Identification and validation of screening models for breast cancer with 3 serum miRNAs in an 11,349 samples mixed cohort.

PURPOSE: The study focuses on enhancing breast cancer (BC) prognosis through early detection, aiming to establish a non-invasive, clinically viable BC screening method using specific serum miRNA levels. METHODS: Involving 11,349 participants across BC, 11 other cancer types, and control groups, the study identified serum biomarkers through feature selection and developed two BC screening models using six machine learning algorithms. These models underwent evaluation across test, internal, and external validation sets, assessing performance metrics like accuracy, sensitivity, specificity, and the area under the curve (AUC). Subgroup analysis was conducted to test model stability. RESULTS: Based on the three serum miRNA biomarkers (miR-1307-3p, miR-5100, and miR-4745-5p), a BC screening model, SM4BC3miR model, was developed. This model achieved AUC performances of 0.986, 0.986, and 0.939 on the test, internal, and external sets, respectively. Furthermore, the SSM4BC model, utilizing ratio scores of miR-1307-3p/miR-5100 and miR-4745-5p/miR-5100, showed AUCs of 0.973, 0.980, and 0.953, respectively. Subgroup analyses underscored both models' robustness and stability. CONCLUSION: This research introduced the SM4BC3miR and SSM4BC models, leveraging three specific serum miRNA biomarkers for breast cancer screening. Demonstrating high accuracy and stability, these models present a promising approach for early detection of breast cancer. However, their practical application and effectiveness in clinical settings remain to be further validated.

Methodology for Isolation of miRNA From the Serum of Women Investigated for Pre-eclampsia.

Background Pre-eclampsia remains a leading cause of maternal and foetal mortality with a poorly understood pathophysiology. It can lead to a range of clinical presentations, but proteinuria and hypertension are key components of the diagnosis. These signs arise due to disordered placental implantation due to poor trophoblastic invasion, resulting in placental oxidative stress due to hypoxia. Oxidative stress triggers the release of syncytiotrophoblast microvesicles (STMBs), of which placenta-derived exosomes may be a key component. The high specificity of exosomes for their cell of origin makes them ideal candidates as diagnostic biomarkers. We are particularly interested in the miRNAs (microRNAs) contained within these exosomes, as they may give us an insight into the genomic regulation within the pre-eclamptic placenta that leads to the disease state. The development of workflows for miRNA quantitation may enable us to identify novel biomarkers. Methods We extracted exosomes and purified total RNA from 23 serum samples using the Norgen Plasma/Serum Exosome Purification and RNA Isolation Midi Kit. We then used the bioanalyser to determine the concentration and quality of the RNA obtained. It uses rapid electrophoresis, requires minimal sample sizes, and can assess the quality of genetic material as small as 25 bases. Results We have successfully isolated RNA from these samples; however, the concentration of the total RNA was too low for downstream molecular analysis. We did gain insight into how to optimise and develop the workflow so that, with each attempt, the yield increased. Our greatest concentrations were obtained by combining serum samples from multiple patients, demonstrating that we needed a higher volume to optimise the yield. Future studies should aim to obtain samples specifically for use in this research so that we can process a larger volume of serum. Conclusions We have also noted that there is a positive correlation between the overall concentration of total RNA and a high sFlt-1/PlGF ratio. Preliminary analysis from Illumina identified with a high degree of confidence the presence of three miRNAs, namely, mir-498(46), mir-122(1), and mir-134(41). Further work is necessary to validate these findings and should focus on the possible future role of these miRNAs as biomarkers for the early diagnosis of pre-eclampsia.

Proposing new early detection indicators for pancreatic cancer: Combining machine learning and neural networks for serum miRNA-based diagnostic model.

