Integrated analysis of RNA-binding proteins in thyroid cancer

IFIT3: a crucial mediator in innate immunity and tumor progression with therapeutic implications

Interferon-Induced Protein with Tetratricopeptide Repeats 3 (IFIT3) plays a dual role in innate immunity and tumor immunity, functioning as both a viral defense molecule and a regulator of tumor progression. This review explores the mechanisms through which IFIT3 modulates immune responses, including interferon signaling, RIG-I-like receptors, and the NF-κB pathway. IFIT3 facilitates immune evasion and promotes inflammation-mediated tumor growth by regulating immune checkpoints and the tumor microenvironment, its emerging role as a target for cancer immunotherapy opens new avenues for therapeutic strategies. Finally, this paper underscores IFIT3's potential clinical applications in the modulation of tumor immunity, highlighting the need for further research on IFIT3-targeted therapies.

NOLC1 was identified as a tumor suppressor gene in thyroid cancer and correlated with prognosis by bioinformatics

Thyroid cancer (THCA) is the most common endocrine malignancy, mainly affecting women's unilateral glandular lobes. However, for relapsed and distant metastasis of THCA patients, the existing early diagnosis and treatment methods were still insufficient, and a new method was urgently needed to diagnose and treat them. Nucleolar and coiled-body phosphoprotein 1 (NOLC1) was one of the most phosphorylated proteins in the cell, which was located mainly in the nucleolus. In addition, more and more studies have confirmed that NOLC1 plays a crucial role in various pathological processes, such as the occurrence and progression of cancer and viral infection. A previous study showed that NOLC1, as a member of RNA-binding protein, was significantly correlated with the prognosis of THCA patients. However, further exploration of NOLC1 in THCA is limited. To further explore the role of NOLC1 in THCA, we conducted expression and survival prognosis analysis of NOLC1 using multiple databases. We also evaluated the correlation between NOLC1 gene expression and clinical characteristics of THCA patients. Furthermore, we analyzed the relationship between NOLC1 and other genes, followed by enrichment analysis to investigate its metabolic pathways and molecular metabolism processes. Additionally, we examined the association between immune cell infiltration in tumor microenvironment and NOLC1. Notably, through vitro experiments, we confirmed the tumor suppressive effect of NOLC1 on the proliferation and migration of human THCA cells, providing evidence for clinical diagnosis of THCA. Furthermore, we confirmed the tumor suppressive effect of NOLC1 in vivo xenograft assay. To sum up, our results suggest that NOLC1 is a tumor suppressor gene for THCA.

Identification and verification of feature biomarkers associated with immune cells in neonatal sepsis

BACKGROUND

Neonatal sepsis (NS), a life-threatening condition, is characterized by organ dysfunction and is the most common cause of neonatal death. However, the pathogenesis of NS is unclear and the clinical inflammatory markers currently used are not ideal for diagnosis of NS. Thus, exploring the link between immune responses in NS pathogenesis, elucidating the molecular mechanisms involved, and identifying potential therapeutic targets is of great significance in clinical practice. Herein, our study aimed to explore immune-related genes in NS and identify potential diagnostic biomarkers. Datasets for patients with NS and healthy controls were downloaded from the GEO database; GSE69686 and GSE25504 were used as the analysis and validation datasets, respectively. Differentially expressed genes (DEGs) were identified and Gene Set Enrichment Analysis (GSEA) was performed to determine their biological functions. Composition of immune cells was determined and immune-related genes (IRGs) between the two clusters were identified and their metabolic pathways were determined. Key genes with correlation coefficient > 0.5 and p < 0.05 were selected as screening biomarkers. Logistic regression models were constructed based on the selected biomarkers, and the diagnostic models were validated.

RESULTS

Fifty-two DEGs were identified, and GSEA indicated involvement in acute inflammatory response, bacterial detection, and regulation of macrophage activation. Most infiltrating immune cells, including activated CD8 + T cells, were significantly different in patients with NS compared to the healthy controls. Fifty-four IRGs were identified, and GSEA indicated involvement in immune response and macrophage activation and regulation of T cell activation. Diagnostic models of DEGs containing five genes (PROS1, TDRD9, RETN, LOC728401, and METTL7B) and IRG with one gene (NSUN7) constructed using LASSO algorithm were validated using the GPL6947 and GPL13667 subset datasets, respectively. The IRG model outperformed the DEG model. Additionally, statistical analysis suggested that risk scores may be related to gestational age and birth weight, regardless of sex.

CONCLUSIONS

We identified six IRGs as potential diagnostic biomarkers for NS and developed diagnostic models for NS. Our findings provide a new perspective for future research on NS pathogenesis.

Follicular Thyroid Adenoma and Follicular Thyroid Carcinoma-A Common or Distinct Background? Loss of Heterozygosity in Comprehensive Microarray Study

Pre- and postsurgical differentiation between follicular thyroid adenoma (FTA) and follicular thyroid cancer (FTC) represents a significant diagnostic challenge. Furthermore, it remains unclear whether they share a common or distinct background and what the mechanisms underlying follicular thyroid lesions malignancy are. The study aimed to compare FTA and FTC by the comprehensive microarray and to identify recurrent regions of loss of heterozygosity (LOH). We analyzed formalin-fixed paraffin-embedded (FFPE) samples acquired from 32 Caucasian patients diagnosed with FTA (16) and FTC (16). We used the OncoScan™ microarray assay (Affymetrix, USA), using highly multiplexed molecular inversion probes for single nucleotide polymorphism (SNP). The total number of LOH was higher in FTC compared with FTA (18 vs. 15). The most common LOH present in 21 cases, in both FTA (10 cases) and FTC (11 cases), was 16p12.1, which encompasses many cancer-related genes, such as TP53, and was followed by 3p21.31. The only LOH present exclusively in FTA patients (56% vs. 0%) was 11p11.2-p11.12. The alteration which tended to be detected more often in FTC (6 vs. 1 in FTA) was 12q24.11-q24.13 overlapping FOXN4, MYL2, PTPN11 genes. FTA and FTC may share a common genetic background, even though differentiating rearrangements may also be detected.

A metabolism-related gene signature for predicting the prognosis in thyroid carcinoma

Metabolic reprogramming is one of the cancer hallmarks, important for the survival of malignant cells. We investigated the prognostic value of genes associated with metabolism in thyroid carcinoma (THCA). A prognostic risk model of metabolism-related genes (MRGs) was built and tested based on datasets in The Cancer Genome Atlas (TCGA), with univariate Cox regression analysis, LASSO, and multivariate Cox regression analysis. We used Kaplan-Meier (KM) curves, time-dependent receiver operating characteristic curves (ROC), a nomogram, concordance index (C-index) and restricted mean survival (RMS) to assess the performance of the risk model, indicating the splendid predictive performance. We established a three-gene risk model related to metabolism, consisting of PAPSS2, ITPKA, and CYP1A1. The correlation analysis in patients with different risk statuses involved immune infiltration, mutation and therapeutic reaction. We also performed pan-cancer analyses of model genes to predict the mutational value in various cancers. Our metabolism-related risk model had a powerful predictive capability in the prognosis of THCA. This research will provide the fundamental data for further development of prognostic markers and individualized therapy in THCA.