Objective:To screen bile acid-related characteristic genes in IgA nephropathy (IgAN) based on the feature gene selection algorithm in the machine learning method, aiming to exploring the molecular biological mechanisms and biomarkers of IgAN.Methods:The gene expression data and sample grouping information of GSE93798, GSE116626 and GSE35487 were downloaded from the Gene Expression Omnibus (GEO). Bile acid-related gene sequences were obtained from the Molecular Signatures Database (MSigDB). R language was used to identify differentially expressed genes between IgAN samples and healthy control samples. Candidate genes were obtained by intersecting differentially expressed genes and bile acid-related genes. The least absolute shrinkage and selection operator (LASSO) algorithm in machine learning was used to screen the feature genes in the candidate genes as biomarkers, and the feature genes in the training set and validation set were analyzed by the rate of change index. Receiver operating characteristic curve (ROC) method was used to evaluate the diagnostic value of identified bile acid related characteristic genes for IgAN. Gene set enrichment analysis (GSEA) was used to analyze the Spearman correlation between the characteristic genes and all other genes and their related metabolic pathways. The expression of disease-characteristic genes in the kidney tissues of IgAN rats was validated by real-time PCR.Results:Gene expression information from kidney tissue samples of 20 IgAN cases and 22 healthy controls were obtained from GEO database. A total of 204 bile acid-related genes including 24 pathways were obtained from MSigDB. The results of gene differential expression analysis showed that 333 genes in the kidney tissues of IgAN patients were differentially expressed compared with those of healthy controls, including 102 up-regulated genes and 231 down-regulated genes, among which 12 differentially expressed genes were related to bile acid genes, as follows: NR1H4,SLC23A1, ALDH8A1, FABP1, ALB, SLC27A2, DIO1, CYP8B1, BBOX1, PIPOX, AKR1C1 and SLC10A2. Five characteristic genes ( NR1H4, SLC23A1, FABP1, ALB and AKR1C1) were screened by LASSO regression algorithm.ROC analysis results showed that in GSE93798 cohort genes, the AUC of NR1H4, SLC23A1, FABP1 and ALB genes with differential expression was >0.95 respectively in diagnosing IgAN, and that of AKR1C1 genes with differential expression was >0.85 in diagnosing IgAN. The gene expression data of SLC23A1 in GSE35487 cohort was missing. ROC analysis results of other four genes showed that the AUC of differential expression of ALB gene for IgAN was >0.95 respectively, that of NR1H4 gene was >0.70, and that of both FABP1 and AKR1C1 gene was >0.60. In the GSE116626 cohort genes, the AUC of five disease characteristic genes ( NR1H4, SLC23A1, FABP1, ALB, AKR1C1) for diagnosing IgAN was >0.60, respectively. These results suggested that 5 characteristic genes have certain distinguishing ability between IgAN group and control group. GSEA results were displayed that the characteristic genes were related to butyric acid metabolism, propionic acid metabolism, arginine and proline metabolism, valine leucine and isoleucine degradation, fatty acid metabolism, etc. These results suggested that five characteristic genes might be related to IgAN through the above metabolic mechanisms. The verification results of five bile acid characteristic genes in the rat model of IgAN in the kidney tissue showed that the expressions of four genes, NR1H4, SLC23A1, FABP1 and ALB, were higher than those of the control group, and there was no statistical significance in the expression of AKR1C1 gene between the two groups. Conclusions:The expression of bile acid-related characteristic genes is abnormal in the kidney tissue of IgAN patients. Four bile acid-related differentially expressed genes, NR1H4, SLC23A1, FABP1 and ALB, are expected to be biomarkers for non-invasive diagnosis and therapeutic targets .

