Conditional cell reprogramming for modeling host-virus interactions and human viral diseases

Identification of HPV oncogene and host cell differentiation associated cellular heterogeneity in cervical cancer via single-cell transcriptomic analysis

Human Papillomaviruses (HPVs) are associated with around 5-10% of human cancer, notably nearly 99% of cervical cancer. The mechanisms HPV interacts with stratified epithelium (differentiated layers) during the viral life cycle, and oncogenesis remain unclear. In this study, we used single-cell transcriptome analysis to study viral gene and host cell differentiation-associated heterogeneity of HPV-positive cervical cancer tissue. We examined the HPV16 genes - E1, E6, and E7, and found they expressed differently across nine epithelial clusters. We found that three epithelial clusters had the highest proportion of HPV-positive cells (33.6%, 37.5%, and 32.4%, respectively), while two exhibited the lowest proportions (7.21% and 5.63%, respectively). Notably, the cluster with the most HPV-positive cells deviated significantly from normal epithelial layer markers, exhibiting functional heterogeneity and altered epithelial structuring, indicating that significant molecular heterogeneity existed in cancer tissues and that these cells exhibited unique/different gene signatures compared with normal epithelial cells. These HPV-positive cells, compared to HPV-negative, showed different gene expressions related to the extracellular matrix, cell adhesion, proliferation, and apoptosis. Further, the viral oncogenes E6 and E7 appeared to modify epithelial function via distinct pathways, thus contributing to cervical cancer progression. We investigated the HPV and host transcripts from a novel viewpoint focusing on layer heterogeneity. Our results indicated varied HPV expression across epithelial clusters and epithelial heterogeneity associated with viral oncogenes, contributing biological insights to this critical field of study.

Identification of HPV oncogene and host cell differentiation associated cellular heterogeneity in cervical cancer via single-cell transcriptomic analysis

Human Papillomaviruses (HPVs) are associated with around 5%-10% of human cancer, notably nearly 99% of cervical cancer. The mechanisms HPV interacts with stratified epithelium (differentiated layers) during the viral life cycle, and oncogenesis remain unclear. In this study, we used single-cell transcriptome analysis to study viral gene and host cell differentiation-associated heterogeneity of HPV-positive cervical cancer tissue. We examined the HPV16 genes-E1, E6, and E7, and found they expressed differently across nine epithelial clusters. We found that three epithelial clusters had the highest proportion of HPV-positive cells (33.6%, 37.5%, and 32.4%, respectively), while two exhibited the lowest proportions (7.21% and 5.63%, respectively). Notably, the cluster with the most HPV-positive cells deviated significantly from normal epithelial layer markers, exhibiting functional heterogeneity and altered epithelial structuring, indicating that significant molecular heterogeneity existed in cancer tissues and that these cells exhibited unique/different gene signatures compared with normal epithelial cells. These HPV-positive cells, compared to HPV-negative, showed different gene expressions related to the extracellular matrix, cell adhesion, proliferation, and apoptosis. Further, the viral oncogenes E6 and E7 appeared to modify epithelial function via distinct pathways, thus contributing to cervical cancer progression. We investigated the HPV and host transcripts from a novel viewpoint focusing on layer heterogeneity. Our results indicated varied HPV expression across epithelial clusters and epithelial heterogeneity associated with viral oncogenes, contributing biological insights to this critical field of study.

Conditional Cell Reprogramming and Air-Liquid Interface Modeling Life Cycle of Oncogenic Viruses (HPV and EBV) in Epithelial Cells and Virus-Associated Human Carcinomas

Several oncogenic viruses are associated with approximately 20% of human cancers. Experimental models are crucial for studying the pathogenicity and biological aspects of oncogenic viruses and their potential mechanisms in tumorigenesis. Current cell models have considerable limitations such as: their low yield, genetic and epigenetic modification, and reduction in tumor heterogeneity during long propagation. Cancer cell lines are limited and not appropriate for studying the viral life cycle, for example, natural viral life cycles of HPV and EBV, and their persistence and latency in epithelial cells are poorly understood, since these processes are highly related to epithelial differentiation. Therefore, there is an urgent need of reliable human physiological cell models to study viral life cycle and cancer initiation. Conditional cell reprogramming (CCR) is a rapid and robust cell culture system, where the cells can be established from minimally invasive or noninvasive specimens and their lineage functions preserved during the long-term culture. These CR cells retain their ability to differentiate at air-liquid interface (ALI). Here, we recapitulated the applications of CR and ALI approaches in modeling host-virus interactions and viral-mediated tumorigenesis.

Application of Organoids in Carcinogenesis Modeling and Tumor Vaccination

Organoids well recapitulate organ-specific functions from their tissue of origin and remain fundamental aspects of organogenesis. Organoids are widely applied in biomedical research, drug discovery, and regenerative medicine. There are various cultivated organoid systems induced by adult stem cells and pluripotent stem cells, or directly derived from primary tissues. Researchers have drawn inspiration by combination of organoid technology and tissue engineering to produce organoids with more physiological relevance and suitable for translational medicine. This review describes the value of applying organoids for tumorigenesis modeling and tumor vaccination. We summarize the application of organoids in tumor precision medicine. Extant challenges that need to be conquered to make this technology be more feasible and precise are discussed.

