Molecular and immune characterization of Chinese early-stage non-squamous non-small cell lung cancer: a multi-omics cohort study.

Background: Albeit considered with superior survival, around 30% of the early-stage non-squamous non-small cell lung cancer (Ns-NSCLC) patients relapse within 5 years, suggesting unique biology. However, the biological characteristics of early-stage Ns-NSCLC, especially in the Chinese population, are still unclear. Methods: Multi-omics interrogation of early-stage Ns-NSCLC (stage I-III), paired blood samples and normal lung tissues (n=76) by whole-exome sequencing (WES), RNA sequencing, and T-cell receptor (TCR) sequencing were conducted. Results: An average of 128 exonic mutations were identified, and the most frequently mutant gene was EGFR (55%), followed by TP53 (37%) and TTN (26%). Mutations in MUC17, ABCA2, PDE4DIP, and MYO18B predicted significantly unfavorable disease-free survival (DFS). Moreover, cytobands amplifications in 8q24.3, 14q13.1, 14q11.2, and deletion in 3p21.1 were highlighted in recurrent cases. Higher incidence of human leukocyte antigen loss of heterozygosity (HLA-LOH), higher tumor mutational burden (TMB) and tumor neoantigen burden (TNB) were identified in ever-smokers than never-smokers. HLA-LOH also correlated with higher TMB, TNB, intratumoral heterogeneity (ITH), and whole chromosomal instability (wCIN) scores. Interestingly, higher ITH was an independent predictor of better DFS in early-stage Ns-NSCLC. Up-regulation of immune-related genes, including CRABP2, ULBP2, IL31RA, and IL1A, independently portended a dismal prognosis. Enhanced TCR diversity of peripheral blood mononuclear cells (PBMCs) predicted better prognosis, indicative of a noninvasive method for relapse surveillance. Eventually, seven machine-learning (ML) algorithms were employed to evaluate the predictive accuracy of clinical, genomic, transcriptomic, and TCR repertoire data on DFS, showing that clinical and RNA features combination in the random forest (RF) algorithm, with area under the curve (AUC) of 97.5% and 83.3% in the training and testing cohort, respectively, significantly outperformed other methods. Conclusions: This study comprehensively profiled the genomic, transcriptomic, and TCR repertoire spectrums of Chinese early-stage Ns-NSCLC, shedding light on biological underpinnings and candidate biomarkers for prognosis development.

Analyzing the associations between tertiary lymphoid structures and postoperative prognosis, along with immunotherapy response in gastric cancer: findings from pooled cohort studies.

BACKGROUND: The clinical significance of tertiary lymphoid structure (TLS) in gastric cancer (GC) was uncertain. METHODS: A systematic search was performed in public databases for eligible studies as of April 2, 2023. Meta-analyses were performed to interrogate the associations between TLS levels and prognosis and immunotherapy response of GC. Bioinformatic analyses based on the nine-gene signature of TLS were further conducted to capture the biological underpinnings. RESULTS: Eleven studies containing 4224 GC cases were enrolled in the meta-analysis. TLS levels positively correlated with smaller tumor size, earlier T stage and N stage. Moreover, higher TLS levels were detected in diffuse and mix subtypes of GC (P < 0.001). Higher TLS levels strongly predicted favorable postoperative overall survival of GC, with HR of 0.36 (95%CI 0.26-0.50, P < 0.001) and 0.55 (95%CI 0.45-0.68, P < 0.001) of univariate and multivariate Cox analysis, respectively. Higher TLS levels were also in favor of the treatment response of anti-PD-1 inhibitors as later-line therapy of GC. TLS levels positively correlated with immune effector cells infiltration, diversity and richness of T cell receptor and B cell receptor repertoire, immune checkpoint genes expression, and immune-related genes mutation of GC in the TCGA-STAD cohort, representing higher immunogenicity and immunoactivity. Moreover, moderate accuracy of TLS levels in predicting benefit from anti-PD-1 inhibitors in the PRJEB25780 cohort was also validated (AUC 0.758, 95%CI 0.583-0.933), higher than the microsatellite instability-score and Epstein-Barr virus status. CONCLUSIONS: TLS levels demonstrated potential in predicting the postoperative prognosis and immunotherapy response of GC.

