PKCα-induced drug resistance in pancreatic cancer cells is associated with transforming growth factor-β1

<p>Abstract</p> <p>Background</p> <p>Drug resistance remains a great challenge in the treatment of pancreatic cancer. The goal of this study was to determine whether TGF-β1 is associated with drug resistance in pancreatic cancer.</p> <p>Methods</p> <p>Pancreatic cancer BxPC3 cells were stably transfected with TGF-β1 cDNA. Cellular morphology and cell cycle were determined and the suppressive subtracted hybridization (SSH) assay was performed to identify differentially expressed genes induced by TGF-β1. Western blotting and immunohistochemistry were used to detect expression of TGF-β1-related genes in the cells and tissue samples. After that, the cells were further treated with an anti-cancer drug (e.g., cisplatin) after pre-incubated with the recombinant TGF-β1 plus PKCα inhibitor Gö6976. TGF-β1 type II receptor, TβRII was also knocked down using TβRII siRNA to assess the effects of these drugs in the cells. Cell viability was assessed by MTT assay.</p> <p>Results</p> <p>Overexpression of TGF-β1 leads to a markedly increased invasion potential but a reduced growth rate in BxPC3 cells. Recombinant TGF-β1 protein increases expression of PKCα in BxPC3 cells, a result that we confirmed by SSH. Moreover, TGF-β1 reduced the sensitivity of BxPC3 cells to cisplatin treatment, and this was mediated by upregulation of PKCα. However, blockage of PKCα with Gö6976 and TβRII with siRNA reversed the resistance of BxPC3 cells to gemcitabine, even in the presence of TGF-β1. Immunohistochemical data show that pancreatic cancers overexpress TGF-β1 and P-gp relative to normal tissues. In addition, TGF-β1 expression is associated with P-gp and membranous PKCα expression in pancreatic cancer.</p> <p>Conclusions</p> <p>TGF-β1-induced drug resistance in pancreatic cancer cells was associated with PKCα expression. The PKCα inhibitor Gö6976 could be a promising agent to sensitize pancreatic cancer cells to chemotherapy.</p

ShRNA-Targeted Centromere Protein A Inhibits Hepatocellular Carcinoma Growth

Centromere protein A (CENP-A) plays important roles in cell-cycle regulation and genetic stability. Herein, we aimed to investigate its expression pattern, clinical significance, and biological function in hepatocellular carcinoma (HCC).. Conversely, CENP-A overexpression promoted HCC cell growth and reduced apoptosis. Furthermore, many genes implicated in cell-cycle regulation and apoptosis, including CHK2, P21waf1, P27 Kip1, SKP2, cyclin G1, MDM2, Bcl-2, and Bax, were deregulated by manipulating CENP-A.Overexpression of CENP-A is frequently observed in HCC. Targeting CENP-A can inhibit HCC growth, likely through the regulation of a large number genes involved in cell-cycle progression and apoptosis, and thereby represents a potential therapeutic strategy for this malignancy

A Retrospective Survey of Research Design and Statistical Analyses in Selected Chinese Medical Journals in 1998 and 2008

BACKGROUND: High quality clinical research not only requires advanced professional knowledge, but also needs sound study design and correct statistical analyses. The number of clinical research articles published in Chinese medical journals has increased immensely in the past decade, but study design quality and statistical analyses have remained suboptimal. The aim of this investigation was to gather evidence on the quality of study design and statistical analyses in clinical researches conducted in China for the first decade of the new millennium. METHODOLOGY/PRINCIPAL FINDINGS: Ten (10) leading Chinese medical journals were selected and all original articles published in 1998 (N = 1,335) and 2008 (N = 1,578) were thoroughly categorized and reviewed. A well-defined and validated checklist on study design, statistical analyses, results presentation, and interpretation was used for review and evaluation. Main outcomes were the frequencies of different types of study design, error/defect proportion in design and statistical analyses, and implementation of CONSORT in randomized clinical trials. From 1998 to 2008: The error/defect proportion in statistical analyses decreased significantly ( = 12.03, p<0.001), 59.8% (545/1,335) in 1998 compared to 52.2% (664/1,578) in 2008. The overall error/defect proportion of study design also decreased ( = 21.22, p<0.001), 50.9% (680/1,335) compared to 42.40% (669/1,578). In 2008, design with randomized clinical trials remained low in single digit (3.8%, 60/1,578) with two-third showed poor results reporting (defects in 44 papers, 73.3%). Nearly half of the published studies were retrospective in nature, 49.3% (658/1,335) in 1998 compared to 48.2% (761/1,578) in 2008. Decreases in defect proportions were observed in both results presentation ( = 93.26, p<0.001), 92.7% (945/1,019) compared to 78.2% (1023/1,309) and interpretation ( = 27.26, p<0.001), 9.7% (99/1,019) compared to 4.3% (56/1,309), some serious ones persisted. CONCLUSIONS/SIGNIFICANCE: Chinese medical research seems to have made significant progress regarding statistical analyses, but there remains ample room for improvement regarding study designs. Retrospective clinical studies are the most often used design, whereas randomized clinical trials are rare and often show methodological weaknesses. Urgent implementation of the CONSORT statement is imperative

