Syndecan-4 regulates the HER2-positive breast cancer cell proliferation cells via CK19/AKT signalling.

Despite the use of the highly specific anti-HER2 receptor (trastuzumab) therapy, HER2-positive breast cancers account for 20-30% of all breast cancer carcinomas, with HER2 status a challenge to treatment interventions. The heparan sulfate proteoglycans (HSPGs) are prominently expressed in the extracellular matrix (ECM), mediate breast cancer proliferation, development, and metastasis with most studies to date conducted in animal models. This study examined HSPGs in HER2-positive human breast cancer cell lines and their contribution to cancer cell proliferation. The study examined the cells following enhancement (via the addition of heparin) and knockdown (KD; using short interfering RNA, siRNA) of HSPG core proteins. The interaction of HSPG core proteins and AKT signalling molecules was examined to identify any influence of this signalling pathway on cancer cell proliferation. Our findings illustrated the HSPG syndecan-4 (SDC4) core protein significantly regulates cell proliferation with increased BC cell proliferation following heparin addition to cultures and decreased cell number following SDC4 KD. In addition, along with SDC4, significant changes in CK19/AKT signalling were identified as mediators of BC HER2-positive BC cell proliferation. This study provides evidence for a cell growth regulatory axis involving HSPGs/CK19 and AKT that represents a potential molecular target to prevent proliferation of HER2-positive breast cancer cells.

Syndecan-1 and -4 influence Wnt signaling and cell migration in human breast cancers.

Heparan sulfate proteoglycans (HSPGs) participate in numerous normal and pathophysiological cellular functions. HSPGs are crucial components of the extracellular matrix (ECM) binding signalling molecules such as fibroblast growth factors (FGF) and Wnts to mediate various cellular processes including cell proliferation, migration, and cancer invasion. The syndecans (SDCs1-4) are a major family of four HSPGs, implicated in the development of breast carcinomas. This study examined syndecan-1 (SDC1) and syndecan-4 (SDC4; SDC1/4) in breast cancer (BC) in vitro cell models and their role in tumorigenesis. Gene expression of HSPG core proteins, biosynthesis and modification enzymes along with Wnt/FGF morphogen pathway components were examined following inhibition of SDC1 and SDC4 via small interfering RNA (siRNA), and enhancement of HSPGs via addition of heparin and FGF. siRNAs knockdowns (KDs) were performed in the MCF-7 (lowly invasive and poorly metastatic) and the MDA-MB-231 (highly invasive and metastatic) human BC cell lines. Significantly decreased gene expression of SDC1 and SDC4 was observed in both cell lines following KD. Additionally, via gene expression analysis, downregulation of SDC1/4 decreased the biosynthesis of heparan sulfate modification enzymes and reduced expression of Wnt signalling molecules. Following the enhancement/inhibition of HSPGs via heparin/siRNA treatment, heparin increased the migratory characteristics of MCF-7 cells while KD of SDC1 increased cell migration in both MCF-7 and MDA-MB-231 cells when compared to scramble negative control conditions. Our findings suggest that a niche-specific function exists for SDC1/4 in the BC microenvironment, mediating Wnt signalling cascades and potentially regulating migration of BC cells.

A combinatorial in silico approach for microRNA-target identification: Order out of chaos.

Contemporary computational microRNA(miRNA)-target prediction tools have been playing a vital role in pursuing putative targets for a solitary miRNA or a group of miRNAs. These tools utilise a set of probabilistic algorithms, machine learning techniques and analyse experimentally validated miRNA targets to identify the potential miRNA-target pairs. Unfortunately, current tools generate a huge number of false-positive predictions. A standardized approach with a single tool or a combination of tools is still lacking. Moreover, sensitivity, specificity and overall efficiency of any single tool are yet to be satisfactory. Therefore, a systematic combination of selective online tools combining the factors regarding miRNA-target identification would be valuable as an miRNA-target prediction scheme. The focus of this study was to develop a theoretical framework by combining six available online tools to facilitate the current understanding of miRNA-target identification.