Objective:To screen bile acid-related characteristic genes in IgA nephropathy (IgAN) based on the feature gene selection algorithm in the machine learning method, aiming to exploring the molecular biological mechanisms and biomarkers of IgAN.Methods:The gene expression data and sample grouping information of GSE93798, GSE116626 and GSE35487 were downloaded from the Gene Expression Omnibus (GEO). Bile acid-related gene sequences were obtained from the Molecular Signatures Database (MSigDB). R language was used to identify differentially expressed genes between IgAN samples and healthy control samples. Candidate genes were obtained by intersecting differentially expressed genes and bile acid-related genes. The least absolute shrinkage and selection operator (LASSO) algorithm in machine learning was used to screen the feature genes in the candidate genes as biomarkers, and the feature genes in the training set and validation set were analyzed by the rate of change index. Receiver operating characteristic curve (ROC) method was used to evaluate the diagnostic value of identified bile acid related characteristic genes for IgAN. Gene set enrichment analysis (GSEA) was used to analyze the Spearman correlation between the characteristic genes and all other genes and their related metabolic pathways. The expression of disease-characteristic genes in the kidney tissues of IgAN rats was validated by real-time PCR.Results:Gene expression information from kidney tissue samples of 20 IgAN cases and 22 healthy controls were obtained from GEO database. A total of 204 bile acid-related genes including 24 pathways were obtained from MSigDB. The results of gene differential expression analysis showed that 333 genes in the kidney tissues of IgAN patients were differentially expressed compared with those of healthy controls, including 102 up-regulated genes and 231 down-regulated genes, among which 12 differentially expressed genes were related to bile acid genes, as follows: NR1H4,SLC23A1, ALDH8A1, FABP1, ALB, SLC27A2, DIO1, CYP8B1, BBOX1, PIPOX, AKR1C1 and SLC10A2. Five characteristic genes ( NR1H4, SLC23A1, FABP1, ALB and AKR1C1) were screened by LASSO regression algorithm.ROC analysis results showed that in GSE93798 cohort genes, the AUC of NR1H4, SLC23A1, FABP1 and ALB genes with differential expression was >0.95 respectively in diagnosing IgAN, and that of AKR1C1 genes with differential expression was >0.85 in diagnosing IgAN. The gene expression data of SLC23A1 in GSE35487 cohort was missing. ROC analysis results of other four genes showed that the AUC of differential expression of ALB gene for IgAN was >0.95 respectively, that of NR1H4 gene was >0.70, and that of both FABP1 and AKR1C1 gene was >0.60. In the GSE116626 cohort genes, the AUC of five disease characteristic genes ( NR1H4, SLC23A1, FABP1, ALB, AKR1C1) for diagnosing IgAN was >0.60, respectively. These results suggested that 5 characteristic genes have certain distinguishing ability between IgAN group and control group. GSEA results were displayed that the characteristic genes were related to butyric acid metabolism, propionic acid metabolism, arginine and proline metabolism, valine leucine and isoleucine degradation, fatty acid metabolism, etc. These results suggested that five characteristic genes might be related to IgAN through the above metabolic mechanisms. The verification results of five bile acid characteristic genes in the rat model of IgAN in the kidney tissue showed that the expressions of four genes, NR1H4, SLC23A1, FABP1 and ALB, were higher than those of the control group, and there was no statistical significance in the expression of AKR1C1 gene between the two groups. Conclusions:The expression of bile acid-related characteristic genes is abnormal in the kidney tissue of IgAN patients. Four bile acid-related differentially expressed genes, NR1H4, SLC23A1, FABP1 and ALB, are expected to be biomarkers for non-invasive diagnosis and therapeutic targets .

Objective:To develop a prognostic prediction model for patients with colorectal cancer based on a peripheral blood cell composite score (PBCS) system.Methods:This retrospective observational study included patients who had primary colorectal cancer without distant metastasis, who did not undergo radiotherapy or chemotherapy before surgery, who did not receive leukocyte or platelet-raising therapy within 1 month before surgery, and whose postoperative pathology confirmed colorectal adenocarcinoma with complete tumor resection. Patients with severe anemia, infection, or hematologic diseases before surgery, as well as those with severe heart, lung, or other important organ diseases or concurrent malignant tumors, were excluded. In total, 1021 patients with colorectal cancer who underwent surgical treatment in the Department of Gastrointestinal Surgery of the Fourth Hospital of Hebei Medical University from April 2018 to April 2020 were retrospectively included as the training set (766 patients) and the internal validation set (255 patients). Additionally, using the same criteria, 215 patients with colorectal cancer who underwent surgical treatment in another treatment group from March 2015 to December 2020 were selected as the external validation set. The "surv_cutpoint" function in R software was used to analyze the optimal cut-off values of neutrophils, lymphocytes, and platelets, and a PBCS system was established based on the optimal cut-off values. The scoring rules of the PBCS system were as follows: Neutrophils and platelets below the optimal cut-off value = 1 point, otherwise 0 points; Lymphocytes above the optimal cut-off value = 1 point, otherwise 0 points. The scores of the three cell types were added together to obtain the PBCS. Univariate and multivariate Cox regression analyses were performed to explore the correlation between patients' clinicopathological features and prognosis, and a nomogram was constructed based on the Cox regression analysis to predict patients' prognosis. The accuracy of the nomogram