环境肿瘤学研究方法进展

环境肿瘤学作为一门新兴的交叉学科,采用多学科交叉融合的方法,研究肿瘤的环境因素,为肿瘤防控提供科学依据。本文系统介绍环境流行病学、临床环境流行病学和实验室研究等常用研究方法;详细阐述分子流行病学、高通量组学和基因环境交互作用研究等新兴研究方法;探讨大数据与人工智能对环境肿瘤学研究的价值;强调了环境致癌风险评价、地理信息系统和遥感技术对环境暴露研究的作用;指出了环境肿瘤学研究方法未来的发展方向和挑战。

环境肿瘤学的发展及现状

全球肿瘤发病趋势表明,肿瘤将成为所有国家的主要死亡原因,对21世纪人类健康构成重大威胁^([1])。2021年,世界卫生组织国际肿瘤研究机构(International Agency for Research on Cancer,IARC)发布报告指出,2020年全球肿瘤负担上升至1930万新发病例和1000万死亡病例。2020年,中国约有457万新发肿瘤病例,300万人死于肿瘤,其中肺癌新发病和死亡人数占比最高,肿瘤也成为死亡的首要原因^([2])。全球和中国的肿瘤发病率和死亡率均存在明显的地区差异,可能与环境因素有关^([3])。

Prognositic value of anoikis and tumor immune microenvironment-related gene in the treatment of osteosarcoma

Objective:Osteosarcoma is a highly aggressive primary malignant bone tumor commonly seen in children and adolescents,with a poor prognosis.Anchorage-dependent cell death(anoikis)has been proven to be indispensable in tumor metastasis,regulating the migration and adhesion of tumor cells at the primary site.However,as a type of programmed cell death,anoikis is rarely studied in osteosarcoma,especially in the tumor immune microenvironment.This study aims to clarify prognostic value of anoikis and tumor immune microenvironment-related gene in the treatment of osteosarcoma.Methods:Anoikis-related genes(ANRGs)were obtained from GeneCards.Clinical information and ANRGs expression profiles of osteosarcoma patients were sourced from the therapeutically applicable research to generate effective therapies and Gene Expression Omnibus(GEO)databases.ANRGs highly associated with tumor immune microenvironment were identified by the estimate package and the weighted gene coexpression network analysis(WGCNA)algorithm.Machine learning algorithms were performed to construct long-term survival predictive strategy,each sample was divided into high-risk and low-risk subgroups,which was further verified in the GEO cohort.Finally,based on single-cell RNA-seq from the GEO database,analysis was done on the function of signature genes in the osteosarcoma tumor microenvironment.Results:A total of 51 hub ANRGs closely associated with the tumor microenvironment were identified,from which 3 genes(MERTK,BNIP3,S100A8)were selected to construct the prognostic model.Significant differences in immune cell activation and immune-related signaling pathways were observed between the high-risk and low-risk groups based on tumor microenvironment analysis(all P<0.05).Additionally,characteristic genes within the osteosarcoma microenvironment were identified in regulation of intercellular crosstalk through the GAS6-MERTK signaling pathway.Conclusion:The prognostic model based on ANRGs and tumor microenvironment demonstrate good predictive power and provide more personalized treatment options for patients with osteosarcoma.

Janus γ-Fe2O3/SiO2-based nanotheranostics for dual-modal imaging and enhanced synergistic cancer starvation/chemodynamic therapy

Multimodal cancer synergistic therapy exhibited remarkable advantages over monotherapy in producing an improved therapeutic efficacy. In this work, Janus-type γ-Fe2 O3/SiO2 nanoparticles(JFSNs) are conjugated with glucose oxidase(GOx) for synergistic cancer starvation/chemodynamic therapy. The γ-Fe2O3 hemisphere of JFSNs can perform photoacoustic/T2 magnetic resonance dual-modal imaging of tumors.GOx on the surface of JFSNs catalyzes the decomposition of glucose and produces H2O2 for cancer starvation therapy. Subsequently, the γ-Fe2O3 hemisphere catalyzes the disproportionation of H2O2 to generate highly reactive hydroxyl radicals in an acidic tumor microenvironment. The close distance between GOx and JFSNs ensures adequate contact between the γ-Fe2O3 hemisphere and its substrate H2O2, thus enhancing the catalytic efficiency. This synergy of glucose depletion, biotoxic H2O2 and hydroxyl radicals significantly suppresses 4 T1 mammary tumor growth with minimal adverse effects.