FMO1 gene expression independently predicts favorable recurrence-free survival of classical papillary thyroid cancer

PCDH8 is a novel prognostic biomarker in thyroid cancer and promotes cell proliferation and viability

Protocadherin 8 (PCDH8), a calcium-dependent transmembrane protein in the protocadherin family, regulates cell adhesion and signal transduction. While some studies have provided indirect evidence that PCDH8 has cancer-promoting properties, this association is controversial. In particular, its involvement in thyroid cancer (THCA) remains unclear. We aimed to elucidate the role of PCDH8 in THCA using bioinformatic analysis. Subsequently, the results were experimentally validated. The analysis conducted using the R programming language and online web tools explored PCDH8 expression levels, prognostic, and clinical implications, and its relationship with the tumor immune microenvironment in THCA. Furthermore, we examined the association between PCDH8 and co-expressed genes, highlighting their involvement in several biological processes relevant to THCA. The potential of PCDH8 as a therapeutic target for this pathology was also explored. Immunohistochemical (IHC) staining was performed on samples from 98 patients with THCA, and experimental validation was carried out. PCDH8 was significantly elevated in cancer tissues and associated with poor prognosis, several clinical factors, and immune cell and checkpoint abundance. Cox regression and survival analyses, together with Receiver Operating Curves (ROC) indicated that PCDH8 was an independent prognostic factor for THCA. Furthermore, PCDH8 impacts cell viability and proliferation, promoting tumorigenesis. Also, it influences tumor cell sensitivity to various drugs. Thus, PCDH8 might be a potential therapeutic target for THCA. IHC, cell culture, MTT, and colony formation experiments further confirmed our findings. This analysis provided insights into the potential carcinogenic role of PCDH8 in THCA, as it impacts cell viability and proliferation. Thus, PCDH8 might play an important role in its prognosis, immune infiltration, and diagnosis.

FMO family may serve as novel marker and potential therapeutic target for the peritoneal metastasis in gastric cancer

Objective

To explore the relationship between flavin-containing monooxygenases (FMOs) and peritoneal metastasis (PM) in gastric cancer (GC).

Materials and methods

TIMER 2.0 was used to perform pan-cancer analysis and assess the correlation between the expression of FMOs and cancers. A dataset from The Cancer Genome Atlas (TCGA) was used to analyze the correlation between FMOs and clinicopathological features of GC. PM is well established as the most common mode of metastasis in GC. To further analyze the correlation between FMOs and PM of GC, a dataset was obtained from the National Center for Biotechnology Information Gene Expression Omnibus (GEO) database. The results were validated by immunohistochemistry. The relationship between FMOs and PM of GC was explored, and a novel PM risk signature was constructed by least absolute shrinkage and selection operator (LASSO) regression analysis. The regression model's validity was tested by multisampling. A nomogram was established based on the model for predicting PM in GC patients. The mechanism of FMOs in GC patients presenting with PM was assessed by conducting Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses in TCGA and GEO datasets. Finally, the potential relationship between FMOs and immunotherapy was analyzed.

Results

The pan-cancer analysis in TCGA and GEO datasets showed that FMO1 was upregulated, while FMO2 and FMO4 were downregulated in GC. Moreover, FMO1 and FMO2 correlated positively with the T and N stage of GC in the TCGA dataset. FMO1 and FMO2 expression was a risk factor for GC (hazard ratio: 1.112 and 1.185). The overexpression of FMO1 was significantly correlated with worse disease-free-survival (DFS) and overall survival (OS). However, no relationship was found between FMO2 expression in GC and DFS and OS. PM was highly prevalent among GC patients and typically associated with a worse prognosis. FMO1 was highly expressed in GC with PM. FMO1 and FMO2 were positively correlated with PM in GC. We identified a 12-gene panel for predicting the PM risk signature by LASSO (Area Under Curve (AUC) = 0.948, 95%CI: 0.896-1.000). A 10-gene panel for PM prediction was identified (AUC = 0.932, 95%CI: 0.874-0.990), comprising FMO1 and FMO2. To establish a model for clinical application, a 7-gene panel was established (AUC = 0.927, 95% CI: 0.877-0.977) and successfully validated by multisampling. (AUC = 0.892, 95% CI: 0.878-0.906). GO and KEGG analyses suggest that FMO1 and FMO2 regulate the extracellular matrix and cell adhesion. FMO1 and FMO2 were positively correlated with the immune score of GC, and their expression was associated with the infiltration of immune cells.

Conclusion

PM in GC is strongly correlated with FMOs. Overall, FMO1 and FMO2 have huge prospects for application as novel diagnostic and therapeutic targets.

