Identification and bioinformatic characterization of a serum miRNA signature for early detection of laryngeal squamous cell carcinoma.

BACKGROUND: The growing understanding of cancer biology and the establishment of new treatment modalities has not yielded the expected results in terms of survival for Laryngeal Squamous Cell Cancer (LSCC). Early diagnosis, as well as prompt identification of patients with high risk of relapse would ensure greater chance of therapeutic success. However, this goal remains a challenge due to the absence of specific biomarkers for this neoplasm. METHODS: Serum samples from 45 LSCC patients and 23 healthy donors were collected for miRNA expression profiling by TaqMan Array analysis. Additional 20 patients and 42 healthy volunteers were included for the validation set, reaching an equal number of clinical samples for each group. The potential diagnostic ability of the such identified three-miRNA signature was confirmed by ROC analysis. Moreover, each miRNA was analyzed for the possible correlation with HNSCC patients' survival and TNM status by online databases Kaplan-Meier (KM) plotter and OncomiR. In silico analysis of common candidate targets and their network relevance to predict shared biological functions was finally performed by PANTHER and GeneMANIA software. RESULTS: We characterized serum miRNA profile of LSCC patients identifying a novel molecular signature, including miR-223, miR-93 and miR-532, as circulating marker endowed with high selectivity and specificity. The oncogenic effect and the prognostic significance of each miRNA was investigated by bioinformatic analysis, denoting significant correlation with OS. To analyse the molecular basis underlying the pro-tumorigenic role of the signature, we focused on the simultaneously regulated gene targets-IL6ST, GTDC1, MAP1B, CPEB3, PRKACB, NFIB, PURB, ATP2B1, ZNF148, PSD3, TBC1D15, PURA, KLF12-found by prediction tools and deepened for their functional role by pathway enrichment analysis. The results showed the involvement of 7 different biological processes, among which inflammation, proliferation, migration, apoptosis and angiogenesis. CONCLUSIONS: In conclusion, we have identified a possible miRNA signature for early LSCC diagnosis and we assumed that miR-93, miR-223 and miR-532 could orchestrate the regulation of multiple cancer-related processes. These findings encourage the possibility to deepen the molecular mechanisms underlying their oncogenic role, for the desirable development of novel therapeutic opportunities based on the use of short single-stranded oligonucleotides acting as non-coding RNA antagonists in cancer.

miRNA-Seq Tissue Diagnostic Signature: A Novel Model for NSCLC Subtyping.

Non-small cell lung cancer (NSCLC) encompasses distinct histopathological subtypes, namely adenocarcinoma (AC) and squamous cell lung carcinoma (SCC), which require precise differentiation for effective treatment strategies. In this study, we present a novel molecular diagnostic model that integrates tissue-specific expression profiles of microRNAs (miRNAs) obtained through next-generation sequencing (NGS) to discriminate between AC and SCC subtypes of NSCLC. This approach offers a more comprehensive and precise molecular characterization compared to conventional methods such as histopathology or immunohistochemistry. Firstly, we identified 31 miRNAs with significant differential expression between AC and SCC cases. Subsequently, we constructed a 17-miRNA signature through rigorous multistep analyses, including LASSO/elastic net regression. The signature includes both upregulated miRNAs (hsa-miR-326, hsa-miR-450a-5p, hsa-miR-1287-5p, hsa-miR-556-5p, hsa-miR-542-3p, hsa-miR-30b-5p, hsa-miR-4728-3p, hsa-miR-450a-1-3p, hsa-miR-375, hsa-miR-147b, hsa-miR-7705, and hsa-miR-653-3p) and downregulated miRNAs (hsa-miR-944, hsa-miR-205-5p, hsa-miR-205-3p, hsa-miR-149-5p, and hsa-miR-6510-3p). To assess the discriminative capability of the 17-miRNA signature, we performed receiver operating characteristic (ROC) curve analysis, which demonstrated an impressive area under the curve (AUC) value of 0.994. Our findings highlight the exceptional diagnostic performance of the miRNA signature as a stratifying biomarker for distinguishing between AC and SCC subtypes in lung cancer. The developed molecular diagnostic model holds promise for providing a more accurate and comprehensive molecular characterization of NSCLC, thereby guiding personalized treatment decisions and improving clinical management and prognosis for patients.

