Identification and validation of potential target genes in papillary thyroid cancer

The role of MAPK, notch and Wnt signaling pathways in papillary thyroid cancer: Evidence from a systematic review and meta-analyzing microarray datasets employing bioinformatics knowledge and literature

Papillary thyroid cancer (PTC) is a prevalent kind of thyroid cancer (TC), with the risk of metastasis increasing faster than any other malignancy. So, understanding the role of PTC in pathogenesis requires studying the various gene expressions to find out which particular molecular biomarkers will be helpful. The authors conducted a comprehensive search on the PubMed microarray database and a meta-analysis approach on the remaining ones to determine the differentially expressed genes between PTC and normal tissues, along with the analyses of overall survival (OS) and recurrence-free survival (RFS) rates in patients with PTC. We considered the associated genes with MAPK, Wnt, and Notch signaling pathways. Two GEO datasets have been included in this research, considering inclusion and exclusion criteria. Nineteen genes were found to have higher differences through the meta-analysis procedure. Among them, ten genes were upregulated, and nine genes were downregulated. The expression of 19 genes was examined using the GEPIA2 database, and the Kaplan-Meier plot statistics were used to analyze RFS and the OS rates. We discovered seven significant genes with the validation: PRICKLE1, KIT, RPS6KA5, GADD45B, FGFR2, FGF7, and DTX4. To further explain these findings, it was discovered that the mRNA expression levels of these seven genes and the remaining 12 genes were shown to be substantially linked with the results of the experimental literature investigations on the PTC. Our research found nineteen panels of genes that could be involved in the PTC progression and metastasis and the immune system infiltration of these cancers.

Multimerin 1 aids in the progression of ovarian cancer possibly via modulation of DNA damage response and repair pathways

Ovarian cancer is one of the leading causes of deaths among women. Despite advances in the treatment regimes, a high rate of diagnosis in the advanced stage makes it almost an incurable malignancy. Thus, more research efforts are required to identify potential molecular markers for early detection of the disease and therapeutic targets to augment the survival rate of ovarian cancer patients. Previously, in this context, we identified dysregulated expression of multimerin 1 (MMRN1) in ovarian cancer. To elucidate the relationship between MMRN1 expression and ovarian cancer progression, siRNA-based MMRN1 knockdown was employed and various cell assays were performed to study its effect on ovarian cancer cells. In addition, network of dysregulated proteins was identified by quantitative proteomics and associated pathways were explored by bioinformatics analysis. MMRN1 silencing showed a significant reduction in cell viability, adhesion, migration, and invasion and a high frequency of cell apoptosis. Label-free quantitative proteomics and in-depth statistical analysis identified 448 dysregulated proteins, majority of which were overexpressed in MMRN1 knockdown cells. The pathways overrepresented in ovarian cancer were DNA replication, mismatch repair, nucleotide excision repair, and cell cycle regulation. Conclusively, the findings of this study suggest that MMRN1 aids in the progression of ovarian cancer via modulation of DNA damage response and repair pathways.

PROS1 shapes the immune-suppressive tumor microenvironment and predicts poor prognosis in glioma

Background

Glioma is the most malignant cancer in the brain. As a major vitamin-K-dependent protein in the central nervous system, PROS1 not only plays a vital role in blood coagulation, and some studies have found that it was associated with tumor immune infiltration. However, the prognostic significance of PROS1 in glioma and the underlying mechanism of PROS1 in shaping the tumor immune microenvironment (TIME) remains unclear.

Methods

The raw data (including RNA-seq, sgRNA-seq, clinicopathological variables and prognosis, and survival data) were acquired from public databases, including TCGA, GEPIA, CGGA, TIMER, GEO, UALCAN, and CancerSEA. GO enrichment and KEGG pathway analyses were performed using "cluster profiler" package and visualized by the "ggplot2" package. GSEA was conducted using R package "cluster profiler". Tumor immune estimation resource (TIMER) and spearman correlation analysis were applied to evaluate the associations between infiltration levels of immune cells and the expression of PROS1. qRT-PCR and WB were used to assay the expression of PROS1. Wound-healing assay, transwell chambers assays, and CCK-8 assays, were performed to assess migration and proliferation. ROC and KM curves were constructed to determine prognostic significance of PROS1 in glioma.

