T helper 17 cells (Th17) constitute a distinct subset of helper T cells with a unique transcriptional profile (STAT3, RORγ, and RORα), cytokine production pattern (IL17 family), and requirement of specific cytokines for their differentiation (TGF-β, IL6, IL21, and IL23). Recent studies involving experimental animals and humans have shown that Th17/IL17 plays a crucial role in host defense against a variety of pathogens, including bacteria and viruses. The underlying mechanisms by which Th17 performs include dendritic cell (DC) regulation, neutrophil recruitment, Th1 modulation, and T regulatory cell (Treg) balance. In recent years, researchers have generated an accumulating wealth of evidence on the role of Th17/IL17 in protective immunity to intracellular bacterial pathogens, such asMycobacterium tuberculosisandChlamydia trachomatis, which are one of the most important pathogens that inflict significant socioeconomic burden across the globe. In this article, we reviewed the current literature on the functions and mechanisms by which Th17/IL17 responds to intracellular bacterial infections. A better understanding of Th17/IL17 immunity to pathogens would be crucial for developing effective prophylactics and therapeutics.

Glutamine metabolism provides energy to tumor cells and also produces reactive oxygen species (ROS). Excessive accumulation of ROS can damage mitochondria and eventually lead to cell death. xCT (SLC7A11) is responsible for the synthesis of glutathione in order to neutralize ROS. In addition, mitophagy can remove damaged mitochondria to keep the cell alive. Ionizing radiation kills tumor cells by causing the accumulation of ROS, which subsequently induces nuclear DNA damage. With this in mind, we explored the mechanism of intracellular ROS accumulation induced by ionizing radiation and hypothesized new methods to enhance the effect of radiotherapy. We used MCF‐7 breast cancer cells and HCT116 colorectal cancer cells in our study. The above‐mentioned cells were irradiated with different doses of X‐rays or carbon ions. Clone formation assays were used to detect cell proliferation, enzyme‐linked immunosorbent assay (ELISA) detected ATP, and glutathione (GSH) production, while the expression of proteins was detected by Western blot and quantitative real‐time PCR analysis. The production of ROS was detected by flow cytometry, and immunofluorescence was used to track mitophagy‐related processes. Finally, BALB/C tumor‐bearing nude mice were irradiated with X‐rays in order to further explore the protein expression found in tumors with the use of immunohistochemistry. Ionizing radiation increased the protein expressions of ASCT2, GLS, and GLUD in order to upregulate the glutamine metabolic flux in tumor cells. This caused an increase in ATP secretion. Meanwhile, ionizing radiation inhibited the expression of the xCT (SLC7A11) protein and reduced the generation of glutathione, leading to excessive accumulation of intracellular ROS. The mitophagy inhibitor, or knockdown Parkin gene, is able to enhance the ionizing radiation‐induced ROS production and increase nucleus DNA damage. This combined treatment can significantly improve the killing effect of radiation on tumor cells. We concluded that ionizing radiation could upregulate the glutamine metabolic flux and enhance ROS accumulation in mitochondria. Ionizing radiation also decreased the SLC7A11 expression, resulting in reduced GSH generation. Therefore, inhibition of mitophagy can increase ionizing radiation‐induced cell death.

Background and Aim: Metabolic reprogramming is characterized by dysregulated levels of metabolites and metabolic enzymes. Integrated metabolomic and transcriptomic data analysis can help to elucidate changes in the levels of metabolites and metabolic enzymes, screen the core metabolic pathways, and develop novel therapeutic strategies for cancer.Methods: Here, the metabolome of gastric cancer tissues was determined using liquid chromatography–mass spectrometry. The transcriptome data from The Cancer Genome Atlas dataset were integrated with the liquid chromatography–mass spectrometry data to identify the common dysregulated gastric cancer‐specific metabolic pathways. Additionally, the protein expression and clinical significance of key metabolic enzymes were examined using a gastric cancer tissue array.Results: Metabolomic analysis of 16 gastric cancer tissues revealed that among the 15 dysregulated metabolomic pathways, the aminoacyl‐tRNA biosynthesis pathway in the gastric tissues was markedly upregulated relative to that in the adjacent noncancerous tissues, which was consistent with the results of transcriptome analysis. Bioinformatic analysis revealed that among the key regulators in the aminoacyl‐tRNA biosynthesis pathway, the expression levels of threonyl‐tRNA synthetase (TARS) and phenylalanyl‐tRNA synthetase (FARSB) were correlated with tumor grade and poor survival, respectively. Additionally, gastric tissue array data analysis indicated that TARS and FARSB were upregulated in gastric cancer tissues and were correlated with poor prognosis and tumor metastasis.Conclusions: This study demonstrated that the aminoacyl‐tRNA biosynthesis pathway is upregulated in gastric cancer and both TARS and FARSB play key roles in the progression of gastric cancer. Additionally, a novel therapeutic strategy for gastric cancer was proposed that involves targeting the aminoacyl‐tRNA biosynthesis pathway.

