Exploring and clinical validation of prognostic significance and therapeutic implications of copper homeostasis-related gene dysregulation in acute myeloid leukemia.

The patterns and biological functions of copper homeostasis-related genes (CHRGs) in acute myeloid leukemia (AML) remain unclear. We explored the patterns and biological functions of CHRGs in AML. Using independent cohorts, including TCGA-GTEx, GSE114868, GSE37642, and clinical samples, we identified 826 common differentially expressed genes. Specifically, 12 cuproptosis-related genes (e.g., ATP7A, ATP7B) were upregulated, while 17 cuproplasia-associated genes (e.g., ATOX1, ATP7A) were downregulated in AML. We used LASSO-Cox, Kaplan-Meier, and Nomogram analyses to establish prognostic risk models, effectively stratifying patients with AML into high- and low-risk groups. Subgroup analysis revealed that high-risk patients exhibited poorer overall survival and involvement in fatty acid metabolism, apoptosis, and glycolysis. Immune infiltration analysis indicated differences in immune cell composition, with notable increases in B cells, cytotoxic T cells, and memory T cells in the low-risk group, and increased monocytes and neutrophils in the high-risk group. Single-cell sequencing analysis corroborated the expression characteristics of critical CHRGs, such as MAPK1 and ATOX1, associated with the function of T, B, and NK cells. Drug sensitivity analysis suggested potential therapeutic agents targeting copper homeostasis, including Bicalutamide and Sorafenib. PCR validation confirmed the differential expression of 4 cuproptosis-related genes (LIPT1, SLC31A1, GCSH, and PDHA1) and 9 cuproplasia-associated genes (ATOX1, CCS, CP, MAPK1, SOD1, COA6, PDK1, DBH, and PDE3B) in AML cell line. Importantly, these genes serve as potential biomarkers for patient stratification and treatment. In conclusion, we shed light on the expression patterns and biological functions of CHRGs in AML. The developed risk models provided prognostic implications for patient survival, offering valuable information on the regulatory characteristics of CHRGs and potential avenues for personalized treatment in AML.

Primary tumor resection improves prognosis of unresectable carcinomas of the transverse colon including flexures with pulmonary metastasis: a cohort study.

PURPOSE: Studies of unresectable colorectal cancer pulmonary metastasis (CRPM) have rarely analyzed patient prognosis from the perspective of colonic subsites. This study aimed to evaluate the effects of primary tumor resection (PTR) on the prognosis of patients with unresectable pulmonary metastases of transverse colon cancer pulmonary metastasis (UTCPM), hepatic flexure cancer pulmonary metastasis (UHFPM), and splenic flexure cancer pulmonary metastasis (USFPM). METHODS: Patients were identified from the Surveillance, Epidemiology, and End Results database between 2000 and 2018. The Cox proportional hazards regression models were used to identify prognostic factors of overall survival (OS) and cause-specific survival (CSS). The Kaplan-Meier analyses and log-rank tests were conducted to assess the effectiveness of PTR on survival. RESULTS: This study included 1294 patients: 419 with UHFPM, 636 with UTCPM, and 239 with USFPM. Survival analysis for OS and CSS in the PTR groups, showed that there were no statistical differences in the the UHFPM, UTCPM, and USFPM patients. There were statistical differences in the UHFPM, UTCPM, and USFPM patients for OS and CSS. Three non-PTR subgroups showed significant statistical differences for OS and CSS. CONCLUSION: We confirmed the different survival rates of patients with UTCPM, UHFPM, and USFPM and proved for the first time that PTR could provide survival benefits for patients with unresectable CRPM from the perspective of the colonic subsites of the transverse colon, hepatic flexure, and splenic flexure.

A novel prognostic signature contributes to precision treatment in colon adenocarcinoma with KRAS mutation.

