The Function of RhoA/ROCK Pathway and MYOCD in Airway Remodeling in Asthma.

INTRODUCTION: Asthma is a common chronic respiratory disease characterized by chronic airway inflammation and abnormal airway remodeling. The RhoA/ROCK pathway and myocardin-related transcription factor A (MRTF-A) demonstrate significant associations with the proliferation of airway smooth muscle cells (ASCMs), which tightly correlates with the process of airway remodeling. MYOCD, which is homologous to MRTF-A but specifically expressed in smooth muscle cells, potentially regulates RhoA/ROCK activated cell proliferation and subsequent airway remodeling. METHODS: The RhoA/ROCK overexpression and silencing cell lines were constructed in vitro, as well as MYOCD overexpression/silencing. The cytoskeleton alterations induced by RhoA/ROCK pathway were identified by the measuring of globular actin and filamentous actin. RESULTS: The comparison between controls for overexpression/silencing and ROCK overexpression/silencing revealed that MYOCD presented consistent change trends with cytoskeleton and RhoA/ROCK pathway. The ROCK1 facilitates the proliferation and migration of ASCMs. The MYOCD enhanced the proliferation and migration of HASMCs. CONCLUSION: Our study indicates that Rho/ROCK/MYOCD is a key pathway involved in the migration and proliferation of airway smooth muscle cells. Inhibition of Rho/ROCK may be an effective approach to breaking the vicious cycle of asthmatic ASCMs proliferation, providing a novel strategy in treating asthma airway remodeling.

PEX26 Functions as a Metastasis Suppressor in Colorectal Cancer.

BACKGROUND/AIMS: Aberrant Peroxisomal Biogenesis Factor 26 (PEX26) occurs in multiple cell process. However, the role of PEX26 in colorectal cancer (CRC) development remains unknown. We aimed to study PEX26 expression, regulation, and function in CRC cells. METHODS: Using the bioinformatic analysis, real-time quantitative PCR, and immunohistochemistry staining, we detected the expression of PEX26 in CRC and normal tissues. We performed functional experiments in vitro to elucidate the effect of PEX26 on CRC cells. We analyzed the RNA-seq data to reveal the downstream regulating network of PEX26. RESULTS: PEX26 is significantly down-regulated in CRC and its low expression correlates with the poor overall survival of CRC patients. We further demonstrated that PEX26 over-expression inhibits the ability of CRC cell migration, invasion, and epithelial-mesenchymal transition (EMT), while PEX26 knockdown promotes the malignant phenotypes of migration, invasion, and EMT via activating the Wnt pathway. CONCLUSION: Overall, our results showed that the loss of PEX26 contributes to the malignant phenotype of CRC. PEX26 may serve as a novel metastasis repressor for CRC.

Effect of knee osteoarthritis on the postoperative outcome of proximal femoral nail anti-rotation in the treatment of intertrochanteric fractures in the elderly: a retrospective analysis.

BACKGROUND: The proximal femoral nail anti-rotation (PFNA) is a commonly used internal fixation system for intertrochanteric fractures (IFs) in older adults. Knee osteoarthritis (KOA) is a degenerative lower extremity disease that occurs most frequently in the elderly. Some patients have already had KOA before the IFs. However, whether KOA impacts the postoperative outcome of IFs has not been reported. OBJECTIVE: This study aimed to investigate the effect of KOA on the fracture side on the outcome after PFNA for IFs in the elderly. METHODS: Between January 2016 and November 2021, 297 elderly patients treated with PFNA for IFs were enrolled in this study. They were divided into two groups according to the American Rheumatism Association KOA clinical and radiographic criteria: the control group and the KOA group. Intraoperative bleeding, operative time, length of hospital stay, postoperative time out of bed, fracture healing time, postoperative complications, postoperative Harris hip function score, and Barthel ability to daily living Score were compared between the two groups. Follow-up was routinely scheduled at 1, 3, 6, and 12 months postoperatively. RESULTS: Based on the exclusion criteria, 254 patients who met the requirements were left to be included in this study, including the control group (n = 133) and the KOA group (n = 121). Patients were followed up for a mean of 17.5 months (12-24 months). There was no significant difference between the two groups in preoperative demographic data, intraoperative blood loss, operation time, and length of stay in the hospital. The control group was statistically significant compared to the KOA group in terms of postoperative time out of bed (17.8 ± 4.0 days vs. 19.1 ± 5.8 days), fracture healing time (13.7 ± 2.2 weeks vs. 14.6 ± 3.7 weeks), and postoperative complications (12.8 vs. 23.1%). The Harris hip function score and Barthel ability to daily living score were higher in the control group than in the KOA group at 1, 3, 6, and 12 months postoperatively (the control group: 63.8 ± 10.9, 71.8 ± 10.3, 81.5 ± 8.7, and 91.6 ± 6.3 vs. The KOA group 61.0 ± 10.4, 68.6 ± 9.1, 79.0 ± 9.2, and 88.5 ± 5.9). CONCLUSIONS: In elderly patients with IFs combined with KOA of the fracture side treated with PFNA internal fixation, KOA increases the incidence of postoperative complications of the fracture, prolongs postoperative time out of bed and fracture healing, and reduces postoperative hip function and ability to daily living. Therefore, treating KOA on the fractured side needs to be considered when treating IFs in the elderly.

