Gramicidin A: A New Mission for an Old Antibiotic

Gramicidin A (GA) is a channel-forming ionophore that renders biological membranes permeable to specific cations which disrupts cellular ionic homeostasis.  It is a well-known antibiotic, however it’s potential as a therapeutic agent for cancer has not been widely evaluated.  In two recently published studies, we showed that GA treatment is toxic to cell lines and tumor xenografts derived from renal cell carcinoma (RCC), a devastating disease that is highly resistant to conventional therapy.  GA was found to possess the qualities of both a cytotoxic drug and a targeted angiogenesis inhibitor, and this combination significantly compromised RCC growth in vitro and in vivo.  In this review, we summarize our recent research on GA, discuss the possible mechanisms whereby it exerts its anti-tumor effects, and share our perspectives on the future opportunities and challenges to the use of GA as a new anticancer agent

Tumor Response to Combination Celecoxib and Erlotinib Therapy in Non-small Cell Lung Cancer Is Associated with a Low Baseline Matrix Metalloproteinase-9 and a Decline in Serum-Soluble E-Cadherin

IntroductionCyclooxygenase-2 overexpression may mediate resistance to epidermal growth factor receptor tyrosine kinase inhibition through prostaglandin E2-dependent promotion of epithelial to mesenchymal transition (EMT). Suppression of epithelial markers, such as E-cadherin, can lead to resistance to erlotinib. Prostaglandin E2 down-regulates E-cadherin expression by up-regulating transcriptional repressors, including ZEB1 and Snail. Furthermore, E-cadherin can be modulated by matrix metalloproteinases (MMPs) and tissue inhibitors of MMPs (TIMPs), promoting tumor invasion and metastasis. Markers of EMT and tumor invasion were evaluated in patient serum from a phase I clinical trial investigating the combination of celecoxib and erlotinib in non-small cell lung cancer (NSCLC) patients.MethodsSamples from 22 subjects were evaluated. Soluble E-cadherin (sEC) was evaluated by enzyme linked immunosorbent assay in patient serum at baseline, week 4, and week 8 of treatment. Other markers of EMT and angiogenesis were evaluated by enzyme linked immunosorbent assay, including MMP-9, TIMP-1, and CCL15.ResultsSerum sEC, MMP-9, TIMP-1, and CCL15 levels were determined at baseline and week 8. Patients with a partial response to therapy had a significant decrease in sEC, TIMP-1, and CCL15 at week 8. In patients who responded to the combination therapy, baseline MMP-9 was significantly lower compared with nonresponders (p = 0.006).ConclusionssEC, MMP-9, TIMP-1, and CCL15 levels correlate with response to combination therapy with erlotinib and celecoxib in patients with NSCLC. A randomized phase II trial is planned comparing erlotinib and celecoxib with erlotinib plus placebo in advanced NSCLC. This study will prospectively assess these and other biomarkers in serum and tumor tissue

Protein expression based multimarker analysis of breast cancer samples

<p>Abstract</p> <p>Background</p> <p>Tissue microarray (TMA) data are commonly used to validate the prognostic accuracy of tumor markers. For example, breast cancer TMA data have led to the identification of several promising prognostic markers of survival time. Several studies have shown that TMA data can also be used to cluster patients into clinically distinct groups. Here we use breast cancer TMA data to cluster patients into distinct prognostic groups.</p> <p>Methods</p> <p>We apply weighted correlation network analysis (WGCNA) to TMA data consisting of 26 putative tumor biomarkers measured on 82 breast cancer patients. Based on this analysis we identify three groups of patients with low (5.4%), moderate (22%) and high (50%) mortality rates, respectively. We then develop a simple threshold rule using a subset of three markers (p53, Na-KATPase-β1, and TGF β receptor II) that can approximately define these mortality groups. We compare the results of this correlation network analysis with results from a standard Cox regression analysis.</p> <p>Results</p> <p>We find that the rule-based grouping variable (referred to as WGCNA*) is an independent predictor of survival time. While WGCNA* is based on protein measurements (TMA data), it validated in two independent Affymetrix microarray gene expression data (which measure mRNA abundance). We find that the WGCNA patient groups differed by 35% from mortality groups defined by a more conventional stepwise Cox regression analysis approach.</p> <p>Conclusions</p> <p>We show that correlation network methods, which are primarily used to analyze the relationships between gene products, are also useful for analyzing the relationships between patients and for defining distinct patient groups based on TMA data. We identify a rule based on three tumor markers for predicting breast cancer survival outcomes.</p

Repression of Na,K-ATPase β(1)-Subunit by the Transcription Factor Snail in Carcinoma

The Na,K-ATPase consists of two essential α- and β-subunits and regulates the intracellular Na(+) and K(+) homeostasis. Although the α-subunit contains the catalytic activity, it is not active without functional β-subunit. Here, we report that poorly differentiated carcinoma cell lines derived from colon, breast, kidney, and pancreas show reduced expression of the Na,K-ATPase β(1)-subunit. Decreased expression of β(1)-subunit in poorly differentiated carcinoma cell lines correlated with increased expression of the transcription factor Snail known to down-regulate E-cadherin. Ectopic expression of Snail in well-differentiated epithelial cell lines reduced the protein levels of E-cadherin and β(1)-subunit and induced a mesenchymal phenotype. Reduction of Snail expression in a poorly differentiated carcinoma cell line by RNA interference increased the levels of Na,K-ATPase β(1)-subunit. Furthermore, Snail binds to a noncanonical E-box in the Na,K-ATPase β(1)-subunit promoter and suppresses its promoter activity. These results suggest that down-regulation of Na,K-ATPase β(1)-subunit and E-cadherin by Snail are associated with events leading to epithelial to mesenchymal transition