BACKGROUND: Approximately 40% of colon cancer harbor Kirsten rat sarcoma viral oncogene ( KRAS ) mutations, but the prognostic value of KRAS mutations in colon cancer is still controversial. METHODS: We enrolled 412 colon adenocarcinoma (COAD) patients with KRAS mutations, 644 COAD patients with KRAS wild-type and 357 COAD patients lacking information on KRAS status from five independent cohorts. A random forest model was developed to estimate the KRAS status. The prognostic signature was established using least absolute shrinkage and selection operator-Cox regression and evaluated by Kaplan-Meier survival analysis, multivariate-Cox analysis, receiver operating characteristic curve and nomogram. The expression data of KRAS -mutant COAD cell lines from the Cancer Cell Line Encyclopedia database and the corresponding drug sensitivity data from the Genomics of Drug Sensitivity in Cancer database were used for potential target and agent exploration. RESULTS: We established a 36-gene prognostic signature classifying the KRAS -mutant COAD as high and low risk. High risk patients had inferior prognoses compared to those with low risk, while the signature failed to distinguish the prognosis of COAD with KRAS wild-type. The risk score was the independent prognostic factor for KRAS -mutant COAD and we further fabricated the nomograms with good predictive efficiency. Moreover, we suggested FMNL1 as a potential drug target and three drugs as potential therapeutic agents for KRAS -mutant COAD with high risk. CONCLUSION: We established a precise 36-gene prognostic signature with great performance in prognosis prediction of KRAS -mutant COAD providing a new strategy for personalized prognosis management and precision treatment for KRAS -mutant COAD.

[Oculo-facio-cardio-dental syndrome caused by BCOR gene mutations: a case report]. / BCORåŸºå› çªå˜è‡´æ–°ç”Ÿå„¿çœ¼-面-心-牙综合征1例.

A full-term female infant was admitted at 5 hours after birth due to heart malformations found during the fetal period and cyanosis once after birth. Mmultiple malformations of eyes, face, limbs, and heart were noted. The whole-exome sequencing revealed a pathogenic heterozygous mutation, c.2428C>T(p.Arg810*), in the BCOR gene. The infant was then diagnosed with oculo-facio-cardio-dental syndrome. He received assisted ventilation to improve oxygenation and nutritional support during hospitalization. Right ventricular double outlet correction was performed 1 month after birth. Ocular lesions were followed up and scheduled for elective surgery. The possibility of oculo-facio-cardio-dental syndrome should be considered for neonates with multiple malformations of eyes, face, and heart, and genetic testing should be performed as early as possible to confirm the diagnosis; meanwhile, active ophthalmic and cardiovascular symptomatic treatment should be given to improve the prognosis.

RAB27A promotes the proliferation and invasion of colorectal cancer cells.

Colorectal cancer (CRC) is one of the most commonly diagnosed cancer types worldwide. Despite significant advances in prevention and diagnosis, CRC is still one of the leading causes of cancer-related mortality globally. RAB27A, the member of RAB27 family of small GTPases, is the critical protein for intracellular secretion and has been reported to promote tumor progression. However, it is controversial for the role of RAB27A in CRC progression, so we explored the exact function of RAB27A in CRC development in this study. Based on the stable colon cancer cell lines of RAB27A knockdown and ectopic expression, we found that RAB27A knockdown inhibited proliferation and clone formation of SW480 colon cancer cells, whereas ectopic expression of RAB27A in RKO colon cancer cells facilitated cell proliferation and clone formation, indicating that RAB27A is critical for colon cancer cell growth. In addition, our data demonstrated that the migration and invasion of colon cancer cells were suppressed by RAB27A knockdown, but promoted by RAB27A ectopic expression. Therefore, RAB27A is identified as an onco-protein in mediating CRC development, which may be a valuable prognostic indicator and potential therapeutic target for CRC.

Spectrum of Mutations in Pediatric Non-glomerular Chronic Kidney Disease Stages 2-5.