prediction model was validated using the C-index, calibration curve, and decision curve analysis.Results:The optimal cut-off values for neutrophils, lymphocytes, and platelets were 4.40×10 9/L, 1.41×10 9/L, and 355×10 9/L, respectively. The patients were divided into high and low groups according to the optimal cut-off values of these cells. Survival curve analysis showed that a high lymphocyte count (training set: P=0.042, internal validation: P=0.010, external validation: P=0.029), low neutrophil count (training set: P=0.035, internal validation: P=0.001, external validation: P=0.024), and low platelet count (training set: P=0.041, internal validation: P=0.030, external validation: P=0.024) were associated with prolonged overall survival (OS), with statistically significant differences in all cases. Survival analysis of different PBCS groups showed that patients with a high PBCS had longer OS than those with a low PBCS ( P<0.05). Univariate and multivariate Cox regression analysis results showed that aspirin use history, vascular thrombus, neural invasion, CA19-9, N stage, operation time, M stage, and PBCS were independent factors affecting OS (all P<0.05). The PBCS was also an independent factor affecting disease-specific survival ( P<0.05), but not progression-free survival ( P>0.05). The above independent risk or protective factors were included in R software to construct a nomogram for predicting OS. The C-index (0.873), calibration curve, and decision curve analysis (threshold probability: 0.0%–75.2%) all indicated that the nomogram prediction model had good predictive performance for OS. Conclusion:This study demonstrates that the PBCS constructed based on preoperative peripheral blood levels of neutrophils, lymphocytes, and platelets is an independent factor associated with the prognosis of patients with colorectal cancer. The nomogram model constructed based on this score system exhibits good predictive efficacy for the prognosis of these patients.

Objective:To develop a prognostic prediction model for patients with colorectal cancer based on a peripheral blood cell composite score (PBCS) system.Methods:This retrospective observational study included patients who had primary colorectal cancer without distant metastasis, who did not undergo radiotherapy or chemotherapy before surgery, who did not receive leukocyte or platelet-raising therapy within 1 month before surgery, and whose postoperative pathology confirmed colorectal adenocarcinoma with complete tumor resection. Patients with severe anemia, infection, or hematologic diseases before surgery, as well as those with severe heart, lung, or other important organ diseases or concurrent malignant tumors, were excluded. In total, 1021 patients with colorectal cancer who underwent surgical treatment in the Department of Gastrointestinal Surgery of the Fourth Hospital of Hebei Medical University from April 2018 to April 2020 were retrospectively included as the training set (766 patients) and the internal validation set (255 patients). Additionally, using the same criteria, 215 patients with colorectal cancer who underwent surgical treatment in another treatment group from March 2015 to December 2020 were selected as the external validation set. The "surv_cutpoint" function in R software was used to analyze the optimal cut-off values of neutrophils, lymphocytes, and platelets, and a PBCS system was established based on the optimal cut-off values. The scoring rules of the PBCS system were as follows: Neutrophils and platelets below the optimal cut-off value = 1 point, otherwise 0 points; Lymphocytes above the optimal cut-off value = 1 point, otherwise 0 points. The scores of the three cell types were added together to obtain the PBCS. Univariate and multivariate Cox regression analyses were performed to explore the correlation between patients' clinicopathological features and prognosis, and a nomogram was constructed based on the Cox regression analysis to predict patients' prognosis. The accuracy of the nomogram prediction model was validated using the C-index, calibration curve, and decision curve analysis.Results:The optimal cut-off values for neutrophils, lymphocytes, and platelets were 4.40×10 9/L, 1.41×10 9/L, and 355×10 9/L, respectively. The patients were divided into high and low groups according to the optimal cut-off values of these cells. Survival curve analysis showed that a high lymphocyte count (training set: P=0.042, internal validation: P=0.010, external validation: P=0.029), low neutrophil count (training set: P=0.035, internal validation: P=0.001, external validation: P=0.024), and low platelet count (training set: P=0.041, internal validation: P=0.030, external validation: P=0.024) were associated with prolonged overall survival (OS), with statistically significant differences in all cases. Survival analysis of different PBCS groups showed that patients with a high PBCS had longer OS than those with a low PBCS ( P<0.05). Univariate and multivariate Cox regression analysis results showed that aspirin use history, vascular thrombus, neural invasion, CA19-9, N stage, operation time, M stage, and PBCS were independent factors affecting OS (all P<0.05). The PBCS was also an independent factor affecting disease-specific survival ( P<0.05), but not progression-free survival ( P>0.05). The above independent risk or protective factors were included in R software to construct a nomogram for predicting OS. The C-index (0.873), calibration curve, and decision curve analysis (threshold probability: 0.0%–75.2%) all indicated that the nomogram prediction model had good predictive performance for OS. Conclusion:This study demonstrates that the PBCS constructed based on preoperative peripheral blood levels of neutrophils, lymphocytes, and platelets is an independent factor associated with the prognosis of patients with colorectal cancer. The nomogram model constructed based on this score system exhibits good predictive efficacy for the prognosis of these patients.

