Dataset Information

Multiple Screening Methods for the Detection of Chinese Colorectal Advanced Adenomatous Polyps and Cancer

ABSTRACT: The primary objective is to determine the sensitivity and specificity of two Colorectal Cancer (CRC) screening methods, including stool DNA test and blood mRNA test, for colorectal cancer in Chinese population, with colonoscopy as reference method. Lesions will be confirmed as malignant or precancerous by colonoscopy and histopathologic examination. The secondary objective is to compare the performance of these two CRC screening methods to a commercially available FIT assay, both with respect to cancer and advanced adenoma. Lesions will be confirmed as malignant or precancerous by colonoscopy and histopathologic examination.

DISEASE(S): Adenomatous Polyps,Colorectal Cancer,Colorectal Neoplasms,Colorectal Adenomatous Polyp,Polyps

PROVIDER: 2264226 | ecrin-mdr-crc |

REPOSITORIES: ECRIN MDR

ACCESS DATA

Similar Datasets

Project description:Oral squamous cell carcinomas are neoplasms that are mostly preceded by precancerous lesions such as leukoplakia and erythroplakia. It is important for the clinician to know about the predilection and possibility of these precancerous conditions transforming to cancer. This will inturn help to efficiently treat and manage patients. It is therefore important to understand the molecular events that explain the biology of predilection and transformation of precancerous lesions such as erythroplakia and leukoplakia to cancer. Our study aims to identify potential biomarker proteins in precancerous lesions of leukoplakia and erythroplakia that can flag its transformation to oral cancer. Four biological replicate clinical phenotypes of healthy control, leukoplakia, erythroplakia, and oral carcinoma were recruited based on clinical screening and histopathological evaluation of buccal mucosa tissue. Differentially expressed proteins were delineated using Label-free quantitative proteomics experiment done on Orbitrap fusion Tribrid mass spectrometer in three technical replicate sets of samples. Raw files were processed using Maxquant version 2.0.1.0. and down stream analysis was done by Perseus version 1.6.15.0. Validation included functional annotation based on biological process and KEGG pathways using ClueGO plug-in of cytoscape. Hierarchical clustering, and principal component analysis were performed using ClustVis tool. Across control, leukoplakia, and cancer, l- lactate dehydrogenase A chain, plectin, and WD repeat-containing protein 1 were upregulated, whereas thioredoxin 1 and spectrin alpha chain non-erythrocytic 1 were downregulated. Across control, erythroplakia, and cancer, l- lactate dehydrogenase A chain was upregulated whereas aldehyde dehydrogenase 2, peroxiredoxin 1, Heat shock 70 kDa protein 1B, and spectrin alpha chain non-erythrocytic 1 were downregulated. We found proteins involved in leukoplakia were associated with alteration in cytoskeletal reorganization and glycolysis, while in erythroplakia they were associated with alteration in response to oxidative stress and glycolysis across phenotypes. Hierarchical clustering sub-grouped half of precancerous samples under the main branch of control and the remaining half under carcinoma. Similarly, principal component analysis identified segregated clusters of control, precancerous lesions, and cancer but erythroplakia phenotypes particularly overlapped more with cancer cluster. Label-free proteomics offers a good platform for identification of protein biomarkers that can flag premalignant conditions that could become malignant. Qualitative and quantitative protein signatures across control, precancer and cancer phenotypes explain the possible functional outcomes that dictate malignant transformation to oral carcinoma. The observations place the previously observed clinical findings of erythroplakia having more predilection for cancer, in the right perspective.

Dataset Information

Multiple Screening Methods for the Detection of Chinese Colorectal Advanced Adenomatous Polyps and Cancer

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure