Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography.

Many COVID-19 patients infected by SARS-CoV-2 virus develop pneumonia (called novel coronavirus pneumonia, NCP) and rapidly progress to respiratory failure. However, rapid diagnosis and identification of high-risk patients for early intervention are challenging. Using a large computed tomography (CT) database from 3,777 patients, we developed an AI system that can diagnose NCP and differentiate it from other common pneumonia and normal controls. The AI system can assist radiologists and physicians in performing a quick diagnosis especially when the health system is overloaded. Significantly, our AI system identified important clinical markers that correlated with the NCP lesion properties. Together with the clinical data, our AI system was able to provide accurate clinical prognosis that can aid clinicians to consider appropriate early clinical management and allocate resources appropriately. We have made this AI system available globally to assist the clinicians to combat COVID-19.

Artificial intelligence-based risk stratification, accurate diagnosis and treatment prediction in gynecologic oncology.

As data-driven science, artificial intelligence (AI) has paved a promising path toward an evolving health system teeming with thrilling opportunities for precision oncology. Notwithstanding the tremendous success of oncological AI in such fields as lung carcinoma, breast tumor and brain malignancy, less attention has been devoted to investigating the influence of AI on gynecologic oncology. Hereby, this review sheds light on the ever-increasing contribution of state-of-the-art AI techniques to the refined risk stratification and whole-course management of patients with gynecologic tumors, in particular, cervical, ovarian and endometrial cancer, centering on information and features extracted from clinical data (electronic health records), cancer imaging including radiological imaging, colposcopic images, cytological and histopathological digital images, and molecular profiling (genomics, transcriptomics, metabolomics and so forth). However, there are still noteworthy challenges beyond performance validation. Thus, this work further describes the limitations and challenges faced in the real-word implementation of AI models, as well as potential solutions to address these issues.

Predicting gene mutation status via artificial intelligence technologies based on multimodal integration (MMI) to advance precision oncology.

Personalized treatment strategies for cancer frequently rely on the detection of genetic alterations which are determined by molecular biology assays. Historically, these processes typically required single-gene sequencing, next-generation sequencing, or visual inspection of histopathology slides by experienced pathologists in a clinical context. In the past decade, advances in artificial intelligence (AI) technologies have demonstrated remarkable potential in assisting physicians with accurate diagnosis of oncology image-recognition tasks. Meanwhile, AI techniques make it possible to integrate multimodal data such as radiology, histology, and genomics, providing critical guidance for the stratification of patients in the context of precision therapy. Given that the mutation detection is unaffordable and time-consuming for a considerable number of patients, predicting gene mutations based on routine clinical radiological scans or whole-slide images of tissue with AI-based methods has become a hot issue in actual clinical practice. In this review, we synthesized the general framework of multimodal integration (MMI) for molecular intelligent diagnostics beyond standard techniques. Then we summarized the emerging applications of AI in the prediction of mutational and molecular profiles of common cancers (lung, brain, breast, and other tumor types) pertaining to radiology and histology imaging. Furthermore, we concluded that there truly exist multiple challenges of AI techniques in the way of its real-world application in the medical field, including data curation, feature fusion, model interpretability, and practice regulations. Despite these challenges, we still prospect the clinical implementation of AI as a highly potential decision-support tool to aid oncologists in future cancer treatment management.

Investigating causal associations between pneumonia and lung cancer using a bidirectional mendelian randomization framework.

BACKGROUND: Pneumonia and lung cancer are both major respiratory diseases, and observational studies have explored the association between their susceptibility. However, due to the presence of potential confounders and reverse causality, the comprehensive causal relationships between pneumonia and lung cancer require further exploration. METHODS: Genome-wide association study (GWAS) summary-level data were obtained from the hitherto latest FinnGen database, COVID-19 Host Genetics Initiative resource, and International Lung Cancer Consortium. We implemented a bidirectional Mendelian randomization (MR) framework to evaluate the causal relationships between several specific types of pneumonia and lung cancer. The causal estimates were mainly calculated by inverse-variance weighted (IVW) approach. Additionally, sensitivity analyses were also conducted to validate the robustness of the causalty. RESULTS: In the MR analyses, overall pneumonia demonstrated a suggestive but modest association with overall lung cancer risk (Odds ratio [OR]: 1.21, 95% confidence interval [CI]: 1.01 - 1.44, P = 0.037). The correlations between specific pneumonia types and overall lung cancer were not as significant, including bacterial pneumonia (OR: 1.07, 95% CI: 0.91 - 1.26, P = 0.386), viral pneumonia (OR: 1.00, 95% CI: 0.95 - 1.06, P = 0.891), asthma-related pneumonia (OR: 1.18, 95% CI: 0.92 - 1.52, P = 0.181), and COVID-19 (OR: 1.01, 95% CI: 0.78 - 1.30, P = 0.952). Reversely, with lung cancer as the exposure, we observed that overall lung cancer had statistically crucial associations with bacterial pneumonia (OR: 1.08, 95% CI: 1.03 - 1.13, P = 0.001) and viral pneumonia (OR: 1.09, 95% CI: 1.01 - 1.19, P = 0.037). Sensitivity analysis also confirmed the robustness of these findings. CONCLUSION: This study has presented a systematic investigation into the causal relationships between pneumonia and lung cancer subtypes. Further prospective study is warranted to verify these findings.

Association Between Daily Internet Use and Incidence of Chronic Diseases Among Older Adults: Prospective Cohort Study.

BACKGROUND: Chronic disease incidence among the elderly is increasing, which is correlated with the acceleration of population aging. Evolving internet technologies may help prevent and provide interventions for chronic diseases in an accelerating aging process. However, the impact of daily internet use on the incidence of chronic diseases is not well understood. OBJECTIVE: This study aims to investigate whether daily internet use by middle-aged and older adults may inhibit or promote the occurrence of chronic diseases. METHODS: We included participants from the China Health and Retirement Longitudinal Study (CHARLS), a longitudinal survey of Chinese residents aged ≥45 years. We assessed 8-year data from wave 1 (June 2011-March 2012) to wave 4 (July-September 2018) in CHARLS. Data from wave 4 were used for a cross-sectional study, and data from all 4 waves were used for a longitudinal study. Self-reported data were used to track variables, including internet use, use frequency, and the incidence of different chronic diseases. Cox proportional hazards modeling was applied in the longitudinal study to examine the relationship between daily internet use and chronic diseases among middle-aged and older adults, while adjusting for sociodemographic characteristics and health behaviors. In addition, longitudinal data were used to analyze internet usage trends, and cross-sectional data were used to analyze the factors influencing internet use. RESULTS: Among the 20,113 participants included in the longitudinal analyses, internet use increased significantly, from 2% to 12.3%, between 2011 and 2018. The adjusted model found statistically significant relationships between daily internet use and a lower incidence of the following chronic diseases: hypertension (hazard ratio [HR] 0.78, 95% CI 0.65-0.95, P=.01), chronic lung disease (HR 0.74, 95% CI 0.57-0.97, P=.03), stroke (HR 0.69, 95% CI 0.50-0.94, P=.02), digestive disease (HR 0.73, 95% CI 0.58-0.91, P=.005), memory-related disorders (HR 0.58, 95% CI 0.37-0.91, P=.02), arthritis or rheumatism (HR 0.60, 95% CI 0.48-0.76, P<.001), asthma (HR 0.52, 95% CI 0.33-0.84, P=.007), depression (HR 0.80, 95% CI 0.71-0.89, P<.001), and vision impairment (HR 0.83, 95% CI 0.74-0.93, P=.004). Moreover, our study also showed that with increasing frequency of internet use, the risk of some chronic diseases decreases. CONCLUSIONS: This study found that middle-aged and older adults who use the internet have a reduced risk of developing chronic diseases versus those who do not use the internet. The increasing prevalence of daily internet use among middle-aged and older adults may stimulate contemplation of the potential role of internet platforms in future research on chronic disease prevention.

Characterization of distinct circular RNA signatures in solid tumors.

BACKGROUND: Circular RNAs (circRNAs) are differentially expressed between normal and cancerous tissues, contributing to tumor initiation and progression. However, comprehensive landscape of dysregulated circRNAs across cancer types remains unclear. METHODS: In this study, we conducted Ribo-Zero transcriptome sequencing on tumor tissues and their adjacent normal samples including glioblastoma, esophageal squamous cell carcinoma, lung adenocarcinoma, thyroid cancer, colorectal cancer, gastric cancer and hepatocellular carcinoma. CIRCexplorer2 was employed to identify circRNAs and dysregulated circRNAs and genes were determined by DESeq2 package. The expression of hsa_circ_0072309 (circLIFR) was measured by reverse transcription and quantitative real-time PCR, and its effect on cell migration was examined by Transwell and wound healing assays. The role of circLIFR in tumor metastasis was evaluated via mouse models of tail-vein injection and spleen injection for lung and liver metastasis, respectively. RESULTS: Distinct circRNA expression signatures were identified among seven types of solid tumors, and the dysregulated circRNAs exhibited cancer-specific expression or shared common expression signatures across cancers. Bioinformatics analyses indicated that aberrant expression of host genes and/or RNA-binding proteins contributed to circRNA dysregulation in cancer. Finally, circLIFR was experimentally validated to be downregulated in six solid tumors and to significantly inhibit cell migration in vitro and tumor metastasis in vivo. CONCLUSIONS: Our results provide a comprehensive landscape of differentially expressed circRNAs in solid tumors and highlight that circRNAs are extensively involved in cancer pathogenesis.

The landscape of immune checkpoint inhibitor therapy in advanced lung cancer.

BACKGROUND: The advent of immune checkpoint inhibitors (ICIs) therapy has resulted in significant survival benefits in patients with non-small-cell lung cancer (NSCLC) without increasing toxicity. However, the utilisation of immunotherapy for small-cell lung cancer (SCLC) remains unclear, with a scarcity of systematic comparisons of therapeutic effects and safety of immunotherapy in these two major lung cancer subtypes. Herein, we aimed to provide a comprehensive landscape of immunotherapy and systematically review its specific efficacy and safety in advanced lung cancer, accounting for histological types. METHODS: We identified studies assessing immunotherapy for lung cancer with predefined endpoints, including overall survival (OS), progression-free survival (PFS), objective response rate (ORR), and treatment-related adverse events (TRAE), from PubMed, Embase, Medline, and Cochrane library. A random-effects or fixed-effect model was adopted according to different settings. RESULTS: Overall, 38 trials with 20,173 patients with lung cancer were included in this study. ICI therapy resulted in a significantly prolonged survival in both patients with NSCLC and SCLC when compared with chemotherapy (hazard ratio [HR] = 0.74; 95% confidence interval [CI], 0.70-0.79] and [HR = 0.82; 95% CI, 0.75-0.90], respectively). The magnitude of disease control and survival benefits appeared superior with ICI plus standard of care (SOC) when compared with SOC alone. OS and PFS advantages were observed only when immunotherapy was employed as the first-line treatment in patients with SCLC. CONCLUSION: ICI therapy is a promising therapeutic option in patients with NSCLC and SCLC. ICI plus SOC can be recommended as the optimal first-line treatment for patients with SCLC, and double-target ICIs combined with SOC are recommended in patients with NSCLC as both the first and subsequent lines of treatment. Additionally, non-first-line immunotherapy is not recommended in patients with SCLC.

The landscape of immune checkpoint inhibitor plus chemotherapy versus immunotherapy for advanced non-small-cell lung cancer: A systematic review and meta-analysis.

BACKGROUND: Lung cancer is the leading cause of cancer-related deaths worldwide and the prognosis remains poor. The recent introduction of the immune checkpoint inhibitor (ICI), or plus chemotherapy, both resulted in the survival benefit for patients with advanced non-small-cell lung cancer (NSCLC), but it remains unanswered which is superior. The current study aimed to estimate the comparative efficacy and safety of ICI-chemotherapy versus ICI-monotherapy in advanced NSCLC. METHODS: Studies were identified by searching PubMed, Embase, and Cochrane library. The randomized controlled trials (RCTs) that ICI monotherapy or ICI plus chemotherapy compared with chemotherapy in NSCLC were included with available primary endpoints of progression-free survival (PFS), overall survival (OS), objective response rate, or treatment-related adverse events. A fixed-effect or random-effects model was adopted depending on between-study heterogeneity. RESULTS: A total of 20 RCTs involving 12,025 patients with NSCLC were included. Both ICI-monotherapy and ICI-chemotherapy resulted in significantly prolonged survival compared to chemotherapy and the former led to significantly longer PFS. The magnitude of survival benefits appeared to be greatest among those treated with pembrolizumab plus platinum-based chemotherapy (OS, 0.56; PFS, 0.54). Additionally, OS and PFS advantages of ICI therapies were observed in patients with NSCLC with low or high programmed cell death 1 ligand 1 (PD-L1) expression level, but not in intermediate PD-L1 TPS. CONCLUSIONS: Pembrolizumab plus platinum-based chemotherapy was recommended as the optimal first-line therapy for advanced patients with NSCLC. Additionally, PD-L1 alone is not recommended as an adequate molecular biomarker to identify eligible patients for routine clinical practice in immunotherapy.

Unraveling the molecular mechanism of BNC105, a phase II clinical trial vascular disrupting agent, provides insights into drug design.

Microtubules are made up of tubulin protein and play a very important part in numerous cellular events of eukaryotic cells, which is why they are seen as attractive targets for tumor chemotherapy. BNC105, a known vascular targeting agent, has entered in phase II clinical trials. It has previously been confirmed that BNC105 is an effective microtubule targeting agent for various cancers. BNC105 exhibits selectivity for tumor cells, elicits vascular disrupting effects, and inhibits tumor growth. However, the molecular mechanism of BNC105 is still elusive. Herein, the crystal structure of BNC105 in complex with tubulin protein is revealed, demonstrating the its interaction with the colchicine binding site. In order to thoroughly evaluate its molecular mechanism from a structural-activity-relationship standpoint, the binding mode of tubulin to BNC-105 is compared with colchicine, CA-4 and other BNC-105 derivatives. Our study not only confirms the detailed interactions of the BNC105-tubulin complex, but also offer substantial structural foundation for the design and development of novel benzo[b]furan derivatives as microtubule targeting agents.

Clinicopathological variables influencing overall survival, recurrence and post-recurrence survival in resected stage I non-small-cell lung cancer.

BACKGROUND: To investigate clinicopathological variables influencing overall survival, overall recurrence, and post-recurrence survival (PRS) in patients who experienced curative-intent surgical resection of stage I non-small-cell lung cancer (NSCLC). METHODS: We investigated a series of 1387 patients with stage I NSCLC who underwent surgical resection from 2008 to 2015. The effect clinicopathological factors on death, recurrence, and PRS were evaluated by Kaplan-Meier estimates and cox regression analysis. RESULTS: Among the 1387 stage I patients, 301 (21.7%) experienced recurrence. The 5-year cumulative incidence of recurrence (CIR) for all patients was 20.2% and median PRS was 25.5 months. The older age (P = 0.036), p-stage IB (P = 0.001), sublobar resection(P<0.001), histology subtype (P<0.001), and lymphovascular invasion (LVI) (P = 0.042) were significantly associated with worse overall survival. Among 301 recurrent patients, univariable analysis indicated that p-stage IB (versus IA) (P<0.001), LVI (P<0.001) and visceral pleural invasion (VPI) (P<0.001) were remarkably correlated with the higher incidence of recurrence. Taking the effect of clinicopathological variables on PRS into consideration, smoking history (P = 0.043), non-adenocarcinoma (P = 0.013), high architectural grade of LUAD (P = 0.019), EGFR wild status (P = 0.002), bone metastasis (P =0.040) and brain metastasis (P = 0.042) were substantially related with poorer PRS. Multivariate analysis demonstrated that high architectural grade of LUAD (P = 0.008), brain metastasis (P = 0.010) and bone metastasis (P = 0.043) were independently associated with PRS. CONCLUSION: In patients with resected stage I NSCLC, the older age, p-stage IB (versus IA), sublobar resection, histology subtype, and LVI were significantly associated with worse overall survival. P-stage IB (versus IA), LVI, and VPI were significantly correlated with the higher incidence of recurrence. High architectural grade of LUAD, brain metastasis and bone metastasis were independent risk factors with PRS.

Clinical and molecular characteristics associated with survival among cancer patients receiving first-line anti-PD-1/PD-L1-based therapies.

BACKGROUND: Anti-PD-1/PD-L1-based therapy has emerged recently, and we aimed to figure out the latent value of different clinical and molecular factors to predict the efficacy of immune checkpoint inhibitors (ICIs) therapy compared with non-immunotherapy in the first-line setting. METHODS: We assessed the clinical outcomes of 8711 patients in 13 trials receiving anti-PD-1/PD-L1-based therapy or non-immunotherapy as first-line treatment, and different predictors were investigated. RESULTS: Overall, compared with non-immunotherapy, anti-PD-1/PD-L1-based therapy reduced the risk of death by 31% (HR 0.69, 95%CI: 0.60-0.79) for all cancers. Stratified analysis showed that the progression-free survival (PFS) benefit from anti-PD-1/PD-L1-based therapy existed in all three PD-L1 status subgroups (tumour proportion score, TPS ≥50%: HR 0.54, 95%CI: 0.38-0.78; TPS 1-49%: HR 0.56, 95%CI: 0.46-0.68; TPS <1%: HR 0.82, 95%CI: 0.73-0.91; interaction, p < 0.01). ICI therapy also prolonged PFS in males (HR 0.64, 95%CI: 0.50-0.83) and younger patients (HR 0.70, 95%CI: 0.52-0.93), and they might prolong overall survival (OS) in patients without brain metastasis (HR 0.54, 95%CI: 0.41-0.71). CONCLUSION: PD-L1 expression level alone is imperfect to predict the efficacy of anti-PD-1/PD-L1-based therapies as first-line cancer treatment. Meanwhile, sex, age, and status of brain metastases might also be predictive parameters for the selection of cancer patients.

RNA-Seq profiling of circular RNA in human lung adenocarcinoma and squamous cell carcinoma.

Emerging evidences demonstrate that circular RNAs (circRNAs) are abnormally expressed in tumors and could serve as prognostic markers for cancers. However, the expression patterns and clinical implications of circRNAs in non-small cell lung cancer (NSCLC) remain obscure. In this study, we profiled circRNA expressions in 10 pairs of lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) after ribosomal RNA-depletion and RNase R digestion to enrich circRNAs. Combining five circRNA computational programs, we found that LUAD and LUSC not only share common expression patterns, but also exhibit distinct circRNA expression signatures. Moreover, the Receiver Operating Characteristic (ROC) curve analysis indicated that hsa_circ_0077837 and hsa_circ_0001821 could serve as potential biomarkers for both LUAD and LUSC, while hsa_circ_0001073 and hsa_circ_0001495 could be diagnostic/subtyping marker for LUAD and LUSC, respectively. Therefore, our findings highlight the important diagnostic potential of circRNAs in NSCLC.

Molecular mechanism of crolibulin in complex with tubulin provides a rationale for drug design.

Microtubules (MTs) is one of the most important proteins in eukaryotic cells and plays a key role in the maintenance of cell morphology and cell division. The discovery and development of small molecule drugs targeting MTs has always been an important direction of anti-cancer research. Nowadays 4-Aryl-4H-chromenes have emerged as potent microtubule-targeting agents (MTAs) for various cancers. Crolibulin, a derivative of 4-Aryl-4H-chromenes, which has been progressed to Phase I/II clinical testing's for anaplastic thyroid cancer with the National Cancer Institute. However, the design and development of 4-Aryl-4H-chromenes family drugs have been hindered for a long time by the lack of structural information of the tubulin-agent complex. Here we report a 2.5 Šcrystal structure of tubulin complexed with crolibulin. This complex structure reveals the interactions between crolibulin and tubulin, helps explain the results of the structure-activity-relationship (SAR) studies and provides a solid structural basis for the design and development of new 4-Aryl-4H-chromenes derivatives as MTAs.

DeepLNAnno: a Web-Based Lung Nodules Annotating System for CT Images.

Lung cancer is one of the most common and fatal types of cancer, and pulmonary nodule detection plays a crucial role in the screening and diagnosis of this disease. A well-trained deep neural network model can help doctors to find nodules on computed tomography(CT) images while requiring lots of labeled data. However, currently available annotating systems are not suitable for annotating pulmonary nodules in CT images. We propose a web-based lung nodules annotating system named as DeepLNAnno. DeepLNAnno has a unique three-tier working process and loads of features like semi-automatic annotation, which not only make it much easier for doctors to annotate compared to some other annotating systems but also increase the accuracy of the labels. We invited a medical group from West China Hospital to annotate the CT images using our DeepLNAnno system, and collected a large number of labeled data. The results of our experiments demonstrated that a usable nodule-detection system is developed, and good benchmark scores on our evaluation data are obtained.

Structure of a benzylidene derivative of 9(10H)-anthracenone in complex with tubulin provides a rationale for drug design.

Microtubules are composed of αß-tubulin heterodimers and have been treated as highly attractive targets for antitumor drugs. A broad range of agents bind to tubulin and interfere with microtubule assembly, including colchicine binding site inhibitors (CBSIs). Tubulin Polymerization Inhibitor I (TPI1), a benzylidene derivative of 9(10H)-anthracenone, is a CBSI that inhibits the assembly of microtubules. However, for a long time, the design and development of anthracenone family drugs have been hindered by the lack of structural information of the tubulin-agent complex. Here we report a 2.3 Å crystal structure of tubulin complexed with TPI1, the first structure of anthracenone family agents. This complex structure reveals the interactions between TPI1 and tubulin, and thus provides insights into the development of new anthracenone derivatives targeting the colchicine binding site.

Preparation and characterization of a high-affinity monoclonal antibody against human epididymis protein-4.

Human epididymis protein-4 (HE4) may serve as a putative biomarker for the early diagnosis, therapy and especially prognosis of ovarian, lung and breast cancer. Detection and targeting of HE4 using the anti-HE4 antibody could be one of the effective strategies for the cancer diagnosis and treatment in clinical practice. In this study, a high-efficiency expression system was established to purify recombinant HE4. We obtained high purity HE4 in 400 mg quantity from 1 L culture supernatant of HEK293F cells. CCK-8 and cell cycle assays indicated that the purified recombinant HE4 protein could promote SKOV3 cell cycle and proliferation at the concentration of 0.1 mg/L. Furthermore, an anti-HE4 high-affinity monoclonal antibody 9C3 (ka = 8.1 × 106 1/MS, kd = 4.4 × 10-5 1/S, KD = 5.5 × 10-12 M) was prepared using hybridoma technique and analyzed by surface plasmon resonance technology using this HE4 protein. Differential Scanning calorimeter (DSC) analysis showed that 9C3 had a commendable thermal stability with the Tm value of 73 °C. Analyses of western blot, immunohistochemistry and immunofluorescence showed that the 9C3 was highly specific to HE4 in human cancer cells and tissues. In conclusion, our study designed a method to prepare human recombinant HE4 with high yield and generated a high-affinity anti-HE4 monoclonal antibody that might have potential for basic research and clinical application.

Structure of 4'-demethylepipodophyllotoxin in complex with tubulin provides a rationale for drug design.

Microtubules consists of αß-tubulin heterodimers and are highly attractive targets for anti-cancer drugs. A broad range of agents have been identified to bind to tubulin and interfere with microtubule assembly, including colchicine binding site inhibitors (CBSIs). Podophyllotoxin is a CBSI that inhibits the assembly of microtubules. However, for a long time, the design and development of podophyllotoxin family drugs have been hindered by the lack of high-resolution structural information of the tubulin-agent complex. We report the first high-resolution (2.8 Å) structure of a podophyllotoxin family agent (4'-demethylepipodophyllotoxin, DMEP) complexed with tubulin and revealed the detailed interactions between DMEP and tubulin. Comparison of this structure and other CBSIs explains previous results of the structure-activity-relationship (SAR) studies, and provides insights into the development of new podophyllotoxin derivatives targeting the colchicine site.

Association between interleukin-17a gene polymorphisms and asthma risk: a meta-analysis.

BACKGROUND: Interleukin-17A (IL-17A), a proinflammatory cytokine, plays an important role in the pathogenesis of asthma. Considerable research has assessed the association between IL-17A polymorphisms and asthma risk, but the results are inconsistent. OBJECTIVE: This meta-analysis was carried out to make a more precise estimation of the relationship between IL-17A polymorphisms and asthma risk. METHODS: The PUBMED, MEDLINE, EMBASE, Chinese National Knowledge Infrastructure and Wan Fang databases were searched systemically on December 12, 2014 and data were extracted from eligible studies by two independent reviewers. Meta-analysis, sub-group analysis, sensitivity analysis and publication bias assessments were all done using Stata 12.1 software. RESULTS: The IL-17A -737C/T polymorphism and IL-17A -197G/A polymorphism were included in the analysis with seven case-control studies. Asthma patients (n = 2882) and healthy controls (n = 2093) were included. The IL17A -737C/T polymorphism was found to have a significantly protective effect on asthma in the allele model (OR = 0.86, 95% CI 0.78-0.96, P = 0.007), dominant model (OR = 0.76, 95% CI 0.65-0.88, P <0.001) and heterozygous model (OR = 0.75, 95% CI 0.64-0.88, P < 0.001) in the overall analysis. Stratified by ethnicity and age, the effects were also significant in the Asian population and in children. However, for IL-17A -197G/A, no significant association was revealed either in the overall analysis in the ethnicity-special subgroup analysis. CONCLUSIONS: The IL-17A -737C/T polymorphism is likely to contribute to protection against asthma, while the IL-17A -197G/A polymorphism may not be associated with asthma susceptibility.

Single-cell RNA sequencing in tuberculosis: Application and future perspectives.

ABSTRACT: Tuberculosis (TB) has one of the highest mortality rates among infectious diseases worldwide. The immune response in the host after infection is proposed to contribute significantly to the progression of TB, but the specific mechanisms involved remain to be elucidated. Single-cell RNA sequencing (scRNA-seq) provides unbiased transcriptome sequencing of large quantities of individual cells, thereby defining biological comprehension of cellular heterogeneity and dynamic transcriptome state of cell populations in the field of immunology and is therefore increasingly applied to lung disease research. Here, we first briefly introduce the concept of scRNA-seq, followed by a summarization on the application of scRNA-seq to TB. Furthermore, we underscore the potential of scRNA-seq for clinical biomarker exploration, host-directed therapy, and precision therapy research in TB and discuss the bottlenecks that need to be overcome for the broad application of scRNA-seq to TB-related research.