Causal relationship between gut microbiota and gynecological tumor: a two-sample Mendelian randomization study.

Introduction: Previous research has established associations between alterations in gut microbiota composition and various gynecologic tumors. However, establishing a causal relationship between gut microbiota and these tumors remains necessary. This study employs a two-sample Mendelian randomization (MR) approach to investigate causality, aiming to identify pathogenic bacterial communities potentially involved in gynecologic tumor development. Methods: Data from the MiBioGen consortium's Genome-Wide Association Study (GWAS) on gut microbiota were used as the exposure variable. Four common gynecologic neoplasms, including uterine fibroids (UF), endometrial cancer (EC), ovarian cancer (OC), and cervical cancer (CC), were selected as outcome variables. Single-nucleotide polymorphisms (SNPs) significantly associated with gut microbiota were chosen as instrumental variables (IVs). The inverse variance-weighted (IVW) method was used as the primary MR analysis to assess the causal relationship. External validation An was conducted using an independent. Sensitivity analyses were performed to ensure robustness. Reverse MR analysis was also conducted to assess potential reverse causation. Results: Combining discovery and validation cohorts, we found that higher relative abundance of Lachnospiraceae is associated with lower UF risk (OR: 0.882, 95% CI: 0.793-0.982, P = 0.022). Conversely, higher OC incidence is associated with increased relative abundance of Lachnospiraceae (OR: 1.329, 95% CI: 1.019-1.732, P = 0.036). Sensitivity analyses confirmed these findings' reliability. Reverse MR analysis showed no evidence of reverse causation between UF, OC, and Lachnospiraceae. Discussion: This study establishes a causal relationship between Lachnospiraceae relative abundance and both UF and OC. These findings provide new insights into the potential role of gut microbiota in mechanisms underlying gynecological tumors development.

IL20Rb aggravates pulmonary fibrosis through enhancing bone marrow derived profibrotic macrophage activation.

Idiopathic pulmonary fibrosis (IPF) is one of the most fatal chronic interstitial lung diseases with unknown pathogenesis, current treatments cannot truly reverse the progression of the disease. Pulmonary macrophages, especially bone marrow derived pro-fibrotic macrophages, secrete multiple kinds of profibrotic mediators (SPP1, CD206, CD163, IL-10, CCL18…), thus further promote myofibroblast activation and fibrosis procession. IL20Rb is a cell-surface receptor that belongs to IL-20 family. The role of IL20Rb in macrophage activation and pulmonary fibrosis remains unclear. In this study, we established a bleomycin-induced pulmonary fibrosis model, used IL4/13-inducing THP1 cells to induce profibrotic macrophage (M2-like phenotype) polarization models. We found that IL20Rb is upregulated in the progression of pulmonary fibrosis, and its absence can alleviate the progression of pulmonary fibrosis. In addition, we demonstrated that IL20Rb promote the activation of bone marrow derived profibrotic macrophages by regulating the Jak2/Stat3 and Pi3k/Akt signaling pathways. In terms of therapeutic strategy, we used IL20Rb neutralizing antibodies for animal administration, which was found to alleviate the progression of IPF. Our results suggest that IL20Rb plays a profibrotic role by promoting profibrotic macrophage polarization, and IL20Rb may become a potential therapeutic target for IPF. Neutralizing antibodies against IL20Rb may become a potential drug for the clinical treatment of IPF.

Exploring the optimal indicator of short-term peridiagnosis weight dynamics to predict cancer survival: A multicentre cohort study.

BACKGROUND: Body weight and its changes have been associated with cancer outcomes. However, the associations of short-term peridiagnosis weight dynamics in standardized, clinically operational time frames with cancer survival remain largely unknown. This study aimed to screen for and evaluate the optimal indicator of short-term peridiagnosis weight dynamics to predict overall survival (OS) in patients with cancer. METHODS: This multicentre cohort study prospectively collected data from 7460 patients pathologically diagnosed with cancer between 2013 and 2019. Body weight data were recorded 1 month before, at the time of and 1 month following diagnosis. By permuting different types (point value in kg, point height-adjusted value in kg/m2, absolute change in kg or relative change in percentage) and time frames (prediagnosis, postdiagnosis or peridiagnosis), we generated 12 different weight-related indicators and compared their prognostic performance using Harrell's C-index, integrated discrimination improvement, continuous net reclassification improvement and time-dependent C-index. We analysed associations of peridiagnosis relative weight change (RWC) with OS using restricted cubic spine (RCS), Kaplan-Meier analysis and multivariable-adjusted Cox regression models. RESULTS: The study enrolled 5012 males and 2448 females, with a median age of 59 years. During a median follow-up of 37 months, 1026 deaths occurred. Peridiagnosis (1 month before diagnosis to 1 month following diagnosis) RWC showed higher prognostic performance (Harrell's C-index = 0.601, 95% confidence interval [CI] = [0.583, 0.619]) than other types of indicators including body mass index (BMI), absolute weight change, absolute BMI change, prediagnosis RWC and postdiagnosis RWC in the study population (all P < 0.05). Time-dependent C-index analysis also indicated that peridiagnosis RWC was optimal for predicting OS. The multivariable-adjusted RCS analysis revealed an N-shaped non-linear association between peridiagnosis RWC and OS (PRWC < 0.001, Pnon-linear < 0.001). Univariate survival analysis showed that the peridiagnosis RWC groups could represent distinct mortality risk stratifications (P < 0.001). Multivariable survival analysis showed that, compared with the maintenance group (weight change < 5%), the significant (gain >10%, hazard ratio [HR] = 0.530, 95% CI = [0.413, 0.680]) and moderate (gain 5-10%, HR = 0.588, 95% CI = [0.422, 0.819]) weight gain groups were both associated with improved OS. In contrast, the moderate (loss 5-10%, HR = 1.219, 95% CI = [1.029, 1.443]) and significant (loss >10%, HR = 1.280, 95% CI = [1.095, 1.497]) weight loss groups were both associated with poorer OS. CONCLUSIONS: The prognostic performance of peridiagnosis RWC is superior to other weight-related indicators in patients with cancer. The findings underscore the importance of expanding the surveillance of body weight from at diagnosis to both past and future, and conducting it within clinically operational time frames, in order to identify and intervene with patients who are at risk of weight change-related premature deaths.