Construction of a novel methylation-related prognostic model for colorectal cancer based on microsatellite status.

The present study aimed to construct a novel methylation-related prognostic model based on microsatellite status that may enhance the prognosis of colorectal cancer (CRC) from methylation and microsatellite status perspective. DNA methylation and mRNA expression data with clinical information were downloaded from The Cancer Genome Atlas (TCGA) data set. The samples were divided into microsatellite stability and microsatellite instability group, and CIBERSORT was used to assess the immune cell infiltration characteristics. After identifying the differentially methylated genes and differentially expression genes using R packages, the methylation-driven genes were further identified. Prognostic genes that were used to establish the methylation-related risk score model were generated by the univariate and multivariate Cox regression model. Finally, we established and evaluated the methylation-related prognostic model for CRC patients. A total of 69 MDGs were obtained and three of these genes (MIOX, TH, DKFZP434K028) were selected to construct the prognostic model. Patients in the low-risk score group had a conspicuously better overall survival than those in the high-risk score group (p < .0001). The area under the receiver operating characteristic curve for this model was 0.689 at 3 years, 0.674 at 4 years, and 0.658 at 5 years. The Wilcoxon test showed that higher risk score was associated with higher T stage (p = .01), N stages (p = .0028), metastasis (p = .013), and advanced pathological stage (p = .0013). However, the more instability of microsatellite status, the lower risk score of CRC patients (p = .0048). Our constructed methylation-related prognostic model based on microsatellite status presents potential significance in assessing recurrence risk stratification, tumor staging, and immunotherapy for CRC patients.

Exploration of bacterial lipopolysaccharide-related genes signature based on T cells for predicting prognosis in colorectal cancer.

PURPOSE: The intratumoral microorganisms participates in the progression and immunotherapy of colorectal cancer (CRC). However, due to technical limitations, the impact of microorganisms on CRC has not been fully understood. Therefore, we conducted a systematic analysis of relationship between bacterial lipopolysaccharide (LPS)-associated genes and immune cells to explore new biomarkers for predicting the prognosis of CRC. METHODS: The single-cell RNA sequencing data and the Comparative Toxicogenomics Database were used to screen T cells-associated LPS-related genes (TALRGs). Then, we established and validated the TALRGs risk signature in The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD) cohort and GSE39582 cohort. Besides, we compared the differences in tumor-infiltrating immune cell types, immunotherapeutic response, somatic mutation profiles, and tumor mutation burden (TMB) between high-risk group and low-risk group. In addition, the immunotherapeutic cohort (Imvigor210) treated with an anti-PD-L1 agent was performed to explore the potential value of the TALRGs signature on immunotherapy. RESULTS: Five prognostic TALRGs were identified and selected to build the prognostic model. The high-risk group had poor prognosis in both TCGA-COAD cohort (P < 0.0001) and GSE39582 cohort (P = 0.00019). The areas under the curves (AUCs) of TALRGs signature were calculated (TCGA-COAD cohort: 0.624 at 1 years, 0.639 at 3 years, 0.648 at 5 years; anti-PD-L1 cohort was 0.59). The high-risk group had advanced pathological stages and higher TMN stages in both TCGA-COAD cohort and GSE39582 cohort. The high-risk group had the higher infiltration of immunosuppressive cells, the expressions of immune checkpoint molecules, the IC50 values of chemotherapy drugs, and TP53 mutation rate (P < 0.05). In addition, patients with high TMB had worse prognosis (P < 0.05). Furthermore, the Imvigor210 also showed patients with high-risk scores had poor prognosis (platinum-treated cohort: P = 0.0032; non-platinum-treated cohort: P = 0.00017). CONCLUSIONS: Microorganisms are closely related to the tumor microenvironment to influence the progression and immune response of CRC via stimulating T cells through LPS-related genes. The TALRGs signature contributed to predict the prognosis and immunotherapy of CRC, and became new therapeutic targets and biomarkers of CRC.