Epithelial-mesenchymal transition (EMT) is a biological process that transforms epithelial cells into a mesenchymal phenotype, conferring cell migration and invasion capabilities. EMT is involved in the progression and metastasis of colorectal cancer (CRC). Recently, emerging evidence has shown dysregulation of non-coding RNA (ncRNA) was linked to EMT. ncRNAs, including long non-coding RNA (lncRNA), regulate the transcription of downstream target genes (mRNA) through interaction with microRNAs (miRNAs); these are termed competitive endogenous RNA (ceRNA) networks. CeRNA dysregulation-induced EMT, which is linked to the progression and prognosis of CRC, has attracted wide attention. However, understanding the role of the regulation of the ceRNA network in the EMT of CRC remains limited. We discuss the molecular functions of lncRNA, the ceRNA networks related to miRNAs and mRNAs in EMT, as well as EMT transcription factors, such as the zinc finger E-box binding homeobox 1/2 (ZEB1/2), SNAIL, SLUG, and TWIST1/2. In addition, miRNAs and lncRNAs that directly target genes, thereby initiating different signaling pathways to promote EMT in CRC, were summarized. Clarifying the role of these molecules in EMT is critical for understanding molecular mechanisms and exploring the potential therapeutic targets of CRC.

In recent years, studies on the diagnostic accuracy of in-house real-time PCR (hRT-PCR) assay for the detection of Mycobacterium tuberculosis (Mtb) have been reported with unignorable discrepancies. To assess the overall accuracy of the hRT-PCR assay for Mtb diagnosis in different samples for individuals with active pulmonary and extra-pulmonary Mtb infection, a systematic review and meta-analysis were performed. The PUBMED, EMBASE, Web of Science, and Cochrane databases were searched up to June 2017 for eligible studies that estimated diagnostic sensitivity and specificity with the hRT-PCR assay in respiratory and non-respiratory samples in pulmonary and extra-pulmonary Mtb infection patients, with Mtb culture as the reference standard. Bivariate random effect models were used to provide pooled estimation of diagnostic accuracy. Further, subgroup and meta-regression analyses were performed to explore sources of heterogeneity. The risk of bias was assessed by the QUADAS-2 tool. Of the 3589 candidate studies, 18 eligible studies met our inclusion criteria. Compared to Mtb culture data, the pooled sensitivity and specificity were 0.96 and 0.92, respectively. The diagnostic odds ratio (DOR) was 192.96 (95% CI 68.46, 543.90), and the area under the summary ROC curve (AUC) was 0.9791. There was significant heterogeneity in sensitivity and specificity among the enrolled studies (p < 0.001). The studies with high-quality assessment and application of respiratory specimen were associated with better accuracy. In low-income/high-burden settings, our results suggested that the hRT-PCR assay could be a useful test for the diagnosis of TB with high sensitivity and specificity.

Background: One forth whole-world population is infected with Mycobacterium tuberculosis (Mtb), but 90% of them are asymptotic latent infection without any symptoms but positive result in IFN-γ release assay. There is lack of ideal strategy to distinguish active tuberculosis (TB) and latent tuberculosis infection (LTBI). Some scientist had focused on a set of cytokines as biomarkers besides interferon- gamma (IFN-γ) to distinguish active TB and LTBI, but with considerable variance of results. This meta-analysis aimed to evaluate the overall discriminative ability of potential immune molecules to distinguish active TB and LTBI. Methods: PubMed, the Cochrane Library, and Web of Science databases were searched to identify studies assessing diagnostic roles of cytokines for distinguishing active TB and LTBI published up to August 2018. The quality of enrolled studies was assessed using Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). The pooled diagnostic sensitivity and specificity of each cytokine was calculated by using Meta-DiSc software. Area under the summary receiver operating characteristic curve (AUC) was used to summarize the overall diagnostic performance of each biomarker. Results: Fourteen studies with 982 subjects met the inclusion criteria, including 526 active TB and 456 LTBI patients. Pooled sensitivity, specificity and AUC for discriminating between active TB and LTBI were analyzed for IL-2 (0.87, 0.61 and 0.9093), IP-10 (0.77, 0.73 and 0.8609), IL-5 (0.64, 0.75 and 0.8533), IL-13 (0.75, 0.71 and 0.8491), IFN-γ (0.67, 0.75 and 0.8031), IL-10 (0.68, 0.74 and 0.7957) and TNF-α (0.67, 0.64 and 0.7783). The heterogeneous subgroup analysis showed that cytokine detection assays, TB incidence, and stimulator with Mtb antigens are main influence factors for their diagnostic performance. Conclusions: The meta-analysis showed cytokine production could assist the distinction between active TB and LTBI, IL-2 with the highest overall accuracy. No single biomarker is likely to show sufficiently diagnostic performance due to limited sensitivity and specificity. Further prospective studies are needed to identify the optimal combination of biomarkers to enhanced diagnostic capacity in clinical practice.