Identification of candidate miRNA biomarkers from miRNA regulatory network with application to prostate cancer

Tirzepatide prevents neurodegeneration through multiple molecular pathways

BACKGROUND

Several evidence demonstrated that glucagon-like peptide 1 receptor agonists (GLP1-RAs) reduce the risk of dementia in type 2 diabetes patients by improving memory, learning, and overcoming cognitive impairment. In this study, we elucidated the molecular processes underlying the protective effect of Tirzepatide (TIR), a dual glucose-dependent insulinotropic polypeptide receptor agonist (GIP-RA)/ GLP-1RA, against learning and memory disorders.

METHODS

We investigated the effects of TIR on markers of neuronal growth (CREB and BDNF), apoptosis (BAX/Bcl2 ratio) differentiation (pAkt, MAP2, GAP43, and AGBL4), and insulin resistance (GLUT1, GLUT4, GLUT3 and SORBS1) in a neuroblastoma cell line (SHSY5Y) exposed to normal and high glucose concentration. The potential role on DNA methylation of genes involved in neuroprotection and epigenetic modulators of neuronal growth (miRNA 34a), apoptosis (miRNA 212), and differentiation (miRNA 29c) was also investigated. The cell proliferation was detected by measuring Ki-67 through flow cytometry. The data were analysed by SPSS IBM Version 23 or GraphPad Prism 7.0 software and expressed as the means ± SEM. Differences between the mean values were considered significant at a p-value of < 0.05. GraphPad Prism software was used for drawing figures.

RESULTS

For the first time, it was highlighted: (a) the role of TIR in the activation of the pAkt/CREB/BDNF pathway and the downstream signaling cascade; (b) TIR efficacy in neuroprotection; (c) TIR counteracting of hyperglycemia and insulin resistance-related effects at the neuronal level.

CONCLUSIONS

We demonstrated that TIR can ameliorate high glucose-induced neurodegeneration and overcome neuronal insulin resistance. Thus, this study provides new insight into the potential role of TIR in improving diabetes-related neuropathy.

The role of microRNA in psoriasis: A review

Psoriasis is a chronic immune-mediated inflammatory skin disease that involves a complex interplay between infiltrated immune cells and keratinocytes. Great progress has been made in the research on the molecular mechanism of coding and non-coding genes, which has helped in clinical treatment. However, our understanding of this complex disease is far from clear. MicroRNAs (miRNAs) are small non-coding RNA molecules that are involved in post-transcriptional regulation, characterised by their role in mediating gene silencing. Recent studies on miRNAs have revealed their important role in the pathogenesis of psoriasis. We reviewed the current advances in the study of miRNAs in psoriasis; the existing research has found that dysregulated miRNAs in psoriasis notably affect keratinocyte proliferation and/or differentiation processes, as well as inflammation progress. In addition, miRNAs also influence the function of immune cells in psoriasis, including CD4+ T cells, dendritic cells, Langerhans cells and so on. In addition, we discuss possible miRNA-based therapy for psoriasis, such as the topical delivery of exogenous miRNAs, miRNA antagonists and miRNA mimics. Our review highlights the potential role of miRNAs in the pathogenesis of psoriasis, and we expect more research progress with miRNAs in the future, which will help us understand this complex skin disease more accurately.

Prostate cancer bone metastases biology and clinical management (Review)

Prostate cancer (PCa) is one of the most prominent causes of cancer-related mortality in the male population. A highly impactful prognostic factor for patients diagnosed with PCa is the presence or absence of bone metastases. The formation of secondary tumours at the bone is the most commonly observed site for the establishment of PCa metastases and is associated with reduced survival of patients in addition to a cohort of life-debilitating symptoms, including mobility issues and chronic pain. Despite the prevalence of this disease presentation and the high medical relevance of bone metastases, the mechanisms underlying the formation of metastases to the bone and the understanding of what drives the osteotropism exhibited by prostate tumours remain to be fully elucidated. This lack of in-depth understanding manifests in limited effective treatment options for patients with advanced metastatic PCa and culminates in the low rate of survival observed for this sub-set of patients. The present review aims to summarise the most recent promising advances in the understanding of how and why prostate tumours metastasise to the bone, with the ultimate aim of highlighting novel treatment and prognostic targets, which may provide the opportunity to improve the diagnosis and treatment of patients with PCa with bone metastases.

Next-Generation Sequencing Markup Language (NGSML): A Medium for the Representation and Exchange of NGS Data

With the increasing demand for low-cost high-throughput sequencing of large genomes, next-generation sequencing (NGS) technology has developed rapidly. NGS can not only be used in basic scientific research but also in clinical diagnostics and healthcare. Numerous software systems and tools have been developed to analyze NGS data, and various data formats have been produced to accommodate different sequencing equipment providers or analytical software. However, the data interoperability between these tools brings great challenges to researchers. A generic format that could be shared by most of the software and tools in the NGS field would make data interoperability and sharing easier. In this paper, we defined a general XML-based NGS markup language (NGSML) format for the representation and exchange of NGS data. We also developed a user-friendly GUI tool, NGSMLEditor, for presenting, creating, editing, and converting NGSML files. By using NGSML, various types of NGS data can be saved in one unified format. Compared with the unstructured plain text file, a structured data format based on XML technology solves the incompatibility of various NGS data formats. The NGSML specifications are freely available from http://www.sysbio.org.cn/NGSML. NGSMLEditor is open source under GNU GPL and can be downloaded from the website.

A novel platform using homobifunctional hydrazide for enrichment and isolation of urinary circulating RNAs

Changes in specific circulating RNA (circRNA) expressions can serve as diagnostic noninvasive biomarkers for prostate cancer (PCa). However, there are still unmet needs, such as unclear types and roles of circRNAs, PCa detection in benign prostatic hyperplasia (BPH) by unstandardized methods, and limitations of sample volume capacity and low circRNA concentrations. This study reports a simple and rapid circRNA enrichment and isolation technique named "HAZIS-CirR" for the analysis of urinary circRNAs. The method utilizes homobifunctional hydrazides with amine-modified zeolite and polyvinylidene fluoride (PVDF) syringe filtration for combining electrostatic and covalent coupling and size-based filtration, and it offers instrument-free isolation of circRNAs in 20 min without volume limitation, thermoregulation, and lysis. HAZIS-CirR has high capture efficiency (82.03%-92.38%) and a 10-fold more sensitive detection limit (20 fM) than before enrichment (200 fM). The clinical utility of HAZIS-CirR is confirmed by analyzing circulating mRNAs and circulating miRNAs in 89 urine samples. Furthermore, three miRNA panels that differentiate PCa from BPH and control, PCa from control, and BPH from control, respectively, are established by comparing miRNA levels. HAZIS-CirR will be used as an optimal and established method for the enrichment and isolation of circRNAs as diagnostic, prognostic, and predictive biomarkers in human cancers.

A Novel Strategy for Identifying NSCLC MicroRNA Biomarkers and Their Mechanism Analysis Based on a Brand-New CeRNA-Hub-FFL Network

Finding reliable miRNA markers and revealing their potential mechanisms will play an important role in the diagnosis and treatment of NSCLC. Most existing computational methods for identifying miRNA biomarkers only consider the expression variation of miRNAs or rely heavily on training sets. These deficiencies lead to high false-positive rates. The independent regulatory model is an important complement to traditional models of co-regulation and is more impervious to the dataset. In addition, previous studies of miRNA mechanisms in the development of non-small cell lung cancer (NSCLC) have mostly focused on the post-transcriptional level and did not distinguish between NSCLC subtypes. For the above problems, we improved mainly in two areas: miRNA identification based on both the NOG network and biological functions of miRNA target genes; and the construction of a 4-node directed competitive regulatory network to illustrate the mechanisms. NSCLC was classified as lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) in this work. One miRNA biomarker of LUAD (miR-708-5p) and four of LUSC (miR-183-5p, miR-140-5p, miR-766-5p, and miR-766-3p) were obtained. They were validated using literature and external datasets. The ceRNA-hub-FFL involving transcription factors (TFs), microRNAs (miRNAs), mRNAs, and long non-coding RNAs (lncRNAs) was constructed. There were multiple interactions among these components within the net at the transcriptional, post-transcriptional, and protein levels. New regulations were revealed by the network. Meanwhile, the network revealed the reasons for the previous conflicting conclusions on the roles of CD44, ACTB, and ITGB1 in NSCLC, and demonstrated the necessity of typing studies on NSCLC. The novel miRNA markers screening method and the 4-node directed competitive ceRNA-hub-FFL network constructed in this work can provide new ideas for screening tumor markers and understanding tumor development mechanisms in depth.

