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BACKGROUND: Elucidation of candidate colorectal cancer biomarkers often begins by comparing the expression profiles of cancerous and normal tissue by performing high throughput gene expression profiling. While many such studies have been performed, the resulting lists of differentially expressed genes tend to be inconsistent with each other, suggesting that there are some false positives and negatives. One logical solution to this problem is to determine the intersection of the lists of differentially expressed genes from independent studies. It is expected that genes that are biologically relevant to cancer tumorigenesis will be reported most often, while sporadically reported genes are due to the inherent biases and limitations of each of the profiling platforms used. However, the statistical significance of the observed intersection among many independent studies is usually not considered. PURPOSE: To address these issues, we developed a computational meta-analysis method that ranked differentially expressed genes based on the following criteria, which are presented in order of importance: the amount of intersection among studies, total tissue sample sizes, and average fold change in expression. We applied this meta-analysis method to 25 independent colorectal cancer profiling studies that compared cancer versus normal, adenoma versus normal, and cancer versus adenoma tissues. RESULTS: We observed that some genes were consistently reported as differentially expressed with a statistically significant frequency (P <.0001) in the cancer versus normal and adenoma versus normal comparisons, but not in the cancer versus adenoma comparison. We performed a review of some of the high ranking candidates and determined that some have previously been shown to have diagnostic and/or prognostic utility in colorectal cancer. More interestingly, the meta-analysis method also identified genes that had yet to be tested and validated as biomarkers. Thus, these candidates are currently being validated at the protein level on colorectal tissue microarrays. CONCLUSION: Our meta-analysis method identified genes that were consistently reported as differentially expressed. Besides identifying new biomarker candidates, our meta-analysis method also provides another filter to remove false positive genes from further consideration. In conclusion, the genes presented here will aid in the identification of highly sensitive and specific biomarkers in colorectal cancer.

COLORECTAL CANCER SCREENING: A NON-INVASIVE APPROACH Amy Frazier May, 2004 58 Pages Directed by: Dr. Donna Blackburn, Dr. Patricia Bailey, and Dr. Thomas Nicholson Department of Nursing Western Kentucky University Colorectal cancer (CRC) is the third most common malignant neoplasm worldwide and is expected to affect six percent of Americans within their lifetime (National Cancer Institute, 2003). Clinicians worldwide struggle with selecting the most accurate, cost-effective CRC screening tool. Could a noninvasive screening tool be the answer or part of the answer to the dilemmas surrounding CRC screening? The purpose of this correlational, replication study was to determine whether symptoms such as rectal bleeding, change in bowel habit, and weight loss are associated with symptomatic colorectal cancer using a sample of individuals scheduled for a routine colonoscopy. This study can be considered a pilot study since it has never been replicated in the United States (U.S). Data obtained from 47 Bowel Symptom Assessment Questionnaires (BSAQs) given to patients undergoing routine colonoscopy at Greenview Regional Hospital in Bowling Green, Kentucky were analyzed to address the research objectives of the study. None of the patients had colorectal cancer, but 15 of the 47 patients had polyps. None of the symptoms showed a significant correlation with polyps according to chi-square analysis. T-tests of the means of the polyp group versus the no polyp group showed no difference between the population means for each of the examined variables. Selva scores generated from the BSAQ did not show a 8 significant relationship with the presence or absence of polyps. Additional findings, limitations, and implications for future research are discussed.

BACKGROUND: Elucidation of candidate colorectal cancer biomarkers often begins by comparing the expression profiles of cancerous and normal tissue by performing high throughput gene expression profiling. While many such studies have been performed, the resulting lists of differentially expressed genes tend to be inconsistent with each other, suggesting that there are some false positives and negatives. One logical solution to this problem is to determine the intersection of the lists of differentially expressed genes from independent studies. It is expected that genes that are biologically relevant to cancer tumorigenesis will be reported most often, while sporadically reported genes are due to the inherent biases and limitations of each of the profiling platforms used. However, the statistical significance of the observed intersection among many independent studies is usually not considered. PURPOSE: To address these issues, we developed a computational meta-analysis method that ranked differentially expressed genes based on the following criteria, which are presented in order of importance: the amount of intersection among studies, total tissue sample sizes, and average fold change in expression. We applied this meta-analysis method to 25 independent colorectal cancer profiling studies that compared cancer versus normal, adenoma versus normal, and cancer versus adenoma tissues. RESULTS: We observed that some genes were consistently reported as differentially expressed with a statistically significant frequency (P <.0001) in the cancer versus normal and adenoma versus normal comparisons, but not in the cancer versus adenoma comparison. We performed a review of some of the high ranking candidates and determined that some have previously been shown to have diagnostic and/or prognostic utility in colorectal cancer. More interestingly, the meta-analysis method also identified genes that had yet to be tested and validated as biomarkers. Thus, these candidates are currently being validated at the protein level on colorectal tissue microarrays. CONCLUSION: Our meta-analysis method identified genes that were consistently reported as differentially expressed. Besides identifying new biomarker candidates, our meta-analysis method also provides another filter to remove false positive genes from further consideration. In conclusion, the genes presented here will aid in the identification of highly sensitive and specific biomarkers in colorectal cancer.

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Background: Colorectal cancer (CRC) is the third most common cancer in Manitoba. We sought to determine if regional differences exist for treatments, wait times, and quality measures for Manitobans with CRC. Methods: A population-based historical cohort analysis for patients diagnosed with CRC between 2004 and 2006 was undertaken using administrative databases. Results: 2086 patients were diagnosed with Stage I-IV CRC between 2004 and 2006. Diagnosis wait times and treatment wait times were longer in Winnipeg than rural Manitoba. There were no differences between Winnipeg and rural Manitoba in rates of total colonic examination, adequate lymphadenectomy, and consultations with oncologists. Rural patients with rectal cancer experienced higher local recurrence and mortality rates than urban patients. Conclusion: This study establishes population-based benchmarks for the quality of CRC therapy in Manitoba. Minimal geographic differences exist for quality measures. For rectal cancer local recurrence, rural patients represent an important area for quality improvement initiatives.

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No description available.