Cellular dynamics in tumour microenvironment along with lung cancer progression underscore spatial and evolutionary heterogeneity of neutrophil.

BACKGROUND: The cellular dynamics in the tumour microenvironment (TME) along with non-small cell lung cancer (NSCLC) progression remain unclear. METHODS: Multiplex immunofluorescence test detecting 10 immune-related markers on 553 primary tumour (PT) samples of NSCLC was conducted and spatial information in TME was assessed by the StarDist depth learning model. The single-cell transcriptomic atlas of PT (n = 4) and paired tumour-draining lymph nodes (TDLNs) (n = 5 for tumour-invaded, n = 3 for tumour-free) microenvironment was profiled. Various bioinformatics analyses based on Gene Expression Omnibus, TCGA and Array-Express databases were also used to validate the discoveries. RESULTS: Spatial distances of CD4+ T cells-CD38+ T cells, CD4+ T cells-neutrophils and CD38+ T cells-neutrophils prolonged and they were replaced by CD163+ macrophages in PT along with tumour progression. Neutrophils showed unique stage and location-dependent prognostic effects. A high abundance of stromal neutrophils improved disease-free survival in the early-stage, whereas high intratumoural neutrophil infiltrates predicted poor prognosis in the mid-to-late-stage. Significant molecular and functional reprogramming in PT and TDLN microenvironments was observed. Diverse interaction networks mediated by neutrophils were found between positive and negative TDLNs. Five phenotypically and functionally heterogeneous subtypes of tumour-associated neutrophil (TAN) were further identified by pseudotime analysis, including TAN-0 with antigen-presenting function, TAN-1 with strong expression of interferon (IFN)-stimulated genes, the pro-tumour TAN-2 subcluster, the classical subset (TAN-3) and the pro-inflammatory subtype (TAN-4). Loss of IFN-stimulated signature and growing angiogenesis activity were discovered along the transitional trajectory. Eventually, a robust six neutrophil differentiation relevant genes-based model was established, showing that low-risk patients had longer overall survival time and may respond better to immunotherapy. CONCLUSIONS: The cellular composition, spatial location, molecular and functional changes in PT and TDLN microenvironments along with NSCLC progression were deciphered, highlighting the immunoregulatory roles and evolutionary heterogeneity of TANs.

Intratumoral tertiary lymphoid structure (TLS) maturation is influenced by draining lymph nodes of lung cancer.

BACKGROUND: Tertiary lymphoid structure (TLS) is an organized infiltration of immune cells, showing features of germinal center (GC) commonly seen in secondary lymphoid organs. However, its relationship with tumor-draining lymph nodes (TDLNs) has not been studied and we hypothesized that TDLN may influence maturation of intratumoral TLS in non-small cell lung cancer (NSCLC). METHODS: Tissue slides of 616 patients that had undergone surgeries were examined. Cox proportional hazard regression model was used to assess risk factors of patients' survival, and logistic regression model was used for their relationship with TLS. Single-cell RNA-sequencing (scRNA-seq) was employed to explore transcriptomic features of TDLNs. Immunohistochemistry, multiplex immunofluorescence and flow cytometry were performed to analyze cellular composition. Cellular components of NSCLC samples from The Cancer Genome Atlas database were inferred with Microenvironment Cell Populations-counter (MCP-counter) method. Murine NSCLC models were used to dissect underlying mechanisms for relationship between TDLN and TLS maturation. RESULTS: While GC+ TLS was associated with better prognosis, GC- TLS was not. TDLN metastasis reduced the prognostic relevance of TLS, and was associated with less GC formation. Primary tumor sites showed reduced B cell infiltration in TDLN-positive patients, and scRNA-seq revealed diminished memory B cell formation in tumor-invaded TDLNs, together with an emphasis on weakened interferon (IFN)-γ response. Murine NSCLC models revealed that IFN-γ signaling is involved in memory B cell differentiation in TDLNs and GC formation in primary tumors. CONCLUSIONS: Our research emphasizes the influence of TDLN on intratumoral TLS maturation and suggests a role of memory B cells and IFN-γ signaling in this communication.

Global trends in the burden of esophageal cancer, 1990-2019: results from the Global Burden of Disease Study 2019.

