Reciprocal Dysregulation of MiR-146b and MiR-451 Contributes in Malignant Phenotype of Follicular Thyroid Tumor

Algorithmically Reconstructed Molecular Pathways as the New Generation of Prognostic Molecular Biomarkers in Human Solid Cancers

Individual gene expression and molecular pathway activation profiles were shown to be effective biomarkers in many cancers. Here, we used the human interactome model to algorithmically build 7470 molecular pathways centered around individual gene products. We assessed their associations with tumor type and survival in comparison with the previous generation of molecular pathway biomarkers (3022 "classical" pathways) and with the RNA transcripts or proteomic profiles of individual genes, for 8141 and 1117 samples, respectively. For all analytes in RNA and proteomic data, respectively, we found a total of 7441 and 7343 potential biomarker associations for gene-centric pathways, 3020 and 2950 for classical pathways, and 24,349 and 6742 for individual genes. Overall, the percentage of RNA biomarkers was statistically significantly higher for both types of pathways than for individual genes (p < 0.05). In turn, both types of pathways showed comparable performance. The percentage of cancer-type-specific biomarkers was comparable between proteomic and transcriptomic levels, but the proportion of survival biomarkers was dramatically lower for proteomic data. Thus, we conclude that pathway activation level is the advanced type of biomarker for RNA and proteomic data, and momentary algorithmic computer building of pathways is a new credible alternative to time-consuming hypothesis-driven manual pathway curation and reconstruction.

NOVAprep-miR-Cervix: New Method for Evaluation of Cervical Dysplasia Severity Based on Analysis of Six miRNAs

Cervical cancer is one of the most common gynecological malignancies and it is preventable through the yearly diagnosis and management of pre-cancerous cervical disease. The profile of miRNA expression in cervical epithelium cells is altered with cervical dysplasia development and further progression. The NOVAprep-miR-CERVIX is a new approach for the assessment of cervical dysplasia through the analysis of six marker miRNAs. This study aims to evaluate theperformance and diagnostic potency of the new method. Cytological smears from 226 women (NILM, n.114; HSIL, n.112) were included in the study. A VPH test was performed with RealBest DNAHPV HR screen Kit, six marker miRNAs (miR-21, -29b, -145, -451a, -1246, -1290) were assayed using NOVAprep-miR-CERVIX kit. Obtained data were analyzed using the Delta Ct method and random forest machine learning algorithm. The results of the quantitative analysis of six microRNAs were expressed as a miR-CERVIX parameter, which ranged from 0 to 1, where "0" corresponded to the healthy cervical epithelium, while "1" corresponded to high-grade squamous intraepithelial dysplasia. The average value of miR-CERVIX differed in groups of NILM and HSIL samples (0.34 vs. 0.72; p < 0.000005). An estimation of miR-CERVIX allowed for the differentiation between healthy and pre-cancerous samples with sensitivity of 0.79 and specificity of 0.79, as well as to confirm HSIL with specificity of 0.98. Interestingly, the HSIL group included HPV(+) and HPV(-) samples, which were statistically significantly different in terms of miR-CERVIX value. Analysis of CC-associated miRNAs in material of cervical smear might serve as an additional method for the evaluation of cervical dysplasia severity.

Attacking Cancer Progression and Metastasis

This Special Issue, focused on a collection of papers on "attacking cancer progression and metastasis", is devoted to communicating current knowledge about the cellular and molecular mechanisms involved in cancer progression and metastasis, as well as suggesting new targets for possible future therapeutic interventions [...].

MicroRNA expression profiling of RAS-mutant thyroid tumors with follicular architecture: microRNA signatures to discriminate benign from malignant lesions

PURPOSE

RAS mutations represent common driver alterations in thyroid cancer. They can be found in benign, low-risk and malignant thyroid tumors with follicular architecture, which are often diagnosed as indeterminate nodules on preoperative cytology. Therefore, the detection of RAS mutations in preoperative setting has a suboptimal predictive value for malignancy. In this study, we investigated differentially expressed microRNA (miRNA) in benign and malignant thyroid tumors with follicular architecture carrying mutations in RAS genes.

METHODS

Total RNA was purified from 60 RAS-mutant follicular-patterned thyroid tumors, including follicular adenoma (FA), noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP), papillary and follicular thyroid carcinoma cases (PTC, FTC); 22 RAS-negative FAs were used as controls. The expression analysis of 798 miRNAs was performed by digital counting (nCounter nanoString platform).

RESULTS

Comparing RAS-mutant and RAS-negative FAs, 12 miRNAs showed significant deregulation, which was likely related to the oncogenic effects of RAS mutations. Twenty-two miRNAs were differentially expressed in RAS-mutant benign versus malignant tumors. Considering the tumor type, 24 miRNAs were deregulated in PTC, 19 in NIFTP, and seven in FTC and compared to FA group; among these, miR-146b-5p, miR-144-3p, and miR-451a showed consistent deregulation in all the comparisons with the highest fold change.

CONCLUSIONS

The miRNA expression analysis of follicular-patterned thyroid tumors demonstrated that RAS mutations influences miRNA profile in benign tumors. In addition, several miRNAs showed a histotype-specific deregulation and could discriminate between RAS-mutant benign and RAS-mutant malignant thyroid lesions, thus deserving further investigation as potential diagnostic markers.

MiR-29b-3p Inhibits Migration and Invasion of Papillary Thyroid Carcinoma by Downregulating COL1A1 and COL5A1

Introduction

MicroRNAs (miRNAs) are small noncoding RNA molecules that regulate genetic expression and are also vital for tumor initiation and development. MiR-29b-3p was found to be involved in regulating various biological processes of tumors, including tumor cell proliferation, metastasis, and apoptosis inhibition; however, the biofunction and molecule-level mechanisms of miR-29b-3p inpapillary thyroid carcinoma (PTC) remain unclear.