Renal hypodysplasia and cystic kidney diseases, the common non-glomerular causes of pediatric chronic kidney disease (CKD), are usually diagnosed by their clinical and imaging characteristics. The high degree of phenotypic heterogeneity, in both conditions, makes the correct final diagnosis dependent on genetic testing. It is not clear, however, whether the frequencies of damaged alleles vary among different ethnicities in children with non-glomerular CKD, and this will influence the strategy used for genetic testing. In this study, 69 unrelated children (40 boys, 29 girls) of predominantly Han Chinese ethnicity with stage 2-5 non-glomerular CKD caused by suspected renal hypodysplasia or cystic kidney diseases were enrolled and assessed by molecular analysis using proband-only targeted exome sequencing and array-comparative genomic hybridization. Targeted exome sequencing discovered genetic etiologies in 33 patients (47.8%) covering 10 distinct genetic disorders. The clinical diagnoses in 13/48 patients (27.1%) with suspected renal hypodysplasia were confirmed, and two patients were reclassified carrying mutations in nephronophthisis (NPHP) genes. The clinical diagnoses in 16/20 patients (80%) with suspected cystic kidney diseases were confirmed, and one patient was reclassified as carrying a deletion in the hepatocyte nuclear factor-1-beta gene (HNF1B). The diagnosis of one patient with unknown non-glomerular disease was elucidated. No copy number variations were identified in the 20 patients with negative targeted exome sequencing results. NPHP genes were the most common disease-causing genes in the patients with disease onsets above 6 years of age (14/45, 31.1%). The children with stage 2 and 3 CKD at onset were found to carry causative mutations in paired box gene 2 (PAX2) and HNF1B gene (11/24, 45.8%), whereas those with stage 4 and 5 CKD mostly carried causative mutations in NPHP genes (19/45, 42.2%). The causative genes were not suspected by the kidney imaging patterns at disease onset. Thus, our data show that in Chinese children with non-glomerular renal dysfunction caused by renal hypodysplasia and cystic kidney diseases, the common causative genes vary with age and CKD stage at disease onset. These findings have the potential to improve management and genetic counseling of these diseases in clinical practice.

Phenotypic spectrum and antialbuminuric response to angiotensin converting enzyme inhibitor and angiotensin receptor blocker therapy in pediatric Dent disease.

BACKGROUND: To characterize the phenotypic spectrum and assess the antialbuminuric response to angiotensin converting enzyme (ACE) inhibitor and/or angiotensin receptor blocker (ARB) therapy in a cohort of children with Dent disease. METHODS: The patients' clinical findings, renal biopsy results, genetic and follow-up data were analyzed retrospectively. Mutations in CLCN5 or OCRL were detected by next-generation sequencing or Sanger sequencing. RESULTS: Of 31 Dent disease boys, 24 carried CLCN5 and 7 carried OCRL mutations. Low molecular weight proteinuria and albuminuria were detected in all cases. Nephrotic-range proteinuria and severe albuminuria were identified in 52% and 62% of cases, respectively; by 7 years of age, 6 patients had hematuria and nephrotic-range proteinuria, and 7 patients had hematuria and moderate to severe albuminuria. In addition to disease-related renal features, patients with Dent-1 disease also presented with congenital cataract (1/9) and developmental delay (2/7). Seventeen of 31 patients underwent renal biopsy. Glomerular changes included mild glomerular lesions, mesangial proliferative glomerulonephritis and focal segmental glomerular sclerosis. Thirteen of the 31 patients had follow-up records and received ACE inhibitor and/or ARB treatment for more than 3 months. After a median 1.7 (range 0.3-8.5) years of treatment, a reduction in the urinary microalbumin-to-creatinine ratio was observed in 54% of children. CONCLUSIONS: Hematuria with nephrotic-range proteinuria or moderate to severe albuminuria was common in Dent disease patients. Extrarenal manifestations were observed in Dent-1 patients, which extends the phenotypic spectrum. In addition, ACE inhibitors and ARBs are well tolerated, and they are partially effective in controlling albuminuria.