Background: Esophageal cancer is one of the leading causes of cancer death worldwide. A deeper understanding of the trends in annual incidence, mortality, and disability-adjusted life-years (DALYs) of esophageal cancer is critical for management and prevention. In this study, we report on the disease burden of esophageal cancer in 204 countries and territories between 1990 and 2019 by age, sex, and sociodemographic index (SDI). Methods: Data on incidence, mortality, and DALYs were extracted from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. The estimated numbers and age-standardized rates for esophageal cancer in 2019 are presented in this paper, as well as trends from 1990 to 2019. All estimates are presented as counts and age-standardized rates per 100,000 population, with 95% uncertainty intervals (UIs) for each estimate. Results: In 2019, nearly 535,000 (95% UI: 467,000-595,000) new cases of esophageal cancer occurred globally. Esophageal cancer was responsible for more than 498,000 (95% UI: 438,000-551,000) deaths and 11.7 million (95% UI: 10.4-12.9 million) DALYs. Worldwide age-standardized rates of esophageal cancer, including incidence, deaths, and DALYs, have declined since 1990. However, the trends differ across countries and territories. Notably, there was a nonlinear but generally inverse correlation between age-standardized DALY rates and SDI. Higher age-standardized incidence and death rates were observed in males compared to females, and both increased with age. Regarding risk factors, smoking, alcohol use, and high body-mass index were 3 predominant contributors to esophageal cancer DALYs in 2019 for both sexes worldwide. Conclusions: This study found a global reduction in the esophageal cancer burden, but substantial heterogeneity remains across regions and countries. Hence, the identification of high-risk groups and the exploration of specific local strategies and primary prevention efforts are required.

Risk mapping of lung cancer: a comprehensive appraisal of published meta-analyses incorporating Mendelian randomization studies.

INTRODUCTION: A comprehensive appraisal of published meta-analyses incorporating Mendelian randomization studies was performed to map the different risk factors and assess the causality for lung cancer. METHODS: Systematic reviews and meta-analyses of observational and interventional studies were reviewed based on PubMed, Embase, Web of Science, and Cochrane Library. Mendelian randomization analyses were conducted to validate the causal associations of those various exposures with lung cancer using summary statistics from 10 genome-wide association studies (GWAS) consortia and other GWAS databases in MR-Base platform. RESULTS: In the review of meta-analyses, 105 risk factors associated with lung cancer were identified from 93 articles. It was found that 72 risk factors were nominally significant (P < 0.05) associated with lung cancer. Mendelian randomization analyses were performed to analyze 36 exposures based on 551 SNPs and 4,944,052 individuals, finding that 3 exposures had a consistent risk/protective effect on lung cancer with the results of the meta-analysis. In Mendelian randomization anaylses, smoking (OR 1.44, 95% CI 1.18-1.75; P = 0.001) and blood copper (OR 1.14, 95% CI 1.01-1.29; P = 0.039) significantly associated with increased risk of lung cancer, whereas aspirin use (OR 0.67, 95% CI 0.50-0.89; P = 0.006) showed protective effects. CONCLUSION: This study mapped putative associations of risk factors for lung cancer, revealing the causal hazard effect of smoking, blood copper, and the protective effect of aspirin use in the development of lung cancer. CLINICAL TRIAL REGISTRY: This study is registered with PROSPERO (CRD42020159082).

Multiplex immunofluorescence and single-cell transcriptomic profiling reveal the spatial cell interaction networks in the non-small cell lung cancer microenvironment.

