Characterization of plasma proteins in children of different Mycobacterium tuberculosis infection status using label-free quantitative proteomics

The Common miRNAs between Tuberculosis and Non-Small Cell Lung Cancer: A Critical Review

Tuberculosis (TB) and non-small cell lung cancer (NSCLC) are two major contributors to mortality and morbidity worldwide. In this regard, TB and NSCLC have similar symptoms, and TB has symptoms that are identical to malignancy; therefore, sometimes it is mistakenly diagnosed as lung cancer. Moreover, patients with active pulmonary TB are at a higher risk of dying due to lung cancer. In addition, several signaling pathways involved in TB and NSCLC have been identified. Also, the miRNAs are biological molecules shown to play essential roles in the above-mentioned diseases through targeting the signaling pathways' genes. Most of the pathways affected by miRNAs are immune responses such as autophagy and apoptosis in TB and NSCLC, respectively. Several studies have separately investigated the expression of miRNAs profile in patients with NSCLC and infectious TB. In this critical review, we attempted to gather common miRNAs between TB and NSCLC and to explain the involved-pathways, which are affected by miRNAs in both TB and NSCLC. Results of this critical review show that the expressions of miR-155, miR-146a, miR-125b, miR-30a, miR-29a, and miR-Let7 have significantly changed in TB and NSCLC. The data suggest that miRNAs expression may provide a new method for screening or differential diagnosis of NSCLC and TB.

Pediatric Tuberculosis: The Impact of "Omics" on Diagnostics Development

Tuberculosis (TB) is a major public health concern for all ages. However, the disease presents a larger challenge in pediatric populations, partially owing to the lack of reliable diagnostic standards for the early identification of infection. Currently, there are no biomarkers that have been clinically validated for use in pediatric TB diagnosis. Identification and validation of biomarkers could provide critical information on prognosis of disease, and response to treatment. In this review, we discuss how the “omics” approach has influenced biomarker discovery and the advancement of a next generation rapid point-of-care diagnostic for TB, with special emphasis on pediatric disease. Limitations of current published studies and the barriers to their implementation into the field will be thoroughly reviewed within this article in hopes of highlighting future avenues and needs for combating the problem of pediatric tuberculosis.

Aging increases the systemic molecular degree of inflammatory perturbation in patients with tuberculosis

Tuberculosis (TB) is a chronic infection that can affect individuals of all ages. The description of determinants of immunopathogenesis in TB is of tremendous interest due to the perspective of finding a reliable host-directed therapy to reduce disease burden. The association between specific biomarker profiles related to inflammation and the diverse clinical disease presentations in TB has been extensively studied in adults. However, relatively scarce data on profiling the inflammatory responses in pediatric TB are available. Here, we employed the molecular degree of perturbation (MDP) score adapted to plasma biomarkers in two distinct databanks from studies that examined either adults or children presenting with pulmonary or extrapulmonary disease. We used multidimensional statistical analyses to characterize the impact of age on the overall changes in the systemic inflammation profiles in subpopulation of TB patients. Our findings indicate that TB results in significant increases in molecular perturbation, with the highest values being detected in adult patients. Furthermore, there were unique differences in the biomarker perturbation patterns and the overall degree of inflammation according to disease site and age. Importantly, the molecular degree of perturbation was not influenced by sex. Our results revealed that aging is an important determinant of the differences in quality and magnitude of systemic inflammatory perturbation in distinct clinical forms of TB.

Label-Free Quantitative Proteomics Identifies Novel Biomarkers for Distinguishing Tuberculosis Pleural Effusion from Malignant Pleural Effusion

PURPOSE

To identify potential protein biomarkers for distinguishing tuberculosis plural effusion (TBPE) from malignant plural effusion (MPE).

EXPERIMENTAL DESIGN

Five independent samples from each group (TBPE and MPE) are enrolled for label-free quantitative proteomics analyses. The differentially expressed proteins are validated by western blot and ELISA. Logistic regression analysis is used to obtain the optimal diagnostic model.

