Combining bioinformatics and biological detection to identify novel biomarkers for diagnosis and prognosis of pulmonary tuberculosis

Identification and Validation of Novel Biomarkers for Hepatocellular Carcinoma, Liver Fibrosis/Cirrhosis and Chronic Hepatitis B via Transcriptome Sequencing Technology

Purpose

The aim of this study was to identify and validate novel biomarkers for distinguishing among hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC), liver fibrosis/liver cirrhosis (LF/LC) and chronic hepatitis B (CHB).

Patients and Methods

Transcriptomic sequencing was conducted on the liver tissues of 5 patients with HCC, 5 patients with LF/LC, 5 patients with CHB, and 4 healthy controls. The expression levels of selected mRNAs and proteins were assessed by quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemical (IHC) staining, and were verified in validation set (n=200) and testing set (n=400) via enzyme-linked immunosorbent assay (ELISA).

Results

A total of 9 hub mRNAs were identified by short time-series expression miner and weighted gene co-expression network analysis. Of note, the results of qRT-PCR and IHC staining demonstrated that SHC adaptor protein 1 (SHC1), SLAM family member 8 (SLAMF8), and interleukin-32 (IL-32) exhibited gradually increasing trends in the four groups. Subsequent ELISA tests on the validation cohort indicated that the plasma levels of SHC1, SLAMF8 and IL-32 also gradually increased. Furthermore, a diagnostic model APFSSI (age, PLT, ferritin, SHC1, SLAMF8 and IL-32) was established to distinguish among CHB, LF/LC and HCC. The performance of APFSSI model for discriminating CHB from healthy subjects (AUC=0.966) was much greater compared to SHC1 (AUC=0.900), SLAMF8 (AUC=0.744) and IL-32 (AUC=0.821). When distinguishing LF/LC from CHB, APFSSI was the most outstanding diagnostic parameter (AUC=0.924), which was superior to SHC1, SLAMF8 and IL-32 (AUC=0.812, 0.684 and 0.741, respectively). Likewise, APFSSI model with the greatest AUC value displayed an excellent performance for differentiating between HCC and LF/LC than other variables (SHC1, SLAMF8 and IL-32) via ROC analysis. Finally, the results in the test set were consistent with those in the validation set.

Conclusion

SHC1, SLAMF8 and IL-32 can differentiate among patients with HCC, LF/LC, CHB and healthy controls. More importantly, the APFSSI model greatly improves the diagnostic accuracy of HBV-associated liver diseases.

Biomarkers that correlate with active pulmonary tuberculosis treatment response: a systematic review and meta-analysis

Current WHO recommendations for monitoring treatment response in adult pulmonary tuberculosis (TB) are sputum smear microscopy and/or culture conversion at the end of the intensive phase of treatment. These methods either have suboptimal accuracy or a long turnaround time. There is a need to identify alternative biomarkers to monitor TB treatment response. We conducted a systematic review of active pulmonary TB treatment monitoring biomarkers. We screened 9,739 articles published between 1 January 2008 and 31 December 2020, of which 77 met the inclusion criteria. When studies quantitatively reported biomarker levels, we meta-analyzed the average fold change in biomarkers from pretreatment to week 8 of treatment. We also performed a meta-analysis pooling the fold change since the previous time point collected. A total of 81 biomarkers were identified from 77 studies. Overall, these studies exhibited extensive heterogeneity with regard to TB treatment monitoring study design and data reporting. Among the biomarkers identified, C-reactive protein (CRP), interleukin-6 (IL-6), interferon gamma-induced protein 10 (IP-10), and tumor necrosis factor alpha (TNF-α) had sufficient data to analyze fold changes. All four biomarker levels decreased during the first 8 weeks of treatment relative to baseline and relative to previous time points collected. Based on limited data available, CRP, IL-6, IP-10, and TNF-α have been identified as biomarkers that should be further explored in the context of TB treatment monitoring. The extensive heterogeneity in TB treatment monitoring study design and reporting is a major barrier to evaluating the performance of novel biomarkers and tools for this use case. Guidance for designing and reporting treatment monitoring studies is urgently needed.