Results

The level of PROS1 expression was significantly increased in glioma in comparison to normal tissue, which was further certificated by qRT-PCR and WB in LN-229 and U-87MG glioma cells. High expression of PROS1 positively correlated with inflammation, EMT, and invasion identified by CancerSEA, which was also proved by downregulation of PROS1 could suppress cells migration, and proliferation in LN-229 and U-87MG glioma cells. GO and KEGG analysis suggested that PROS1 was involved in disease of immune system and T cell antigen receptor pathway. Immune cell infiltration analysis showed that expression of PROS1 was negatively associated with pDC and NK CD56 bright cells while positively correlated with Macrophages, Neutrophils in glioma. Immune and stromal scores analysis indicated that PROS1 was positively associated with immune score. The high level of PROS1 resulted in an immune suppressive TIME via the recruitment of immunosuppressive molecules. In addition, Increased expression of PROS1 was correlated with T-cell exhaustion, M2 polarization, poor Overall-Survival (OS) in glioma. And it was significantly related to tumor histological level, age, primary therapy outcome. The results of our experiment and various bioinformatics approaches validated that PROS1 was a valuable poor prognostic marker.

Conclusion

Increased expression of PROS1 was correlated with malignant phenotype and associated with poor prognosis in glioma. Besides, PROS1 could be a possible biomarker and potential immunotherapeutic target through promoting the glioma immunosuppressive microenvironment and inducing tumor-associated macrophages M2 polarization.

Novel prognostic matrisome-related gene signature of head and neck squamous cell carcinoma

Background: Head and neck squamous cell carcinoma (HNSCC) is a common malignancy of the mucosal epithelium of the oral cavity, pharynx, and larynx. Laryngeal squamous cell carcinoma (LSCC) and oral squamous cell carcinoma are common HNSCC subtypes. Patients with metastatic HNSCC have a poor prognosis. Therefore, identifying molecular markers for the development and progression of HNSCC is essential for improving early diagnosis and predicting patient outcomes.

Methods: Gene expression RNA-Seq data and patient clinical traits were obtained from The Cancer Genome Atlas-Head and Neck Squamous Cell Carcinoma (TCGA-HNSC) and Gene Expression Omnibus databases. Differentially expressed gene (DEG) screening was performed using the TCGA-HNSC dataset. Intersection analysis between the DEGs and a list of core matrisome genes obtained from the Matrisome Project was used to identify differentially expressed matrisome genes. A prognostic model was established using univariate and multivariate Cox regression analyses, least absolute shrinkage, and selection operator (LASSO) regression analysis. Immune landscape analysis was performed based on the single-sample gene set enrichment analysis algorithm, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, prognostic value, receiver operating characteristic curve analysis, and gene mutation analyses. Immunohistochemical results regarding prognostic protein levels were obtained from the Human Protein Atlas. Single-gene RNA-sequencing data were obtained from GSE150321 and GSE172577 datasets. CCK-8 and Transwell assays were used to confirm cell proliferation and migration.

Results: A total of 1,779 DEGs, including 939 upregulated and 840 downregulated genes, between tumor and normal samples were identified using the TCGA-HNSC microarray data. Intersection analysis revealed 52 differentially expressed matrisome-related genes. After performing univariate and multivariate Cox regression and LASSO analyses, a novel prognostic model based on six matrisome genes (FN1, LAMB4, LAMB3, DMP1, CHAD, and MMRN1) for HNSCC was established. This risk model can successfully predict HNSCC survival. The high-risk group had worse prognoses and higher enrichment of pathways related to cancer development than the low-risk group. Silencing LAMB4 in HNSCC cell lines promoted cell proliferation and migration.

Conclusion: This study provides a novel prognostic model for HNSCC. Thus, FN1, LAMB4, LAMB3, DMP1, CHAD, and MMRN1 may be the promising biomarkers for clinical practice.

LncRNA RP3-525N10.2-NFKB1-PROS1 triplet-mediated low PROS1 expression is an onco-immunological biomarker in low-grade gliomas: a pan-cancer analysis with experimental verification

Background

Glioma is the most common cancer in the central nervous system, and low grade gliomas are notorious for many types of tumors and heterogeneity. PROS1 not only plays an important role in the blood coagulation system, and recent studies have found that it was correlated with the development of tumors, especially related to tumor immune infiltration. However, the study of underlying role and mechanism of PROS1 in gliomas, especially in low-grade gliomas, is almost absent.

Methods

We integrated the information of patients with LGG in The Cancer Genome Atlas (TCGA) cohort and Chinese Glioma Genome Atlas (CGGA) cohort. Then, we systematically demonstrated the differences and prognostic prognosis value of PROS1 based on multi-omics analyses. In addition, Cell counting kit-8 (CCK-8) assay, colony formation assay, 5-Ethynyl-2’-deoxyuridine (EdU) incorporation assay, and Transwell assays were performed to evaluate cell proliferation and invasion. qRT-PCR and immunohistochemistry were used to evaluate the expression of PROS1 in LGG.

