Identification of potential biomarkers and drugs for papillary thyroid cancer based on gene expression profile analysis

Gene-expression profile analysis to disclose diagnostics and therapeutics biomarkers for thyroid carcinoma

The most frequent endocrine cancer of the head and neck is thyroid carcinoma (THCA). Although there is increasing evidence linking THCA to genetic alterations, the exact molecular mechanism behind this relationship is not yet completely known to the researchers. There is still much to learn about THCA's molecular roots and genetic biomarkers. Though drug therapies are the best choice after metastasis, unfortunately, the majority of the patients progressively develop resistance against the therapeutic drugs after receiving them for a few years. Therefore, multi-targeted different variants of therapeutic drugs may be essential for effective treatment against THCA. To understand molecular mechanisms of THCA development and progression and explore multi-targeted different variants of therapeutic drugs, we detected 80 common differentially expressed genes (cDEGs) between THCA and non-THCA samples from six microarray gene expression datasets using the statistical LIMMA approach. Through protein-protein interaction (PPI) network analysis, we identified the top-ranked eight differentially expressed genes (TIMP1, FN1, THBS1, RUNX2, SHANK2, TOP2A, LRP2, and ACTN1) as the THCA-causing key genes (KGs), where 6 KGs (TIMP1, TOP2A, FN1, ACTN1, RUNX2, THBS1) are upregulated and 2 KGs (LRP2, SHANK2) are downregulated. The expression pattern analysis of KGs with the independent TCGA database by Box plots also confirmed their upregulated and downregulated patterns. The expression analysis of KGs in different stages of THCA development indicated that these KGs might be utilized as early diagnostic and prognostic biomarkers. The pan-cancer analysis of KGs indicated a substantial correlation of KGs with multiple cancers, including THCA. Some transcription factors (TFs) and microRNAs were detected as the key transcriptional and post-transcriptional regulators of KGs using gene regulatory network (GRN) analysis. The enrichment analysis of the cDEGs revealed several key molecular functions, biological processes, cellular components, and pathways significantly associated with THCA. These findings highlight critical mechanisms influenced by the identified key genes (KGs), providing deeper insight into their roles in THCA development. Then we detected 6 repurposable drug molecules (Entrectinib, Imatinib, Ponatinib, Sorafenib, Retevmo, and Pazopanib) by molecular docking with KGs-mediated receptor proteins, ADME/T analysis, and cross-validation with the independent receptors. Therefore, these findings might be useful resources for wet lab researchers and clinicians to consider an effective treatment strategy against THCA.

Identification of potential targetable genes in papillary, follicular, and anaplastic thyroid carcinoma using bioinformatics analysis

PURPOSE

To perform an extensive exploratory analysis to build a deeper insight into clinically relevant molecular biomarkers in Papillary, Follicular, and Anaplastic thyroid carcinomas (PTC, FTC, ATC).

METHODS

Thirteen Thyroid Cancer (THCA) datasets incorporating PTC, FTC, and ATC were derived from the Gene Expression Omnibus. Genes differentially expressed (DEGs) between THCA and normal were identified and subjected to GO and KEGG analyses. Multiple topological properties were harnessed and protein-protein interaction (PPI) networks were constructed to identify the hub genes followed by survival analysis and validation.

RESULTS

There were 70, 87, and 377 DEGs, and 23, 27, and 53 hub genes for PTC, FTC, and ATC samples, respectively. Survival analysis detected 39 overall and 49 relapse-free survival-relevant hub genes. Six hub genes, BCL2, FN1, ITPR1, LYVE1, NTRK2, TBC1D4, were found common to more than one THCA type. The most significant hub genes found in the study were: BCL2, CD44, DCN, FN1, IRS1, ITPR1, MFAP4, MKI67, NTRK2, PCLO, TGFA. The most enriched and significant GO terms were Melanocyte differentiation for PTC, Extracellular region for FTC, and Extracellular exosome for ATC. Prostate cancer for PTC was the most significantly enriched KEGG pathway. The results were validated using TCGA data.

CONCLUSIONS

The findings unravel potential biomarkers and therapeutic targets of thyroid carcinomas.

LAMB3: Central role and clinical significance in neoplastic and non-neoplastic diseases

Recently, topics related to targeted gene therapy and diagnosis have become increasingly important in disease research. The progression of many diseases is associated with specific gene signaling pathways. Therefore, the identification of precise gene targets in various diseases is crucial for the development of effective treatments. Laminin subunit beta 3 (LAMB3), a component of laminin 5, functions as an adhesive protein in the extracellular matrix and plays a vital role in regulating cell proliferation, migration, and cell cycle in certain diseases. Previous studies have indicated that LAMB3 is highly expressed in numerous tumorous and non-tumorous conditions, including renal fibrosis; squamous cell carcinoma of the skin, thyroid, lung, pancreatic, ovarian, colorectalr, gastric, breast, cervical, nasopharyngeal, bladder, prostate cancers; and cholangiocarcinoma. Conversely, it is underexpressed in other conditions, such as hepatocellular carcinoma, epidermolysis bullosa, and amelogenesis imperfecta. Consequently, LAMB3 may serve as a molecular diagnostic and therapeutic target for various diseases through its involvement in critical gene signaling pathways. This paper reviews the research status of LAMB3 and its role in related diseases.

Expression of Collagen XIII in Tissues of the Thyroid and Orbit With Relevance to Thyroid-Associated Ophthalmopathy

Purpose

Antibodies against collagen XIII have previously been identified in patients with active thyroid-associated ophthalmopathy (TAO). Although collagen XIII expression has been described in extraocular muscles and orbital fat, its detailed localization in extraocular and thyroid tissues and the connection to autoimmunity for collagen XIII remain unclear. Our objective was to map the potential targets for these antibodies in the tissues of the orbit and thyroid.

Methods

We evaluated the expression of collagen XIII in human patient and mouse orbital and thyroid tissues with immunostainings and RT-qPCR using Col13a1-/- mice as negative controls. COL13A1 expression in Graves' disease and goiter thyroid samples was compared with TGF-β1 and TNF, and these were also studied in human thyroid epithelial cells and fibroblasts.

Results

Collagen XIII expression was found in the neuromuscular and myotendinous junctions of extraocular muscles, blood vessels of orbital connective tissue and fat and the thyroid, and in the thyroid epithelium. Thyroid expression was also seen in germinal centers in Graves' disease and in neoplastic epithelium. The expression of COL13A1 in goiter samples correlated with levels of TGF-B1. Upregulation of COL13A1 was reproduced in thyroid epithelial cells treated with TGF-β1.

Conclusions

We mapped the expression of collagen XIII to various locations in the orbit, demonstrated its expression in the pathologies of the Graves' disease thyroid and confirmed the relationship between collagen XIII and TGF-β1. Altogether, these data add to our understanding of the targets of anti-collagen XIII autoantibodies in TAO.

Large-scale transcriptomic analysis of coding and non-coding pathological biomarkers, associated with the tumor immune microenvironment of thyroid cancer and potential target therapy exploration

Papillary thyroid carcinoma (PTC) is the most prevalent endocrine malignancy with a steadily increasing global incidence in recent decades. The pathogenesis of PTC is poorly understood, and the present diagnostic protocols are deficient. Thus, identifying novel prognostic biomarkers to improve our understanding of the mechanisms of pathogenesis, diagnosis, and designing therapeutic strategies for PTC is crucial. In this study, we integrated 27 PTC transcriptomic datasets and identified overlapping differentially expressed genes (DEGs) and differentially expressed microRNAs, collectively known as thyroid tumor-enriched proteins (TTEPs), and TTEmiRs, respectively. Our integrated bioinformatics analysis revealed that TTEPs were associated with tumor stages, poor surgical outcomes, distant metastasis, and worse prognoses in PTC cohorts. In addition, TTEPs were found to be associated with tumor immune infiltrating cells and immunosuppressive phenotypes of PTC. Enrichment analysis suggested the association of TTEPs with epithelial-to-mesenchymal transition (EMT), cell-matrix remodeling, and transcriptional dysregulation, while the TTEmiRs (miR-146b-5p and miR-21-5p) were associated with the modulation of the immune response, EMT, migration, cellular proliferation, and stemness. Molecular docking simulations were performed to evaluate binding affinities between TTEPs and antrocinnamomin, antcin, and antrocin, the bioactive compounds from one of the most reputable Taiwan indigenous medicinal plants (Antrodia camphorata). Our results revealed that antcin exhibited higher binding efficacies toward FN1, ETV5, and NRCAM, whereas antrocin demonstrated the least. Among the targets, fibronectin (FN1) demonstrated high ligandability potential for the compounds whereas NRCAM demonstrated the least. Collectively, our results hinted at the potential of antcin for targeting TTEPs. In conclusion, this comprehensive bioinformatics analysis strongly suggested that TTEPs and TTEmiRs could be used as potential diagnostic biomarker signatures and be exploited as potential targets for therapeutics development.

Comprehensive bioinformatic analysis reveals a cancer-associated fibroblast gene signature as a poor prognostic factor and potential therapeutic target in gastric cancer

BACKGROUND

Gastric cancer is one of the deadliest cancers, currently available therapies have limited success. Cancer-associated fibroblasts (CAFs) are pivotal cells in the stroma of gastric tumors posing a great risk for progression and chemoresistance. The poor prognostic signature for CAFs is not clear in gastric cancer, and drugs that target CAFs are lacking in the clinic. In this study, we aim to identify a poor prognostic gene signature for CAFs, targeting which may increase the therapeutic success in gastric cancer.

METHODS

We analyzed four GEO datasets with a network-based approach and validated key CAF markers in The Cancer Genome Atlas (TCGA) and The Asian Cancer Research Group (ACRG) cohorts. We implemented stepwise multivariate Cox regression guided by a pan-cancer analysis in TCGA to identify a poor prognostic gene signature for CAF infiltration in gastric cancer. Lastly, we conducted a database search for drugs targeting the signature genes.

RESULTS

Our study revealed the COL1A1, COL1A2, COL3A1, COL5A1, FN1, and SPARC as the key CAF markers in gastric cancer. Analysis of the TCGA and ACRG cohorts validated their upregulation and poor prognostic significance. The stepwise multivariate Cox regression elucidated COL1A1 and COL5A1, together with ITGA4, Emilin1, and TSPAN9 as poor prognostic signature genes for CAF infiltration. The search on drug databases revealed collagenase clostridium histolyticum, ocriplasmin, halofuginone, natalizumab, firategrast, and BIO-1211 as the potential drugs for further investigation.

CONCLUSIONS

Our study demonstrated the central role of extracellular matrix components secreted and remodeled by CAFs in gastric cancer. The gene signature we identified in this study carries high potential as a predictive tool for poor prognosis in gastric cancer patients. Elucidating the mechanisms by which the signature genes contribute to poor patient outcomes can lead to the discovery of more potent molecular-targeted agents and increase the therapeutic success in gastric cancer.

Interpreting the Pharmacological Mechanisms of Sho-saiko-to on Thyroid Carcinoma through Combining Network Pharmacology and Experimental Evaluation

Sho-saiko-to is a well-known traditional Chinese medicine compound and is considered to have therapeutic effects against many diseases, including thyroid cancer (TC). However, the mechanisms and therapeutic targets of Sho-saiko-to against TC remain unclear. In this study, network pharmacology, molecular docking, and cell experiments were combined to predict and verify the targets and mechanisms of the active ingredients of Sho-saiko-to against TC. The results demonstrated that the main chemical ingredients of Sho-saiko-to could suppress the viability and proliferation of TC cells, promote apoptosis through the caspase3 pathway, and induce autophagy through the PI3K-AKT pathway. In addition, Sho-saiko-to could also induce the redifferentiation of anaplastic thyroid cancer. Our study provides a novel approach for treating differentiated thyroid cancer (DTC) or radioactive iodine refractory differentiated thyroid cancer (RAIR-DTC).

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.

GABRB2, a key player in neuropsychiatric disorders and beyond

The GABA receptors represent the main inhibitory system in the central nervous system that ensure synaptogenesis, neurogenesis, and the regulation of neuronal plasticity and learning. GABAA receptors are pentameric in structure and belong to the Cys-loop superfamily. The GABRB2 gene, located on chromosome 5q34, encodes the β2 subunit that combines with the α and γ subunits to form the major subtype of GABAA receptors, which account for 43% of all GABAA receptors in the mammalian brain. Each subunit probably consists of an extracellular N-terminal domain, four membrane-spanning segments, a large intracellular loop between TM3 and TM4, and an extracellular C-terminal domain. Alternative splicing of the RNA transcript of the GABRB2 gene gives rise at least to four long and short isoforms with dissimilar electrophysiological properties. Furthermore, GABRB2 is imprinted and subjected to epigenetic regulation and positive selection. It has been associated with schizophrenia first in Han Chinese, and subsequently validated in other populations. Gabrb2 knockout mice also exhibited schizophrenia-like behavior and neuroinflammation that were ameliorated by the antipsychotic drug risperidone. GABRB2 was also associated with other neuropsychiatric disorders including bipolar disorder, epilepsy, autism spectrum disorder, Alzheimer's disease, frontotemporal dementia, substance dependence, depression, internet gaming disorder, and premenstrual dysphoric disorder. Recently, it has been postulated that GABRB2 might be a potential marker for different cancer types. As GABRB2 has a pivotal role in the central nervous system and is increasingly recognized to contribute to human diseases, further understanding of its structure and function may expedite the generation of new therapeutic approaches.

Single neonatal irradiation induces long-term gene expression changes in the thyroid gland, which may be involved in the tumorigenesis

Exposure to ionizing radiation in childhood has been recognized as a risk factor for thyroid cancer. We previously demonstrated that neonatal X-irradiation induced specific deformation of the thyroid follicles. Here, we further analyzed this model to understand the possible relationship with thyroid carcinogenesis. Wistar rats were subjected to cervical X-irradiation at different ages of 1–8 weeks old and at different doses of 1.5–12 Gy. For tumor promotion, rats were fed with an iodine-deficient diet (IDD). In cervically X-irradiated neonatal rats, the size of thyroid follicles decreased, accompanied by an increase in the number of TUNEL-positive cells. Fas and Lgals3 mRNA levels increased, while Mct8 and Lat4 expressions decreased. The co-administration of IDD induced the proliferation and the upregulation in Lgals3 expression, resulting in thyroid adenoma development at 28 weeks post-exposure. Our data demonstrated that single neonatal X-irradiation induced continuous apoptotic activity in the thyroid with the long-term alternation in Fas, Mct8, Lat4, and Lgals3 mRNA expressions. Some of these changes were similar to those induced by IDD, suggesting that neonatal X-irradiation may partially act as a thyroid tumor promoter. These radiation-induced thyroidal changes may be enhanced by the combined treatment with IDD, resulting in the early development of thyroid adenoma.

Searching for essential genes and drug discovery in breast cancer and periodontitis via text mining and bioinformatics analysis

The primary purpose of the study was (1) to search for the essential genes associated with breast cancer and periodontitis, and (2) to identify candidate drugs targeted to these genes for expanding the potential drug indications. The genes related to both breast cancer and periodontitis were determined by text mining. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis were performed on these genes, and protein-protein interaction analysis was carried out to export significant module genes. Drug-gene interaction database was employed for potential drug discovery. We identified 221 genes common to both breast cancer and periodontitis. The top six significant enrichment terms and 15 enriched signal pathways were selected. Among 24 significant genes demonstrated as a gene cluster, we found SERPINA1 and TF were significantly related to poor overall survival between the relatively high and low groups in patients. Using the final two genes, 12 drugs were identified that had potential therapeutic effects. SERPINA1 and TF were screened out as essential genes related to both breast cancer and periodontitis, targeting 12 candidate drugs that may expand drug indications. Drug discovery using text mining and analysis of different databases can promote the identification of existing drugs that have the potential of administration to improve treatment in breast cancer.

Genome-Wide Histone H3K27 Acetylation Profiling Identified Genes Correlated With Prognosis in Papillary Thyroid Carcinoma

Thyroid carcinoma (TC) is the most common endocrine malignancy, and papillary TC (PTC) is the most frequent subtype of TC, accounting for 85–90% of all the cases. Aberrant histone acetylation contributes to carcinogenesis by inducing the dysregulation of certain cancer-related genes. However, the histone acetylation landscape in PTC remains elusive. Here, we interrogated the epigenomes of PTC and benign thyroid nodule (BTN) tissues by applying H3K27ac chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) along with RNA-sequencing. By comparing the epigenomic features between PTC and BTN, we detected changes in H3K27ac levels at active regulatory regions, identified PTC-specific super-enhancer-associated genes involving immune-response and cancer-related pathways, and uncovered several genes that associated with disease-free survival of PTC. In summary, our data provided a genome-wide landscape of histone modification in PTC and demonstrated the role of enhancers in transcriptional regulations associated with prognosis of PTC.

The role of PI3K signaling pathway and its associated genes in papillary thyroid cancer

BACKGROUND

One of the well-differentiated types of thyroid cancer is papillary thyroid cancer (PTC), often developed by genetic mutations and radiation.

METHODS

In this study, the public NCBI-GEO database was systematically searched. The eligible datasets were the targets for biomarker discovery associated with PI3K signaling pathway.

RESULTS

Only two datasets were suitable and passed the inclusion criteria. The meta-analysis outcomes revealed eleven upregulation and thirteen downregulation genes differentially expressed between PTC and healthy tissues. Moreover, the outcomes for survival and disease-free rates for each gene were illustrated.

CONCLUSIONS

The present research suggests a panel signature of 24 gene biomarkers in diagnosing the PTC.

Identification of key biomarkers for thyroid cancer by integrative gene expression profiles

Thyroid cancer is a frequently diagnosed malignancy and the incidence has been increased rapidly in recent years. Despite the favorable prognosis of most thyroid cancer patients, advanced patients with metastasis and recurrence still have poor prognosis. Therefore, the molecular mechanisms of progression and targeted biomarkers were investigated for developing effective targets for treating thyroid cancer. Eight chip datasets from the gene expression omnibus database were selected and the inSilicoDb and inSilicoMerging R/Bioconductor packages were used to integrate and normalize them across platforms. After merging the eight gene expression omnibus datasets, we obtained one dataset that contained the expression profiles of 319 samples (188 tumor samples plus 131 normal thyroid tissue samples). After screening, we identified 594 significantly differentially expressed genes (277 up-regulated genes plus 317 down-regulated genes) between the tumor and normal tissue samples. The differentially expressed genes exhibited enrichment in multiple signaling pathways, such as p53 signaling. By building a protein-protein interaction network and module analysis, we confirmed seven hub genes, and they were all differentially expressed at all the clinical stages of thyroid cancer. A diagnostic seven-gene signature was established using a logistic regression model with the area under the receiver operating characteristic curve (AUC) of 0.967. Seven robust candidate biomarkers predictive of thyroid cancer were identified, and the obtained seven-gene signature may serve as a useful marker for thyroid cancer diagnosis and prognosis.

Identification of key genes of papillary thyroid carcinoma by integrated bioinformatics analysis

BACKGROUND

Papillary thyroid carcinoma (PTC) is one of the fastest-growing malignant tumor types of thyroid cancer. Therefore, identifying the interaction of genes in PTC is crucial for elucidating its pathogenesis and finding more specific molecular biomarkers.

METHODS

Four pairs of PTC tissues and adjacent tissues were sequenced using RNA-Seq, and 3745 differentially expressed genes were screened (P<0.05, |logFC|>1). The enrichment analysis indicated that the vast majority of differentially expressed genes (DEGs) may play a positive role in the development of cancer. Then, the significant modules were analyzed using Cytoscape software in the protein-protein interaction network. Survival analysis, TNM analysis, and immune infiltration analysis of key genes were analyzed. And the expression of ADORA1, APOE, and LPAR5 genes were verified by qPCR in PTC compared with matching adjacent tissues.

RESULTS

Twenty-five genes were identified as hub genes with nodes greater than 10. The expression of 25 genes were verified by the GEPIA database, and the overall survival and disease-free survival analyses were conducted with Kaplan-Meier plotter. We found only three genes were confirmed with our validation and were statistically significant in PTC, namely ADORA1, APOE, and LPAR5. Further analysis found that the mRNA levels and methylation degree of these three genes were significantly correlated with the TNM staging of PTC. And these three genes were related to PTC immune infiltration. Verification of the expression of these three genes by RT-qPCR and Western blot further confirmed the reliability of our results.

CONCLUSION

Our study identified three genes that may play key regulatory roles in the development, metastasis, and immune infiltration of papillary thyroid carcinoma.

Exploration of the Potential Biomarkers of Papillary Thyroid Cancer (PTC) Based on RT2 Profiler PCR Arrays and Bioinformatics Analysis

Background

Papillary thyroid carcinoma (PTC) has increased rapidly over recent years, and radiation, hormone effects, gene mutations, and others were viewed as closely related. However, the molecular mechanisms of PTC have not been cleared. Therefore, we intended to screen more accurate key genes and pathways of PTC by combining RT² profiler PCR arrays and bioinformatics methods in this study.

Materials and Methods

RT² profiler PCR arrays were firstly analyzed to identify differential expression genes (DEGs) in PTC. RT-qPCR were performed to verify the most significant differential expression genes. The TCGA database was used to further verify for expanded data. Enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) was analyzed. To construct the protein–protein interaction (PPI) network, we used STRING and Cytoscape to make module analysis of these DEGs.

Results

Sixteen differentially expressed genes were presented in RT² profiler PCR arrays, including 13 down-regulated DEGs (DEGs) and three up-regulated DEGs (DEGs), while 13 stable DEGs were eventually verified. A total of 155 DEGs were presented in the TCGA database, including 82 up-regulated DEGs (DEGs) and 73 down-regulated DEGs (dDEGs). A total of 29 important genes were extracted after integrating these two results, GO and KEGG analyses were used to observe the possible mechanisms of action of these DEGs. The PPI network was constructed to observe hub genes. Prognostic analysis further demonstrated the involvement of these genes in the biological processes of PTC.

Conclusion

This study identified some potential molecular targets and signal pathways, which might help us raise our awareness of the mechanisms of PTC.

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.

Exploring the roles of MACIT and multiplexin collagens in stem cells and cancer

The extracellular matrix (ECM) is ubiquitously involved in neoplastic transformation, tumour growth and metastatic dissemination, and the interplay between tumour and stromal cells and the ECM is now considered crucial for the formation of a tumour-supporting microenvironment. The 28 different collagens (Col) form a major ECM protein family and display extraordinary functional diversity in tissue homeostasis as well as in pathological conditions, with functions ranging from structural support for tissues to regulatory binding activities and storage of biologically active cryptic domains releasable through ECM proteolysis. Two subfamilies of collagens, namely the plasma membrane-associated collagens with interrupted triple-helices (MACITs, including ColXIII, ColXXIII and ColXXV) and the basement membrane-associated collagens with multiple triple-helix domains with interruptions (multiplexins, including ColXV and ColXVIII), have highly interesting regulatory functions in tissue and organ development, as well as in various diseases, including cancer. An increasing, albeit yet sparse, data suggest that these collagens play crucial roles in conveying regulatory signals from the extracellular space to cells. We summarize here the current knowledge about MACITs and multiplexins as regulators of stemness and oncogenic processes, as well as their roles in influencing cell fate decisions in healthy and cancerous tissues. In addition, we present a bioinformatic analysis of the impacts of MACITs and multiplexins transcript levels on the prognosis of patients representing a wide array of malignant diseases, to aid future diagnostic and therapeutic efforts.

MiR-4500 Regulates PLXNC1 and Inhibits Papillary Thyroid Cancer Progression

Although most patients with papillary thyroid cancer (PTC) are curable, there are still a few patients showing poor outcomes and increased risk of secondary cancers after therapies. In this study, we aimed to investigate the correlation between miR-4500 and PTC and to explore its molecular functions. A total of 50 patients were included, and sonography and histological examinations were used for diagnosis. Quantitative real-time polymerase chain reaction (qRT-PCR) was applied for detection of mRNA levels while Western blotting was used for measuring protein expression. Cell proliferation was tested using CCK-8 and colony formation assays. Caspase-3 activity and nucleosomal fragmentation assays were employed to test cell apoptosis. Cell invasive ability was measured using transwell assay. MiR-4500 target was identified using luciferase assay and RNA pull-down assay. MiR-4500 expression was significantly decreased in five PTC cell lines compared with Nthy-ori 3-1 cells and in PTC tissues compared with adjacent normal thyroid tissues, respectively. Decreased expression of miR-4500 showed lower survival rate, higher cancer stage, and lymphatic metastasis. Therefore, our results implied that miR-4500 could serve as a potential biomarker for PTC prognosis. Overexpression of miR-4500 repressed colony formation, proliferation, and invasiveness of PTC cells whereas increased cell apoptosis. We identified that PLXNC1 was a direct target of miR-4500. PLXNC1 knockdown showed similar effects on cell viability, colony formation, and cell apoptosis as overexpression of miR-4500 in PTC cells. In conclusion, miR-4500 inhibits the malignant transformation of PTC cells by directly targeting and repressing PLXNC1.

Screening and identification of potential target genes in head and neck cancer using bioinformatics analysis

Head and neck cancer (HNC) is the sixth most common cancer worldwide. Recent studies on the pathogenesis of HNC have identified some biochemical associations of this disease, but the molecular mechanisms are not clear. To explore the genetic alterations in head and neck tumors, to identify new high-specificity and high-sensitivity tumor markers, and to investigate potentially effective therapeutic targets, in silico methods were used to study HNC. The GSE58911 microarray dataset was downloaded from the Gene Expression Omnibus online database to identify potential target genes in the carcinogenesis and progression of HNC. Differentially expressed genes (DEGs) were identified and functional enrichment analysis was performed. In addition, a protein-protein interaction network was also constructed, and gene analysis was undertaken using Search Tool for the Retrieval of Interacting Genes and Cytoscape. A total of 648 differentially expressed genes were identified. Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology functional enrichment analysis of DEGs included muscle system process, extracellular matrix organization, actin binding, structural molecule activity, structural constituent of muscle, extracellular region part, ECM-receptor interaction, amoebiasis, focal adhesion, drug metabolism-cytochrome P450, and chemical carcinogenesis. There were 26 hub genes identified and biological process analysis revealed that these genes were mainly enriched in extracellular matrix organization, serine-type endopeptidase activity, extracellular matrix, and complement and coagulation cascades. Survival analysis revealed that interleukin (IL)-8 (C-X-C motif chemokine ligand 8), IL1B, and serpin family A member 1 may be involved in the carcinogenesis of HNC. In summary, the DEGs and hub genes identified in the present study may increase understanding of the molecular mechanisms of development of HNC and provide potential target genes for clinical diagnosis and targeted therapy.

Papillary Thyroid Cancer: Genetic Alterations and Molecular Biomarker Investigations

Papillary thyroid cancer (PTC) is the most prevalent form of malignancy among all cancers of the thyroid. It is also one of the few cancers with a rapidly increasing incidence. PTC is usually contained within the thyroid gland and generally biologically indolent. Prognosis of the cancer is excellent, with less than 2% mortality at 5 years. However, more than 25% of patients with PTC developed a recurrence during a long term follow-up. The present article provides an updated condensed overview of PTC, which focuses mainly on the molecular alterations involved and recent biomarker investigations.

Discovery of potential transcriptional biomarkers in broiler chicken for detection of amantadine abuse based on RNA sequencing technology

The aim of this study was to identify candidate transcriptional biomarkers so as to provide a new method for monitoring amantadine residues during the feeding of broiler chicken. RNA sequencing (RNA-seq) and bioinformatic analyses were conducted to examine the transcriptomic changes and screen differentially expressed genes (DEGs) in broiler chicken breast muscle and liver tissues treated with amantadine. The results indicated that a total of 170 DEGs were screened from broiler chicken breast muscle tissues after amantadine was fed. Among the genes, 120 were up-regulated and 50 were down-regulated. The gene ontology (GO) terms for these genes mainly existed in the areas of hydrolase activity, immune reaction and chemokine activity. The significantly enriched pathways in the Kyoto Encyclopedia for Genes and Genomes (KEGG) were in phagosomes, cell adhesion molecules (CAMs), lysosomes and extracellular matrix (ECM) receptors. From the broiler chicken liver tissues, 172 DEGs were screened, among which 116 were up-regulated and 56 were down-regulated. The GO terms of these DEGs were related to functions such as catalytic activities, metabolic activities, oxidation-reduction activities, immune reactions and cofactor binding. The significantly enriched KEGG pathways existed in metabolism, CAM, ECM receptor reaction and drug metabolism-cytochrome P450. According to the fold-change (FC), significance levels, functional annotations and possible biological processes of DEGs, 11 and 9 candidate DEGs related to amantadine treatment were further screened from broiler chicken breast muscle and liver tissues, respectively. In addition, the quantitative real-time polymerase chain reaction (qRT-PCR) verification showed exactly concordant results with the RNA-seq data. Principal components analysis (PCA) on the qRT-PCR data resulted in the separation of treated samples from the control samples in both tissues. The results provided a basis for identification of transcriptional biomarkers for detecting amantadine residues in broiler chicken breast muscle and liver tissues.

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.

Genetic expression profile-based screening of genes and pathways associated with papillary thyroid carcinoma

Papillary thyroid carcinoma (PTC) is the most common subtype of thyroid cancer; however, the specific genes and signaling pathways involved in this cancer remain largely unclear. The present study analyzed three profile datasets, GSE6004, GSE29265 and GSE60542, which were comprised of 47 PTC and 41 normal thyroid tissue samples, to identify key genes and pathways associated with PTC. Initially, differentially-expressed genes (DEGs) between PTC and normal thyroid tissue were screened using R 3.4.0 (2017-04-21, R Foundation, Vienna, Austria, http://www.R-project.org/). These DEGs were then clustered by gene ontology functional terms and representative signaling pathways. Additionally, specific key gene nodes were filtered out from a constructed protein-protein interaction (PPI) network. The results identified a total of 423 shared DEGs associated with PTC, including 211 upregulated and 212 downregulated genes. These 423 genes were primarily enriched in glycosaminoglycan binding, sulfur compound binding, heparin binding, enzyme activator activity, peptidase activator activity and hsa04512: Extracellular matrix (ECM)-receptor interaction. A total of 21 central node genes were identified as key genes in the PTC disease process including complement factor D (CFD), Collagen Type I α 1 Chain (COL1A1), Extracellular Matrix Protein 1 (ECM1) and Fibronectin 1 (FN1). These genes are involved in protease binding, G-protein coupled receptor binding, extracellular matrix structural constituent and peptidase regulator activity. To conclude, using bioinformatics analysis, the present study identified candidate DEGs and critical pathways in PTC that may improve the current understanding regarding the underlying mechanisms of PTC. These genes and pathways may be used as potential therapeutic targets of PTC in the future.

Identification of key genes of papillary thyroid cancer using integrated bioinformatics analysis

OBJECTIVE

To identify novel clinically relevant genes in papillary thyroid carcinoma from public databases.

METHODS

Four original microarray datasets, GSE3678, GSE3467, GSE33630 and GSE58545, were downloaded. Differentially expressed genes (DEGs) were filtered from integrated data. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed, followed by protein-protein interaction (PPI) network construction. The CentiScape pug-in was performed to scale degree. The genes at the top of the degree distribution (≥ 95% percentile) in the significantly perturbed networks were defined as central genes. UALCAN and The Cancer Genome Atlas Clinical Explorer were used to verify clinically relevant genes and perform survival analysis.

RESULT

225 commonly changed DEGs (111 up-regulated and 114 down-regulated) were identified. The DEGs were classified into three groups by GO terms. KEGG pathway enrichment analysis showed DEGs mainly enriched in the PI3K-Akt signaling pathway, pathways in cancer, focal adhesion and proteoglycans in cancer. DEGs' protein-protein interaction (PPI) network complex was developed; six central genes (BCL2, CCND1, FN1, IRS1, COL1A1, CXCL12) were identified. Among them, BCL2, CCND1 and COL1A1 were identified as clinically relevant genes.