In silico prediction of potential miRNA-disease association using an integrative bioinformatics approach based on kernel fusion.

Accumulating experimental evidence has demonstrated that microRNAs (miRNAs) have a huge impact on numerous critical biological processes and they are associated with different complex human diseases. Nevertheless, the task to predict potential miRNAs related to diseases remains difficult. In this paper, we developed a Kernel Fusion-based Regularized Least Squares for MiRNA-Disease Association prediction model (KFRLSMDA), which applied kernel fusion technique to fuse similarity matrices and then utilized regularized least squares to predict potential miRNA-disease associations. To prove the effectiveness of KFRLSMDA, we adopted leave-one-out cross-validation (LOOCV) and 5-fold cross-validation and then compared KFRLSMDA with 10 previous computational models (MaxFlow, MiRAI, MIDP, RKNNMDA, MCMDA, HGIMDA, RLSMDA, HDMP, WBSMDA and RWRMDA). Outperforming other models, KFRLSMDA achieved AUCs of 0.9246 in global LOOCV, 0.8243 in local LOOCV and average AUC of 0.9175 ± 0.0008 in 5-fold cross-validation. In addition, respectively, 96%, 100% and 90% of the top 50 potential miRNAs for breast neoplasms, colon neoplasms and oesophageal neoplasms were confirmed by experimental discoveries. We also predicted potential miRNAs related to hepatocellular cancer by removing all known related miRNAs of this cancer and 98% of the top 50 potential miRNAs were verified. Furthermore, we predicted potential miRNAs related to lymphoma using the data set in the old version of the HMDD database and 80% of the top 50 potential miRNAs were confirmed. Therefore, it can be concluded that KFRLSMDA has reliable prediction performance.

Anticancer Drug Response Prediction in Cell Lines Using Weighted Graph Regularized Matrix Factorization.

Precision medicine has become a novel and rising concept, which depends much on the identification of individual genomic signatures for different patients. The cancer cell lines could reflect the "omic" diversity of primary tumors, based on which many works have been carried out to study the cancer biology and drug discovery both in experimental and computational aspects. In this work, we presented a novel method to utilize weighted graph regularized matrix factorization (WGRMF) for inferring anticancer drug response in cell lines. We constructed a p-nearest neighbor graph to sparsify drug similarity matrix and cell line similarity matrix, respectively. Using the sparsified matrices in the graph regularization terms, we performed matrix factorization to generate the latent matrices for drug and cell line. The graph regularization terms including neighbor information could help to exclude the noisy ingredient and improve the prediction accuracy. The 10-fold cross-validation was implemented, and the Pearson correlation coefficient (PCC), root-mean-square error (RMSE), PCCsr, and RMSEsr averaged over all drugs were calculated to evaluate the performance of WGRMF. The results on the Genomics of Drug Sensitivity in Cancer (GDSC) dataset are 0.64 ± 0.16, 1.37 ± 0.35, 0.73 ± 0.14, and 1.71 ± 0.44 for PCC, RMSE, PCCsr, and RMSEsr in turn. And for the Cancer Cell Line Encyclopedia (CCLE) dataset, WGRMF got results of 0.72 ± 0.09, 0.56 ± 0.19, 0.79 ± 0.07, and 0.69 ± 0.19, respectively. The results showed the superiority of WGRMF compared with previous methods. Besides, based on the prediction results using the GDSC dataset, three types of case studies were carried out. The results from both cross-validation and case studies have shown the effectiveness of WGRMF on the prediction of drug response in cell lines.

Computational models for lncRNA function prediction and functional similarity calculation.