Glutathione peroxidase 4 inhibition induces ferroptosis and mTOR pathway suppression in thyroid cancer

Papillary thyroid carcinoma (PTC) demonstrates significantly reduced patient survival with metastatic progression. Tumor progression can be influenced by metabolism, including antioxidant glutathione (GSH). Glutathione peroxidase 4 (GPX4) is a selenoenzyme that uses GSH as a co-factor to regulate lipid peroxidation of cell membranes during increased oxidative stress. GPX4 suppression in tumor cells can induce ferroptosis. This study aims to examine ferroptosis as a potentially critical pathway in effective targeting of thyroid cancer (TC) cells. We treated human TC cells (K1, MDA-T68, MDA-T32, TPC1) with (1S,3R)-RSL3 (RSL3), a small-molecule inhibitor of GPX4 and examined the effects on ferroptosis, tumor cell survival and migration, spheroid formation, oxidative stress, DNA damage repair response, and mTOR signaling pathway in vitro. GPX4 inhibition activated ferroptosis, inducing TC cell death, rapid rise in reactive oxygen species and effectively arrested cell migration in vitro. Suppression of mTOR signaling pathway triggered autophagy. GPX4 genetic knockdown mirrored RSL3 effect on mTOR pathway suppression. RSL3 subdued DNA damage repair response by suppressing phosphorylation of nucleophosmin 1 (NPM1). Thus, observed potent induction of ferroptosis, GPX4-dependent novel suppression of mTOR pathway and DNA damage repair response in preclinical in vitro model of TC supports GPX4 targeting for therapeutic benefit in advanced therapy-resistant thyroid cancers.

F12 as a reliable diagnostic and prognostic biomarker associated with immune infiltration in papillary thyroid cancer

Objective: To explore the function of coagulation factor XII (F12) in papillary thyroid cancer (PTC).

Materials and Methods: We assessed F12 expression and its relationship with overall survival (OS) in various cancers using TIMER and TISIDB databases. Further, we evaluated the mRNA and protein expression levels of F12 in PTC via different bioinformatics tools. The receiver operating characteristic (ROC) curve was applied to determine the diagnostic value of F12 in PTC. Then, the Kaplan-Meier plotter and Cox regression analyses were performed to examine the prognostic significance of F12. The possible mechanism of F12 in PTC was investigated through enrichment analyses. Finally, the correlation between F12 expression and immune cell infiltration was analyzed using TCGA data.

Results: This study revealed the clinical significance of F12 in various cancers. Higher mRNA (P <0.001) and protein expressions of F12 were observed in PTC compared with normal tissues. Besides, F12 expression exhibited high diagnostic performance in PTC and its overexpression served as an independent predictor for the poor OS (P <0.05). Enrichment analyses results showed that F12 was mainly involved in metabolism-associated pathways. Additionally, F12 expression was significantly linked to immune cell infiltration levels, especially macrophage infiltration.

Conclusions: F12 might be a reliable diagnostic and prognostic biomarker for PTC. Moreover, F12 expression might affect the OS of PTC patients via regulating metabolic pathways.

Functional roles of the SHCBP1 and KIF23 interaction in modulating the cell-cycle and cisplatin resistance of head and neck squamous cell carcinoma

BACKGROUND

This study aimed to explore the functional roles of Shc SH2-domain-binding protein 1 (SHCBP1) and Kinesin Family Member 23 (KIF23) in HPV-negative head and neck squamous cell carcinoma (HNSCC).

METHODS

Bioinformatic analysis was conducted using data from The Cancer Genome Atlas (TCGA) and GSE103322. HNSCC cell lines were used for in vitro and in vivo analysis.

RESULTS

SHCBP1 upregulation was associated with unfavorable survival. SHCBP1 knockdown reduced cell proliferation and increased the cisplatin sensitivity of SCC9/SCC25 cells. SHCBP1 interacted with KIF23 via its Nesd homology domain (NHD) domain, which was important for its nucleus localization. SHCBP1 positively modulated KIF23 expression and activated phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt), extracellular signal regulated kinase (ERK)1/2, nuclear factor kappa B (NF/κB)-p65, and Wnt/β-catenin signaling. KIF23 knockdown abrogated cisplatin resistance induced by SHCBP1 overexpression.

CONCLUSION

SHCBP1 interacts with KIF23 and cooperatively regulates cell-cycle progression and cisplatin resistance of HNSCC tumor cells.

