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

BARX1 repressed FOXF1 expression and activated Wnt/β-catenin signaling pathway to drive lung adenocarcinoma

BACKGROUND

Underlying molecular mechanisms of BARX homeobox 1 (BARX1) in lung adenocarcinoma (LUAD) remain elusive.

METHODS

Abnormally expressed genes in LUAD tissues were analyzed by RNA-sequencing. CCK-8, colony formation, transwell, and wound healing assays examined proliferation, colony formation, invasion, and migration of LUAD cells, respectively. Electrophoretic mobility shift assay and chromatin immunoprecipitation assay examined the interaction between BARX1 and Forkhead Box F1 (FOXF1). Xenograft mouse model of LUAD was constructed to monitor the growth and metastasis of tumor.

RESULTS

BARX1 was upregulated, FOXF1 was downregulated in LUAD tissues and cells. There was a negative correlation between BARX1 and FOXF1 expression. BARX1 deficiency limited malignant phenotypes of LUAD cells, including proliferation, invasion, migration and EMT. In vivo, BARX1 knockdown suppressed tumor growth and metastasis in A549-drove xenograft mouse model. BARX1 interacted with FOXF1 promoter and repressed FOXF1 expression. Upregulation of BARX1 promoted the expression of Wnt5a, β-catenin, and phosphorylated-glycogen synthase kinase-3 beta (p-GSK3β), whereas inhibited FOXF1, p-β-catenin, and GSK3β in LUAD cells. BARX1 knockdown caused an opposite result. Rescue assays uncovered that FOXF1 reversed the impact of BARX1 on malignant phenotypes and Wnt/β-catenin of LUAD cells.

CONCLUSION

BARX1 repressed FOXF1 expression and activated Wnt/β-catenin signaling pathway to drive lung adenocarcinoma.

Signal peptidase complex catalytic subunit SEC11A upregulation is a biomarker of poor prognosis in patients with head and neck squamous cell carcinoma

In the current study, we aimed to investigate the expression of the five microsomal signal peptidase complex (SPC) subunit genes (SEC11A, SEC11C, SPCS1, SPCS2, and SPCS3) in head and neck squamous cell carcinoma (HNSC) and to explore their prognostic value. Data from the HNSC subset of The Cancer Genome Atlas (TCGA) and one previous single-cell RNA-seq dataset was used. Subgroup analysis was conducted in tumors from different anatomic sites. Gene set enrichment analysis (GSEA), and immune cell infiltration analysis were performed to check the influence of SEC11A on the tumor microenvironment. Among the genes significantly upregulated in the tumor group, only SEC11A expression (as a continuous variable) is independently associated with poorer progression-free survival (PFS) (HR: 2.075, 95%CI: 1.447–2.977, p<0.001) and disease-specific survival (DSS) (HR: 2.023, 95%CI: 1.284–3.187, p = 0.002). Subgroup analysis confirmed the prognostic value in tumors from three anatomic origins, including laryngeal squamous cell carcinoma, oral cavity-related squamous cell carcinoma, and oropharynx-related squamous cell carcinoma. SEC11A is expressed in all subtypes of cells in the tumor microenvironment. Its expression showed a moderate positive correlation with its gene-level copy number (Pearson’s r = 0.53, p<0.001). SEC11A expression was negatively correlated with CD8+ T cells and B cells, but was positively correlated with cancer-associated fibroblast and myeloid-derived suppressor cells (MDSCs) in the tumor microenvironment. In summary, SEC11A upregulation is a result of gene amplification in head and neck squamous cell carcinoma. Its upregulation might serve as an independent prognostic biomarker and a predictor of the infiltration of certain types of immune cells.

SLCO4A1 is a Prognosis-Associated Biomarker Involved in Neutrophil-Mediated Immunity in Thyroid Cancer

Objective

The study aimed to investigate the value of solute carrier organic anion transporter family member 4A1 (SLCO4A1) in thyroid cancer mainly from three aspects: expression, prognosis, and biological function analyses.

Methods

Based on various bioinformatic approaches, genes co-expressed with vascular endothelial growth factor C (VEGFC) in thyroid cancer were used for further survival and expression analyses to identify the target gene. After evaluation of the SLCO4A1 expression levels in thyroid cancer, Cox regression analysis was utilized to predict the risk factors for survival of thyroid cancer patients. And receiving operating characteristic curve analysis was performed to validate the prognostic value of SLCO4A1. Additionally, WebGestalt was employed for enrichment analysis of SLCO4A1 and its co-expressed genes. Further, the relation between SLCO4A1 and neutrophil was analyzed, followed by exploring the association of SLCO4A1 with immunomodulators.

Results

A total of 38 consistent VEGFC co-expressed genes were generated, and SLCO4A1 was selected as the target gene due to its oncogenic characteristics. SLCO4A1 was highly expressed in thyroid cancer at both gene and protein levels, and SLCO4A1 mRNA expression was significantly associated with the cancer stage (all P <0.05). Besides, high SLCO4A1 expression led to unfavorable progression-free survival (PFS) of thyroid cancer patients (P =0.0066). Further, Cox regression analysis indicated that high SLCO4A1 expression was an independent predictor of poor PFS in patients with papillary thyroid cancer, particularly in patients at stage 1 and female patients (all P <0.001). The enrichment analysis results showed that SLCO41A was involved in the neutrophil-mediated immunity pathway. Moreover, SLCO4A1 had a positive relation with neutrophils (all P <0.05). Finally, a significant correlation between SLCO4A1 and immunomodulators was observed (all P <0.001).

Conclusion

SLCO4A1 was a potential prognostic biomarker for papillary thyroid cancer patients. And SLCO4A1 might affect PFS in thyroid cancer patients by positive regulation of neutrophil-mediated immunity pathway.

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.

Low expression of TFF3 in papillary thyroid carcinoma may correlate with poor prognosis but high immune cell infiltration

Background: Papillary thyroid carcinoma (PTC) is one of the most common endocrine malignancies and has a favorable prognosis. However, optimal treatments and prognostic markers have not been clearly identified. Methods: Gene expression data from primary PTC were downloaded from the Gene Expression Omnibus database and subjected to two analyses of differentially expressed genes (DEGs), followed by intersecting individual and integrated DEGs analyses as well as gene set enrichment analysis. Analysis of data from Sequence Read Archive and The Cancer Genome Atlas, immunohistochemistry and qRT-PCR of TFF3 were performed to validate the results. Finally, the relationship between gene expression and disease-free survival as well as immune cell infiltration were investigated. Results: Six critical DEGs and several tumor-enriched signaling pathways were identified. Immunohistochemistry and qRT-PCR validated the low expression of TFF3 in PTC. TFF3 and FCGBP are coexpressed in PTC, and patients with lower gene expression had worse disease-free survival but higher immune cell infiltration. Conclusion: TFF3 was significantly underexpressed and may function with FCGBP synergistically in 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.