TBX2 Expression predicts Tumor Recurrence and Adjuvant Chemotherapy Benefits in Gastric Cancer Patients following R0 Resection: a proposed approach for risk stratification

T-box transcription factor 2 mediates antitumor immune response in cutaneous squamous cell carcinoma by regulating the expression of programmed death ligand 1

BACKGROUND

Cutaneous squamous cell carcinoma (CSCC) is the second largest nonmelanoma skin cancer in humans; effective treatment options for metastatic CSCC are still in short. In this study, we aimed to explore the function of T-box transcription factor 2 (TBX2) in CSCC.

METHODS

The expression level of TBX2 was determined in CSCC samples and cell lines. Programmed death ligand 1 (PD-L1) expression was also analyzed in human CSCC samples. Furthermore, SCC13 cells were transfected with TBX2-DN (loss of function) or normal TBX2 to check its role in regulating PD-L1.

RESULTS

The expression level of TBX2 was positively correlated with the stage of CSCC. CSCC tumor cell lines have significantly higher expression levels of TBX2 than normal skin cell lines, and SCC13 cells showed the highest expression. PD-L1 expressions were upregulated during the progression of CSCC, and positively correlated with TBX2. Furthermore, PD-L1 expression increased in SCC13 cells overexpressing TBX2. However, TBX2 did not regulate the activation of IFNγ signal, but mediated the expression of interferon regulatory factor 1 (IRF1) and PD-L1 in both SCC13 and PDV cells.

CONCLUSION

TBX2 could mediate antitumor immune response in CSCC by regulating the expression of PD-L1 through IRF1. It might be a prognostic marker in CSCC and synergistic target for PD-1 immunotherapy.

Construction and Validation of a Novel Immunosignature for Overall Survival in Uveal Melanoma

Objectives

Uveal melanoma (UM) is the most common primary intraocular malignancy in adults, and immune infiltration plays a crucial role in the prognosis of UM. This study aimed to generate an immunological marker-based predictive signature for the overall survival (OS) of UM patients.

Methods

Single-sample gene-set enrichment analysis (ssGSEA) was used to profile immune cell infiltration in 79 patients with UM from The Cancer Genome Atlas (TCGA) database. Univariate and multivariate least absolute shrinkage and selection operator (LASSO) Cox regressions were used to determine the prognostic factors for UM and construct the predictive immunosignature. Receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and calibration curves were performed to evaluate the clinical ability and accuracy of the model. In addition, the predictive accuracy was compared between the immunosignature and the Tumor, Node, Metastasis (TNM) staging system of American Joint Committee on Cancer (AJCC). We further analyzed the differences in clinical characteristics, immune infiltrates, immune checkpoints, and therapy sensitivity between high- and low-risk groups characterized by the prognostic model.

Results

Higher levels of immune cell infiltration in UM were related to a lower survival rate. Matrix metallopeptidase 12 (MMP12), TCDD inducible poly (ADP-ribose) polymerase (TIPARP), and leucine rich repeat neuronal 3 (LRRN3) were identified as prognostic signatures, and an immunological marker-based prognostic signature was constructed with good clinical ability and accuracy. The immunosignature was developed with a concordance index (C-index) of 0.881, which is significantly better than that of the TNM staging system (p < 0.001). We further identified 1,762 genes with upregulated expression and 798 genes with downregulated expression in the high-risk group, and the differences between the high- and low-risk groups were mainly in immune-related processes. In addition, the expression of most of the immune checkpoint-relevant and immune activity-relevant genes was significantly higher in the high-risk group, which was more sensitive to therapy.

Conclusion

We developed a novel immunosignature constructed by MMP12, TIPARP, and LRRN3 that could effectively predict the OS of UM.