Clinical evidence construction of East Asian herbal medicine for inflammatory pain in rheumatoid arthritis based on integrative data mining approach

BACKGROUND

Rheumatoid arthritis (RA) is a chronic inflammatory disease that leads to a significant social burden. East Asian herbal medicine (EAHM) has long been used to treat RA. Therefore, a systematic study of how EAHM treatments can be developed into new drugs using specific materials is needed.

METHODS

Eleven databases containing literature in English, Korean, Chinese, and Japanese were searched for randomized controlled trials comparing EAHM with conventional medicine (CM). A meta-analysis was performed on the variable data to assess their effects on inflammatory pain. Subsequently, we searched for core materials and combinations of core material-based data mining methods.

RESULTS

A total of 186 trials involving 19,716 patients with RA met the inclusion criteria. According to the meta-analysis, EAHM had a significantly superior effect on continuous pain intensity, tender joint count, and response rate. Patients treated with EAHM had a significantly reduced incidence of adverse events compared with those treated with CM. Based on additional analysis of the EAHM formula data included in this meta-analysis, 21 core materials and five core herbal combinations were identified.

CONCLUSION

EAHM remedies for RA have the adequate potential for use as candidate materials for treating inflammatory pain in RA. The candidate core herbs evaluated in this study act on multiple pathways and are expected to provide pain relief, sustained inflammation suppression, immune regulation, and prevention of joint destruction. It seems worthwhile to conduct follow-up research on drug development using the core materials derived from this review.

miRNAs as molecular biomarkers for prostate cancer

MicroRNAs (miRNAs) are short noncoding RNA able to regulate specific mRNA stability, thus influencing target gene expression. Disrupted levels of several miRNA have been associated with prostate cancer, the leading cause of cancer death among men and the fifth leading cause of death worldwide. Here, we investigated whether miR-145, miR-148, and miR-185 circulating levels in plasma could be used as molecular biomarkers, to allow distinguishing between individuals with benign prostatic hyperplasia, precancerous lesion, and prostate cancer. In this study, we recruited 170 urological clinic patients with suspected prostate cancer who underwent prostate biopsy. Total RNA was isolated from plasma, and TaqMan MicroRNA assays were used to analyze miR-145, miR-185, and miR-148 expression. First, differential miRNA expression among patient groups was evaluated. Then, miRNA levels were combined with clinical assessment outcomes, including results from invasive tests, using multivariate analysis to examine their ability in discriminating among the three patient groups. Our results suggest that miRNA is a promising molecular tool for clinical management of at-risk patients.

Identification of key miRNAs in prostate cancer progression based on miRNA-mRNA network construction

Prostate cancer (PC) is one of the major male cancers. Differential diagnosis of PC is indispensable for the individual therapy, i.e., Gleason score (GS) that describes the grade of cancer can be used to choose the appropriate therapy. However, the current techniques for PC diagnosis and prognosis are not always effective. To identify potential markers that could be used for differential diagnosis of PC, we analyzed miRNA-mRNA interactions and we build specific networks for PC onset and progression. Key differentially expressed miRNAs for each GS were selected by calculating three parameters of network topology measures: the number of their single regulated mRNAs (NSR), the number of target genes (NTG) and NSR/NTG. miRNAs that obtained a high statistically significant value of these three parameters were chosen as potential biomarkers for computational validation and pathway analysis. 20 miRNAs were identified as key candidates for PC. 8 out of 20 miRNAs (miR-25-3p, miR-93-3p, miR-122-5p, miR-183-5p, miR-615-3p, miR-7-5p, miR-375, and miR-92a-3p) were differentially expressed in all GS and proposed as biomarkers for PC onset. In addition, "Extracellular-receptor interaction", "Focal adhesion", and "microRNAs in cancer" were significantly enriched by the differentially expressed target genes of the identified miRNAs. miR-10a-5p was found to be differentially expressed in GS 6, 7, and 8 in PC samples. 3 miRNAs were identified as PC GS-specific differentially expressed miRNAs: miR-155-5p was identified in PC samples with GS 6, and miR-142-3p and miR-296-3p in PC samples with GS 9. The efficacy of 20 miRNAs as potential biomarkers was revealed with a Random Forest classification using an independent dataset. The results demonstrated our 20 miRNAs achieved a better performance (AUC: 0.73) than miRNAs selected with Boruta algorithm (AUC: 0.55), a method for the automated feature extraction. Studying miRNA-mRNA associations, key miRNAs were identified with a computational approach for PC onset and progression. Further experimental validations are needed for future translational development.

MoS2@Ti3C2 nanohybrid-based photoelectrochemical biosensor: A platform for ultrasensitive detection of cancer biomarker exosomal miRNA

As a class of newly identified biomarkers, miRNAs show enormous potential in cancer diagnosis. The sensitive detection of abnormal miRNAs concentration to realize early diagnosis of malignant tumors is a frontier in the field of biosensing. In this work, a photoelectrochemical (PEC) biosensor based on MoS₂@Ti₃C₂ nanohybrid was fabricated for the ultrasensitive detection of miRNAs. The hybridization of Ti₃C₂ with excellent electron transfer capability significantly enhances the photocurrent response of the PEC biosensor. Moreover, the electrodeposition of Au nanoparticles on the surface of MoS₂@Ti₃C₂ nanohybrid further enhances the photocurrent. The detection performance of the PEC biosensor has been tested using colorectal cancer-related exosomal miRNA (miR-92a-3p) as the target. The PEC biosensor shows a broad linear detection ranged from 1 fM to 100 nM and a calculated detection limit of 0.27 fM. In terms of selectivity, the PEC biosensor can distinguish miR-92a-3p from mismatched sequences. The 16 continuous radiation source on-off cycles test indicates the high stability of the PEC biosensor. Furthermore, the accurate detection of exosomal miR-92a-3p concentrations of patients and healthy controls demonstrates the clinical feasibility of the PEC biosensor. Based on these outcomes, the PEC biosensor exhibits the prospect of realizing the ultrasensitive point-of-care detection of miRNAs.

A facile biosynthesis strategy of plasmid DNA-derived nanowires for readable microRNA logic operations

Multiple microRNAs (miRNAs) logical assays have attracted wide attention recently, which can be applied to mimic and reveal cellular events at the molecular level. However, it remains challenging to develop...

Communication between cells: exosomes as a delivery system in prostate cancer

Despite the considerable efforts in screening and diagnostic protocols, prostate cancer still represents the second leading cause of cancer-related death in men. Many patients with localized disease and low risk of recurrence have a favourable outcome. In a substantial proportion of patients, however, the disease progresses and becomes aggressive. The mechanisms that promote prostate cancer progression remain still debated. Many findings point to the role of cross-communication between prostate tumor cells and their surrounding microenvironment during the disease progression. Such a connection fosters survival, proliferation, angiogenesis, metastatic spreading and drug-resistance of prostate cancer. Recent years have seen a profound interest in understanding the way by which prostate cancer cells communicate with the surrounding cells in the microenvironment. In this regard, direct cell-to-cell contacts and soluble factors have been identified. Increasing evidence indicates that PC cells communicate with the surrounding cells through the release of extracellular vesicles, mainly the exosomes. By directly acting in stromal or prostate cancer epithelial cells, exosomes represent a critical intercellular communication system. By querying the public database ( https://pubmed.ncbi.nlm.nih.gov ) for the past 10 years, we have found more than four hundred papers. Among them, we have extrapolated the most relevant about the role of exosomes in prostate cancer malignancy and progression. Emerging data concerning the use of these vesicles in diagnostic management and therapeutic guidance of PC patients are also presented. Video Abstract.

Integrating microRNA expression, miRNA-mRNA regulation network and signal pathway: a novel strategy for lung cancer biomarker discovery

Background

Since there are inextricably connections among molecules in the biological networks, it would be a more efficient and accurate research strategy to screen microRNA (miRNA) markers combining with miRNA-mRNA regulatory networks. The independent regulation mode is more “fragile” and “influential” than the co-regulation mode. miRNAs can be used as biomarkers if they can independently regulate hub genes with important roles in the PPI network, simultaneously the expression products of the regulated hub genes play important roles in the signaling pathways of related tissue diseases.

Methods

We collected miRNA expression of non-small cell lung cancer (NSCLC) from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. Volcano plot and signal-to-noise ratio (SNR) methods were used to obtain significant differentially expressed (SDE) miRNAs from the TCGA database and GEO database, respectively. A human miRNA-mRNA regulatory network was constructed and the number of genes uniquely targeted (NOG) by a certain miRNA was calculated. The area under the curve (AUC) values were used to screen for clinical sensitivity and specificity. The candidate markers were obtained using the criteria of the top five maximum AUC values and NOG ≥ 3. The protein–protein interaction (PPI) network was constructed and independently regulated hub genes were obtained. Gene Ontology (GO) analysis and KEGG pathway analysis were used to identify genes involved in cancer-related pathways. Finally, the miRNA which can independently regulate a hub gene and the hub gene can participate in an important cancer-related pathway was considered as a biomarker. The AUC values and gene expression profile analysis from two external GEO datasets as well as literature validation were used to verify the screening capability and reliability of this marker.

