Advancement and Applications of Nanotherapy for Cancer Immune Microenvironment.

Cancer treatment has evolved rapidly due to major advances in tumor immunity research. However, due to the complexity, heterogeneity, and immunosuppressive microenvironment of tumors, the overall efficacy of immunotherapy is only 20%. In recent years, nanoparticles have attracted more attention in the field of cancer immunotherapy because of their remarkable advantages in biocompatibility, precise targeting, and controlled drug delivery. However, the clinical application of nanomedicine also faces many problems concerning biological safety, and the synergistic mechanism of nano-drugs with immunity remains to be elucidated. Our study summarizes the functional characteristics and regulatory mechanisms of nanoparticles in the cancer immune microenvironment and how nanoparticles activate and long-term stimulate innate immunity and adaptive immunity. Finally, the current problems and future development trends regarding the application of nanoparticles are fully discussed and prospected to promote the transformation and application of nanomedicine used in cancer treatment.

Prediction of Tumor Microenvironment Characteristics and Treatment Response in Lung Squamous Cell Carcinoma by Pseudogene OR7E47P-related Immune Genes.

OBJECTIVE: Pseudogenes are initially regarded as nonfunctional genomic sequences, but some pseudogenes regulate tumor initiation and progression by interacting with other genes to modulate their transcriptional activities. Olfactory receptor family 7 subfamily E member 47 pseudogene (OR7E47P) is expressed broadly in lung tissues and has been identified as a positive regulator in the tumor microenvironment (TME) of lung adenocarcinoma (LUAD). This study aimed to elucidate the correlation between OR7E47P and tumor immunity in lung squamous cell carcinoma (LUSC). METHODS: Clinical and molecular information from The Cancer Genome Atlas (TCGA) LUSC cohort was used to identify OR7E47P-related immune genes (ORIGs) by weighted gene correlation network analysis (WGCNA). Based on the ORIGs, 2 OR7E47P clusters were identified using non-negative matrix factorization (NMF) clustering, and the stability of the clustering was tested by an extreme gradient boosting classifier (XGBoost). LASSO-Cox and stepwise regressions were applied to further select prognostic ORIGs and to construct a predictive model (ORPScore) for immunotherapy. The Botling cohorts and 8 immunotherapy cohorts (the Samstein, Braun, Jung, Gide, IMvigor210, Lauss, Van Allen, and Cho cohorts) were included as independent validation cohorts. RESULTS: OR7E47P expression was positively correlated with immune cell infiltration and enrichment of immune-related pathways in LUSC. A total of 57 ORIGs were identified to classify the patients into 2 OR7E47P clusters (Cluster 1 and Cluster 2) with distinct immune, mutation, and stromal programs. Compared to Cluster 1, Cluster 2 had more infiltration by immune and stromal cells, lower mutation rates of driver genes, and higher expression of immune-related proteins. The clustering performed well in the internal and 5 external validation cohorts. Based on the 7 ORIGs (HOPX, STX2, WFS, DUSP22, SLFN13, GGCT, and CCSER2), the ORPScore was constructed to predict the prognosis and the treatment response. In addition, the ORPScore was a better prognostic factor and correlated positively with the immunotherapeutic response in cancer patients. The area under the curve values ranged from 0.584 to 0.805 in the 6 independent immunotherapy cohorts. CONCLUSION: Our study suggests a significant correlation between OR7E47P and TME modulation in LUSC. ORIGs can be applied to molecularly stratify patients, and the ORPScore may serve as a biomarker for clinical decision-making regarding individualized prognostication and immunotherapy.

Bioinformatic and Experimental Analyses Reveal That KIF4A Is a Biomarker of Therapeutic Sensitivity and Predicts Prognosis in Cervical Cancer Patients.

OBJECTIVE: This study aims to investigate the expression, prognostic value, and function of kinesin superfamily 4A (KIF4A) in cervical cancer. METHODS: Cervical cancer cell lines (Hela and SiHa) and TCGA data were used for experimental and bioinformatic analyses. Overall survival (OS) and progression free survival (PFS) were compared between patients with high or low KIF4A expression. Copy number variation (CNV) and somatic mutations of patients were visualized and GISTIC 2.0 was used to identify significantly altered sites. The function of KIF4A was also explored based on transcriptome analysis and validated by experimental methods. Chemotherapeutic and immunotherapeutic benefits were inferred using multiple reference databases and algorithms. RESULTS: Patients with high KIF4A expression had better OS and PFS. KIF4A could inhibit proliferation and migration and induce G1 arrest of cervical cancer cells. Higher CNV load was observed in patients with low KIF4A expression, while the group with low KIF4A expression displayed more significantly altered sites. A total of 13 genes were found to mutate more in the low KIF4A expression group, including NOTCH1 and PUM1. The analysis revealed that low KIF4A expression may indicate an immune escape phenotype, and patients in this group may benefit more from immunotherapy. With respect to chemotherapy, cisplatin and gemcitabine may respond better in patients with high KIF4A expression, while 5-fluorouracil etc. may be responded better in patients with low KIF4A expression CONCLUSION: KIF4A is a tumor suppressor gene in cervical cancer, and it can be used as a prognostic and therapeutic biomarker in cervical cancer.