Reduction of T-Box 15 gene expression in tumor tissue is a prognostic biomarker for patients with hepatocellular carcinoma

Role of T-box genes in cancer, epithelial-mesenchymal transition, and cancer stem cells

Sharing a common DNA binding motif called T-box, transcription factor T-box gene family controls embryonic development and is also involved in cancer progression and metastasis. Cancer metastasis shows therapy resistance and involves complex processes. Among them, epithelial-mesenchymal transition (EMT) triggers cancer cell invasiveness and the acquisition of stemness of cancer cells, called cancer stem cells (CSCs). CSCs are a small fraction of tumor bulk and are capable of self-renewal and tumorsphere formation. Recent progress has highlighted the critical roles of T-box genes in cancer progression, EMT, and CSC function, and such regulatory functions of T-box genes have emerged as potential therapeutic candidates for cancer. Herein we summarize the current understanding of the regulatory mechanisms of T-box genes in cancer, EMT, and CSCs, and discuss the implications of targeting T-box genes as anticancer therapeutics.

Combined DNA Methylation and Transcriptomic Assessments to Determine a Prognostic Model for PD-1-Negative Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) has the highest incidence and mortality of any malignancy in the world. Immunotherapy has been a major breakthrough for HCC treatment, but immune checkpoint inhibitors (ICIs) are effective in only a small percentage of HCC patients. In the present study, we screened programmed cell death protein 1 (PD-1) -negative HCC samples, which are frequently resistant to ICIs, and identified their methylation and transcription characteristics through the assessment of differential gene methylation and gene expression. We also screened for potential targeted therapeutic drugs using the DrugBank database. Finally, we used a LASSO (least absolute shrinkage and selection operator) regression analysis to construct a prognostic model based on three differentially methylated and expressed genes (DMEGs). The results showed that ESTIMATE (Estimation of Stromal and Immune Cells in Malignant Tumors using Expression Data) scores for the tumor samples were significantly lower compared to normal sample ESTIMATE scores. In addition, we identified 31 DMEGs that were able to distinguish PD-1-negative samples from normal samples. A functional enrichment analysis showed that these genes were involved in a variety of tumor-related pathways and immune-related pathways, and the DrugBank screening identified potential therapeutic drugs. Finally, the prognostic model based on three DMEGs (UBD, CD5L, and CD213A2) demonstrated good predictive power for HCC prognosis and was verified using an independent cohort. The present study demonstrated the methylation characteristics of PD-1-negative HCC samples, identified several potential therapeutic drugs, and proposed a prognostic model based on UBD, CD5L, and CD213A2 methylation expression. In conclusion, this work provides an in-depth understanding of methylation in HCC samples that are not sensitive to ICIs.