Results

Fifteen SDE miRNAs in lung cancer were obtained from the intersection of volcano plot and SNR based on the GEO database and the TCGA database. Five miRNAs with the top five maximum AUC values and NOG ≥ 3 were screened out. A total of 61 hub genes were obtained from the PPI network. It was found that the hub gene GTF2F2 was independently regulated by miR-708-5p. Further pathway analysis indicated that GTF2F2 participates in protein expression by binding with polymerase II, and it can regulate transcription and accelerate tumor growth. Hence, miR-708-5p could be used as a biomarker. The good screening capability and reliability of miR-708-5p as a lung cancer marker were confirmed by AUC values and gene expression profiling of external datasets, and experimental literature. The potential mechanism of miR-708-5p was proposed.

Conclusions

This study proposes a new idea for lung cancer marker screening by integrating microRNA expression, regulation network and signal pathway. miR-708-5p was identified as a biomarker using this novel strategy. This study may provide some help for cancer marker screening.

miR‑367‑3p downregulates Rab23 expression and inhibits Hedgehog signaling resulting in the inhibition of the proliferation, migration, and invasion of prostate cancer cells

MicroRNAs play an important role in tumor cell proliferation, invasion, and Rab23 is a member of the Ras-related small GTPase family and plays a critical role in the progression of may types of tumors. The present study was designed to investigate the inhibitory effect of microRNA (miR)-367-3p on the proliferation, invasion, and metastasis of prostate cancer cells. qRT-PCR was used to detect the expression of miR-367-3p in prostate cancer and adjacent tissues. Cell proliferation, scratch, and Transwell assays were performed to verify the inhibitory effect of miR-367-3p overexpression or Ras-related protein Rab 23 (Rab23) knockdown on prostate cancer. Double luciferase reporter assay was utilized to verify whether miR-367-3p could target the Rab23 3′-untranslated region (UTR). The expression levels of Rab23, Gli1, and Gli2 in prostate cancer cells transfected with the miR-367-3p mimic were detected via qRT-PCR analysis. miR-367-3p expression in the prostate cancer tissues was downregulated compared with that in the para-cancer control tissues. miR-367-3p expression in DU145 and PC3 cells was also downregulated compared with that in the human prostate epithelial cell line RWPE-1. The overexpression of miR-367-3p or the knockdown of Rab23 inhibited the proliferation, invasion, and metastasis of prostate cancer cells. The results of the luciferase reporter assay confirmed that Rab23 was a target gene that was regulated by miR-367-3p. miR-367-3p specifically bound to the 3′-UTR of Rab23 mRNA. The overexpression of miR-367-3p inhibited Rab23 expression and the Hedgehog pathway. Cell function experiments confirmed that the overexpression of Rab23 reversed the anticancer effect of miR-367-3p. miR-367-3p was able to inhibit the Hedgehog pathway by targeting the expression of the Rab23 gene, thus inhibiting the proliferation, invasion, and metastasis of prostate cancer cells.

Bioinformatics Accelerates the Major Tetrad: A Real Boost for the Pharmaceutical Industry

With advanced technology and its development, bioinformatics is one of the avant-garde fields that has managed to make amazing progress in the pharmaceutical-medical field by modeling the infrastructural dimensions of healthcare and integrating computing tools in drug innovation, facilitating prevention, detection/more accurate diagnosis, and treatment of disorders, while saving time and money. By association, bioinformatics and pharmacovigilance promoted both sample analyzes and interpretation of drug side effects, also focusing on drug discovery and development (DDD), in which systems biology, a personalized approach, and drug repositioning were considered together with translational medicine. The role of bioinformatics has been highlighted in DDD, proteomics, genetics, modeling, miRNA discovery and assessment, and clinical genome sequencing. The authors have collated significant data from the most known online databases and publishers, also narrowing the diversified applications, in order to target four major areas (tetrad): DDD, anti-microbial research, genomic sequencing, and miRNA research and its significance in the management of current pandemic context. Our analysis aims to provide optimal data in the field by stratification of the information related to the published data in key sectors and to capture the attention of researchers interested in bioinformatics, a field that has succeeded in advancing the healthcare paradigm by introducing developing techniques and multiple database platforms, addressed in the manuscript.

Identification of Specific Modules and Hub microRNAs Related to Osteosarcoma by Weighted microRNA Co-Expression Network Analysis

Osteosarcoma (OS) is a malignant tumor with high morbidity and poor prognosis, especially for patients with metastasis. New therapeutic approaches are extremely needed. MicroRNAs can affect manykey biological processes, including the development and progression of complex diseases, such as OS. Here we identified specific modules and hub microRNAs related to OS through weighted gene co-expression network analysis (WGCNA). A module consisting of 72 microRNAs were found to be highly related to OS and 22 of them have been reported as deregulatedmicroRNAs in OS patients which play a role in OS tumorigenesis, development or prognosis. Then the target genes of the microRNAs were predicted and the functional enrichment analysis was performed on these genes. This study will provide a more clear understanding for facilitating the characterization and identification of new biomarkers and treatment for patients with OS by targeted miRNA.

MiR-378a-3p as a putative biomarker for hepatocellular carcinoma diagnosis and prognosis: Computational screening with experimental validation

BACKGROUND

Hepatocellular carcinoma (HCC) is a malignant disease with high morbidity and mortality, and the molecular mechanism for the genesis and progression is complex and heterogeneous. Biomarker discovery is crucial for the personalized and precision treatment of HCC. The accumulation of reported microRNA biomarkers makes it possible to combine computational identification with experimental validation to accelerate the discovery of novel biomarker.

RESULTS

In the present work, we applied a rational computer-aided biomarker discovery model to screen for the HCC diagnosis biomarker. Two HCC-associated networks were constructed based on the microRNA and mRNA expression profiles, and the potential microRNA biomarkers were identified based on their unique regulatory and influential power in the network. These putative biomarkers were then experimentally validated. One prominent example among these identified biomarkers is MiR-378a-3p: It was shown to independently regulate several important transcription factors such as PLAGL2 and β-catenin, affecting the β-catenin signaling. Such mechanism may indicate a potential tumor suppressor role of MiR-378a-3p and the impact of its abnormal expression on the cell growth and invasion of HCC.

CONCLUSIONS

A bioinformatics model with network topological and functional characterization was successfully applied to the identification of HCC biomarkers. The predicted microRNA biomarkers were than validated with experiments using human HCC cell lines, model animal, and clinical specimens. The results confirmed the prediction by our proposed model that miR-378a-3p was a putative biomarker for diagnosis and prognosis of HCC.

Globally ncRNAs Expression Profiling of TNBC and Screening of Functional lncRNA

One of the most well-known cancer subtypes worldwide is triple-negative breast cancer (TNBC) which has reduced prediction due to its antagonistic biotic actions and target's deficiency for the treatment. The current work aims to discover the countenance outlines and possible roles of lncRNAs in the TNBC via computational approaches. Long non-coding RNAs (lncRNAs) exert profound biological functions and are widely applied as prognostic features in cancer. We aim to identify a prognostic lncRNA signature for the TNBC. First, samples were filtered out with inadequate tumor purity and retrieved the lncRNA expression data stored in the TANRIC catalog. TNBC sufferers were divided into two prognostic classes which were dependent on their survival time (shorter or longer than 3 years). Random forest was utilized to select lncRNA features based on the lncRNAs differential expression between shorter and longer groups. The Stochastic gradient boosting method was used to construct the predictive model. As a whole, 353 lncRNAs were differentially transcribed amongst the shorter and longer groups. Using the recursive feature elimination, two lncRNAs were further selected. Trained by stochastic gradient boosting, we reached the highest accuracy of 69.69% and area under the curve of 0.6475. Our findings showed that the two-lncRNA signs can be proved as potential biomarkers for the prognostic grouping of TNBC's sufferers. Many lncRNAs remained dysregulated in TNBC, while most of them are likely play a role in cancer biology. Some of these lncRNAs were linked to TNBC's prediction, which makes them likely to be promising biomarkers.

