Background: Glioblastoma multiforme (GBM) is the most common cancer of the central nervous system, while Parkinson’s disease (PD) is a degenerative neurological condition frequently affecting the elderly. Neurotrophic factors are key factors associated with the progression of degenerative neuropathies and gliomas.Methods: The 2601 neurotrophic factor-related genes (NFRGs) available in the Genecards portal were analyzed and 12 NFRGs with potential roles in the pathogenesis of Parkinson’s disease and the prognosis of GBM were identified. LASSO regression and random forest algorithms were then used to screen the key NFRGs. The correlation of the key NFRGs with immune pathways was verified using GSEA (Gene Set Enrichment Analysis). A prognostic risk scoring system was constructed using LASSO (Least absolute shrinkage and selection operator) and multivariate Cox risk regression based on the expression of the 12 NFRGs in the GBM cohort from The Cancer Genome Atlas (TCGA) database. We also investigated differences in clinical characteristics, mutational landscape, immune cell infiltration, and predicted efficacy of immunotherapy between risk groups. Finally, the accuracy of the model genes was validated using multi-omics mutation analysis, single-cell sequencing, QT-PCR, and HPA.Results: We found that 4 NFRGs were more reliable for the diagnosis of Parkinson’s disease through the use of machine learning techniques. These results were validated using two external cohorts. We also identified 7 NFRGs that were highly associated with the prognosis and diagnosis of GBM. Patients in the low-risk group had a greater overall survival (OS) than those in the high-risk group. The nomogram generated based on clinical characteristics and risk scores showed strong prognostic prediction ability. The NFRG signature was an independent prognostic predictor for GBM. The low-risk group was more likely to benefit from immunotherapy based on the degree of immune cell infiltration, expression of immune checkpoints (ICs), and predicted response to immunotherapy. In the end, 2 NFRGs (EN1 and LOXL1) were identified as crucial for the development of Parkinson’s disease and the outcome of GBM.Conclusions: Our study revealed that 4 NFRGs are involved in the progression of PD. The 7-NFRGs risk score model can predict the prognosis of GBM patients and help clinicians to classify the GBM patients into high and low risk groups. EN1, and LOXL1 can be used as therapeutic targets for personalized immunotherapy for patients with PD and GBM.

Background: Colorectal cancer is a malignant tumor of the digestive system originating from abnormal cell proliferation in the colon or rectum, often leading to gastrointestinal symptoms and severe health issues. Nucleotide metabolism, which encompasses the synthesis of DNA and RNA, is a pivotal cellular biochemical process that significantly impacts both the progression and therapeutic strategies of colorectal cancer Methods: For single-cell RNA sequencing (scRNA-seq), five functions were employed to calculate scores related to nucleotide metabolism. Cell developmental trajectory analysis and intercellular interaction analysis were utilized to explore the metabolic characteristics and communication patterns of different epithelial cells. These findings were further validated using spatial transcriptome RNA sequencing (stRNA-seq). A risk model was constructed using expression profile data from TCGA and GEO cohorts to optimize clinical decision-making. Key nucleotide metabolism-related genes (NMRGs) were functionally validated by further in vitro experiments. Results: In both scRNA-seq and stRNA-seq, colorectal cancer (CRC) exhibited unique cellular heterogeneity, with myeloid cells and epithelial cells in tumor samples displaying higher nucleotide metabolism scores. Analysis of intercellular communication revealed enhanced signaling pathways and ligand-receptor interactions between epithelial cells with high nucleotide metabolism and fibroblasts. Spatial transcriptome sequencing confirmed elevated nucleotide metabolism states in the core region of tumor tissue. After identifying differentially expressed NMRGs in epithelial cells, a risk prognostic model based on four genes effectively predicted overall survival and immunotherapy outcomes in patients. High-risk group patients exhibited an immunosuppressive microenvironment and relatively poorer prognosis and responses to chemotherapy and immunotherapy. Finally, based on data analysis and a series of cellular functional experiments, ACOX1 and CPT2 were identified as novel therapeutic targets for CRC. Conclusion: In this study, a comprehensive analysis of NMRGs in CRC was conducted using a combination of single-cell sequencing, spatial transcriptome sequencing, and high-throughput data. The prognostic model constructed with NMRGs shows potential as a standalone prognostic marker for colorectal cancer patients and may significantly influence the development of personalized treatment approaches for CRC.

The transcription factor zinc finger E-box binding homeobox 1 (ZEB1) is a critical inducer of epithelial mesenchymal transformation (EMT) and plays a robust role in tumor metastasis. It can promote not only the movement and diffusion of tumor cells but also cell stemness, treatment resistance, tumor metastasis and immune escape. The expression of ZEB1 is strictly regulated by a variety of pretranscriptional and posttranscriptional signaling pathways and molecules. Increasing evidence indicates that protein modifications such as methylation and acetylation of ZEB1 can also affect tumor metastasis. More importantly, ZEB1 induces immunosuppressive cells and chemokines into the tumor microenvironment (TME), leading to the formation of a tumor immunosuppressive microenvironment. This review summarizes the regulatory factors involved in ZEB1 expression and its important role. The areas of research covered in this review contribute to providing new thoughts and new treatment insights for targeted ZEB1 therapy of malignant tumors.

Adoptive T cell therapy has shown great promise in the treatment of solid tumors, which, however, poses a great challenge to obtain autologous tumor-reactive T cells in a cost-effective manner. Here, we present a dynamic tumor immunology-on-a-chip, mimicking immune responses, for achieving the enrichment and expansion of tumor-reactive T cells. Tumor spheroids with uniform size can be generated by seeding tumor cells in hydrogel-embedded micropillar arrays, and could be trapped upon removal of hydrogel. Then, T cells were infused and fully contacted with these tumor spheroids under biomimetic flow conditions provided by herringbone-patterned microgrooves arrays. We found that the tamed tumor-reactive T cells could be fully activated and a rapid clonal proliferation was realized during the cultivation. In addition, these tumor-reactive T cells exhibited a specific and powerful tumor-killing capability in vitro. Thus, the suggested dynamic microfluidic chips with staged structure-transformable properties realize both the producible formation of tumor spheroids and the recapitulation of tumor-immune crosstalk to expand tumor-reactive T cells. These features indicate that the dynamic and reproducible tumor immunology-on-a-chip has potential in the preparation of therapeutic T cell products for clinical cancer immunotherapy.

Pharmacological chemotherapy remains a cornerstone in treating osteosarcoma (OS), where the application of drug combinations not only enhances therapeutic efficacy but also mitigates adverse side effects. However, the absence of an efficient and reliable drug screening platform poses a significant challenge in optimizing these combination therapies. In this study, we introduce a novel OS chip designed to facilitate the high‐throughput and precise evaluation of drug combination efficacy, addressing this critical gap in OS treatment research. Leveraging the precise control of microfluidic electrospray technology, we successfully fabricated core–shell microcarriers (CSMs) encapsulating OS cells with uniform size and monodisperse distribution. Through three‐dimensional culture, OS cell spheroids were efficiently formed within the CSMs, which were subsequently integrated into a microfluidic chip equipped with a concentration gradient generator and cell culture chambers. This innovative platform enables high‐throughput screening of single drugs and diverse drug combinations. Our results demonstrate that this OS‐on‐a‐chip exhibits significant potential for clinical drug screening, offering a robust tool for optimizing therapeutic strategies in OS treatment.

Targeted drug delivery remains pivotal for enhancing therapeutic efficacy in cancer treatment. While nanomedicines harness the enhanced permeability and re