BACKGROUND: Conventional immunohistochemistry technologies were limited by the inability to simultaneously detect multiple markers and the lack of identifying spatial relationships among cells, hindering understanding of the biological processes in cancer immunology. METHODS: Tissue slices of primary tumours from 553 IA∼IIIB non-small cell lung cancer (NSCLC) cases were stained by multiplex immunofluorescence (mIF) assay for 10 markers, including CD4, CD38, CD20, FOXP3, CD66b, CD8, CD68, PD-L1, CD133 and CD163, evaluating the amounts of 26 phenotypes of cells in tumour nest and tumour stroma. StarDist depth learning model was utilised to determine the spatial location of cells based on mIF graphs. Single-cell RNA sequencing (scRNA-seq) on four primary NSCLC cases was conducted to investigate the putative cell interaction networks. RESULTS: Spatial proximity among CD20+ B cells, CD4+ T cells and CD38+ T cells (r2  = 0.41) was observed, whereas the distribution of regulatory T cells was associated with decreased infiltration levels of CD20+ B cells and CD38+ T cells (r2  = -0.45). Univariate Cox analyses identified closer proximity between CD8+ T cells predicted longer disease-free survival (DFS). In contrast, closer proximity between CD133+ cancer stem cells (CSCs), longer distances between CD4+ T cells and CD20+ B cells, CD4+ T cells and neutrophils, and CD20+ B cells and neutrophils were correlated with dismal DFS. Data from scRNA-seq further showed that spatially adjacent N1-like neutrophils could boost the proliferation and activation of T and B lymphocytes, whereas spatially neighbouring M2-like macrophages showed negative effects. An immune-related risk score (IRRS) system aggregating robust quantitative and spatial prognosticators showed that high-IRRS patients had significantly worse DFS than low-IRRS ones (HR 2.72, 95% CI 1.87-3.94, p < .001). CONCLUSIONS: We developed a framework to analyse the cell interaction networks in tumour microenvironment, revealing the spatial architecture and intricate interplays between immune and tumour cells.

Ankylosing Spondylitis and the Risk of Lung Cancer: A Meta-Analysis and Mendelian Randomization.

Background: It remains uncertain whether ankylosing spondylitis is associated with an increased risk of lung cancer. Methods: We conducted a meta-analysis to comprehensively evaluate the correlation between ankylosing spondylitis and lung cancer based on existing literature. Eligible studies were identified by searching the PubMed, Web of Science, Embase, and Cochrane Library before 26 March 2021. Subgroup analyses based on regions were also carried out. To further explore their causality, a two-sample Mendelian randomization analysis was performed, with 25 ankylosing spondylitis-related single nucleotide polymorphisms derived from the largest sample genome-wide association study of ankylosing spondylitis (ebi-a-GCST005529, 22,647 individuals). The inverse variance-weighted method was applied to estimate the causality, and the pleiotropy was assessed utilizing the Mendelian randomization-Egger regression approach. Results: The meta-analysis including seven studies, with a total of 39,186 individuals, suggested no significant association between ankylosing spondylitis and lung cancer (relative risk, 1.10; 95% confidence interval, 0.89-1.36; I2, 61.8%). After excluding one study leading to high heterogeneity, we found that ankylosing spondylitis was associated with a 19% increased risk of lung cancer (relative risk, 1.19; 95% confidence interval, 1.01-1.40; I2, 0.0%). Subgroup analyses suggested that ankylosing spondylitis was not associated with increased risks of lung cancer in neither European (relative risk, 1.05; 95% confidence interval, 0.80-1.39; I2, 0.0%) nor non-European (relative risk, 1.14; 95% confidence interval, 0.84-1.55; I2, 79.6%) patients. Nevertheless, the Mendelian randomization results indicated that genetically determined ankylosing spondylitis was causally correlated with a remarkably increased risk of lung cancer among European populations (odds ratio, 1.26; 95% confidence interval, 1.07-1.48). Subgroup analyses further elucidated that genetically determined ankylosing spondylitis was causally associated with a notably higher risk of only squamous cell lung cancer (odds ratio, 1.39; 95% confidence interval, 1.05-1.83), rather than lung adenocarcinoma (odds ratio, 1.18; 95% confidence interval, 0.91-1.54). In addition, the results indicated the absence of pleiotropy. Conclusion: The results of both modified meta-analysis and Mendelian randomization analysis suggested that ankylosing spondylitis was likely to be correlated with the development of lung cancer. Further research is warranted to clarify the specific mechanism regarding the causality between the two diseases.

Causal effects of genetically determined metabolites on cancers included lung, breast, ovarian cancer, and glioma: a Mendelian randomization study.