BACKGROUND: The effect of intra-operative chemotherapy (IOC) on the long-term survival of patients with colorectal cancer (CRC) remains unclear. In this study, we evaluated the independent effect of intra-operative infusion of 5-fluorouracil in combination with calcium folinate on the survival of CRC patients following radical resection. METHODS: 1820 patients were recruited, and 1263 received IOC and 557 did not. Clinical and demographic data were collected, including overall survival (OS), clinicopathological features, and treatment strategies. Risk factors for IOC-related deaths were identified using multivariate Cox proportional hazards models. A regression model was developed to analyze the independent effects of IOC. RESULTS: Proportional hazard regression analysis showed that IOC (hazard ratio [HR]=0.53, 95% confidence intervals [CI] [0.43, 0.65], P  < 0.001) was a protective factor for the survival of patients. The mean overall survival time in IOC group was 82.50 (95% CI [80.52, 84.49]) months, and 71.21 (95% CI [67.92, 74.50]) months in non-IOC group. The OS in IOC-treated patients were significantly higher than non-IOC-treated patients ( P  < 0.001, log-rank test). Further analysis revealed that IOC decreased the risk of death in patients with CRC in a non-adjusted model (HR=0.53, 95% CI [0.43, 0.65], P  < 0.001), model 2 (adjusted for age and gender, HR=0.52, 95% CI [0.43, 0.64], P  < 0.001), and model 3 (adjusted for all factors, 95% CI 0.71 [0.55, 0.90], P  = 0.006). The subgroup analysis showed that the HR for the effect of IOC on survival was lower in patients with stage II (HR = 0.46, 95% CI [0.31, 0.67]) or III disease (HR=0.59, 95% CI [0.45, 0.76]), regardless of pre-operative radiotherapy (HR=0.55, 95% CI [0.45, 0.68]) or pre-operative chemotherapy (HR=0.54, 95% CI [0.44, 0.66]). CONCLUSIONS: IOC is an independent factor that influences the survival of CRC patients. It improved the OS of patients with stages II and III CRC after radical surgery. TRIAL REGISTRATION chictr.org.cn, ChiCTR 2100043775.
Humans ; Fluorouracil/therapeutic use* ; Leucovorin/therapeutic use* ; Colorectal Neoplasms/pathology* ; Retrospective Studies ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use* ; Proportional Hazards Models ; Prognosis

Objective:To establish a rat model of neurogenic bladder and analyze the changes in kidney morphology and function and the expression of proteins in AngiotensinⅡ(AngⅡ)/transforming growth factor β1 (TGF-β1)/Smads pathway.Methods:Sprague-Dawley rats were randomly divided into experimental group (spinal nerve amputation, n=36) and control group (sham operation, n=12). At 6, 12, and 24 weeks, the bladder compliance was measured by cystometry, the kidney morphology was detected by B-ultrasound, blood urea nitrogen (BUN) and serum creatinine (Scr) in blood samples were examined, the kidney pathological changes were detected by Masson and HE staining, the distribution of AngⅡ/TGF-β1/Smads pathway proteins was analyzed by immunohistochemisty, and the protein expressions in kidney were detected by Western blotting. Results:Urodynamics showed that the basic bladder pressure in experimental group was higher than that in control group. B-ultrasound showed that compared with the control group, the diameter of the renal pelvis of the rats with nerve dissection gradually increased ( P<0.05), and the hydronephrosis was gradually obvious. Compared with the control group, the BUN and Scr in experimental group gradually increased (both P<0.01). Masson and HE staining showed that compared with the control group, the collagen expression and renal tubulointerstitial scores in experimental group were gradually increased (both P<0.01). Immunohistochemisty showed that compared with the control group, in experimental group the expression of angiotensinⅡ receptor type 1 (AT1), TGF-β receptor 1(TGF-βR1), phosphorylated Smad2 gradually increased (all P<0.01), the pathway inhibitor Smad6 gradually decreased ( P<0.01), and the distribution of each protein in kidney was consistent. Western blotting showed a corresponding expression trend with immunohistochemisty. Conclusions:In neurogenic bladder caused by bilateral spinal nerve amputation, due to bladder dysfunction, increased bladder pressure induces hydronephrosis, destruction of the nephron structure, activation of AngⅡ/TGF-β1/Smads pathway, and renal fibrosis. This method is effective and has clinical similarities, laying a foundation for exploring neurogenic bladder treatment.