Dataset Information

Blood and Tissue Sample Collection for Future Colon Cancer Biomarker Studies in Patients Undergoing Colonoscopy

ABSTRACT: RATIONALE: Collecting and storing samples of blood and tissue from patients undergoing colonoscopy to study in the laboratory may help doctors learn more about colon cancer and identify biomarkers related to colon cancer in the future. PURPOSE: This laboratory study is collecting blood and tissue samples for future colon cancer biomarker studies in patients undergoing colonoscopy.

DISEASE(S): Colon Cancer,Colorectal Cancer,Health Status Unknown,Colonic Neoplasms

PROVIDER: 2072002 | ecrin-mdr-crc |

REPOSITORIES: ECRIN MDR

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Project description:In colorectal cancer (CRC), chromosomal instability (CIN) is typically studied using comparative-genomic hybridization (CGH) arrays. We studied paired (tumor and surrounding healthy) fresh-frozen tissue from 86 CRC patients using Illumina’s Infinium-based SNP array. This method allowed us to study CIN in CRC, with simultaneous analysis of copy number (CN) and B-allele frequency (BAF), which is a representation of allelic composition. This data helped us to detect mono-allelic and bi-allelic amplifications/deletion, copy neutral loss of heterozygosity, and levels of mosaicism for mixed cell populations, some of which can not be assessed with other methods that do not measure BAF. We identified associations between CN abnormalities and different CRC phenotypes (MSI, histological diagnosis, location, tumor grade, stage, MSI and presence of lymph node metastasis). We showed commonalities between regions of CN change observed in CRC and the regions reported in previous studies of other solid cancers (e.g., amplifications of 20q, 13q, 8q, 5p and deletions of 18q, 17p and 8p). From the Therapeutic Target Database we found relevant drugs, targeted to the genes located in these regions with CN changes, approved or in trials for other cancers and common diseases. These drugs may be considered for future therapeutic trials in CRC, based on personalized cytogenetic diagnosis. We also found many regions harboring genes which are not currently targeted by any relevant drugs that may be considered for future drug discovery studies. Our study shows the application of high-density SNP arrays for cytogenetic study in CRC and its importance for personalized treatment. DNA was extracted from colon tissue samples provided by 86 CRC patients. Each patient provided paired CRC tumor tissue and adjacent normal colon mucosa samples, which were fresh-frozen after resection. Samples were genotyped using Illumina's Infinium-based 610 Quad and CytoSNP 12 microarray chips. The genotype data from paired tumor and normal samples was used to detect tumor-specific chromosomal instabilities in copy number, including copy-neutral LOH, which cannot be assessed by many other cytogenetic methods. Supplementary file "GSE34678_raw_GPL8887.txt" includes the raw data for Samples using GPL8887 (GSM853162-GSM853239); supplementary file "GSE34678_raw_GPL13829.txt" includes the raw data for Samples using GPL13829 (GSM853240-GSM853363).

Project description:Colorectal cancer is the third most common cancer in the UK and Ireland, it is the second commonest cancer in both men and women. Very often the diagnosis is made by either endoscopy/colonoscopy and the surgical treatment is carried out by a minimally invasive approach ("Keyhole"surgery). Tissue samples gathered by either approach are sent to the pathologist to confirm the nature of their content. At present this takes some time (days) and so the information cannot guide the procedure being done or indeed any other investigations or processes that need implementation as soon as possible until the pathology process is completed. Fluorescence guided surgery uses an approved dye along with approved cameras to add more information regarding tissue characteristics then is available by normal viewing alone. It has already been shown to be associated with an improvement in safety related to healing after colorectal surgery and the investigators are sooning in a randomised trial examining this in rectal cancer to prove it. Whether or not this trial proves this or not, the ability to better understand tissue health during investigation/operation needs further examination and development. In this study, the investigators will examine the role of computer vision and machine learning in determining the nature of the tissue being seen in real-time additive to the surgeons’ own opinion and experience. This is needed because the dynamic phases of fluorescence inflow into any tissue is difficult to interpret most especially when it relates to microvasculature as is present within a cancer site or deposit. By this means the investigators hope to better understand the dynamic perfusion in and out of tissue whether normal or abnormal and define signatures that can speed up and/or help inform the surgeon regarding the actual nature of the tissue being seen. The investigators will compare the data being generated with that already being captured with regard to standard pathology and radiology and other laboratory measures of clinical course. Tissue resected from a patient will also be examined in the laboratory under near-infrared microscopy and analysed for fluorescence intensity to understand where exactly and how much of the dye accumulates in specific regions of tissue. There are no new operations in this study and no new interventions are being made on the basis of the information being gathered- it’s a comparative study to see how this added information can add value to interventionalists during surgery. There are four collaborating groups involved in this research consortium, two are commercial partners as they add value in both this advanced field of analytics and in the ensuring a clinical business case is included so that findings of this work can be useful for patients.

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Blood and Tissue Sample Collection for Future Colon Cancer Biomarker Studies in Patients Undergoing Colonoscopy

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