Optimized approach for Ion Proton RNA sequencing reveals details of RNA splicing and editing features of the transcriptome.

RNA-sequencing (RNA-seq) has become the standard method for unbiased analysis of gene expression but also provides access to more complex transcriptome features, including alternative RNA splicing, RNA editing, and even detection of fusion transcripts formed through chromosomal translocations. However, differences in library methods can adversely affect the ability to recover these different types of transcriptome data. For example, some methods have bias for one end of transcripts or rely on low-efficiency steps that limit the complexity of the resulting library, making detection of rare transcripts less likely. We tested several commonly used methods of RNA-seq library preparation and found vast differences in the detection of advanced transcriptome features, such as alternatively spliced isoforms and RNA editing sites. By comparing several different protocols available for the Ion Proton sequencer and by utilizing detailed bioinformatics analysis tools, we were able to develop an optimized random primer based RNA-seq technique that is reliable at uncovering rare transcript isoforms and RNA editing features, as well as fusion reads from oncogenic chromosome rearrangements. The combination of optimized libraries and rapid Ion Proton sequencing provides a powerful platform for the transcriptome analysis of research and clinical samples.

Identification of FRA-1 as a novel player in pancreatic cancer in cooperation with a MUC1: ERK signaling axis.

The MUC1 glycoprotein is overexpressed and aberrantly glycosylated in >90% of pancreatic ductal adenocarcinoma cases and impacts tumor progression by initiating downstream signaling through phosphorylation of its cytoplasmic tail. Previous studies have demonstrated that MUC1 alters expression of known targets of activator protein 1 (AP-1); however, no studies have evaluated the precise impact of MUC1 signaling on the activity and formation of AP-1. Given the known role of these proteins in modulating migration, invasion, and tumor progression, we explored the effects of MUC1 on AP-1 dimer formation and function. We determined that MUC1 increased the protein levels of c-Jun, the major component of AP-1, and promoted dimerization of c-Jun with the Fos-protein FRA-1. We demonstrate that FRA-1 acts as a potent mediator of migration and invasion in a manner that is modulated by signals through MUC1, which acts as a dominant regulator of specific AP-1 and FRA-1 target genes. Our results provide the first in vivo evidence of a FRA-1 mediated expression profile that impacts pancreatic tumor growth properties. In summary, we show that MUC1 enhancement of ERK activation influences FRA-1 activity to modulate tumor migration, invasion and metastasis in a subset of pancreatic cancer cases.

MUC1 mucin stabilizes and activates hypoxia-inducible factor 1 alpha to regulate metabolism in pancreatic cancer.

Aberrant glucose metabolism is one of the hallmarks of cancer that facilitates cancer cell survival and proliferation. Here, we demonstrate that MUC1, a large, type I transmembrane protein that is overexpressed in several carcinomas including pancreatic adenocarcinoma, modulates cancer cell metabolism to facilitate growth properties of cancer cells. MUC1 occupies the promoter elements of multiple genes directly involved in glucose metabolism and regulates their expression. Furthermore, MUC1 expression enhances glycolytic activity in pancreatic cancer cells. We also demonstrate that MUC1 expression enhances in vivo glucose uptake and expression of genes involved in glucose uptake and metabolism in orthotopic implantation models of pancreatic cancer. The MUC1 cytoplasmic tail is known to activate multiple signaling pathways through its interactions with several transcription factors/coregulators at the promoter elements of various genes. Our results indicate that MUC1 acts as a modulator of the hypoxic response in pancreatic cancer cells by regulating the expression/stability and activity of hypoxia-inducible factor-1α (HIF-1α). MUC1 physically interacts with HIF-1α and p300 and stabilizes the former at the protein level. By using a ChIP assay, we demonstrate that MUC1 facilitates recruitment of HIF-1α and p300 on glycolytic gene promoters in a hypoxia-dependent manner. Also, by metabolomic studies, we demonstrate that MUC1 regulates multiple metabolite intermediates in the glucose and amino acid metabolic pathways. Thus, our studies indicate that MUC1 acts as a master regulator of the metabolic program and facilitates metabolic alterations in the hypoxic environments that help tumor cells survive and proliferate under such conditions.

