miR-210 is induced by hypoxia and regulates neural cell adhesion molecule in prostate cells

Hypoxia in prostate tumours has been associated with disease progression and metastasis. MicroRNAs are short noncoding RNA molecules that are important in several cell processes, but their role in hypoxic signalling is still poorly understood. miR-210 has been linked with hypoxic mechanisms, but this relationship has been poorly characterised in prostate cancer. In this report, the link between hypoxia and miR-210 in prostate cancer cells is investigated. Polymerase chain reaction analysis demonstrates that miR-210 is induced by hypoxia in prostate cancer cells using in vitro cell models and an in vivo prostate tumour xenograft model. Analysis of The Cancer Genome Atlas prostate biopsy datasets shows that miR-210 is significantly correlated with Gleason grade and other clinical markers of prostate cancer progression. Neural cell adhesion molecule (NCAM) is identified as a target of miR-210, providing a biological mechanism whereby hypoxia-induced miR-210 expression can contribute to prostate cancer. This study provides evidence that miR-210 is an important regulator of cell response to hypoxic stress and proposes that its regulation of NCAM may play an important role in the pathogenesis of prostate cancer.     

Suppression of tumorigenicity by MicroRNA-138 through inhibition of EZH2-CDK4/6-pRb-E2F1 signal loop in glioblastoma multiforme

Deregulation of microRNAs (miRNAs) is implicated in tumor progression. We attempt to indentify the tumor suppressive miRNA not only down-regulated in glioblastoma multiforme (GBM) but also potent to inhibit the oncogene EZH2, and then investigate the biological function and pathophysiologic role of the candidate miRNA in GBM. In this study, we show that miRNA-138 is reduced in both GBM clinical specimens and cell lines, and is effective to inhibit EZH2 expression. Moreover, high levels of miR-138 are associated with long overall and progression-free survival of GBM patients from The Cancer Genome Atlas dataset (TCGA) data portal. Ectopic expression of miRNA-138 effectively inhibits GBM cell proliferation in vitro and tumorigenicity in vivo through inducing cell cycles G1/S arrest. Mechanism investigation reveals that miRNA-138 acquires tumor inhibition through directly targeting EZH2, CDK6, E2F2 and E2F3. Moreover, an EZH2-mediated signal loop, EZH2-CDK4/6-pRb-E2F1, is probably involved in GBM tumorigenicity, and this loop can be blocked by miRNA-138. Additionally, miRNA-138 negatively correlates to mRNA levels of EZH2 and CDK6 among GBM clinical samples from both TCGA and our small amount datasets. In conclusion, our data demonstrate a tumor suppressive role of miRNA-138 in GBM tumorigenicity, suggesting a potential application in GBM therapy.     

Survival analysis for long noncoding RNAs identifies TP53TG1 as an antioncogenic target for the breast cancer

Breast carcinoma is one of the most commonly diagnosed tumors and also one of the deadliest cancers in the female. Long noncoding RNAs (lncRNAs) are emerging as novel targets and biomarkers for breast cancer diagnosis and treatment. In this study, we aimed to study the lncRNAs associated with the outcomes in patients using the breast invasive carcinoma datasets from The Cancer Genome Atlas. The Cox proportional hazards regression model was fitted to each lncRNA. Hierarchy clustering was carried out using these survival-related lncRNAs and the log-rank test was carried out for the clustered groups. DNA methylation status was utilized to identify the lncRNAs regulated by epigenetics. Finally, the coexpressed messenger RNA with the potential lncRNAs were utilized to study the possible functions and mechanisms of lncRNAs. In total, 182 lncRNAs had an impact on the survival time of the patients with a cutoff <0.01. The patients were clustered into three groups using these survival-related genes, which performed significantly different prognosis. Two lncRNAs, which were significantly correlated with the outcomes of breast cancer and were regulated by methylation status, were obtained. These two lncRNAs were TP53TG1 and RP5-1061H20.4. We proposed that TP53TG1 was activated by the wild-type TP53 and performed an impact on the PI3Ks family by binding YBX2 in breast cancer.     

