Identification of Prognostic Biomarkers of Cutaneous Melanoma Based on Analysis of Tumor Mutation Burden

Histopathological Aspects of the Prognostic Factors for Salivary Gland Cancers

Salivary gland cancers (SGCs) are diagnosed using histopathological examination, which significantly contributes to their progression, including lymph node/distant metastasis or local recurrence. In the current World Health Organization (WHO) Classification of Head and Neck Tumors: Salivary Glands (5th edition), malignant and benign epithelial tumors are classified into 21 and 15 tumor types, respectively. All malignant tumors have the potential for lymph node/distant metastasis or local recurrence. In particular, mucoepidermoid carcinoma (MEC), adenoid cystic carcinoma (AdCC), salivary duct carcinoma, salivary carcinoma, not otherwise specified (NOS, formerly known as adenocarcinoma, NOS), myoepithelial carcinoma, epithelial-myoepithelial carcinoma, and carcinoma ex pleomorphic adenoma (PA) are relatively prevalent. High-grade transformation is an important aspect of tumor progression in SGCs. MEC, AdCC, salivary carcinoma, and NOS have a distinct grading system; however, a universal histological grading system for SGCs has not yet been recommended. Conversely, PA is considered benign; nonetheless, it should be cautiously treated to avoid the development of metastasizing/recurrent PA. The aim of this review is to describe the current histopathological aspects of the prognostic factors for SGCs and discuss the genes or molecules used as diagnostic tools that might have treatment target potential in the future.

Pan-cancer analysis of tumor mutation burden sensitive tumors reveals tumor-specific subtypes and hub genes related to immune infiltration

BACKGROUND

High tumor mutation burden (TMB) failed to serve as a favorable prognostic biomarker for immunotherapy across all tumors. This study aimed to explore TMB-sensitive tumors on a pan-cancer level and construct their immune infiltration phenotypes in TMB-high groups.

METHODS

Pan-cancer patients were separated into TMB-high and TMB-low groups based on the median TMB values per tumor. TMB-related genes were identified using differently expressed genes (DEGs) and differently mutated genes (DMGs) between the above two TMB groups. CIBERSORT algorithm was used to estimate the abundance of 22 tumor immune infiltrating cells (TIICs). Consensus clustering analysis was applied to predict molecular subtypes. Cox regression analysis was performed to evaluate the correlations between hub genes and TIICs and immunomodulator genes.

RESULTS

Nine TMB-sensitive tumors were identified by high-frequency of TMB-related genes. A total of 126 tumor-specific hub genes (1 in BLCA, 19 in BRCA, 4 in COAD, 4 in HNSC, 25 in LUAD, 2 in LUSC, 27 in SKCM, 37 in STAD, and 7 UCEC) were identified. In five out of nine TMB-sensitive tumors, the molecular subtypes based on hub gene expression were characterized by TMB values, prognostic values and tumor-specific TIICs levels. In TMB-high groups, hub genes associated immune infiltration phenotypes were constructed with key TIICs and immunomodulators spanning TMB-sensitive tumors.

CONCLUSIONS

Our tumor-specific analysis revealed hub genes associated immune infiltration features may serve as potential therapeutic targets and prognostic markers of immunotherapy, providing the potential underlying mechanism of immune infiltration in TMB-high groups across TMB-sensitive tumors.

A Bioinformatic Analysis: The Overexpression and Prognostic Potential of GPX7 in Lower-Grade Glioma

Purpose

Glutathione peroxidase-7 (GPX7) is a newly discovered non-selenium-containing protein with glutathione peroxidase activity, which mainly protects the organism from oxidative damage and is very important for basic biology studies. This study aims to reveal the expression pattern of GPX7 and its prognosis potential from a pan-cancer perspective.

Methods

Expression levels of GPX7 in human tumor tissues and normal tissues were evaluated using Human Protein Atlas (HPA), the Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx) and UALCAN databases. The prognostic potential of GPX7 for 33 TCGA tumors was evaluated by Kaplan–Meier analysis and Cox regression analysis. Subsequently, the Chinese Glioma Genome Atlas (CGGA) dataset was used to further verify the expression of GPX7 and its prognostic potential in glioma. We explored the correlation between GPX7 and immune infiltration, tumor mutational burden (TMB) and microsatellite instability (MSI). Furthermore, a nomogram lower-grade glioma (LGG) was constructed to verify the prognostic outcome of patients. Finally, the relationship between GPX7 and treatment regimens for LGG was also explored.

Results

GPX7 was overexpressed in multiple tumors. Elevated expression of GPX7 was associated with poor prognosis of LGG patients (OS hazard ratio (HR) = 1.044, P < 0.0001; DFS HR = 1.035, P < 0.0001; PFS HR = 1.045, P < 0.0001). GPX7 was proved to be an independent prognostic factor of LGG through univariate and multivariate Cox analysis. The nomogram confirmed a better predictability (Concordance index (C-index): 0.845; 95% CI, 0.825–0.865). GPX7 was positively correlated with TMB in LGG. GPX7 expression was negatively correlated with half-maximal inhibitory concentration (IC50) of temozolomide (TMZ) (\documentclass[12pt]{minimal} \usepackage{wasysym} \usepackage[substack]{amsmath} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage[mathscr]{eucal} \usepackage{mathrsfs} \DeclareFontFamily{T1}{linotext}{} \DeclareFontShape{T1}{linotext}{m}{n} {linotext }{} \DeclareSymbolFont{linotext}{T1}{linotext}{m}{n} \DeclareSymbolFontAlphabet{\mathLINOTEXT}{linotext} \begin{document} $$\mathord{\buildrel{\lower3pt\hbox{$\scriptscriptstyle\frown$}}\over \rho } $$ \end{document}_spearman= −0.59, P =1.3e-48).

Conclusion

GPX7 was upregulated in multiple tumors, and it was a potential prognostic biomarker in LGG. High-expressed GPX7 can predict the sensitivity of TMZ in LGG patients.