Comprehensive metabolomics analysis of key taste components in different varieties of table grapes.

Grapes are one of the world's largest fruit crops, which are rich in nutrients and taste. Summer Black, Gui Fei, Kyoho Grape, Giant Rose, Shine Muscat, and Rosario Bianco are the six most popular table grapes in Wuxi city, Jiangsu province. Owing to the lack of comprehensive investigations of metabolites in table grapes, the metabolic causes of differences in their taste are unknown. In this study, metabolites of six table grapes were profiled using ultra-high-performance liquid chromatography-Q-Exactive Orbitrap tandem mass spectrometry combined with multivariate analysis. Orthogonal partial least squares discriminant analysis discriminated among the metabolites of these varieties. Metabolic pathway analysis revealed that carbohydrate and amino acid metabolisms were highly conserved among these varieties. Our results suggest that the taste differences in the six table grape varieties can be explained by variations in composition and abundance of carbohydrates, organic acids, amino acids, and polyphenols. This study provides comprehensive insights into the underlying metabolic causes of taste variation in table grapes.

Radiomics analysis of multicenter CT images for discriminating mucinous adenocarcinoma from nomucinous adenocarcinoma in rectal cancer and comparison with conventional CT values.

OBJECTIVE: To investigate the value of CT-based radiomics signature for preoperatively discriminating mucinous adenocarcinoma (MA) from nomucinous adenocarcinoma (NMA) in rectal cancer and compare with conventional CT values. METHOD: A total of 225 patients with histologically confirmed MA or NMA of rectal cancer were retrospectively enrolled. Radiomics features were computed from the entire tumor volume segmented from the post-contrast phase CT images. The maximum relevance and minimum redundancy (mRMR) and LASSO regression model were performed to select the best preforming features and build the radiomics models using a training cohort of 155 cases. Then, predictive performance of the models was validated using a validation cohort of 70 cases and receiver operating characteristics (ROC) analysis method. Meanwhile, CT values in post- and pre-contrast phase, as well as their difference (D-values) of tumors in two cohorts were measured by two radiologists. ROC curves were also calculated to assess diagnostic efficacies. RESULTS: One hundred and sixty-three patients were confirmed by pathology as NMA and 62 cases were MA. The radiomics signature comprised 19 selected features and showed good discrimination performance in both the training and validation cohorts. The areas under ROC curves (AUC) are 0.93 (95% confidence interval [CI]: 0.89-0.98) in training cohort and 0.93 (95% CI: 0.87-0.99) in validation cohort, respectively. Three sets of CT values of MA in pre- and post-contrast phase, and their difference (D-value) (31±7.0, 51±12.6 and 20±9.3, respectively) were lower than those of NMA (37±5.6, 69±13.3 and 32±11.7, respectively). Comparing to the radiomics signature, using three sets of conventional CT values yielded relatively low diagnostic performance with AUC of 0.84 (95% CI: 0.78-0.88), 0.75 (95% CI: 0.69-0.81) and 0.78 (95% CI: 0.72-0.83), respectively. CONCLUSION: This study demonstrated that CT radiomics features could be utilized as a noninvasive biomarker to identify MA patients from NMA of rectal cancer preoperatively, which is more accurate than using the conventional CT values.

Up-regulated Wnt1-inducible signaling pathway protein 1 correlates with poor prognosis and drug resistance by reducing DNA repair in gastric cancer.