Implementing guidelines for smoking cessation: comparing the efforts of nurses and medical assistants.

BACKGROUND: It is unclear how different types of intake clinicians (registered nurses [RNs], and less costly licensed practical nurses [LPNs] and medical assistants [MAs]) compare in the performance of smoking-cessation activities recommended in the Agency for Healthcare Research and Quality (AHRQ) smoking-cessation clinical practice guideline. METHODS: A secondary analysis of data from a randomized controlled trial of guideline implementation was performed. Exit interviews of consecutive adult smokers who presented to nine primary care clinics for routine, non-emergency care were conducted during the period February 2000 to May 2001; a total of 1221 patients with adequate data were analyzed. Intake clinicians were surveyed prior to guideline training. Hierarchical logistic regression models were used to determine the association between type of intake clinician and performance of cessation counseling at the clinic visit, after adjustment for patient-level covariates, intake clinicians' characteristics, and study site. RESULTS: Performance of all guideline-recommended counseling activities were significantly greater for all intake clinicians at test versus control sites. MAs were significantly less likely to assess willingness to quit (adjusted odds ratio [AOR]=0.4, 95% confidence interval [CI]=0.2-0.8, p =0.005) and tended to offer advice and assistance in quitting less often than RNs. Similar findings were observed for LPNs (AOR=0.5, 95% CI=0.3-1.0, p =0.03, for assessing willingness to quit). Subset analysis in subjects with complete survey data revealed that being seen by a MA was no longer associated with statistically significant differences in performance, after accounting for personal beliefs, self-efficacy, and role satisfaction in cessation counseling. CONCLUSIONS: Although both MAs and LPNs showed marked improvements in performance in response to the guideline intervention, patients seen by these intake clinicians were less likely to receive guideline-recommended counseling, compared to those patients seen by RNs. Given their important role in the delivery of preventive care, MAs and LPNs should receive proper training in cessation counseling, should have strong physician and administrative support, and should be included in efforts to implement smoking-cessation guidelines in primary care.

Effectiveness of a clinic-based strategy for implementing the AHRQ Smoking Cessation Guideline in primary care.

BACKGROUND: The Agency for Healthcare Research and Quality Smoking Cessation Practice Guideline recommends systematic assessment of smoking status and counseling of smokers at every visit, but the actual effectiveness of the guideline in primary care practice is unknown. METHODS: We conducted a nonrandomized, controlled before-after trial of a guideline-derived intervention that includes routine identification and brief counseling of smokers by nurses and medical assistants, coupled with free nicotine replacement therapy (NRT) and telephone counseling of those smokers who are willing to make a quit attempt, and feedback on performance of guideline-recommended activities. The intervention was pilot tested at 1 family practice (FP) clinic over a 2-month period; patterns of usual care were observed concurrently at four control FP clinics. We obtained exit interviews of 651 consecutive adult smokers who presented for routine, nonemergency care. Abstinence (7-day point prevalence) was determined by telephone interview during 6-month follow-up. RESULTS: Concordance with guidelines was significantly greater for all recommended actions at the test site during the intervention versus baseline (P < or = 0.05). Significantly more intervention versus baseline patients at the test site reported abstinence at 2-month follow-up (21 vs. 4%, P = 0.0004), and more patients tended to be abstinent at 6-month follow-up (21 vs. 11%, P = 0.08). No significant differences in 2- or 6-month quit rates between intervention and baseline patients were observed at the control sites. CONCLUSIONS: Implementation of a guideline-driven smoking cessation intervention that focuses primarily on smokers who are interested in making a quit attempt is associated with increased abstinence in primary care practice.