Background: Previous studies have shown that metabolites play important roles in phenotypic regulation, but the causal link between metabolites and tumors has not been examined adequately. Herein, we investigate the causality between metabolites and various cancers through a Mendelian randomization (MR) study. Methods: We carried out a two-sample MR analysis based on genetic instrumental variables as proxies for 486 selected human serum metabolites to evaluate the causal effects of genetically determined metabotypes (GDMs) on cancers. Summary data from various cancer types obtained from large consortia. Inverse variance weighted (IVW), MR-Egger and weighted-median methods were implemented to infer the causal effects, moreover, we particularly explored the presentence of horizontal pleiotropy through MR-Egger regression and MR-PRESSO Global test. Metabolic pathways analysis and subgroup analyses were further explored using available data. Statistical analyses were all performed in R. Results: In MR analysis, 202 significant causative relationship features were identified. 7-alpha-hydroxy-3-oxo-4-cholestenoate (ORIVW =1.45; 95% CI: 1.06-1.97; PIVW =0.018), gamma-glutamylisoleucine (ORIVW =1.40; 95% CI: 1.16-1.69; PIVW =0.0004), 1-oleoylglycerophosphocholine (ORIVW =1.22; 95% CI: 1.1-1.35; PIVW =0.0001), gamma-glutamylleucine (ORIVW =4.74; 95% CI: 1.18-18.93; PIVW =0.027) were the most dangerous metabolites for lung cancer, ovarian cancer, breast cancer, and glioma, respectively; while pseudouridine (ORIVW =0.50; 95% CI: 0.30-0.83; PIVW =0.007), 2-methylbutyroylcarnitine (ORIVW =0.77; 95% CI: 0.68-0.86; PIVW =2.9×10-6), 2-methylbutyroylcarnitine (ORIVW =0.77; 95% CI: 0.70-0.85; PIVW =3.4×10-7), glycylvaline (ORIVW =0.13; 95% CI: 0.02-0.75; PIVW =0.021) were associated with lower risk of lung cancer, ovarian cancer, breast cancer, and glioma, respectively. Interestingly, 2-methylbutyroylcarnitine was also associated with decreased risk of lung cancer (ORIVW =0.59; 0.50-0.70; P IVW =1.98×10-9) expect ovarian cancer and breast cancer. In subgroup analysis, 2-methylbutyroylcarnitine was associated with decreased risk of estrogen receptor (ER) positive breast cancer (ORIVW =0.72; 0.64-0.80; PIVW =3.55×10-9), lung adenocarcinoma (LAC) (ORIVW =0.60; 0.48-0.70; PIVW =1.14×10-5). Metabolic pathways analysis identified 4 significant pathways. Conclusions: Our study integrated metabolomics and genomics to explore the risk factors involved in the development of cancers. It is worth exploring whether metabolites with causality can be used as biomarkers to distinguish patients at high risk of cancer in clinical practice. More detailed studies are needed to clarify the mechanistic pathways.

Front-line treatment for advanced non-small-cell lung cancer and ALK fusion: a network meta-analysis.

Background: It remains unknown what is the optimal front-line choice for advanced non-small-cell lung cancer (NSCLC) with anaplastic lymphoma kinase (ALK) fusion. Methods: We conducted a systematic review and network meta-analysis of randomized phase III clinical trials comparing two or more treatments as the front-line setting for patients with advanced ALK-positive NSCLC. Results: Nine phase III randomized clinical trials with 2367 patients were included. As to efficacy, lorlatinib had the most favorable progression-free survival [PFS; surface under the cumulative ranking curve (SUCRA) = 98.4%] in the first-line setting, with noticeable outcome benefits versus chemotherapy [hazard ratio (HR): 0.12; 95% confidence interval (CI): 0.08-0.19], crizotinib (HR: 0.28; 95% CI: 0.19-0.41), ceritinib (HR: 0.22; 95% CI: 0.13-0.37), and brigatinib (HR: 0.58; 95% CI: 0.35-0.96), as well as beneficial trends when compared with alectinib (HR: 0.66; 95% CI: 0.41-1.04) and ensartinib (HR: 0.62; 95% CI: 0.36-1.08). Meanwhile, alectinib showed the optimal overall survival (OS; SUCRA = 91.2%), with significant improvements over chemotherapy (HR: 0.47; 95% CI: 0.30-0.72) and crizotinib (HR: 0.58; 95% CI: 0.41-0.82). Similarly, brigatinib also displayed prolonged OS compared with crizotinib after adjustment for crossover by the marginal structural model (HR: 0.54; 95% CI: 0.31-0.92). In terms of safety, alectinib had the fewest grade 3-5 adverse events (SUCRA = 98.9%), with marked advantages versus crizotinib [odds ratio (OR): 0.67; 95% CI: 0.46-0.97], ceritinib (OR: 0.21; 95% CI: 0.10-0.43), brigatinib (OR: 0.37; 95% CI: 0.20-0.69), ensartinib (OR: 0.48; 95% CI: 0.27-0.89), and lorlatinib (OR: 0.30; 95% CI: 0.16-0.54). Conclusions: Lorlatinib may have advantageous PFS compared with other agents but a greater risk of severe toxicity. Second-generation inhibitors, including alectinib, brigatinib, and ensartinib, provide major efficacy with less toxicity and remain appropriate regimens in the front-line setting.