Results

Various bioinformatics approaches revealed that PROS1 was a valuable prognostic marker and may influence tumour development via distinct mechanisms, including expression of DNA methyltransferase, RNA modification, and DNA mismatch repair system genes, copy number variation, single nucleotide variation frequency, genomic heterogeneity, cancer stemness, DNA methylation, and alternative PROS1 splicing. Our analyses indicated that the long non-coding RNA RP3-525N10.2 may “decoy” or “guide” the transcription factor NFKB1 and prevent its association with PROS1, thereby reducing PROS1 expression and improving poor LGG prognosis. PROS1 expression was also closely associated with tumour infiltration by immune cells, especially tumour-associated macrophages, as well as the expression of various immune checkpoint inhibitors, immunomodulators, and immune cell markers.

Conclusion

long non-coding RNA RP3-525N10.2-NFKB1-PROS1 triplet-mediated PROS1 expression could serve as a biomarker for cancer diagnosis, prognosis, therapy selection, and follow-up in LGG patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03536-y.

Multimerin-1 and cancer: a review

Multimerin-1 (MMRN1) is a platelet protein with a role in haemostasis and coagulation. It is also present in endothelial cells (ECs) and the extracellular matrix (ECM), where it may be involved in cell adhesion, but its molecular functions and protein–protein interactions in these cellular locations have not been studied in detail yet. In recent years, MMRN1 has been identified as a differentially expressed gene (DEG) in various cancers and it has been proposed as a possible cancer biomarker. Some evidence suggest that MMRN1 expression is regulated by methylation, protein interactions, and non-coding RNAs (ncRNAs) in different cancers. This raises the questions if a functional role of MMRN1 is being targeted during cancer development, and if MMRN1’s differential expression pattern correlates with cancer progression. As a result, it is timely to review the current state of what is known about MMRN1 to help inform future research into MMRN1’s molecular mechanisms in cancer.

Susceptibility Genes and Chromosomal Regions Associated With Non-Syndromic Familial Non-Medullary Thyroid Carcinoma: Some Pathogenetic and Diagnostic Keys

Thyroid cancer is the malignant tumor that is increasing most rapidly in the world, mainly at the expense of sporadic papillary thyroid carcinoma. The somatic alterations involved in the pathogenesis of sporadic follicular cell derived tumors are well recognized, while the predisposing alterations implicated in hereditary follicular tumors are less well known. Since the genetic background of syndromic familial non-medullary carcinoma has been well established, here we review the pathogenesis of non-syndromic familial non-medullary carcinoma emphasizing those aspects that may be useful in clinical and pathological diagnosis. Non-syndromic familial non-medullary carcinoma has a complex and heterogeneous genetic basis involving several genes and loci with a monogenic or polygenic inheritance model. Most cases are papillary thyroid carcinoma (classic and follicular variant), usually accompanied by benign thyroid nodules (follicular thyroid adenoma and/or multinodular goiter). The possible diagnostic and prognostic usefulness of the changes in the expression and/or translocation of various proteins secondary to several mutations reported in this setting requires further confirmation. Given that non-syndromic familial non-medullary carcinoma and sporadic non-medullary thyroid carcinoma share the same morphology and somatic mutations, the same targeted therapies could be used at present, if necessary, until more specific targeted treatments become available.

Protein S-mediated signal transduction pathway regulates lung cancer cell proliferation, migration and angiogenesis

OBJECTIVE/BACKGROUND

Protein S (PS; encoded by the PROS1 gene), a key vitamin K-dependent anticoagulant protein, is emerging as a key structural and functional protein that is overexpressd in various malignancies, but how PS signals to promote lung cancer progression is unclear.

METHODS

We used immortalized, nontumorigenic human lung epithelial cell line NL-20, A549 cells as experimental cellular models for lung cancer, and human microvascular endothelial cells (HMEC-1) as a model system for angiogenesis. A loss- and gain-of-function approach was then used to analyze the role of tumor-derived PS and their natural TAM receptors Tyro3 and MerTK in regulating cell proliferation, migration, anchorage-independent growth, and capillary-like tube formation, all prominent attributes of the metastatic phenotype of tumor cells.

RESULTS

Evidence is now provided that regulation of PROS1 gene expression using either stable cell lines expressing lentiviral-short hairpin RNA (shRNAs) or a replication-incompetent adenovirus alters the phosphorylation of several major signaling pathways, including Erk, PKB/Akt, p38, and focal adhesion kinase (FAK), and modulates PS-dependent Tyro3- and MerTK-mediated cell migration, proliferation, and anchorage-independent growth of lung cancer cells, and endothelial cell capillary-like tube formation.

CONCLUSION

These finding suggest that the PS-Tyro3 and -MerTK axis mediates important signaling pathways to promote lung cancer progression. Genetic inhibition of endogenous PS may serve as a promising target for anticancer drug development.