Plasma MicroRNAs as Potential Noninvasive Biomarkers for In-Stent Restenosis

<div><p>Objective</p><p>To investigate whether microRNAs (miRs) can serve as novel biomarkers for in-stent restenosis (ISR).</p><p>Methods</p><p>This retrospective, observational single-centre study was conducted at the cardiovascular department of a tertiary hospital centre in the north of China. Follow-up coronary angiography at 6 to 12 months was performed in 181 consecutive patients implanted with drug-eluting stents. Fifty-two healthy volunteers served as the control group. The plasma miRs levels were analyzed by quantitative real-time PCR. Receiver-operating characteristic curve (ROC) analysis was performed to investigate the characters of these miRs as potential biomarkers of ISR.</p><p>Results</p><p>MiR-21 levels in ISR patients were significantly higher than those in non-ISR patients and healthy controls (<i>P</i><0.05), while miR-100 (<i>P</i><0.05), miR-143 (<i>P</i><0.001) and miR-145 (<i>P</i><0.0001) levels were significantly decreased in ISR patients. Further analysis showed that miR-21 levels were remarkably increased (<i>P</i> = 0.045), while miR-100 (<i>P</i> = 0.041), miR-143 (<i>P</i> = 0.029) and miR-145 (<i>P</i><0.01) levels were dramatically decreased in patients with diffuse ISR compared to those with focal ISR. ROC analysis demonstrated that the area under curve of miR-145, miR-143, miR-100 and miR-21 were 0.880 (95% confidence interval; CI = 0.791–0.987, <i>P</i><0.001), 0.818 (95% confidence interval; CI = 0.755–0.963, <i>P</i><0.001), 0.608 (95% confidence interval; CI = 0.372–0.757, <i>P</i><0.05) and 0.568 (95% confidence interval; CI = 0.372–0.757, <i>P</i><0.05), with specificity of 83.1%, 80.1%, 68.9% and 68.6%, and sensitivity of 88.7%, 82.1%, 60.2% and 50.1%, respectively.</p><p>Conclusions</p><p>Circulating miR-143 and miR-145 levels are associated with the occurrence of ISR and can serve as novel noninvasive biomarkers for ISR.</p></div

Representative angiographic images of non-ISR, focal and diffuse ISR.

<p>Angiographic results after successful percutaneous coronary intervention with stent implantation in the left anterior descending coronary artery from three different patients (1A, 2A and 3A). Follow-up angiography showed non-ISR (1B), focal ISR (2B) and diffuse ISR (3B) respectively. White arrows indicate the margins of stent. Black arrows indicate the stenotic lesions.</p

Clinical characteristics of patients between ISR group and non-ISR group used for miRNAs profiling.

<p>Data are presented as means (±SD) or as numbers (percentages).</p><p>*<i>P</i><0.05 vs. Non-ISR.</p><p>Clinical characteristics of patients between ISR group and non-ISR group used for miRNAs profiling.</p

Global view of the network.

<p>Global view of the network.</p

Clinical characteristics of patients between ISR group and non-ISR group.

<p>LDL-C, low density lipoprotein cholesterol; CCB, Calcium channel blockers;</p><p>ACEI, angiotensin converting enzyme inhibitor; ARB, angiotensin receptor blocker.</p><p>NA, not applicable.</p><p>Data are presented as means (±SD) or as numbers (percentages).</p>#<p>comparison among patients with ISR, non-ISR and control: P<0.05 for three groups.</p><p>*comparison between patients with ISR and non-ISR: P<0.05 for ISR vs. Non-ISR.</p><p>Clinical characteristics of patients between ISR group and non-ISR group.</p