CONCLUSION

BCL2, CCND1 and COL1A1 may be key genes for papillary thyroid carcinoma. Further molecular biological experiments are required to confirm the function of the identified genes.

Identification of potential functional genes in papillary thyroid cancer by co-expression network analysis

Interactions between multiple genes are involved in the development of complex diseases. However, there are few analyses of gene interactions associated with papillary thyroid cancer (PTC). Weighted gene co-expression network analysis (WGCNA) is a novel and powerful method that detects gene interactions according to their co-expression similarities. In the present study, WGCNA was performed in order to identify functional genes associated with PTC using R package. First, differential gene expression analysis was conducted in order to identify the differentially expressed genes (DEGs) between PTC and normal samples. Subsequently, co-expression networks of the DEGs were constructed for the two sample groups, respectively. The two networks were compared in order to identify a poorly preserved module. Concentrating on the significant module, validation analysis was performed to confirm the identified genes and combined functional enrichment analysis was conducted in order to identify more functional associations of these genes with PTC. As a result, 1062 DEGs were identified for network construction. A brown module containing 118 highly related genes was selected as it exhibited the lowest module preservation. After validation analysis, 61 genes in the module were confirmed to be associated with PTC. Following the enrichment analysis, two PTC-related pathways were identified: Wnt signal pathway and transcriptional misregulation in cancer. LRP4, KLK7, PRICKLE1, ETV4 and ETV5 were predicted to be candidate genes regulating the pathogenesis of PTC. These results provide novel insights into the etiology of PTC and the identification of potential functional genes.

LAMB3 mediates metastatic tumor behavior in papillary thyroid cancer by regulating c-MET/Akt signals

Laminin subunit beta-3 (LAMB3) encodes one of the three subunits of LM-332, a protein of the extracellular matrix secreted by cultured human keratinocytes. While LAMB3 is involved in the invasive and metastatic abilities of several tumor types, including those found in the colon, pancreas, lung, cervix, stomach, and prostate, its mechanism of action in thyroid cancer has not been investigated previously. Our results show that LAMB3 is up-regulated in papillary thyroid cancer, and that its suppression reduces cell migration/invasion via down-regulation of epithelial‒mesenchymal transition-associated proteins (N-cadherin, vimentin, slug) and inhibition of matrix metalloproteinase 9. LAMB3 suppression also significantly decreases Akt phosphorylation and inhibits the transcription of c-MET, reducing its activation. These results suggest that LAMB3 leads to tumor invasion via Akt activation induced by the HGF/c-MET axis in papillary thyroid cancer cells. Our findings reveal a novel mechanism of action for LAMB3 in papillary thyroid cancer cells.

Integrated Characterization of MicroRNA and mRNA Transcriptome in Papillary Thyroid Carcinoma

The incidence rate of papillary thyroid carcinoma (PTC) has rapidly increased in the recent decades, and the microRNA (miRNA) is one of the potential biomarkers in this cancer. Despite good prognosis, certain features such as lymph node metastasis (LNM) and BRAF V600E mutation are associated with a poor outcome. More than 50% of PTC patients present with LNM and BRAF V600E is the most common mutation identified in this cancer. The molecular mechanisms underlying these features are yet to be elucidated. This study aims to elucidate miRNA-genes interaction networks in PTC with or without LNM and to determine the association of BRAF V600E mutation with miRNAs and genes expression profiles. Next generation sequencing was performed to characterize miRNA and gene expression profiles in 20 fresh frozen tumor and the normal adjacent tissues of PTC with LNM positive (PTC LNM-P) and PTC without LNM (PTC LNN). BRAF V600E was genotyped using Sanger sequencing. Bioinformatics integration and pathway analysis were performed to determine the regulatory networks involved. Based on network analysis, we then investigated the association between miRNA and gene biomarkers, and pathway enrichment analysis was performed to study the role of candidate biomarkers. We identified 138 and 43 significantly deregulated miRNAs (adjusted p value < 0.05; log2 fold change ≤ -1.0 or ≥1.0) in PTC LNM-P and PTC LNN compared to adjacent normal tissues, respectively. Ninety-six miRNAs had significant expression ratios of 3p-to-5p in PTC LNM-P as compared to PTC LNN. In addition, ribosomal RNA-reduced RNA sequencing analysis revealed 699 significantly deregulated genes in PTC LNM-P versus normal adjacent tissues, 1,362 genes in PTC LNN versus normal adjacent tissue, and 1,576 genes in PTC LNM-P versus PTC LNN. We provide the evidence of miRNA and gene interactions, which are involved in LNM of papillary thyroid cancer. These findings may lead to better understanding of carcinogenesis and metastasis processes. This study also complements the existing knowledge about deregulated miRNAs in papillary thyroid carcinoma development.