Myocardial RNA Sequencing Reveals New Potential Therapeutic Targets in Heart Failure with Preserved Ejection Fraction.

Heart failure with preserved ejection fraction (HFpEF) represents a global health challenge, with limited therapies proven to enhance patient outcomes. This makes the elucidation of disease mechanisms and the identification of novel potential therapeutic targets a priority. Here, we performed RNA sequencing on ventricular myocardial biopsies from patients with HFpEF, prospecting to discover distinctive transcriptomic signatures. A total of 306 differentially expressed mRNAs (DEG) and 152 differentially expressed microRNAs (DEM) were identified and enriched in several biological processes involved in HF. Moreover, by integrating mRNA and microRNA expression data, we identified five potentially novel miRNA-mRNA relationships in HFpEF: the upregulated hsa-miR-25-3p, hsa-miR-26a-5p, and has-miR4429, targeting HAPLN1; and NPPB mRNA, targeted by hsa-miR-26a-5p and miR-140-3p. Exploring the predicted miRNA-mRNA interactions experimentally, we demonstrated that overexpression of the distinct miRNAs leads to the downregulation of their target genes. Interestingly, we also observed that microRNA signatures display a higher discriminative power to distinguish HFpEF sub-groups over mRNA signatures. Our results offer new mechanistic clues, which can potentially translate into new HFpEF therapies.

Diesel exhaust particles exposure induces liver dysfunction: Exploring predictive potential of human circulating microRNAs signature relevant to liver injury risk.

Diesel exhaust particles (DEP) pollution should be taken seriously because it is an extensive environmental and occupational health concern. Exploring early effect biomarkers is crucial for monitoring and managing DEP-associated health risk assessment. Here, we found that serum levels of 67 miRNAs were dysregulated in DEP exposure group. Notably, 20 miRNAs were identified as each having a significant dose-response relationship with the internal exposure level of DEP. Further, we revealed that the DEP exposure could affect the liver function of subjects and that 7 miRNAs (including the well-known liver injury indicator, miR-122-5p) could serve as the novel epigenetic-biomarkers (epi-biomarkers) to reflect the liver-specific response to the DEP exposure. Importantly, an unprecedented prediction model using these 7 miRNAs was established for the assessment of DEP-induced liver injury risk. Finally, bioinformatic analysis indicated that the unique set of miRNA panel in serum might also contribute to the molecular mechanism of DEP exposure-induced liver damage. These results broaden our understanding of the adverse health outcomes of DEP exposure. Noteworthy, we believe this study could shed light on roles and functions of epigenetic biomarkers from environmental exposure to health outcomes by revealing the full chain of exposure-miRNAs-molecular pathways-disease evidence.

Survival associated miRNA signature in patients with head and neck carcinomas.

Head and neck carcinoma (HNSC) is often diagnosed at advanced stage, incurring poor patient outcome. Despite of advances in chemoradiation and surgery approaches, limited improvements in survival rates of HNSC have been observed over the last decade. Accumulating evidences have demonstrated the importance of microRNAs (miRNAs) in carcinogenesis. In this context, we sought to identify a miRNA signature associated with the survival time in patients with HNSC. This study proposed a survival estimation method called HNSC-Sig that identified a miRNA signature consists of 25 miRNAs associated with the survival in 133 patients with HNSC. HNSC-Sig achieved 10-fold cross validation a mean correlation coefficient and a mean absolute error of 0.85 ± 0.01 and 0.46 ± 0.02 years, respectively, between actual and estimated survival times. The survival analysis revealed that five miRNAs, hsa-miR-3605-3p, hsa-miR-629-3p, hsa-miR-3127-5p, hsa-miR-497-5p, and hsa-miR-374a-5p, were significantly associated with prognosis in patients with HNSC. Comparing the relative expression difference of top 10 prioritized miRNAs, eight miRNAs, hsa-miR-629-3p, hsa-miR-3127-5p, hsa-miR-221-3p, hsa-miR-501-5p, hsa-miR-491-5p, hsa-miR-149-3p, hsa-miR-3934-5p, and hsa-miR-3170, were significantly expressed between cancer and normal groups. In addition, biological relevance, disease association, and target interactions of the miRNA signature were discussed. Our results suggest that identified miRNA signature have potential to serve as biomarker for diagnosis and clinical practice in HNSC.