From transcriptional noise to dark matter of biology, the rapidly changing view of long non-coding RNA (lncRNA) leads to deep understanding of human complex diseases induced by abnormal expression of lncRNAs. There is urgent need to discern potential functional roles of lncRNAs for further study of pathology, diagnosis, therapy, prognosis, prevention of human complex disease and disease biomarker detection at lncRNA level. Computational models are anticipated to be an effective way to combine current related databases for predicting most potential lncRNA functions and calculating lncRNA functional similarity on the large scale. In this review, we firstly illustrated the biological function of lncRNAs from five biological processes and briefly depicted the relationship between mutations or dysfunctions of lncRNAs and human complex diseases involving cancers, nervous system disorders and others. Then, 17 publicly available lncRNA function-related databases containing four types of functional information content were introduced. Based on these databases, dozens of developed computational models are emerging to help characterize the functional roles of lncRNAs. We therefore systematically described and classified both 16 lncRNA function prediction models and 9 lncRNA functional similarity calculation models into 8 types for highlighting their core algorithm and process. Finally, we concluded with discussions about the advantages and limitations of these computational models and future directions of lncRNA function prediction and functional similarity calculation. We believe that constructing systematic functional annotation systems is essential to strengthen the prediction accuracy of computational models, which will accelerate the identification process of novel lncRNA functions in the future.

A Hybrid Interpolation Weighted Collaborative Filtering Method for Anti-cancer Drug Response Prediction.

Individualized therapies ask for the most effective regimen for each patient, while the patients' response may differ from each other. However, it is impossible to clinically evaluate each patient's response due to the large population. Human cell lines have harbored most of the same genetic changes found in patients' tumors, thus are widely used to help understand initial responses of drugs. Based on the more credible assumption that similar cell lines and similar drugs exhibit similar responses, we formulated drug response prediction as a recommender system problem, and then adopted a hybrid interpolation weighted collaborative filtering (HIWCF) method to predict anti-cancer drug responses of cell lines by incorporating cell line similarity and drug similarity shown from gene expression profiles, drug chemical structure as well as drug response similarity. Specifically, we estimated the baseline based on the available responses and shrunk the similarity score for each cell line pair as well as each drug pair. The similarity scores were then shrunk and weighted by the correlation coefficients drawn from the know response between each pair. Before used to find the K most similar neighbors for further prediction, they went through the case amplification strategy to emphasize high similarity and neglect low similarity. In the last step for prediction, cell line-oriented and drug-oriented collaborative filtering models were carried out, and the average of predicted values from both models was used as the final predicted sensitivity. Through 10-fold cross validation, this approach was shown to reach accurate and reproducible outcome for those missing drug sensitivities. We also found that the drug response similarity between cell lines or drugs may play important role in the prediction. Finally, we discussed the biological outcomes based on the newly predicted response values in GDSC dataset.

[Efficacy of recombinant human thrombopoietin combined with high-dose dexamethasone in the treatment of refractory immune thrombocytopenia in children].

OBJECTIVE: To explore the efficacy and safety of recombinant human thrombopoietin (rhTPO) combined with high-dose dexamethasone (DXM) in the treatment of children with refractory immune thrombocytopenic purpura (ITP). METHODS: Fifty-eight ITP children who had failed first-line therapy were randomly divided into two groups: DXM treatment (n=27) and rhTPO + DXM treatment (n=31). The DXM treatment group received two continuous cycles of DXM treatment; in each cycle, patients received high-dose DXM (0.6 mg/kg daily) by intravenous drip for 4 days every 28 days. The rhTPO group received subcutaneous injection of rhTPO (300 U/kg daily) for 14 days additional to DXM treatment. The overall response rate (marked response rate + slight response rate) and adverse reactions were evaluated after 3, 7, and 14 days and 1, 2, and 3 months of treatment. RESULTS: After 7 and 14 days and 1 month of treatment, the rhTPO + DXM treatment group had a significantly higher marked response rate and a significantly higher overall response rate than the DXM treatment group (P<0.05). After 2 months of treatment, the rhTPO + DXM treatment group had a significantly higher overall response rate than the DXM group (P<0.05). One patient in the DXM treatment group had liver damage during the first week of treatment. There was no hypertension, fever, rash, allergy, or weakness in the two groups. CONCLUSIONS: rhTPO combined with high-dose DXM is an effective and safe approach for treating refractory ITP.

