The Emerging Roles and Mechanisms of PAQR3 in Human Cancer: Pathophysiology and Therapeutic Implications.

Cancer was one of the common causes of death in the world, and it was increasing year by year. At present, Progestin and AdipoQ receptor family member 3 (PAQR3) was widely studied in cancer. It has been found that PAQR3 was down regulated in various cancers, such as the gastric cancer, osteosarcoma, glioma, hepatocellular carcinoma, acute lymphoblastic leukemia, laryngeal squamous cell carcinoma, esophageal cancer, breast cancer, non-small cell lung cancer, and colorectal cancer. The decreased expression of PAQR3 was associated with short overall survival and disease-free survival in patients with gastric cancer, hepatocellular carcinoma, laryngeal squamous cell carcinoma, esophageal cancer, breast cancer, and non-small cell lung cancer. PAQR3 could inhibit cancer progression by using the Ras/Raf/MEK/ERK, PI3/AKT, EMT and other mechanisms, and was negatively regulated by the miR-543, miR-15b-5p and miR-15b. The roles and signaling mechanisms of PAQR3, and the relationship between the expression of PAQR3 and prognosis in cancer progression are reviewed in this article, and provides new tumor marker and idea to guide cancer treatment.

Overexpression of TWF1 promotes lung adenocarcinoma progression and is associated with poor prognosis in cancer patients through the MMP1 signaling pathway.

Background: It has been reported that twinfilin actin binding protein 1 (TWF1) is associated with the progression of breast and pancreatic cancers. However, the roles and mechanisms of TWF1 in lung adenocarcinoma (LUAD) have not been reported. Methods: The expression levels of TWF1 in LUAD and normal tissues were analyzed using The Cancer Genome Atlas (TCGA) database, and validation was carried out with 12 clinical samples. The relationship between TWF1 expression and LUAD patients' clinical indices and immunity was investigated. Cell Counting Kit-8 (CCK-8) and migration and invasion assays were employed to explore the effects of downregulated TWF1 on LUAD cell proliferation and metastasis. Results: TWF1 was upregulated in LUAD tissues, and upregulated TWF1 was correlated with the tumor (T) stage, node (N) stage, clinical classification, overall survival (OS), and progression-free interval (PFI) of LUAD patients. Moreover, the Cox regression analysis showed that TWF1 overexpression was an independent risk factor for the poor prognosis of LUAD patients. TWF1 expression was associated with tumor immune infiltration (such as dendritic cells resting, eosinophils, macrophages M0, and others), drug sensitivity (such as A-770041, Bleomycin, and BEZ235), tumor mutation burden (TMB), and sensitivity to immunotherapy. In the cell model, TWF1 expression interference significantly prohibited LUAD cell proliferation, migration, and invasion, which might be relevant to aberrant MMP1 protein downregulation. Conclusions: TWF1 overexpression was correlated with poor prognoses and immune status of LUAD patients. Inhibited TWF1 expression delayed the growth and migration of cancer cells by downregulating MMP protein, implying that TWF1 is a promising biomarker for the prognoses of LUAD patients.

A new prognostic model for RHOV, ABCC2, and CYP4B1 to predict the prognosis and association with immune infiltration of lung adenocarcinoma.

Background: Lymph node metastasis is one of the important factors affecting the prognosis of lung adenocarcinoma (LUAD) patients. The key molecules in lymph node metastasis have not yet been fully revealed. Therefore, we aimed to construct a prognostic model based on lymph node metastasis-related genes to evaluate the prognosis of LUAD patients. Methods: The differentially expressed genes (DEGs) in the process of LUAD metastasis were identified in The Cancer Genome Atlas (TCGA) database, and the biological roles of the DEGs were depicted using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and a protein-protein interaction (PPI) network. Survival analysis and Cox regression analysis were used to identify the genes related to the prognosis of patients with LUAD, and a nomogram and a prognostic model were constructed. The potential prognostic value, immune escape, and regulatory mechanisms of the prognostic model in LUAD progression were explored through survival analysis and gene set enrichment analysis (GSEA). Results: A total of 75 genes were upregulated, and 138 genes were downregulated in tissues of lymph node metastasis. The expression levels of STC1, CYP17A1, RHOV, GUCA2B, TM4SF20, DEFB1, CRHR2, ABCC2, CYP4B1, KRT16, and NTS were revealed as risk factors for a poor prognosis in LUAD patients. High-risk LUAD patients had a poor prognosis in the prognostic model based on RHOV, ABCC2, and CYP4B1. The clinical stage and the risk score were found to be independent risk factors for a poor prognosis in LUAD patients, and the risk score was associated with the tumor purity, T cell, natural killer (NK) cell, and other immune cells. The prognostic model might affect the progression of LUAD using DNA replication, the cell cycle, P53, and other signaling pathways. Conclusions: Lymph node metastasis-related genes RHOV, ABCC2, and CYP4B1 are associated with a poor prognosis in LUAD. A prognostic model based on RHOV, ABCC2, and CYP4B1 might predict the prognosis of LUAD patients and be associated with immune infiltration.