Background: Pancreatic cancer (PC) is a lethal malignancy that ranks seventh in terms of global cancer-related mortality. Despite advancements in treatment, the five-year survival rate remains low, emphasizing the urgent need for reliable early detection methods. MicroRNAs (miRNAs), a group of non-coding RNAs involved in critical gene regulatory mechanisms, have garnered significant attention as potential diagnostic and prognostic biomarkers for pancreatic cancer (PC). Their suitability stems from their accessibility and stability in blood, making them particularly appealing for clinical applications. Methods: In this study, we analyzed serum miRNA expression profiles from three independent PC datasets obtained from the Gene Expression Omnibus (GEO) database. To identify serum miRNAs associated with PC incidence, we employed three machine learning algorithms: Support Vector Machine-Recursive Feature Elimination (SVM-RFE), Least Absolute Shrinkage and Selection Operator (LASSO), and Random Forest. We developed an artificial neural network model to assess the accuracy of the identified PC-related serum miRNAs (PCRSMs) and create a nomogram. These findings were further validated through qPCR experiments. Additionally, patient samples with PC were classified using the consensus clustering method. Results: Our analysis revealed three PCRSMs, namely hsa-miR-4648, hsa-miR-125b-1-3p, and hsa-miR-3201, using the three machine learning algorithms. The artificial neural network model demonstrated high accuracy in distinguishing between normal and pancreatic cancer samples, with verification and training groups exhibiting AUC values of 0.935 and 0.926, respectively. We also utilized the consensus clustering method to classify PC samples into two optimal subtypes. Furthermore, our investigation into the expression of PCRSMs unveiled a significant negative correlation between the expression of hsa-miR-125b-1-3p and age. Conclusion: Our study introduces a novel artificial neural network model for early diagnosis of pancreatic cancer, carrying significant clinical implications. Furthermore, our findings provide valuable insights into the pathogenesis of pancreatic cancer and offer potential avenues for drug screening, personalized treatment, and immunotherapy against this lethal disease.

A validation study for the utility of serum microRNA as a diagnostic and prognostic marker in patients with osteosarcoma.

In our previous study, osteosarcoma advanced locally, and metastasis was promoted through the secretion of large number of small extracellular vesicles, followed by suppressing osteoclastogenesis via the upregulation of microRNA (miR)-146a-5p. An additional 12 miRNAs in small extracellular vesicles were also detected ≥6× as frequently in high-grade malignancy with the capacity to metastasize as in those with a low metastatic potential. However, the utility of these 13 miRNAs for determining the prognosis or diagnosis of osteosarcoma has not been validated in the clinical setting. In the present study, the utility of these miRNAs as prognostic and diagnostic markers was therefore assessed. In total, 30 patients with osteosarcoma were retrospectively reviewed, and the survival rate was compared according to the serum miRNA levels in 27 patients treated with chemotherapy and surgery. In addition, to confirm diagnostic competency for osteosarcoma, the serum miRNA levels were compared with those in patients with other bone tumors (n=112) and healthy controls (n=275). The patients with osteosarcoma with high serum levels of several miRNAs (miR-146a-5p, miR-1260a, miR-487b-3p, miR-1260b and miR-4758-3p) exhibited an improved survival rate compared with those with low levels. In particular, patients with high serum levels of miR-1260a exhibited a significantly improved overall survival rate, metastasis-free survival rate and disease-free survival rate compared with those with low levels. Thus, serum miR-1260a may potentially be a prognostic marker for patients with osteosarcoma. Moreover, patients with osteosarcoma had higher serum miR-1261 levels than those with benign or intermediate-grade bone tumors and thus may be a potential therapeutic target, in addition to being useful for differentiating whether or not a bone tumor is high-grade. A larger investigation is required to clarify the actual utility of these miRNAs in the clinical setting.

Construction of a serum diagnostic signature based on m5C-related miRNAs for cancer detection.

Currently, no clinically relevant non-invasive biomarkers are available for screening of multiple cancer types. In this study, we developed a serum diagnostic signature based on 5-methylcytosine (m5C)-related miRNAs (m5C-miRNAs) for multiple-cancer detection. Serum miRNA expression data and the corresponding clinical information of patients were collected from the Gene Expression Omnibus database. Serum samples were then randomly assigned to the training or validation cohort at a 1:1 ratio. Using the identified m5C-miRNAs, an m5C-miRNA signature for cancer detection was established using a support vector machine algorithm. The constructed m5C-miRNA signature displayed excellent accuracy, and its areas under the curve were 0.977, 0.934, and 0.965 in the training cohort, validation cohort, and combined training and validation cohort, respectively. Moreover, the diagnostic capability of the m5C-miRNA signature was unaffected by patient age or sex or the presence of noncancerous disease. The m5C-miRNA signature also displayed satisfactory performance for distinguishing tumor types. Importantly, in the detection of early-stage cancers, the diagnostic performance of the m5C-miRNA signature was obviously superior to that of conventional tumor biomarkers. In summary, this work revealed the value of serum m5C-miRNAs in cancer detection and provided a new strategy for developing non-invasive and cost effective tools for large-scale cancer screening.