Cancer-associated fibroblast-secreted exosomal miR-423-5p promotes chemotherapy resistance in prostate cancer by targeting GREM2 through the TGF-β signaling pathway

Therapeutic failure in prostate cancer (PC) is believed to result from its unusually invasive and metastatic nature. Cancer-associated fibroblasts (CAFs) are essential in the tumor microenvironment. We intended to study the role of CAF-derived exosomes in the context of PC and the potential regulatory mechanism associated with miR-423-5p and GREM2. CAF-derived exosomes decreased the chemosensitivity of parental PC cells and enhanced the drug resistance of drug-resistant cells. PC-associated fibroblast-derived exosomes carrying miR-423-5p increased the resistance of PC to taxane by inhibiting GREM2 through the TGF-β pathway. Inhibition of the TGF-β pathway partially reversed the increased drug resistance in PC cells induced by CAF-derived exosomes. Inhibition of miR-423-5p enhanced the drug sensitivity of PC cells in vivo. We showed that CAF-secreted exosomal miR-423-5p promoted chemotherapy resistance in PC by targeting GREM2 through the TGF-β pathway. This study may allow the development of novel approaches for PC.

Biomarker Discovery for the Carcinogenic Heterogeneity Between Colon and Rectal Cancers Based on lncRNA-Associated ceRNA Network Analysis

Background

Colorectal cancer (CRC) is one of the leading causes of cancer death worldwide. Emerging evidence has revealed that risk factors and metastatic patterns differ greatly between colon and rectal cancers. However, the molecular mechanism underlying their pathogenic differences remains unclear. Therefore, we here aimed to identify non-coding RNA biomarkers based on lncRNA-associated ceRNA network (LceNET) to elucidate the carcinogenic heterogeneity between colon and rectal cancers.

Methods

A global LceNET in human was constructed by employing experimental evidence-based miRNA-mRNA and miRNA-lncRNA interactions. Then, four context-specific ceRNA networks related to cancer initiation and metastasis were extracted by mapping differentially expressed lncRNAs, miRNAs and mRNAs to the global LceNET. Notably, a novel network-based bioinformatics model was proposed and applied to identify lncRNA/miRNA biomarkers and critical ceRNA triplets for understanding the carcinogenic heterogeneity between colon and rectal cancers. Moreover, the identified biomarkers were further validated by their diagnostic/prognostic performance, expression pattern and correlation analysis.

Results

Based on network modeling, lncRNA KCNQ1OT1 (AUC>0.85) and SNHG1 (AUC>0.94) were unveiled as common diagnostic biomarkers for the initiation and metastasis of colon and rectal cancers. qRT-PCR analysis uncovered that these lncRNAs had significantly higher expression level in CRC cell lines with high metastatic potential. In particular, KCNQ1OT1 and SNHG1 function in colon and rectal cancers via different ceRNA mechanisms. For example, KCNQ1OT1/miR-484/ANKRD36 axis was involved in the initiation of colon cancer, while KCNQ1OT1/miR-181a-5p/PCGF2 axis was implicated in the metastasis of rectal cancer; the SNHG1/miR-484/ORC6 axis played a role in colon cancer, while SNHG1/miR-423-5p/EZH2 and SNHG1/let-7b-5p/ATP6V1F axes participated in the initiation and metastasis of rectal cancer, respectively. In these ceRNA triplets, miR-484, miR-181a-5p, miR-423-5p and let-7b-5p were identified as miRNA biomarkers with excellent distinguishing ability between normal and tumor tissues, and ANKRD36, PCGF2, EZH2 and ATP6V1F were closely related to the prognosis of corresponding cancer.

Conclusion

The landscape of lncRNA-associated ceRNA network not only facilitates the exploration of non-coding RNA biomarkers, but also provides deep insights into the oncogenetic heterogeneity between colon and rectal cancers, thereby contributing to the optimization of diagnostic and therapeutic strategies of CRC.

MicroRNAs expression in pituitary tumors: differences related to functional status, pathological features, and clinical behavior

BACKGROUND

MicroRNAs (miRNAs) are small non-coding RNA molecules that regulate gene expression at post-transcriptional level, having a role in many biological processes, such as control of cell proliferation, cell cycle, and cell death. Altered miRNA expression has been reported in many neoplasms, including pituitary adenomas (PAs).

PURPOSE

In this study, we aimed to evaluate the expression of 20 miRNAs involved in pathways relevant to pituitary pathophysiology, in PAs and normal pituitary tissue and to correlate their expression profile with clinical and pathological features.

METHODS

Pituitary tumor samples were obtained during transphenoidal surgery from patients with non-functioning (NFPA, n = 12) and functioning (n = 11, 5 GH-, 3 ACTH-, 3 PRL-omas) PAs. The expression of selected miRNAs in PAs and in normal pituitary was analyzed by RT-qPCR. miRNAs expression was correlated with demographic, clinical, and neuroradiological data and with histopathological features including pituitary hormones immunostaining, Ki-67 proliferation index, and p53 immunohistochemistry evaluation.

RESULTS

All evaluated miRNAs except miR-711 were expressed in both normal and tumor pituitary tissue. Seventeen miRNAs were significantly down-regulated in pituitary tumors compared to normal pituitary. miRNAs were differentially expressed in functioning PAs or in NFPAs, as in the latter group miR-149-3p (p = 0.036), miR-130a-3p (p = 0.014), and miR-370-3p (p = 0.026) were significantly under expressed as compared to functioning tumors. Point-biserial correlation analysis demonstrated a negative correlation between miR-26b-5p and Ki-67 (p = 0.031) and between miR-30a-5p and 'atypical' morphological features (p = 0.038) or cavernous sinus invasion (p = 0.049), while 508-5p was inversely correlated with clinical aggressiveness (p = 0.043).

CONCLUSIONS

In this study, we found a significant down-regulation of 17 miRNAs in PAs vs normal pituitary, with differential expression profile related to functional status and tumor aggressiveness.

Computer-aided biomarker discovery for precision medicine: data resources, models and applications

Biomarkers are a class of measurable and evaluable indicators with the potential to predict disease initiation and progression. In contrast to disease-associated factors, biomarkers hold the promise to capture the changeable signatures of biological states. With methodological advances, computer-aided biomarker discovery has now become a burgeoning paradigm in the field of biomedical science. In recent years, the 'big data' term has accumulated for the systematical investigation of complex biological phenomena and promoted the flourishing of computational methods for systems-level biomarker screening. Compared with routine wet-lab experiments, bioinformatics approaches are more efficient to decode disease pathogenesis under a holistic framework, which is propitious to identify biomarkers ranging from single molecules to molecular networks for disease diagnosis, prognosis and therapy. In this review, the concept and characteristics of typical biomarker types, e.g. single molecular biomarkers, module/network biomarkers, cross-level biomarkers, etc., are explicated on the guidance of systems biology. Then, publicly available data resources together with some well-constructed biomarker databases and knowledge bases are introduced. Biomarker identification models using mathematical, network and machine learning theories are sequentially discussed. Based on network substructural and functional evidences, a novel bioinformatics model is particularly highlighted for microRNA biomarker discovery. This article aims to give deep insights into the advantages and challenges of current computational approaches for biomarker detection, and to light up the future wisdom toward precision medicine and nation-wide healthcare.

Data-driven translational prostate cancer research: from biomarker discovery to clinical decision

Prostate cancer (PCa) is a common malignant tumor with increasing incidence and high heterogeneity among males worldwide. In the era of big data and artificial intelligence, the paradigm of biomarker discovery is shifting from traditional experimental and small data-based identification toward big data-driven and systems-level screening. Complex interactions between genetic factors and environmental effects provide opportunities for systems modeling of PCa genesis and evolution. We hereby review the current research frontiers in informatics for PCa clinical translation. First, the heterogeneity and complexity in PCa development and clinical theranostics are introduced to raise the concern for PCa systems biology studies. Then biomarkers and risk factors ranging from molecular alternations to clinical phenotype and lifestyle changes are explicated for PCa personalized management. Methodologies and applications for multi-dimensional data integration and computational modeling are discussed. The future perspectives and challenges for PCa systems medicine and holistic healthcare are finally provided.

Human bone marrow mesenchymal stem cells-derived microRNA-205-containing exosomes impede the progression of prostate cancer through suppression of RHPN2

BACKGROUND

Human bone marrow mesenchymal stem cells (hBMSCs) are implicated in cancer initiation and metastasis, sometimes by releasing exosomes that mediate cell communication by delivering microRNAs (miRNAs). This study aimed to investigate the physiological mechanisms by which exosomal miR-205 derived from hBMSCs may modulate the growth of prostate cancer cells.

METHODS

Microarray-based gene expression profiling of prostate cancer was adopted to identify differentially expressed genes and regulatory miRNAs, which identified the candidates RHPN2 and miR-205 as the study focus. Then the binding affinity between miR-205 and RHPN2 was identified using in silico analysis and luciferase activity detection. Prostate cancer cells were co-cultured with exosomes derived from hBMSCs treated with either miR-205 mimic or miR-205 inhibitor. Subsequently, prostate cancer cell proliferation, invasion, migration, and apoptosis were detected in vitro. The effects of hBMSCs-miR-205 on tumor growth were investigated in vivo.