Serially passaged, conditionally reprogrammed nasal epithelial cells as a model to study epithelial functions and SARS-CoV-2 infection

Primary airway epithelial cells (pAECs) cultivated at air-liquid interface (ALI) conditions are widely used as surrogates for human in vivo epithelia. To extend the proliferative capacity and to enable serially passaging of pAECs, conditional reprogramming (cr) has been employed in recent years. However, ALI epithelia derived from cr cells often display functional changes with increasing passages. This highlights the need for thorough validation of the ALI cultures for the respective application. In our study, we evaluated the use of serially passaged cr nasal epithelial cells (crNECs) as a model to study SARS-CoV-2 infection and effects on ion and water transport. NECs were obtained from healthy individuals and cultivated as ALI epithelia derived from passages 1, 2, 3, and 5. We compared epithelial differentiation, ion and water transport, and infection with SARS-CoV-2 between passages. Our results show that epithelia maintained major differentiation characteristics and physiological ion and water transport properties through all passages. However, the frequency of ciliated cells, short circuit currents reflecting epithelial Na⁺ channel (ENaC) and cystic fibrosis transmembrane conductance regulator (CFTR) activity and expression of aquaporin 3 and 5 decreased gradually over passages. crNECs also expressed SARS-CoV-2 receptors angiotensin converting enzyme 2 (ACE2) and transmembrane serin2 protease 2 (TMPRSS2) across all passages and allowed SARS-CoV-2 replication in all passages. In summary, we provide evidence that passaged crNECs provide an appropriate model to study SARS-CoV-2 infection and also epithelial transport function when considering some limitations that we defined herein.

Human Nasal Epithelial Cells (hNECs ) Generated by Air-Liquid Interface (ALI) Culture as a Model System for Studying the Pathogenesis of SARS-CoV-2

The nasal epithelium lining the human upper airway is the primary portal of entry for several respiratory pathogens, including the recently emerged SARS-CoV-2 virus responsible for the ongoing COVID-19 pandemic. Here, we describe in detail methods for in vitro ALI differentiation of primary cells collected from human donors, to obtain differentiated hNECs. This can serve as a physiologically relevant model to investigate various aspects of host-pathogen responses to SARS-CoV-2 and other emerging respiratory viruses.

Conditional Cell Reprogramming in Modeling Digestive System Diseases

Digestive diseases have become an important source of morbidity and mortality. The considerable financial and health burdens caused by digestive diseases confirm the importance of extensive research to better understand and treat these diseases. The development of reliable preclinical models is essential for understanding the pathogenesis of digestive diseases and developing treatment and prevention methods. However, traditional established cell lines and animal models still have many limitations in the study of the digestive system. Conditional reprogramming (CR) cell culture is a newly developed primary technology that uses irradiated Swiss-3T3-J2 mouse fibroblast cells and the Rho-associated kinase (ROCK) inhibitor Y-27632 to rapidly and efficiently generate many cells from diseased and normal tissues. CR cells (CRCs) can be reprogrammed to maintain a highly proliferative state and recapitulate the histological and genomic features of the original tissue. Moreover, after removing these conditions, the phenotype was completely reversible. Therefore, CR technology may represent an ideal model to study digestive system diseases, to test drug sensitivity, to perform gene profile analysis, and to undertake xenograft research and regenerative medicine. Indeed, together with organoid cultures, CR technology has been recognized as one of the key new technologies by NIH precision oncology and also used for NCI human cancer model initiatives (HCMI) program with ATCC. In this article, we review studies that use CR technology to conduct research on diseases of the digestive system.

Conditional cell reprogramming for modeling host-virus interactions and human viral diseases

Conventional cancer and transformed cell lines are widely used in cancer biology and other fields within biology. These cells usually have abnormalities from the original tumor itself, but may also develop abnormalities due to genetic manipulation, or genetic and epigenetic changes during long-term passages. Primary cultures may maintain lineage functions as the original tissue types, yet they have a very limited life span or population doubling time because of the nature of cellular senescence. Primary cultures usually have very low yields, and the high variability from any original tissue specimens, largely limiting their applications in research. Animal models are often used for studies of virus infections, disease modeling, development of antiviral drugs, and vaccines. Human viruses often need a series of passages in vivo to adapt to the host environment because of variable receptors on the cell surface and may have intracellular restrictions from the cell types or host species. Here, we describe a long-term cell culture system, conditionally reprogrammed cells (CRCs), and its applications in modeling human viral diseases and drug discovery. Using feeder layer coculture in presence of Y-27632 (conditional reprogramming, CR), CRCs can be obtained and rapidly propagated from surgical specimens, core or needle biopsies, and other minimally invasive or noninvasive specimens, for example, nasal cavity brushing. CRCs preserve their lineage functions and provide biologically relevant and physiological conditions, which are suitable for studies of viral entry and replication, innate immune responses of host cells, and discovery of antiviral drugs. In this review, we summarize the applications of CR technology in modeling host-virus interactions and human viral diseases including severe acute respiratory syndrome coronavirus-2 and coronavirus disease-2019, and antiviral discovery.