Vascular Mimicry Expression in Invasive Ductal Carcinoma; A New Technique for Prospect of Aggressiveness

Vasculogenic mimicry score identifies the prognosis and immune landscape of lung adenocarcinoma

Background: Lung cancer has a high incidence and mortality rate worldwide. Vasculogenic mimicry (VM) is a specific modality of tumor angiogenesis that could potentially be a new target for tumor therapy. The purpose of this study was to explore the role of VM-related genes in assessing the prognosis and immune landscape of lung cancer. Methods: VM-related genes were obtained from previous studies, and the expression data and clinical data of lung adenocarcinoma (LUAD) patients were obtained from the TCGA database and GEO database. We performed enrichment analysis of 24 VM-related genes and screened hub genes by constructing a protein-protein interaction network and using Cytoscape software. Subsequently, we developed the VM score based on univariate Cox regression analysis and Lasso analysis and validated the VM score on the GSE72094 dataset. In addition, we constructed a nomogram based on the VM score in the TCGA cohort. Finally, we explored the correlation between the VM score and the tumor microenvironment, immune cell infiltration, immune checkpoints, and drug sensitivity. Results: Enrichment analysis revealed that VM-related genes were associated with the HIF signaling pathway and angiogenic pathway. We developed a VM score based on 3 genes (EPHA2, LAMC2 and LOXL2) in LUAD patients. Kaplan-Meier analysis showed that the VM score was associated with poor prognosis in LUAD patients. The receiver operating characteristic curve suggested that the VM score and nomogram are valid predictors for the overall survival of LUAD patients. The VM score was significantly correlated with immune cell infiltration, such as naïve B cells, neutrophils, and eosinophils, and there was a difference in the TME between the high VM score group and the low VM score group. LUAD patients in the high VM score group were more sensitive to antitumor drugs. Conclusion: In summary, the VM score developed in this study is a valuable indicator for evaluating the prognosis and immune landscape of LUAD patients. VM may be a potential target for antitumor therapy in lung cancer.

Breast tumor localization and segmentation using machine learning techniques: Overview of datasets, findings, and methods

The Global Cancer Statistics 2020 reported breast cancer (BC) as the most common diagnosis of cancer type. Therefore, early detection of such type of cancer would reduce the risk of death from it. Breast imaging techniques are one of the most frequently used techniques to detect the position of cancerous cells or suspicious lesions. Computer-aided diagnosis (CAD) is a particular generation of computer systems that assist experts in detecting medical image abnormalities. In the last decades, CAD has applied deep learning (DL) and machine learning approaches to perform complex medical tasks in the computer vision area and improve the ability to make decisions for doctors and radiologists. The most popular and widely used technique of image processing in CAD systems is segmentation which consists of extracting the region of interest (ROI) through various techniques. This research provides a detailed description of the main categories of segmentation procedures which are classified into three classes: supervised, unsupervised, and DL. The main aim of this work is to provide an overview of each of these techniques and discuss their pros and cons. This will help researchers better understand these techniques and assist them in choosing the appropriate method for a given use case.

Vitamin D Exerts Significant Antitumor Effects by Suppressing Vasculogenic Mimicry in Breast Cancer Cells

Background

Numerous clinical and experimental observations have alluded to the substantial anti-neoplastic role of vitamin D in breast cancer (BC), primarily by inducing apoptosis and affecting metastasis. Tumor progression and resistance to chemotherapy have been linked to vasculogenic mimicry (VM), which represents the endothelial-independent formation of microvascular channels by cancer cells. However, the effect of vitamin D on VM formation in BC has not been thoroughly investigated. This study examined the impact of 1α,25-dihydroxyvitamin D3 (calcitriol), the active form of vitamin D, on the expression of major factors involved in BC migration, invasion, and VM formation.

Experimental Methods

Publicly available transcriptomic datasets were used to profile the expression status of the key VM markers in vitamin D-treated BC cells. The in silico data were validated by examining the expression and activity of the key factors that are involved in tumor progression and MV formation in hormone-positive MCF-7 and aggressive triple‐negative MDA-MB-231 BC cells after treatment with calcitriol.

Results and Discussions

The bioinformatics analysis showed that tumor VM formation-enriched pathways were differentially downregulated in vitamin D-treated cells when compared with control counterparts. Treatment of BC cells with calcitriol resulted in increased expression of tissue inhibitors of metalloproteinases (TIMPs 1 and 2) and decreased content and gelatinolytic activity of matrix metalloproteinases (MMPs 2 and 9). Furthermore, calcitriol treatment reduced the expression of several pro-MV formation regulators including vascular endothelial growth factor (VEGF), tumor growth factor (TGF-β1), and amphiregulin. Eventually, this process resulted in a profound reduction in cell migration and invasion following the treatment of BC cells with calcitriol when compared to the controls. Finally, the formation of VM was diminished in the aggressive triple‐negative MDA-MB-231 cancer cell line after calcitriol treatment.

Conclusion

Our findings demonstrate that vitamin D mediates its antitumor effects in BC cells by inhibiting and curtailing their potential for VM formation.

Vasculogenic Mimicry in Breast Cancer: Clinical Relevance and Drivers

In solid tumors, vasculogenic mimicry (VM) is the formation of vascular structures by cancer cells, allowing to generate a channel-network able to transport blood and tumor cells. While angiogenesis is undertaken by endothelial cells, VM is assumed by cancer cells. Besides the participation of VM in tumor neovascularization, the clinical relevance of this process resides in its ability to favor metastasis and to drive resistance to antiangiogenic therapy. VM occurs in many tumor types, including breast cancer, where it has been associated with a more malignant phenotype, such as triple-negative and HER2-positive tumors. The latter may be explained by known drivers of VM, like hypoxia, TGFB, TWIST1, EPHA2, VEGF, matrix metalloproteinases, and other tumor microenvironment-derived factors, which altogether induce the transformation of tumor cells to a mesenchymal phenotype with a high expression rate of stemness markers. This review analyzes the current literature in the field, including the participation of some microRNAs and long noncoding RNAs in VM-regulation and tumorigenesis of breast cancer. Considering the clinical relevance of VM and its association with the tumor phenotype and clinicopathological parameters, further studies are granted to target VM in the clinic.

Three dimensional engineered models to study hypoxia biology in breast cancer

Breast cancer is the second leading cause of mortality among women worldwide. Despite the available therapeutic regimes, variable treatment response is reported among different breast cancer subtypes. Recently, the effects of the tumor microenvironment on tumor progression as well as treatment responses have been widely recognized. Hypoxia and hypoxia inducible factors in the tumor microenvironment have long been known as major players in tumor progression and survival. However, the majority of our understanding of hypoxia biology has been derived from two dimensional (2D) models. Although many hypoxia-targeted therapies have elicited promising results in vitro and in vivo, these results have not been successfully translated into clinical trials. These limitations of 2D models underscore the need to develop and integrate three dimensional (3D) models that recapitulate the complex tumor-stroma interactions in vivo. This review summarizes role of hypoxia in various hallmarks of cancer progression. We then compare traditional 2D experimental systems with novel 3D tissue-engineered models giving accounts of different bioengineering platforms available to develop 3D models and how these 3D models are being exploited to understand the role of hypoxia in breast cancer progression.