Selenium donor restricts the intracellular growth of Mycobacterium tuberculosis through the induction of c-Jun-mediated both canonical autophagy and LC3-associated phagocytosis of alveolar macrophages

The relationship between selenium and Mycobacterium tuberculosis (MTB) infection has been reported previously; however, the specific mechanism is still not clear. In this study, selenium levels decreased in the serum of patients with pulmonary tuberculosis (PTB) compared with the healthy controls; they were associated with the treatment outcome of such patients. The qRT-PCR assay revealed that selenium might function through proinflammatory and autophagy pathways. The treatment with methylseleninic acid (MSeA), a selenium donor, blocked the M1 polarization of MTB-infected macrophages through the induction of both canonical autophagy and LC3-associated phagocytosis (LAP). c-Jun is vital in mediating the MSeA-triggered canonical autophagy and LAP process, thus displaying a restricting function against intracellular MTB. An in vivo study confirmed that the activity of MSeA was shown through enhancing macrophage autophagy related pathway. The results showed that selenium had a restricting function against intracellular MTB by regulating autophagy in macrophages. The findings might provide a novel direction for PTB therapy in the future.

Leukocyte immunoglobulin-like receptor subfamily B: therapeutic targets in cancer

Inhibitory leukocyte immunoglobulin-like receptors (LILRBs 1–5) transduce signals via intracellular immunoreceptor tyrosine-based inhibitory motifs that recruit phosphatases to negatively regulate immune activation. The activation of LILRB signaling in immune cells may contribute to immune evasion. In addition, the expression and signaling of LILRBs in cancer cells especially in certain hematologic malignant cells directly support cancer development. Certain LILRBs thus have dual roles in cancer biology—as immune checkpoint molecules and tumor-supporting factors. Here, we review the expression, ligands, signaling, and functions of LILRBs, as well as therapeutic development targeting them. LILRBs may represent attractive targets for cancer treatment, and antagonizing LILRB signaling may prove to be effective anti-cancer strategies.

A bioinformatics analysis to identify novel biomarkers for prognosis of pulmonary tuberculosis

Background

Due to the fact that pulmonary tuberculosis (PTB) is a highly infectious respiratory disease characterized by high herd susceptibility and hard to be treated, this study aimed to search novel effective biomarkers to improve the prognosis and treatment of PTB patients.

Methods

Firstly, bioinformatics analysis was performed to identify PTB-related differentially expressed genes (DEGs) from GEO database, which were then subjected to GO annotation and KEGG pathway enrichment analysis to initially describe their functions. Afterwards, clustering analysis was conducted to identify PTB-related gene clusters and relevant PPI networks were established using the STRING database.

Results

Based on the further differential and clustering analyses, 10 DEGs decreased during PTB development were identified and considered as candidate hub genes. Besides, we retrospectively analyzed some relevant studies and found that 7 genes (CCL20, PTGS2, ICAM1, TIMP1, MMP9, CXCL8 and IL6) presented an intimate correlation with PTB development and had the potential serving as biomarkers.

Conclusions

Overall, this study provides a theoretical basis for research on novel biomarkers of PTB, and helps to estimate PTB prognosis as well as probe into targeted molecular treatment.

Supplementary information

Supplementary information accompanies this paper at 10.1186/s12890-020-01316-2.

LILRB4, from the immune system to the disease target

Leukocyte immunoglobulin (Ig)-like receptor B4 (LILRB4) is a member of leukocyte Ig-like receptors (LILRs), which associate with membrane adaptors to signal through multiple cytoplasmic immunoreceptor tyrosine-based inhibitory motifs (ITIMs). Under physiological conditions, LILRB4 plays a very important role in the function of the immune system through its expression on various immune cells, such as T cells and plasma cells. Under pathological conditions, LILRB4 affects the processes of various diseases, such as the transformation and infiltration of tumors and leukemias, through various signaling pathways. Differential expression of LILRB4 is present in a variety of immune system diseases, such as Kawasaki disease, systemic lupus erythematosus (SLE), and sepsis. Recent studies have shown that LILRB4 also plays a role in mental illness. The important role of LILRB4 in the immune system and its differential expression in a variety of diseases make LILRB4 a potential prophylactic and therapeutic target for a variety of diseases.