Ribonucleic-acid-biomarker candidates for early-phase group detection of common cancers

Cancer is considered as a challenging lethal agent around the world and its detection at early stages would help prevention of the high mortality. Among the widely used biomarkers in clinical diagnosis of cancer, extracellular non-coding RNAs as ribonucleic acid biomarkers serve as state-of-the-art candidates for molecular diagnosis. In that regard, microRNAs are of great priority mainly because of high variety and stability in body fluids. Accordingly, common miRNAs among most prevalent cancers could help us (pre)diagnose cancer with high accuracy in target samples. In this study, common lethal cancers to humans were investigated in case of miRNA profiles to determine the possible common correlation between miRNA up-regulation or down-regulation (as a ribonucleic acid biomarker) and developing the cancers. It was shown that among the investigated miRNAs, five typical extracellular miRNAs (miR-18a, miR-21, miR-155, miR-221, and miR-375) dysregulation are predominant in most cancer varieties comprising breast, colon, lung, prostate, pancreas, gastric, ovarian, esophagus and liver. This could serve as an appropriate target site for developing point-of-care approaches for cancer detection e.g. designing diagnostic biosensor-based microarrays or kits for both quantification and qualification of the biomarkers. Besides, the miRNA candidates could be efficiently applied to cancer therapeutic approaches.     

A cross-cancer metastasis signature in the microRNA–mRNA axis of paired tissue samples

In the progression of cancer, cells acquire genetic mutations that cause uncontrolled growth. Over time, the primary tumour may undergo additional mutations that allow for the cancerous cells to spread throughout the body as metastases. Since metastatic development typically results in markedly worse patient outcomes, research into the identity and function of metastasis-associated biomarkers could eventually translate into clinical diagnostics or novel therapeutics. Although the general processes underpinning metastatic progression are understood, no clear cross-cancer biomarker profile has emerged. However, the literature suggests that some microRNAs (miRNAs) may play an important role in the metastatic progression of several cancer types. Using a subset of The Cancer Genome Atlas (TCGA) data, we performed an integrated analysis of mRNA and miRNA expression with paired metastatic and primary tumour samples to interrogate how the miRNA–mRNA regulatory axis influences metastatic progression. From this, we successfully built mRNA- and miRNA-specific classifiers that can discriminate pairs of metastatic and primary samples across 11 cancer types. In addition, we identified a number of miRNAs whose metastasis-associated dysregulation could predict mRNA metastasis-associated dysregulation. Among the most predictive miRNAs, we found several previously implicated in cancer progression, including miR-301b, miR-1296, and miR-423. Taken together, our results suggest that metastatic samples have a common cross-cancer signature when compared with their primary tumour pair, and that these miRNA biomarkers can be used to predict metastatic status as well as mRNA expression.

     

A novel microRNA signature predicts vascular invasion in hepatocellular carcinoma

Vascular invasion (VI) in hepatocellular carcinoma (HCC) is an important clinical parameter to predict survival. In this study, we collected microRNA (miRNA) expression data from HCC patients using The Cancer Genome Atlas database and identified a novel miRNA signature associated with VI. First, we categorized HCC patients into groups with or without VI (VI+ and VI−). We identified three miRNAs (miRNA-210, miRNA-10b, and miRNA-9-1) that were associated with VI according to a Kaplan–Meier analysis. This three-miRNA signature exhibited good predictive ability for VI in patients with HCC according to a receiver operating characteristic curve analysis at 1, 3, and 5 years. Patients with HCC with a high risk score exhibited a trend toward worse outcomes as determined by multivariable Cox regression and stratified analyses. This three-miRNA signature provides an accurate prediction of VI and can be used as an independent prognostic indicator for predicting VI in HCC patients.     

Circulating microRNAs,miR-939, miR-595, miR-519d and miR-494, Identify Cirrhotic Patients with HCC

