Mitochondria-derived small RNAs as diagnostic biomarkers in lung cancer patients through a novel ratio-based expression analysis methodology.

Small non-coding RNAs are potential diagnostic biomarkers for lung cancer. Mitochondria-derived small RNA (mtRNA) is a novel regulatory small non-coding RNA that only recently has been identified and cataloged. Currently, there are no reports of studies of mtRNA in human lung cancer. Currently, normalization methods are unstable, and they often fail to identify differentially expressed small non-coding RNAs (sncRNAs). In order to identify reliable biomarkers for lung cancer screening, we used a ratio-based method using mtRNAs newly discovered in human peripheral blood mononuclear cells. In the discovery cohort (AUC = 0.981) and independent validation cohort (AUC = 0.916) the prediction model of eight mtRNA ratios distinguished lung cancer patients from controls. The prediction model will provide reliable biomarkers that will allow blood-based screening to become more feasible and will help make lung cancer diagnosis more accurate in clinical practice.

mtTB: A Web-Based R/Shiny App for Pulmonary Tuberculosis Screening.

Pulmonary tuberculosis caused by Mycobacterium tuberculosis remains a global issue. However, the diagnosis of active pulmonary tuberculosis (TB) remains a challenge in the clinic. Small non-coding RNAs are potential diagnostic biomarkers for pulmonary tuberculosis. However, the current normalization methods are not stable and usually fail to reliably detect differentially expressed sncRNAs. To identify reliable biomarkers for pulmonary tuberculosis screening, we utilized the ratio-based method on the newly discovered mitochondria-derived small RNAs in human peripheral blood mononuclear cells. The prediction model of seven mtRNA biomarkers noteworthily enables the discrimination between pulmonary tuberculosis patients and controls in discovery (AUC = 0.906, 23 patients) and independent validation cohort (AUC = 0.968, 20 patients). Moreover, we present mtTB (https://tuberculosis.shinyapps.io/mtTB/), a novel R Graphical User Interface (GUI) that provides reliable biomarkers for the feasibility of blood-based screening, and produce a more accurate tool for pulmonary tuberculosis diagnosis in real clinical practice.

The Metabolome of Carbapenem-Resistant Klebsiella pneumoniae Infection in Plasma.

AIM: Carbapenem-resistant Klebsiella pneumoniae- (CR-Kp-) mediated infections represent a challenge for clinical practitioners due to their expanding prevalence in hospital environments and antibiotic resistance. However, few studies have shown metabolic changes of carbapenem-resistant Klebsiella pneumoniae and CR-Kp-negative patients, and relevant studies are urgently needed. METHODS: In this study, we comprehensively profile the metabolites of 20 CR-Kp-positive and 18 CR-Kp-negative patients in plasma by using 2D gas chromatography-time-of-flight mass spectrometry (GC×GC-TOFMS). RESULTS: We identified 58 metabolites that were carbapenem-resistant Klebsiella pneumoniae-associated. N-Acetyl glucosamine, butanedioic acid, and myoinositol play a significant character in CR-Kp infection. CONCLUSIONS: Our study provides valuable data to serve as potential targets for developing therapies against CR-Kp infection.

Development of a tRNA-Derived Small RNA Prognostic Panel and Their Potential Functions in Osteosarcoma.

BACKGROUND: Therapeutic outcomes of osteosarcoma treatment have not significantly improved in several decades. Therefore, strong prognostic biomarkers are urgently needed. METHODS: We first extracted the tRNA-derived small RNA (tsRNA) expression profiles of osteosarcoma from the GEO database. Then, we performed a unique module analysis and use the LASSO-Cox model to select survival-associated tsRNAs. Model effectiveness was further verified using an independent validation dataset. Target genes with selected tsRNAs were predicted using RNAhybrid. RESULTS: A LASSO-Cox model was established to select six prognostic tsRNA biomarkers: tRF-33-6SXMSL73VL4YDN, tRF-32-6SXMSL73VL4YK, tRF-32-M1M3WD8S746D2, tRF-35-RPM830MMUKLY5Z, tRF-33-K768WP9N1EWJDW, and tRF-32-MIF91SS2P46I3. We developed a prognostic panel for osteosarcoma patients concerning their overall survival by high-low risk. Patients with a low-risk profile had improved survival rates in training and validation dataset. CONCLUSIONS: The suggested prognostic panel can be utilized as a reliable biomarker to predict osteosarcoma patient survival rates.

The Value of a Seven-Autoantibody Panel Combined with the Mayo Model in the Differential Diagnosis of Pulmonary Nodules.

BACKGROUND: Identifying malignant pulmonary nodules and detecting early-stage lung cancer (LC) could reduce mortality. This study investigated the clinical value of a seven-autoantibody (7-AAB) panel in combination with the Mayo model for the early detection of LC and distinguishing benign from malignant pulmonary nodules (MPNs). METHODS: The concentrations of the elements of a 7-AAB panel were quantitated by enzyme-linked immunosorbent assay (ELISA) in 806 participants. The probability of MPNs was calculated using the Mayo predictive model. The performances of the 7-AAB panel and the Mayo model were analyzed by receiver operating characteristic (ROC) analyses, and the difference between groups was evaluated by chi-square tests (χ 2). RESULTS: The combined area under the ROC curve (AUC) for all 7 AABs was higher than that of a single one. The sensitivities of the 7-AAB panel were 67.5% in the stage I-II LC patients and 60.3% in the stage III-IV patients, with a specificity of 89.6% for the healthy controls and 83.1% for benign lung disease patients. The detection rate of the 7-AAB panel in the early-stage LC patients was higher than that of traditional tumor markers. The AUC of the 7-AAB panel in combination with the Mayo model was higher than that of the 7-AAB panel alone or the Mayo model alone in distinguishing MPN from benign nodules. For early-stage MPN, the sensitivity and specificity of the combination were 93.5% and 58.0%, respectively. For advanced-stage MPN, the sensitivity and specificity of the combination were 91.4% and 72.8%, respectively. The combination of the 7-AAB panel with the Mayo model significantly improved the detection rate of MPN, but the positive predictive value (PPV) and the specificity were not improved when compared with either the 7-AAB panel alone or the Mayo model alone. CONCLUSION: Our study confirmed the clinical value of the 7-AAB panel for the early detection of lung cancer and in combination with the Mayo model could be used to distinguish benign from malignant pulmonary nodules.

LncRNA TGFB2-AS1 regulates lung adenocarcinoma progression via act as a sponge for miR-340-5p to target EDNRB expression.

Long non-coding RNA TGFB2-antisense RNA1 (TGFB2-AS1) has been reported could regulate tumorigenesis. However, the roles of TGFB2-AS1 in lung adenocarcinoma (LUAD) remain largely unknown. In this work, we aimed to explore the expression levels of TGFB2-AS1 and mechanisms in regulating LUAD progression. Expression level of TGFB2-AS1 in LUAD tissues and normal tissues was analyzed at StarBase. Moreover, its expression in LUAD cells and normal cell was analyzed with quantitative real-time polymerase chain reaction method. Gain- and loss-of-function studies were conducted to analyze the biological roles of TGFB2-AS1 in LUAD. Results indicated TGFB2-AS1 was evidently downregulated in LUAD tissues and cells. Moreover, as analyzed by cell counting kit-8 assay, wound-healing and transwell invasion assays, results revealed TGFB2-AS1 overexpression could suppress proliferation, migration and invasion abilities of LUAD cells in vitro and tumor growth in vivo. In addition, LncBase V2.0 and TargetScan prediction tools showed TGFB2-AS1 and endothelin receptor type B (EDNRB) shares binding site in microRNA-340-5p (miR-340-5p). Furthermore, luciferase activity reporter assay and RT-qPCR assay validated these prediction results. Furthermore, we showed TGFB2-AS1 functions as sponge for miR-340-5p to regulate EDNRB expression. Collectively, our results indicated TGFB2-AS1/miR-340-5p/EDNRB axis plays crucial roles in regulating LUAD progression, indicating TGFB2-AS1 may be a novel therapeutic target for LUAD.