Construction of a Diagnostic Model for Distinguishing Benign or Malignant Bone Cancer by Mining miRNA Expression Data.

Bone tumor is a kind of rare cancer, the location of which is mainly in bone tissue as well as cartilage tissue. Bone tumor is mainly classified into benign and malignant types. The survival rate of patients with bone tumors can be considerably improved by early detection, and the danger of amputation caused by bone tumors can be greatly reduced. In this study, we first screened the top 25% serum miRNAs with the greatest variance in patients with malignant and benign bone tumor and healthy individuals. The expression of serum miRNAs in patients with bone tumor was then examined using unsupervised clustering and PCA, and the results revealed that the overall expression of serum miRNAs was ineffective in distinguishing patients with benign/malignant bone tumors. Subsequently, we screened 19 miRNA biomarkers that could be used to determine the benign/malignant bone tumor of patients by LASSO logistic regression. These genes were validated using ROC curves. Results showed that there were 11 miRNAs that could accurately distinguish benign/malignant bone tumor alone. These 11 miRNAs were, namely, hsa-miR-192-5p, hsa-miR-137, hsa-miR-142-3p, hsa-miR-155-3p, hsa-miR-1205, hsa-miR-1273a, hsa-miR-3187-3p, hsa-miR-1255b-2-3p, hsa-miR-1288-5p, hsa-miR-6836-5p, and hsa-miR-6862-5p. Next, we established a diagnostic model using logistic regression and validated the diagnostic model using ROC curves; the result of which showed that the model had good diagnostic efficacy. Then, we also verified that the diagnostic model established by these 11 miRNAs could distinguish patients with benign/malignant bone tumor using unsupervised clustering as well as PCA. Finally, by using qPCR, we validated the expression of 11 miRNAs in the serum of patients with malignant and benign bone tumors, as well as healthy volunteers. The results were consistent with the trend of miRNAs expression in public databases. In summary, we examined the differential expression of serum miRNAs in individuals with benign and malignant bone tumors and discovered 11 miRNA biomarkers that could be utilized to discriminate between the two.

Thyroid Cancer Persistence in Patients with Unreliable Thyroglobulin Measurement: Circulating microRNA as Candidate Alternative Biomarkers.

BACKGROUND: We aimed to evaluate the role of circulating miRNAs as a biomarker of the persistence of papillary thyroid cancer (PTC) in patients with an "uninformative" thyroglobulin (Tg) measurement. METHODS: We prospectively enrolled 49 consecutive PTC patients with Tg-positive antibodies (TgAb) who had undergone a (near)-total thyroidectomy and 131I therapy (RIT). The serum thyroid stimulating hormone (TSH), Tg, and TgAb levels were measured before and at 6 and 12 months after RIT, respectively. The serum miRNA (221, 222, 375, 155, and 146b) levels were measured simultaneously. RESULTS: The response to the initial therapy was assessed according to the 2015 ATA criteria. A decrease in 50% or more of serum miRNA over time was observed in 41/49 PTC patients, who showed an excellent response (ER), but six and two patients were classified to have an indeterminate/incomplete biochemical or incomplete structural response to initial therapy. CONCLUSION: Serum miRNA kinetics emerge as a promising biomarker for the early detection of a persistent disease in PTC patients with uninformative Tg results.

Predict ovarian cancer by pairing serum miRNAs: Construct of single sample classifiers.

