Meta-analysis and meta-review of thyroid cancer gene expression profiling studies identifies important diagnostic biomarkers

Role of glutaminyl-peptide cyclotransferase in breast cancer doxorubicin sensitivity

Doxorubicin (DOX) is one of the most effective and widely used chemotherapeutic drugs. However, DOX resistance is a critical risk problem for breast cancer treatment. Previous studies have demonstrated that metadherin (MTDH) involves in DOX resistance in breast cancer, but the exact mechanism remains unclear. In this study, we found that glutaminyl-peptide cyclotransferase (QPCT) was a MTDH DOX resistance-related downstream gene in breast cancer. Elevated expression of QPCT was found in the GEPIA database, breast cancer tissue, and breast cancer cells. Clinical data showed that QPCT expression was positively associated with poor prognosis in DOX-treated patients. Overexpression of QPCT could promote the proliferation, invasion and migration, and reduce DOX sensitivity in MCF-7 and MDA-MB-231 cells. Mechanistically, MTDH positively regulates the expressions of NF-κB (p65) and QPCT, and NF-κB (p65) directly regulates the expression of QPCT. Therefore, MTDH/NF-κB (p65)/QPCT signal axis was proposed. Collectively, our findings delineate the mechanism by which the MTDH/NF-κB (p65) axis regulate QPCT signaling and suggest that this complex may play an essential role in breast cancer progression and affect DOX sensitivity.

miRNAs in patients with alcoholic liver disease: a systematic review and meta-analysis

INTRODUCTION

Alcoholic liver disease (ALD) encompasses a spectrum of liver conditions, including liver steatosis, alcoholic hepatitis (AH), fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). microRNAs (miRNAs) have garnered significant interest as potential biomarkers for ALD.

METHODS

We searched PubMed, Embase, Web of Science and Cochrane Central Register of Controlled Trials (CENTRAL) systemically from inception to June 2024. All extracted data was stratified according to the stages of ALD. The vote-counting strategy performed a meta-analysis on miRNA expression profiles.

RESULTS

We included 40 studies. In serum of individuals with alcohol-use vs. no alcohol-use, miRNA-122 and miRNA-155 were upregulated, and miRNA-146a was downregulated. In patients with ALD vs. healthy controls, miRNA-122 and miRNA-155 were also upregulated, and miRNA-146a was downregulated. However, in patients with AH vs. healthy individuals, only the serum miRNA-122 level was upregulated. Due to insufficient data on diagnostic accuracy, we failed to conclude the ability of miRNAs to distinguish between different stages of ALD-related liver fibrosis. The results for ALD-related HCC were also insufficient and controversial.

CONCLUSIONS

Circulating miRNA-122 was the most promising biomarker to manage individuals with ALD. More studies were needed for the diagnostic accuracy of miRNAs in ALD.

REGISTRATION

This protocol was registered on the International Prospective Register of Systematic Reviews (PROSPERO) (www.crd.york.ac.uk/prospero/) with registration number CRD42023391931.

A Systematic Review and Meta-Analysis of microRNA Profiling Studies in Chronic Kidney Diseases

Chronic kidney disease (CKD) represents an increasing health burden. Evidence suggests the importance of miRNA in diagnosing CKD, yet the reports are inconsistent. This study aimed to determine novel miRNA biomarkers and potential therapeutic targets from hypothesis-free miRNA profiling studies in human and murine CKDs. Comprehensive literature searches were conducted on five databases. Subgroup analyses of kidney diseases, sample types, disease stages, and species were conducted. A total of 38 human and 12 murine eligible studies were analyzed using Robust Rank Aggregation (RRA) and vote-counting analyses. Gene set enrichment analyses of miRNA signatures in each kidney disease were conducted using DIANA-miRPath v4.0 and MIENTURNET. As a result, top target genes, Gene Ontology terms, the interaction network between miRNA and target genes, and molecular pathways in each kidney disease were identified. According to vote-counting analysis, 145 miRNAs were dysregulated in human kidney diseases, and 32 were dysregulated in murine CKD models. By RRA, miR-26a-5p was significantly reduced in the kidney tissue of Lupus nephritis (LN), while miR-107 was decreased in LN patients' blood samples. In both species, epithelial-mesenchymal transition, Notch, mTOR signaling, apoptosis, G2/M checkpoint, and hypoxia were the most enriched pathways. These miRNA signatures and their target genes must be validated in large patient cohort studies.

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.

BioVDB: biological vector database for high-throughput gene expression meta-analysis

High-throughput sequencing has created an exponential increase in the amount of gene expression data, much of which is freely, publicly available in repositories such as NCBI's Gene Expression Omnibus (GEO). Querying this data for patterns such as similarity and distance, however, becomes increasingly challenging as the total amount of data increases. Furthermore, vectorization of the data is commonly required in Artificial Intelligence and Machine Learning (AI/ML) approaches. We present BioVDB, a vector database for storage and analysis of gene expression data, which enhances the potential for integrating biological studies with AI/ML tools. We used a previously developed approach called Automatic Label Extraction (ALE) to extract sample labels from metadata, including age, sex, and tissue/cell-line. BioVDB stores 438,562 samples from eight microarray GEO platforms. We show that it allows for efficient querying of data using similarity search, which can also be useful for identifying and inferring missing labels of samples, and for rapid similarity analysis.

PROS1, a clinical prognostic biomarker and tumor suppressor, is associated with immune cell infiltration in breast cancer: A bioinformatics analysis combined with experimental verification

BACKGROUND

PROS1 is an encoding gene that can generate protein S. This protein is a glycoprotein found in plasma that conducts physiological functions with vitamin K. However, the impact of its expression remains absent in the progression and prognosis of breast cancer (BC).

METHODS

In this study, we comprehensively explored the expression of PROS1 in BC and its relationship with BC patient survival, prognosis, and other clinicopathological features. We investigated how PROS1 influenced the malignant biological behavior of BC cells. A series of enrichment analyses were conducted, and the immune landscape was explored in BC affected by PROS1. We also determined correlations between PROS1 and common drug sensitivities used for BC treatments.

RESULTS

PROS1 had low expression in BC, which tended to result in poor survival of BC patients. Overexpressed PROS1 inhibited the migration and invasion of BC cells as well as the epithelial-mesenchymal transition process by downregulating SNAIL. Functional enrichment analyses revealed that PROS1 was more active in extracellular matrix (ECM) organization and structural constituent, ECM-receptor interaction, and other pathways with its related genes. PROS1 was also found to affect immune activity, including various immune cells infiltrating BC. BC patients with high PROS1 expression tended to have lower IC50 values of three common medications and obtained better efficacy.

CONCLUSIONS

PROS1 can become a promising prognostic factor and a possible therapeutic target in BC patients and suppress BC cell metastatic potential. In addition, PROS1 is a crucial factor in immune infiltration in BC.

Downregulation of cellular retinoic acid binding protein 1 fosters epithelial-mesenchymal transition in thyroid cancer

Cellular retinoic acid binding protein 1 (CRABP1) participates in the regulation of retinoid signaling. Previous studies showed conflicting results regarding the role of CRABP1 in tumor biology, including protumorigenic and tumor-suppressive effects in different types of cancer. Our bioinformatics analyses suggested that CRABP1 expression was downregulated in thyroid cancer. Ectopic expression of CRABP1 in thyroid cancer cells suppressed migratory and invasive activity without affecting cell growth or cell cycle distribution. In transformed normal thyroid follicular epithelial cells, silencing of CRABP1 expression increased invasiveness. Additionally, CRABP1 overexpression was associated with downregulation of the mesenchymal phenotype. Kinase phosphorylation profiling indicated that CRABP1 overexpression was accompanied by a decrease in phosphorylation of epidermal growth factor (EGF) receptor and downstream phosphorylation of Akt, STAT3, and FAK, which were reversed by exogenous EGF treatment. Immunohistochemical analysis of our tissue microarrays revealed an inverse association between CRABP1 expression and disease stage of differentiated thyroid cancer. Taken together, our results suggest that CRABP1 expression is aberrantly lost in thyroid cancer, and this downregulation promotes the epithelial-mesenchymal transition at least partly through modulating EGF receptor signaling.

Identification of Serpin peptidase inhibitor clade A member 1 (SERPINA1) might be a poor prognosis biomarker promoting the progression of papillary thyroid cancer

BACKGROUND

Papillary thyroid carcinoma (PTC) is the most prevalent malignancy within the endocrine system, exhibiting a rapid growth rate in recent years. Serpin peptidase inhibitor clade A member 1 (SERPINA1) has been previously proposed as a diagnostic biomarker; however, it's potential molecular relevance and biological function in PTC remains largely unexplored.

METHODS

Our study utilized multi-omics bioinformatic data from several public databases, supplemented with transcriptional profiles using our local cohort comprising 79 paired PTC samples.