Topoisomerase II alpha inhibition can overcome taxane-resistant prostate cancer through DNA repair pathways

Cabazitaxel (CBZ) is approved for the treatment of docetaxel-resistant castration-resistant prostate cancer (CRPC). However, its efficacy against CRPC is limited, and there are no effective treatments for CBZ-resistant CRPC. This study explored the optimal treatment for CRPC in the post-cabazitaxel setting. PC3 (CBZ-sensitive) and PC3CR cells (CBZ-resistant) were used in this study. We performed in silico drug screening for candidate drugs that could reprogram the gene expression signature of PC3CR cells. The in vivo effect of the drug combination was tested in xenograft mice models. We identified etoposide (VP16) as a promising treatment candidate for CBZ-resistant CRPC. The WST assay revealed that VP16 had a significant antitumor effect on PC3CR cells. PC3CR cells exhibited significantly higher topoisomerase II alpha (TOP2A) expression than PC3 cells. Higher TOP2A expression was a poor prognostic factor in The Cancer Genome Atlas prostate cancer cohort. In the Fred Hutchinson Cancer Research Center dataset, docetaxel-exposed tissues and metastatic tumors had higher TOP2A expression. In addition, VP16 significantly inhibited the growth of tumors generated from both cell lines. Based on these findings, VP16-based chemotherapy may be an optimal treatment for CPRC in the post-CBZ setting.

Identification of Prognosis-Associated Biomarkers in Thyroid Carcinoma by a Bioinformatics Analysis

Background

This study aimed to identify the key genes associated with prognosis in thyroid cancer (TC), and to explore potential pathways.

Methods

GSE66783, GSE58545, and GSE129562 datasets were used to identify differentially expressed genes (DEGs) between tumor and normal tissues, followed by KEGG analyses on DEGs. The protein-protein interaction (PPI) network of DEGs was subsequently constructed to find the top 10 hub genes and seed genes in the whole network. Furthermore, the mRNA expressions of hub genes and prognostic values were explored. Regarding the seed gene, pathway activity score and GSEA analyses were conducted as well.

Results

1) A total of 183 DEGs were consistently expressed in three datasets comprising 76 up-regulated and 107 down-regulated genes. DEGs were mainly enriched in the p53 signaling pathway, complement and coagulation cascades, and hedgehog signaling pathway. 2) The top 10 hub genes, including CCND1, TIMP1, ICAM1, MET, PLAU, LDLR, PLAUR, ITGA2, ITGA3, and LGALS3, were identified. All hub genes were highly expressed in TC compared with normal samples. 3) High expression of CCND1, TIMP1, MET, and LGALS3 statistically correlated with a favorable prognosis of patients. Poor survival was observed in patients with ITGA2 and ITGA3 high expression. There was no association between ICAM1, PLAU, and PLAUR expression and survival of patients. LGALS3 and TIMP1 were further identified as independent prognostic factors in TC. 4) Among 10 hub genes, TIMP1 was determined as the seed gene, indicating its significance in the whole network. We further found that in most of the famous cancer-related pathways, TIMP1 higher expression caused a lower pathway activity, suggesting its inhibitory effect to these pathways in TC. In addition, TIMP1 positively correlated with the p53 signaling pathway, complement, and coagulation cascades involved in TC.

Conclusion

The present study provided seven prognosis-associated genes in TC and revealed several significant pathways, which contributed to elucidate the pathogenesis of TC.

Gene Mutation Analysis in Papillary Thyroid Carcinoma Using a Multi-Gene Panel in China

Purpose

To detect low-frequency mutation in the 57 genes of small panels that are associated with developing thyroid cancer in papillary thyroid carcinoma (PTC) patients and provide patients with precise-targeted therapy.

Patients and Methods

This study included 144 patients diagnosed with PTC who underwent total thyroidectomy and lymph node dissection in the central area of the neck between May 2017 and October 2018. We performed ultra-deep sequencing of 57 genes from 144 patients and detected the 57 genes mutations with bioinformatics.

Results

There were 698 mutations in 45 genes from 138 PTC patients. A high frequency of mutations was detected in the RBM10 gene (44%) and TERT (43%), and some hotspot mutations, such as RBM10:p.E119D and TERT:p.P112fs, were also found.

Conclusion

Ultra-deep sequencing of small gene panels can find some low-frequency mutation genes, which can provide targeted therapy for patients.

Aberrant expression of PROS1 correlates with human papillary thyroid cancer progression

Background

Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer (TC). Considering the important association between cellular immunity and PTC progression, it is worth exploring the biological significance of immune-related signaling in PTC.

