let-7b and let-7c are determinants of intrinsic chemoresistance in renal cell carcinoma

Inhibition of Let-7b-5p maturation by LIN28A promotes thermal skin damage repair after burn injury

Burn injuries, especially severe ones, result in direct and indirect thermal damage to skin tissues, with a complex and slow wound healing process. Improper treatment can induce sustained inflammatory responses, causing systemic damage. Lin28A, a highly conserved RNA binding protein, was found to exert a significant effect on cell proliferation and wound repair. Lin28A exerts the functions through inhibiting the maturation of the let-7 family miRNAs. Herein, the roles of Lin28A and let-7b in thermal injury repair were investigated using a mouse thermal injury model and a human skin fibroblast (HSF) model for thermal injuries. Lin28A could inhibit the maturation of let-7b, thus participating in skin repair after burns. In the animal model, Lin28A was highly expressed after thermal injury. In the HSF model for thermal injuries, downregulation of Lin28A inhibited the proliferation, migration, and extracellular matrix (ECM) generation of fibroblasts. When let-7b was knocked down in HSFs, the impacts on fibroblast functions caused by downregulation of Lin28A were partially reversed. Moreover, let-7b overexpression might significantly attenuate the promotive effects of Lin28A upon thermal injury repair. Finally, AKT2 and IGF1R were the let-7b target genes within cells. These findings reveal that Lin28A might promote thermal injury repair in burn-injured skin by inhibiting the maturation of let-7b and improving HSF viability and functions, thus illustrating the critical effect of let-7b on burn wound healing and providing new therapeutic targets and strategies for burn treatment.

Diagnostic, prognostic, and therapeutic potential of exosomal microRNAs in renal cancer

Renal cell carcinoma (RCC) arises from the tubular epithelial cells of the nephron. It has the highest mortality rate among urological cancers. There are no effective therapeutic approaches and no non-invasive biomarkers for diagnosis and follow-up. Thus, suitable novel biomarkers and therapeutic targets are essential for improving RCC diagnosis/prognosis and treatment. Circulating exosomes such as exosomal microRNAs (Exo-miRs) provide non-invasive prognostic/diagnostic biomarkers and valuable therapeutic targets, as they can be easily isolated and quantified and show high sensitivity and specificity. Exosomes secreted by an RCC can exhibit alterations in the miRs' profile that may reflect the cellular origin and (patho)physiological state, as a ''signature'' or ''fingerprint'' of the donor cell. It has been shown that the transportation of renal-specific miRs in exosomes can be rapidly detected and measured, holding great potential as biomarkers in RCC. The present review highlights the studies reporting tumor microenvironment-derived Exo-miRs with therapeutic potential as well as circulating Exo-miRs as potential diagnostic/prognostic biomarkers in patients with RCC.

Exosomes in renal cell carcinoma: challenges and opportunities

Renal cell carcinoma (RCC) is the most common type of kidney cancer that accounts for approximately 2-3% of adult malignancies. Among the primary treatment methods for this type of cancer are surgery and targeted treatment. Still, due to less than optimal effectiveness, there are problems such as advanced distant metastasis, delayed diagnosis, and drug resistance that continue to plague patients. In recent years, therapeutic advances have increased life expectancy and effective treatment in renal cell carcinoma patients. One of these methods is the use of stem cells. Although the therapeutic effects of stem cells, especially mesenchymal stem cells, are still impressive, today, extracellular vesicles (EVs) as carrying molecules and various mediators in intercellular communications, having a central role in tumorigenesis, metastasis, immune evasion, and drug response, and on the other hand, due to its low immunogenicity and strong regulatory properties of the immune system, has received much attention from researchers and doctors. Despite the increasing interest in exosomes as the most versatile type of EVs, the heterogeneity of their efficacy presents challenges and, on the other hand, exciting opportunities for diagnostic and clinical interventions.In the upcoming article, we will review the various aspects of exosomes' effects in the prevention, treatment, and progress of renal cell carcinoma and also ways to optimize them to strengthen their positive sides.

Circulating serum microRNAs as biomarkers of drug resistance in multiple myeloma patients treated with bortezomib-based regimens - pilot study

Despite advances in multiple myeloma (MM) treatment, drug resistance remains a clinical challenge. We aimed to develop a prognostic model for bortezomib resistance based on miRNA expression profiling. The study included 40 previously untreated MM patients receiving bortezomib-based regimens (20 treatment-sensitive, 20 resistant). Pretreatment venous blood samples were analyzed for miRNA expression. Differential expression analysis revealed upregulated miR-27b-3p (FC 1.45, p = 0.017) and let-7b-5p (FC 1.44, p = 0.025) in the resistant group. Univariate analysis identified let-7b-5p (OR 3.17, 95%CI: 1.19-11.4, p = 0.04) and miR-27b-3p (OR 4.73, 95%CI: 1.4-26.6, p = 0.036) as risk factors for resistance. The final multivariate model included miR-27b-3p (OR 23.1, 95% CI: 2.8-452, p = 0.015), let-7b-5p (OR 4.38, 95% CI: 1.28-22.2, p = 0.038), and miR-103a-3p (OR 15.3, 95% CI: 1.33-351, p = 0.049). These miRNAs may serve as biomarkers of treatment response in MM. However, external validation is necessary to confirm the clinical utility of our model.

Neighborhood-based inference and restricted Boltzmann machine for small molecule-miRNA associations prediction

Background

A growing number of experiments have shown that microRNAs (miRNAs) can be used as target of small molecules (SMs) to regulate gene expression for treating diseases. Therefore, identifying SM-related miRNAs is helpful for the treatment of diseases in the domain of medical investigation.

Methods

This article presents a new computational model, called NIRBMSMMA (neighborhood-based inference (NI) and restricted Boltzmann machine (RBM)), which we developed to identify potential small molecule-miRNA associations (NIRBMSMMA). First, grounded on known SM-miRNAs associations, SM similarity and miRNA similarity, NI was used to predict score of an unknown SM-miRNA pair by reckoning the sum of known associations between neighbors of the SM (miRNA) and the miRNA (SM). Second, utilizing a two-layered generative stochastic artificial neural network, RBM was used to predict SM-miRNA association by learning potential probability distribution from known SM-miRNA associations. At last, an ensemble learning model was conducted to combine NI and RBM for identifying potential SM-miRNA associations.