Identifying important microbial biomarkers for the diagnosis of colon cancer using a random forest approach.

Colon cancer is one of the most common cancers, with 30-50 % of patients returning or metastasizing within 5 years of treatment. Increasingly, researchers have highlighted the influence of microbes on cancer malignant activity, while no studies have explored the relationship between colon cancer and the microbes in tumors. Here, we used tissue and blood samples from 67 colon cancer patients to identify pathogenic microorganisms associated with the diagnosis and prediction of colon cancer and evaluate the predictive performance of each pathogenic marker and its combination based on the next-generation sequencing data by using random forest algorithms. The results showed that we constructed a database of 13,187 pathogenic microorganisms associated with human disease and identified 2 pathogenic microorganisms (Synthetic.construct_32630 and Dicrocoelium.dendriticum_57078) associated with colon cancer diagnosis, and the constructed diagnostic prediction model performed well for tumor tissue samples and blood samples. In summary, for the first time, we provide new molecular markers for the diagnosis of colon cancer based on the expression of pathogenic microorganisms in order to provide a reference for improving the effective screening rate of colon cancer in clinical practice and ameliorating the personalized treatment of colon cancer patients.

Prognostic cellular senescence-related lncRNAs patterns to predict clinical outcome and immune response in colon cancer.

Background: Cellular senescence (CS) is believed to be a major factor in the evolution of cancer. However, CS-related lncRNAs (CSRLs) involved in colon cancer regulation are not fully understood. Our goal was to create a novel CSRLs prognostic model for predicting prognosis and immunotherapy and exploring its potential molecular function in colon cancer. Methods: The mRNA sequencing data and relevant clinical information of GDC TCGA Colon Cancer (TCGA-COAD) were obtained from UCSC Xena platform, and CS-associated genes was acquired from the CellAge website. Pearson correlation analysis was used to identify CSRLs. Then we used Kaplan-Meier survival curve analysis and univariate Cox analysis to acquire prognostic CSRL. Next, we created a CSRLs prognostic model using LASSO and multivariate Cox analysis, and evaluated its prognostic power by Kaplan-Meier and ROC curve analysis. Besides, we explored the difference in tumor microenvironment, somatic mutation, immunotherapy, and drug sensitivity between high-risk and low-risk groups. Finally, we verified the functions of MYOSLID in cell experiments. Results: Three CSRLs (AC025165.1, LINC02257 and MYOSLID) were identified as prognostic CSRLs. The prognostic model exhibited a powerful predictive ability for overall survival and clinicopathological features in colon cancer. Moreover, there was a significant difference in the proportion of immune cells and the expression of immunosuppressive point biomarkers between the different groups. The high-risk group benefited from the chemotherapy drugs, such as Teniposide and Mitoxantrone. Finally, cell proliferation and CS were suppressed after MYOSLID knockdown. Conclusion: CSRLs are promising biomarkers to forecast survival and therapeutic responses in colon cancer patients. Furthermore, MYOSLID, one of 3-CSRLs in the prognostic model, could dramatically regulate the proliferation and CS of colon cancer.

Direct prediction of antimicrobial resistance in Pseudomonas aeruginosa by metagenomic next-generation sequencing.

Objective: Pseudomonas aeruginosa has strong drug resistance and can tolerate a variety of antibiotics, which is a major problem in the management of antibiotic-resistant infections. Direct prediction of multi-drug resistance (MDR) resistance phenotypes of P. aeruginosa isolates and clinical samples by genotype is helpful for timely antibiotic treatment. Methods: In the study, whole genome sequencing (WGS) data of 494 P. aeruginosa isolates were used to screen key anti-microbial resistance (AMR)-associated genes related to imipenem (IPM), meropenem (MEM), piperacillin/tazobactam (TZP), and levofloxacin (LVFX) resistance in P. aeruginosa by comparing genes with copy number differences between resistance and sensitive strains. Subsequently, for the direct prediction of the resistance of P. aeruginosa to four antibiotics by the AMR-associated features screened, we collected 74 P. aeruginosa positive sputum samples to sequence by metagenomics next-generation sequencing (mNGS), of which 1 sample with low quality was eliminated. Then, we constructed the resistance prediction model. Results: We identified 93, 88, 80, 140 AMR-associated features for IPM, MEM, TZP, and LVFX resistance in P. aeruginosa. The relative abundance of AMR-associated genes was obtained by matching mNGS and WGS data. The top 20 features with importance degree for IPM, MEM, TZP, and LVFX resistance were used to model, respectively. Then, we used the random forest algorithm to construct resistance prediction models of P. aeruginosa, in which the areas under the curves of the IPM, MEM, TZP, and LVFX resistance prediction models were all greater than 0.8, suggesting these resistance prediction models had good performance. Conclusion: In summary, mNGS can predict the resistance of P. aeruginosa by directly detecting AMR-associated genes, which provides a reference for rapid clinical detection of drug resistance of pathogenic bacteria.