RESULTS

In total, 14 proteins with significant difference are identified between TBPE and MPE. Seven differentially expressed proteins are validated using western blot, and the expression patterns of these seven proteins are similar with those in proteomics analysis. Statistically significant differences in four proteins (AGP1, ORM2, C9, and SERPING1) are noted between TBPE and MPE in the training set (n = 230). Logistic regression analysis shows the combination of AGP1-ORM2-C9 presents a sensitivity of 73.0% (92/126) and specificity of 89.4% (93/104) in discriminating TBPE from MPE. Additional validation is performed to evaluate the diagnostic model in an independent blind testing set (n = 80), and yielded a sensitivity of 74.4% (32/43) and specificity of 91.9% (34/37) in discriminating TBPE from MPE.

CONCLUSION

The study uncovers the proteomic profiles of TBPE and MPE, and provides new potential diagnostic biomarkers for distinguishing TBPE from MPE.

Plasma proteomics and the paediatric patient

INTRODUCTION

Plasma proteomics has been extensively utilized for studies that investigate various disease settings (e.g. cardiovascular disease), as well as to monitor the effect of pharmaceuticals on the plasma proteome (e.g. chemotherapy). However, plasma proteomic studies focusing on children represent a very small proportion of the plasma proteomic studies completed to date. Early disease detection and prevention is critical in pediatrics, as children must live with the disease outcomes for many years and often carry negative outcomes into adulthood. Pediatrics represents an area of plasma proteomics that is about to undergo a significant expansion. Areas covered: This review is based on a PubMed search focusing on five keywords that are plasma, biomarkers, pediatric, proteomics, and children. It is a comprehensive summary of plasma proteomic studies specific to the pediatric patient and discusses aspects such as the clinical setting, sample size, methodological approaches and outlines the significance of the findings. Expert commentary: Plasma proteomics is expanding significantly as a result of major advancements in proteomic technology. This is in synergy with the growing focus on true early disease detection and prevention in early life. We are about to see a new era of advanced medical science built from pediatric proteomics.

Label-Free Quantitative Proteomics Identifies Novel Plasma Biomarkers for Distinguishing Pulmonary Tuberculosis and Latent Infection

The lack of effective differential diagnostic methods for active tuberculosis (TB) and latent infection (LTBI) is still an obstacle for TB control. Furthermore, the molecular mechanism behind the progression from LTBI to active TB has been not elucidated. Therefore, we performed label-free quantitative proteomics to identify plasma biomarkers for discriminating pulmonary TB (PTB) from LTBI. A total of 31 overlapping proteins with significant difference in expression level were identified in PTB patients (n = 15), compared with LTBI individuals (n = 15) and healthy controls (HCs, n = 15). Eight differentially expressed proteins were verified using western blot analysis, which was 100% consistent with the proteomics results. Statistically significant differences of six proteins were further validated in the PTB group compared with the LTBI and HC groups in the training set (n = 240), using ELISA. Classification and regression tree (CART) analysis was employed to determine the ideal protein combination for discriminating PTB from LTBI and HC. A diagnostic model consisting of alpha-1-antichymotrypsin (ACT), alpha-1-acid glycoprotein 1 (AGP1), and E-cadherin (CDH1) was established and presented a sensitivity of 81.2% (69/85) and a specificity of 95.2% (80/84) in discriminating PTB from LTBI, and a sensitivity of 81.2% (69/85) and a specificity of 90.1% (64/81) in discriminating PTB from HCs. Additional validation was performed by evaluating the diagnostic model in blind testing set (n = 113), which yielded a sensitivity of 75.0% (21/28) and specificity of 96.1% (25/26) in PTB vs. LTBI, 75.0% (21/28) and 92.3% (24/26) in PTB vs. HCs, and 75.0% (21/28) and 81.8% (27/33) in PTB vs. lung cancer (LC), respectively. This study obtained the plasma proteomic profiles of different M.TB infection statuses, which contribute to a better understanding of the pathogenesis involved in the transition from latent infection to TB activation and provide new potential diagnostic biomarkers for distinguishing PTB and LTBI.