Systematic proteome-wide Mendelian randomization using the human plasma proteome to identify therapeutic targets for lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is the predominant histological subtype of lung cancer and the leading cause of cancer-related mortality. Identifying effective drug targets is crucial for advancing LUAD treatment strategies. METHODS: This study employed proteome-wide Mendelian randomization (MR) and colocalization analyses. We collected data on 1394 plasma proteins from a protein quantitative trait loci (pQTL) study involving 4907 individuals. Genetic associations with LUAD were derived from the Transdisciplinary Research in Cancer of the Lung (TRICL) study, including 11,245 cases and 54,619 controls. We integrated pQTL and LUAD genome-wide association studies (GWASs) data to identify candidate proteins. MR utilizes single nucleotide polymorphisms (SNPs) as genetic instruments to estimate the causal effect of exposure on outcome, while Bayesian colocalization analysis determines the probability of shared causal genetic variants between traits. Our study applied these methods to assess causality between plasma proteins and LUAD. Furthermore, we employed a two-step MR to quantify the proportion of risk factors mediated by proteins on LUAD. Finally, protein-protein interaction (PPI) analysis elucidated potential links between proteins and current LUAD medications. RESULTS: We identified nine plasma proteins significantly associated with LUAD. Increased levels of ALAD, FLT1, ICAM5, and VWC2 exhibited protective effects, with odds ratios of 0.79 (95% CI 0.72-0.87), 0.39 (95% CI 0.28-0.55), 0.91 (95% CI 0.72-0.87), and 0.85 (95% CI 0.79-0.92), respectively. Conversely, MDGA2 (OR, 1.13; 95% CI 1.08-1.19), NTM (OR, 1.12; 95% CI 1.09-1.16), PMM2 (OR, 1.35; 95% CI 1.18-1.53), RNASET2 (OR, 1.15; 95% CI 1.08-1.21), and TFPI (OR, 4.58; 95% CI 3.02-6.94) increased LUAD risk. Notably, none of the nine proteins showed evidence of reverse causality. Bayesian colocalization indicated that RNASET2, TFPI, and VWC2 shared the same variant with LUAD. Furthermore, NTM and FLT1 demonstrated interactions with targets of current LUAD medications. Additionally, FLT1 and TFPI are currently under evaluation as therapeutic targets, while NTM, RNASET2, and VWC2 are potentially druggable. These findings shed light on LUAD pathogenesis, highlighting the tumor-promoting effects of RNASET2, TFPI, and NTM, along with the protective effects of VWC2 and FLT1, providing a significant biological foundation for future LUAD therapeutic targets. CONCLUSIONS: Our proteome-wide MR analysis highlighted RNASET2, TFPI, VWC2, NTM, and FLT1 as potential drug targets for further clinical investigation in LUAD. However, the specific mechanisms by which these proteins influence LUAD remain elusive. Targeting these proteins in drug development holds the potential for successful clinical trials, providing a pathway to prioritize and reduce costs in LUAD therapeutics.

MICAL2 implies immunosuppressive features and acts as an independent and adverse prognostic biomarker in pancreatic cancer.

At present, clinical outcomes of pancreatic cancer patients are still poor. New therapeutic targets for pancreatic cancer are urgently needed. Previous studies have indicated that Microtubule Associated Monooxygenase, Calponin and LIM Domain Containing 2 (MICAL2) is highly expressed in many tumors and promotes tumor progression. However, the role played by MICAL2 in pancreatic cancer remains unclear. Based on gene expression and clinical information from multiple datasets, we used comprehensive bioinformatics analysis in combination with tissue microarray to explore the function and clinical value of MICAL2. The results showed that MICAL2 was highly expressed in pancreatic cancer tissue and exhibited potential diagnostic capability. High expression of MICAL2 was also associated with poor prognosis and acted as an independent prognostic factor. MICAL2, mainly expressed in fibroblasts of pancreatic cancer, was closely related to metastasis and immune-related features, such as epithelial-mesenchymal transformation, extracellular cell matrix degradation, and inflammatory response. Furthermore, higher MICAL2 expression in pancreatic cancer was also associated with an increase in cancer-associated fibroblasts as well as M2 macrophage infiltration, and a reduction in CD8 + T cell infiltration, thereby facilitating the formation of an immunosuppressive microenvironment. Our results helped elucidate the clinical value and function in metastasis and immunity of MICAL2 in pancreatic cancer. These findings provided potential clinical strategies for diagnosis, targeted therapy combination immunotherapy, and prognosis in patients with pancreatic cancer.