Predicting miRNA-disease association based on inductive matrix completion.

Motivation: It has been shown that microRNAs (miRNAs) play key roles in variety of biological processes associated with human diseases. In Consideration of the cost and complexity of biological experiments, computational methods for predicting potential associations between miRNAs and diseases would be an effective complement. Results: This paper presents a novel model of Inductive Matrix Completion for MiRNA-Disease Association prediction (IMCMDA). The integrated miRNA similarity and disease similarity are calculated based on miRNA functional similarity, disease semantic similarity and Gaussian interaction profile kernel similarity. The main idea is to complete the missing miRNA-disease association based on the known associations and the integrated miRNA similarity and disease similarity. IMCMDA achieves AUC of 0.8034 based on leave-one-out-cross-validation and improved previous models. In addition, IMCMDA was applied to five common human diseases in three types of case studies. In the first type, respectively, 42, 44, 45 out of top 50 predicted miRNAs of Colon Neoplasms, Kidney Neoplasms, Lymphoma were confirmed by experimental reports. In the second type of case study for new diseases without any known miRNAs, we chose Breast Neoplasms as the test example by hiding the association information between the miRNAs and Breast Neoplasms. As a result, 50 out of top 50 predicted Breast Neoplasms-related miRNAs are verified. In the third type of case study, IMCMDA was tested on HMDD V1.0 to assess the robustness of IMCMDA, 49 out of top 50 predicted Esophageal Neoplasms-related miRNAs are verified. Availability and implementation: The code and dataset of IMCMDA are freely available at https://github.com/IMCMDAsourcecode/IMCMDA. Supplementary information: Supplementary data are available at Bioinformatics online.

IP3R-Grp75-VDAC1-MCU calcium regulation axis antagonists protect podocytes from apoptosis and decrease proteinuria in an Adriamycin nephropathy rat model.

BACKGROUND: The mechanism of podocyte apoptosis is not fully understood. In addition, the role of the inositol 1,4,5-triphosphate receptor (IP3R)/glucose-regulated protein 75 (Grp75)/voltage-dependent anion channel 1 (VDAC1)/mitochondrial calcium uniporter (MCU) calcium regulation axis, which is located at sites of endoplasmic reticulum (ER) mitochondria coupling, in the mechanism of podocyte apoptosis is unclear. This study aimed to understand the roles of this axis in podocyte apoptosis and explore potential targets for podocyte protection. METHODS: The expression of IP3R, Grp75, VDAC1, and MCU and mitochondrial Ca2+ were analyzed during Adriamycin- or angiotensin II-induced apoptosis in cultured mouse podocytes. The interaction between IP3R, Grp75, and VDAC1 was investigated using co-immunoprecipitation experiments. The effects of IP3R, Grp75, and MCU agonists and antagonists on mitochondrial Ca2+ and apoptosis were investigated in cultured podocytes. The podocyte-protective effects of an MCU inhibitor were further investigated in rats with Adriamycin-induced nephropathy. RESULTS: Increased expression of IP3R, Grp75, VDAC1 and MCU, enhanced interaction among the IP3R-Grp75-VDAC1 complex, mitochondrial Ca2+ overload, and increased active caspase-3 levels were confirmed during Adriamycin- or angiotensin II-induced mouse podocyte apoptosis. Agonists of this axis facilitated mitochondrial Ca2+ overload and podocyte apoptosis, whereas specific antagonists against IP3R, Grp75, or MCU prevented mitochondrial Ca2+ overload and podocyte apoptosis. A specific MCU inhibitor prevented Adriamycin-induced proteinuria and podocyte foot process effacement in rats. CONCLUSIONS: This study identified a novel pathway in which the IP3R-Grp75-VDAC1-MCU calcium regulation axis mediated podocyte apoptosis by facilitating mitochondrial Ca2+ overload. Antagonists that inhibit Ca2+ transfer from ER to mitochondria protected mouse podocytes from apoptosis. An MCU inhibitor protected podocytes and decreased proteinuria in rats with Adriamycin-induced nephropathy. Therefore, antagonists to this pathway have promise as novel podocyte-protective drugs.