RESULTS

Using multi-omics profiling of a PTC cohort, we have identified SERPINA1 as a potential oncogene involved in PTC progression. Our clinical analysis revealed a significant association between SERPINA1 expression and mutations in BRAFV600E and RAS. Furthermore, SERPINA1 level was correlated with clinicopathological factors in patients with PTC and with a worse prognosis in early-stage patients. Functionally, we found a strong correlation between SERPINA1 expression and increased infiltration of dendritic cells and regulatory T-cells, suggesting an elevated level of immune infiltration. Moreover, SERPINA1 knockdown reduced the proliferative and migrational ability of PTC cells in vitro.

CONCLUSION

Our study highlights the high expression of SERPINA1 in PTC and its potential role in shaping the immune microenvironment, thereby promoting disease progression. These findings suggest that SERPINA1 could serve as a promising therapeutic target for intervention in PTC.

Clinical significance and diagnostic value of QPCT, SCEL and TNFRSF12A in papillary thyroid cancer

PURPOSE

To identify specific novel genes that could be used as diagnostic and prognostic factors in papillary thyroid carcinoma (PTC).

METHODS

Screening of differential genes by RNA sequencing (RNA-Seq) in normal thyroid, Hashimoto's thyroiditis, PTC combined with Hashimoto's thyroiditis and PTC tissues. The genes QPCT, SCEL and TNFRSF12A were selected by qRT-PCR and immunohistochemical pre-experiments. The GEPIA2 database, qRT-PCR, and immunohistochemical studies were used to confirm the target genes QPCT, SCEL, and TNFRSF12A. ROC curves were used to assess the diagnostic usefulness of these 3 genes for PTC in more detail.

RESULTS

Functional enrichment analysis showed that QPCT, SCEL and TNFRSF12A were enriched in the pathways for peptidyl-pyroglutamic acid biosynthesis, keratinocyte differentiation, WNT signaling, apoptosis. GEPIA2 database analysis revealed that QPCT, SCEL and TNFRSF12A were high in thyroid cancer, and TC patients with lower TNFRSF12A levels had short survival. QPCT, SCEL and TNFRSF12A were elevated in PTC and thyroid adenoma. The mRNA diagnostic values were as follows: for QPCT, AUROC = 0.891, 95% CI, 0.835-0.947; for SCEL, AUROC = 0.921, 95% CI, 0.869-0.974; for TNFRSF12A, AUROC = 0.884, 95% CI, 0.809-0.958. Immunohistochemical results showed that QPCT, SCEL, and TNFRSF12A differed to varying degrees between subgroups of thyroid tissue. SCEL was associated with BRAF V600E mutation status and stratification of recurrence risk, while TNFRSF12A was associated with Cyclin D1. The protein diagnostic values were as follows: for QPCT, AUROC = 0.752, 95% CI, 0.685-0.819; for SCEL, AUROC = 0.715, 95% CI, 0.645-0.784; for TNFRSF12A, AUROC = 0.660, 95% CI, 0.587-0.734.

CONCLUSION

QPCT, SCEL and TNFRSF12A are expected to be diagnostic markers for PTC.

Integration of Stemness Gene Signatures Reveals Core Functional Modules of Stem Cells and Potential Novel Stemness Genes

Stem cells encompass a variety of different cell types which converge on the dual capacity to self-renew and differentiate into one or more lineages. These characteristic features are key for the involvement of stem cells in crucial biological processes such as development and ageing. To decipher their underlying genetic substrate, it is important to identify so-called stemness genes that are common to different stem cell types and are consistently identified across different studies. In this meta-analysis, 21 individual stemness signatures for humans and another 21 for mice, obtained from a variety of stem cell types and experimental techniques, were compared. Although we observed biological and experimental variability, a highly significant overlap between gene signatures was identified. This enabled us to define integrated stemness signatures (ISSs) comprised of genes frequently occurring among individual stemness signatures. Such integrated signatures help to exclude false positives that can compromise individual studies and can provide a more robust basis for investigation. To gain further insights into the relevance of ISSs, their genes were functionally annotated and connected within a molecular interaction network. Most importantly, the present analysis points to the potential roles of several less well-studied genes in stemness and thus provides promising candidates for further experimental validation.

Candidate MicroRNA Biomarkers in Lupus Nephritis: A Meta-analysis of Profiling Studies in Kidney, Blood and Urine Samples

CONTEXT

Lupus nephritis (LN) is a kidney disease caused by systemic lupus erythematosus in which kidneys are attacked by the immune system. So far, various investigations have reported altered miRNA expression profiles in LN patients and different miRNAs have been introduced as biomarkers and/or therapeutic targets in LN. The aim of this study was to introduce a consensus panel of potential miRNA biomarkers by performing a meta-analysis of miRNA profiles in the LN patients.

MATERIALS AND METHODS

A comprehensive literature review approach was performed to find LN-related miRNA expression profiles in renal tissues, blood, and urine samples. After selecting the eligible studies and performing the data extraction, meta-analysis was done based on the vote-counting rank strategy as well as meta-analysis of p-values. The meta-miRNAs and their related genes were subjected to functional enrichment analyses and network construction.

RESULTS

The results of the meta-analysis of 41 studies were three lists of consensus miRNAs with altered expression profiles in the various tissue samples of LN patients (meta-analysis of p-values < 0.05). Of the 13 studies on kidney tissue, the meta-miRNAs were let-7a, miR-198, let-7e, miR-145, and miR-26a. In addition, meta-miRNAs of miR-199a, miR-21, miR-423, miR-1260b, miR-589, miR-150, miR-155, miR-146a, and miR-183 from 21 studies on blood samples, and miR-146a, miR-204, miR-30c, miR-3201, and miR-1273e from 11 studies on urine samples can be considered as non-invasive biomarker panels for LN. Functional enrichment analysis on the meta-miRNA lists confirmed the involvement of their target genes in nephropathy-related signaling pathways.

CONCLUSION

Using a meta-analytical approach, our study proposes three meta-miRNA panels that could be the target of further research to assess their potential as therapeutic targets/biomarkers in LN disease.

A meta-analysis of mRNA expression profiling studies in sheep with different FecB genotypes

The FecB mutation in the sheep BMPRIB is strongly correlated with high ovulation traits but its mechanism remains unclear. This study explored differentially expressed genes (DEGs) and their associated molecular mechanisms that may be involved in FecB mutation-induced high ovulation from the perspective of the hypothalamic-pituitary-gonadal (HPG) axis by conducting a systematic review and meta-analysis. The PubMed, EMBASE, CNKI, WanFang, and CBM databases were searched for eligible articles published before August 2022, focusing on mRNA sequencing of different tissues in the HPG axis in sheep with different FecB genotypes. A total of 6555 DEGs were identified from the analysis of six published articles and experimental results from our laboratory. The DEGs were screened by vote-counting rank and robust rank aggregation. Among these, in the follicular phase, FKBP5, CDCA7 and CRABP1 were upregulated in the hypothalamus. INSM2 was upregulated, while LDB3 was downregulated in the pituitary. CLU, SERPINA14, PENK, INHA and STAR were upregulated, while FERMT2 and NPY1R were downregulated in the ovary. On the HPG axis, TAC1 was upregulated and NPNT was downregulated. Many DEGs were found in sheep with different FecB genotypes. The genes FKBP5, CDCA7, CRABP1, INSM2, LDB3, CLU, SERPINA14, PENK, INHA, STAR, FERMT2, NPY1R, TAC1 and NPNT, may be associated with FecB mutation-induced high ovulation in different tissues. These candidate genes will further improve the mechanism of multiple fertility traits induced by the FecB mutation from the perspective of the HPG axis.

Long noncoding RNA as a potential diagnostic tool for prostate cancer: a systematic review and meta-analysis

PURPOSE

To identify consistently expressed lncRNAs and suitable lncRNAs with high sensitivity and specificity from multiple independent studies as potential biomarkers for PCa diagnostics.

METHODS

We searched multiple electronic databases including PubMed, Web of Science, EMBASE, Cochrane Library, CNKI, CQVIP, Wanfang, and CBMdisc for studies published up to July 2022. The quality of the included studies was assessed by two independent reviewers based on the QUADAS-2 tool using Review Manager 5.3. A vote-counting method was used based on the ranking of potential molecular biomarkers. The top-ranked lncRNAs were further assessed for diagnostic value using Meta-disc version 1.4 software.

RESULTS

Among the 26 included studies, 2 circulating lncRNAs (PCA3 and MALAT-1) were reported 3 or more times in PCa patients versus non-PCa patients. In further analysis, the areas under the curve of the summary receiver operating characteristic curves for PCA3 and MALAT-1 distinguishing PCa patients were 0.775 and 0.771, respectively.

CONCLUSIONS

Based on the current evidence, PCA3 and MALAT-1 are reliable lncRNAs for the diagnosis of PCa.