Results

Furthermore, we conducted global leave one out cross validation (LOOCV), miRNA-fixed LOOCV, SM-fixed LOOCV and five-fold cross validation to assess performance of NIRBMSMMA based on three datasets. Results showed that NIRBMSMMA obtained areas under the curve (AUC) of 0.9912, 0.9875, 0.8376 and 0.9898 ± 0.0009 under global LOOCV, miRNA-fixed LOOCV, SM-fixed LOOCV and five-fold cross validation based on dataset 1, respectively. For dataset 2, the AUCs are 0.8645, 0.8720, 0.7066 and 0.8547 ± 0.0046 in turn. For dataset 3, the AUCs are 0.9884, 0.9802, 0.8239 and 0.9870 ± 0.0015 in turn. Also, we conducted case studies to further assess the predictive performance of NIRBMSMMA. These results illustrated the proposed model is a useful tool in predicting potential SM-miRNA associations.

AMCSMMA: Predicting Small Molecule-miRNA Potential Associations Based on Accurate Matrix Completion

Exploring potential associations between small molecule drugs (SMs) and microRNAs (miRNAs) is significant for drug development and disease treatment. Since biological experiments are expensive and time-consuming, we propose a computational model based on accurate matrix completion for predicting potential SM-miRNA associations (AMCSMMA). Initially, a heterogeneous SM-miRNA network is constructed, and its adjacency matrix is taken as the target matrix. An optimization framework is then proposed to recover the target matrix with the missing values by minimizing its truncated nuclear norm, an accurate, robust, and efficient approximation to the rank function. Finally, we design an effective two-step iterative algorithm to solve the optimization problem and obtain the prediction scores. After determining the optimal parameters, we conduct four kinds of cross-validation experiments based on two datasets, and the results demonstrate that AMCSMMA is superior to the state-of-the-art methods. In addition, we implement another validation experiment, in which more evaluation metrics in addition to the AUC are introduced and finally achieve great results. In two types of case studies, a large number of SM-miRNA pairs with high predictive scores are confirmed by the published experimental literature. In summary, AMCSMMA has superior performance in predicting potential SM-miRNA associations, which can provide guidance for biological experiments and accelerate the discovery of new SM-miRNA associations.

MFIDMA: A Multiple Information Integration Model for the Prediction of Drug-miRNA Associations

Abnormal microRNA (miRNA) functions play significant roles in various pathological processes. Thus, predicting drug-miRNA associations (DMA) may hold great promise for identifying the potential targets of drugs. However, discovering the associations between drugs and miRNAs through wet experiments is time-consuming and laborious. Therefore, it is significant to develop computational prediction methods to improve the efficiency of identifying DMA on a large scale. In this paper, a multiple features integration model (MFIDMA) is proposed to predict drug-miRNA association. Specifically, we first formulated known DMA as a bipartite graph and utilized structural deep network embedding (SDNE) to learn the topological features from the graph. Second, the Word2vec algorithm was utilized to construct the attribute features of the miRNAs and drugs. Third, two kinds of features were entered into the convolution neural network (CNN) and deep neural network (DNN) to integrate features and predict potential target miRNAs for the drugs. To evaluate the MFIDMA model, it was implemented on three different datasets under a five-fold cross-validation and achieved average AUCs of 0.9407, 0.9444 and 0.8919. In addition, the MFIDMA model showed reliable results in the case studies of Verapamil and hsa-let-7c-5p, confirming that the proposed model can also predict DMA in real-world situations. The model was effective in analyzing the neighbors and topological features of the drug-miRNA network by SDNE. The experimental results indicated that the MFIDMA is an accurate and robust model for predicting potential DMA, which is significant for miRNA therapeutics research and drug discovery.

MicroRNA Associated with the Invasive Phenotype in Clear Cell Renal Cell Carcinoma: Let-7c-5p Inhibits Proliferation, Migration, and Invasion by Targeting Insulin-like Growth Factor 1 Receptor

Differential microRNA (miRNA) expression can portend clear cell renal cell carcinoma (ccRCC) progression. In a previous study, we identified a subset of dysregulated miRNA in small renal masses, pT1 ccRCC (≤5 cm) that are associated with an aggressive phenotype. The present study investigated miRNA expression in clinical stage I (cT1) tumors (≤5 cm), comparing pathologic stage I (pT1) tumors to those upstaged to pathologic stage 3 (pT3) after surgery following identification of renal vein invasion or invasion into adjacent fat tissue within Gerota’s fascia. Twenty cT1 tumors were examined in an miRNA screening, 10 pT1 and 10 pT3 tumors. The ccRCC cell lines 786-O and Caki-1 were used to assess the impact of let-7c-5p and its protein target insulin-like growth factor 1 receptor (IGF1R). Cells were transfected with pre-let-7c-5p and assessed through cell proliferation, migration, and invasion assays. IGF1R expression was evaluated through Simple Western, and interaction between let-7c-5p and IGF1R was confirmed via luciferase reporter assay. Screening identified 20 miRNA, including let-7c-5p, that were dysregulated between pT1 and pT3 upstaged tumors. This miRNA was also downregulated in our previous study of pT1 tumors that progressed to metastatic disease. Transfection of ccRCC cells with pre-let-7c-5p significantly inhibited proliferation, migration, invasion, and IGF1R expression. These findings suggest that miRNA dysregulation is involved in ccRCC progression, specifically through invasion, and that let-7c-5p downregulation contributes to the aggressiveness of small ccRCC tumors, in part, through its regulation of IGF1R.

Effects of Let-7c on the processing of hepatitis B virus associated liver diseases

Background

The most common type of cancer of the digestive system is hepatocellular carcinoma. In China, many patients harbour HBV. The lin28B/Let-7c/MYC axis is associated with the occurrence of many cancers. Therefore, we aimed to illuminate the function of the lin28B/Let-7c/MYC axis in hepatocellular carcinoma. We aimed to evaluate the critical involvement of lin28B and Let-7c in the carcinogenesis of human hepatocellular carcinoma (B-HCC).

Methods

Data from the GEO database were used to analyse differentially expressed genes and IRGs. A protein − protein interaction (PPI) network and Venn diagram were generated to analyse relationships. Real-time RT-PCR, Western blotting, and cell counting kit-8 assays were used to examine the association of lin28B, Let-7c, and MYC with cell proliferation.

Results

A total of 2552 functionally annotated differentially expressed RNAs were analysed in HBV patients from the GSE135860 database. In addition, 46 let-7c target genes were screened in HBV patients, and the interactions were analysed through PPI network analysis. The results confirmed that Let-7c and its target genes play a key role in HBV-related diseases. Next, we discovered a gradual decrease in Let-7c expression during the progression from HBV-associated chronic hepatitis (B-CH) and HBV-associated liver cirrhosis (B-LC) to B-HCC. We found evidence for a negative association between lin28B expression and Let-7c expression. The expression of MYC was obviously upregulated when Let-7c was inhibited.

Conclusion

Our results highlight that Let-7c and lin28B participate in the carcinogenesis of HBV-associated diseases through the lin28B/Let-7c/MYC axis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13027-022-00458-8.

Curcumin Sensitises Cancerous Kidney Cells to TRAIL Induced Apoptosis via Let-7C Mediated Deregulation of Cell Cycle Proteins and Cellular Metabolism

Targeted therapies are the most attractive options in the treatment of different tumours, including kidney cancers. Such therapies have entered a golden era due to advancements in research, breakthroughs in scientific knowledge, and a better understanding of cancer therapy mechanisms, which significantly improve the survival rates and life expectancy of patients. The use of tumour necrosis factor (TNF)-related apoptosis inducing ligand (TRAIL) as an anticancer therapy has attracted the attention of the scientific community and created great excitement due to its selectivity in targeting cancerous cells with no toxic impacts on normal tissues. However, clinical studies disappointingly showed the emergence of resistance against TRAIL. This study aimed to employ curcumin to sensitise TRAIL-resistant kidney cancerous ACHN cells, as well as to gain insight into the molecular mechanisms of TRAIL sensitization. Curcumin deregulated the expression of apoptosis-regulating micro Ribonucleic Acid (miRNAs), most notably, let-7C. Transfecting ACHN cells with a let-7C antagomir significantly increased the expression of several cell cycle protein, namely beta (β)-catenin, cyclin dependent kinase (CDK)1/2/4/6 and cyclin B/D. Further, it overexpressed the expression of the two key glycolysis regulating proteins including hypoxia-inducible factor 1-alpha (HIF-1α) and pyruvate dehydrogenase kinase 1 (PDK1). Curcumin also suppressed the expression of the overexpressed proteins when added to the antagomir transfected cells. Overall, curcumin targeted ACHN cell cycle and cellular metabolism by promoting the differential expression of let-7C. To the best of our knowledge, this is the first study to mechanistically report the cancer chemosensitisation potential of curcumin in kidney cancer cells via induction of let-7C.

Tumor-targeted miRNA nanomedicine for overcoming challenges in immunity and therapeutic resistance

miRNA are critical messengers in the tumor microenvironment (TME) that influence various processes leading to immune suppression, tumor progression, metastasis and resistance. Strategies to modulate miRNAs in the TME have important implications in overcoming these challenges. However, miR delivery to specific cells in the TME has been challenging. This review discusses nanomedicine strategies to achieve cell-specific delivery of miRNAs. The key goal of delivery is to activate the tumor immune landscape as well as to prevent chemotherapy resistance. Specifically, the use of hyaluronic acid-based nanoparticle miRNA delivery to the TME is discussed. The discussion is focused on miRNA-125b for reprogramming tumor-associated macrophages to overcome immunosuppression and miRNA-let-7b to overcome resistance to anticancer chemotherapeutics because both these miRNAs have been extensively evaluated for delivery with hyaluronic acid-based delivery systems.

DNA methylation and miRNA expression in colon adenomas compared with matched normal colon mucosa and carcinomas

Dysregulation of DNA methylation patterns and non-coding RNA, including miRNAs, has been implicated in colon cancer, and these changes may occur early in the development of carcinoma. In this study, the role of epigenetics as early changes in colon tumorigenesis was examined through paired sample analysis of patient-matched normal, adenoma and carcinoma samples. Global methylation was assessed by genomic 5-methyl cytosine (5-mC) and long interspersed nuclear element-1 (LINE-1) promoter methylation by pyrosequencing. KRAS mutations were also assessed by pyrosequencing. Expression of miRNA, specifically, two microRNA genes-miR-200a and let-7c-was analysed using RT-qPCR. Differences in global methylation in adenomas were not observed, compared with normal tissue. However, LINE-1 methylation was decreased in adenomas (p = .056) and carcinomas (p = .011) compared with normal tissue. Expressions of miRNA, miR-200a and let-7c were significantly higher in adenomas than normal tissues (p = .008 and p = .045 respectively). Thus the significant changes in LINE-1 methylation and microRNA expression in precancerous lesions support an early role for epigenetic changes in the carcinogenic process. Epigenetic characteristics in adenomas may provide potential diagnostic and prognostic therapeutic targets early in cancer development at the adenoma stage.

Dual-Network Collaborative Matrix Factorization for predicting small molecule-miRNA associations

MicroRNAs (miRNAs) play crucial roles in multiple biological processes and human diseases and can be considered as therapeutic targets of small molecules (SMs). Because biological experiments used to verify SM-miRNA associations are time-consuming and expensive, it is urgent to propose new computational models to predict new SM-miRNA associations. Here, we proposed a novel method called Dual-network Collaborative Matrix Factorization (DCMF) for predicting the potential SM-miRNA associations. Firstly, we utilized the Weighted K Nearest Known Neighbors (WKNKN) method to preprocess SM-miRNA association matrix. Then, we constructed matrix factorization model to obtain two feature matrices containing latent features of SM and miRNA, respectively. Finally, the predicted SM-miRNA association score matrix was obtained by calculating the inner product of two feature matrices. The main innovations of this method were that the use of WKNKN method can preprocess the missing values of association matrix and the introduction of dual network can integrate more diverse similarity information into DCMF. For evaluating the validity of DCMF, we implemented four different cross validations (CVs) based on two distinct datasets and two different case studies. Finally, based on dataset 1 (dataset 2), DCMF achieved Area Under receiver operating characteristic Curves (AUC) of 0.9868 (0.8770), 0.9833 (0.8836), 0.8377 (0.7591) and 0.9836 ± 0.0030 (0.8632 ± 0.0042) in global Leave-One-Out Cross Validation (LOOCV), miRNA-fixed local LOOCV, SM-fixed local LOOCV and 5-fold CV, respectively. For case studies, plenty of predicted associations have been confirmed by published experimental literature. Therefore, DCMF is an effective tool to predict potential SM-miRNA associations.