Longitudinal large-scale changes in maternal circulating microRNAs associated with gestation-related compartments, fetal sex, and growth during and post-pregnancy.

Circulating microRNAs (c-miRNAs) during pregnancy could provide information regarding the functional status of the mother and fetus. However, it remains unclear which pregnancy-related processes are actually reflected by changes c-miRNAs. Here, we used large-scale c-miRNA profiling of maternal plasma during and post-pregnancy, and compared it with that of non-pregnant women. Fetal growth measurements and fetal sex data were used to identify associated changes in these transcripts. Surprisingly, c-miRNA subpopulations with prominent expression in maternal/fetal compartments (placenta, amniotic fluid, umbilical cord plasma and breast milk) were found to be under-expressed in circulation throughout pregnancy relative to non-pregnant plasma profiles. Furthermore, we found a bias in global c-miRNA expression in association with fetal sex right from the first trimester, in addition to a specific c-miRNA signature of fetal growth. Our results demonstrate the existence of specific temporal changes in c-miRNA populations associated with specific pregnancy-related compartments and processes, including fetal sex, and growth.

Dysregulation of miR-155 Expression in Professional Mixed Martial Arts (MMA) Fighters.

Psychological and physical stress can induce dysregulation of gene expression via changes in DNA methylation and microRNA (miRNA) expression. Such epigenetic modifications are yet to be investigated in professional Mixed Martial Arts (MMA) fighters subject to highly stressful training involving repetitive head impacts. This study examined differences in DNA methylation and miRNA expression in elite MMA fighters compared to active controls. Global methylation differences between groups were assessed via a LINE-1 assay. At the same time, PCR arrays were used to estimate differential expression in samples of 21 fighters and 15 controls for 192 different miRNAs associated with inflammatory diseases. An Independent-Samples t-Test found no significant difference in LINE-1 methylation between groups. However, an Independent-Samples Mann-Whitney U Test revealed a significant upregulation in the expression of miR-155 in MMA fighter plasma. Since miR-155 has been recognized as an important regulator of neuroinflammation, this dysregulation suggests a possible epigenetic mechanism responsible for chronic inflammation associated with professional-level MMA training. Consistent with other published works, this study highlights the potential of miR-155 not only as a biomarker for monitoring long-term health risks linked to head trauma but also as a target to remediate the impact of chronic neuroinflammation.

Computational analysis of a microRNA signature for poor prognosis suggests a microRNA-controlled stemness pathway in paediatric acute leukaemia.

Esperanza-Cebollada E., et al. found a group of 24 microRNAs, to be differentially expressed between two groups of paediatric acute myeloid leukaemia (AML) cases with distinct outcomes. The main target of this microRNA signature is SOCS2, a gene that controls stemness. The results of this study may open doors for further investigation of the role for microRNAs in poor prognostic paediatric AML. Commentary on: Esperanza-Cebollada et al. A miRNA signature related to stemness identifies high-risk patients in paediatric acute myeloid leukaemia. Br J Haematol 2023;202:96-110.

Endometriosis-associated infertility diagnosis based on saliva microRNA signatures.

RESEARCH QUESTION: Can a saliva-based miRNA signature for endometriosis-associated infertility be designed and validated by analysing the human miRNome? DESIGN: The prospective ENDOmiARN study (NCT04728152) included 200 saliva samples obtained between January 2021 and June 2021 from women with pelvic pain suggestive of endometriosis. All patients underwent either laparoscopy, magnetic resonance imaging, or both. Patients diagnosed with endometriosis were allocated to one of two groups according to their fertility status. Data analysis consisted of identifying a set of miRNA biomarkers using next-generation sequencing, and development of a saliva-based miRNA signature of infertility among patients with endometriosis based on a random forest model. RESULTS: Among the 153 patients diagnosed with endometriosis, 24% (n = 36) were infertile and 76% (n = 117) were fertile. Small RNA-sequencing of the 153 saliva samples yielded approximately 3712 M raw sequencing reads (from ∼13.7 M to ∼39.3 M reads/sample). Of the 2561 known miRNAs, the feature selection method generated a signature of 34 miRNAs linked to endometriosis-associated infertility. After validation, the most accurate signature model had a sensitivity, specificity and area under the curve of 100%. CONCLUSION: A saliva-based miRNA signature for endometriosis-associated infertility is reported. Although the results still require external validation before using the signature in routine practice, this non-invasive tool is likely to have a major effect on care provided to women with endometriosis.