Prognostic biomarkers for predicting papillary thyroid carcinoma patients at high risk using nine genes of apoptotic pathway

Aberrant expressions of apoptotic genes have been associated with papillary thyroid carcinoma (PTC) in the past, however, their prognostic role and utility as biomarkers remains poorly understood. In this study, we analysed 505 PTC patients by employing Cox-PH regression techniques, prognostic index models and machine learning methods to elucidate the relationship between overall survival (OS) of PTC patients and 165 apoptosis related genes. It was observed that nine genes (ANXA1, TGFBR3, CLU, PSEN1, TNFRSF12A, GPX4, TIMP3, LEF1, BNIP3L) showed significant association with OS of PTC patients. Five out of nine genes were found to be positively correlated with OS of the patients, while the remaining four genes were negatively correlated. These genes were used for developing risk prediction models, which can be utilized to classify patients with a higher risk of death from the patients which have a good prognosis. Our voting-based model achieved highest performance (HR = 41.59, p = 3.36x10^-4, C = 0.84, logrank-p = 3.8x10^-8). The performance of voting-based model improved significantly when we used the age of patients with prognostic biomarker genes and achieved HR = 57.04 with p = 10⁻⁴ (C = 0.88, logrank-p = 1.44x10^-9). We also developed classification models that can classify high risk patients (survival ≤ 6 years) and low risk patients (survival > 6 years). Our best model achieved AUROC of 0.92. Further, the expression pattern of the prognostic genes was verified at mRNA level, which showed their differential expression between normal and PTC samples. Also, the immunostaining results from HPA validated these findings. Since these genes can also be used as potential therapeutic targets in PTC, we also identified potential drug molecules which could modulate their expression profile. The study briefly revealed the key prognostic biomarker genes in the apoptotic pathway whose altered expression is associated with PTC progression and aggressiveness. In addition to this, risk assessment models proposed here can help in efficient management of PTC patients.

Identification of ferroptosis genes in immune infiltration and prognosis in thyroid papillary carcinoma using network analysis

BACKGROUND

Papillary thyroid carcinoma (PTC) is the most common thyroid cancer. While many patients survive, a portion of PTC cases display high aggressiveness and even develop into refractory differentiated thyroid carcinoma. This may be alleviated by developing a novel model to predict the risk of recurrence. Ferroptosis is an iron-dependent form of regulated cell death (RCD) driven by lethal accumulation of lipid peroxides, is regulated by a set of genes and shows a variety of metabolic changes. To elucidate whether ferroptosis occurs in PTC, we analyse the gene expression profiles of the disease and established a new model for the correlation.

METHODS

The thyroid carcinoma (THCA) datasets were downloaded from The Cancer Genome Atlas (TCGA), UCSC Xena and MisgDB, and included 502 tumour samples and 56 normal samples. A total of 60 ferroptosis related genes were summarised from MisgDB database. Gene set enrichment analysis (GSEA) and Gene set variation analysis (GSVA) were used to analyse pathways potentially involving PTC subtypes. Single sample GSEA (ssGSEA) algorithm was used to analyse the proportion of 28 types of immune cells in the tumour immune infiltration microenvironment in THCA and the hclust algorithm was used to conduct immune typing according to the proportion of immune cells. Spearman correlation analysis was performed on the ferroptosis gene expression and the correlation between immune infiltrating cells proportion. We established the WGCNA to identify genes modules that are highly correlated with the microenvironment of immune invasion. DEseq2 algorithm was further used for differential analysis of sequencing data to analyse the functions and pathways potentially involving hub genes. GO and KEGG enrichment analysis was performed using Clusterprofiler to explore the clinical efficacy of hub genes. Univariate Cox analysis was performed for hub genes combined with clinical prognostic data, and the results was included for lasso regression and constructed the risk regression model. ROC curve and survival curve were used for evaluating the model. Univariate Cox analysis and multivariate Cox analysis were performed in combination with the clinical data of THCA and the risk score value, the clinical efficacy of the model was further evaluated.

RESULTS

We identify two subtypes in PTC based on the expression of ferroptosis related genes, with the proportion of cluster 1 significantly higher than cluster 2 in ferroptosis signature genes that are positively associated. The mutations of Braf and Nras are detected as the major mutations of cluster 1 and 2, respectively. Subsequent analyses of TME immune cells infiltration indicated cluster 1 is remarkably richer than cluster 2. The risk score of THCA is in good performance evaluated by ROC curve and survival curve, in conjunction with univariate Cox analysis and multivariate Cox analysis results based on the clinical data shows that the risk score of the proposed model could be used as an independent prognostic indicator to predict the prognosis of patients with papillary thyroid cancer.

CONCLUSIONS

Our study finds seven crucial genes, including Ac008063.2, Apoe, Bcl3, Acap3, Alox5ap, Atxn2l and B2m, and regulation of apoptosis by parathyroid hormone-related proteins significantly associated with ferroptosis and immune cells in PTC, and we construct the risk score model which can be used as an independent prognostic index to predict the prognosis of patients with PTC.