Circular RNAs and their role in renal cell carcinoma: a current perspective

Circular RNAs (circRNAs) are a new class of long non-coding RNAs, that results from a special type of alternative splicing referred to as back-splicing. They are widely distributed in eukaryotic cells and demonstrate tissue-specific expression patterns in humans. CircRNAs actively participate in various important biological activities like gene transcription, pre-mRNA splicing, translation, sponging miRNA and proteins, etc. With such diverse biological functions, circRNAs not only play a crucial role in normal human physiology, as well as in multiple diseases, including cancer. In this review, we summarized our current understanding of circRNAs and their role in renal cell carcinoma (RCC), the most common cancer of kidneys. Studies have shown that the expression level of several circRNAs are considerably varied in RCC samples and RCC cell lines suggesting the potential role of these circRNAs in RCC progression. Several circRNAs promote RCC development and progression mostly via the miRNA/target gene axis making them ideal candidates for novel anti-cancer therapy. Apart from these, there are a few circRNAs that are significantly downregulated in RCC and overexpression of these circRNAs leads to suppression of RCC growth. Differential expression patterns and novel functions of circRNAs in RCC suggest that circRNAs can be utilized as potential biomarkers and therapeutic targets for RCC therapy. However, our current understanding of the role of circRNA in RCC is still in its infancy and much comprehensive research is needed to achieve clinical translation of circRNAs as biomarkers and therapeutic targets in developing effective treatment options for RCC.

Predicting potential small molecule-miRNA associations based on bounded nuclear norm regularization

Mounting evidence has demonstrated the significance of taking microRNAs (miRNAs) as the target of small molecule (SM) drugs for disease treatment. Given the fact that exploring new SM-miRNA associations through biological experiments is extremely expensive, several computing models have been constructed to reveal the possible SM-miRNA associations. Here, we built a computing model of Bounded Nuclear Norm Regularization for SM-miRNA Associations prediction (BNNRSMMA). Specifically, we first constructed a heterogeneous SM-miRNA network utilizing miRNA similarity, SM similarity, confirmed SM-miRNA associations and defined a matrix to represent the heterogeneous network. Then, we constructed a model to complete this matrix by minimizing its nuclear norm. The Alternating Direction Method of Multipliers was adopted to minimize the nuclear norm and obtain predicted scores. The main innovation lies in two aspects. During completion, we limited all elements of the matrix within the interval of (0,1) to make sure they have practical significance. Besides, instead of strictly fitting all known elements, a regularization term was incorporated to tolerate the noise in integrated similarities. Furthermore, four kinds of cross-validations on two datasets and two types of case studies were performed to evaluate the predictive performance of BNNRSMMA. Finally, BNNRSMMA attained areas under the curve of 0.9822 (0.8433), 0.9793 (0.8852), 0.8253 (0.7350) and 0.9758 ± 0.0029 (0.8759 ± 0.0041) under global leave-one-out cross-validation (LOOCV), miRNA-fixed LOOCV, SM-fixed LOOCV and 5-fold cross-validation based on Dataset 1(Dataset 2), respectively. With regard to case studies, plenty of predicted associations have been verified by experimental literatures. All these results confirmed that BNNRSMMA is a reliable tool for inferring associations.

MicroRNA-203 inhibits epithelial-mesenchymal transition, migration, and invasion of renal cell carcinoma cells via the inactivation of the PI3K/AKT signaling pathway by inhibiting CAV1

The present study aimed to evaluate the underlying mechanism of microRNA-203 (miR-203) in renal cell carcinoma (RCC) involving the PI3K/AKT signaling pathway. The results revealed downregulated miR-203 and upregulated CAV1 in RCC tissues. Upregulated miR-203 and downregulated CAV1 increased E-cadherin expression and cell apoptosis, decreased β-catenin and N-cadherin expression and cell proliferation, migration and invasion, and blocked cell cycle entry. CAV1, a target gene of miR-203, decreased by up-regulated miR-203, and silencing CAV1 led to the inactivation of PI3K/AKT signaling pathway. In conclusion, our findings suggested that miR-203-mediated direct suppression of CAV1 inhibits EMT of RCC cells via inactivation of the PI3K/AKT signaling pathway.

The PP2A subunit PR130 is a key regulator of cell development and oncogenic transformation

Protein phosphatase 2A (PP2A) is a major serine/threonine phosphatase. This enzyme is involved in a plethora of cellular processes, including apoptosis, autophagy, cell proliferation, and DNA repair. Remarkably, PP2A can act as a context-dependent tumor suppressor or promoter. Active PP2A complexes consist of structural (PP2A-A), regulatory (PP2A-B), and catalytic (PP2A-C) subunits. The regulatory subunits define the substrate specificity and the subcellular localization of the holoenzyme. Here we condense the increasing evidence that the PP2A B-type subunit PR130 is a critical regulator of cell identity and oncogenic transformation. We summarize knowledge on the biological functions of PR130 in normal and transformed cells, targets of the PP2A-PR130 complex, and how diverse extra- and intracellular stimuli control the expression and activity of PR130. We additionally review the impact of PP2A-PR130 on cardiac functions, neuronal processes, and anti-viral defense and how this might affect cancer development and therapy.

Circulating Non-coding RNAs in Renal Cell Carcinoma-Pathogenesis and Potential Implications as Clinical Biomarkers

Liquid biopsy-the determination of circulating cells, proteins, DNA or RNA from biofluids through a "less invasive" approach-has emerged as a novel approach in all cancer entities. Circulating non-(protein) coding RNAs including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and YRNAs can be passively released by tissue or cell damage or actively secreted as cell-free circulating RNAs, bound to lipoproteins or carried by exosomes. In renal cell carcinoma (RCC), a growing body of evidence suggests circulating non-coding RNAs (ncRNAs) such as miRNAs, lncRNAs, and YRNAs as promising and easily accessible blood-based biomarkers for the early diagnosis of RCC as well as for the prediction of prognosis and treatment response. In addition, circulating ncRNAs could also play a role in RCC pathogenesis and progression. This review gives an overview over the current study landscape of circulating ncRNAs and their involvement in RCC pathogenesis as well as their potential utility as future biomarkers in RCC diagnosis and treatment.

