Background: Vascular endothelial growth factor-C (VEGF-C), which contributes to lymphatic metastasis (LM) in malignant disease, is one of the most important factors involved in physical and pathological lymphangiogenesis. Some VEGF-C related factors such as sine oculis homeobox homolog (SIX) 1, contactin (CNTN) 1 and dual specificity phosphatase (DUSP) 6 have been extensively studied in malignancies, but their expression levels and associations have still to be elucidated in stomach cancer.
Methods: We detected their expression levels in 30 paired stomach cancer tissues using quantitative real-time reverse transcription-PCR (qRT-PCR). The expression and clinical significance of each factor was analyzed using Wilcoxon signed rank sum test. The correlation among all the factors was performed by Spearman rank correlation analysis.
Results: The results suggest that VEGF-C and CNTN1 are significantly correlated with tumor size, SIX1 with the age and CNTN1 also with the cTNM stage. There are significant correlations of expression levels among VEGF-C, SIX1, CNTN1 and DUSP6.
Conclusions: There exists an important regulatory crosstalk involving SIX1, VEGF-C, CNTN1 and DUSP6 in stomach cancer.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.7314/apjcp.2014.15.5.1925 | DOI Listing |
Pharmaceuticals (Basel)
January 2025
Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing 100071, China.
Aromatase plays a crucial role in the conversion of androgens to oestrogens and is often overexpressed in hormone-dependent tumours, particularly breast cancer. [18F]BIBD-071, which has excellent binding affinity for aromatase and good pharmacokinetics, has potential for the diagnosis and treatment of aromatase-related diseases. The MCF-7 cell line, which is hormone receptor-positive (HR+), was used in the assessment of the novel [18F]-labelled radiotracer [18F]BIBD-071 via positron emission tomography (PET) imaging of an HR+ breast cancer xenograft model.
View Article and Find Full Text PDFInt J Mol Sci
January 2025
Department of Anaesthesiology, West China Hospital, Sichuan University, Chengdu 610041, China.
With the widespread use of lidocaine for pain control in cancer therapy, its antitumor activity has attracted considerable attention in recent years. This paper provides a simple strategy of combining lidocaine with chemotherapy drugs for cancer therapy, aiming to relieve chemotherapy-induced pain and achieve stronger antitumor efficacy. However, there is still a lack of substantial pre-clinical evidence for the efficacy and related mechanisms of such combinations, obstructing their potential clinical application.
View Article and Find Full Text PDFInt J Mol Sci
January 2025
Department of Molecular Medicine and Surgery, Karolinska Institutet, 17176 Stockholm, Sweden.
A previous genome-wide association study (GWAS) in colorectal cancer (CRC) patients with gastric and/or prostate cancer in their families suggested genetic loci with a shared risk for these three cancers. A second haplotype GWAS was undertaken in the same colorectal cancer patients and different controls with the aim of confirming the result and finding novel loci. The haplotype GWAS analysis involved 685 patients with colorectal cancer cases and 1642 healthy controls from Sweden.
View Article and Find Full Text PDFInt J Mol Sci
January 2025
Department of Normal, Clinical and Imaging Anatomy, Medical University of Lublin, 20-950 Lublin, Poland.
Gastric cancer (GC) is one of the most common cancers in the world. It is a multi-factorial disease influenced by both genetic and environmental factors such as diet, obesity, radiation exposure, and infectious agents. Viral infections usually lead to chronic inflammation, which can initiate the development of cancers.
View Article and Find Full Text PDFCancers (Basel)
January 2025
Department of Biostatistics, Data Science, and Epidemiology, School of Public Health, Georgia Cancer Center at Augusta University, Augusta, GA 30912, USA.
: Recent growth in the number and applications of high-throughput "omics" technologies has created a need for better methods to integrate multiomics data. Much progress has been made in developing unsupervised methods, but supervised methods have lagged behind. : Here we present the first algorithm, PLASMA, that can learn to predict time-to-event outcomes from multiomics data sets, even when some samples have only been assayed on a subset of the omics data sets.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!