Macrophages-based immune-related risk score model for relapse prediction in stage I-III non-small cell lung cancer assessed by multiplex immunofluorescence.

Background: Macrophages are critical players in regulating innate and adaptive immunity in the tumor microenvironment (TME). The prognostic value of macrophages and their heterogeneous phenotypes in non-small cell lung cancer (NSCLC) is still uncertain. Methods: Surgically-resected samples of 681 NSCLC cases were stained by multiplex immunofluorescence to examine macrophage phenotypes as well as the expression levels of program death-ligand 1 (PD-L1) on them in both tumor nest and tumor stroma, including pan-macrophage (CD68+), M1 (CD68+CD163-), and M2 macrophages (CD68+CD163+). Various other immune cell markers, including CD4, CD8, CD20, CD38, CD66B, FOXP3, and CD133, were also evaluated. Machine learning algorithm by Random Forest (RF) model was utilized to screen the robust prognostic markers and construct the CD68-based immune-related risk score (IRRS) for predicting disease-free survival (DFS). Results: The expression levels of CD68 were moderately correlated with the levels of PD-L1 (P<0.001), CD133 (P<0.001), and CD8 (P<0.001). Higher levels of CD68 (OR 1.03, 95% CI: 1.01-1.05, P<0.001) as well as M1 macrophage (OR 1.04, 95% CI: 1.01-1.06, P<0.001) indicated shorter DFS. Despite without statiscial significance, intratumoral M2 macrophage (OR 1.05, 95% CI: 0.99-1.10, P=0.081) was also associated with worse DFS. IRRS incorporating three intratumoral CD68-related markers and four intrastromal markers was constructed and validated to predict recurrence (high-risk group vs. low-risk group: OR 2.52, 95% CI: 1.89-3.38, P<0.001). The IRRS model showed good accuracy [area under the curve (AUC) =0.670, 0.709, 0.695, 0.718 for 1-, 3-, 5-year, and overall DFS survival, respectively] and the predictive performance was better than the single-marker model (area under the curve 0.718 vs. 0.500-0.654). A nomogram based on clinical characteristics and IRRS for relapse prediction was then established and exhibited better performance than the tumor-node-metastasis (TNM) classification and IRRS system (C-index 0.76 vs. 0.69 vs. 0.60, 0.74 vs. 0.67 vs. 0.60, 0.81 vs. 0.74 vs. 0.60 of the entire, training, testing cohort, respectively). Conclusions: Our study suggested close interactions between CD68 and other immune markers in TME, demonstrating the prognostic value of CD68 in relapse prediction in resectable NSCLC.

Plasma Circulating Vitamin C Levels and Risk of Endometrial Cancer: A Bi-Directional Mendelian Randomization Analysis.