MicroRNA profile in stage I clear cell renal cell carcinoma predicts progression to metastatic disease

OBJECTIVE

This study sought to identify microRNA (miRNA) profiles of small, pathologically confirmed stage 1 clear cell renal cell carcinoma (ccRCC) tumors that are associated with progression to metachronous metastatic disease.

MATERIALS AND METHODS

Fifty-five pathologic stage 1 ccRCC tumors ≤5cm, from 2 institutions, were examined in a miRNA screening, followed by a validation study. For the screening phase 752 miRNA were evaluated on each sample to identify those with differential expression between tumors that subsequently did (n = 10) or did not (n = 10) progress to metastatic disease. For the validation, 35 additional samples (20 nonprogressors and 15 with distant progression) were utilized to investigate 20 miRNA to determine if a miRNA panel could differentiate aggressive tumors: associations of miRNA expression with cancer specific survival was also investigated.

RESULTS

In the screening analysis, 35 miRNA were differentially expressed (P < 0.05, FDR < 0.1) between the groups. In the validation, 11 miRNA were confirmed to have differential expression. The miRNA -10a-5p, -23b-3p, and -26a-5p differentiated nonprogressive and distant progressive disease with a sensitivity of 73.3% and a specificity of 85% (AUC=0.893). In addition, levels of miR-30a-3p and -145-5p were identified as independent prognostic factors of cancer specific survival.

CONCLUSIONS

This investigation identified miRNA biomarkers that may differentiate between non-progressive ccRCC tumors and those that progress to metastatic disease in this group of stage I tumors. The miRNA profiles determined in this study have the potential to identify patients with small renal masses who are likely to have progressive ccRCC. Such information may be valuable to incorporate into predictive models.

MicroRNA-let-7c suppresses hepatitis C virus replication by targeting Bach1 for induction of haem oxygenase-1 expression

MicroRNAs are small noncoding RNAs that are central factors between hepatitis C virus (HCV) and host cellular factors for viral replication and liver disease progression, including liver fibrosis, cirrhosis and hepatocellular carcinoma. In the present study, we found that overexpressing miR-let-7c markedly reduced HCV replication because it induced haem oxygenase-1 (HO-1) expression by targeting HO-1 transcriptional repressor Bach1, ultimately leading to stimulating an antiviral interferon response and blockade of HCV viral protease activity. In contrast, the antiviral actions of miR-let-7c were attenuated by miR-let-7c inhibitor treatment, exogenously expressing Bach1 or suppressing HO-1 activity and expression. A proposed model indicates a key role for miR-let-7c targeting Bach1 to transactivate HO-1-mediated antiviral actions against HCV. miR-let-7c may serve as an attractive target for antiviral development.

MicroRNA let-7c-5p promotes osteogenic differentiation of dental pulp stem cells by inhibiting lipopolysaccharide-induced inflammation via HMGA2/PI3K/Akt signal blockade

Pulpitis suppressed the level of let-7c-5p that promotes osteogenesis and bone formation by repressing HMGA2. In the current study, the function of let-7c-5p in the inflammation and osteogenesis in dental pulp stem cells (DPSCs) was explored. The level of let-7c-5p in DPSCs was up-regulated, and the cells were subjected to lipopolysaccharide (LPS) to induce inflammation. The effect of let-7c-5p on cell proliferation potential, osteogenic differentiation potential, and activity of HMGA2/PI3K/Akt pathway was detected. The administration of LPS suppressed the cell proliferation of DPSCs and suppressed calcium deposition, activity of alkaline phosphatase (ALP), and levels of OCN, OPN, OSX, MSX2, and RUNX2 in inflamed DPSCs. The impaired osteogenic differentiation of inflamed DPSCs was associated with the increased levels of HMGA2, p-PI3K, and p-Akt. In let-7c-5p-overexpressed inflamed DPSCs, the proliferation and osteogenic differentiation potential of DPSCs were restored, and the activation of HMGA2/PI3K/Akt signalling was inhibited. In rat pulpitis models, the injection of let-7c-5p agomir restored the osteogenic differentiation potential of dental pulp cells and inhibited HMGA2/PI3K/Akt signalling. The findings demonstrated the anti-inflammation and pro-osteogenesis effect of let-7c-5p during the attack of pulpitis, which depended on the inhibition of HMGA2/PI3K/Akt signalling.

MicroRNA let-7c-5p Suppressed Lipopolysaccharide-Induced Dental Pulp Inflammation by Inhibiting Dentin Matrix Protein-1-Mediated Nuclear Factor kappa B (NF-κB) Pathway In Vitro and In Vivo

Background

Let-7c-5p is down-regulated in dental pulp tissues in inflammatory disorders. The microRNA (miR) molecule shows an anti-inflammation potential due to its direct regulation of dentin matrix protein-1 (DMP1), which promotes inflammation changes in dental pulp tissues. In the present study, the effect of let-7c-5p on lipopolysaccharide (LPS)-induced pulpitis was detected and the associated mechanism was explored.

Material/Methods

Dental pulp stem cells (DPSCs) were isolated from rat dental tissues, infected with let-7c-5p lentivirus particles, and subjected to LPS administration to induce inflammation. Then, the effect of let-7c-5p overexpression on LPS-induced impairments on DPSCs were detected and the mechanism was explained by focusing on the DMP1 expression and NF-κB pathway. The role of DMP1 in the anti-inflammation effect of let-7c-5p was assessed by incubating let-7c-5p-expressed DPSCs with DMP1 protein. The results of in vitro assays were verified in LPS-induced rat pulpitis models.

Results

LPS administration increased the production of IL-1β and TNF-α and decreased DPSCs viability by increasing the expression of DMP1 and activating NF-κB pathway. However, the induced expression of let-7c-5p relieved DPSCs from LPS-induced inflammation and suppressed DMP1 as well as NF-κB pathway. The incubation of let-7c-5p-expressed DPSCs with DMP1 protein blocked the effect of let-7c-5p. In in vivo experiments, the injection of let-7c-5p attenuated LPS-induced pulpitis by inhibiting DMP1-mediated NF-κB pathway.

Conclusions

Findings outlined in the current study demonstrated the dental pulp protecting function of let-7c-5p during LPS-induced inflammation, which was exerted by inhibiting the DMP1-mediated NF-κB pathway.