RESULTS

miR-205 was downregulated, while RHPN2 was upregulated in prostate cancer cells. RHPN2 was a target of miR-205, and upregulated miR-205 inhibited prostate cancer cell proliferation, invasion, and migration and promoted apoptosis by targeting RHPN2. Next, experiments demonstrated that hBMSCs-derived exosomes carrying miR-205 contributed to repressed prostate cancer cell proliferation, invasion, and migration and enhanced apoptosis. Furthermore, in vivo assays confirmed the inhibitory effects of hBMSCs-derived exosomal miR-205 on prostate cancer.

CONCLUSION

The hBMSCs-derived exosomal miR-205 retards prostate cancer progression by inhibiting RHPN2, suggesting that miR-205 may present a predictor and potential therapeutic target for prostate cancer.

Molecular Biomarkers in Localized Prostate Cancer: ASCO Guideline

PURPOSE

This guideline provides recommendations for available tissue-based prostate cancer biomarkers geared toward patient selection for active surveillance, identification of clinically significant disease, choice of postprostatectomy adjuvant versus salvage radiotherapy, and to address emerging questions such as the relative value of tissue biomarkers compared with magnetic resonance imaging.

METHODS

An ASCO multidisciplinary Expert Panel, with representatives from the European Association of Urology, American Urological Association, and the College of American Pathologists, conducted a systematic literature review of localized prostate cancer biomarker studies between January 2013 and January 2019. Numerous tissue-based molecular biomarkers were evaluated for their prognostic capabilities and potential for improving management decisions. Here, the Panel makes recommendations regarding the clinical use and indications of these biomarkers.

RESULTS

Of 555 studies identified, 77 were selected for inclusion plus 32 additional references selected by the Expert Panel. Few biomarkers had rigorous testing involving multiple cohorts and only 5 of these tests are commercially available currently: Oncotype Dx Prostate, Prolaris, Decipher, Decipher PORTOS, and ProMark. With various degrees of value and validation, multiple biomarkers have been shown to refine risk stratification and can be considered for select men to improve management decisions. There is a paucity of prospective studies assessing short- and long-term outcomes of patients when these markers are integrated into clinical decision making.

RECOMMENDATIONS

Tissue-based molecular biomarkers (evaluating the sample with the highest volume of the highest Gleason pattern) may improve risk stratification when added to standard clinical parameters, but the Expert Panel endorses their use only in situations in which the assay results, when considered as a whole with routine clinical factors, are likely to affect a clinical decision. These assays are not recommended for routine use as they have not been prospectively tested or shown to improve long-term outcomes-for example, quality of life, need for treatment, or survival. Additional information is available at www.asco.org/genitourinary-cancer-guidelines.

Network vulnerability-based and knowledge-guided identification of microRNA biomarkers indicating platinum resistance in high-grade serous ovarian cancer

Background

High-grade serous ovarian cancer (HGSC), the most common ovarian carcinoma type, is associated with the highest mortality rate among all gynecological malignancies. As chemoresistance has been demonstrated as the major challenge in improving the prognosis of HGSC patients, we here aimed to identify microRNA (miRNA) biomarkers for predicting platinum resistance and further explore their functions in HGSC.

Results

We developed and applied our network vulnerability-based and knowledge-guided bioinformatics model first time for the study of drug-resistance in cancer. Four miRNA biomarkers (miR-454-3p, miR-98-5p, miR-183-5p and miR-22-3p) were identified with potential in stratifying platinum-sensitive and platinum-resistant HGSC patients and predicting prognostic outcome. Among them, miR-454-3p and miR-183-5p were newly discovered to be closely implicated in platinum resistance in HGSC. Functional analyses highlighted crucial roles of the four miRNA biomarkers in platinum resistance through mediating transcriptional regulation, cell proliferation and apoptosis. Moreover, expression patterns of the miRNA biomarkers were validated in both platinum-sensitive and platinum-resistant ovarian cancer cells.

Conclusions

With bioinformatics modeling and analysis, we identified and confirmed four novel putative miRNA biomarkers, miR-454-3p, miR-98-5p, miR-183-5p and miR-22-3p that could serve as indicators of resistance to platinum-based chemotherapy, thereby contributing to the improvement of chemotherapeutic efficiency and optimization of personalized treatments in HGSC.

Micro-RNA 205-5p is Involved in the Progression of Gastric Cancer and Targets Phosphatase and Tensin Homolog (PTEN) in SGC-7901 Human Gastric Cancer Cells

Background

This study aimed to investigate the role of micro-RNA 205-5p (miR-205-5p) in the progression of gastric cancer, and the target of miR-205-5p in human gastric cancer cells in vitro.

Material/Methods

Expression of miR-205-5p and PTEN in gastric cancer tissue samples and adjacent normal gastric tissue from 35 patients was studied using immunohistochemistry and in situ hybridization. SGC-7901 human gastric cancer cells included a normal control (NC) group, a group transfected with empty vector (Vector), a group treated with miR-205-5p inhibitor (miR-inhibitor), and a group treated with miR-205-5p inhibitor and small interfering PTEN mRNA (miR-inhibitor+si-PTEN). Quantitative reverse transcription polymerase chain reaction (qRT-PCR) measured miR-205-5p expression, cell proliferation was measured by MTT assay, cell apoptosis by flow cytometry, transwell and wound healing assays measured cell migration, and transmission electron microscopy (TEM) showed ultrastructural changes in SGC-7901 cells. PTEN, AKT and p-AKT protein expression were measured using Western blot. The correlation between miR-205-5p and PTEN was analyzed using a dual-luciferase reporter assay.

Results

Increased expression of miR-205-5p and PTEN in gastric cancer tissues were correlated with tumor stage. In SGC-7901 cells, miR-205-5p mRNA expression in the miR-inhibitor and miR-inhibitor+si-PTEN groups was significantly lower than that in the NC group (P<0.001). In the miR-inhibitor group, cell proliferation was significantly decreased, and apoptosis was significantly increased (P<0.001).

Conclusions

In gastric cancer, increased expression of miR-205-5p was associated with tumor stage, and in SGC-7901 cells PTEN was a target gene for miR-205-5p.

miRFA: an automated pipeline for microRNA functional analysis with correlation support from TCGA and TCPA expression data in pancreatic cancer

BACKGROUND

MicroRNAs (miRNAs) are small RNAs that regulate gene expression at a post-transcriptional level and are emerging as potentially important biomarkers for various disease states, including pancreatic cancer. In silico-based functional analysis of miRNAs usually consists of miRNA target prediction and functional enrichment analysis of miRNA targets. Since miRNA target prediction methods generate a large number of false positive target genes, further validation to narrow down interesting candidate miRNA targets is needed. One commonly used method correlates miRNA and mRNA expression to assess the regulatory effect of a particular miRNA. The aim of this study was to build a bioinformatics pipeline in R for miRNA functional analysis including correlation analyses between miRNA expression levels and its targets on mRNA and protein expression levels available from the cancer genome atlas (TCGA) and the cancer proteome atlas (TCPA). TCGA-derived expression data of specific mature miRNA isoforms from pancreatic cancer tissue was used.

RESULTS

Fifteen circulating miRNAs with significantly altered expression levels detected in pancreatic cancer patients were queried separately in the pipeline. The pipeline generated predicted miRNA target genes, enriched gene ontology (GO) terms and Kyoto encyclopedia of genes and genomes (KEGG) pathways. Predicted miRNA targets were evaluated by correlation analyses between each miRNA and its predicted targets. MiRNA functional analysis in combination with Kaplan-Meier survival analysis suggest that hsa-miR-885-5p could act as a tumor suppressor and should be validated as a potential prognostic biomarker in pancreatic cancer.

CONCLUSIONS

Our miRNA functional analysis (miRFA) pipeline can serve as a valuable tool in biomarker discovery involving mature miRNAs associated with pancreatic cancer and could be developed to cover additional cancer types. Results for all mature miRNAs in TCGA pancreatic adenocarcinoma dataset can be studied and downloaded through a shiny web application at https://emmbor.shinyapps.io/mirfa/ .

MicroRNA dysregulational synergistic network: discovering microRNA dysregulatory modules across subtypes in non-small cell lung cancers

Background

The majority of cancer-related deaths are due to lung cancer, and there is a need for reliable diagnostic biomarkers to predict stages in non-small cell lung cancer cases. Recently, microRNAs were found to have potential as both biomarkers and therapeutic targets for lung cancer. However, some of the microRNA’s functions are unknown, and their roles in cancer stage progression have been mostly undiscovered in this clinically and genetically heterogeneous disease. As evidence suggests that microRNA dysregulations are implicated in many diseases, it is essential to consider the changes in microRNA-target regulation across different lung cancer subtypes.