The performance of circulating biomarkers for the diagnosis of hepatocellular carcinoma (HCC) is sub-optimal. In this study we tested circulating microRNAs as biomarkers for HCC in cirrhotic patients by performing a two stage study: a discovery phase conducted by microarray and a validation phase performed by qRT-PCR in an independent series of 118 patients. Beside miRNAs emerged from the discovery phase, miR-21, miR-221, miR-519d were also tested in the validation setting on the basis of literary and tissue findings. Deregulated microRNAs were assayed in HCC-derived cells in the intracellular compartment, cell culture supernatant and exosomal fraction. Serum and tissue microRNA levels were compared in 14 patients surgically treated for HCC. From the discovery study, it emerged that seven circulating microRNAs were differentially expressed in cirrhotic patients with and without HCC. In the validation set, miR-939, miR-595 and miR-519d were shown to differentiate cirrhotic patients with and without HCC. MiR-939 and miR-595 are independent factors for HCC. ROC curves of miR-939, miR-595 and miR-519d displayed that AUC was higher than AFP. An exosomal secretion of miR-519d, miR-21, miR-221 and miR-1228 and a correlation between circulating and tissue levels of miR-519d, miR-494 and miR-21 were found in HCC patients. Therefore, we show that circulating microRNAs deserve attention as non-invasive biomarkers in the diagnostic setting of HCC and that exosomal secretion contributes to discharging a subset of microRNAs into the extracellular compartment.     

Identification of key genes and pathways of thyroid cancer by integrated bioinformatics analysis

Thyroid cancer is a common endocrine malignancy with a rapidly increasing incidence worldwide. Although its mortality is steady or declining because of earlier diagnoses, its survival rate varies because of different tumour types. Thus, the aim of this study was to identify key biomarkers and novel therapeutic targets in thyroid cancer. The expression profiles of GSE3467, GSE5364, GSE29265 and GSE53157 were downloaded from the Gene Expression Omnibus database, which included a total of 97 thyroid cancer and 48 normal samples. After screening significant differentially expressed genes (DEGs) in each data set, we used the robust rank aggregation method to identify 358 robust DEGs, including 135 upregulated and 224 downregulated genes, in four datasets. Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes pathway enrichment analyses of DEGs were performed by DAVID and the KOBAS online database, respectively. The results showed that these DEGs were significantly enriched in various cancer-related functions and pathways. Then, the STRING database was used to construct the protein–protein interaction network, and modules analysis was performed. Finally, we filtered out five hub genes, including LPAR5, NMU, FN1, NPY1R, and CXCL12, from the whole network. Expression validation and survival analysis of these hub genes based on the The Cancer Genome Atlas database suggested the robustness of the above results. In conclusion, these results provided novel and reliable biomarkers for thyroid cancer, which will be useful for further clinical applications in thyroid cancer diagnosis, prognosis and targeted therapy.     

Preclinical strategies to define predictive biomarkers for therapeutically relevant cancer subtypes

Defining key driver mutations in cancer, the resulting aberrations in molecular mechanisms and the subsequent phenotype underpins the development and implementation of novel personalized medicine strategies. The literature is replete with biomarkers of prognosis and therapeutic responsiveness identified in single cohorts of patients that have not been independently validated and as a consequence, not developed. Integrating companion biomarker discovery with therapeutic development at the preclinical stage creates the opportunity to identify candidate biomarkers early, which would significantly facilitate both biomarker and therapeutic development. Advances in “-omic” technologies have led to large-scale efforts in characterizing and cataloguing the full range of aberrations in cancer. These include the International Cancer Genome Consortium and The Cancer Genome Atlas, which aim to comprehensively catalogue the range of genomic aberrations for large numbers of cancers for a progressively increasing range of cancer types and subtypes. The technical challenges associated with achieving these goals in some instances have required the generation of primary xenografts and cell lines. These extensively characterized model systems will provide an unprecedented resource for the discovery of biomarkers of therapeutic responsiveness for established therapies, and the development of companion biomarkers linked with preclinical novel therapeutic development in the future.     

Visualizing Molecular Profiles of Glioblastoma with GBM-BioDP

Validation of clinical biomarkers and response to therapy is a challenging topic in cancer research. An important source of information for virtual validation is the datasets generated from multi-center cancer research projects such as The Cancer Genome Atlas project (TCGA). These data enable investigation of genetic and epigenetic changes responsible for cancer onset and progression, response to cancer therapies, and discovery of the molecular profiles of various cancers. However, these analyses often require bulk download of data and substantial bioinformatics expertise, which can be intimidating for investigators. Here, we report on the development of a new resource available to scientists: a data base called Glioblastoma Bio Discovery Portal (GBM-BioDP). GBM-BioDP is a free web-accessible resource that hosts a subset of the glioblastoma TCGA data and enables an intuitive query and interactive display of the resultant data. This resource provides visualization tools for the exploration of gene, miRNA, and protein expression, differential expression within the subtypes of GBM, and potential associations with clinical outcome, which are useful for virtual biological validation. The tool may also enable generation of hypotheses on how therapies impact GBM molecular profiles, which can help in personalization of treatment for optimal outcome. The resource can be accessed freely at http://gbm-biodp.nci.nih.gov (a tutorial is included).     