Identification of novel characteristic biomarkers and immune infiltration profile for the anaplastic thyroid cancer via machine learning algorithms

PURPOSE

Anaplastic thyroid cancer (ATC) is a rare and lethal malignant cancer. In recent years, the application of molecular-driven targeted therapy and immunotherapy has markedly improved the prognosis of ATC. This study aimed to identify characteristic genes for ATC diagnosis and revealed the role of ATC characteristic genes in drug sensitivity and immune cell infiltration.

METHODS

We downloaded ATC RNA-sequencing data from the GEO database. Following the combination and normalization of the dataset, we first divided the combined datasets into the training cohort and the validation cohort. We identified differentially expressed genes (DEGs) in ATC by differential expression analysis in the training cohort. We used two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) to identify ATC characteristic genes. The CIBERSORT algorithm was performed to calculate the abundance of various immune cells in ATC. Finally, we validated the expression of ATC characteristic genes by quantitative RT-PCR (RT-qPCR) in ATC cell lines and immunohistochemistry (IHC).

RESULTS

A total of 425 DEGs were identified in the training cohort, including 240 upregulated genes and 185 downregulated genes. Four ATC characteristic genes (ADM, PXDN, MMP1, and TFF3) were identified, and their diagnostic value was validated in the validation cohort (AUC in ROC analysis > 0.75). We established a practical gene expression-based nomogram to accurately predict the probability of ATC. We also found that ATC characteristic biomarkers are associated with the tumor immune microenvironment and drug sensitivity.

CONCLUSION

ADM, PXDN, MMP1, and TFF3 might serve as potential ATC diagnostic biomarkers and may be helpful for ATC molecular targeted therapy and immunotherapy.

The role of miR-128 in cancer development, prevention, drug resistance, and immunotherapy

A growing body of evidence has revealed that microRNA (miRNA) expression is dysregulated in cancer, and they can act as either oncogenes or suppressors under certain conditions. Furthermore, some studies have discovered that miRNAs play a role in cancer cell drug resistance by targeting drug-resistance-related genes or influencing genes involved in cell proliferation, cell cycle, and apoptosis. In this regard, the abnormal expression of miRNA-128 (miR-128) has been found in various human malignancies, and its verified target genes are essential in cancer-related processes, including apoptosis, cell propagation, and differentiation. This review will discuss the functions and processes of miR-128 in multiple cancer types. Furthermore, the possible involvement of miR-128 in cancer drug resistance and tumor immunotherapeutic will be addressed.

Dental implant material related changes in molecular signatures in peri-implantitis - A systematic review and integrative analysis of omics in-vitro studies

OBJECTIVE

Since peri-implantitis differs clinically and histopathologically from periodontitis, implant wear debris is considered to play a role in the destructive processes. This work aims to systematically review if titanium particles affect oral-related cells through changes in molecular signatures (e.g., transcriptome, proteome, epigenome), thereby promoting peri-implantitis.

METHODS

Leveraging three literature databases (Medline, Embase, Cochrane) a systematic search based on a priori defined PICOs was conducted: '-omics' studies examining titanium exposure in oral-related cells. After risk of bias assessments, lists of differentially expressed genes, proteins, and results of functional enrichment analyses were compiled. The significance of overlapping genes across multiple studies was assessed via Monte Carlo simulation and their ranking was verified using rank aggregation.

RESULTS

Out of 2104 screened articles we found 12 eligible publications. A significant overlap of gene expression in oral-related cells exposed to titanium particles was found in four studies. Furthermore, changes in biological processes like immune/inflammatory or stress response as well as toll-like receptor (TLR) and mitogen-activated protein kinase (MAPK) signaling pathways were linked to titanium in transcriptome and proteome studies. Epigenetic changes caused by titanium were detected but inconsistent.

CONCLUSION

An influence of titanium implant wear debris on the development and progression of peri-implantitis is plausible but needs to be proven in further studies. Limitations arise from small sample sizes of included studies and insufficient publication of re-analyzable data.

CircRTN1 acts as a miR-431-5p sponge to promote thyroid cancer progression by upregulating TGFA

PURPOSE

This study aimed to explore the role and underlying mechanism of circular RNA (circRNA) reticulon 1 (circRTN1) in thyroid cancer (TC).

METHODS

The expression levels of circRTN1, microRNA-431-5p (miR-431-5p), and transforming growth factor-alpha (TGFA) mRNA were measured by quantitative real-time PCR (qRT-PCR). Cell proliferation was evaluated using colony formation and 5-ethynyl-2'-deoxyuridine (EdU) assays. Cell apoptosis was analyzed using flow cytometry. Cell migration and invasion were measured using the transwell assay. The protein levels of ki-67, Bax, matrix metalloproteinase 2 (MMP-2), and TGFA were detected using Western blot assay. The interaction between miR-431-5p and circRTN1 or TGFA was verified by dual-luciferase reporter assay and RNA immunoprecipitation (RIP) assay. The effect of circRTN1on TC in vivo was explored via xenograft tumor assay.

RESULTS

The expression of circRTN1 was increased in TC tissues and cells. Knockdown of circRTN1 suppressed TC cell proliferation, migration, and invasion, and increased cell apoptosis. MiR-431-5p was a target of circRTN1, and miR-431-5p downregulation reversed the role of circRTN1 knockdown in TC cells. TGFA was identified as a direct target of miR-431-5p, and miR-431-5p exerted the anti-tumor role in TC cells by downregulating TGFA. Moreover, circRTN1 sponged miR-431-5p to regulate TGFA expression. Furthermore, circRTN1 knockdown inhibited tumor growth in vivo.

CONCLUSION

CircRTN1 acted as a cancer-promoting circRNA in TC by regulating the miR-431-5p/TGFA axis, providing a potential therapeutic strategy for TC treatment.

Heat Shock Transcription Factor 2 Is Significantly Involved in Neurodegenerative Diseases, Inflammatory Bowel Disease, Cancer, Male Infertility, and Fetal Alcohol Spectrum Disorder: The Novel Mechanisms of Several Severe Diseases

HSF (heat shock transcription factor or heat shock factor) was discovered as a transcription factor indispensable for heat shock response. Although four classical HSFs were discovered in mammals and two major HSFs, HSF1 and HSF2, were cloned in the same year of 1991, only HSF1 was intensively studied because HSF1 can give rise to heat shock response through the induction of various HSPs' expression. On the other hand, HSF2 was not well studied for some time, which was probably due to an underestimate of HSF2 itself. Since the beginning of the 21st century, HSF2 research has progressed and many biologically significant functions of HSF2 have been revealed. For example, the roles of HSF2 in nervous system protection, inflammation, maintenance of mitosis and meiosis, and cancer cell survival and death have been gradually unveiled. However, we feel that the fact HSF2 has a relationship with various factors is not yet widely recognized; therefore, the biological significance of HSF2 has been underestimated. We strongly hope to widely communicate the significance of HSF2 to researchers and readers in broad research fields through this review. In addition, we also hope that many readers will have great interest in the molecular mechanism in which HSF2 acts as an active transcription factor and gene bookmarking mechanism of HSF2 during cell cycle progression, as is summarized in this review.

How does plasticity of migration help tumor cells to avoid treatment: Cytoskeletal regulators and potential markers

Tumor shrinkage as a result of antitumor therapy is not the only and sufficient indicator of treatment success. Cancer progression leads to dissemination of tumor cells and formation of metastases - secondary tumor lesions in distant organs. Metastasis is associated with acquisition of mobile phenotype by tumor cells as a result of epithelial-to-mesenchymal transition and further cell migration based on cytoskeleton reorganization. The main mechanisms of individual cell migration are either mesenchymal, which depends on the activity of small GTPase Rac, actin polymerization, formation of adhesions with extracellular matrix and activity of proteolytic enzymes or amoeboid, which is based on the increase in intracellular pressure caused by the enhancement of actin cortex contractility regulated by Rho-ROCK-MLCKII pathway, and does not depend on the formation of adhesive structures with the matrix, nor on the activity of proteases. The ability of tumor cells to switch from one motility mode to another depending on cell context and environmental conditions, termed migratory plasticity, contributes to the efficiency of dissemination and often allows the cells to avoid the applied treatment. The search for new therapeutic targets among cytoskeletal proteins offers an opportunity to directly influence cell migration. For successful treatment it is important to assess the likelihood of migratory plasticity in a particular tumor. Therefore, the search for specific markers that can indicate a high probability of migratory plasticity is very important.

Transcriptomic Data Meta-Analysis Sheds Light on High Light Response in Arabidopsis thaliana L

The availability and intensity of sunlight are among the major factors of growth, development and metabolism in plants. However, excessive illumination disrupts the electronic balance of photosystems and leads to the accumulation of reactive oxygen species in chloroplasts, further mediating several regulatory mechanisms at the subcellular, genetic, and molecular levels. We carried out a comprehensive bioinformatic analysis that aimed to identify genetic systems and candidate transcription factors involved in the response to high light stress in Arabidopsis thaliana L. using resources GEO NCBI, string-db, ShinyGO, STREME, and Tomtom, as well as programs metaRE, CisCross, and Cytoscape. Through the meta-analysis of five transcriptomic experiments, we selected a set of 1151 differentially expressed genes, including 453 genes that compose the gene network. Ten significantly enriched regulatory motifs for TFs families ZF-HD, HB, C2H2, NAC, BZR, and ARID were found in the promoter regions of differentially expressed genes. In addition, we predicted families of transcription factors associated with the duration of exposure (RAV, HSF), intensity of high light treatment (MYB, REM), and the direction of gene expression change (HSF, S1Fa-like). We predicted genetic components systems involved in a high light response and their expression changes, potential transcriptional regulators, and associated processes.

FcGBP and VCAM-1 are ponderable biomarkers for differential diagnosis of alcoholic liver cirrhosis

BACKGROUND/ AIMS

Early diagnosis of alcoholic liver cirrhosis (ALD) and coexisting ALD and hepatitis B virus-induced cirrhosis (ALD+HBV) is primordial for an optimal management of these conditions. However, the lack of specific noninvasive biomarkers coupled with the inaccuracy of self-reported alcohol consumption make the early diagnosis of these pathologies difficult. This study aimed to identify biomarkers to diagnose ALD and differentiate ALD+HBV from HBV.

METHODS

Proteomics mass spectrometry technique was used to identify specific proteins of ALD by contrasting serums of ALD to that of healthy subjects. The accuracy of the selected proteins in diagnosing ALD and discriminating ALD+HBV from HBV was assessed in two independent cohorts using the area under the receiver operator characteristic curve (AUROC).

RESULTS

452 cirrhotic and normal subjects were enrolled in this study. The proteomic results revealed that FcGBP and VCAM-1 were the highest overexpressed proteins while comparing ALD samples to the healthy cohort. The combination of these two biomarkers had an AUROC of 0.986 (P < 0.001, sensitivity: 97.2%, specificity: 100%) in identifying ALD from the healthy cohort, and AUROC of 0.781 (P < 0.001, sensitivity: 81.8%, specificity: 77.0%) in differentiating ALD+HBV from HBV. This combination was more accurate than the combination of AST/ALT, MCV and GGT (ALD vs healthy, AUROC = 0.898; ALD+HBV vs HBV, AUROC = 0.599). The discrimination performance of this combination was further validated in another independent cohort.

CONCLUSION

FcGBP and VCAM-1 are two promising biomarkers in the diagnosis of ALD and in the differentiating of ALD+HBV from HBV subjects.

Construction of the Classification Model Using Key Genes Identified Between Benign and Malignant Thyroid Nodules From Comprehensive Transcriptomic Data

Thyroid nodules are present in upto 50% of the population worldwide, and thyroid malignancy occurs in only 5–15% of nodules. Until now, fine-needle biopsy with cytologic evaluation remains the diagnostic choice to determine the risk of malignancy, yet it fails to discriminate as benign or malignant in one-third of cases. In order to improve the diagnostic accuracy and reliability, molecular testing based on transcriptomic data has developed rapidly. However, gene signatures of thyroid nodules identified in a plenty of transcriptomic studies are highly inconsistent and extremely difficult to be applied in clinical application. Therefore, it is highly necessary to identify consistent signatures to discriminate benign or malignant thyroid nodules. In this study, five independent transcriptomic studies were combined to discover the gene signature between benign and malignant thyroid nodules. This combined dataset comprises 150 malignant and 93 benign thyroid samples. Then, there were 279 differentially expressed genes (DEGs) discovered by the feature selection method (Student’s t test and fold change). And the weighted gene co-expression network analysis (WGCNA) was performed to identify the modules of highly co-expressed genes, and 454 genes in the gray module were discovered as the hub genes. The intersection between DEGs by the feature selection method and hub genes in the WGCNA model was identified as the key genes for thyroid nodules. Finally, four key genes (ST3GAL5, NRCAM, MT1F, and PROS1) participated in the pathogenesis of malignant thyroid nodules were validated using an independent dataset. Moreover, a high-performance classification model for discriminating thyroid nodules was constructed using these key genes. All in all, this study might provide a new insight into the key differentiation of benign and malignant thyroid nodules.

MicroRNA expression profiling in myopia: a meta-analysis and systematic review

BACKGROUND

Myopia (nearsightedness) is currently the most common human eye disorder worldwide. In the recent years, several studies have addressed the role of microRNAs (miRNAs) in the pathogenesis of myopia.

OBJECTIVES

The aim of this study was to perform a meta-analysis on the miRNA expression profiling studies in myopia to identify commonly dysregulated miRNAs in myopic tissues.

METHOD

Seven independent studies were included in the meta-analysis. A vote-counting strategy were employed as the meta-analysis method. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and Gene Ontology (GO) functional enrichment analysis were performed to identify the pathways most strongly affected by the dysregulated mouse miRNAs.

RESULTS

According to the vote-counting method, eighteen miRNAs were reported in at least two studies with the consistent direction, of which 13 miRNAs were commonly up-regulated in myopic samples compared with control samples and five miRNAs were commonly down-regulated. Subgroup analyses divided and compared the differentially expressed miRNAs according to species (human and animal) and ocular tissue types. The KEGG analysis showed that the dysregulated mouse miRNAs were most enriched in extracellular matrix (ECM)-receptor interaction signal pathway. The most enriched GO processes regulated by the dysregulated mouse miRNAs was cellular protein modification process.

CONCLUSIONS

Our meta-analysis recommends several miRNAs may provide some clues of the potential biomarkers in myopia. Further mechanistic studies are warranted to elucidate the biological role of the dysregulated miRNAs in the development of myopia.

Construction and validation of a novel aging-related gene signature and prognostic nomogram for predicting the overall survival in ovarian cancer

BACKGROUND

Ovarian cancer (OC) is the most lethal gynecological malignancy. The objective of this study was to establish and validate an individual aging-related gene signature and a clinical nomogram that can powerfully predict independently the overall survival rate of patients with ovarian cancer.

METHODS

Data on transcriptomic profile and relevant clinical information were retrieved from The Cancer Genome Atlas (TCGA) database as a training group, and the same data from three public Gene Expression Omnibus (GEO) databases as validation groups. Univariate Cox regression analysis, lasso regression analysis, and multiple multivariate Cox analysis were analyzed sequentially to select the genes to be included in the aging-associated signature. A risk scoring model was established and verified, the predictive value of the model was evaluated, and a clinical nomogram was established.

RESULTS

We found eight genes that were most relevant to prognosis and constructed an eight-mRNA signature. Based on the model, each OC patient's risk score was able to be calculated and patients were split into groups of low and high risks with a distinct outcome. Survival analysis confirmed that the outcome of patients in the high-risk group was dramatically shorter than that of those in the low-risk group, and the eight-mRNA signature can be considered as a powerful and independent predictor that could predict the outcome of OC patient. Additionally, the risk score and age can be used to construct a clinical nomogram as a simpler tool for predicting prognosis. We also explored the association between the risk score and immunity and drug sensitivity.

CONCLUSION

This study suggested that the aging-related gene signature could be used as an intervention point and latent prognostic predictor in OC, which may provide new perceptions for postoperative treatment strategies.

Comprehensive analysis of abnormal expression, prognostic value and oncogenic role of the hub gene FN1 in pancreatic ductal adenocarcinoma via bioinformatic analysis and in vitro experiments

Background

Pancreatic ductal adenocarcinoma (PDAC) is one of the most commonly diagnosed cancers with a poor prognosis worldwide. Although the treatment of PDAC has made great progress in recent years, the therapeutic effects are still unsatisfactory. Methods. In this study, we identified differentially expressed genes (DEGs) between PDAC and normal pancreatic tissues based on four Gene Expression Omnibus (GEO) datasets (GSE15471, GSE16515, GSE28735 and GSE71729). A protein–protein interaction (PPI) network was established to evaluate the relationship between the DEGs and to screen hub genes. The expression levels of the hub genes were further validated through the Gene Expression Profiling Interactive Analysis (GEPIA), ONCOMINE and Human Protein Atlas (HPA) databases, as well as the validation GEO dataset GSE62452. Additionally, the prognostic values of the hub genes were evaluated by Kaplan–Meier plotter and the validation GEO dataset GSE62452. Finally, the mechanistic roles of the most remarkable hub genes in PDAC were examined through in vitro experiments.

Results

We identified the following nine hub genes by performing an integrated bioinformatics analysis: COL1A1, COL1A2, FN1, ITGA2, KRT19, LCN2, MMP9, MUC1 and VCAN. All of the hub genes were significantly upregulated in PDAC tissues compared with normal pancreatic tissues. Two hub genes (FN1 and ITGA2) were associated with poor overall survival (OS) rates in PDAC patients. Finally, in vitro experiments indicated that FN1 plays vital roles in PDAC cell proliferation, colony formation, apoptosis and the cell cycle.

Conclusions

In summary, we identified two hub genes that are associated with the expression and prognosis of PDAC. The oncogenic role of FN1 in PDAC was first illustrated by performing an integrated bioinformatic analysis and in vitro experiments. Our results provide a fundamental contribution for further research aimed finding novel therapeutic targets for overcoming PDAC.

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.

A Transcriptomic Analysis of Head and Neck Squamous Cell Carcinomas for Prognostic Indications

Survival analysis of the Cancer Genome Atlas (TCGA) dataset is a well-known method for discovering gene expression-based prognostic biomarkers of head and neck squamous cell carcinoma (HNSCC). A cutoff point is usually used in survival analysis for patient dichotomization when using continuous gene expression values. There is some optimization software for cutoff determination. However, the software's predetermined cutoffs are usually set at the medians or quantiles of gene expression values. There are also few clinicopathological features available in pre-processed datasets. We applied an in-house workflow, including data retrieving and pre-processing, feature selection, sliding-window cutoff selection, Kaplan-Meier survival analysis, and Cox proportional hazard modeling for biomarker discovery. In our approach for the TCGA HNSCC cohort, we scanned human protein-coding genes to find optimal cutoff values. After adjustments with confounders, clinical tumor stage and surgical margin involvement were found to be independent risk factors for prognosis. According to the results tables that show hazard ratios with Bonferroni-adjusted p values under the optimal cutoff, three biomarker candidates, CAMK2N1, CALML5, and FCGBP, are significantly associated with overall survival. We validated this discovery by using the another independent HNSCC dataset (GSE65858). Thus, we suggest that transcriptomic analysis could help with biomarker discovery. Moreover, the robustness of the biomarkers we identified should be ensured through several additional tests with independent datasets.

Non-invasive metabolic biomarkers for early diagnosis of diabetic nephropathy: Meta-analysis of profiling metabolomics studies

AIM

Diabetic nephropathy (DN) is one of the worst complications of diabetes. Despite a growing number of DN metabolite profiling studies, most studies are suffering from inconsistency in their findings. The main goal of this meta-analysis was to reach to a consensus panel of significantly dysregulated metabolites as potential biomarkers in DN.

DATA SYNTHESIS

To identify the significant dysregulated metabolites, meta-analysis was performed by "vote-counting rank" and "robust rank aggregation" strategies. Bioinformatics analyses were performed to identify the most affected genes and pathways. Among 44 selected studies consisting of 98 metabolite profiles, 17 metabolites (9 up-regulated and 8 down-regulated metabolites), were identified as significant ones by both the meta-analysis strategies (p-value<0.05 and OR>2 or <0.5) and selected as DN metabolite meta-signature. Furthermore, enrichment analyses confirmed the involvement of various effective biological pathways in DN pathogenesis, such as urea cycle, TCA cycle, glycolysis, and amino acid metabolisms. Finally, by performing a meta-analysis over existing time-course studies in DN, the results indicated that lactic acid, hippuric acid, allantoin (in urine), and glutamine (in blood), are the topmost non-invasive early diagnostic biomarkers.

CONCLUSION

The identified metabolites are potentially involved in diabetic nephropathy pathogenesis and could be considered as biomarkers or drug targets in the disease.

PROSPERO REGISTRATION NUMBER

CRD42020197697.

Autophagy-related genes contribute to malignant progression and have a clinical prognostic impact in colon adenocarcinoma

Autophagy has an important role in regulating tumor cell survival. However, the roles of autophagy-related genes (ARGs) during colon adenocarcinoma (COAD) progression and their prognostic value have remained elusive. The present study aimed to identify the correlation between ARGs and the progression of COAD, as well as the prognostic significance of ARGs. The transcriptome profiles and the corresponding clinicopathological information of patients with COAD were downloaded from The Cancer Genome Atlas and Genotype-Tissue Expression databases. A list of ARGs was obtained from the Human Autophagy Database and bioinformatics analysis was performed to investigate the functions of these ARGs. Statistical analyses of these genes were performed to identify independent prognostic markers. The selected prognostic markers were then validated in 15 patients with COAD via immunohistochemistry. Differentially expressed ARGs between normal and tumor tissues were identified. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses revealed that the differentially expressed ARGs were mainly enriched in toxoplasmosis and pathways in cancer. The ATG4B, DAPK1 and SERPINA1 genes were determined to be associated with COAD progression. In addition, a risk signature was proposed that may serve as an independent prognostic marker. In conclusion, ATG4B, DAPK1 and SERPINA1 are crucial participants in tumorigenesis of COAD. The present study may promote the development of novel treatment strategies for COAD.

QPCT regulation by CTCF leads to sunitinib resistance in renal cell carcinoma by promoting angiogenesis

Sunitinib is widely used as a first‑line treatment for advanced renal cell carcinoma (RCC). However, a number of patients with RCC who receive sunitinib develop drug resistance; and the biological mechanisms involved in resistance to sunitinib remain unclear. It has previously been suggested that the protein glutaminyl‑peptide cyclotransferase (QPCT) is closely related to sunitinib resistance in RCC. Thus, in the present study, in order to further examine the molecular mechanisms responsible for sunitinib resistance in RCC, sunitinib‑non‑responsive and ‑responsive RCC tissue and plasma samples were collected and additional experiments were performed in order to elucidate the molecular mechanisms responsible for sunitinib resistance in RCC. The upstream and downstream regulatory mechanisms of QPCT were also evaluated. On the whole, the data from the present study suggest that QPCT, CCCTC‑binding factor (CTCF) and phosphatidylinositol‑4,5‑bisphosphate 3‑kinase catalytic subunit alpha (PIK3CA) may be used as targets for predicting, reversing and treating sunitinib‑resistant RCC.

Identification of Key mRNAs, miRNAs, and mRNA-miRNA Network Involved in Papillary Thyroid Carcinoma

Background:

In the past decades, the incidence of thyroid cancer (TC) has been gradually increasing, owing to the widespread use of ultrasound scanning devices. However, the key mRNAs, miRNAs, and mRNA-miRNA network in papillary thyroid carcinoma (PTC) has not been fully understood.

Material and Methods:

In this study, multiple bioinformatics methods were employed, including differential expression analysis, gene set enrichment analysis, and miRNA-mRNA interaction network construction.

Results:

First, we investigated the key miRNAs that regulated significantly more differentially expressed genes based on GSEA method. Second, we searched for the key miRNAs based on the mRNA-miRNA interaction subnetwork involved in PTC. We identified hsa-mir-1275, hsa-mir-1291, hsa-mir-206 and hsa-mir-375 as the key miRNAs involved in PTC pathogenesis.

Conclusion:

The integrated analysis of the gene and miRNA expression data not only identified key mRNAs, miRNAs, and mRNA-miRNA network involved in papillary thyroid carcinoma, but also improved our understanding of the pathogenesis of 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 the candidate lncRNA biomarkers for acute kidney injury: a systematic review and meta-analysis

Background: This meta-analysis aims to summarize the studies of lncRNAs dysregulation in individual acute kidney injury (AKI) and identify the potential lncRNA biomarkers of AKI.Research design and methods: We systematically searched four databases to identify the lncRNA expression studies of AKI in animal models and patients. The lncRNAs expression data were extracted from 38 included studies, and lncRNA vote-counting strategy was applied to identify significant lncRNA biomarkers. The predicted targets of lncRNA biomarkers were obtained by searching Co-LncRNA, RBPmap, and LncBase v.2. Further, GO enrichment analysis and KEGG pathway analysis were performed.Results: We recognized a significant lncRNA signature of 21 up-regulated and 11 down-regulated lncRNAs, among which TapSAKI, XIST, MALAT1, CASC2, and HOXA-AS2 were dysregulated both in AKI rodent models and patients. About 28.0% of these lncRNAs mainly exist in the nucleus, which was also the most enriched GO cellular components term. The most relevant GO terms in biological process and molecular function associated with these lncRNAs were splicing, processing, and binding of mRNA.Conclusions: The present meta-analysis identified 31 significant dysregulated lncRNAs from 38 studies. TapSAKI, XIST, MALAT1, CASC2, and HOXA-AS2 were considered as the potential predictive biomarkers and therapeutic targets of AKI.

Identification of Potential BRAF Inhibitor Joint Therapy Targets in PTC based on WGCAN and DCGA

As the most common mutation in papillary thyroid cancer (PTC), B-type Raf kinase V600E mutation (BRAFV600E ) has become an important target for the clinical treatment of PTC. However, the clinical application still faces the problem of resistance to BRAF inhibitors (BRAFi). Therefore, exploring BRAFV600E-associated prognostic factors to providing potential joint targets is important for combined targeted therapy with BRAFi. In this study, we combined transcript data and clinical information from 199 BRAF wild-type (BRAFWT ) patients and 283 BRAFV600E mutant patients collected from The Cancer Genome Atlas (TCGA), and screened 455 BRAFV600E- associated genes through differential analysis and weighted gene co-expression network analysis. Based on these BRAFV600E -associated genes, we performed functional enrichment analysis and co-expression differential analysis and constructed a core co-expression network. Next, genes in the differential co-expression network were used to predict drugs for therapy in the crowd extracted expression of differential signatures (CREEDS) database, and the key genes were selected based on the hub co-expression network through survival analyses and receiver operating characteristic (ROC) curve analyses. Finally, we obtained eight BRAFV600E -associated biomarkers with both prognostic and diagnostic values as potential BRAFi joint targets, including FN1, MET, SLC34A2, NGEF, TBC1D2, PLCD3, PROS1, and NECTIN4. Among these genes, FN1, MET, PROS1, and TBC1D2 were validated through GEO database. Two novel biomarkers, PROS1 and TBC1D2, were further validated by qRT-PCR experiment. Besides, we obtained four potential targeted drugs that could be used in combination with BRAFi to treat PTC, including MET inhibitor, ERBB3 inhibitor, anti-NaPi2b antibody-drug conjugate, and carboplatin through literature review. The study provided potential drug targets for combination therapy with BRAFi for PTC to overcome the drug resistance for BRAFi.

A meta-analysis of microRNA expression profiling studies in heart failure

Heart failure (HF) is a major consequence of many cardiovascular diseases with high rate of morbidity and mortality. Early diagnosis and prevention are hampered by the lack of informative biomarkers. The aim of this study was to perform a meta-analysis of the miRNA expression profiling studies in HF to identify novel candidate biomarkers or/and therapeutic targets. A comprehensive literature search of the PubMed for miRNA expression studies related to HF was carried out. The vote counting and robust rank aggregation meta-analysis methods were used to identify significant meta-signatures of HF-miRs. The targets of HF-miRs were identified, and network construction and gene set enrichment analysis (GSEA) were performed to identify the genes and cognitive pathways most affected by the dysregulation of the miRNAs. The literature search identified forty-five miRNA expression studies related to CHF. Shared meta-signature was identified for 3 up-regulated (miR-21, miR-214, and miR-27b) and 13 down-regulated (miR-133a, miR-29a, miR-29b, miR-451, miR-185, miR-133b, miR-30e, miR-30b, miR-1, miR-150, miR-486, miR-149, and miR-16-5p) miRNAs. Network properties showed miR-29a, miR-21, miR-29b, miR-1, miR-16, miR-133a, and miR-133b have the most degree centrality. GESA identified functionally related sets of genes in signaling and community pathways in HF that are the targets of HF-miRs. The miRNA expression meta-analysis identified sixteen highly significant HF-miRs that are differentially expressed in HF. Further validation in large patient cohorts is required to confirm the significance of these miRs as HF biomarkers and therapeutic targets.

Comprehensive Identification of Potential Crucial Genes and miRNA-mRNA Regulatory Networks in Papillary Thyroid Cancer

Background

Thyroid cancer is the most common endocrine malignancy, with a recent global increase of 20% in age-related incidence. Ultrasonography and ultrasonography-guided fine-needle aspiration biopsy (FNAB) are the most widely used diagnostic tests for thyroid nodules; however, it is estimated that up to 25% of thyroid biopsies are cytologically inconclusive. Molecular markers can help guide patient-oriented and targeted treatment of thyroid nodules and thyroid cancer.

Methods

Datasets related to papillary thyroid cancer (PTC) or thyroid carcinoma (GSE129562, GSE3678, GSE54958, GSE138042, and GSE124653) were downloaded from the GEO database and analysed using the Limma package of R software. For functional enrichment analysis, the Kyoto Encyclopedia of Genes and Genomes pathway analysis and Gene Ontology were applied to differentially expressed genes (DEGs) using the Metascape website. A protein-protein interaction (PPI) network was built from the STRING database. Gene expression, protein expression, immunohistochemistry, and potential functional gene survival were analysed using the GEPIA website, the Human Protein Atlas website, and the UALCAN website. Potential target miRNAs were predicted using the miRDB and Starbase datasets.

Results

We found 219 upregulated and 310 downregulated DEGs, with a cut-off of p < 0.01 and ∣log FC | >1.5. The DEGs in papillary thyroid cancer were mainly enriched in extracellular structural organisation. At the intersection of the PPI network and Metascape MCODEs, the hub genes in common were identified as FN1, APOE, CLU, and SDC2. In the targeted regulation network of miRNA-mRNA, the hsa-miR-424-5p was found to synchronously modulate two hub genes. Survival analysis showed that patients with high expression of CLU and APOE had better prognosis.

Conclusions

CLU and APOE are involved in the molecular mechanism of papillary thyroid cancer. The hsa-miR-424-5p might have the potential to reverse the processes of papillary thyroid cancer by modulating the hub genes. These are potential targets for the treatment of patients with papillary thyroid cancer.

A systematic review of microRNAs as potential biomarkers for diagnosis and prognosis of gastric cancer

Gastric cancer (GC) is the third leading cause of global cancer morbidity and mortality. One of the significant challenges in GC treatment is that most GC patients are diagnosed with advanced-stage disease due to the lack of suitable biomarkers. Recent studies have shown that microRNAs (miRNAs) can acts as a potential biomarker in GC diagnosis and prognosis. I performed a systematic review of published miRNA studies in GC, which includes the miRNA expression profiles between GC tissues and normal tissues and also miRNA studies to evaluate their potential value in the diagnosis and prognosis of GC. Among the studies, upregulation of miR-21, miR-106b, miR-25, miR-214, miR-18a, miR-191, and miR-93 and downregulation of miR-375, miR-148a, miR-92, miR-155, and miR-564 were observed in GC tissues. In evaluating of diagnosis value of miRNAs, the study was performed on a combined miRNA include miR-21, miR-93, miR-106a, and miR-106b indicated the panel of these miRNAs have the highest AUC 0.887 to discriminate GC patients from healthy. Also, miR-940 with a sensitivity of 81.25% and specificity of 98.57% may be used for diagnostic biomarkers for GC. Finally, the pooled prognostic result of miR-21 for hazard ratios (HR) was 1.260 (95% CI 0.370-4.330, P < 0.001), showing that miR-21 could predict poor survival in GC patients. This systematic review can confirm that we need to find a miRNA or a panel of miRNAs with high sensitivity and specificity for further exploration to investigate a better diagnostic or therapeutic tool for personalized management of GC patients.

A Novel Nanoproteomic Approach for the Identification of Molecular Targets Associated with Thyroid Tumors

A thyroid nodule is the most common presentation of thyroid cancer; thus, it is extremely important to differentiate benign from malignant nodules. Within malignant lesions, classification of a thyroid tumor is the primary step in the assessment of the prognosis and selection of treatment. Currently, fine-needle aspiration biopsy (FNAB) is the preoperative test most commonly used for the initial thyroid nodule diagnosis. However, due to some limitations of FNAB, different high-throughput “omics” approaches have emerged that could further support diagnosis based on histopathological patterns. In the present work, formalin-fixed paraffin-embedded (FFPE) tissue specimens from normal (non-neoplastic) thyroid (normal controls (NCs)), benign tumors (follicular thyroid adenomas (FTAs)), and some common types of well-differentiated thyroid carcinoma (follicular thyroid carcinomas (FTCs), conventional or classical papillary thyroid carcinomas (CV-PTCs), and the follicular variant of papillary thyroid carcinomas (FV-PTCs)) were analyzed. For the first time, FFPE thyroid samples were deparaffinized using an easy, fast, and non-toxic method. Protein extracts from thyroid tissue samples were analyzed using a nanoparticle-assisted proteomics approach combined with shotgun LC-MS/MS. The differentially regulated proteins found to be specific for the FTA, FTC, CV-PTC, and FV-PTC subtypes were analyzed with the bioinformatic tools STRING and PANTHER showing a profile of proteins implicated in the thyroid cancer metabolic reprogramming, cancer progression, and metastasis. These proteins represent a new source of potential molecular targets related to thyroid tumors.

The Physiological MicroRNA Landscape in Nipple Aspirate Fluid: Differences and Similarities with Breast Tissue, Breast Milk, Plasma and Serum

Background: MicroRNAs (miRNAs) target 60% of human messenger RNAs and can be detected in tissues and biofluids without loss of stability during sample processing, making them highly appraised upcoming biomarkers for evaluation of disease. However, reporting of the abundantly expressed miRNAs in healthy samples is often surpassed. Here, we characterized for the first time the physiological miRNA landscape in a biofluid of the healthy breast: nipple aspirate fluid (NAF), and compared NAF miRNA expression patterns with publically available miRNA expression profiles of healthy breast tissue, breast milk, plasma and serum. Methods: MiRNA RT-qPCR profiling of NAF (n = 41) and serum (n = 23) samples from two healthy female cohorts was performed using the TaqMan OpenArray Human Advanced MicroRNA 754-Panel. MiRNA quantification data based on non-targeted or multi-targeted profiling techniques for breast tissue, breast milk, plasma and serum were retrieved from the literature by means of a systematic search. MiRNAs from each individual study were orderly ranked between 1 and 50, combined into an overall ranking per sample type and compared. Results: NAF expressed 11 unique miRNAs and shared 21/50 miRNAs with breast tissue. Seven miRNAs were shared between the five sample types. Overlap between sample types varied between 42% and 62%. Highly ranked NAF miRNAs have established roles in breast carcinogenesis. Conclusion: This is the first study to characterize and compare the unique physiological NAF-derived miRNA landscape with the physiological expression pattern in breast tissue, breast milk, plasma and serum. Breast-specific sources did not mutually overlap more than with systemic sources. Given their established role in carcinogenesis, NAF miRNA assessment could be a valuable tool in breast tumor diagnostics.

miR-224 is an early-stage biomarker of hepatocellular carcinoma with miR-224 and miR-125b as prognostic biomarkers

Aim: The aim was to systematically investigate the miRNA biomarkers for early diagnosis of hepatocellular carcinoma (HCC). Materials & methods: A systematic review and meta-analysis of miRNA expression in HCC were performed. Results: A total of 4903 cases from 30 original studies were comprehensively analyzed. The sensitivity and specificity of miR-224 in discriminating early-stage HCC patients from benign lesion patients were 0.868 and 0.792, which were superior to α-fetoprotein. Combined miR-224 with α-fetoprotein, the sensitivity and specificity were increased to 0.882 and 0.808. Prognostic survival analysis showed low expression of miR-125b and high expression of miR-224 were associated with poor prognosis. Conclusion: miR-224 had a prominent diagnostic efficiency in early-stage HCC, with miR-224 and miR-125b being valuable in the prognostic diagnosis.

Serum miRNAs associated with tumor-promoting cytokines in non-small cell lung cancer

Tumor-promoting cytokines are a cause of tumor progression; therefore, identifying key regulatory microRNAs (miRNAs) for controlling their production is important. The aim of this study is to identify promising miRNAs associated with tumor-promoting cytokines in non-small cell lung cancer (NSCLC). We identified circulating miRNAs from 16 published miRNA profiles. The selected miRNAs were validated in the serum of 32 NSCLC patients and compared with 33 patients with other lung diseases and 23 healthy persons using quantitative real-time PCR. The cytokine concentration was investigated using the enzyme-linked immunoassay in the same sample set, with clinical validation of the miRNAs. The correlation between miRNA expression and cytokine concentration was evaluated by Spearman’s rank correlation. For consistent direction, one up-regulated miRNA (miR-145) was found in four studies, and seven miRNAs were reported in three studies. One miRNA (miR-20a) and four miRNAs (miR-25-3p, miR-223, let-7f, and miR-20b) were reported in six and five studies. However, their expression was inconsistent. In the clinical validation, serum miR-145 was significantly down-regulated, whereas serum miR-20a was significantly up-regulated in NSCLC, compared with controls. Regarding serum cytokine, all cytokines [vascular endothelial growth factor (VEGF), interleukin-6 (IL-6), and transforming growth factor β (TGF-β)], except tumor necrosis factor-α (TNF-α), had a higher level in NSCLC patients than controls. In addition, we found a moderate correlation between the TGF-β concentration and miR-20a (r = −0.537, p = 0.002) and miR-223 (r = 0.428, p = 0.015) and a weak correlation between the VEGF concentration with miR-20a (r = 0.376, p = 0.037) and miR-223 (r = −0.355, p = 0.046). MiR-145 and miR-20a are potential biomarkers for NSCLC. In addition, the regulation of tumor-promoting cytokine, through miR-20a and miR-223, might be a new therapeutic approach for lung cancer.

Identification of a Novel Signature and Construction of a Nomogram Predicting Overall Survival in Clear Cell Renal Cell Carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma (RCC), which accounts for majority of RCC-related deaths. It is clearly essential to further identify more novel prognostic signatures and therapeutic targets.

Material and Methods

We identified differentially expressed genes (DEGs) between ccRCC and adjacent normal tissues in GEO database using a Robust Rank Aggregation (RRA) method. An mRNA signature (mRNASig) based on DEGs was developed using Cox and LASSO analysis in the TCGA database and validated in the ICGC database. Afterward, the influence of mRNASig mRNAs on the immune microenvironment in ccRCC was explored using comprehensive bioinformatics analysis.

Results

A total of 957 robust DEGs were identified using the RRA method. mRNASig comprised CEP55, IFI44, NCF4, and TCIRG1 and was developed and validated to identify high-risk patients who had poorer prognosis than low-risk patients. A nomogram was also constructed based on mRNASig, AJCC stage, and tumor grade. The mRNASig were closely related to a variety of tumor-infiltrating lymphocytes, especially including CD8+ T cells, activated CD4+ memory T cells, regulatory T cells, activated NK cells, and resting NK cells. The mRNASig were also correlated positively with the expression of CTLA4, LAG3, PDCD1, TIGIT, and HAVCR2.

Conclusion

We developed and validated mRNASig to assist clinicians in making personalized treatment decisions. Furthermore, CEP55, IFI44, NCF4, and TCIRG1 may be novel potential targets for future treatment of ccRCC.

Identification of candidate lncRNA biomarkers for renal fibrosis: A systematic review

AIMS

To combine the results of dysregulated lncRNAs in individual renal fibrosis lncRNA expression profiling studies and to identify potential lncRNA biomarkers.

MATERIALS AND METHODS

We systematically searched three databases to identify lncRNA expression studies of renal fibrosis in animal models and humans. The lncRNA expression data were extracted from 24 included studies, and a lncRNA vote-counting strategy was applied to identify significant lncRNA biomarkers. The lncLocator algorithm was utilized to predict the potential subcellular localization of these lncRNAs. The predicted targets of the identified lncRNA biomarkers were obtained by searching LncBase v.2 and catRAPID. Finally, GO enrichment and KEGG pathway analyses were performed.

KEY FINDINGS

We recognized a significant lncRNA signature of 95 differentially expressed lncRNAs in 731 samples from rodent models of renal fibrosis and CKD patients, among which TCONS_01181049 and TCONS_01496394 were commonly upregulated in both urine and renal tissues, while lncRNA-Cancer Susceptibility Candidate 2 was downregulated in both blood and renal tissues. About 73.33% dysregulated lncRNAs in renal fibrosis animal models and 81.82% dysregulated lncRNAs in CKD patients were predicted to be localized to the cytoplasm. The most relevant biological processes and molecular functions associated with these lncRNAs were mRNA processing and RNA binding.

SIGNIFICANCE

The present systematic review identified 95 significantly dysregulated lncRNAs from 24 studies and future investigations should focus on exploring their potential effects on renal fibrosis and their clinical utility as biomarkers or therapeutic targets.

Diagnostic value of microRNA panel in endometrial cancer: A systematic review

PURPOSE

We conducted a systematic review to evaluate the overall diagnostic accuracy of miRNAs in detecting endometrial cancer.

MATERIALS AND METHODS

A systematic search of Medline, Embase, Cinahl and the Cochrane Controlled Register of Trials was performed to identify studies reporting on the diagnostic value of miRNA in EC patients. Included were diagnostic studies looking at miRNA expression in women diagnosed with endometrial cancer. Two reviewers independently selected studies and assessed quality of studies using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) score system. Data extraction was completed and the vote-counting strategy was used to rank miRNAs.

RESULTS

26 studies were included with a total number of 1,400 EC patients reporting on 106 differentially expressed miRNAs. The most frequently found up-regulated miRNA was miR-205 followed by miR-200c, -223, -182, -183 and -200a. In addition, miR-135b, miR-429, miR-141 and miR-200b were also frequently up-regulated. There was less consensus on down-regulated miRNAs.

CONCLUSIONS

miRNAs yield a promising diagnostic biomarker potential in endometrial cancer, especially miR-205, the miR-200 family and miR-135b, -182, -183 and -223. However, no sufficient high quality data are available to draw hard conclusions. More research is needed to validate the diagnostic potential of these miRNAs in larger studies. In addition, the potential of urine as a non-invasive biofluid should be investigated in more detail.

Digital gene expression analysis might aid in the diagnosis of thyroid cancer

Background

Thyroid cancer represents approximately 90% of endocrine cancers. Difficulties in diagnosis and low inter-observer agreement are sometimes encountered, especially in the distinction between the follicular variant of papillary thyroid carcinoma (fvptc) and other follicular-patterned lesions, and can present significant challenges. In the present proof-of-concept study, we report a gene-expression assay using NanoString nCounter technology (NanoString Technologies, Seattle, WA, U.S.A.) that might aid in the differential diagnosis of thyroid neoplasms based on gene-expression signatures.

Methods

Our cohort included 29 patients with classical papillary thyroid carcinoma (ptc), 13 patients with fvptc, 14 patients with follicular thyroid carcinoma (ftc), 14 patients with follicular adenoma (fa), and 14 patients without any abnormality. We developed a 3-step classifier that shows good correlation with the pathologic diagnosis of various thyroid neoplasms. Step 1 differentiates normal from abnormal thyroid tissue; step 2 differentiates benign from malignant lesions; and step 3 differentiates the common malignant entities ptc, ftc, and fvptc.

Results

Using our 3-step classifier approach based on selected genes, we developed an algorithm that attempts to differentiate thyroid lesions with varying levels of sensitivity and specificity. Three genes-namely SDC4, PLCD3, and NECTIN4/PVRL4-were the most informative in distinguishing normal from abnormal tissue with a sensitivity and a specificity of 100%. One gene, SDC4, was important for differentiating benign from malignant lesions with a sensitivity of 89% and a specificity of 92%. Various combinations of genes were required to classify specific thyroid neoplasms.

Conclusions

This preliminary proof-of-concept study suggests a role for nCounter technology, a digital gene expression analysis technique, as an adjunct assay for the molecular diagnosis of thyroid neoplasms.

Impact of the Tumor Microenvironment on the Gene Expression Profile in Papillary Thyroid Cancer

Transcriptome of papillary thyroid cancer (PTC) is well characterized and correlates with some prognostic and genotypic factors, but data addressing the interaction between PTC and tumor microenvironment (TME) are scarce. Therefore, in the present study, we aimed to assess the impact of TME on gene expression profile in PTC. We evaluated the gene expression profile in PTC and normal thyroid cells isolated by laser capture microdissection and in whole tissue slides corresponding to the entire tumor. We included 26 microdissected samples for gene expression analysis (HG-U133 PLUS 2.0, Affymetrix, currently Thermo Fisher Scientific USA): 15 PTC samples, 11 samples of normal thyrocytes, and 30 whole slides (15 PTC and 15 normal thyroid). Transcripts were divided into three groups: differentially expressed both in microdissected and whole slides, transcripts differently expressed in microdissected samples and not changed in whole slides, and transcripts differentially expressed in whole slides and not changed in microdissected samples. Eleven genes were selected for validation in an independent set of samples; among them, four genes differentiated only microdissected PTC and normal cells. Two genes (PTCSC and CTGF) were confirmed. One gene (FOS) was not confirmed by the validation, whereas EGR1 was also significant in whole slide analysis. The other seven genes (TFF3, FN1, MPPED2, MET, KCNJ2, TACSTD2, and GALE) showed differentiated expression in microdissected thyrocytes and in whole tumor slides. Most of identified genes were related to the tumor-microenvironment interaction and confirmed the crosstalk between TME and cancer cells.

Identification of potential novel biomarkers to differentiate malignant thyroid nodules with cytological indeterminate

Background

The fine-needle aspiration (FNA) biopsy was broadly applied to clinical diagnostics evaluation for thyroid carcinomas nodule, while companioning with higher uncertainty rate (15~30%) to identify malignancy for cytological indeterminate cases. It is requirement to discover novel molecular biomarkers to differentiate malignant thyroid nodule more precise.

Methods

We employed weighted gene co-expression network analysis (WGCNA) to discover genes significantly associated with malignant histopathology for cytological indeterminate nodules. In addition, identified significantly genes were validated through another independently investigations of thyroid carcinomas patient’s samples via cBioportal and Geipa. The key function pathways of significant genes involving were blast through GenClip.

Results

Twenty-four signature genes were identified significantly related to thyroid nodules malignancy. Furthermore, five novel genes with missense mutation, FN1 (R534P), PROS1((K200I), (Q571K)), SCEL (T320S), SLC34A2(T688M) and TENM1 (S1131F), were highlighted as potential biomarkers to rule out nodules malignancy. It was identified that the key functional pathways involving in thyroid carcinomas.

Conclusion

These results will be helpful to better understand the mechanism of thyroid nodules malignant transformation and characterize the potentially biomarkers for thyroid carcinomas early diagnostics.

microRNA Expression Profiling Based on Microarray Approach in Human Diabetic Retinopathy: A Systematic Review and Meta-Analysis

Diabetes mellitus (DM) is one of the growing public health threats globally and as one of the common serious microvascular complications of DM, diabetic retinopathy (DR) is the leading cause of irreversible visual impairments and blindness. There is growing concern about the role of microRNAs (miRNAs) in the pathogenesis of DR. This meta-analysis was designed to collect those published miRNA expression profiling studies that compared the miRNA expression profiles in the biological samples of DR patients with those in the control group. Eight publications were finally included in the meta-analysis, and a total of 93 differentially expressed miRNAs were reported. Although six miRNAs were reported in at least two studies and with the consistent direction, after stratification by the type of biological samples, miR-320a was consistently reported to be upregulated in two serum sample-based studies and miR-423-5p was consistently reported to be upregulated in two vitreous humor sample-based studies. miR-27b was consistently reported to be downregulated in two serum sample-based studies. In conclusion, the results of this meta-analysis of human DR miRNAs' expression profiling studies might provide some clues of the potential biomarkers of DR. Further investigation of the mechanisms of miRNAs and more external validation studies are warranted with the aim of developing new diagnostic markers for preventing or reversing DR.

Heterogenous nature of gene expression patterns in BRAF-like papillary thyroid carcinomas with BRAFV600E

PURPOSE

Papillary thyroid cancers (PTCs) are the most common type of thyroid cancers, in which BRAF^V600E is the most prevalent driver mutation. It is known that BRAF^V600E-positive PTCs are clinically and molecularly heterogenous in terms of aggressiveness and prognosis. The molecular mechanisms of this heterogeneity were evaluated.

METHODS

The publicly available RNA-seq data for 26 classical (c) and 5 follicular variant (fv) PTCs with BRAF^V600E mutation and the BRAF-like expression signature in the BRAF^V600E-RAS score (BRS) and their respective normal adjacent tissues were downloaded, and analyzed for differentially expressed genes (DEGs). The DEGs were then analyzed with the Gene Ontology annotation and the KEGG pathway dataset.

RESULTS

We found four lines of evidence for heterogeneity of cPTCs. First, the cluster dendrogram and principle component analyses could not completely distinguish the cancer tissues from normal tissues. Second, the DEGs identified in each sample were highly diverse from one another. Third, although the DEGs were enriched in many terms containing the word "extracellular" ("extracellular region", "extracellular space", and so on) when analyzed as groups, the degree of this enrichment was variable when analyzed individually. Fourth, there are only a few intersections in the over-/underexpressed genes annotated with the terms containing the word "extracellular" among the samples examined. Essentially same results were obtained with BRAF-like, fvPTCs with BRAF^V600E. Nevertheless, some frequently over-/underexpressed genes were detected, of which LIPH (lipase H) expression was found to be prognostic and its high expression was favorable for PTCs.

CONCLUSION

Groups of BRAF-like, BRAF^V600E-positive cPTCs and fvPTCs that are homogenous in regard to histopathology, driver mutation and BRS were found to be highly heterogenous in terms of gene expression patterns. Yet, among the genes that were annotated with the terms containing the word "extracellular" and frequently over-/underexpressed, LIPH is a favorable prognostic marker for PTCs.

Digital Gene Expression Analysis on Cytology Smears Can Rule Out Malignancy in Follicular-Patterned Thyroid Tumors

Patients with indeterminate thyroid nodules (Bethesda III and IV) are often treated with diagnostic lobectomy, which in most cases represents an overtreatment. A reliable rule-out molecular test could spare patients unnecessary surgery. Stained smears of 88 indeterminate thyroid nodules with histologic diagnosis of follicular-patterned tumors were selected: 34 follicular adenomas (FAs), 34 follicular variant papillary thyroid carcinomas (FVPTCs), and 20 noninvasive follicular neoplasms with papillary-like nuclear features (NIFTPs). The expression level of 126 genes was measured by digital counting. Mutation testing was performed for the main gene mutations and fusions. Performance of gene expression and mutation tests was calculated by receiver operating characteristic analysis. The gene expression model showed an area under the curve (AUC) of 88%, with 91% negative predictive value in FAs and FVPTCs only. Part of NIFTPs was labeled as benign, and part was labeled as malignant; thus, the classifier performance worsened. Two FAs (5.9%), eight NIFTPs (40%), and 22 FVPTCs (64.7%) were mutation positive. Mutation testing AUC was 79% in FAs and FVPTCs, and decreased by including NIFTPs. This gene expression-based test was feasible in thyroid-stained smears, showed higher AUC than mutation test, and had a high negative predictive value-making it a good candidate as a rule-out test for indeterminate thyroid cytology. NIFTPs have a heterogeneous phenotype, and their preoperative diagnosis requires further investigation.