High serum vascular endothelial growth factor C predicts better relapse-free survival in early clinically node-negative breast cancer

Vascular endothelial growth factor (VEGF) -A, -C and VE-cadherin as potential biomarkers in early breast cancer patients

BACKGROUND

Vascular endothelial growth factor (VEGF) -A and -C act as multifunctional molecules and growth factors, while VE-cadherin (cadherin 5, CDH5) is the endothelial junction protein.

AIM

To assess the relationship between intratumoral VEGF -A, -C and CDH5 levels and clinical outcome, in primary, early-stage, breast cancer patients.

PATIENTS AND METHODS

The study included 69 node-negative (N0) breast cancer patients, all of whom had not received any prior hormonal or chemotherapeutic systemic therapy that would affect the course of disease. The median follow-up period was 144 months. Intratumoral mRNA levels of VEGF -A, -C and CDH5 were determined by RT-qPCR. Prognostic performance was evaluated by Cox proportional hazards regression, Kaplan-Meier analysis, as well as by the multivariable approach based on the least absolute shrinkage and selection operator (LASSO) logit regression. Classification of patients into the low and high subgroups was performed using the outcome-oriented cut-off point categorization approach.

RESULTS

Of the measured mRNAs, only CDH5 mRNA (t = -2.17; p = 0.04) and VEGF-C mRNA (t = -2.41; p = 0.03) showed significant differences between values in patient subgroups with distant metastasis and those without recurrences, respectively. These t-test results were in agreement with the Cox regression by which CDH5 mRNA reached the most pronounced hazard ratio (HR=2.07; p = 0.05), followed by VEGF-C mRNA (HR=1.59; p = 0.005). HR values above 1.0 indicate that high levels of either CDH5 or VEGF-C mRNAs associated with a higher risk of poor clinical outcome. Distant recurrence incidence was 26% for the CDH5high and 3% for the CDH5low subgroup (Kaplan-Meier analysis). Distant recurrence incidence was 23% for the VEGF-Chigh and 0% for VEGF-Clow subgroup. The independent prognostic value of VEGF-C mRNA was confirmed by LASSO regression.

CONCLUSION

Intratumoral VEGF-A levels did not associate with disease outcome in primary, early-stage, breast cancer patients, whilst raised levels of either CDH5 or VEGF-C prognosticated a high risk of distant metastasis.

Opposing Roles of Vascular Endothelial Growth Factor C in Metastatic Dissemination and Resistance to Radio/Chemotherapy: Discussion of Mechanisms and Therapeutic Strategies

Many cancers can be cured by combining surgery with healthy margins, radiation therapy and chemotherapies. However, when the pathology becomes metastatic, cancers can be incurable. The best situation involves "chronicization" of the pathology even for several years. However, most of the time, patients die within a few months. To disseminate throughout the body, cancer cells must enter the vascular network and seed in another organ. However, during the initiation of cancer processes, the tumor is avascular. Later, the production of angiogenic factors causes tumor neovascularization and subsequent growth and spread, and the presence of blood and/or lymphatic vessels is associated with high grade tumors. Moreover, during tumor development, cancer cells enter lymphatic vessels and disseminate via the lymphatic network. Hence, blood and lymphatic vessels are considered as main routes of metastatic dissemination and cancer aggressiveness. Therefore, anti-angiogenic drugs entered in the therapeutic arsenal from 2004. Despite undeniable effects however, they are far from curative and only prolong survival by a few months.Recently, the concepts of angio/lymphangiogenesis were revisited by analyzing the role of blood and lymphatic vessels at the initiation steps of tumor development. During this period, cancer cells enter lymphatic vessels and activate immune cells within lymph nodes to initiate an antitumor immune response. Moreover, the presence of blood vessels at the proximity of the initial nodule allows immune cells to reach the tumor and eliminate cancer cells. Therefore, blood and lymphatic networks have a beneficial role during a defined time window. Considering only their detrimental effects is a concern. Hence, administration of anti-angio/lymphangiogenic therapies should be revisited to avoid the destruction of networks involved in antitumor immune response. This review mainly focuses on one of the main drivers of lymphangiogenesis, the VEGFC and its beneficial and pejorative roles according to the grade of aggressive tumors.

The Roles of Non-Coding RNAs in Tumor-Associated Lymphangiogenesis

Simple Summary

The lymphatic system plays key roles in the bodies’ defence against disease, including cancer. The expansion of this system is termed lymphangiogenesis and it is orchestrated by factors and conditions within the microenvironment. One approach to prevent cancer progression is by interfering with these microenvironment factors that promote this process and that facilitate the spread of cancer cells to distant organs. One of these factors are non-coding RNAs. This review will summarize recent findings of the distinct roles played by non-coding RNAs in the lymphatic system within normal tissues and tumours. Understanding the mechanisms involved in this process can provide new avenues for therapeutic intervention for inhibiting the spread of cancer.

Abstract

Lymphatic vessels are regarded as the ”forgotten” circulation. Despite this, growing evidence has shown significant roles for the lymphatic circulation in normal and pathological conditions in humans, including cancers. The dissemination of tumor cells to other organs is often mediated by lymphatic vessels that serve as a conduit and is often referred to as tumor-associated lymphangiogenesis. Some of the most well-studied lymphangiogenic factors that govern tumor lymphangiogenesis are the vascular endothelial growth factor (VEGF-C/D and VEGFR-2/3), neuroplilin-2 (NRP2), fibroblast growth factor (FGF), and hepatocyte growth factor (HGF), to name a few. However, recent findings have illustrated that non-coding RNAs are significantly involved in regulating gene expression in most biological processes, including lymphangiogenesis. In this review, we focus on the regulation of growth factors and non-coding RNAs (ncRNAs) in the lymphatic development in normal and cancer physiology. Then, we discuss the lymphangiogenic factors that necessitate tumor-associated lymphangiogenesis, with regards to ncRNAs in various types of cancer. Understanding the different roles of ncRNAs in regulating lymphatic vasculature in normal and cancer conditions may pave the way towards the development of ncRNA-based anti-lymphangiogenic therapy.

Modeling and comparing data mining algorithms for prediction of recurrence of breast cancer

Breast cancer is the most common invasive cancer and the second leading cause of cancer death in women. and regrettably, this rate is increasing every year. One of the aspects of all cancers, including breast cancer, is the recurrence of the disease, which causes painful consequences to the patients. Moreover, the practical application of data mining in the field of breast cancer can help to provide some necessary information and knowledge required by physicians for accurate prediction of breast cancer recurrence and better decision-making. The main objective of this study is to compare different data mining algorithms to select the most accurate model for predicting breast cancer recurrence. This study is cross-sectional and data gathering of this research performed from June 2018 to June 2019 from the official statistics of Ministry of Health and Medical Education and the Iran Cancer Research Center for patients with breast cancer who had been followed for a minimum of 5 years from February 2014 to April 2019, including 5471 independent records. After initial pre-processing in dataset and variables, seven new and conventional data mining algorithms have been applied that each one represents one kind of data mining approach. Results show that the C5.0 algorithm possibly could be a helpful tool for the prediction of breast cancer recurrence at the stage of distant recurrence and nonrecurrence, especially in the first to third years. also, LN involvement rate, Her2 value, Tumor size, free or closed tumor margin were found to be the most important features in our dataset to predict breast cancer recurrence.