Comprehensive Urinary Proteome Profiling Analysis Identifies Diagnosis and Relapse Surveillance Biomarkers for Bladder Cancer.

Bladder cancer (BCa) is the predominant malignancy of the urinary system. Herein, a comprehensive urine proteomic feature was initially established for the noninvasive diagnosis and recurrence monitoring of bladder cancer. 279 cases (63 primary BCa, 87 nontumor controls (NT), 73 relapsed BCa (BCR), and 56 nonrelapsed BCa (BCNR)) were collected to screen urinary protein biomarkers. 4761 and 3668 proteins were qualified and quantified by DDA and sequential window acquisition of all theoretical mass spectra (SWATH-MS) analysis in two discovery sets, respectively. Upregulated proteins were validated by multiple reaction monitoring (MRM) in two independent combined sets. Using the multi-support vector machine-recursive feature elimination (mSVM-RFE) algorithm, a model comprising 13 proteins exhibited good performance between BCa and NT with an AUC of 0.821 (95% CI: 0.675-0.967), 90.9% sensitivity (95% CI: 72.7-100%), and 73.3% specificity (95% CI: 53.3-93.3%) in the diagnosis test set. Meanwhile, an 11-marker classifier significantly distinguished BCR from BCNR with 75.0% sensitivity (95% CI: 50.0-100%), 81.8% specificity (95% CI: 54.5-100%), and an AUC of 0.784 (95% CI: 0.609-0.959) in the test cohort for relapse surveillance. Notably, six proteins (SPR, AK1, CD2AP, ADGRF1, GMPS, and C8A) of 24 markers were newly reported. This paper reveals novel urinary protein biomarkers for BCa and offers new theoretical insights into the pathogenesis of bladder cancer (data identifier PXD044896).

The RNA-binding protein sorbin and SH3 domain-containing 2 are transcriptionally regulated by specificity protein 1 and function as tumor suppressors in bladder cancer by stabilizing tissue factor pathway inhibitor.

Sorbin and SH3 domain-containing 2 (SORBS2) is an RNA-binding protein and has been implicated in the development of some cancers. However, its role in bladder cancer (BC) is yet to be established. The expression of SORBS2 in BC tissues was determined from the Gene Expression Omnibus and Gene Expression Profiling Interactive Analysis databases and collected paired tumor/normal samples. The effects of SORBS2 on BC cells were detected by CCK-8, colony formation, Transwell, dual-luciferase, RNA immunoprecipitation, chromatin immunoprecipitation, and DNA pull-down assays. In vivo, BC cell growth and metastasis were studied by a xenograft subcutaneous model and a tail-vein metastasis model. The results showed that SORBS2 expression was significantly decreased in BC tissues and cells. SORBS2 overexpression inhibited cell proliferation, migration, invasion, and epithelial-mesenchymal transition in vitro and tumor growth and metastasis in vivo, while silencing SORBS2 produced the opposite effect. Mechanistically, we found that SORBS2 enhanced the stability of tissue factor pathway inhibitor (TFPI) mRNA via direct binding to its 3' UTR. Restoration of TFPI expression reversed SORBS2 knockdown-induced malignant phenotypes of BC cells. In addition, SORBS2 expression was negatively regulated by the transcription factor specificity protein 1 (SP1). Conversely, SORBS2 can be transcriptionally regulated by SP1 and inhibit BC cell growth and metastasis via stabilization of TFPI mRNA, indicating SORBS2 may be a promising therapeutic target for BC.

Effect of High Efficiency Digestion and Utilization of Organic Iron Made by Saccharomyces cerevisiae on Antioxidation and Caecum Microflora in Weaned Piglets.

Organic iron is expected to replace inorganic iron used in diets as an iron source. Organic iron possesses high absorption efficiency and low fecal iron excretion. This study aims to study the effect of organic iron produced by Saccharomyces cerevisiae (yeast iron) on digestion, utilization, antioxidation and caecum microflora in weaned piglets. In total, 20 piglets that had been weaned after 28 days were divided into 4 groups, each of which followed a different basal diet. The basal diet of each of these 4 groups contained, respectively, 104 mg/kg iron (ferrous sulfate, CON), 84 mg/kg iron (yeast iron, LSC), 104 mg/kg iron (yeast iron, MSC) or 124 mg/kg iron (yeast iron, HSC). This experiment lasted 35 d. The apparent digestibility of iron in LSC, MSC and HMS was higher than that in CON (p < 0.01) and the fecal iron content in LSC, MSC and HMS was lower than that in CON (p < 0.01). Serum iron contents in LSC, MSC and HMS were higher than that in CON (p < 0.01). The iron contents of the heart, lungs, liver, kidney and left gluteus muscle in the MSC and HMS groups were higher than that in CON and LSC (p < 0.05). Serum catalase, glutathione peroxidase, superoxide dismutase activity, superoxide anion, glutathione, hydroxyl free radical scavenging rate, total antioxidant capacity, and liver superoxide anion clearance rate and peroxidase in MSC and HMS were higher than that in CON and LSC (p < 0.05). The contents of nitric oxide and peroxide of the weaned piglets in MSC and HMS were lower than that in CON and LSC (p < 0.05). The abundance of Firmicutes, Blautia and Peptococcus in LSC, HSC and MSC was higher than that in CON (p < 0.01). The abundance of Lactobacillus in CON and LSC was higher than that in MSC and HSC (p < 0.01). The abundance of Acinetobacter, Streptococcus and Prevotella in LSC, MSC and HSC was lower than that in CON (p < 0.01). The results suggested that a diet containing 84 mg/kg iron of yeast iron has the same effect as a diet containing 104 mg/kg iron of ferric sulfate, and that a diet containing 104 or 124 mg/kg iron of yeast iron is superior to a diet containing 104 mg/kg iron of ferric sulfate.

MRI Image Segmentation Model with Support Vector Machine Algorithm in Diagnosis of Solitary Pulmonary Nodule.

This study focused on the application value of MRI images processed by a Support Vector Machine (SVM) algorithm-based model in diagnosis of benign and malignant solitary pulmonary nodule (SPN). The SVM algorithm was constrained by a self-paced regularization item and gradient value to establish the MRI image segmentation model (SVM-L) for lung. Its performance was compared factoring into the Dice index (DI), sensitivity (SE), specificity (SP), and Mean Square Error (MSE). 28 SPN patients who underwent the parallel MRI examination were selected as research subjects and were divided into the benign group (11 patients) and malignant group (17 patients) according to different plans for diagnosis and treatment. The apparent diffusion coefficient (ADC) at different b values was analyzed, and the steepest slope (SS) and washout ratio (WR) values in the two groups were calculated. The result showed that the MSE, DI, SE, SP values, and operation time of the SVM-L model were (0.41 ± 0.02), (0.84 ± 0.13), (0.89 ± 0.04), (0.993 ± 0.004), and (30.69 ± 2.60)s, respectively, apparently superior to those of the other algorithms, but there were no statistic differences (P > 0.05) in the WR value between the two groups of patients. The SS values of the time-signal curve in the benign and malignant groups were (2.52 ± 0.69) %/s and (3.34 ± 00.41) %/s, respectively. Obviously, the SS value of the benign group was significantly lower than that of the malignant group (P < 0.01). The ADC value with different b values in the benign group was significantly lower than that of the malignant group (P < 0.01). It suggested that the SVM-L model significantly improved the quality of lung MRI images and increased the accuracy to differentiate benign and malignant SPN, providing reference for the diagnosis and treatment of SPN patients.