ArticleInternational journal of molecular sciences2020
Mechanisms of Tumor-Lymphatic Interactions in Invasive Breast and Prostate Carcinoma.
Article in International journal of molecular sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
12 citing papers in PubMed, 21 citations in OpenAlex.
- Large-Scale Quantitative Morphometry of Platelet α-Granules via SIM Super-Resolution Microscopy for Cancer Liquid Biopsy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- The Significance of CXCL1 in Cancer: An Overview of Molecular Mechanisms.International journal of molecular sciences · 2026Review
- Molecular Regulation of SASP in Cellular Senescence: Therapeutic Implications and Translational Challenges.Cells · 2025Review
- Hyaluronan: An Architect and Integrator for Cancer and Neural Diseases.International journal of molecular sciences · 2025Review
- The role of proinflammatory cytokines and CXC chemokines (CXCL1-CXCL16) in the progression of prostate cancer: insights on their therapeutic management.Cellular & molecular biology letters · 2024Review
- Acid-sensing receptor GPR4 plays a crucial role in lymphatic cancer metastasis.Cancer science · 2024Article
- Involvement in Tumorigenesis and Clinical Significance of CXCL1 in Reproductive Cancers: Breast Cancer, Cervical Cancer, Endometrial Cancer, Ovarian Cancer and Prostate Cancer.International journal of molecular sciences · 2023Review
- Hyaluronan Receptors as Mediators and Modulators of the Tumor Microenvironment.Advanced healthcare materials · 2023Review
- Glycosylation as a regulator of site-specific metastasis.Cancer metastasis reviews · 2022Review
- Inside-Out of Complement in Cancer.Frontiers in immunology · 2022Review
- Role of Exosomes in Prostate Cancer Metastasis.International journal of molecular sciences · 2021Review
- Identifying M1 Macrophage-Related Genes Through a Co-expression Network to Construct a Four-Gene Risk-Scoring Model for Predicting Thyroid Cancer Prognosis.Frontiers in genetics · 2020Article
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
Abstract
During the last few years, diverse studies have shown that tumors can actively interact with the lymphatic system and promote metastases development. In order to examine the molecular mechanisms involved in this interaction, we co-cultured tumor and lymphatic endothelial cells (LEC) and subsequently analyzed the molecular alterations of LECs. Therefore, LECs were co-cultivated with either a highly or weakly metastatic breast cancer cell line using contact (mixture) and non-contact (transwell) co-cultures. mRNA profiles from LECs were subsequently analyzed for genes specifically induced by highly metastatic tumor cells ("metastatic specific"). Among the up-regulated "metastatic specific" genes, we found candidates involved in cell cycle, cell adhesion and motility (BST2, E-selectin, and HMMR), cytokines (CCL7, CXCL6, CXCL1, and CSF2) and factors of the complement system (C1R, C3, and CFB). Among the down-regulated genes, we detected the hyaluronan receptor STAB2, angiogenic factor apelin receptor (APLNR), and the glycosylation enzyme MAN1A1. In an additional prostate cancer co-culture model, we could confirm a "metastatic specific" upregulation of E-selectin and CCL7 in LECs after interaction with the prostate cancer cell lines LNCAP (highly metastatic) and DU145 (weakly metastatic). These data allowed us to identify a set of genes regulated in LECs during in vitro communication with cancer cells, which might subsequently facilitate lymphatic metastasis.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.