Objective: The accuracy of CA125 or clinical examination in ovarian cancer (OVC) screening is still facing challenges. Serum miRNAs have been considered as promising biomarkers for clinical applications. Here, we propose a single sample classifier (SSC) method based on within-sample relative expression orderings (REOs) of serum miRNAs for OVC diagnosis. Methods: Based on the stable REOs within 4,965 non-cancer serum samples, we developed the SSC for OVC in the training cohort (GSE106817: OVC = 200, non-cancer = 2,000) by focusing on highly reversed REOs within OVC. The best diagnosis is achieved using a combination of reversed miRNA pairs, considering the largest evaluation index and the lowest number of miRNA pairs possessed according to the voting rule. The SSC was then validated in internal data (GSE106817: OVC = 120, non-cancer = 759) and external data (GSE113486: OVC = 40, non-cancer = 100). Results: The obtained 13-miRPairs classifier showed high diagnostic accuracy on distinguishing OVC from non-cancer controls in the training set (sensitivity = 98.00%, specificity = 99.60%), which was reproducible in internal data (sensitivity = 98.33%, specificity = 99.21%) and external data (sensitivity = 97.50%, specificity = 100%). Compared with the published models, it stood out in terms of correct positive predictive value (PPV) and negative predictive value (NPV) (PPV = 96.08% and NPV=95.16% in training set, and both above 99% in validation set). In addition, 13-miRPairs demonstrated a classification accuracy of over 97.5% for stage I OVC samples. By integrating other non-OVC serum samples as a control, the obtained 17-miRPairs classifier could distinguish OVC from other cancers (AUC>92% in training and validation set). Conclusion: The REO-based SSCs performed well in predicting OVC (including early samples) and distinguishing OVC from other cancer types, proving that REOs of serum miRNAs represent a robust and non-invasive biomarker.

DNA-gold nanoprobe-based integrated biosensing technology for non-invasive liquid biopsy of serum miRNA: A new frontier in prostate cancer diagnosis.

The low specificity of prostate-specific antigen contributes to overdiagnosis and ov ertreatment of prostate cancer (PCa) patients. Hence, there is an urgent need for inclusive diagnostic platforms that could improve the diagnostic accuracy of PCa. Dysregulated miRNAs are closely associated with the progression and recurrence and have emerged as promising diagnostic and prognostic biomarkers for PCa. Nevertheless, simple, rapid, and ultrasensitive quantification of serum miRNAs is highly challenging. This study designed, synthesized, and demonstrated the practicability of DNA-linked gold nanoprobes (DNA-AuNPs) for the single-step quantification of miR-21/miR-141/miR-375. In preclinical study, the assay differented PCa Pten conditional knockout (PtencKO) mice compared to their age-matched Pten wild-type (PtenWT) control mice. In human sera, receiver operating characteristic (ROC) curve-based correlation analyses revealed clear discrimination between PCa patients from normal healthy controls using training and validation sets. Overall, we established integrated nano-biosensing technology for the PCR-free, non-invasive liquid biopsies of multiple miRNAs for PCa diagnosis.

Alterations in the Expression Profile of Serum miR-155, miR-223, miR-17, miR-200a, miR-205, as well as Levels of Interleukin 6, and Prostaglandins during Endometritis in Arabian Mares.

So far the intimate link between serum microRNA (miRNA) and uterine inflammation in mares is unknown. We aimed (I) to investigate expression profile of eca-miR-155, eca-miR-223, eca-miR-17, eca-miR-200a, and eca-miR-205 (II) and to measure concentrations of interleukin 6 (IL-6), and prostaglandins (PGF2α and PGE2) in serum of mares with healthy and abnormal uterine status (endometritis). This study was conducted on 80 Arabian mares: young (4-7 years), and old (8-14 years). Mares were divided into 48 sub-fertile (endometritis) and 32 fertile (control) at stud farms. Serum was collected for measuring IL-6, PGF2α, and PGE2, as well as miRNA isolation and qRT-PCR. Concentrations of IL-6, PGE2, and PGF2α were higher in mares with endometritis compared to control. Age of mares had a remarkable effect on IL-6, PGE2, and PGF2α concentrations. Relative abundance of eca-miR-155, eca-miR-223, eca-miR-17, eca-miR-200a, and eca-miR-205 was higher in both young and old mares with endometritis. We noticed that eca-miR-155, eca-miR-223, eca-miR-200a, and eca-miR-205 revealed higher expression level in old than young mares with endometritis. This is the first study that has revealed the changes in cell free miRNA and serum inflammatory mediators during endometritis, and these findings could be used for a better understanding the pathophysiology mechanisms of endometritis in equine.

Significant Changes in Serum MicroRNAs after High Tibial Osteotomy in Medial Compartmental Knee Osteoarthritis: Potential Prognostic Biomarkers.

High tibial osteotomy (HTO) is an effective alternative for medial compartmental knee osteoarthritis (OA). Circulating microRNAs (miRNAs) are known to serve as OA-related biomarkers. The present study investigated the differential expression of serum miRNAs before and after HTO to identify potential miRNAs as prognostic biomarkers. miRNA-polymerase chain reaction (PCR) arrays were used to screen for miRNAs in the serum at preoperative and 6-month postoperative time points from six patients, and the differentially expressed miRNAs identified in the profiling stage were validated using real-time PCR at post-operative months 6 and 18 in 27 other HTO-treated patients. Among 84 miRNAs involved in the inflammatory process, three (miR-19b-3p, miR-29c-3p, and miR-424-5p) showed differential expression patterns in the profiling stage (p = 0.011, 0.015, and 0.021, respectively). Levels of these three and four other miRNAs (miR-140-3p, miR-454-3p, miR-let-7e-5p, and miR-885-5p) known to be related to OA progression were evaluated in the serum of 27 patients. Only four miRNAs (miR-19b-3p, miR-140-3p, miR-454-3p, and miR-let-7e-5p) were significantly upregulated at postoperative month 6 (p = 0.003, 0.005, 0.004, and 0.004, respectively), and only miR-140-3p was significantly upregulated up to 18 months after operation (p = 0.003). Together, this study reveals the significantly upregulated serum miRNAs after HTO as potential prognostic biomarkers; however, further studies are warranted to elucidate their clinical implications.

Circulating miRNA Signatures Associated with Insulin Resistance in Adolescents with Obesity.

PURPOSE: MicroRNAs (miRNAs) are implicated in metabolic changes accompanying progression of obesity, insulin resistance (IR), and metabolic disorders in children. Identifying circulating miRNAs that uniquely associate with these disorders may be useful in early identification and prevention of obesity-related complications. We aimed to identify circulating miRNA signatures that distinguish adolescents with obesity and IR from those with obesity unaccompanied by IR. METHODS: Adolescents (aged 10-17 years) with obesity were recruited from a weight management clinic. Fasting serum samples were obtained from 33 participants. A total of 179 miRNAs were queried by a quantitative RT-PCR-based miRNA focus panel. Differentially expressed miRNAs were compared between groups using Student's t-test or one-way ANOVA analysis, and the association between IR evaluated by homeostatic model assessment model (HOMA-IR > 4) and body mass index (BMI) status was assessed using Pearson's correlation analysis. RESULTS: We found an expression pattern consisting of 12 elevated miRNAs linked to IR in obese adolescents. miR-30d, -221, and -122 were significantly correlated with clinical and biochemical markers of obesity and IR, suggestive of IR in adolescents at risk. CONCLUSION: Specific signatures of circulating miRNAs reflected metabolic phenotypes and predicted the presence of IR in adolescents with obesity, suggesting that miRNA indicators may identify obesity-associated complications in childhood. Further studies will be needed to understand cause versus effect and the mechanisms by which IR status links to changes in blood miRNA profiles.

The association between circulating MicroRNA-150 level and cholangiocarcinoma.

Cholangiocarcinoma (CCA) is a rare tumor which requires a multimodality approach for its diagnosis. Carbohydrate antigen 19-9 (CA19-9) is currently the most commonly used tumor marker for CCA; nevertheless, it has certain limitations which need to be considered when using it as a tumor marker. MiRNA-150 altered expression has been linked to the development and tumorigenesis of several cancers including CCA. This work aimed to study the serum level of CA19-9 and miRNA-150 expression in CCA patients and, also, to correlate their levels with tumor staging and different studied clinical and laboratory parameters. This work included 35 patients with CCA who were admitted to Hepatobiliary Unit, Alexandria Main University Hospital (Group I). Also, 35 age- and sex-matched healthy subjects were included as a control group (Group II). All included subjects were submitted to measurement of serum CA19-9 and MiRNA-150 expression levels. Serum CA19-9 levels showed an evident high median among CCA patients, while serum miRNA-150 expression levels were evidently low among those patients. Moreover, combining miRNA-150 with CA19-9 made the accuracy of diagnosis of CCA much more reliable. Thus, miRNA-150 can be considered as a non-invasive, sensitive serum biomarker for the diagnosis of CCA especially when combined with CA 19-9.

Cell-free microRNA-21: biomarker for intracranial aneurysm rupture.

BACKGROUND: Deregulation of miRNA-21 expression has been reported to be associated with vascular smooth muscle behavior and cytoskeletal stability. This study is aimed to investigate the density of serum miRNA-21 in patients with different phases of intracranial aneurysms (IAs) and explore its warning function for IA rupture. METHODS: A total of 16 in 200 IA patients were selected and categorized into 4 groups based on the phase of IA. Microarray study was carried out using serum miRNA and differentially expressed miRNAs were identified. Another 24 samples from a cohort of 360 patients were added and real-time polymerase chain reaction (RT-PCR) was performed on expanded sample size (n = 40) for miRNA-21 validation. Potential gene targets of miRNA-21 were screened out from Gene Ontology (GO) database and literatures. RESULTS: Microarray study identified 77 miRNAs with significantly different expression levels between experimental groups and the control group. RT-PCR assays validated significant downregulation of miRNA-21 in experimental groups, among which miRNA-21 expression level of daughter aneurysm group decreased the most. Bioinformatic analyses revealed that several target genes related with miRNA-21 may be involved in IA formation and rupture. CONCLUSIONS: This study suggested that miRNA-21 had a protective effect for intracranial vascular wall against remodeling and warning function for intracranial aneurysm rupture. Significant suppression of serum miRNA-21 in IA patients may provide diagnostic clues for aneurysm rupture and guide clinical intervention.

Urinary versus serum microRNAs in human oxalic acid poisoning: Contrasting signals and performance.

MicroRNAs are key regulators of the normal kidney function and development, and altered in acute kidney injury (AKI). However, there is a lack of studies comparing serum and urine miRNA expression in toxic AKI in humans. We aimed to compare the global signature of urinary and serum microRNAs, with and without kidney injury, after human oxalic acid poisoning. We profiled urinary microRNAs in patients who ingested oxalic acid and developed no injury (No AKI n = 3), moderate injury (AKIN2 n = 3) or severe injury (AKIN3 n = 3) and healthy controls (n = 3). We validated a signature of 30 urinary microRNAs identified in the discovery profiling, in a second cohort of individuals exposed to oxalic acid (No AKI n = 15, AKIN2 n=11 & AKIN3 n= 18) and healthy controls (n=-27) and we compared the results with previously published serum data. Global profiling in toxic AKI patients showed a higher expression of urinary microRNAs and lower expression of serum microRNAs. Most urine microRNA in the validation cohort were significantly upregulated (25/30, fold change >2.8 and p < 0.05) in AKIN2/3 patients compared to No AKI. Four urinary microRNAs (miR-191, miR-19b, miR-20a and miR-30b) had good diagnostic performance (AUC greater than 0.8) to predict AKIN2/3 between 4-8 hours post ingestion. Poisoning irrespective of AKI led to significantly lower expression of many microRNAs in serum but relatively few changes in urinary miRNA expression. In conclusion, urinary microRNA signature provides a stronger measure of AKI in oxalic acid poisoning compared to serum microRNA. Kidney injury has the greatest impact on urinary microRNA, while poisoning itself was better reflected in serum miRNA. Plasma and urinary microRNAs signatures provide complementary information in toxic kidney injury.

A Three-microRNA Panel in Serum: Serving as a Potential Diagnostic Biomarker for Renal Cell Carcinoma.

PURPOSE: Renal cell carcinoma (RCC) accounts for about 120,000 death each year. Although surgery is a routine treatment, RCC could be fatal if not diagnosed at an early stage. This study aims to search for suitable serum biomarkers and construct a miRNA panel with high diagnostic sensitivity or specificity. METHODS: Totally 146 RCC patients and 150 normal control were involved in this three-stage study. Serum expression levels of 30 miRNAs selected from literature were tested by reverse transcription quantitative PCR (RT-qPCR) in the screening stage, the testing stage, and the validation stage. The diagnostic efficiency of miRNAs was evaluated by receiver operating characteristic (ROC) curve and area under curve (AUC) analysis. A panel with the highest diagnostic efficiency was constructed by backward stepwise logistic regression analysis. Additionally, bioinformatics analysis was used to investigate potential biological functions and mechanisms of candidate miRNAs. RESULTS: MiR-224-5p, miR-34b-3p, miR-129-2-3p and miR-182-5p with low to moderate diagnostic ability (AUC = 0.692, 0.778, 0.687 and 0.745, respectively) were selected as candidate miRNAs after the three-stage study. The final diagnostic panel was consisted by miR-224-5p, miR-34b-3p and miR-182-5p with AUC = 0.855. No significance has been found between these four miRNAs and tumor location, Fuhrman Grade and AJCC clinical stages of RCC. Bioinformatic analysis suggested that the three-miRNAs panel may participate in tumorigenesis of RCC by targeting CORO1C. CONCLUSIONS: The three-miRNA panel in serum could serve as a non-invasive diagnostic biomarker of RCC.