HNMDA: heterogeneous network-based miRNA-disease association prediction.

Recently, accumulating evidences have shown that microRNAs (miRNAs) could play key roles in the development and progression of multiple important human diseases. Nonetheless, due to the shortcoming of being expensive and time-consuming existing in experimental approaches, computational methods are needed for the prediction of potential miRNA-disease associations. In our study, we proposed a computational model named Heterogeneous Network-based MiRNA-Disease Association prediction (HNMDA) for the latent miRNA-disease association prediction by integrating known miRNA-disease associations, miRNA functional similarity, disease semantic similarity and Gaussian interaction profile kernel similarity. The Gaussian interaction profile kernel similarity can make up for the shortages of the traditional similarity calculation methods. Furthermore, we applied a heterogeneous network-based method, in which we first implemented a network diffusion algorithm of random walk with restart, and then we applied a method to find the optimal projection from miRNA space to disease space, which enabled the prediction of new miRNA-disease associations that are not experimentally confirmed so far. In the cross-validation, HNMDA obtained the AUC of 0.8394, which achieved improvement compared with previous methods. In the case studies of breast neoplasms, esophageal neoplasms and kidney neoplasms based on known miRNA-disease associations in the HMDD V2.0 database, there were 82, 76 and 84% of top 50 predicted related miRNAs that were confirmed to have associations with these three diseases, respectively. In the further case studies for new diseases without any known related miRNAs and the case using HMDD V1.0 database as known associations, there were also high ratio of the predicted miRNAs confirmed by experimental reports.

GRMDA: Graph Regression for MiRNA-Disease Association Prediction.

Nowadays, as more and more associations between microRNAs (miRNAs) and diseases have been discovered, miRNA has gradually become a hot topic in the biological field. Because of the high consumption of time and money on carrying out biological experiments, computational method which can help scientists choose the most likely associations between miRNAs and diseases for further experimental studies is desperately needed. In this study, we proposed a method of Graph Regression for MiRNA-Disease Association prediction (GRMDA) which combines known miRNA-disease associations, miRNA functional similarity, disease semantic similarity, and Gaussian interaction profile kernel similarity. We used Gaussian interaction profile kernel similarity to supplement the shortage of miRNA functional similarity and disease semantic similarity. Furthermore, the graph regression was synchronously performed in three latent spaces, including association space, miRNA similarity space, and disease similarity space, by using two matrix factorization approaches called Singular Value Decomposition and Partial Least-Squares to extract important related attributes and filter the noise. In the leave-one-out cross validation and five-fold cross validation, GRMDA obtained the AUCs of 0.8272 and 0.8080 ± 0.0024, respectively. Thus, its performance is better than some previous models. In the case study of Lymphoma using the recorded miRNA-disease associations in HMDD V2.0 database, 88% of top 50 predicted miRNAs were verified by experimental literatures. In order to test the performance of GRMDA on new diseases with no known related miRNAs, we took Breast Neoplasms as an example by regarding all the known related miRNAs as unknown ones. We found that 100% of top 50 predicted miRNAs were verified. Moreover, 84% of top 50 predicted miRNAs in case study for Esophageal Neoplasms based on HMDD V1.0 were verified to have known associations. In conclusion, GRMDA is an effective and practical method for miRNA-disease association prediction.

The role of ATP signalling in response to mechanical stimulation studied in T24 cells using new microphysiological tools.

