LncRNA SELL/L-selectin Promotes HPV-Positive HNSCC Progression and Drives Fucoidan-Mediated Therapeutic Strategies

Elucidating the role of FOS in modulating the immune microenvironment through fibroblast and myeloid cell regulation in locoregional recurrent HNSCC

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) presents a significant clinical challenge, particularly due to its high propensity for locoregional recurrence. Current research underscores the need to unravel the complex interactions within the tumor microenvironment. This study addresses the critical gap in understanding how FOS modulates the immune landscape in HNSCC, with a focus on its influence on fibroblast and myeloid cell dynamics.

METHODS

Employing a comprehensive approach, we analyzed tissue samples from HNSCC patients and adjacent non-cancerous tissues using bulk RNA sequencing complemented by in-depth bioinformatics analyses, including gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis, and immune infiltration assessment. A pivotal aspect of our research involved dissecting single-cell RNA-seq data from GSE234933 to elucidate the cell-type-specific expression of FOS.

RESULTS

We found that FOS expression varies significantly in different cell populations in the HNSCC tumor microenvironment, especially in fibroblasts and myeloid cells. This expression difference may reflect the different roles of these cells in tumor progression and their impact on the tumor microenvironment.

CONCLUSION

Our results uncover a significant correlation between FOS expression and key immune and hypoxia-related pathways, suggesting its integral role in the tumor microenvironment. These findings not only enhance our understanding of HNSCC pathogenesis but also highlight FOS as a potential therapeutic target. This study marks a significant step towards addressing the urgent need for targeted interventions in HNSCC, particularly in the context of locoregional recurrence.

Cisplatin-based miRNA delivery strategy inspired by the circCPNE1/miR-330-3p pathway for oral squamous cell carcinoma

Circular RNAs (circRNAs) are ideal biomarkers of oral squamous cell carcinoma (OSCC) because of their highly stable closed-loop structure, and they can act as microRNA (miRNA) sponges to regulate OSCC progression. By analyzing clinical samples, we identified circCPNE1, a dysregulated circRNA in OSCC, and its expression level was negatively correlated with the clinical stage of OSCC patients. Gain-of-function assays revealed the tumor-suppressive effect of circCPNE1, which was then identified as a miR-330-3p sponge. MiR-330-3p was recognized as a tumor promoter in multiple studies, consistent with our finding that it could promote the proliferation, migration, and invasion of OSCC cells. These results indicated that selective inhibition of miR-330-3p could be an effective strategy to inhibit OSCC progression. Therefore, we designed cationic polylysine-cisplatin prodrugs to deliver antagomiR-330-3p (a miRNA inhibitory analog) via electrostatic interactions to form PP@miR nanoparticles (NPs). Paratumoral administration results revealed that PP@miR NPs effectively inhibited subcutaneous tumor progression and achieved partial tumor elimination (2/5), which confirmed the critical role of miR-330-3p in OSCC development. These findings provide a new perspective for the development of OSCC treatments.

Using machine learning methods to study the tumour microenvironment and its biomarkers in osteosarcoma metastasis

Background

The long-term prognosis for patients with osteosarcoma (OS) metastasis remains unfavourable, highlighting the urgent need for research that explores potential biomarkers using innovative methodologies.

Methods

This study explored potential biomarkers for OS metastasis by analysing data from the Cancer Genome Atlas Program (TCGA) and Gene Expression Omnibus (GEO) databases. The synthetic minority oversampling technique (SMOTE) was employed to tackle class imbalances, while genes were selected using four feature selection algorithms (Monte Carlo feature selection [MCFS], Borota, minimum-redundancy maximum-relevance [mRMR], and light gradient-boosting machine [LightGBM]) based on the gene expression matrix. Four machine learning (ML) algorithms (support vector machine [SVM], extreme gradient boosting [XGBoost], random forest [RF], and k-nearest neighbours [kNN]) were utilized to determine the optimal number of genes for building the model. Interpretable machine learning (IML) was applied to construct prediction networks, revealing potential relationships among the selected genes. Additionally, enrichment analysis, survival analysis, and immune infiltration were performed on the featured genes.

Results

In DS1, DS2, and DS3, the IML algorithm identified 53, 45, and 46 features, respectively. Using the merged gene set, we obtained a total of 79 interpretable prediction rules for OS metastasis. We subsequently conducted an in-depth investigation on 39 crucial molecules associated with predicting OS metastasis, elucidating their roles within the tumour microenvironment. Importantly, we found that certain genes act as both predictors and differentially expressed genes. Finally, our study unveiled statistically significant differences in survival between the high and low expression groups of TRIP4, S100A9, SELL and SLC11A1, and there was a certain correlation between these genes and 22 various immune cells.

Conclusions

The biomarkers discovered in this study hold significant implications for personalized therapies, potentially enhancing the clinical prognosis of patients with OS.

Opportunities and challenges of fucoidan for tumors therapy

The large-scale collections, screening and discovery of biologically active and pharmacologically significant marine-derived natural products have garnered tremendous attraction. Edible brown algae are rich in fucoidan. Importantly, fucoidan has been reported to inhibit carcinogenesis and metastasis mainly through the regulation of deregulated cell signaling pathways. This review summarizes the structural features of fucoidan, including monosaccharide type, sulfate content, and main chain structure. We have set spotlight on fucoidan-mediated tumor suppressive effects in cell cultures studies and tumor-bearing rodent models. Fucoidan exerts anti-tumor effects primarily through the inhibition of tumor cell viability, proliferation and metastatic dissemination of cancer cells from primary tumor sites to distant secondary sites. Fucoidan not only promotes immunological responses in tumor microenvironment but also induces apoptotic death in cancer cells. In addition, fucoidan can be used as a dietary supplement for preventive purposes, in combination with other drugs as complementary and alternative medicine or with nanoparticle modifications will be the future of fucoidan use. Cutting-edge research related to fucoidan has catalyzed the transition of fucoidan from preclinical studies to different phases of clinical trials. Rationally designed clinical trials for the critical evaluation of fucoidan against different cancers will be valuable to reap full benefits.