Lack of Efficacy of Combined Carbohydrate Antigen Markers for Lung Cancer Diagnosis.

BACKGROUND: Lung cancer (LC) is top-ranked in cancer incidence and is the leading cause of cancer death globally. Combining serum biomarkers can improve the accuracy of LC diagnosis. The identification of the best potential combination of traditional tumor markers is essential for LC diagnosis. Patients and Methods. Blood samples were collected from 132 LC cases and 118 benign lung disease (BLD) controls. The expression levels of ten serum tumor markers (CYFR21, CEA, NSE, SCC, CA15-3, CA 19-9, CA 125, CA50, CA242, and CA724) were assayed, and that the expression in the levels of tumor markers were evaluated, isolated, and combined in different patients. The performance of the biomarkers was analyzed by receiver operating characteristic (ROC) analyses, and the difference between combinations of biomarkers was compared by Chi-square (χ 2) tests. RESULTS: As single markers, CYFR21 and CEA showed good diagnostic efficacy for nonsmall cell lung cancer (NSCLC) patients, while NSE and CEA were the most sensitive in the diagnosis of small cell lung cancer (SCLC). The area under the curve (AUC) value was 0.854 for the panel of four biomarkers (CYFR21, CEA, NSE, and SCC), 0.875 for the panel of six biomarkers (CYFR21, CEA, NSE, SCC, CA125, and CA15-3), and 0.884 for the panel of ten markers (CYFR21, CEA, NSE, SCC, CA125, CA15-3, CA19-9, CA50, CA242, and CA724). With a higher sensitivity and negative predictive value (NPV), the diagnostic accuracy of the three panels was better than that of any single biomarker, but there were no statistically significant differences among them (all P values > 0.05). However, the panel of six carbohydrate antigen (CA) biomarkers (CA125, CA15-3, CA19-9, CA50, CA242, and CA724) showed a lower diagnostic value (AUC: 0.776, sensitivity: 59.8%, specificity: 73.0%, and NPV: 60.4%) than the three panels (P value < 0.05). The performance was similar even when analyzed individually by LC subtypes. CONCLUSION: The biomarkers isolated are elevated for different types of lung cancer, and the panel of CYFR21, CEA, NSE, and SCC seems to be a promising serum biomarker for the diagnosis of lung cancer, while the combination with carbohydrate antigen markers does not improve the diagnostic efficacy.

Serum tumor-associated autoantibodies as diagnostic biomarkers for lung cancer: A systematic review and meta-analysis.

OBJECTIVE: We performed a comprehensive review and meta-analysis to evaluate the diagnostic values of serum single and multiplex tumor-associated autoantibodies (TAAbs) in patients with lung cancer (LC). METHODS: We searched the MEDLINE and EMBASE databases for relevant studies investigating serum TAAbs for the diagnosis of LC. The primary outcomes included sensitivity, specificity and accuracy of the test. RESULTS: The systematic review and meta-analysis included 31 articles with single autoantibody and 39 with multiplex autoantibodies. Enzyme-linked immunosorbent assay (ELISA) was the most common detection method. For the diagnosis of patients with all stages and early-stage LC, different single or combinations of TAAbs demonstrated different diagnostic values. Although individual TAAbs showed low diagnostic sensitivity, the combination of multiplex autoantibodies offered relatively high sensitivity. For the meta-analysis of a same panel of autoantibodies in patients at all stages of LC, the pooled results of the panel of 6 TAAbs (p53, NY-ESO-1, CAGE, GBU4-5, Annexin 1 and SOX2) were: sensitivity 38% (95% CI 0.35-0.40), specificity 89% (95% CI 0.86-0.91), diagnostic accuracy 65.9% (range 62.5-81.8%), AUC 0.52 (0.48-0.57), while the summary estimates of 7 TAAbs (p53, CAGE, NY-ESO-1, GBU4-5, SOX2, MAGE A4 and Hu-D) were: sensitivity 47% (95% CI 0.34-0.60), specificity 90% (95% CI 0.89-0.92), diagnostic accuracy 78.4% (range 67.5-88.8%), AUC 0.90 (0.87-0.93). For the meta-analysis of the same panel of autoantibodies in patients at early-stage of LC, the sensitivities of both panels of 7 TAAbs and 6 TAAbs were 40% and 29.7%, while their specificities were 91% and 87%, respectively. CONCLUSIONS: Serum single or combinations of multiplex autoantibodies can be used as a tool for the diagnosis of LC patients at all stages or early-stage, but the combination of multiplex autoantibodies shows a higher detection capacity; the diagnostic value of the panel of 7 TAAbs is higher than the panel of 6 TAAbs, which may be used as potential biomarkers for the early detection of LC.