BACKGROUND: Wnt1-inducible signaling pathway protein 1 (WISP1) is upregulated in several types of human cancer, and has been implicated in cancer progression. However, its clinical implications in gastric cancer (GC) remain unclear. AIM: To explore the expression pattern and clinical significance of WISP1 in GC. METHODS: Public data portals, including Oncomine, The Cancer Genome Atlas database, Coexpedia, and Kaplan-Meier plotter, were analyzed for the expression and clinical significance of WISP1 mRNA levels in GC. One hundred and fifty patients who underwent surgery for GC between February 2010 and October 2012 at the Affiliated Hospital of Jiangnan University were selected for validation study. WISP1 levels were measured at both the mRNA and protein levels by RT-qPCR, Western blot analysis, and immunohistochemistry (IHC). In addition, the in situ expression of WISP1 in the GC tissues was determined by IHC, and the patients were accordingly classified into high- and low-expression groups. The correlation of WISP1 expression status with patient prognosis was then determined by univariate and multivariate Cox regression analyses. WISP1 was knocked down by RNA interference. The 50% inhibitory concentration of oxaliplatin was detected by CellTiter-Blue assay. RESULTS: WISP1 levels at both the mRNA and protein levels were remarkably upregulated in GC tissues compared to normal tissues. Moreover, IHC revealed that WISP1 expression was associated with T stage and chemotherapy outcome, but not with lymph node metastasis, age, gender, histological grade, or histological type. GC patients with high WISP1 expression showed a poor overall survival. Multivariate survival analysis indicated that WISP1 was an important prognostic factor for GC patients. Mechanistically, knock-down of WISP1 expression enhanced sensitivity to oxaliplatin by reducing DNA repair and enhancing DNA damage. CONCLUSION: Significantly upregulated WISP1 expression is associated with cancer progression, chemotherapy outcome, and prognosis in GC. Mechanistically, knock-down of WISP1 expression enhances oxaliplatin sensitivity by reducing DNA repair and enhancing DNA damage. WISP1 may be a potential therapeutic target for GC treatment or a potential biomarker for diagnosis and prognosis.

Vestigial like family member 3 is a novel prognostic biomarker for gastric cancer.

BACKGROUND: Vestigial like family member 3 (VGLL3) is associated with the prognosis of epithelial ovarian cancer and soft tissue sarcoma, but its role in gastric cancer (GC) is unclear. AIM: To explore the expression pattern and clinical significance of VGLL3 in GC. METHODS: Integrative analysis was performed on the GC transcriptome profiles and survival information deposited in the ONCOMINE, GEPIA, and ONCOLNC databases. The expression levels of VGLL3 mRNA and protein were analyzed in the freshly resected tumor and normal gastric tissues from GC patients by quantitative RT-PCR and Western blot, respectively. In addition, the in situ expression of VGLL3 in the GC tissues was determined by immunohistochemistry (IHC), and the patients were accordingly classified into the high and low expression groups. The correlation of VGLL3 expression status with patient prognosis was then determined by univariate and multivariate Cox regression analyses. RESULTS: Analysis of the ONCOMINE and GEPIA databases showed that VGLL3 was significantly up-regulated in GC tissues (P = 0.003), and associated with the tumor TNM stage (P = 0.0163). The high VGLL3 expression group had a significantly worse prognosis compared to the low expression group, as per both GEPIA (P = 0.0057) and ONCOLNC (P = 0.01). The bioinformatics results were validated by the significantly higher VGLL3 mRNA and protein levels in the GC tissues compared to the adjacent normal tissues (P < 0.001) in a cohort of 30 GC patients. Furthermore, high in situ expression of VGLL3 protein was associated with more advanced N and TNM stages and HER2 mutation (P < 0.05) in a cohort of 172 patients. Kaplan-Meier analysis showed that the high VGLL3 expression group had a worse prognosis compared to the low expression group (P = 0.019). Multivariate analysis showed that VGLL3 expression status was an independent risk factor for prognosis. In addition, the prognostic risk model nomogram showed that VGLL3 was the most important indicator, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.613 for 3-year survival and 0.706 for 5-year survival. Finally, the protein interaction network analysis revealed that VGLL3 is likely involved in the Hippo signaling pathway. CONCLUSION: VGLL3 is overexpressed in GC tissues and associated with a poor prognosis, indicating its potential as a novel prognosis biomarker and therapeutic target for GC.