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The circRNA expression profile of colorectal inflammatory cancer transformation revealed potential predictive biomarkers

Colorectal cancer (CRC) is one of the most common malignant tumors in the world, and most colorectal cancer is transformed from colorectal adenoma (CRA). Identifying biomarkers for the early prediction of colorectal cancer would be an important finding. Circular RNA (circRNA) plays a key role in the...

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Autores principales: Lu, Lu, Liu, Yujing, Zhang, Guangtao, Xu, Yangxian, Hu, Dan, Ji, Guang, Xu, Hanchen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9740358/
https://www.ncbi.nlm.nih.gov/pubmed/36446351
http://dx.doi.org/10.18632/aging.204406
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author Lu, Lu
Liu, Yujing
Zhang, Guangtao
Xu, Yangxian
Hu, Dan
Ji, Guang
Xu, Hanchen
author_facet Lu, Lu
Liu, Yujing
Zhang, Guangtao
Xu, Yangxian
Hu, Dan
Ji, Guang
Xu, Hanchen
author_sort Lu, Lu
collection PubMed
description Colorectal cancer (CRC) is one of the most common malignant tumors in the world, and most colorectal cancer is transformed from colorectal adenoma (CRA). Identifying biomarkers for the early prediction of colorectal cancer would be an important finding. Circular RNA (circRNA) plays a key role in the occurrence and development of tumors, and its biological characteristics make it a potential biomarker for the early diagnosis of diseases. Therefore, we explored the relationship between circRNA and the malignant transformation from colorectal adenoma to colorectal cancer. We constructed inflammation-based tumorigenesis mouse models and performed high-throughput RNA sequencing to determine the expression profile of circRNAs in tissues at different stages of disease. Subsequent STEM analysis showed that with the development of the disease, 30 circRNAs were significantly downregulated, and 10 circRNAs were significantly upregulated. After qRT-PCR and Fish analysis verification, it was clear that mmu_circ_0008035 and mmu_circ_0000420 were significantly and continuously overexpressed in the development of colorectal cancer in our mouse model. Next, through homology analysis of circRNA in human and mouse and validation of clinical normal tissues, adenoma tissues and CRC tissues, we found biomarkers of has_circ0101338 ahashsa_circ0022426 that could predict the malignant transformation of human colorectal inflammation into CRC and have certain diagnostic value. In conclusion, our results may shed light on the mechanism of progression from precancerous adenoma to cancer and provide biomarkers that may be used in the early diagnosis of CRC.
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spelling pubmed-97403582022-12-12 The circRNA expression profile of colorectal inflammatory cancer transformation revealed potential predictive biomarkers Lu, Lu Liu, Yujing Zhang, Guangtao Xu, Yangxian Hu, Dan Ji, Guang Xu, Hanchen Aging (Albany NY) Research Paper Colorectal cancer (CRC) is one of the most common malignant tumors in the world, and most colorectal cancer is transformed from colorectal adenoma (CRA). Identifying biomarkers for the early prediction of colorectal cancer would be an important finding. Circular RNA (circRNA) plays a key role in the occurrence and development of tumors, and its biological characteristics make it a potential biomarker for the early diagnosis of diseases. Therefore, we explored the relationship between circRNA and the malignant transformation from colorectal adenoma to colorectal cancer. We constructed inflammation-based tumorigenesis mouse models and performed high-throughput RNA sequencing to determine the expression profile of circRNAs in tissues at different stages of disease. Subsequent STEM analysis showed that with the development of the disease, 30 circRNAs were significantly downregulated, and 10 circRNAs were significantly upregulated. After qRT-PCR and Fish analysis verification, it was clear that mmu_circ_0008035 and mmu_circ_0000420 were significantly and continuously overexpressed in the development of colorectal cancer in our mouse model. Next, through homology analysis of circRNA in human and mouse and validation of clinical normal tissues, adenoma tissues and CRC tissues, we found biomarkers of has_circ0101338 ahashsa_circ0022426 that could predict the malignant transformation of human colorectal inflammation into CRC and have certain diagnostic value. In conclusion, our results may shed light on the mechanism of progression from precancerous adenoma to cancer and provide biomarkers that may be used in the early diagnosis of CRC. Impact Journals 2022-11-29 /pmc/articles/PMC9740358/ /pubmed/36446351 http://dx.doi.org/10.18632/aging.204406 Text en Copyright: © 2022 Lu et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Lu, Lu
Liu, Yujing
Zhang, Guangtao
Xu, Yangxian
Hu, Dan
Ji, Guang
Xu, Hanchen
The circRNA expression profile of colorectal inflammatory cancer transformation revealed potential predictive biomarkers
title The circRNA expression profile of colorectal inflammatory cancer transformation revealed potential predictive biomarkers
title_full The circRNA expression profile of colorectal inflammatory cancer transformation revealed potential predictive biomarkers
title_fullStr The circRNA expression profile of colorectal inflammatory cancer transformation revealed potential predictive biomarkers
title_full_unstemmed The circRNA expression profile of colorectal inflammatory cancer transformation revealed potential predictive biomarkers
title_short The circRNA expression profile of colorectal inflammatory cancer transformation revealed potential predictive biomarkers
title_sort circrna expression profile of colorectal inflammatory cancer transformation revealed potential predictive biomarkers
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9740358/
https://www.ncbi.nlm.nih.gov/pubmed/36446351
http://dx.doi.org/10.18632/aging.204406
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