Background: Observational studies indicated that circulating vitamin C (VitC) levels may be correlated with the risk of endometrial cancer (EC). However, the causal effects and direction between them were still unclear. Methods: In this study, 11 single nucleotide polymorphisms (SNPs) robustly correlated with plasma VitC levels were extracted from the latest genome-wide association study (GWAS), containing 52,018 individuals. Genetic data of EC were obtained from the Endometrial Cancer Association Consortium (ECAC) (12,906 cases and 108,979 controls). An inverse-variance weighted method was utilized as the primary analysis of Mendelian randomization (MR), supplemented by the weighted median, MR Pleiotropy Residual Sum and Outlier test (MR-PRESSO), and MR-Egger methods. Additional sensitivity analyses excluding 3 SNPs with secondary phenotypes were conducted to rule out the possible pleiotropic effects. Potential impacts of several risk factors of EC, such as obesity, body mass index (BMI), hypertension, and diabetes on VitC levels, were assessed. We additionally evaluated the effects of VitC on LDL cholesterol levels, HDL cholesterol levels, and triglycerides levels to probe into the possible mediators in the VitC-EC pathway. Results: Genetically predicted higher plasma VitC levels (per 1 SD increase, approximately 20 µmol/L) were causally associated with an increased risk of EC overall [odds ratio (OR) 1.374, 95% CI 1.128-1.674, p = 0.0016], supported by complementary sensitivity analyses. In the subgroup analyses, genetically predicted higher levels of VitC were associated with a tendency of increased risks of both endometrioid (OR SD 1.324, 95% CI 0.959-1.829, p = 0.0881) and non-endometrioid histology (OR SD 1.392, 95% CI 0.873-2.220, p = 0.1647) while without statistical significance. The association remained significant after the exclusion of the three pleiotropic SNPs (OR SD 1.394, 95% CI 1.090-1.784, p = 0.0082). The confounders and mediators were unlikely to affect the VitC-EC relationship. The causal effect of EC on VitC levels was not supported (OR 1.001, 95% CI 0.998-1.004, p = 0.4468). Conclusions: This bi-directional MR study demonstrated a causal risk role of higher circulating VitC at physiological levels on an increased risk of EC, which was independent of confounders and mediators. Further studies are warranted to elucidate the possible mechanisms.

Myocardial infarction and stroke risks in multiple sclerosis patients: A two-sample Mendelian randomization study.

Observational studies indicated multiple sclerosis (MS) patients may have a higher risk of myocardial infarction (MI) and stroke than the general population, whereas the previously reported findings were inconsistent. Using two-sample Mendelian randomization (MR) analysis with genetic data from large-scale genome-wide association studies (International Multiple Sclerosis Genetics Consortium containing 14,498 MS cases, Coronary ARtery DIsease Genome wide Replication and Meta-analysis plus The Coronary Artery Disease Genetics consortium containing 43,676 MI cases and 40,585 stroke cases), we found that MS was causally associated with an increased risk of MI (OR = 1.03; 95%CI 1.00-1.06; P = 0.0243), directionally consistent in the weighted median, MR-Egger, and the MR-PRESSO methods. No causal association between MS and stroke was observed (OR = 1.01; 95%CI 0.99-1.04; P = 0.2974). Therefore, timelier and more effective measures should be conducted among MS patients to decrease the burden of both diseases.

Univariable and Multivariable Two-Sample Mendelian Randomization Investigating the Effects of Leisure Sedentary Behaviors on the Risk of Lung Cancer.

Leisure sedentary behaviors (LSB) are widespread, and observational studies have provided emerging evidence that LSB play a role in the development of lung cancer (LC). However, the causal inference between LSB and LC remains unknown. Methods: We utilized univariable (UVMR) and multivariable two-sample Mendelian randomization (MVMR) analysis to disentangle the effects of LSB on the risk of LC. MR analysis was conducted with genetic variants from genome-wide association studies of LSB (408,815 persons from UK Biobank), containing 152 single-nucleotide polymorphisms (SNPs) for television (TV) watching, 37 SNPs for computer use, and four SNPs for driving, and LC from the International Lung Cancer Consortium (11,348 cases and 15,861 controls). Multiple sensitivity analyses were further performed to verify the causality. Results: UVMR demonstrated that genetically predisposed 1.5-h increase in LSB spent on watching TV increased the odds of LC by 90% [odds ratio (OR), 1.90; 95% confidence interval (CI), 1.44-2.50; p < 0.001]. Similar trends were observed for squamous cell lung cancer (OR, 1.97; 95%CI, 1.31-2.94; p = 0.0010) and lung adenocarcinoma (OR, 1.64; 95%CI 1.12-2.39; p = 0.0110). The causal effects remained significant after adjusting for education (OR, 1.97; 95%CI, 1.44-2.68; p < 0.001) and body mass index (OR, 1.86; 95%CI, 1.36-2.54; p < 0.001) through MVMR approach. No association was found between prolonged LSB spent on computer use and driving and LC risk. Genetically predisposed prolonged LSB was additionally correlated with smoking (OR, 1.557; 95%CI, 1.287-1.884; p < 0.001) and alcohol consumption (OR, 1.010; 95%CI, 1.004-1.016; p = 0.0016). Consistency of results across complementary sensitivity MR methods further strengthened the causality. Conclusion: Robust evidence was demonstrated for an independent, causal effect of LSB spent on watching TV in increasing the risk of LC. Further work is necessary to investigate the potential mechanisms.