Methods

The expression of miR-29b-3p in PTC samples was tested via qRT-PCR. Cellular proliferation was analyzed by CCK-8 and EdU assays, and cellular migratory and invasive abilities were assessed utilizing wound-healing and Transwell assays. In addition, protein expressions of COL1A1, COL5A1, E-cadherin, N-cadherin, Snail, and Vimentin were identified via Western blot (WB) assay. Bioinformatics, qRT-PCR, WB, and dual luciferase reporter assays were completed to identify whether miR-29b-3p targeted COL1A1 and COL5A1. In addition, our team explored the treatment effects of miR-29b-3p on a murine heterograft model.

Results

Our findings revealed that miR-29b-3p proved much more regulated downward in PTC tissue specimens than in adjacent non-cancerous tissues. Meanwhile, decreased expression of miR-29b-3p was strongly related to the TNM stage of PTC patients (p<0.001), while overexpression of miR-29b-3p in PTC cells suppressed cellular migration, invasion, proliferation, and EMT. Conversely, silencing miR-29b-3p yielded the opposite effect. COL1A1 and COL5A1 were affirmed as the target of miR-29b-3p. Additionally, the COL1A1 and COL5A1 were highly expressed in PTC tumor samples than in contrast to neighboring healthy samples. Functional assays revealed that overexpression of COL1A1 or COL5A1 reversed the suppressive role of miR-29b-3p in migration, invasion, and EMT of PTC cells. Finally, miR-29b-3p agomir treatment dramatically inhibited Xenograft tumor growth in the animal model.

Conclusions

These findings document that miR-29b-3p inhibited PTC cells invasion and metastasis by targeting COL1A1 and COL5A1; this study also sparks new ideas for risk assessment and miRNA replacement therapy in PTC.

Papillary Thyroid Carcinoma: Molecular Distinction by MicroRNA Profiling

Papillary thyroid carcinoma (PTC) is a miscellaneous disease with a variety of histological variants, each with its own mutational profile, and clinical and prognostic characteristics. Identification of microRNA (miRNA) expression profiles represents an important benchmark for understanding the molecular mechanisms underlying the biological behavior of these unique PTC subtypes in order that they be better characterized. We considered a series of 35 PTC samples with a histological diagnosis of either hobnail (17 cases) or classical variant (nine cases) and with a specific BRAF p.K601E mutation (nine cases). We determined the overall miRNA expression profile with NanoString technology, and both quantitative reverse transcription-PCR and in situ hybridization were used to confirm selected miRNAs. The miRNA signature was found to consistently differentiate specific histotypes and mutational profiles. In contrast to the BRAF p.K601E mutation and classic PTCs, three miRNAs (miR-21-5p, miR-146b-5p, and miR-205-5p) were substantially overexpressed in the hobnail variant. The current study found that different miRNA signature profiles were linked to unique histological variants and BRAF mutations in PTC. Further studies focusing on the downstream pathogenetic functions of mRNAs in thyroid neoplasms are warranted.

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.

MicroRNAs and Stem-like Properties: The Complex Regulation Underlying Stemness Maintenance and Cancer Development

Embryonic stem cells (ESCs) have the extraordinary properties to indefinitely proliferate and self-renew in culture to produce different cell progeny through differentiation. This latter process recapitulates embryonic development and requires rounds of the epithelial-mesenchymal transition (EMT). EMT is characterized by the loss of the epithelial features and the acquisition of the typical phenotype of the mesenchymal cells. In pathological conditions, EMT can confer stemness or stem-like phenotypes, playing a role in the tumorigenic process. Cancer stem cells (CSCs) represent a subpopulation, found in the tumor tissues, with stem-like properties such as uncontrolled proliferation, self-renewal, and ability to differentiate into different cell types. ESCs and CSCs share numerous features (pluripotency, self-renewal, expression of stemness genes, and acquisition of epithelial-mesenchymal features), and most of them are under the control of microRNAs (miRNAs). These small molecules have relevant roles during both embryogenesis and cancer development. The aim of this review was to recapitulate molecular mechanisms shared by ESCs and CSCs, with a special focus on the recently identified classes of microRNAs (noncanonical miRNAs, mirtrons, isomiRs, and competitive endogenous miRNAs) and their complex functions during embryogenesis and cancer development.

Using proteomic and transcriptomic data to assess activation of intracellular molecular pathways

Analysis of molecular pathway activation is the recent instrument that helps to quantize activities of various intracellular signaling, structural, DNA synthesis and repair, and biochemical processes. This may have a deep impact in fundamental research, bioindustry, and medicine. Unlike gene ontology analyses and numerous qualitative methods that can establish whether a pathway is affected in principle, the quantitative approach has the advantage of exactly measuring the extent of a pathway up/downregulation. This results in emergence of a new generation of molecular biomarkers-pathway activation levels, which reflect concentration changes of all measurable pathway components. The input data can be the high-throughput proteomic or transcriptomic profiles, and the output numbers take both positive and negative values and positively reflect overall pathway activation. Due to their nature, the pathway activation levels are more robust biomarkers compared to the individual gene products/protein levels. Here, we review the current knowledge of the quantitative gene expression interrogation methods and their applications for the molecular pathway quantization. We consider enclosed bioinformatic algorithms and their applications for solving real-world problems. Besides a plethora of applications in basic life sciences, the quantitative pathway analysis can improve molecular design and clinical investigations in pharmaceutical industry, can help finding new active biotechnological components and can significantly contribute to the progressive evolution of personalized medicine. In addition to the theoretical principles and concepts, we also propose publicly available software for the use of large-scale protein/RNA expression data to assess the human pathway activation levels.