Results

We proposed a pipeline to identify microRNA synergistic modules with similar dysregulation patterns across multiple subtypes by constructing the MicroRNA Dysregulational Synergistic Network. From the network, we extracted microRNA modules and incorporated them as prior knowledge to the Sparse Group Lasso classifier. This leads to a more relevant selection of microRNA biomarkers, thereby improving the cancer stage classification accuracy. We applied our method to the TCGA Lung Adenocarcinoma and the Lung Squamous Cell Carcinoma datasets. In cross-validation tests, the area under ROC curve rate for the cancer stages prediction has increased considerably when incorporating the learned microRNA dysregulation modules. The extracted modules from multiple independent subtypes differential analyses were found to have high agreement with microRNA family annotations, and they can also be used to identify mutual biomarkers between different subtypes. Among the top-ranked candidate microRNAs selected by the model, 87% were reported to be related to Lung Adenocarcinoma. The overall result demonstrates that clustering microRNAs from the dysregulation pattern between microRNAs and their targets leads to biomarkers with high precision and recall rate to known differentially expressed disease-associated microRNAs.

Conclusions

The results indicated that our method improves microRNA biomarker selection by detecting similar microRNA dysregulational synergistic patterns across the multiple subtypes. Since microRNA-target dysregulations are implicated in many cancers, we believe this tool can have broad applications for discovery of novel microRNA biomarkers in heterogeneous cancer diseases.

The role of microRNAs in prostate cancer migration, invasion, and metastasis

Prostate cancer (PCa) is considered the most prevalent malignancy and the second major cause of cancer-related death in males from Western countries. PCa exhibits variable clinical pictures, ranging from dormant to highly metastatic cancer. PCa suffers from poor prognosis and diagnosis markers, and novel biomarkers are required to define disease stages and to design appropriate therapeutic approach by considering the possible genomic and epigenomic differences. MicroRNAs (miRNAs) comprise a class of small noncoding RNAs, which have remarkable functions in cell formation, differentiation, and cancer development and contribute in these processes through controlling the expressions of protein-coding genes by repressing translation or breaking down the messenger RNA in a sequence-specific method. miRNAs in cancer are able to reflect informative data about the current status of disease and this might benefit PCa prognosis and diagnosis since that is concerned to PCa patients and we intend to highlight it in this paper.

Anabolic Androgenic Steroids: Searching New Molecular Biomarkers

Even if anabolic androgenic steroid (AAS) abuse is clearly associated with a wide spectrum of collateral effects, adolescents and athletes frequently use a large group of synthetic derivatives of testosterone, both for aesthetic uses and for improving performance. Over the last few years, the development of MicroRNA (miRNA) technologies has become an essential part of research projects and their role as potential molecular biomarkers is being investigated by the scientific community. The circulating miRNAs detection as a diagnostic or prognostic tool for the diagnosis and treatment of several diseases is very useful, because with a minimal quantity of sample (peripheral blood), miRNAs are very sensitive. Even more, miRNAs remain stable both at room temperature and during freeze-thaw cycles. These characteristics highlight the important role of miRNAs in the near future as new tools for anti-doping. The article provides a systematic review and meta-analysis on the role of miRNAs as new potential molecular biomarkers of AAS use/abuse. Particularly, this paper analyzed the “miRNA signature” use as biomarkers for health disorders, focusing on the organ damages which are related to ASS use/abuse. Moreover, this review aims to provide a future prospect for less invasive or non-invasive procedures for the detection of circulating miRNA biomarkers as doping assumption signaling.

MiRNA-BD: an evidence-based bioinformatics model and software tool for microRNA biomarker discovery

MicroRNAs (miRNAs) are small non-coding RNAs with the potential as biomarkers for disease diagnosis, prognosis and therapy. In the era of big data and biomedical informatics, computer-aided biomarker discovery has become the current frontier. However, most of the computational models are highly dependent on specific prior knowledge and training-testing procedures, very few are mechanism-guided or evidence-based. To the best of our knowledge, untill now no general rules have been uncovered and applied to miRNA biomarker screening. In this study, we manually collected literature-reported cancer miRNA biomarkers and analyzed their regulatory patterns, including the regulatory modes, biological functions and evolutionary characteristics of their targets in the human miRNA-mRNA network. Two evidences were statistically detected and used to distinguish biomarker miRNAs from others. Based on these observations, we developed a novel bioinformatics model and software tool for miRNA biomarker discovery ( http://sysbio.suda.edu.cn/MiRNA-BD/ ). In contrast to routine methods that focus on miRNA synergic functions, our method searches for vulnerable sites in the miRNA-mRNA network and considers the independent regulatory power of miRNAs, i.e., single-line regulations between miRNAs and mRNAs. The performance comparison demonstrates the generality and precision of our model, which identifies miRNA biomarkers for cancers as well as other complex diseases without training or specific prior knowledge.

The putative tumour suppressor miR-1-3p modulates prostate cancer cell aggressiveness by repressing E2F5 and PFTK1

BACKGROUND

Previous studies report that miR-1-3p, a member of the microRNA-1 family (miR-1), and functions as a tumor suppressor in several different cancers. However, little is known regarding the biological role and intrinsic regulatory mechanisms of miR-1-3p in prostate cancer (PCa).

METHODS

In this study, the expression levels of miR-1-3p were first examined in PCa cell lines and tumor tissues by RT-qPCR and bioinformatics. The in vitro and in vivo functional effect of miR-1-3p was examined further. A luciferase reporter assay was conducted to confirm target associations.

RESULTS

We found that miR-1-3p was significantly downregulated in advanced PCa tissues and cell lines. Low miR-1-3p levels were strongly associated with aggressive clinicopathological features and poor prognosis in PCa patients. Ectopic expression of miR-1-3p in 22RV1 and LncaP cells was sufficient to prevent tumor cell growth and cell cycle progression in vitro and in vivo. Further mechanistic studies revealed that miR-1-3p could directly target the mRNA 3'- untranslated region (3'- UTR) of two central cell cycle genes, E2F5 and PFTK1, and could suppress their mRNA and protein expression. In addition, knockdown of E2F5 and PFTK1 mimicked the tumor-suppressive effects of miR-1-3p overexpression on PCa progression. Conversely, concomitant knockdown of miR-1-3p and E2F5 and PFTK1 substantially reversed the inhibitory effects of either E2F5 or PFTK1 silencing alone.

CONCLUSION

These data highlight an important role for miR-1-3p in the regulation of proliferation and cell cycle in the molecular etiology of PCa and indicate the potential for miR-1-3p in applications furthering PCa prognostics and therapeutics.

miR-1266-5p and miR-185-5p Promote Cell Apoptosis in Human Prostate Cancer Cell Lines

Objective:

Small non-coding RNA molecules are dysregulated in prostate cancer (PCa). In our previous study, downregulation of miR-1266 and miR-185 was demonstrated in PCa tissues and cell lines. The aim of the present study was to investigate whether miR-1266 and miR-185 are involved in the regulation of B-cell lymphoma (BCL) 2 and BCL2L1, respectively, and whether transfection of PCa cell lines with miR-1266 and miR-185 mimics can alter tumorigenic phenotypes.

Methods:

In order to investigate the regulation of BCL2 and BCL2L1 mRNA levels by miR-1266 and miR-185, respectively, a luciferase reporter assay was used. Real-time PCR was also used to analyze changes in the levels of BCL2 and BCL2L1 mRNAs in PCa cell lines following transfection with synthetic miR-1266 and miR-185. Cell apoptosis was determined by Annexin V protein expression analysis via flow cytometry. In addition to the MTT assay, a cell proliferation assay was performed.

Result:

A luciferase assay confirmed that the BCL2 and BCL2L1 genes may be targeted by miR-1266 and miR-185, respectively, through binding to their 3′UTR regions. Transfection of PC3 and DU145 cells with miR-1266 and miR-185 induced apoptosis and reduced proliferation, which also revealed an inverse correlation with BCL2 and BCL2L1 gene expression in the treated cells.

Conclusion:

Our data suggests that miR-1266 and miR-185 may be novel candidates for further research in PCa treatment through the anti-apoptotic pathway.

Translational Bioinformatics for Cholangiocarcinoma: Opportunities and Challenges

Translational bioinformatics is becoming a driven force and a new scientific paradigm for cancer research in the era of big data. To promote the cross-disciplinary communication and research, we take cholangiocarcinoma as an example to review the present status and the future perspectives of the bioinformatics models applied in cancer study. We first summarize the present application of computational methods to the study of cholangiocarcinoma ranged from pattern recognition of biological data, knowledge based data annotation to systems biological level modeling and clinical translation. Then the future opportunities and challenges about database or knowledge base building, novel model developing and molecular mechanism exploring as well as the intelligent decision supporting system construction for the precision diagnosis, prognosis and treatment of cholangiocarcinoma are discussed.