Variability of bile bacterial profiles and drug resistance in patients with choledocholithiasis combined with biliary tract infection: a retrospective study.

Background: Biliary tract infection is a common complication of choledocholithiasis. This study aimed to analyse the distribution of pathogenic bacteria in bile cultures from patients with choledocholithiasis combined with biliary tract infection to guide clinical application of antimicrobials and reduce the emergence of drug resistance. Methods: A total of 880 patients were enrolled in this retrospective study from 30 March 2017 to 31 August 2022 at the Affiliated Hospital of Qingdao University in China. Bile specimens were extracted for microbiological culture under aseptic conditions using endoscopic retrograde cholangiopancreatography. Bacterial culture, strain identification, and antimicrobial susceptibility testing were conducted according to the standard protocol. Baseline data were retrieved from patient files. Results: Overall, 90.34% (795/880) of bile samples showed positive microbiological results and 37.50% (330/880) demonstrated polymicrobial infections. Among the 795 bile specimens with positive culture results, 1,216 pathogenic bacteria were detected, with gram-negative bacilli accounting for 56.33%, gram-positive cocci for 41.86%, and fungi for 1.81%. The predominant gram-negative bacilli in the bile cultures were Escherichia coli (30.43%) and Klebsiella pneumoniae (13.98%), whereas the main gram-positive cocci were Enterococcus faecium (14.04%) and E. casseliflavus (4.28%). The annual trend analysis revealed a gradual decrease in the proportion of gram-negative bacilli and a gradual increase in the proportion of gram-positive cocci, with a concomitant decrease in the dominance of E. coli. Both E. faecium and E. coli showed high resistance to conventional antibiotics but high sensitivity to piperacillin/tazobactam, carbapenems, amikacin, and vancomycin. Conclusions: A significant change has occurred in the bile bacterial spectrum in patients with choledocholithiasis and biliary tract infection. The incidence of gram-positive cocci infections has increased annually, while that of gram-negative bacilli and E. coli infections has decreased. Antibiotic administration should be tailored based on the local bacterial profile.

Constructing an immune-related prognostic signature for predicting prognosis and immune response in hepatocellular carcinoma.

Background: Currently, there are few studies on immune-related prognostic analysis of hepatocellular carcinoma (HCC). Our aim was to establish an immune-correlated prognostic model for HCC. Methods: Immune-associated cells were obtained from the scRNA-seq dataset (GSE149614) of HCC. Differentially expressed genes between normal and tumor cells from immune-associated cells and the immune-related genes from the ImmPort database were used to identify immune-related differentially expressed genes (IRDEGs). Subsequently, the risk model was established in the TCGA-LIHC cohort (n = 438) from the Cancer Genome Atlas (TCGA) database by using Kaplan-Meier (K-M) survival curve, univariate/multivariate Cox regression analysis. Subsequently, we further analyzed tumor immune microenvironment characteristics, somatic mutation, immune checkpoint and its ligand expression levels between high- and low-risk groups, as well as drug sensitivity prediction. ICGC cohort was set as the validation cohort. TCGA-LIHC cohort and three independent the Gene Expression Omnibus (GEO) datasets (GSE54236, GSE14520, and GSE64041) was used to verify IRDEGs expression, as well as PCR assays using clinical samples. Results: The IRDEGs was composed of 4 genes, namely B2M, SPP1, PPIA, and HRG. The 438 HCC patients were divided into high- and low-risk group. The high-risk group was associated with poor prognosis, including higher T stage, advanced pathological stages, less immune cell infiltration, higher TP53 mutation rate, the high expression of CTLA4 and HAVCR2. Besides, high-risk populations benefit from most chemotherapy drugs. Similarly, the performance of the risk model was validated in the ICGC. All four datasets (TCGA-LIHC cohort, GSE54236, GSE14520, and GSE64041) and clinical q-PCR results demonstrated that, compared with normal samples, the expressions of B2M and HRG were lower in tumor samples, and the expression of SPP1 was higher. Conclusion: In summary, the immune-related prognostic signature had a good predictive performance on prognosis and immunotherapy for HCC patients.