The capacity to store urine and initiate voiding is a valued characteristic of the human urinary bladder. To maintain this feature, it is necessary that the bladder can sense when it is full and when it is time to void. The bladder has a specialized epithelium called urothelium that is believed to be important for its sensory function. It has been suggested that autocrine ATP signalling contributes to this sensory function of the urothelium. There is well-established evidence that ATP is released via vesicular exocytosis as well as by pannexin hemichannels upon mechanical stimulation. However, there are still many details that need elucidation and therefore there is a need for the development of new tools to further explore this fascinating field. In this work, we use new microphysiological systems to study mechanostimulation at a cellular level: a mechanostimulation microchip and a silicone-based cell stretcher. Using these tools, we show that ATP is released upon cell stretching and that extracellular ATP contributes to a major part of Ca2+ signalling induced by stretching in T24 cells. These results contribute to the increasing body of evidence for ATP signalling as an important component for the sensory function of urothelial cells. This encourages the development of drugs targeting P2 receptors to relieve suffering from overactive bladder disorder and incontinence.

GIMDA: Graphlet interaction-based MiRNA-disease association prediction.

MicroRNAs (miRNAs) have been confirmed to be closely related to various human complex diseases by many experimental studies. It is necessary and valuable to develop powerful and effective computational models to predict potential associations between miRNAs and diseases. In this work, we presented a prediction model of Graphlet Interaction for MiRNA-Disease Association prediction (GIMDA) by integrating the disease semantic similarity, miRNA functional similarity, Gaussian interaction profile kernel similarity and the experimentally confirmed miRNA-disease associations. The related score of a miRNA to a disease was calculated by measuring the graphlet interactions between two miRNAs or two diseases. The novelty of GIMDA lies in that we used graphlet interaction to analyse the complex relationships between two nodes in a graph. The AUCs of GIMDA in global and local leave-one-out cross-validation (LOOCV) turned out to be 0.9006 and 0.8455, respectively. The average result of five-fold cross-validation reached to 0.8927 ± 0.0012. In case study for colon neoplasms, kidney neoplasms and prostate neoplasms based on the database of HMDD V2.0, 45, 45, 41 of the top 50 potential miRNAs predicted by GIMDA were validated by dbDEMC and miR2Disease. Additionally, in the case study of new diseases without any known associated miRNAs and the case study of predicting potential miRNA-disease associations using HMDD V1.0, there were also high percentages of top 50 miRNAs verified by the experimental literatures.

Inhibitory Effects of Urothelium-related Factors.

The urothelium of the bladder has long been recognized as a protective barrier between detrusor and urine. In recent years, it has become more evident that the urothelium plays a role as an active source of mediators. The urothelium can release neurotransmitters and modulators such as acetylcholine, ATP, nitric oxide, prostaglandins and neuropeptides. They exert both excitatory and inhibitory effects in modulating urinary tract motility. In addition, several studies have reported the existence of an urothelium-derived unknown inhibitory factor in the urinary bladder. By the use of a new serial cascade superfusion bioassay on guinea pig ureter, recent studies confirm that the guinea pig bladder urothelium releases a substance with inhibitory bioactivity, which was resistant to treatment with nitric oxide synthase inhibitor and cyclooxygenase inhibitor and to adenosine A1/A2 receptor blockade. Lately, a marked and quickly inactivated novel release of PGD2 from the bladder urothelium was discovered, together with localization of prostaglandin D synthase therein. PGD2 was found to have an inhibitory influence on nerve-induced contractions in guinea pig urinary bladder and on spontaneous contractions in the out-flow region. An altered release of excitatory and inhibitory factors is likely to play an important part in bladder motility disturbances, of which the prostanoids are a notable group. Due to the fact that the bladder is relaxed 99% of the time, not only excitatory mechanisms in the bladder are necessary to study, but also inhibitory mechanisms need considerable attention, which will contribute to the discovery of new targets to treat bladder motility disorders.