ABSTRACT
Background: Despite significant advances over the past decade, patients diagnosed with advanced colorectal cancer (CRC) continue to face unfavorable prognoses. Recent studies have underscored the pivotal role of lysosomes in tumor development and progression. This led us to postulate and develop a novel lysosomal-centric model for predicting CRC risk and therapeutic response. Methods: CRC tissue samples were sourced from the TCGA database, while lysosome-associated genes were collated from the GSEA database. Differentially expressed lysosome-related genes (DE-LRGs) were discerned by contrasting tumor samples with normal tissue. Based on the expression profile of DE-LRGs, patients were stratified into two distinct clusters. Survival disparities between the clusters were delineated using Kaplan-Meier estimators. For tumor microenvironment assessment, we employed ESTIMATE and ssGSEA. Functional pathway enrichment was ascertained using both GSVA and GSEA. Subsequent uni- and multi-variate Cox regression analyses pinpointed risk-associated DE-LRGs. Leveraging these genes, we constructed a novel risk prediction model and derived risk scores. The model's prognostic capability was externally validated using dataset GSE39084. The mutational landscape across risk categories was evaluated using the Maftools algorithm. The potential efficacy of targeted and immunotherapeutic interventions for each patient cohort was gauged using pRRophetic, CYT, and IMvigor210. Results: We identified 46 DE-LRGs. Tumor Immune MicroEnvironment (TIME) assessment revealed that cluster 2 patients exhibited elevated ESTIMATE, Immunocore, and stromal scores, yet diminished tumor purity relative to cluster 1. Notable differences in immune cell infiltration patterns were observed between clusters, and distinct pathway enrichments were evident. Cluster 2 manifested a pronounced expression of immune checkpoint-related genes. Four DE-LRGs (ATP6V0A4, GLA, IDUA, and SLC11A1) were deemed critical for risk association, leading to the formulation of our novel risk model. The model exhibited commendable predictive accuracy, which was corroborated in an external validation cohort. A palpable survival advantage was observed in high-TMB, low-risk subgroups. Moreover, the low-risk cohort displayed heightened sensitivity to both targeted and immunotherapeutic agents. Conclusion: Our findings underscore the potential of lysosome-associated genes as robust prognostic and therapeutic response markers in CRC patients.
ABSTRACT
Background: Colorectal cancer is one of the most common malignant tumors worldwide. A various of neurotransmitter receptors have been found to be expressed in tumor cells, and the activation of these receptors may promote tumor growth and metastasis. This study aimed to construct a novel neurotransmitter receptor-related genes signature to predict the survival, immune microenvironment, and treatment response of colorectal cancer patients. Methods: RNA-seq and clinical data of colorectal cancer from The Cancer Genome Atlas database and Gene Expression Omnibus were downloaded. Neurotransmitter receptor-related gene were collected from publicly available data sources. The Weighted Gene Coexpression Network Analysis (WGCNA), Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression, Support Vector Machine-Recursive Feature Elimination (SVM-RFE), and Random Forest (RF) algorithms were employed to construct the Neurotransmitter receptor-related gene prognostic signature. Further analyses, functional enrichment, CIBERSORTx, The Tumor Immune Single Cell Center (TISCH), survival analysis, and CellMiner, were performed to analyze immune status and treatment responses. Quantitative real-time polymerase chain reaction (qRT-PCR) assays were carried out to confirm the expression levels of prognostic genes. Results: By combining machine learning algorithm and WGCNA, we identified CHRNA3, GABRD, GRIK3, and GRIK5 as Neurotransmitter receptor-related prognostic genes signature. Functional enrichment analyses showed that these genes were enriched with cellular metabolic-related pathways, such as organic acid, inorganic acid, and lipid metabolism. CIBERSORTx and Single cell analysis showed that the high expression of genes were positively correlated with immunosuppressive cells infiltration, and the genes were mainly expressed in cancer-associated fibroblasts and endothelial cells. A nomogram was further built to predict overall survival (OS). The expression of CHRNA3, GABRD, GRIK3, and GRIK5 in cancer cells significantly impacted their response to chemotherapy. Conclusion: A neurotransmitter receptor-related prognostic gene signature was developed and validated in the current study, giving novel sights of neurotransmitter in predicting the prognostic and improving the treatment of CRC.
ABSTRACT
A multifunctional 'all-in-one' nanocomposite is fabricated using a colloid, template and surface-modification method. This material encompasses magnetic induced target delivery, cell uptake promotion and controlled drug release in one system. The nanocomposite is characterized by scanning electron microscopy, transmission electron microscopy, x-ray diffraction, N(2) adsorption and vibrating sample magnetometry. The prepared material has a diameter of 350-400 nm, a high surface area of 420.29 m(2) g(-1), a pore size of 1.91 nm and a saturation magnetization of 32 emu g(-1). Doxorubicin (DOX) is loaded in mesopores and acid-sensitive blockers are introduced onto the orifices of the mesopores by a Schiff base linker to implement pH-dependent self-release. Folate was also introduced to improve DOX targeted delivery and endocytosis. The linkers remained intact to block pores with ferrocene valves and inhibit the diffusion of DOX at neutral pH. However, in lysosomes of cancer cells, which have a weak acidic pH, hydrolysis of the Schiff base group removes the nanovalves and allows the trapped DOX to be released. These processes are demonstrated by UV-visible absorption spectra, confocal fluorescence microscopy images and methyl thiazolyl tetrazolium assays in vitro, which suggest that the smart nanocomposite successfully integrates targeted drug delivery with internal stimulus induced self-release and is a potentially useful material for nanobiomedicine.
