Tumor organoids, especially patient-derived organoids (PDOs) exhibit marked similarities in histopathological morphology, genomic alterations, and specific marker expression profiles to those of primary tumour tissues. They are applied in various fields including drug screening, gene editing, and identification of oncogenes. However, CAR-T therapy in the treatment of solid tumours is still at an exploratory stage. Tumour organoids offer unique advantages over other preclinical models commonly used for CAR-T therapy research, which the preservation of the biological characteristics of primary tumour tissue is critical for the study of early-stage solid tumour CAR-T therapies. Although some investigators have used this co-culture model to validate newly targeted CAR-T cells, optimise existing CAR-T cells and explore combination therapy strategies, there is still untapped potential in the co-culture models used today. This review introduces the current status of the application of tumour organoid and CAR-T cell co-culture models in recent years and commented on the limitations of the current co-cultivation model. Meanwhile, we compared the tumour organoid model with two pre-clinical models commonly used in CAR-T therapy research. Eventually, combined with the new progress of organoid technologies, optimization suggestions were proposed for the co-culture model from five perspectives: preserving or reconstructing the tumor microenvironment, systematization, vascularization, standardized culture procedures, and expanding the tumor organoids resource library, aimed at assisting related researchers to better utilize co-culture models.

Oseltamivir is a widely used influenza virus neuraminidase (NA) inhibitor that prevents the release of new virus particles from host cells. However, oseltamivir-resistant strains have emerged, but effective drugs against them have not yet been developed. Elucidating the binding mechanisms between NA and oseltamivir may provide valuable information for the design of new drugs against NA mutants resistant to oseltamivir. Here, we conducted large-scale (353.4 μs) free-binding molecular dynamics simulations, together with a Markov State Model and an importance-sampling algorithm, to reveal the binding process of oseltamivir and NA. Ten metastable states and five major binding pathways were identified that validated and complemented previously discovered binding pathways, including the hypothesis that oseltamivir can be transferred from the secondary sialic acid binding site to the catalytic site. The discovery of multiple new metastable states, especially the stable bound state containing a water-mediated hydrogen bond between Arg118 and oseltamivir, may provide new insights into the improvement of NA inhibitors. We anticipated the findings presented here will facilitate the development of drugs capable of combating NA mutations.

Background: The development of HCC is often associated with extensive metabolic disturbances. Single cell RNA sequencing (scRNA-seq) provides a better understanding of cellular behavior in the context of complex tumor microenvironments by analyzing individual cell populations. Methods: The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data was employed to investigate the metabolic pathways in HCC. Principal component analysis (PCA) and uniform manifold approximation and projection (UMAP) analysis were applied to identify six cell subpopulations, namely, T/NK cells, hepatocytes, macrophages, endothelial cells, fibroblasts, and B cells. The gene set enrichment analysis (GSEA) was performed to explore the existence of pathway heterogeneity across different cell subpopulations. Univariate Cox analysis was used to screen genes differentially related to The Overall Survival in TCGA-LIHC patients based on scRNA-seq and bulk RNA-seq datasets, and LASSO analysis was used to select significant predictors for incorporation into multivariate Cox regression. Connectivity Map (CMap) was applied to analysis drug sensitivity of risk models and targeting of potential compounds in high risk groups.Results: Analysis of TCGA-LIHC survival data revealed the molecular markers associated with HCC prognosis, including MARCKSL1, SPP1, BSG, CCT3, LAGE3, KPNA2, SF3B4, GTPBP4, PON1, CFHR3, and CYP2C9. The RNA expression of 11 prognosis-related differentially expressed genes (DEGs) in normal human hepatocyte cell line MIHA and HCC cell lines HCC-LM3 and HepG2 were compared by qPCR. Higher KPNA2, LAGE3, SF3B4, CCT3 and GTPBP4 protein expression and lower CYP2C9 and PON1 protein expression in HCC tissues from Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) databases. The results of target compound screening of risk model showed that mercaptopurine is a potential anti-HCC drug.Conclusion: The prognostic genes associated with glucose and lipid metabolic changes in a hepatocyte subpopulation and comparison of liver malignancy cells to normal liver cells may provide insight into the metabolic characteristics of HCC and the potential prognostic biomarkers of tumor-related genes and contribute to developing new treatment strategies for individuals.

Antigen CD133 is a glycoprotein present on the surface of cancer stem cells (CSCs), which is a key molecule to regulate the fate of stem cells and a functional marker of stem cells. Herein, a novel fluorescence “turn-on” nano-aptamer sensor for quantifying CD133 was designed using hybridization between CD133-targeted aptamers and partially complementary paired RNA (ssRNA), which were modified on the surface of quantum dots (QDs) and gold nanoparticles (AuNPs), respectively. Owing to the hybridization of aptamers and ssRNA, the distance between QDs and AuNPs was shortened, which caused fluorescence resonance energy transfer (FRET) between them, and the florescence of QDs was quenched by AuNPs. When CD133 competitively replaced ssRNA and was bound to aptamers, AuNPs-ssRNA could be released, which led to a recovery of fluorescent signals of QDs. The increase in the relative value of fluorescence intensity was investigated to linearly correlate with the CD133 concentration in the range of 0–1.539 μM, and the detection limit was 6.99 nM. In confocal images of A549 cells, the CD133 aptamer sensor was further proved applicable in lung cancer cell samples with specificity, precision, and accuracy. Compared with complicated methods, this study provided a fresh approach to develop a highly sensitive and selective detection sensor for CSC markers.

Nasopharyngeal carcinoma (NPC) is a unique malignant tumor of the head and neck. Despite higher survival rates by the combination of radiotherapy and chemotherapy, the recurrence or metastasis of NPC still occurs at about 10%. Therefore, there is urgent demand to develop more effective in vivo models for preclinical trials to investigate the mechanisms of NPC development and progression and to explore better treatment approaches. In this study, we transplanted human NPC CNE1 cells into zebrafish embryos to establish a xenograft model of NPC, where the proliferation and invasion behaviors of NPC cells were investigated in vivo. Combining in vitro and in vivo analyses, we found that activating transcription factor 7 (ATF7) was involved in the occurrence and development of NPC regulated by peptidyl-prolyl cis- trans isomerase NIMA-interacting 1 (Pin1). The zebrafish NPC xenograft model established here thereby provides an in vivo tool for exploring the occurrence and development of NPC, which may help to identify new tumor markers and develop new therapeutic strategies for the treatment of NPC.

Corrigendum: Single-cell transcriptome analysis reveals the metabolic changes and the prognostic value of malignant hepatocyte subpopulations and predict new therapeutic agents for hepatocellular carcinoma