HIF-1 alpha (1772C > T) polymorphism as marker for breast cancer development

Hypoxia-inducible factor 1 alpha (HIF-1 alpha) is an important transcription factor that regulates different cellular responses to hypoxia. HIF-1 alpha is rapidly degraded by von Hippel-Lindau (VHL) protein under normoxic conditions and stabilized under hypoxia. A common variant of HIF-1 alpha (1772C > T) (rs 11549465) polymorphism, corresponding to an amino acid change from proline to serine at 582 position within the oxygen-dependent degradation domain, results in increased stability of the protein and altered transactivation of its target genes. The present study was aimed to find the association between HIF-1 alpha (1772C > T) (rs 11549465) polymorphism and breast cancer development. For this purpose, 348 primary breast cancer patients and 320 healthy and age-matched controls were genotyped through PCR-RFLP method. The genotype frequencies were compared between patients and controls, and their influence on clinical characteristics of breast cancer patients was analyzed. Our study revealed a significant increase of TT genotype in breast cancer patients compared to controls (p = 0.038). Further, TT genotype and T allele were found to be associated with progesterone receptor (PR)-negative status (p < 0.09). None of the clinical variables revealed significant association with HIF-1 alpha (1772C > T) (rs 11549465) polymorphism.

Lesion Detection in Breast Ultrasound Images Using Tissue Transition Analysis

Breast cancer is one of the leading cause of cancer related deaths in women and early detection is crucial for reducing mortality rates. In this paper, we present a novel and fully automated approach based on tissue transition analysis for lesion detection in breast ultrasound images. Every candidate pixel is classified as belonging to the lesion boundary, lesion interior or normal tissue based on its descriptor value. The tissue transitions are modeled using a Markov chain to estimate the likelihood of a candidate lesion region. Experimental evaluation on a clinical dataset of 135 images show that the proposed approach can achieve high sensitivity (95 %) with modest (3) false positives per image. The approach achieves very similar results (94 % for 3 false positives) on a completely different clinical dataset of 159 images without retraining, highlighting the robustness of the approach.

Enhanced Metastatic Potential in a 3D Tissue Scaffold toward a Comprehensive in Vitro Model for Breast Cancer Metastasis

Metastasis is clinically the most challenging and lethal aspect of breast cancer. While animal-based xenograft models are expensive and time-consuming, conventional two-dimensional (2D) cell culture systems fail to mimic in vivo signaling. In this study we have developed a three-dimensional (3D) scaffold system that better mimics the topography and mechanical properties of the breast tumor, thus recreating the tumor microenvironment in vitro to study breast cancer metastasis. Porous poly(e-caprolactone) (PCL) scaffolds of modulus 7.0 +/- 0.5 kPa, comparable to that of breast tumor tissue were fabricated, on which MDA-MB-231 cells proliferated forming tumoroids. A comparative gene expression analysis revealed that cells growing in the scaffolds expressed increased levels of genes implicated in the three major events of metastasis, viz., initiation, progression, and the site-specific colonization compared to cells grown in conventional 2D tissue culture polystyrene (TCPS) dishes. The cells cultured in scaffolds showed increased invasiveness and sphere efficiency in vitro and increased lung metastasis in vivo. A global gene expression analysis revealed a significant increase in the expression of genes involved in cell cell and cell matrix interactions and tissue remodeling, cancer inflammation, and the PI3K/Akt, Wnt, NF-kappaB, and HIFI signaling pathways all of which are implicated in metastasis. Thus, culturing breast cancer cells in 3D scaffolds that mimic the in vivo tumor-like microenvironment enhances their metastatic potential. This system could serve as a comprehensive in vitro model to investigate the manifold mechanisms of breast cancer metastasis.