Methods

Several bioinformatics tools, such as R software, WEB-based Gene SeT AnaLysis Toolkit (WebGestalt), Database for Annotation, Visualization and Integrated Discovery (DAVID), Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape were used to identify the immune-related hub genes in PTC. Furthermore, in vitro experiments were adopted to identify the proliferation and migration ability of PROS1 knockdown groups and control groups in PTC cells.

Results

The differentially expressed genes (DEGs) of five datasets from Gene Expression Omnibus (GEO) contained 154 upregulated genes and 193 downregulated genes, with Protein S (PROS1) being the only immune-related hub gene. Quantitative real-time polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC) have been conducted to prove the high expression of PROS1 in PTC. Moreover, PROS1 expression was significantly correlated with lymph nodes classification. Furthermore, knockdown of PROS1 by shRNAs inhibited the cell proliferation and cell migration in PTC cells.

Conclusions

The findings unveiled the clinical relevance and significance of PROS1 in PTC and provided potential immune-related biomarkers for PTC development and prognosis.

Highly heterogeneous-related genes of triple-negative breast cancer: potential diagnostic and prognostic biomarkers

Background

Triple-negative breast cancer (TNBC) is a highly heterogeneous subtype of breast cancer, showing aggressive clinical behaviors and poor outcomes. It urgently needs new therapeutic strategies to improve the prognosis of TNBC. Bioinformatics analyses have been widely used to identify potential biomarkers for facilitating TNBC diagnosis and management.

Methods

We identified potential biomarkers and analyzed their diagnostic and prognostic values using bioinformatics approaches. Including differential expression gene (DEG) analysis, Receiver Operating Characteristic (ROC) curve analysis, functional enrichment analysis, Protein-Protein Interaction (PPI) network construction, survival analysis, multivariate Cox regression analysis, and Non-negative Matrix Factorization (NMF).

Results

A total of 105 DEGs were identified between TNBC and other breast cancer subtypes, which were regarded as heterogeneous-related genes. Subsequently, the KEGG enrichment analysis showed that these genes were significantly enriched in ‘cell cycle’ and ‘oocyte meiosis’ related pathways. Four (FAM83B, KITLG, CFD and RBM24) of 105 genes were identified as prognostic signatures in the disease-free interval (DFI) of TNBC patients, as for progression-free interval (PFI), five genes (FAM83B, EXO1, S100B, TYMS and CFD) were obtained. Time-dependent ROC analysis indicated that the multivariate Cox regression models, which were constructed based on these genes, had great predictive performances. Finally, the survival analysis of TNBC subtypes (mesenchymal stem-like [MSL] and mesenchymal [MES]) suggested that FAM83B significantly affected the prognosis of patients.

Conclusions

The multivariate Cox regression models constructed from four heterogeneous-related genes (FAM83B, KITLG, RBM24 and S100B) showed great prediction performance for TNBC patients’ prognostic. Moreover, FAM83B was an important prognostic feature in several TNBC subtypes (MSL and MES). Our findings provided new biomarkers to facilitate the targeted therapies of TNBC and TNBC subtypes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08318-1.

RAB5A is associated with genes involved in exosome secretion: Integration of bioinformatics analysis and experimental validation

Exosomes, as cell-cell communicators with an endosomal origin, are involved in the progression of various diseases. RAB5A, a member of the small Rab GTPases family, which is well known as a key regulator of cellular endocytosis, is expected to be involved in exosome secretion. Here, we found the impact of RAB5A on exosome secretion from human hepatocellular carcinoma cell line using a rapid yet reliable bioinformatics approach followed by experimental analysis. Initially, RAB5A and exosome secretion-related genes were gathered from bioinformatics tools, namely, CTD, COREMINE, and GeneMANIA; and published papers. Protein-protein interaction (PPI) was then constructed by the Search Tool for Retrieval of Interacting Genes (STRING) database. Among them, several genes with different combined scores were validated by the real-time quantitative polymerase chain reaction (RT-qPCR) in stable RAB5A knockdown cells. Thereafter, to validate the bioinformatics results functionally, the impact of RAB5A knockdown on exosome secretion was evaluated. Bioinformatics analysis showed that RAB5A interacts with 37 genes involved in exosome secretion regulatory pathways. Validation by RT-qPCR confirmed the association of RAB5A with candidate interacted genes and interestingly showed that even medium to low combined scores of the STRING database could be experimentally valid. Moreover, the functional analysis demonstrated that the stable silencing of RAB5A could experimentally decrease exosome secretion. In conclusion, we suggest RAB5A as a regulator of exosome secretion based on our bioinformatics approach and experimental analysis. Also, we propose the usage of PPI-derived from the STRING database regardless of their combined scores in advanced bioinformatics analysis.