[Serum MiRNA as Predictive and Prognosis Biomarker in Advanced Stage Non-small Cell Lung Cancer in Indonesia].

BACKGROUND: Lung cancer is the most common cause of death in men in the world and in Indonesia where non-small cell carcinoma lung cancer (NSCLC) constitutes 85% of all lung cancer cases. The high mortality rate is due to a poor prognosis and is often diagnosed as having advanced stages. If it is known at the initial stage, the prognosis of lung cancer will be better. Prognosis can be predicted with a marker of prognostic biology, one of which is micro RNA (miRNA). This study aims to prove that serum miRNA can be predictive biological marker and prognosis in NSCLC patients in Indonesia. METHODS: This study was cohort retrospective among 52 subjects in "Dharmais" Hospital National Cancer Center. Sample was obtained from patients' serum. MiR-34, miR-148, miR-155 and miR-222 serum are measured through Real-Time PCR (qPCR). Data were analyzed and interpreted with descriptive analysis, bivariate analysis (Mann Whitney-U for two type of variables or Kruskal-Wallis for more than two type of variables. Kaplan-Meier analysis was used to know association between characteristic which are sociodemographic, performance status, clinico-pathology, and survival rate in miRNA expression. RESULTS: From this study, miRNA expression: miR-34 (46.15%), miR-148 (23.08%), miR-155 (40.38%) and miR-222 (32.69%). Performance status score was statistically significant correlation with miR-148 (P=0.049) and miR-222 (P=0.018). High miR-34 is associated with multiple M1b metastatic type (P=0.020), cancer cell type (adenocarcinoma, P=0.009) and adenocarcinoma epidermal growth factor receptor (EGFR) mutation (negative, P=0.031). There was a significant correlation between the high miR-222 as a poor prognosis in advanced stage NSCLC with M1b metastasis (Median Survival/MS: 27 d, P=0.049) and positive EGFR mutations (MS: 74 d, P=0.049) and correlation of miR-155 with adenocarcinoma (MS: 69 d, P=0.034) and positive EGFR gene mutations (MS: 58 d, P=0.023). CONCLUSIONS: High miR-34 expression in advanced stage NSCLC is the predictive factor for multiple metastatic, adenocarcinoma cell type and adenocarcinoma negative EGFR mutation. High expression of miR-155 and miR-222 are poor prognoses, especially high miR-222 found in metastasis M1b and positive EGFR mutation and miR-155 found in adenocarcinoma and positive EGFR gene mutations. Further studies regarding correlation between miRNA and survival rate are needed.

Circulating microRNA Associated to Different Stages of Liver Steatosis in Prader-Willi Syndrome and Non-Syndromic Obesity.

BACKGROUND: Prader-Willi syndrome (PWS) is a rare and poorly characterized disease. Recent genomic and transcriptomic studies contributed to elucidate the molecular bases of the syndrome. In this study, we characterized the expression of circulating miRNAs in patients with PWS compared to those with non-syndromic obesity in association with liver steatosis. METHODS: MiRNAs were studied by qRT-PCR in serum samples from 30 PWS and 30 non-syndromic obese subjects. RESULTS: MiRNA expression was associated with the presence of the syndrome and to the grade of liver steatosis. MiR-122-5p, miR-151a, miR-92a-3p were up-regulated in obese (4.38-fold, p < 0.01; 2.72-fold, p < 0.05; 1.34-fold p < 0.05, respectively) and were able to differentiate obese from PWS (AUC = 0.81, sens/spec 78/71%). When stratifying groups according to the presence of steatosis, the expression of miR-151a-5p, miR-92a-3p, miR-106b-5p, and miR-93-5p were lower in PWS with steatosis grade 1. Within the group with steatosis grade 1, miR-151a-5p was significantly distinguished PWS from obese (AUC = 0.85, sens/spec 80/85%) and the combination of miR-106b-5p and miR-93-5p showed higher performances in discriminating different grades of steatosis in PWS (AUC = 0.84, sens/spec 93/74%). CONCLUSIONS: MiRNAs represent a tool to better classify and characterize PWS, providing new information about the clinical picture and the extent of steatosis.