Saliva microRNA signature to diagnose endometriosis: A cost-effectiveness evaluation of the Endotest®.

OBJECTIVE: To evaluate a saliva diagnostic test (Endotest®) for endometriosis compared with the conventional algorithm. DESIGN: A cost-effectiveness analysis with a decision-tree model based on literature data. SETTING: France. POPULATION: Women with chronic pelvic pain. METHODS: Strategy I is the French algorithm, representing the comparator. For strategy II, all patients have an Endotest®. For strategy III, patients undergo ultrasonography to detect endometrioma and patients with no endometrioma detected have an Endotest®. For strategy IV, patients with no endometrioma detected on ultrasonography undergo pelvic magnetic resonance imaging (MRI) to detect endometrioma and/or deep endometriosis. An Endotest® is then performed for patients with a negative result on MRI. MAIN OUTCOMES MEASURES: Costs and accuracy rates and incremental cost-effectiveness ratios (ICERs). Three analyses were performed with an Endotest® priced at €500, €750, and €1000. Probabilistic sensitivity analysis was conducted with Monte Carlo simulations. RESULTS: With an Endotest® priced at €750, the cost per correctly diagnosed case was €1542, €990, €919 and €1000, respectively, for strategies I, II, III and IV. Strategy I was dominated by all other strategies. Strategies IV, III and II were, respectively, preferred for a willingness-to-pay threshold below €473, between €473 and €4670, and beyond €4670 per correctly diagnosed case. At a price of €500 per Endotest®, strategy I was dominated by all other strategies. At €1000, the ICERs of strategies II and III were €724 and €387 per correctly diagnosed case, respectively, compared with strategy I. CONCLUSION: The present study demonstrates the value of the Endotest® from an economic perspective.

Downregulated miR-367-3p, miR-548aq-5p, and miR-4710 in Human Whole Blood: Potential Biomarkers for Breast Cancer With Axillary Lymph Node Metastasis.

BACKGROUND: Increasing studies have shown that microRNAs (miRNAs) have great diagnostic value in cancer. Axillary lymph node metastasis (ALNM) is closely related to the prognosis of breast cancer. However, it remains unknown whether miRNAs in whole blood could be promising biomarkers in breast cancer ALNM. METHODS: An miRNA microarray was used to screen potential differentially expressed miRNA candidates in whole blood of three breast cancer patients with ALNM and three without ALNM. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect candidate differentially expressed miRNAs in the whole blood of 109 breast cancer patients. Furthermore, bioinformatics analysis was carried to predict the potential targets and enriched pathway of miRNAs. RESULTS: QRT-PCR validated the fact that miR-367-3p, miR-548aq-5p and miR-4710 are downregulated in breast cancer with ALNM compared to it without ALNM. Receiver operating characteristic (ROC) curve analysis revealed that miR-367-3p, miR-548aq-5p and miR-4710 have good diagnostic values. Notably, the three-miRNA signature showed better predictive value, with an area under ROC curve (AUC) of 0.7414. Bioinformatics analysis revealed that the miRNAs could participate in a complex network and thus be involved in cancer-related pathways. CONCLUSIONS: Our findings support the potential of miR-367-3p, miR-548aq-5p and miR-4710 and the three-miRNA signature as biomarkers for breast cancer with ALNM.

Survival estimation in patients with stomach and esophageal carcinoma using miRNA expression profiles.

Identifying a miRNA signature associated with survival will open a new window for developing miRNA-targeted treatment strategies in stomach and esophageal cancers (STEC). Here, using data from The Cancer Genome Atlas on 516 patients with STEC, we developed a Genetic Algorithm-based Survival Estimation method, GASE, to identify a miRNA signature that could estimate survival in patients with STEC. GASE identified 27 miRNAs as a survival miRNA signature and estimated the survival time with a mean squared correlation coefficient of 0.80 ± 0.01 and a mean absolute error of 0.44 ± 0.25 years between actual and estimated survival times, and showed a good estimation capability on an independent test cohort. The miRNAs of the signature were prioritized and analyzed to explore their roles in STEC. The diagnostic ability of the identified miRNA signature was analyzed, and identified some critical miRNAs in STEC. Further, miRNA-gene target enrichment analysis revealed the involvement of these miRNAs in various pathways, including the somatotrophic axis in mammals that involves the growth hormone and transforming growth factor beta signaling pathways, and gene ontology annotations. The identified miRNA signature provides evidence for survival-related miRNAs and their involvement in STEC, which would aid in developing miRNA-target based therapeutics.