Kopp P, Habeos I, Trougakos IP, Khoo NKH, Sykiotis GP. The Transcriptomic Response of the Murine Thyroid Gland to Iodide Overload and the Role of the Nrf2 Antioxidant System

Background: Thyroid follicular cells have physiologically high levels of reactive oxygen species because oxidation of iodide is essential for the iodination of thyroglobulin (Tg) during thyroid hormone synthesis. Thyroid follicles (the functional units of the thyroid) also utilize incompletely understood autoregulatory mechanisms to defend against exposure to excess iodide. To date, no transcriptomic studies have investigated these phenomena in vivo. Nuclear erythroid factor 2 like 2 (Nrf2 or Nfe2l2) is a transcription factor that regulates the expression of numerous antioxidant and other cytoprotective genes. We showed previously that the Nrf2 pathway regulates the antioxidant defense of follicular cells, as well as Tg transcription and Tg iodination. We, thus, hypothesized that Nrf2 might be involved in the transcriptional response to iodide overload. Methods: C57BL6/J wild-type (WT) or Nrf2 knockout (KO) male mice were administered regular water or water supplemented with 0.05% sodium iodide for seven days. RNA from their thyroids was prepared for next-generation RNA sequencing (RNA-Seq). Gene expression changes were assessed and pathway analyses were performed on the sets of differentially expressed genes. Results: Analysis of differentially expressed messenger RNAs (mRNAs) indicated that iodide overload upregulates inflammatory-, immune-, fibrosis- and oxidative stress-related pathways, including the Nrf2 pathway. Nrf2 KO mice showed a more pronounced inflammatory–autoimmune transcriptional response to iodide than WT mice. Compared to previously published datasets, the response patterns observed in WT mice had strong similarities with the patterns typical of Graves’ disease and papillary thyroid carcinoma (PTC). Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) also responded to iodide overload, with the latter targeting mRNAs that participate mainly in inflammation pathways. Conclusions: Iodide overload induces the Nrf2 cytoprotective response and upregulates inflammatory, immune, and fibrosis pathways similar to autoimmune hyperthyroidism (Graves’ disease) and PTC.

Preoperative Sonographic and Clinicopathological Predictors for Solitary Lateral Neck Node Metastasis in Papillary Thyroid Carcinoma: A Retrospective Study

Background

Cervical lymph node metastasis (LNM) is an independent risk factor for poor prognosis of papillary thyroid carcinoma (PTC), but the scope of PTC lateral neck dissection (LND) is controversial. Solitary lateral lymph node metastasis (SLNM) is a special type of PTC with lateral LNM. Currently, study on the preoperative clinical characteristics of SLNM has been seldomly reported. This study evaluated the preoperative characteristics for predicting the SLNM of PTC.

Methods

We included 391 patients diagnosed with PTC between May 2011 and July 2017. Among those patients, 44 had SLNM and 347 had multiple lateral neck node metastasis (MLNM). The clinicopathologic characteristics and other central lymph node metastasis risk factors were retrospectively analyzed.

Results

Univariate analysis revealed that age and tumor size (≤1 cm) were significantly correlated with SLNM. In ROC curve analysis, the optimal cutoff age of preoperative predictors for the prediction of SLNM was 46.5 years (AUC=0.623, 0.536–0.710). Besides, the frequency and mean number of CLNM was significantly less in the SLNM than MLNM group. The oval and round tumor shape and well-defined margin of the tumor were more common in the SLNM group (p =0.001; p=0.024, respectively). In addition, multivariate analysis revealed that age ≥47, capsular invasion, no extrathyroidal extension, with central lymph node metastases and irregular shape were independent SLNM predictors of PTCs (odds ratio 2.386, 0.173, 0.284, 0.239, 0.188; 95% CI 1.07–5.140, 0.058–0.840, 0.066–0.926, 0.091–0.437, 0.167–0.864, respectively).

Conclusion

This study supported that SLNM is more likely to happen in PTC patients with age ≥47 years, capsular invasion, no extrathyroidal extension, with central lymph node metastases and irregular shape. That denotes, selective single level neck dissection can be considered as an alternative to systemic lateral neck dissection in those patients.

Identification and validation of key modules and hub genes associated with the pathological stage of oral squamous cell carcinoma by weighted gene co-expression network analysis

Background

Oral squamous cell carcinoma (OSCC) is a major lethal malignant cancer of the head and neck region, yet its molecular mechanisms of tumourigenesis are still unclear.

Patients and methods

We performed weighted gene co-expression network analysis (WGCNA) on RNA-sequencing data with clinical information obtained from The Cancer Genome Atlas (TCGA) database. The relationship between co-expression modules and clinical traits was investigated by Pearson correlation analysis. Furthermore, the prognostic value and expression level of the hub genes of these modules were validated based on data from the TCGA database and other independent datasets from the Gene Expression Omnibus (GEO) database and the Human Protein Atlas database. The significant modules and hub genes were also assessed by functional analysis and gene set enrichment analysis (GSEA).