Evaluation of clinical value and potential mechanism of MTFR2 in lung adenocarcinoma via bioinformatics.

BACKGROUND: Mitochondrial fission regulator 2 (MTFR2) was involved in the progression and development of various cancers. However, the relationship between MTFR2 with lung adenocarcinoma (LUAD) had not been reported. Herein, this study analyzed the clinical significance and potential mechanisms of MTFR2 in LUAD via bioinformatics tools. RESULTS: We found that the level of MTFR2 was increased, and correlated with sex, age, smoking history, neoplasm staging, histological subtype and TP53 mutation status in LUAD patients. Kaplan-Meier survival analysis showed LUAD patients with increased MTFR2 had a poor prognosis. In addition, univariate COX regression analysis showed neoplasm staging, T stage, distant metastasis and MTFR2 level were risk factors for the prognosis of LUAD. A total of 1127 genes were coexpressed with MTFR2, including 840 positive and 208 negative related genes. KEGG and GSEA found that MTFR2 participated in the progression of LUAD by affecting cell cycle, DNA replication, homologous recombination, p53 signaling pathway and other mechanisms. The top 10 coexpressed genes, namely CDK1, CDC20, CCNB1, PLK1, CCNA2, AURKB, CCNB2, BUB1B, MAD2L1 and BUB1 were highly expressed, and were associated with poor prognosis in LUAD. CONCLUSIONS: Consequently, we elucidated MTFR2 was a biomarker for diagnosis and poor prognosis in LUAD, and might participate in the progression of LUAD via affecting cell cycle, DNA replication, homologous recombination and p53 signaling pathway.

PAQR3 Inhibits Non-small Cell Lung Cancer Growth by Regulating the NF-κB/p53/Bax Axis.

BACKGROUND: The expression of progestin and adipoQ receptor 3 (PAQR3) is generally downregulated in multiple tumors, which is associated with tumor progression and poor prognosis. METHODS: The clinical value of PAQR3 was analyzed using various databases and in 60 patients with non-small cell lung cancer (NSCLC). In addition, cell counting kit-8 (CCK-8), colony formation, and flow cytometry assays were used to evaluate the effect of PAQR3 on the growth of NSCLC cells in vitro. Gene set enrichment analysis (GSEA) was performed to investigate the possible mechanism through which PAQR3 is involved in the progression of lung cancer. Furthermore, western blotting was employed to verify the relevant mechanism. RESULTS: The expression of PAQR3 was decreased in 60 NSCLC patients and was related to the histological subtype, lymph node metastasis, tumor size, and diagnosis of NSCLC. Patients with lung adenocarcinoma with increased PAQR3 expression tended to have a better prognosis. Besides, PAQR3 inhibited proliferation, clone formation, and cycle transition in NSCLC cells, but induced apoptosis. The results of GSEA showed that PAQR3 regulated the progression of lung cancer by affecting cell cycle, DNA replication, and the p53 signaling pathway. We confirmed that PAQR3 overexpression inhibited the expression of NF-κB, while it increased the expression of p53, phospho-p53, and Bax. On the contrary, PAQR3 inhibition played an opposite role in these proteins. CONCLUSION: PAQR3 inhibited the growth of NSCLC cells through the NF-κB/P53/Bax signaling pathway and might be a new target for diagnosis and treatment.

High lncSNHG15 expression may predict poor cancer prognosis: a meta-analysis based on the PRISMA and the bio-informatics analysis.

