Macrophages are key innate immune cells in the tumor microenvironment that regulate primary tumor growth, vascularization, metastatic spread and response to therapies. Macrophages can polarize into two different states (M1 and M2) with distinct phenotypes and functions. To investigate the known tumoricidal effects of M1 macrophages, we obtained RNA expression profiles and clinical data from The Cancer Genome Atlas Thyroid Cancer (TCGA-THCA). The proportions of immune cells in tumor samples were assessed using CIBERSORT, and weighted gene co-expression network analysis (WGCNA) was used to identify M1 macrophage-related modules. Univariate Cox analysis and LASSO-Cox regression analysis were performed, and four genes (SPP1, DHRS3, SLC11A1, and CFB) with significant differential expression were selected through GEPIA. These four genes can be considered hub genes. The four-gene risk-scoring model may be an independent prognostic factor for THCA patients. The validation cohort and the entire cohort confirmed the results. Univariate and multivariate Cox analysis was performed to identify independent prognostic factors for THCA. Finally, a prognostic nomogram was built based on the entire cohort, and the nomogram combining the risk score and clinical prognostic factors was superior to the nomogram with individual clinical prognostic factors in predicting overall survival. Time-dependent ROC curves and DCA confirmed that the combined nomogram is useful. Gene set enrichment analysis (GSEA) was used to elucidate the potential molecular functions of the high-risk group. Our study identified four genes associated with M1 macrophages and established a prognostic nomogram that predicts overall survival for patients with THCA, which may help determine clinical treatment options for different patients.

Papillary thyroid cancer (PTC) is one of the most common malignant tumors in female, and estrogen can affect its progression. However, the targets and mechanisms of estrogen action in PTC remain unclear. Therefore, this study focuses on the relationship between estrogen-related genes (ERGs) expression and prognosis in PTC, particularly neuropeptide U (NMU), and its important role in tumor progression. Based on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, differentially expressed genes (DEGs) predominantly enriched in ERGs were identified between PTC and normal tissue. Then, we identified ERGs that contributed most to PTC prognosis, including Transducer of ERBB2 1 (TOB1), trefoil factor 1 (TFF1), phospholipase A and acyltransferase 3 (PLAAT3), NMU, kinesin family member 20A (KIF20A), DNA topoisomerase II alpha (TOP2A), tetraspanin 13 (TSPAN13), and carboxypeptidase E (CPE). In addition, we confirmed that NMU was highly expressed in PTC and explored the effect of NMU on PTC cells proliferation in vitro and in vivo . The results showed that the proliferative capacity of PTC cells was significantly reduced with NMU knockdown. Moreover, the phosphorylation levels of the Kirsten rat sarcoma virus (KRAS) signaling pathway were significantly lower with NMU knockdown. These results suggest that ERGs, especially NMU, may be novel prognostic indicators in PTC.

Papillary thyroid cancer (PTC) is one of the most common malignant tumors in female, and estrogen can affect its progression. However, the targets and mechanisms of estrogen action in PTC remain unclear. Therefore, this study focuses on the relationship between estrogen-related genes (ERGs) expression and prognosis in PTC, particularly neuropeptide U (NMU), and its important role in the development of PTC. We first downloaded expression data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases for PTC and normal tissue and identified differentially expressed genes (DEGs), which were predominantly enriched for ERGs. Then, we identified ERGs that contributed most to PTC prognosis based on univariate Cox regression and Lasso Cox analysis. We filtered out Transducer of ERBB2 1 (TOB1), trefoil factor 1 (TFF1), phospholipase A and acyltransferase 3 (PLAAT3), NMU, kinesin family member 20A (KIF20A), DNA topoisomerase II alpha (TOP2A), tetraspanin 13 (TSPAN13), and carboxypeptidase E (CPE). In addition, we explored the effect of NMU on the proliferation of PTC cells by in vitro experiments, confirmed high NMU expression in PTC and showed that the proliferative capacity of PTC cells was significantly reduced with NMU knockdown. Moreover, the phosphorylation levels of the Kirsten rat sarcoma virus (KRAS) signaling pathway were significantly lower with NMU knockdown. These results suggest that ERGs, especially NMU, may be novel prognostic indicators in PTC.

Background Head and neck squamous cell carcinoma (HNSCC) is a common malignant tumor., and incidence and mortality of HNSCC are relatively high. Most HNSCC patients are diagnosed at an advanced stage and lack specific treatment. There is an urgent need to identify new molecular markers for prognostic evaluation. It is well known that N6-methyladenosine (m6A) RNA modification plays a critical role in a variety of tumors, especially HNSCC. However, the relationship between the m6A “writer”, METTL3, and the prognosis of HNSCC remains unknown. The present study aimed to evaluate the potential roles and prognostic value of METTL3 in HNSCC. Methods A total of 448 HNSCC samples with clinical information obtained from The Cancer Genome Atlas (TCGA) datasets and 72 HNSCC samples from Gene Expression Omnibus (GEO) datasets were analyzed. The expression of METTL3 across cancers was analyzed with the TIMER database. Univariate and multivariate Cox regression analyses were used to determine the independent prognostic factors for HNSCC. The Kaplan–Meier method was used for survival analysis. Differential expression analysis of METTL3-related genes was performed with DESeq2. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to identify the potential role of METTL3-related genes in HNSCC. The TIMER database was used to analyze the association between METTL3 expression and the infiltration levels of immune cell. Immunohistochemistry was used to verify the relationship between METTL3 expression and immune cells infiltration. Results METTL3 expression was significantly upregulated in HNSCC (P < 0.001), and HNSCC patients had a better prognosis when METTL3 was significantly upregulated. Low METTL3 expression in HNSCC patients over 60 years old was associated with poor prognosis (P = 0.0062) with the most significant result for laryngeal carcinoma patients (P < 0.0001). Additionally, METTL3 expression led to changes in the tumor immune microenvironment. We found that the high expression of METTL3 had a positive correlation with CD4 + T cells and neutrophils but a negative correlation with B cells, CD8 + T cells, macrophages, and dendritic cells. IHC assays further confirmed this conclusion. In addition to oral cancer, METTL3 was positively correlated with CD4 expression in laryngeal and tongue cancers (P < 0.05). Finally, we constructed a prognostic nomogram in HNSCC to predict the individuals’ survival probability by age, stage, T stage, N stage, M stage, and grade. Calibration was performed for the nomogram, and the calibration curves showed that the nomogram-predicted probability matched the observed line for the 1-, 3-, and 5-year survival. Conclusion The present study found that upregulated METTL3 recruits CD4 + T cells around the tumor, reshapes the immune microenvironment and enables prolonged survival. In conclusion, METTL3, as an independent factor affecting the prognosis of HNSCC, may become a novel biomarker for HNSCC, playing a role in regulating the tumor immune response.

N6-methyladenosine (m6A) is one of the most common post-transcriptional modifications of eukaryotic mRNA, accounting for approximately 80% of RNA methylation modifications. Increasing studies have demonstrated that m6A modification has an important role in the development of a variety of tumors. Insulin-like growth factor 2 (IGF2BP2), as an important methylation recognition proteins in the process of m6A modification, is similarly involved in the progression of human cancers. Therefore, based on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets, we first explored the potential oncogenic role of IGF2BP2 in thirty-three tumors and found that IGF2BP2 was highly expressed in most cancers, and it is also strongly associated with poor prognosis in some tumor patients. We performed the first pan-cancer analysis of the m6A methylation recognition protein IGF2BP2with the main goal of gaining a more comprehensive understanding of the oncogenic role of IGF2BP2 in different tumors.