An Exosome-based Transcriptomic Signature for Noninvasive, Early Detection of Patients With Pancreatic Ductal Adenocarcinoma: A Multicenter Cohort Study.

BACKGROUND & AIMS: Pancreatic ductal adenocarcinoma (PDAC) incidence is rising worldwide, and most patients present with an unresectable disease at initial diagnosis. Measurement of carbohydrate antigen 19-9 (CA19-9) levels lacks adequate sensitivity and specificity for early detection; hence, there is an unmet need to develop alternate molecular diagnostic biomarkers for PDAC. Emerging evidence suggests that tumor-derived exosomal cargo, particularly micro RNAs (miRNAs), offer an attractive platform for the development of cancer-specific biomarkers. Herein, genomewide profiling in blood specimens was performed to develop an exosome-based transcriptomic signature for noninvasive and early detection of PDAC. METHODS: Small RNA sequencing was undertaken in a cohort of 44 patients with an early-stage PDAC and 57 nondisease controls. Using machine-learning algorithms, a panel of cell-free (cf) and exosomal (exo) miRNAs were prioritized that discriminated patients with PDAC from control subjects. Subsequently, the performance of the biomarkers was trained and validated in independent cohorts (n = 191) using quantitative reverse transcription polymerase chain reaction (qRT-PCR) assays. RESULTS: The sequencing analysis initially identified a panel of 30 overexpressed miRNAs in PDAC. Subsequently using qRT-PCR assays, the panel was reduced to 13 markers (5 cf- and 8 exo-miRNAs), which successfully identified patients with all stages of PDAC (area under the curve [AUC] = 0.98 training cohort; AUC = 0.93 validation cohort); but more importantly, was equally robust for the identification of early-stage PDAC (stages I and II; AUC = 0.93). Furthermore, this transcriptomic signature successfully identified CA19-9 negative cases (<37 U/mL; AUC = 0.96), when analyzed in combination with CA19-9 levels, significantly improved the overall diagnostic accuracy (AUC = 0.99 vs AUC = 0.86 for CA19-9 alone). CONCLUSIONS: In this study, an exosome-based liquid biopsy signature for the noninvasive and robust detection of patients with PDAC was developed.

Identification of a six-microRNA signature as a potential diagnostic biomarker in breast cancer tissues.

BACKGROUND: Breast cancer (BC) is by far the most common malignancy among women. Epigenetic modulators, microRNAs in particular, may set stages for BC development and its progression. Herein, we aimed to assess the diagnostic potentiality of a signature of six miRNAs (i.e., hsa-miR-25-3p, -29a-5p, -105-3p, -181b1-5p, -335-5p, and -339-5p) in BC and adjacent non-tumor tissues. METHODS: A pair of 50 tumor and adjacent non-tumor samples were taken from BC patients. The expression of each candidate miRNA was measured using quantitative reverse transcription PCR. To investigate the possible roles of each miRNA and their impressions on BC prognosis, in silico tools were used. Receiver operating characteristic (ROC) curves were performed to determine the diagnostic accuracy of each miRNA and the possible association of their expression with clinicopathological characteristics was analyzed. RESULTS: Our findings showed the upregulation of hsa-miR-25-3p, -29a-5p, -105-3p, and -181b1-5p, and the downregulation of hsa-miR-335-5p and -339-5p in BC tumor compared to corresponding adjacent tissues. Except for hsa-miR-339-5p, the up-/down-regulation of the candidate miRNAs was associated with TNM stages. Except for hsa-miR-105-3p, each candidate miRNA was correlated with HER-2 status. ROC curve analysis showed that the signature of six-miRNA is a potential biomarker distinguishing between tumor and non-tumor breast tissue samples. CONCLUSION: We showed that the dysregulation of a novel signature of six-miRNA can be used as a potential biomarker for BC diagnosis.