The Network of Non-coding RNAs in Cancer Drug Resistance

Non-coding RNAs (ncRNAs) have been implicated in most cellular functions. The disruption of their function through somatic mutations, genomic imprinting, transcriptional and post-transcriptional regulation, plays an ever-increasing role in cancer development. ncRNAs, including notorious microRNAs, have been thus proposed to function as tumor suppressors or oncogenes, often in a context-dependent fashion. In parallel, ncRNAs with altered expression in cancer have been reported to exert a key role in determining drug sensitivity or restoring drug responsiveness in resistant cells. Acquisition of resistance to anti-cancer drugs is a major hindrance to effective chemotherapy and is one of the most important causes of relapse and mortality in cancer patients. For these reasons, non-coding RNAs have become recent focuses as prognostic agents and modifiers of chemo-sensitivity. This review starts with a brief outline of the role of most studied non-coding RNAs in cancer and then highlights the modulation of cancer drug resistance via known ncRNAs based mechanisms. We identified from literature 388 ncRNA-drugs interactions and analyzed them using an unsupervised approach. Essentially, we performed a network analysis of the non-coding RNAs with direct relations with cancer drugs. Within such a machine-learning framework we detected the most representative ncRNAs-drug associations and groups. We finally discussed the higher integration of the drug-ncRNA clusters with the goal of disentangling effectors from downstream effects and further clarify the involvement of ncRNAs in the cellular mechanisms underlying resistance to cancer treatments.

Differential expression of microRNAs in recombinant Chinese hamster ovary cells treated with sodium butyrate using digital RNA counting

Sodium butyrate (NaBu) is an efficient supplement for increasing recombinant protein production in Chinese hamster ovary (CHO) cell culture. To elucidate the effects of NaBu on miRNA expression profile in recombinant CHO (rCHO) cells, differentially expressed miRNAs in NaBu-treated rCHO cells were assessed by NanoString nCounter analysis. This result showed that eight mature mouse miRNAs (let-7b, let-7d, miR-15b, miR-25, miR-27a, miR-99a, miR-125a-5p, and miR-125b-5p) were differentially expressed. Furthermore, quantitative real-time RT-PCR analysis of eight mature CHO miRNAs, annotated using a miRBase database, confirmed the transcriptomic findings. Among the potential corresponding target mRNAs for the selected mature miRNAs, seven cell growth-related target genes (e2f2, akt2, mtor, bcl-2, bim, p38α, and bmf) and five N-glycosylation-related target genes (neu1, b4galt3, gale, man1b1 and mgat4a) were selected by considering the effectiveness of NaBu on rCHO cell culture. The altered expression patterns of the 12 target mRNAs were inversely correlated with those of the selected mature miRNAs. Altogether, NanoString nCounter analysis may be useful for identifying differentially expressed miRNAs in rCHO cells.

Identifying a panel of genes/proteins/miRNAs modulated by arsenicals in bladder, prostate, kidney cancers

Arsenic and arsenic-derivative compounds, named as arsenicals, represent a worldwide problem for their effect on the human health and, in particular, for their capability to increase the risk of developing cancer such as kidney, bladder and prostate cancer. The main source of arsenical exposure is drinking water. Nowadays, it is well known that the chronic exposure to arsenicals leads to a series of epigenetic alterations that have a role in arsenic-induced effects on human health including cancer. Based on these observations, the aim of our study was to select by network analysis the genes/proteins/miRNAs implicated in kidney, bladder and prostate cancer development upon arsenical exposure. From this analysis we identified: (i) the nodes linking the three molecular networks specific for kidney, bladder and prostate cancer; (ii) the relative HUB nodes (RXRA, MAP3K7, NR3C1, PABPC1, NDRG1, RELA and CTNNB1) that link the three cancer networks; (iii) the miRNAs able to target these HUB nodes. In conclusion, we highlighted a panel of potential molecules related to the molecular mechanisms of arsenical-induced cancerogenesis and suggest their utility as biomarkers or therapeutic targets.

MicroRNA molecular profiling identifies potential signaling pathways conferring resistance to chemoradiation in locally-advanced rectal adenocarcinoma

Purpose

There has been growing interest in using chemoradiation (CRT) for non-operative management of rectal cancer, and identifying patients who might benefit most from this approach is crucial. This study identified miRNAs (miRs) associated with clinical outcomes and treatment resistance by evaluating both pre- and post-CRT expression profiles.

Methods

Forty patients, 9 with pathologic complete response (pCR) and 31 with pathologic incomplete response (pIR) were included. MicroRNA was extracted from 40 pre-therapy tumor samples and 31 post-chemoradiation surgical samples with pathologic incomplete response (pIR). A generalized linear model was used to identify miRs associated with pCR. A linear mixed effects model was used to identify miRs differentially expressed before and after treatment. miR expression was dichotomized at the mean and clinical outcomes were evaluated using Cox proportional hazard modeling.

Results

Nine miRs were associated with pCR (p<0.05), but none were significant after false discovery rate correction. Among patients with pIR, 68 miRs were differentially expressed between the pre and post-CRT groups (FDR p<0.05). Ingenuity pathway analysis (IPA) demonstrated multiple signaling networks associated with pIR, including p38MAPK, TP53, AKT, IL-6, and RAS. Increased let-7b was correlated with increased distant metastasis (DM), worse relapse-free survival (RFS), and worse overall survival (OS) (p<0.05).

Conclusions

No miRs were significantly correlated with pCR. We identified miRs that were differentially expressed between pre- and post-CRT tumor samples, and these miRs implicated multiple signaling pathways that may confer resistance to CRT. In addition, we identified an association between increased let-7b and worse clinical outcomes (DM, DFS, OS).

The microRNA signature of patients with sunitinib failure: regulation of UHRF1 pathways by microRNA-101 in renal cell carcinoma

Molecular targeted therapy is a standard treatment for patients with advanced renal cell carcinoma (RCC). Sunitinib is one of the most common molecular-targeted drugs for metastatic RCC. Molecular mechanisms of sunitinib resistance in RCC cells is still ambiguous. The microRNA (miRNA) expression signature of patients with sunitinib failure in RCC was constructed using a polymerase chain reaction (PCR)-based array. Several miRNAs that were aberrantly expressed in RCC tissues from patients treated with sunitinib were identified in this analysis. MicroRNA-101 (miR- 101) was markedly suppressed in sunitinib treated RCC tissues. Restoration of miR-101 significantly inhibited cell migration and invasion in Caki-1 and 786-O cells. Ubiquitin-like with PHD and ring finger domains 1 (UHRF1) was directly suppressed by miR-101 in RCC cells, and overexpression of UHRF1 was confirmed in sunitinib-treated RCC tissues. The pathways of nucleotide excision repair and mismatch repair were significantly suppressed by knockdown of UHRF1. Our findings showed that antitumor miR-101- mediated UHRF1 pathways may be suppressed by sunitinib treatment.

LRSSLMDA: Laplacian Regularized Sparse Subspace Learning for MiRNA-Disease Association prediction

Predicting novel microRNA (miRNA)-disease associations is clinically significant due to miRNAs’ potential roles of diagnostic biomarkers and therapeutic targets for various human diseases. Previous studies have demonstrated the viability of utilizing different types of biological data to computationally infer new disease-related miRNAs. Yet researchers face the challenge of how to effectively integrate diverse datasets and make reliable predictions. In this study, we presented a computational model named Laplacian Regularized Sparse Subspace Learning for MiRNA-Disease Association prediction (LRSSLMDA), which projected miRNAs/diseases’ statistical feature profile and graph theoretical feature profile to a common subspace. It used Laplacian regularization to preserve the local structures of the training data and a L₁-norm constraint to select important miRNA/disease features for prediction. The strength of dimensionality reduction enabled the model to be easily extended to much higher dimensional datasets than those exploited in this study. Experimental results showed that LRSSLMDA outperformed ten previous models: the AUC of 0.9178 in global leave-one-out cross validation (LOOCV) and the AUC of 0.8418 in local LOOCV indicated the model’s superior prediction accuracy; and the average AUC of 0.9181+/-0.0004 in 5-fold cross validation justified its accuracy and stability. In addition, three types of case studies further demonstrated its predictive power. Potential miRNAs related to Colon Neoplasms, Lymphoma, Kidney Neoplasms, Esophageal Neoplasms and Breast Neoplasms were predicted by LRSSLMDA. Respectively, 98%, 88%, 96%, 98% and 98% out of the top 50 predictions were validated by experimental evidences. Therefore, we conclude that LRSSLMDA would be a valuable computational tool for miRNA-disease association prediction.

Discovering miRNA-disease associations promotes the understanding towards the molecular mechanisms of various human diseases at the miRNA level, and contributes to the development of diagnostic biomarkers and treatment tools for diseases. Computational models can make the discovery more efficient and experiments more productive. LRSSLMDA was proposed to computationally infer potential miRNA-disease associations via adopting sparse subspace learning with Laplacian regularization on the known miRNA-disease association network and the informative feature profiles extracted from the integrated miRNA/disease similarity networks. Experimental results in global and local leave-one-out cross validation and 5-fold cross validation showed a superior prediction performance of LRSSLMDA over previous models. Moreover, three types of case studies on five important human diseases were carried out to further demonstrate the model’s predictive power: respectively, 98%, 88%, 96%, 98% and 98% out of the top 50 predicted miRNAs were confirmed by experimental literatures. So, we believe that LRSSLMDA could make reliable predictions and might guide future experimental studies on miRNA-disease associations.

MicroRNA-138 suppresses cell proliferation and invasion of renal cell carcinoma by directly targeting SOX9

An accumulating number of studies have reported that the expression levels of microRNAs (miRNAs/miRs) are dysregulated in a variety of human cancer types, including renal cell carcinoma (RCC). miRNAs play essential functions in tumorigenesis and the progression of tumors by serving as oncogenes or tumor suppressors. Recently, the expression and functions of miR-138 have been studied in a number of human cancer types; however, its role in RCC remains poorly understood. In the present study, the results revealed that miR-138 was significantly downregulated in RCC cell lines and tissues, and that low expression levels of miR-138 were correlated with histological grade, tumor stage and lymph node metastasis. In functional studies, restoration of miR-138 expression inhibited cell proliferation and invasion of ACHN and A498 cells. In addition, SOX9 was validated as a direct target gene of miR-138 in RCC. SOX9 knockdown inhibited cell proliferation and invasion of RCC, with a similar effect to that induced by miR-138, rendering SOX9 a functional target of miR-138 in the disease. These findings indicate that miR-138 may present a novel target for therapeutic strategies in RCC.

Plasma exosomal miRNAs-based prognosis in metastatic kidney cancer

Plasma exosomal miRNAs were evaluated for prognosis in an initial set of 44 metastatic renal cell cancer (mRCC) patients by RNA sequencing. Among ∼3.49 million mappable reads per patient, miRNAs accounted for 93.1% of the mapped RNAs. 227 miRNAs with high abundance were selected for survival analysis. Cox regression analysis identified association of 6 miRNAs with overall survival (OS) (P<0.01, False discovery rate (FDR) < 0.3). Five of the associated miRNAs were quantified in an independent follow-up cohort of 65 mRCC patients by TaqMan-based miRNA assays. Kaplan-Meier analysis confirmed the significant OS association of three miRs; miR-let-7i-5p (P=0.018, HR=0.49, 95% CI=0.21-0.84), miR-26a-1-3p (P=0.025, HR=0.43, 95% CI=0.10-0.84) and miR-615-3p (P=0.0007, HR=0.36, 95% CI=0.11-0.54). A multivariate analysis of miR-let-7i-5p with the clinical factor-based Memorial Sloan-Kettering Cancer Center (MSKCC) score improved survival prediction from an area under the curve (AUC) of 0.58 for MSKCC score to an average AUC of 0.64 across 48-month follow-up time. The multivariate model was able to define a high-risk group with median survival of 14 months and low risk group of 39 months (P=0.0002, HR=3.43, 95%CI, 2.73-24.15). Further validation of miRNA-based prognostic biomarkers are needed to improve current clinic-pathologic based prognostic models in patients with mRCC.