Lack of efficacy of nebulized magnesium sulfate in treating adult asthma: A meta-analysis of randomized controlled trials.

BACKGROUND: Nebulized magnesium sulfate (MgSO4) has been used to treat asthma, but the efficacy remains controversial. We aimed to comprehensively review the efficacy of nebulized MgSO4 in treating adult patients with asthma. METHODS: PubMed, Embase, and Cochrane Library were searched for relevant studies published up to July 18, 2016. Randomized controlled trials (RCTs) were included if adult patients with acute or stable asthma had been treated with nebulized MgSO4 compared with placebo or another bronchodilator. Standardized mean differences (SMDs), relative risks (RRs) and 95% confidence intervals (CIs) were calculated. Outcomes included pulmonary function, hospital admission and adverse events. RESULTS: A total of 1386 patients from sixteen trials (1240 acute asthma patients and 146 stable asthma patients) were subjected to meta-analysis. Compared to placebo as normal saline, whether using in acute or stable adult asthma, nebulized MgSO4 did not significantly improve the respiratory function: SMD 0.39 (95% CI -0.03-0.82, P = 0.07), and 1.48 (95% CI -0.14-3.11, P = 0.07), respectively. Furthermore, nebulized MgSO4 did not reduce hospital admission in adult patients with acute asthma (RR, 0.72; 95% CI, 0.52-1.00; P = 0.05), although it was not associated with increased adverse events (RR 1.15; 95% CI, 0.88-1.52; P = 0.31). CONCLUSIONS: Evidence to date suggests that nebulized MgSO4 has no role in the management of adult patients with acute or stable asthma.

Prognostic Value of Pleural Lavage Cytology in Patients with Lung Cancer Resection: An Updated Meta-Analysis.

OBJECTIVE: Pleural lavage cytology (PLC) is considered as a possible tool for assessing prognosis of lung cancer patients. We aimed to comprehensively review the prognosis value of PLC in patients undergoing surgical resection. METHODS: We searched 4 electronic databases for relevant studies comparing positive PLC and negative PLC. The primary outcomes included survival rate and recurrence rate at maximum follow-up. RESULTS: The meta-analysis included 28 studies, with a total of 20,714 patients. For the overall survival rate of all stages, the results demonstrated that positive pre-resection, post-resection and pooled PLC were associated with unfavorable survival: hazard ratio (HR) 2.89 (95% confidence interval [CI] 2.48-3.37), 2.70 (1.90-3.83), and 2.89 (2.52-3.31), respectively. For the stage I survival rate, the combined results also suggested that positive pre-resection, post-resection and pooled PLC were associated with unfavorable survival: HR 3.29 (95% CI 2.55-4.25), 4.85 (2.31-10.20), and 3.16 (2.53-3.94), respectively. Furthermore, a meta-analysis of 14 studies included 14,279 patients showed that positive pre-resection, post-resection and pooled PLC were associated with an increased risk of overall recurrence: risk ratio (RR) 2.45 (95% CI 1.91-3.15), 2.37 (1.11-5.09), and 2.37 (95% CI 2.00-2.80), respectively. Positive PLC was also associated with a high pleural recurrence (RR 4.77; 95% CI 3.13-7.26) or distant recurrence (RR 2.33; 95% CI 1.65-3.29). CONCLUSIONS: Both positive pre- resection and post-resection PLC are associated with not only higher tumor recurrence but also unfavorable survival outcomes in patients with lung cancer resection. This technique can therefore act as a strong prognostic factor for tumor recurrence and adverse survival rates.