5 research outputs found
Complementary and alternative medicine use in oncology: A questionnaire survey of patients and health care professionals
<p>Abstract</p> <p>Background</p> <p>We aimed to investigate the prevalence and predictors of Complementary and Alternative Medicine (CAM) use among cancer patients and non-cancer volunteers, and to assess the knowledge of and attitudes toward CAM use in oncology among health care professionals.</p> <p>Methods</p> <p>This is a cross-sectional questionnaire survey conducted in a single institution in Ireland. Survey was performed in outpatient and inpatient settings involving cancer patients and non-cancer volunteers. Clinicians and allied health care professionals were asked to complete a different questionnaire.</p> <p>Results</p> <p>In 676 participants including 219 cancer patients; 301 non-cancer volunteers and 156 health care professionals, the overall prevalence of CAM use was 32.5% (29.1%, 30.9% and 39.7% respectively in the three study cohorts). Female gender (p < 0.001), younger age (p = 0.004), higher educational background (p < 0.001), higher annual household income (p = 0.001), private health insurance (p = 0.001) and non-Christian (p < 0.001) were factors associated with more likely CAM use. Multivariate analysis identified female gender (p < 0.001), non-Christian (p = 0.001) and private health insurance (p = 0.015) as independent predictors of CAM use. Most health care professionals thought they did not have adequate knowledge (58.8%) nor were up to date with the best evidence (79.2%) on CAM use in oncology. Health care professionals who used CAM were more likely to recommend it to patients (p < 0.001).</p> <p>Conclusions</p> <p>This study demonstrates a similarly high prevalence of CAM use among oncology health care professionals, cancer and non cancer patients. Patients are more likely to disclose CAM usage if they are specifically asked. Health care professionals are interested to learn more about various CAM therapies and have poor evidence-based knowledge on specific oncology treatments. There is a need for further training to meet to the escalation of CAM use among patients and to raise awareness of potential benefits and risks associated with these therapies.</p
MicroRNA expression profiling to identify and validate reference genes for relative quantification in colorectal cancer
<p>Abstract</p> <p>Background</p> <p>Advances in high-throughput technologies and bioinformatics have transformed gene expression profiling methodologies. The results of microarray experiments are often validated using reverse transcription quantitative PCR (RT-qPCR), which is the most sensitive and reproducible method to quantify gene expression. Appropriate normalisation of RT-qPCR data using stably expressed reference genes is critical to ensure accurate and reliable results. Mi(cro)RNA expression profiles have been shown to be more accurate in disease classification than mRNA expression profiles. However, few reports detailed a robust identification and validation strategy for suitable reference genes for normalisation in miRNA RT-qPCR studies.</p> <p>Methods</p> <p>We adopt and report a systematic approach to identify the most stable reference genes for miRNA expression studies by RT-qPCR in colorectal cancer (CRC). High-throughput miRNA profiling was performed on ten pairs of CRC and normal tissues. By using the mean expression value of all expressed miRNAs, we identified the most stable candidate reference genes for subsequent validation. As such the stability of a panel of miRNAs was examined on 35 tumour and 39 normal tissues. The effects of normalisers on the relative quantity of established oncogenic (<it>miR-21 </it>and <it>miR-31</it>) and tumour suppressor (<it>miR-143 </it>and <it>miR-145</it>) target miRNAs were assessed.</p> <p>Results</p> <p>In the array experiment, <it>miR-26a</it>, <it>miR-345</it>, <it>miR-425 </it>and <it>miR-454 </it>were identified as having expression profiles closest to the global mean. From a panel of six miRNAs (<it>let-7a</it>, <it>miR-16</it>, <it>miR-26a</it>, <it>miR-345</it>, <it>miR-425 </it>and <it>miR-454</it>) and two small nucleolar RNA genes (<it>RNU48 </it>and <it>Z30</it>), <it>miR-16 </it>and <it>miR-345 </it>were identified as the most stably expressed reference genes. The combined use of <it>miR-16 </it>and <it>miR-345 </it>to normalise expression data enabled detection of a significant dysregulation of all four target miRNAs between tumour and normal colorectal tissue.</p> <p>Conclusions</p> <p>Our study demonstrates that the top six most stably expressed miRNAs (<it>let-7a</it>, <it>miR-16</it>, <it>miR-26a</it>, <it>miR-345</it>, <it>miR-425 </it>and <it>miR-454</it>) described herein should be validated as suitable reference genes in both high-throughput and lower throughput RT-qPCR colorectal miRNA studies.</p
Microrna expression profiling to identify and validate reference genes for relative quantification in colorectal cancer
Background: Advances in high-throughput technologies and bioinformatics have transformed gene expression profiling methodologies. The results of microarray experiments are often validated using reverse transcription quantitative PCR (RT-qPCR), which is the most sensitive and reproducible method to quantify gene expression. Appropriate normalisation of RT-qPCR data using stably expressed reference genes is critical to ensure accurate and reliable results. Mi(cro)RNA expression profiles have been shown to be more accurate in disease classification than mRNA expression profiles. However, few reports detailed a robust identification and validation strategy for suitable reference genes for normalisation in miRNA RT-qPCR studies.
Methods: We adopt and report a systematic approach to identify the most stable reference genes for miRNA expression studies by RT-qPCR in colorectal cancer (CRC). High-throughput miRNA profiling was performed on ten pairs of CRC and normal tissues. By using the mean expression value of all expressed miRNAs, we identified the most stable candidate reference genes for subsequent validation. As such the stability of a panel of miRNAs was examined on 35 tumour and 39 normal tissues. The effects of normalisers on the relative quantity of established oncogenic (miR-21 and miR-31) and tumour suppressor (miR-143 and miR-145) target miRNAs were assessed.
Results: In the array experiment, miR-26a, miR-345, miR-425 and miR-454 were identified as having expression profiles closest to the global mean. From a panel of six miRNAs (let-7a, miR-16, miR-26a, miR-345, miR-425 and miR-454) and two small nucleolar RNA genes (RNU48 and Z30), miR-16 and miR-345 were identified as the most stably expressed reference genes. The combined use of miR-16 and miR-345 to normalise expression data enabled detection of a significant dysregulation of all four target miRNAs between tumour and normal colorectal tissue.
Conclusions: Our study demonstrates that the top six most stably expressed miRNAs (let-7a, miR-16, miR-26a, miR-345, miR-425 and miR-454) described herein should be validated as suitable reference genes in both high-throughput and lower throughput RT-qPCR colorectal miRNA studies