Biomarker microRNAs for prostate cancer metastasis: screened with a network vulnerability analysis model

Background

Prostate cancer (PCa) is a fatal malignant tumor among males in the world and the metastasis is a leading cause for PCa death. Biomarkers are therefore urgently needed to detect PCa metastatic signature at the early time. MicroRNAs are small non-coding RNAs with the potential to be biomarkers for disease prediction. In addition, computer-aided biomarker discovery is now becoming an attractive paradigm for precision diagnosis and prognosis of complex diseases.

Methods

In this study, we identified key microRNAs as biomarkers for predicting PCa metastasis based on network vulnerability analysis. We first extracted microRNAs and mRNAs that were differentially expressed between primary PCa and metastatic PCa (MPCa) samples. Then we constructed the MPCa-specific microRNA-mRNA network and screened microRNA biomarkers by a novel bioinformatics model. The model emphasized the characterization of systems stability changes and the network vulnerability with three measurements, i.e. the structurally single-line regulation, the functional importance of microRNA targets and the percentage of transcription factor genes in microRNA unique targets.

Results

With this model, we identified five microRNAs as putative biomarkers for PCa metastasis. Among them, miR-101-3p and miR-145-5p have been previously reported as biomarkers for PCa metastasis and the remaining three, i.e. miR-204-5p, miR-198 and miR-152, were screened as novel biomarkers for PCa metastasis. The results were further confirmed by the assessment of their predictive power and biological function analysis.

Conclusions

Five microRNAs were identified as candidate biomarkers for predicting PCa metastasis based on our network vulnerability analysis model. The prediction performance, literature exploration and functional enrichment analysis convinced our findings. This novel bioinformatics model could be applied to biomarker discovery for other complex diseases.

Electronic supplementary material

The online version of this article (10.1186/s12967-018-1506-7) contains supplementary material, which is available to authorized users.

Identification of biomarker microRNAs for predicting the response of colorectal cancer to neoadjuvant chemoradiotherapy based on microRNA regulatory network

Preoperative radiotherapy or chemoradiotherapy has become a standard procedure for treatment of patients with locally advanced colorectal cancer (CRC). However, patients’ responses to treatment are different and personalized. MicroRNAs (miRNAs) are promising biomarkers for predicting personalized responses. In this study, we collected 30 publicly reported miRNAs associated with chemoradiotherapy of CRC. We extracted 46 differentially expressed miRNAs from samples of responders and non-responders to preoperative radiotherapy from the Gene Expression Omnibus dataset (Student's t test, p-value < 0.05 and |fold-change| > 2). We performed a systematic and integrative bioinformatics analysis to identify biomarker miRNAs for prediction of CRC responses to chemoradiotherapy. Using the bioinformatics model, miR-198, miR-765, miR-671-5p, miR-630, miR-371-5p, miR-575, miR-202, miR-483-5p and miR-513a-5p were screened as putative biomarkers for treatment response. Literature validation and functional enrichment analysis were exploited to confirm the reliability of the predicted miRNAs. Quantitative polymerase chain reaction showed that seven of the candidates were significantly differentially expressed between radiosensitive and insensitive CRC cell lines. The unique target genes of miR-198 and miR-765 were altered significantly upon transfection of specific miRNA mimics in the radiosensitive cell line. These results demonstrated the predictive power of our model and suggested that miR-198, miR-765, miR-630, miR-371-5p, miR-575, miR-202 and miR-513a-5p could be used for predicting the response of CRC to preoperative chemoradiotherapy.

EGBMMDA: Extreme Gradient Boosting Machine for MiRNA-Disease Association prediction

Associations between microRNAs (miRNAs) and human diseases have been identified by increasing studies and discovering new ones is an ongoing process in medical laboratories. To improve experiment productivity, researchers computationally infer potential associations from biological data, selecting the most promising candidates for experimental verification. Predicting potential miRNA–disease association has become a research area of growing importance. This paper presents a model of Extreme Gradient Boosting Machine for MiRNA-Disease Association (EGBMMDA) prediction by integrating the miRNA functional similarity, the disease semantic similarity, and known miRNA–disease associations. The statistical measures, graph theoretical measures, and matrix factorization results for each miRNA-disease pair were calculated and used to form an informative feature vector. The vector for known associated pairs obtained from the HMDD v2.0 database was used to train a regression tree under the gradient boosting framework. EGBMMDA was the first decision tree learning-based model used for predicting miRNA–disease associations. Respectively, AUCs of 0.9123 and 0.8221 in global and local leave-one-out cross-validation proved the model’s reliable performance. Moreover, the 0.9048 ± 0.0012 AUC in fivefold cross-validation confirmed its stability. We carried out three different types of case studies of predicting potential miRNAs related to Colon Neoplasms, Lymphoma, Prostate Neoplasms, Breast Neoplasms, and Esophageal Neoplasms. The results indicated that, respectively, 98%, 90%, 98%, 100%, and 98% of the top 50 predictions for the five diseases were confirmed by experiments. Therefore, EGBMMDA appears to be a useful computational resource for miRNA–disease association prediction.

MicroRNAs and regulated interaction networks reveal differences between adult and pediatric acute myeloid leukemia

OBJECTIVES

The purpose of this study was to identify featured microRNAs and their regulated network between adult and pediatric acute myeloid leukemia (AML) and find potential utility as biomarkers for diagnosis and treatment of pediatric AML.

METHODS

We downloaded the microRNA expression dataset GSE35320 from Gene Expression Omnibus database and selected expression chips from bone marrow of 71 pediatric AML samples and 6 adulthood AML samples. Differentially expressed microRNAs were identified by Wilcox test. The target genes of these microRNAs were predicted using an integrative method and their functional enrichment analysis was performed using DAVID. Finally, STRING database and Cytoscape software was used to construct and analyze the interaction network.

RESULTS

A total of 7 differentially expressed microRNAs were identified and the remarkably up-regulated and down-regulated microRNAs were miR-16 and miR-142-5p which included 323 and 22 predicted target genes, respectively. The target genes of 7 microRNAs were most associated with regulation of cell cycle, p53 signaling pathway, Wnt signaling pathway and neurotrophin signaling pathway. The interaction network of miR-16 target genes was constructed among 354 high confidence interaction pairs. The core genes of the network, such as TP53, BCL2, VEGFA, had a role in prognosis of children with AML.

CONCLUSIONS

The featured microRNAs and their target genes are significant in the occurrence and development of pediatric AML, which is likely to be important for the identification of therapeutic targets and biomarkers for these patients.

Biomarker MicroRNAs for Diagnosis of Oral Squamous Cell Carcinoma Identified Based on Gene Expression Data and MicroRNA-mRNA Network Analysis

Oral squamous cell carcinoma is one of the most malignant tumors with high mortality rate worldwide. Biomarker discovery is critical for early diagnosis and precision treatment of this disease. MicroRNAs are small noncoding RNA molecules which often regulate essential biological processes and are good candidates for biomarkers. By integrative analysis of both the cancer-associated gene expression data and microRNA-mRNA network, miR-148b-3p, miR-629-3p, miR-27a-3p, and miR-142-3p were screened as novel diagnostic biomarkers for oral squamous cell carcinoma based on their unique regulatory abilities in the network structure of the conditional microRNA-mRNA network and their important functions. These findings were confirmed by literature verification and functional enrichment analysis. Future experimental validation is expected for the further investigation of their molecular mechanisms.

Inhibition of microRNA-500 has anti-cancer effect through its conditional downstream target of TFPI in human prostate cancer

PURPOSE

We investigated the prognostic potential and regulatory mechanism of microRNA-500 (miR-500), and human gene of tissue factor pathway inhibitor (TFPI) in prostate cancer.

METHODS

MiR-500 expression was assessed by qRT-PCR in prostate cancer cell lines and primary tumors. Cancer patients' clinicopathological factors and overall survival were analyzed according to endogenous miR-500 level. MiR-500 was downregulated in DU145 and VCaP cells. Its effect on prostate cancer proliferation, invasion in vitro, and tumorigenicity in vivo, were probed. Possible downstream target of miR-500, TFPI was assessed by luciferase assay and qRT-PCR in prostate cancer cells. In miR-500-downregulated DU145 and VCaP cells, TFPI was silenced to see whether it was directly involved in the regulation of miR-500 in prostate cancer. TFPI alone was either upregulated or downregulated in DU145 and VCaP cells. Their effect on prostate cancer development was further evaluated.

RESULTS

MiR-500 is upregulated in both prostate cancer cells and primary tumors. In prostate cancer patients, high miR-500 expression is associated with poor prognosis and overall survival. In DU145 and VCaP cells, miR-500 downregulation inhibited cancer proliferation, invasion in vitro, and explant growth in vivo. TFPI was verified to be associated with miR-500 in prostate cancer. Downregulation of TFPI reversed anti-cancer effects of miR-500 downregulation in prostate cancer cells. However, neither TFPI upregulation nor downregulation alone had any functional impact on prostate cancer development.