IPI59: An Actionable Biomarker to Improve Treatment Response in Serous Ovarian Carcinoma Patients

Despite improvements in operative management and therapies, overall survival rates in advanced ovarian cancer have remained largely unchanged over the past three decades. Although it is possible to identify high-risk patients following surgery, the knowledge does not provide information about the genomic aberrations conferring risk, or the implications for treatment. To address these challenges, we developed an integrative pathway-index model and applied it to messenger RNA expression from 458 patients with serous ovarian carcinoma from the Cancer Genome Atlas project. The biomarker derived from this approach, IPI59, contains 59 genes from six pathways. As we demonstrate using independent datasets from six studies, IPI59 is strongly associated with overall and progression-free survival, and also identifies high-risk patients who may benefit from enhanced adjuvant therapy.     

A mechanistic insight into the anti-metastatic role of the prostate specific antigen

AimSince its discovery Prostate Specific Antigen (PSA), also referred to as kallikrein-3 (KLK3), has been used as standard circulating biomarker for prostate cancer (PCa). However, its specificity remains not adequate and its mechanism of action still elusive. Therefore, deciphering PSA role throughout PCa-pathobiology would be relevant in improving both cancer diagnosis and outcome prediction. We investigated the possible role played by PSA on/in the tumor microenvironment and over the first steps of cancer invasion.MethodsFresh PCa-specimens and cell lines were used for ex-vivo/in-vitro invasion assays and assessment of prostate tissue-PSA (tPSA), type 1 collagen (COL1A1) and ß1-integrin expression. Tissue Cancer Genome Atlas (TCGA) and Decipher® datasets were considered to estimate tPSA clinical relevance.ResultsA more precise, inverse, correspondence between tPSA and clinical/pathological parameters was found than for circulating PSA. KLK3 combined with Gleason grade and pathologic stage, better predicted cancer-related mortality. Consistently, we demonstrated that PSA inhibits prostate extracellular-matrix (ECM) invasion by PCa cells. As for the mechanism of action, we provided novel information that PSA is able to cleave COL1A1, a main component of the ECM. Finally, ß1-integrin, a crucial COL1A1 transducing-receptor involved in tumor adhesion/invasion, resulted to be downregulated in PCa specimens with higher levels of tPSA.ConclusionsBy interfering with type 1 collagen and its downstream targets, PSA may hamper adhesion and path of the cancer cells through ECM and their migration ability, thus explaining the inverse correlation highlighted between prostate tPSA levels and clinically significant disease.     

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

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

The up-regulation of Myb may help mediate EGCG inhibition effect on mouse lung adenocarcinoma

Background

Green tea polyphenol epigallocatechin-3-gallate (EGCG) has been demonstrated to inhibit cancer in experimental studies through its antioxidant activity and modulations on cellular functions by binding specific proteins. By means of computational analysis and functional genomic approaches, we previously identified a set of protein coding genes and microRNAs whose expressions were significantly modulated in response to the EGCG treatment in tobacco carcinogen-induced lung adenocarcinoma in A/J mice. However, to what degree these genes are involved in the cancer inhibition of EGCG remains unclear.

Results

In this study, we further employed statistical methods and literature research to analyze these data in combination with The Cancer Genome Atlas (TCGA) lung adenocarcinoma datasets for additional data mining. Under the assumption that, if a gene mediates EGCG’s cancer inhibition, its expression level change caused by EGCG should be opposite to what occurred in the carcinogenesis, we identified Myb and Peg3 as the primary putative genes involved in the cancer inhibitory activity. Further analysis suggested that the regulation of Myb could be mediated through an EGCG-upregulated microRNA, miR-449c-5p.

Conclusions

Although the actions of EGCG involve multiple targets/pathways, further analysis by mining the existing genomic datasets revealed that the upregulations of Myb and Peg3 are likely the key anti-cancer events of EGCG in vivo.