Results

We found that the turquoise module was strongly correlated with pathologic T stage and significantly enriched in critical functions and pathways related to tumourigenesis. PPP1R12B, CFD, CRYAB, FAM189A2 and ANGPTL1 were identified and statistically validated as hub genes in the turquoise module and were closely implicated in the prognosis of OSCC. GSEA indicated that five hub genes were significantly involved in many well-known cancer-related biological functions and signaling pathways.

Conclusion

In brief, we systematically discovered a co-expressed turquoise module and five hub genes associated with the pathologic T stage for the first time, which provided further insight that WGCNA may reveal the molecular regulatory mechanism involved in the carcinogenesis and progression of OSCC. In addition, the five hub genes may be considered candidate prognostic biomarkers and potential therapeutic targets for the precise early diagnosis, clinical treatment and prognosis of OSCC in the future.

Comprehensive analysis of differentially expressed lncRNAs as diagnostic and prognostic markers for colorectal cancer

Colorectal cancer (CRC) is the third most common type of cancer worldwide. Recent studies had revealed the important roles of long non-coding RNAs (lncRNAs) in a variety of human cancers, including CRC. However, the molecular mechanisms associated with CRC remain largely undetermined. In the current study, the GSE21510 dataset was analyzed to identify differentially expressed mRNAs and lncRNAs in CRC samples. The Database for Annotation, Visualization and Integrated Discovery was used to perform Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway bioinformatics analysis. Furthermore, protein-protein interaction networks were constructed to reveal interactions among differentially expressed proteins. Kaplan-Meier analysis was subsequently performed to determine the association between key lncRNA expression and the overall survival of patients with CRC. A total of 107 upregulated lncRNAs and 43 downregulated lncRNAs were identified in CRC. A lncRNA mediated co-expression network was also constructed in CRC. Bioinformatics analysis indicated that lncRNAs were associated with a series of biological processes, including 'xenobiotic glucuronidation', 'rRNA processing', 'sister chromatid cohesion', 'cell proliferation', 'mitotic nuclear division' and 'cell cycle regulation'. Furthermore, a higher expression of small nucleolar RNA host gene 17, tetratricopeptide repeat domain 2B-antisense RNA (AS) 1, erythrocyte membrane protein band 4.1 like 4A-AS2, deleted in lymphocytic leukemia 2, and a lower expression of muscle blind like splicing regulator 1-AS1 and LOC389332 were associated with shorter overall survival time in CRC samples. The present study provides useful information that can be used in the identification of novel biomarkers for CRC.

Bioinformatics analysis to screen key genes in papillary thyroid carcinoma

Papillary thyroid carcinoma (PTC) is the most common type of thyroid carcinoma, and its incidence has been on the increase in recent years. However, the molecular mechanism of PTC is unclear and misdiagnosis remains a major issue. Therefore, the present study aimed to investigate this mechanism, and to identify key prognostic biomarkers. Integrated analysis was used to explore differentially expressed genes (DEGs) between PTC and healthy thyroid tissue. To investigate the functions and pathways associated with DEGs, Gene Ontology, pathway and protein-protein interaction (PPI) network analyses were performed. The predictive accuracy of DEGs was evaluated using the receiver operating characteristic (ROC) curve. Based on the four microarray datasets obtained from the Gene Expression Omnibus database, namely GSE33630, GSE27155, GSE3467 and GSE3678, a total of 153 DEGs were identified, including 66 upregulated and 87 downregulated DEGs in PTC compared with controls. These DEGs were significantly enriched in cancer-related pathways and the phosphoinositide 3-kinase-AKT signaling pathway. PPI network analysis screened out key genes, including acetyl-CoA carboxylase beta, cyclin D1, BCL2, and serpin peptidase inhibitor clade A member 1, which may serve important roles in PTC pathogenesis. ROC analysis revealed that these DEGs had excellent predictive performance, thus verifying their potential for clinical diagnosis. Taken together, the findings of the present study suggest that these genes and related pathways are involved in key events of PTC progression and facilitate the identification of prognostic biomarkers.