Integrative Analysis Identified a 6-miRNA Prognostic Signature in Nasopharyngeal Carcinoma.

BACKGROUND: Nasopharyngeal carcinoma (NPC) is an Epstein-Barr virus-associated epithelial malignancy, which is rare in America but endemic in China. The current clinical gold TNM-based standard for prognosis may not be enough. Although some studies have reported that some miRNAs have a prognostic power in NPC, there is a scarcity of independent validation for these miRNAs. METHODS: In this work, we firstly conducted a literature review of all miRNA profiling datasets with survival information, then integrated miRNA expression data across different profiling platforms and built prognostic models using machine learning methods. The Kaplan-Meier method and log-rank tests were applied to estimate correlations of the miRNA signature with survival, and the area under the time-dependent ROC curve (AUC) and concordance index (C-index) were used to assess the predictive power of prognostic models. We also investigated the biological roles of the prognostic miRNAs through identifying their regulated genes and association with immune infiltration. RESULTS: We constructed a prognostic model based on 6-miRNA signature (ebv-miR-BART12, ebv-miR-BART15, miR-29c-3p, miR-30e-5p, hsa-miR-375-3p, has-miR-93-5p) using the elastic net penalized Cox regression model. The AUCs of our model predicting 1-, 3-, and 5-year overall survival rates were 0.90, 0.73, and 0.70 for the external validation dataset and showed better prognostic power than models using previously reported miRNA signatures. The 6-miRNA risk score was an independent prognostic predictor for overall survival (OS), disease-free survival (DFS), and metastasis-free survival (MFS). It could stratify patients into low-risk and high-risk groups; patients in the low-risk group treated with concurrent chemotherapy had a better survival. On the basis that the 6-miRNA risk score improved the current clinical gold standard for prognosis, we built a nomogram integrating both clinical characterizations and the risk score to predict 3-, 5-, and 10-year overall survival. Functional analysis suggested that the six miRNAs mainly play roles in virus infection pathways and oncogenic signaling pathways and associated with B-cell expression. CONCLUSION: We identified a 6-miRNA prognostic signature in nasopharyngeal carcinoma across miRNA profiling platforms and patient geographical difference, which showed good prediction capability in terms of OS, DFS, and MFS. The 6-miRNA risk score might be helpful for clinicians to make treatment strategies and predict patient outcomes.

Identification of miRNA Signature in Breast Cancer to Predict Neoadjuvant Chemotherapy Response.

Background: Chemotherapy failure causes high breast cancer recurrence and poor patient prognosis. Thus, we studied a cohort of novel biomarkers to predict chemotherapeutic response in breast cancer. In this study, miRNA expression profiling was performed on 10 breast cancer punctured specimens sensitive to chemotherapy (MP grade 4, 5) and 10 chemotherapy resistant (MP grade 1). Differentially expressed miRNAs were verified by qRT-PCR in 60 initial samples, 59 validated samples and 71 independent samples. A miRNA signature was generated using a Logistic regression model. A receiver operating characteristic (ROC) test was used to assess specificity and sensitivity of single miRNA and miRNA signature. Target genes regulated by miRNAs and their involved signaling pathways were analyzed using GO enrichment and KEGG software. MiRNAs expression were separately compared with ER, PR, HER2 immunohistochemical staining and different drugs. qRT-PCR showed that the high expression of miR-23a-3p, miR-200c-3p, miR-214-3p and the low expression of miR-451a and miR-638 were closely related to chemoresistance. According to the formula for calculating the drug resistance risk, patients in the high-risk group were more likely to develop chemotherapy resistance than the low-risk group. Bioinformatics analysis showed that 5 miRNAs and target genes are mainly involved in p53, ubiquitin-mediated proteolysis, mTOR, Wnt, cells skeletal protein regulation, cell adhesion and ErbB signaling pathways. miR-451a expression was associated with ER, HER-2 status and anthracyclines. A miRNA signature of chemotherapeutic response may be clinically valuable for improving current chemotherapy regimens of individual treatment for patients with breast cancer.

Identification of a Two-MicroRNA Signature in Plasma as a Novel Biomarker for Very Early Diagnosis of Breast Cancer.

