Endocrine gland-derived vascular endothelial growth factor (EG-VEGF) and its receptor PROKR2 are associated to human colorectal cancer progression and peritoneal carcinomatosis

Benlahfid, Mohammed; Traboulsi, Waël; Sergent, F.; Benharouga, Mohamed; Elhattabi, Khalid; Erguibi, Driss; Karkouri, Mehdi; Elattar, H; Fadil, Abdelaziz; Fahmi, Yassine; Aboussaouira, Touria; Alfaidy, Nadia

doi:10.3233/cbm-170499

Cited by 10 publications

(2 citation statements)

References 42 publications

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“…Among the SNPs that were associated to microbiome or metabolome traits and had nominal association with adenoma or CRC, we found genetic variants in genes associated with CRC: rs13280938 is located in the long non-coding RNA LINC01605 , which has been described as important regulator in CRC [ 32 ]; rs6085078 of PROKR2 gene, a receptor which is associated with colorectal progression [ 33 ]; and rs17018424 of CCSER1 gene, a gene involved in cell division defect [ 34 ], and the overexpression of a deletion in this gene results in overexpression of adenocarcinoma associated genes [ 35 ]. Thus, our approach allowed to propose biological mechanisms that could link components of different layers.…”

Section: Discussionmentioning

confidence: 99%

Interplay between Genome, Metabolome and Microbiome in Colorectal Cancer

García-Etxebarria

Clos-García

Telleria

et al. 2021

Cancers

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Background: Colorectal cancer (CRC), a major health concern, is developed depending on environmental, genetic and microbial factors. The microbiome and metabolome have been analyzed to study their role in CRC. However, the interplay of host genetics with those layers in CRC remains unclear. Methods: 120 individuals were sequenced and association analyses were carried out for adenoma and CRC risk, and for selected components of the microbiome and metabolome. The epistasis between genes located in cholesterol pathways was analyzed; modifiable risk factors were studied using Mendelian randomization; and the three omic layers were used to integrate their data and to build risk prediction models. Results: We detected genetic variants that were associated to components of metabolome or microbiome and adenoma or CRC risk (e.g., in LINC01605, PROKR2 and CCSER1 genes). In addition, we found interactions between genes of cholesterol metabolism, and HDL cholesterol levels affected adenoma (p = 0.0448) and CRC (p = 0.0148) risk. The combination of the three omic layers to build risk prediction models reached high AUC values (>0.91). Conclusions: The use of the three omic layers allowed for the finding of biological mechanisms related to the development of adenoma and CRC, and each layer provided complementary information to build risk prediction models.

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Section: Discussionmentioning

confidence: 99%

Interplay between Genome, Metabolome and Microbiome in Colorectal Cancer

García-Etxebarria

Clos-García

Telleria

et al. 2021

Cancers

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“…More interestingly, EG-VEGF has recently been con rmed to be involved in the development of tumors in multiple reproductive organs such as testes, prostate [16]. EG-VEGF can promote apoptosis via regulating PI3K/AKT/mTOR pathway [17] and may be involved in the ability of tumor cells to invade other organs [18]. As PROK1 is a well-known actor in cell proliferation and survival [19], one could speculate that PROK1 might then participate with other factors to the development of HDP.…”

Section: Disscussionmentioning

confidence: 99%

Maternal Serum EG-VEGF as A First Trimester Predictor of Hypertensive Disorders of Pregnancy: A Prospective Cohort Study

Zeng¹,

Yu²,

Ding³

et al. 2021

Preprint

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Background This study aims to explore whether plasma endocrine gland-derived vascular endothelial growth factor (EG-VEGF) in the first trimester can be used as a predictor of hypertensive disorders of pregnancy (HDP), and compare it with placental growth factor (PlGF) and soluble fms-like tyrosine kinase-1 (sFlt-1) to evaluate its prediction of HDP value. Methods This is a prospective cohort study that records the medical history of the pregnant women included in the study at 11–13 weeks’ gestation, and analyzes serum biochemical markers including EG-VEGF, PIGF, sFlt-1 and sFlt-1/PIGF. The predictive values of these tests were determined. We used the receiver operating characteristic (ROC) curve to find the optimal cut-off value for each biomarker and compare the operating characteristics (sensitivity, specificity). Logistic regression analysis was used to create a prediction model for HDP based on maternal characteristics and maternal biochemistry. Results Data were obtained from 205 pregnant women. 17 cases were diagnosed with HDP, the incidence rate was 8.2% (17/205). Women who developed HDP had a significantly higher body mass index (BMI) and mean arterial pressure (MAP). Serum EG-VEGF levels in the first trimester are significantly higher in pregnant women with HDP. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value(NPV) of serum EG-VEGF levels more than 227.83 pg/ml for predicting HDP were 43%, 93%, 86% and 62%, respectively. We established a prediction model in the first trimester include maternal BMI, MAP, and EG-VEGF, with an AUC of 0.8861 (95%CI: 0.7905–0.9818), which is better than using EG-VEGF alone (AUC: 0.66). Conclusion This study demonstrated that serum EG-VEGF is a promising biomarker for predicting HDP in the first trimester. It has better predictive performance compared with the currently used biomarkers like PIGF and sFlt-1. Combining maternal clinical characteristics and biochemical tests at 11–13 weeks can effectively identify women at high risk of HDP.

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