Gene expression and methylation profiles identified CXCL3 and CXCL8 as key genes for diagnosis and prognosis of colon adenocarcinoma

Colon adenocarcinoma (COAD) is one of the most common malignant tumors with high morbidity and mortality rates worldwide. Due to the poor clinical outcomes, it is indispensable to investigate novel biomarkers for the diagnosis and prognosis of COAD. The aim of this study is to explore key genes as potential biomarkers for the diagnosis and prognosis of COAD for clinical utility. Gene expression profiles (GSE44076 and GSE44861) and gene methylation profile (GSE29490) were analyzed to identify the aberrantly methylated-differentially expressed genes by R language and Perl software. Function enrichments were performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. Moreover, hub genes were identified through protein-protein interaction (PPI) network. Besides, key genes were found by the module analysis and The Cancer Genome Atlas (TCGA) survival analysis. Finally, TCGA data and quantitative real-time polymerase chain reaction (RT-qPCR) was used to validate the key genes involved in COAD. Our study found two hypomethylation-high-expression genes (CXCL3 and CXCL8) in COAD tissues compared with the adjacent normal tissues. These results were also confirmed by RT-qPCR with 25 pairs of COAD and adjacent normal tissues. Meanwhile, low expression of the two genes was associated with poor survival in patients with COAD. CXCL3 and CXCL8 may serve as key genes in the diagnosis and prognosis for COAD.

Neurexophilin and PC-esterase domain family member 4 (NXPE4) and prostate androgen-regulated mucin-like protein 1 (PARM1) as prognostic biomarkers for colorectal cancer

Owing to the high morbidity and mortality, novel biomarkers in the occurrence and development of colorectal cancer (CRC) are needed nowadays. In this study, the CRC-related datasets were downloaded from the Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database. After screening the differentially expressed genes (DEGs) in R software, a total of 238 upregulated and 199 downregulated DEGs were revealed simultaneously. Then the Kaplan-Meier survival analysis and Cox regression analysis were used to reveal the prognostic function of these DEGs. Neurexophilin and PC-esterase domain family member 4 (NXPE4) and prostate androgen-regulated mucin-like protein 1 (PARM1) were two outstanding independent overall survival (OS) and relapse-free survival (RFS) prognostic genes of CRC in TCGA database. We next verified the expression of NXPE4 and PARM1 messenger RNA (mRNA) levels were significantly lower in CRC tumor tissue than in the adjacent noncancerous tissue in our clinical samples, and NXPE4 mRNA expression level was related to the tumor location and tumor size, while PARM1 was related to tumor location, lymph nodes metastasis, and tumor size. This study demonstrated that NXPE4 and PARM1 might be two potential novel prognostic biomarkers for CRC.

Network Analyses of Integrated Differentially Expressed Genes in Papillary Thyroid Carcinoma to Identify Characteristic Genes

Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer. Identifying characteristic genes of PTC are of great importance to reveal its potential genetic mechanisms. In this paper, we proposed a framework, as well as a measure named Normalized Centrality Measure (NCM), to identify characteristic genes of PTC. The framework consisted of four steps. First, both up-regulated genes and down-regulated genes, collectively called differentially expressed genes (DEGs), were screened and integrated together from four datasets, that is, GSE3467, GSE3678, GSE33630, and GSE58545; second, an interaction network of DEGs was constructed, where each node represented a gene and each edge represented an interaction between linking nodes; third, both traditional measures and the NCM measure were used to analyze the topological properties of each node in the network. Compared with traditional measures, more genes related to PTC were identified by the NCM measure; fourth, by mining the high-density subgraphs of this network and performing Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, several meaningful results were captured, most of which were demonstrated to be associated with PTC. The experimental results proved that this network framework and the NCM measure are useful for identifying more characteristic genes of PTC.

Microgravity Affects Thyroid Cancer Cells during the TEXUS-53 Mission Stronger than Hypergravity

Thyroid cancer is the most abundant tumor of the endocrine organs. Poorly differentiated thyroid cancer is still difficult to treat. Human cells exposed to long-term real (r-) and simulated (s-) microgravity (µg) revealed morphological alterations and changes in the expression profile of genes involved in several biological processes. The objective of this study was to examine the effects of short-term µg on poorly differentiated follicular thyroid cancer cells (FTC-133 cell line) resulting from 6 min of exposure to µg on a sounding rocket flight. As sounding rocket flights consist of several flight phases with different acceleration forces, rigorous control experiments are mandatory. Hypergravity (hyper-g) experiments were performed at 18g on a centrifuge in simulation of the rocket launch and s-µg was simulated by a random positioning machine (RPM). qPCR analyses of selected genes revealed no remarkable expression changes in controls as well as in hyper-g samples taken at the end of the first minute of launch. Using a centrifuge initiating 18g for 1 min, however, presented moderate gene expression changes, which were significant for COL1A1, VCL, CFL1, PTK2, IL6, CXCL8 and MMP14. We also identified a network of mutual interactions of the investigated genes and proteins by employing in-silico analyses. Lastly, µg-samples indicated that microgravity is a stronger regulator of gene expression than hyper-g.