Profiling Tumor Immune Microenvironment of Non-Small Cell Lung Cancer Using Multiplex Immunofluorescence.

This study attempted to profile the tumor immune microenvironment (TIME) of non-small cell lung cancer (NSCLC) by multiplex immunofluorescence of 681 NSCLC cases. The number, density, and proportion of 26 types of immune cells in tumor nest and tumor stroma were evaluated, revealing some close interactions particularly between intrastromal neutrophils and intratumoral regulatory T cells (Treg) (r2 = 0.439, P < 0.001), intrastromal CD4+CD38+ T cells and CD20-positive B cells (r2 = 0.539, P < 0.001), and intratumoral CD8-positive T cells and M2 macrophages expressing PD-L1 (r2 = 0.339, P < 0.001). Three immune subtypes correlated with distinct immune characteristics were identified using the unsupervised consensus clustering approach. The immune-activated subtype had the longest disease-free survival (DFS) and demonstrated the highest infiltration of CD4-positive T cells, CD8-positive T cells, and CD20-positive B cells. The immune-defected subtype was rich in cancer stem cells and macrophages, and these patients had the worst prognosis. The immune-exempted subtype had the highest levels of neutrophils and Tregs. Intratumoral CD68-positive macrophages, M1 macrophages, and intrastromal CD4+ cells, CD4+FOXP3- cells, CD8+ cells, and PD-L1+ cells were further found to be the most robust prognostic biomarkers for DFS, which were used to construct and validate the immune-related risk score for risk stratification (high vs. median vs. low) and the prediction of 5-year DFS rates (23.2% vs. 37.9% vs. 43.1%, P < 0.001). In conclusion, the intricate and intrinsic structure of TIME in NSCLC was demonstrated, showing potency in subtyping and prognostication.

Plasma circulating vitamin C levels and risk of multiple sclerosis: a two-sample Mendelian randomization analysis.

Whether vitamin C (VitC) supplementation can decrease multiple sclerosis (MS) risk remains controversial. Using data from large-scale genome-wide association studies, we conducted a two-sample Mendelian randomization (MR) analysis to evaluate the causal relationship between plasma circulating VitC levels and MS comprehensively. MR analysis did not support the causality between genetically determined per 1 standard deviation increase (around 20 mmol/L) in circulating VitC levels and MS risk (OR 0.88, 95%CI 0.65-1.18, P = 0.3822), supported by complementary sensitivity analyses, including the weighted median, MR-Egger, and MR Pleiotropy Residual Sum and Outlier test methods.

Genetically predicted insomnia and lung cancer risk: a Mendelian randomization study.

BACKGROUND: The relationship between insomnia and lung cancer is scanty. The Mendelian randomization approach provides the rationale for evaluating the potential causality between genetically-predicted insomnia and lung cancer risk. METHODS: We extracted 148 insomnia-related single-nucleotide polymorphisms (SNPs) as instrumental variables (IVs) from published genome-wide association studies (GWASs). Summary data of individual-level genetic information of participants were obtained from the International Lung Cancer Consortium (ILCCO) (29,266 cases and 56,450 controls). MR analyses were performed using the inverse-variance-weighted approach, MR pleiotropy residual sum and outlier (MR-PRESSO) test, weighted median estimator, and MR-Egger regression. Sensitivity analyses were further performed using Egger intercept analysis, leave-one-out analysis, MR-PRESSO global test, and Cochran's Q test to verify the robustness of our findings. RESULTS: The results of the MR analysis indicated an increased risk of lung cancer in insomnia patients (OR = 1.1671; 95% CI 1.0754-1.2666, p = 0.0002). The subgroup analyses showed increased risks of lung adenocarcinoma (OR = 1.1878; 95% CI 1.0594-1.3317, p = 0.0032) and squamous cell lung cancer (OR = 1.1595; 95% CI 1.0248-1.3119, p = 0.0188). CONCLUSION: Our study indicated that insomnia is a causal risk factor in the development of lung cancer. Due to the lack of evidence on both the epidemiology and the mechanism level, more studies are needed to better elucidate the results of the study.