The early diagnosis of breast cancer is essential to improve patients' survival rate. In this context, microRNAs have been described as potential diagnostic biomarkers for breast cancer. Particularly, circulating microRNAs have a strong value as non-invasive biomarkers. Herein, we assessed the potential of a microRNA signature based on miR-30b-5p and miR-99a-5p levels in plasma as a diagnostic biomarker for breast cancer. This two-microRNA signature was constructed by Principal Component Analysis and its prognostic value was assessed in a discovery cohort and blindly validated in a second cohort from an independent institution. ROC curve analysis and biomarker performance parameter evaluation demonstrated that our proposed signature presents a high value as a non-invasive biomarker for very early detection of breast cancer. In addition, pathway enrichment analysis identified three of the well-known pathways involved in cancer as targets of the two microRNAs.

Hallmark microRNA signature in liquid biopsy identifies hepatocellular carcinoma and differentiates it from liver metastasis.

Purpose: This study aims to develop a liquid biopsy assay to identify HCC and differentially diagnose hepatocellular carcinoma (HCC) from colorectal carcinoma (CRC) liver metastasis. Methods: Thirty-two microRNAs ("HallMark-32" panel) were designed to target the ten cancer hallmarks in HCC. Quantitative PCR and supervised machine learning models were applied to develop an HCC-specific diagnostic model. One hundred thirty-three plasma samples from intermediate-stage HCC patients, colorectal cancer (CRC) patients with liver metastasis, and healthy individuals were examined. Results: Six differentially expressed microRNAs ("Signature-Six" panel) were identified after comparing HCC and healthy individuals. The microRNA miR-221-3p, miR-223-3p, miR-26a-5p, and miR-30c-5p were significantly down-regulated in the plasma of HCC samples, while miR-365a-3p and miR-423-3p were significantly up-regulated. Machine learning models combined with HallMark-32 and Signature-Six panels demonstrated promising performance with an AUC of 0.85-0.96 (p ≤ 0.018) and 0.84-0.93 (p ≤ 0.021), respectively. Further modeling improvement by adjusting sample quality variation in the HallMark-32 panel boosted the accuracy to 95% ± 0.01 and AUC to 0.991 (95% CI 0.96-1, p = 0.001), respectively. Even in alpha fetoprotein (AFP)-negative (< 20ng/mL) HCC samples, HallMark-32 still achieved 100% sensitivity in identifying HCC. The Cancer Genome Atlas (TCGA, n=372) analysis demonstrated a significant association between HallMark-32 and HCC patient survival. Conclusion: To the best of our knowledge, this is the first report to utilize circulating miRNAs and machine learning to differentiate HCC from CRC liver metastasis. In this setting, HallMark-32 and Signature-Six are promising non-invasive tests for HCC differential diagnosis and distinguishing HCC from healthy individuals.

Identification of the miRNA signature associated with survival in patients with ovarian cancer.

Ovarian cancer is a major gynaecological malignant tumor associated with a high mortality rate. Identifying survival-related variants may improve treatment and survival in patients with ovarian cancer. In this work, we proposed a support vector regression (SVR)-based method called OV-SURV, which is incorporated with an inheritable bi-objective combinatorial genetic algorithm for feature selection to identify a miRNA signature associated with survival in patients with ovarian cancer. There were 209 patients with miRNA expression profiles and survival information of ovarian cancer retrieved from The Cancer Genome Atlas database. OV-SURV achieved a mean correlation coefficient of 0.77±0.01and a mean absolute error of 0.69±0.02 years using 10-fold cross-validation. Analysis of the top ranked miRNAs revealed that the miRNAs, hsa-let-7f, hsa-miR-1237, hsa-miR-98, hsa-miR-933, and hsa-miR-889, were significantly associated with the survival in patients with ovarian cancer. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that four of these miRNAs, hsa-miR-182, hsa-miR-34a, hsa-miR-342, and hsa-miR-1304, were highly enriched in fatty acid biosynthesis, and the five miRNAs, hsa-let-7f, hsa-miR-34a, hsa-miR-342, hsa-miR-1304, and hsa-miR-24, were highly enriched in fatty acid metabolism. The prediction model with the identified miRNA signature consisting of prognostic biomarkers can benefit therapeutic decision making of ovarian cancer.