BACKGROUND: SNHG15 has been reported to be aberrantly expressed in various tumor tissues and could serve as a promising prognostic cancer biomarker. Previous studies on SNHG15 yielded inconsistent results with insufficient sampling. Here, a meta-analysis was conducted to investigate the prognostic value of SNHG15 in multiple cancers. METHODS: Relevant studies were retrieved from six electronic databases including PubMed, Cochrane Library, Google Scholar, Embase, Web of Science and China National Knowledge Infrastructure (CNKI). Fifteen publications comprising 1318 patients were included. The publication bias was identified by the Begg's Test, and the sensitivity analysis was also performed. RESULTS: The results demonstrated a positive correlation between high expression level of lncSNHG15 and short overall survival (hazard ratio (HR) = 2.07, 95% confidence interval (CI), 1.48-2.88; P<0.0001) and disease-free survival (DFS) (HR = 2.32, 95% CI, 1.53-3.53; P<0.0001). The analysis based on different cancer types showed that SNHG15 had the most prominent prognostic potential in Glioma (HR = 3.81; 95% CI, 0.84-42.69; P=0.28). Moreover, the high expression level of lncSNHG15 indicated advanced TNM stage (OR = 2.52; 95% CI, 1.33-4.76; P=0.00001), lymph node metastasis (OR = 2.41, 95% CI, 0.99-4.81; P=0.05), bigger tumor size (OR = 2.06; 95% CI, 1.03-4.13; P=0.04) and poor histological grade (OR = 2.62, 95% CI, 1.90-3.59; P<0.00001), yet no association with distant metastasis (OR = 1.64, 95% CI, 0.40-6.74; P=0.49), age (OR = 0.98, 95% CI, 0.78-1.22; P=0.84) and gender (OR = 0.9, 95% CI, 0.71-1.14; P=0.3838) was found. Its conclusions further confirmed by exploring TCGA databases. CONCLUSION: It revealed that lncSNHG15 might be a promising prognostic biomarker of multiple cancer types, especially in Glioma.

Evaluation of the Prognostic Value of STEAP1 in Lung Adenocarcinoma and Insights Into Its Potential Molecular Pathways via Bioinformatic Analysis.

BACKGROUND: Upregulation of the six-transmembrane epithelial antigen of prostate-1 (STEAP1) is closely associated with prognosis of numerous malignant cancers. However, its role in lung adenocarcinoma (LUAD), the most common type of lung cancer, remains unknown. This study aimed to investigate the role of STEAP1 in the occurrence and progression of LUAD and the potential mechanisms underlying its regulatory effects. METHODS: STEAP1 mRNA and protein expression were analyzed in 40 LUAD patients via real-time PCR and western blotting, respectively. We accessed the clinical data of 522 LUAD patients from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) to investigate the expression and prognostic role of STEAP1 in LUAD. Further, we performed gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and gene set enrichment analysis (GSEA) to elucidate the potential mechanism underlying the role of STEAP1 in LUAD. The protein-protein interaction (PPI) network of STEAP1 was analyzed using the Search Tool for the Retrieval of Interacting Genes (STRING) database, and hub genes with significant positive and negative associations with STEAP1 were identified and their role in LUAD prognosis was predicted. RESULTS: STEAP1 was significantly upregulated in LUAD patients and associated with LUAD prognosis. Further, TCGA data indicated that STEAP1 upregulation is correlated with the clinical prognosis of LUAD. GO and KEGG analysis revealed that the genes co-expressed with STEAP1 were primarily involved in cell division, DNA replication, cell cycle, apoptosis, cytokine signaling, NF-kB signaling, and TNF signaling. GSEA revealed that homologous recombination, p53 signaling pathway, cell cycle, DNA replication, apoptosis, and toll-like receptor signaling were highly enriched upon STEAP1 upregulation. Gene Expression Profiling Interactive Analysis (GEPIA) analysis revealed that the top 10 hub genes associated with STEAP1 expression were also associated with the LUAD prognosis. CONCLUSION: STEAP1 upregulation potentially influences the occurrence and progression of LUAD and its co-expressed genes via regulation of homologous recombination, p53 signaling, cell cycle, DNA replication, and apoptosis. STEAP1 is a potential prognostic biomarker for LUAD.