Circulating human microRNA biomarkers of oxalic acid-induced acute kidney injury.

Oxalic acid-induced nephrotoxicity and acute kidney injury result from formation of calcium oxalate crystals. Oxalic acid-induced acute kidney injury is a significant problem in many parts of the world. Circulating biomarkers that can accurately and reproducibly detect acute kidney injury are highly desirable. We used a high sensitivity discovery platform to identify signature microRNAs to distinguish healthy individuals never exposed to oxalic acid (n = 4) from those who were exposed to oxalic acid but had no injury (NOAKI; n = 4), moderate injury (AKIN2; n = 4) or severe injury (AKIN3; n = 4). Longitudinal analyses identified 4-8 h post-ingestion as the best time to detect AKIN2/3. We validated a signature of 53 microRNAs identified in the discovery, in a second cohort of individuals exposed to oxalic acid (NOAKI = 11, AKIN2 = 8 and AKIN3 = 18) and healthy controls (n = 19). Thirteen microRNAs were significantly downregulated in acute kidney injury patients compared to NOAKI within 8-h post-ingestion. Five microRNAs (miR-20a, miR-92a, miR-93, miR-195, miR-451) had a highly significant correlation with normalized urinary albumin, serum creatinine at 24 h and creatinine clearance. Logistic regression of these microRNAs had AUC-ROC of 0.85 predicting AKIN2/3 and discriminated patients from healthy controls (AUC-ROC = 0.93). mRNA targets of these microRNAs identified oxidative stress pathways of nephrotoxicity in proximal tubule and glomeruli nephrotoxicity. In conclusion, the downregulation of multiple circulating microRNAs in patients correlated with the severity of oxalic acid-induced acute kidney injury. A set of microRNAs (miR-20a, miR-92a, miR-93, miR-195, miR-451) could be promising biomarkers for early detection of oxalic acid-induced acute kidney injury.

Serum miR-1290 and miR-1246 as Potential Diagnostic Biomarkers of Human Pancreatic Cancer.

Background: Pancreatic cancer (PC) is a highly malignant tumor with no effective early diagnostic biomarkers. This study was performed to screen and identify serum microRNAs (miRNAs) as noninvasive biomarkers for PC diagnosis. Methods: Two upregulated miRNAs were selected by integrated analysis of three independent GEO datasets. Then, the expressions of two miRNAs in serum were determined by quantitative reverse-transcription PCR among 120 PC patients, 40 benign disease controls and 40 healthy controls. The correlation between serum miRNAs and clinical characteristics was analyzed. The diagnostic utility of miRNAs was compared to CA19-9 using receiver operating characteristic curve analysis. Results: We discovered miR-1290 and miR-1246 were upregulated in PC patients through GEO datasets analysis. Serum miR-1290 and miR-1246 expression levels were elevated in PC patients compared to all controls and dramatically decreased after tumor resection (all P<0.001). The area under the curve (AUC) for miR-1290 was larger than miR-1246 and CA19-9 (miR-1290: 0.91; miR-1246: 0.81; CA19-9: 0.82). The combined diagnosis of individual or both miRNAs with CA19-9 was more effective for discriminating PC from all controls than the single CA19-9 assay (miR-1290+CA19-9: 0.96, miR-1246+CA19-9: 0.93, miR-1290+miR-1246+CA19-9: 0.97). The abundance of serum miR-1290 and miR-1246 was associated with tumor stage and size respectively and logistic modeling proved that both of them were independent risk factors for PC. Conclusion: Serum miR-1290 and miR-1246 might be promising biomarkers for PC diagnosis and the combined detection of CA19-9, together with miR-1290 or miR-1246, could improve the diagnostic accuracy of PC.