GADD45B Transcript Is a Prognostic Marker in Papillary Thyroid Carcinoma Patients Treated With Total Thyroidectomy and Radioiodine Therapy

Currently, there is a lack of efficient recurrence prediction methods for papillary thyroid carcinoma (PTC). In this study, we enrolled 202 PTC patients submitted to total thyroidectomy and radioiodine therapy with long-term follow-up (median = 10.7 years). The patients were classified as having favorable clinical outcome (PTC-FCO, no disease in the follow-up) or recurrence (PTC-RE). Alterations in BRAF, RAS, RET, and TERT were investigated (n = 202) and the transcriptome of 48 PTC (>10 years of follow-up) samples was profiled. Although no mutation was associated with the recurrence risk, 68 genes were found as differentially expressed in PTC-RE compared to PTC-FCO. Pathway analysis highlighted a potential role of cancer-related pathways, including signal transduction and FoxO signaling. Among the eight selected genes evaluated by RT-qPCR, SLC2A4 and GADD45B showed down-expression exclusively in the PTC-FCO group compared to non-neoplastic tissues (NT). Increased expression of GADD45B was an independent marker of shorter disease-free survival [hazard ratio (HR) 2.9; 95% confidence interval (CI95) 1.2-7.0] in our cohort and with overall survival in the TCGA dataset (HR = 4.38, CI95 1.2-15.5). In conclusion, GADD45B transcript was identified as a novel prognostic marker candidate in PTC patients treated with total thyroidectomy and radioiodine therapy.

BCL2 and hsa-miR-181a-5p are potential biomarkers associated with papillary thyroid cancer based on bioinformatics analysis

Background

The morbidity of thyroid carcinoma has been rising worldwide and increasing faster than any other cancer type. The most common subtype with the best prognosis is papillary thyroid cancer (PTC); however, the exact molecular pathogenesis of PTC is still not completely understood.

Methods

In the current study, 3 gene expression datasets (GSE3678, GSE3467, and GSE33630) and 2 miRNA expression datasets (GSE113629 and GSE73182) of PTC were selected from the Gene Expression Omnibus (GEO) database and were further used to identify differentially expressed genes (DEGs) and deregulated miRNAs between normal thyroid tissue samples and PTC samples. Then, Gene Ontology (GO) and pathway enrichment analyses were conducted, and a protein-protein interaction (PPI) network was constructed to explore the potential mechanism of PTC carcinogenesis. The hub gene detection was performed using the CentiScaPe v2.0 plugin, and significant modules were discovered using the MCODE plugin for Cytoscape. In addition, a miRNA-gene regulatory network in PTC was constructed using common deregulated miRNAs and DEGs.

Results

A total of 263 common DEGs and 12 common deregulated miRNAs were identified. Then, 6 significant KEGG pathways (P < 0.05) and 82 significant GO terms were found to be enriched, indicating that PTC was closely related to amino acid metabolism, development, immune system, and endocrine system. In addition, by constructing a PPI network and miRNA-gene regulatory network, we found that hsa-miR-181a-5p regulated the most DEGs, while BCL2 was targeted by the most miRNAs.

Conclusions

The results of this study suggested that hsa-miR-181a-5p and BCL2 and their regulatory networks may play important roles in the pathogenesis of PTC.

Bioinformatic analysis of the prognostic value and potential regulatory network of FOXF1 in papillary thyroid cancer

FOXF1 belongs to the forkhead family of transcription factors. In this study, we aimed to explore the expression profile of FOXF1 in papillary thyroid cancer (PTC) and corresponding adjacent normal tissues, by using data from The Cancer Genome Atlas-Thyroid Cancer (TCGA-THCA) and The Genotype-Tissue Expression (GTEx) project. Also, we studied its prognostic significance in PTC and its potential regulatory network. Results showed that FOXF1 expression was significantly lower in PTC tissues compared with adjacent normal tissues. Subgroup analysis only confirmed the downregulation in classical histological variant, but not in tall-cell and follicular variants. FOXF1 downregulation was associated with advanced T stages, positive nodal invasion, and advanced pathological stages of the classical variants. FOXF1 expression might be a fair prognostic marker in terms of recurrence, which independently predicted favorable RFS (HR:0.114, 95%CI: 0.045-0.289, p < .001). We examined FOXF1 somatic mutations, gene-level copy number alterations (CNAs) and the methylation status of 57 CpG sites in more than 350 classical PTC cases. However, no expression-related genetic and epigenetic alterations were identified. Based on 20,048 genes with RNA-seq data, we identified 16 genes that showed strongly positive co-expression (Pearson's r ≥ 0.6) with FOXF1. Available evidence showed that some of the genes have well-characterized tumor suppressive effects. We hypothesized that some of these genes might be the upstream regulators or downstream effectors of FOXF1 in classical PTC. In conclusion, FOXF1 mRNA was typically downregulated in classical PTC. Its expression might be a specific and independent prognostic biomarker in terms of RFS in classical PTC patients.