Possible Therapeutic Strategy Involving the Purine Synthesis Pathway Regulated by ITK in Tongue Squamous Cell Carcinoma

Machine Learning-Based Integrated Multiomics Characterization of Colorectal Cancer Reveals Distinctive Metabolic Signatures

The metabolic signature identification of colorectal cancer is critical for its early diagnosis and therapeutic approaches that will significantly block cancer progression and improve patient survival. Here, we combined an untargeted metabolic analysis strategy based on internal extractive electrospray ionization mass spectrometry and the machine learning approach to analyze metabolites in 173 pairs of cancer samples and matched normal tissue samples to build robust metabolic signature models for diagnostic purposes. Screening and independent validation of metabolic signatures from colorectal cancers via machine learning methods (Logistic Regression_L1 for feature selection and eXtreme Gradient Boosting for classification) was performed to generate a panel of seven signatures with good diagnostic performance (the accuracy of 87.74%, sensitivity of 85.82%, and specificity of 89.66%). Moreover, seven signatures were evaluated according to their ability to distinguish between cancer and normal tissues, with the metabolic molecule PC (30:0) showing good diagnostic performance. In addition, genes associated with PC (30:0) were identified by multiomics analysis (combining metabolic data with transcriptomic data analysis) and our results showed that PC (30:0) could promote the proliferation of colorectal cancer cell SW480, revealing the correlation between genetic changes and metabolic dysregulation in cancer. Overall, our results reveal potential determinants affecting metabolite dysregulation, paving the way for a mechanistic understanding of altered tissue metabolites in colorectal cancer and design interventions for manipulating the levels of circulating metabolites.

In Vitro and In Vivo Analyses Reveal Tumor-Derived Exosome miR-558 Promotes Angiogenesis in Tongue Squamous Cell Carcinoma by Targeting Heparinase

This study aimed to investigate the role of miR-558 in tumor angiogenesis by targeting heparinase (HPSE) in tongue squamous cell carcinoma (TSCC)-derived exosomes. In the present study, the role of exosome miR-558 in angiogenesis in vitro and in vivo was investigated by cell proliferation, migration, tube formation, subcutaneous tumor formation in mice, and in vivo Matrigel plug assay. The target genes of miR-558 were detected by means of dual luciferase assay. It was found that TSCC cells secrete miR-558 into the extracellular environment, with exosome as the carrier. Human umbilical vein endothelial cells (HUVEC) ingested exosomes, which not only increased the expression level of miR-558, but also enhanced their proliferation, migration, and tube formation functions. In vivo Matrigel plug assay demonstrated that TSCC cell-derived exosome miR-558 promoted neovascularization in vivo. Compared with negative control cells, TSCC cells overexpressing miR-558 formed subcutaneous tumors in nude mice, with larger volume, heavier mass, and more vascularization. Dual luciferase assay confirmed that HPSE was the direct target gene regulated by miR-558. HPSE promoted the proliferation, migration, and tube formation of HUVECs, and the knockout of HPSE could downregulate the pro-angiogenic effect of miR-558. In summary, miR-558 in TSCC exosomes promotes the proliferation, migration, and tube formation of HUVECs by targeting HPSE, and enhancing tumor angiogenesis.

RIOK2 Contributes to Cell Growth and Protein Synthesis in Human Oral Squamous Cell Carcinoma

Ribosomes are responsible for the protein synthesis that maintains cellular homeostasis and is required for the rapid cellular division of cancer cells. However, the role of ribosome biogenesis mediators in the malignant behavior of tongue squamous cell carcinoma (TSCC) is unknown. In this study, we found that the expression of RIOK2, a key enzyme involved in the maturation steps of the pre-40S ribosomal complex, was significantly associated with poorer overall survival in patients with TSCC. Further, multivariate analysis revealed that RIOK2 is an independent prognostic factor (hazard ratio, 3.53; 95% confidence interval, 1.19-10.91). Inhibition of RIOK2 expression by siRNA decreased cell growth and S6 ribosomal protein expression in oral squamous cell carcinoma cell lines. RIOK2 knockdown also led to a significant decrease in the protein synthesis in cancer cells. RIOK2 has potential application as a novel therapeutic target for TSCC treatment.