The LIN28/let-7 Pathway in Cancer

Among all tumor suppressor microRNAs, reduced let-7 expression occurs most frequently in cancer and typically correlates with poor prognosis. Activation of either LIN28A or LIN28B, two highly related RNA binding proteins (RBPs) and proto-oncogenes, is responsible for the global post-transcriptional downregulation of the let-7 microRNA family observed in many cancers. Specifically, LIN28A binds the terminal loop of precursor let-7 and recruits the Terminal Uridylyl Transferase (TUTase) ZCCHC11 that polyuridylates pre-let-7, thereby blocking microRNA biogenesis and tumor suppressor function. For LIN28B, the precise mechanism responsible for let-7 inhibition remains controversial. Functionally, the decrease in let-7 microRNAs leads to overexpression of their oncogenic targets such as MYC, RAS, HMGA2, BLIMP1, among others. Furthermore, mouse models demonstrate that ectopic LIN28 expression is sufficient to drive and/or accelerate tumorigenesis via a let-7 dependent mechanism. In this review, the LIN28/let-7 pathway is discussed, emphasizing its role in tumorigenesis, cancer stem cell biology, metabolomics, metastasis, and resistance to ionizing radiation and several chemotherapies. Also, emerging evidence will be presented suggesting that molecular targeting of this pathway may provide therapeutic benefit in cancer.

Influence of microRNAs and Long Non-Coding RNAs in Cancer Chemoresistance

Innate and acquired chemoresistance exhibited by most tumours exposed to conventional chemotherapeutic agents account for the majority of relapse cases in cancer patients. Such chemoresistance phenotypes are of a multi-factorial nature from multiple key molecular players. The discovery of the RNA interference pathway in 1998 and the widespread gene regulatory influences exerted by microRNAs (miRNAs) and other non-coding RNAs have certainly expanded the level of intricacy present for the development of any single physiological phenotype, including cancer chemoresistance. This review article focuses on the latest research efforts in identifying and validating specific key molecular players from the two main families of non-coding RNAs, namely miRNAs and long non-coding RNAs (lncRNAs), having direct or indirect influences in the development of cancer drug resistance properties and how such knowledge can be utilised for novel theranostics in oncology.

Identification of urinary exosomal noncoding RNAs as novel biomarkers in chronic kidney disease

In chronic kidney disease (CKD), the decline in the glomerular filtration rate is associated with increased morbidity and mortality and thus poses a major challenge for healthcare systems. While the contribution of tissue-derived miRNAs and mRNAs to CKD progression has been extensively studied, little is known about the role of urinary exosomes and their association with CKD. Exosomes are small, membrane-derived endocytic vesicles that contribute to cell-to-cell communication and are present in various body fluids, such as blood or urine. Next-generation sequencing approaches have revealed that exosomes are enriched in noncoding RNAs and thus exhibit great potential for sensitive nucleic acid biomarkers in various human diseases. Therefore, in this study we aimed to identify urinary exosomal ncRNAs as novel biomarkers for diagnosis of CKD. Since up to now most approaches have focused on the class of miRNAs, we extended our analysis to several other noncoding RNA classes, such as tRNAs, tRNA fragments (tRFs), mitochondrial tRNAs, or lincRNAs. For their computational identification from RNA-seq data, we developed a novel computational pipeline, designated as ncRNASeqScan. By these analyses, in CKD patients we identified 30 differentially expressed ncRNAs, derived from urinary exosomes, as suitable biomarkers for early diagnosis. Thereby, miRNA-181a appeared as the most robust and stable potential biomarker, being significantly decreased by about 200-fold in exosomes of CKD patients compared to healthy controls. Using a cell culture system for CKD indicated that urinary exosomes might indeed originate from renal proximal tubular epithelial cells.

miR-144 reverses chemoresistance of hepatocellular carcinoma cell lines by targeting Nrf2-dependent antioxidant pathway

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide. Chemoresistance occurrence is a major cause of treatment failure in HCC. Currently, extensive research has revealed diverse mechanisms for chemoresistance, but the molecular mechanisms underlying the role of miRNAs in resistance to 5-FU are not confirmed in HCC cells. By quantitative real-time polymerase chain reaction (qRT-PCR) analysis, we found that miR-144 was significantly decreased in HCC cell lines. It has been further demonstrated that miR-144 were significantly down-regulated in Bel-7402/5-FU cells compared with parental Bel-7402 cells by qRT-PCR and western blot. The expression of Nrf2 was reversely correlated to that of miR-144 in HCC cells. Moreover, Enhancement of 5-FU-induced cytotoxicity and apoptosis are resulted from the transfection with miR-144 mimics in Bel-7402/5-FU cells. Mechanically, miR-144 promoted nuclear factor erythroid-2-related factor-2 (Nrf2) mRNA degradation by directly targeting the Nrf2 3'untranslated region (3'UTR). In addition, ectopic expression of miR-144 in Bel-7402/5-FU cells reduced the levels of Nrf2 and inhibited the transcription of Nrf2-dependent HO-1 gene, thus contributing to 5-FU sensibilization. Conversely, re-expression of Nrf2 partly attenuated the chemosensibilization of miR-144. Our study showed that miR-144 serves as a potential chemoresistance-reversal agent in hepatocellular carcinoma cells, which is at least partly due to the down-regulation of Nrf2-dependent antioxidant pathway.

microRNA-451 inhibited cell proliferation, migration and invasion through regulation of MIF in renal cell carcinoma

The expression and functions of microRNA-451 have been studied in many human cancers. However, up to date, there is no study of microRNA-451 in renal cell carcinoma. In the present study, we aimed to investigate the expression, biological functions and molecular mechanisms of microRNA-451 in renal cell carcinoma. microRNA-451 expression level in renal cell carcinoma tissues and cell lines was measured using quantitative Real-time PCR. By using CCK8 assay, cell migration and invasion assay, we explored the functions of microRNA-451 in renal cell carcinoma. Dual-Luciferase report assay, quantitative Real-time PCR and western blot were performed to explore the molecular mechanisms of microRNA-451 functions in renal cell carcinoma. Functional assays were also performed to explore the effects of endogenous MIF in renal cell carcinoma. In this study, we showed for the first time that microRNA-451 was significantly down-regulated in renal cell carcinomas tissues and cell lines. microRNA-451 expression level was correlated with histological grade and lymph node metastasis. In addition, microRNA-451 inhibited proliferation, migration and invasion of renal cell carcinomas cells. Moreover, MIF was identified as a target of microRNA-451, and down-regulation of MIF could mimic the suppressive functions of microRNA-451 in renal cell carcinomas, suggesting that microRNA-451 might be a novel therapeutic strategy for the treatment of renal cell carcinomas.