CONCLUSION

MiR-500 may be a potential biomarker and molecular target in prostate cancer. TFPI may conditionally regulate prostate cancer in miR-500-downregualted prostate cancer cells.

Diagnostic MicroRNA Biomarker Discovery for Non-Small-Cell Lung Cancer Adenocarcinoma by Integrative Bioinformatics Analysis

Lung cancer is the leading cause of cancer death and its incidence is ranked high in men and women worldwide. Non-small-cell lung cancer (NSCLC) adenocarcinoma is one of the most frequent histological subtypes of lung cancer. The aberration profile and the molecular mechanism driving its progression are the key for precision therapy of lung cancer, while the screening of biomarkers is essential to the precision early diagnosis and treatment of the cancer. In this work, we applied a bioinformatics method to analyze the dysregulated interaction network of microRNA-mRNA in NSCLC, based on both the gene expression data and the microRNA-gene regulation network. Considering the properties of the substructure and their biological functions, we identified the putative diagnostic biomarker microRNAs, some of which have been reported on the PubMed citations while the rest, that is, miR-204-5p, miR-567, miR-454-3p, miR-338-3p, and miR-139-5p, were predicted as the putative novel microRNA biomarker for the diagnosis of NSCLC adenocarcinoma. They were further validated by functional enrichment analysis of their target genes. These findings deserve further experimental validations for future clinical application.

Significantly altered expression of miR-511-3p and its target AKT3 has negative prognostic value in human prostate cancer

PURPOSE

In this study, we assessed the expression and functions of microRNA-511-3p (miR-511-3p) in human prostate cancer (CaP).

METHODS

Gene expressions of miR-511-3p in CaP cells and human CaP tumors were assessed by qPCR. In VCaP and PC3 cells, miR-511-3p was overexpressed by lentivirus. The functions of miR-511-3p upregulation in regulating in vitro cancer proliferation, migration and in vivo cancer growth were assessed by MTT, transwell and transplantation assays, respectively. Downstream target gene of miR-511-3p, AKT3, was verified by dual-luciferase activity and qPCR assays. AKT3 was then overexpressed in miR-511-3p-upregulated CaP cells to assess its functions in miR-511-3p-mediated cancer regulation.

RESULTS

MiR-511-3p is significantly downregulated in CaP cell lines, and human CaP tumors. MiR-511-3p was further downregulated in T3/T4-staged CaP tumors and closely correlated with shorter overall survival among CaP patients. In VCaP and PC3 cells, lentiviral-induced miR-511-3p upregulation was acting as a tumor suppressor by inhibiting in vitro cancer proliferation, migration and in vivo transplantation. Human AKT3 gene was confirmed to be the downstream target of miR-511-3p in CaP. In miR-511-3p-upregulated VCaP and PC3 cells, forced-overexpression of AKT3 reversed the tumor suppressive effects of miR-511-3p in CaP.

CONCLUSION

MiR-511-3p may serve as a prognostic factor and tumor suppressor in CaP, very likely through inverse regulation of its downstream target gene of AKT3.

MYC and hsa‑miRNA‑423‑5p as biomarkers in nasopharyngeal carcinoma revealed by miRNA‑mRNA‑pathway network integrated analysis

The present study was performed to identify the dysregulated microRNAs (miRNAs/miRs) and mRNAs, and enriched pathways involved in nasopharyngeal carcinoma (NPC) through the establishment of an miRNA-mRNA-pathways network. mRNA and miRNA expression profiles were collected from the European Molecular Biology Laboratory-European Bioinformatics Institute. Differentially expressed genes and differentially expressed miRNA were selectively screened using the metaDE package. Following prediction of the risk genes and pathway pairs involved in NPC, an miRNA-mRNA-pathway network was constructed by merging the miRNA-mRNA pairs, the mRNA-pathway pairs and the mRNA-mRNA pairs. The miRNA and mRNA biomarkers, as well as the functional pathway pairs, were identified in the network analysis, based on the topological properties of nodes in the network. Additionally, 10-fold cross-validation was performed to evaluate the performance of the selected risk genes and their corresponding miRNA in NPC by calculating the area under the curve (AUC). In total, 99 upregulated and 841 downregulated genes, and 192 upregulated and 26 downregulated miRNAs were identified. The miRNA-mRNA-pathway network was established using 403 miRNA-mRNA pairs, including 40 miRNAs and 302 risk genes, as well as 22 prominent pathway pairs. Network analysis demonstrated that v-myc avian myelocytomatosis viral oncogene homolog (MYC) and hsa-miR-423-5p were the mRNA and miRNA signatures for NPC, respectively. The AUC of these biomarkers for NPC was 0.7568 and 0.7798, respectively. Additionally, the focal adhesion pair pathway in cancer was identified to be associated with NPC. MYC and hsa-miR-423-5p have been identified to be critical biomarkers in NPC as revealed by miRNA-mRNA-pathway network integrated analysis, suggesting a direction for further research into the diagnosis and treatment of NPC.

High level of miR-196b at newly diagnosed pediatric acute myeloid leukemia predicts a poor outcome

Differential expression of microRNAs (miRNAs) has been implicated in leukemogenesis. We investigate the expression pattern of miR-196b. Using quantitative real-time PCR (qRT-PCR), we detected the expression of miR-196b and its correlated genes (SMC1A/MLH1) in initial pediatric AML. A significant association was observed between overexpression of miR-196b and inferior overall survival of pediatric AML (Log Rank P<0.0001). AML M4/5 subtype, high white blood cell (WBC) count at presentation, MLL rearrangement, or FLT3-ITD mutation at diagnosis and non-remission group after the first induction chemotherapy possessed higher miR-196b expression. Furthermore, a positive relationship was found between the expression of miR-196b and SMC1A/MLH1 (Spearman's r=0.37 and 0.44, P=0.001 and <0.0001, respectively). Taken together, these findings suggest that differentially high expression of miR-196b in diagnostic marrow samples of pediatric AML is associated with unfavorable outcome, and miR-196b potentially can be a novel biomarker for the diagnosis, prognosis and treatment in pediatric AML.

Network Biomarkers Constructed from Gene Expression and Protein-Protein Interaction Data for Accurate Prediction of Leukemia

Leukemia is a leading cause of cancer deaths in the developed countries. Great efforts have been undertaken in search of diagnostic biomarkers of leukemia. However, leukemia is highly complex and heterogeneous, involving interaction among multiple molecular components. Individual molecules are not necessarily sensitive diagnostic indicators. Network biomarkers are considered to outperform individual molecules in disease characterization. We applied an integrative approach that identifies active network modules as putative biomarkers for leukemia diagnosis. We first reconstructed the leukemia-specific PPI network using protein-protein interactions from the Protein Interaction Network Analysis (PINA) and protein annotations from GeneGo. The network was further integrated with gene expression profiles to identify active modules with leukemia relevance. Finally, the candidate network-based biomarker was evaluated for the diagnosing performance. A network of 97 genes and 400 interactions was identified for accurate diagnosis of leukemia. Functional enrichment analysis revealed that the network biomarkers were enriched in pathways in cancer. The network biomarkers could discriminate leukemia samples from the normal controls more effectively than the known biomarkers. The network biomarkers provide a useful tool to diagnose leukemia and also aids in further understanding the molecular basis of leukemia.

miRNAs as novel biomarkers in the management of prostate cancer

microRNAs (miRNAs) are small non-coding RNAs that control gene expression posttranscriptionally and are part of the giant non codifying genoma. Cumulating data suggest that miRNAs are promising potential biomarkers for many diseases, including cancer. Prostate cancer (PCa) detection is currently based in the serum prostate-specific antigen biomarker and digital rectal examination. However, these methods are limited by a low predictive value and the adverse consequences associated with overdiagnosis and overtreatment. New biomarkers that could be used for PCa detection and prognosis are still needed. Recent studies have demonstrated that aberrant expressions of microRNAs are associated with the underlying mechanisms of PCa. This review attempts to extensively summarize the current knowledge of miRNA expression patterns, as well as their targets and involvement in PCa pathogenesis. We focused our review in the value of circulating and urine miRNAs as biomarkers in PCa patients, highlighting the existing discrepancies between different studies, probably associated with the important methodological issues related to their quantitation and normalization. The majority of studies have been performed in serum or plasma, but urine obtained after prostate massage appears as a new way to explore the usefulness of miRNAs. Large screening studies to select a miRNA profile have been completed, but bioinformatics tools appear as a new approach to select miRNAs that are relevant in PCa development. Promising preliminary results were published concerning miR-141, miR-375 and miR-21, but larger and prospective studies using standardized methodology are necessary to define the value of miRNAs in the detection and prognosis of PCa.