Scholar] [CrossRef]
  166. Amoli, M.S.; Rezapourdamanab, S.; Jin, L.; Cadena, M.A.; Kaw, K.; Sridhar, V.; Meselhe, M.; Krikor, S.; Mahmoudi, M.; Ning, L.; et al. Protocol for 3D Bioprinting of a 3D in Vitro Model of Neuroblastoma. STAR Protoc. 2025, 6, 103725. [Google Scholar] [CrossRef]
  167. Yamada, Y.; Beltran, H. Clinical and Biological Features of Neuroendocrine Prostate Cancer. Curr. Oncol. Rep. 2021, 23, 15. [Google Scholar] [CrossRef]
  168. Shaheen, S.; Guddati, A.K. Gastrointestinal Stromal Tumor: A Rare Abdominal Tumor. Case Rep. Oncol. 2013, 6, 148–153. [Google Scholar] [CrossRef]
  169. Rheinwald, J.G.; Green, H. Formation of a Keratinizing Epithelium in Culture by a Cloned Cell Line Derived from a Teratoma. Cell 1975, 6, 317–330. [Google Scholar] [CrossRef] [PubMed]
  170. Kresbach, C.; Neyazi, S.; Schüller, U. Updates in the Classification of Ependymal Neoplasms: The 2021 WHO Classification and Beyond. Brain Pathol. 2022, 32, e13068. [Google Scholar] [CrossRef] [PubMed]
  171. Peng, H.; Ge, P. Long Non-Coding RNA HCG18 Facilitates the Progression of Laryngeal and Hypopharyngeal Squamous Cell Carcinoma by Upregulating FGFR1 via MiR-133b. Mol. Med. Rep. 2022, 25, 46. [Google Scholar] [CrossRef] [PubMed]
Figure 1. The outline of the clinical specimen collection and applications of the conditional cell reprogramming technology. Figure created using BioRender (https://app.biorender.com/, accessed on 1 August 2025).
Figure 1. The outline of the clinical specimen collection and applications of the conditional cell reprogramming technology. Figure created using BioRender (https://app.biorender.com/, accessed on 1 August 2025).
Cancers 17 02834 g001
Figure 2. Major strengths and limitations of the conditional cell reprogramming technology. Figure created using BioRender (https://app.biorender.com/, accessed on 1 August 2025).
Figure 2. Major strengths and limitations of the conditional cell reprogramming technology. Figure created using BioRender (https://app.biorender.com/, accessed on 1 August 2025).
Cancers 17 02834 g002
Figure 3. Cell lines obtained from tissues collected from rare cancers and generated using conditional reprogramming technology: (A) murine neuroblastoma cell line; (B) neuroendocrine cervical cancer cell line; (C) GIST cell line. Scale bars: 400 µm (A,C) and 200 µm (B).
Figure 3. Cell lines obtained from tissues collected from rare cancers and generated using conditional reprogramming technology: (A) murine neuroblastoma cell line; (B) neuroendocrine cervical cancer cell line; (C) GIST cell line. Scale bars: 400 µm (A,C) and 200 µm (B).
Cancers 17 02834 g003
Table 1. Comparison between selected methods of cell immortalization in vitro.
Table 1. Comparison between selected methods of cell immortalization in vitro.
Transformed Cell LinesiPSc *CR Cells **
Success rateMediumMediumHigh
LifespanLongLongLong
Timing1–2 months2–10 weeks1–10 days
ExpansionHighMediumHigh
Genetic stabilityLowMediumHigh
Tissue specificityLowLowHigh
HeterogeneityNoMediumMedium
DifferentiationLowMediumHigh
High-throughput drug screening applicabilityHighLowHigh
Low-throughput drug screening applicabilityHighHighHigh
CostLowMediumLow
* iPSc: induced pluripotent stem cells; ** CR cells: conditionally reprogrammed cells.
Table 2. The list of conditionally reprogrammed cell lines generated from rare cancers. Either standard (CR medium + Y-27632 + feeder cells) or modified (CM conditioned medium, ACC adenoid cystic carcinoma medium, low O2 level, collagen coating) CR technology was utilized.
Table 2. The list of conditionally reprogrammed cell lines generated from rare cancers. Either standard (CR medium + Y-27632 + feeder cells) or modified (CM conditioned medium, ACC adenoid cystic carcinoma medium, low O2 level, collagen coating) CR technology was utilized.
TumorStandard CR TechnologyCM
Medium
ACC **
Medium
2% O2Collagen CoatingNumber of Generated CR Cell LinesRefs
CR
Medium
Feeder
Cells
Y-27632
Neuroblastoma (murine)+ + + 21[59,82,83]
Neuroendocrine cervical cancer+ + +1[60]
Ependymoma+ + + 1[155]
+ ++ 2[156]
Pilocytic astrocytoma+ ++ 3[156]
Pleomorphic xanthoastrocytoma+ ++ 1[156]
Other lower-grade gliomas+ ++ 8 (total)[156]
GIST+ + + 1[39]
Ameloblastomahuman *+ ++ 6[157]
canine+ ++ 4[158]
ACC[159]+ ++ 6 (total)[159]
[84]+++ + 2[84]
Neuroendocrine prostate cancer+++ 1[160]
Laryngeal and hypopharyngeal carcinoma+++ 28[161]
GIST: gastrointestinal stromal tumor; ACC: adenoid cystic carcinoma; CR: conditional reprogramming; CM: conditioned medium. ** ACC medium consists of CR medium supplemented with noggin, SB202190, rhFGF, CHIR-99021 and Wnt-3a [84]. * Human ameloblastoma cell lines grew for 6-8 passages only in CR conditions.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Krawczyk, E. Conditionally Reprogrammed Cells as Preclinical Model for Rare Cancers. Cancers 2025, 17, 2834. https://doi.org/10.3390/cancers17172834

AMA Style

Krawczyk E. Conditionally Reprogrammed Cells as Preclinical Model for Rare Cancers. Cancers. 2025; 17(17):2834. https://doi.org/10.3390/cancers17172834

Chicago/Turabian Style

Krawczyk, Ewa. 2025. "Conditionally Reprogrammed Cells as Preclinical Model for Rare Cancers" Cancers 17, no. 17: 2834. https://doi.org/10.3390/cancers17172834

APA Style

Krawczyk, E. (2025). Conditionally Reprogrammed Cells as Preclinical Model for Rare Cancers. Cancers, 17(17), 2834. https://doi.org/10.3390/cancers17172834

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop