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Multi gene mutation signatures in colorectal cancer patients: predict for the diagnosis, pathological classification, staging and prognosis

BACKGROUND: Identifying gene mutation signatures will enable a better understanding for the occurrence and development of colorectal cancer (CRC), and provide some potential biomarkers for clinical practice. Currently, however, there is still few effective biomarkers for early diagnosis and prognost...

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Autores principales: Zhuang, Yan, Wang, Hailong, Jiang, Da, Li, Ying, Feng, Lixia, Tian, Caijuan, Pu, Mingyu, Wang, Xiaowei, Zhang, Jiangyan, Hu, Yuanjing, Liu, Pengfei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8034139/
https://www.ncbi.nlm.nih.gov/pubmed/33836681
http://dx.doi.org/10.1186/s12885-021-08108-9
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author Zhuang, Yan
Wang, Hailong
Jiang, Da
Li, Ying
Feng, Lixia
Tian, Caijuan
Pu, Mingyu
Wang, Xiaowei
Zhang, Jiangyan
Hu, Yuanjing
Liu, Pengfei
author_facet Zhuang, Yan
Wang, Hailong
Jiang, Da
Li, Ying
Feng, Lixia
Tian, Caijuan
Pu, Mingyu
Wang, Xiaowei
Zhang, Jiangyan
Hu, Yuanjing
Liu, Pengfei
author_sort Zhuang, Yan
collection PubMed
description BACKGROUND: Identifying gene mutation signatures will enable a better understanding for the occurrence and development of colorectal cancer (CRC), and provide some potential biomarkers for clinical practice. Currently, however, there is still few effective biomarkers for early diagnosis and prognostic judgment in CRC patients. The purpose was to identify novel mutation signatures for the diagnosis and prognosis of CRC. METHODS: Clinical information of 531 CRC patients and their sequencing data were downloaded from TCGA database (training group), and 53 clinical patients were collected and sequenced with targeted next generation sequencing (NGS) technology (validation group). The relationship between the mutation genes and the diagnosis, pathological type, stage and prognosis of CRC were compared to construct signatures for CRC, and then analyzed their relationship with RNA expression, immunocyte infiltration and tumor microenvironment (TME). RESULTS: Mutations of TP53, APC, KRAS, BRAF and ATM covered 97.55% of TCGA population and 83.02% validation patients. Moreover, 57.14% validation samples and 22.06% TCGA samples indicated that patients with mucinous adenocarcinoma tended to have BRAF mutation, but no TP53 mutation. Mutations of TP53, PIK3CA, FAT4, FMN2 and TRRAP had a remarkable difference between I-II and III-IV stage patients (P < 0.0001). Besides, the combination of PIK3CA, LRP1B, FAT4 and ROS1 formed signatures for the prognosis and survival of CRC patients. The mutations of TP53, APC, KRAS, BRAF, ATM, PIK3CA, FAT4, FMN2, TRRAP, LRP1B, and ROS1 formed the signatures for predicting diagnosis and prognosis of CRC. Among them, mutation of TP53, APC, KRAS, BRAF, ATM, PIK3CA, FAT4 and TRRAP significantly reduced their RNA expression level. Stromal score, immune score and ESTIMATE score were lower in patients with TP53, APC, KRAS, PIK3CA mutation compared non-mutation patients. All the 11 gene mutations affected the distributions of immune cells. CONCLUSION: This study constructed gene mutation signatures for the diagnosis, treatment and prognosis in CRC, and proved that their mutations affected RNA expression levels, TME and immunocyte infiltration. Our results put forward further insights into the genotype of CRC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-021-08108-9.
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spelling pubmed-80341392021-04-12 Multi gene mutation signatures in colorectal cancer patients: predict for the diagnosis, pathological classification, staging and prognosis Zhuang, Yan Wang, Hailong Jiang, Da Li, Ying Feng, Lixia Tian, Caijuan Pu, Mingyu Wang, Xiaowei Zhang, Jiangyan Hu, Yuanjing Liu, Pengfei BMC Cancer Research Article BACKGROUND: Identifying gene mutation signatures will enable a better understanding for the occurrence and development of colorectal cancer (CRC), and provide some potential biomarkers for clinical practice. Currently, however, there is still few effective biomarkers for early diagnosis and prognostic judgment in CRC patients. The purpose was to identify novel mutation signatures for the diagnosis and prognosis of CRC. METHODS: Clinical information of 531 CRC patients and their sequencing data were downloaded from TCGA database (training group), and 53 clinical patients were collected and sequenced with targeted next generation sequencing (NGS) technology (validation group). The relationship between the mutation genes and the diagnosis, pathological type, stage and prognosis of CRC were compared to construct signatures for CRC, and then analyzed their relationship with RNA expression, immunocyte infiltration and tumor microenvironment (TME). RESULTS: Mutations of TP53, APC, KRAS, BRAF and ATM covered 97.55% of TCGA population and 83.02% validation patients. Moreover, 57.14% validation samples and 22.06% TCGA samples indicated that patients with mucinous adenocarcinoma tended to have BRAF mutation, but no TP53 mutation. Mutations of TP53, PIK3CA, FAT4, FMN2 and TRRAP had a remarkable difference between I-II and III-IV stage patients (P < 0.0001). Besides, the combination of PIK3CA, LRP1B, FAT4 and ROS1 formed signatures for the prognosis and survival of CRC patients. The mutations of TP53, APC, KRAS, BRAF, ATM, PIK3CA, FAT4, FMN2, TRRAP, LRP1B, and ROS1 formed the signatures for predicting diagnosis and prognosis of CRC. Among them, mutation of TP53, APC, KRAS, BRAF, ATM, PIK3CA, FAT4 and TRRAP significantly reduced their RNA expression level. Stromal score, immune score and ESTIMATE score were lower in patients with TP53, APC, KRAS, PIK3CA mutation compared non-mutation patients. All the 11 gene mutations affected the distributions of immune cells. CONCLUSION: This study constructed gene mutation signatures for the diagnosis, treatment and prognosis in CRC, and proved that their mutations affected RNA expression levels, TME and immunocyte infiltration. Our results put forward further insights into the genotype of CRC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-021-08108-9. BioMed Central 2021-04-09 /pmc/articles/PMC8034139/ /pubmed/33836681 http://dx.doi.org/10.1186/s12885-021-08108-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Zhuang, Yan
Wang, Hailong
Jiang, Da
Li, Ying
Feng, Lixia
Tian, Caijuan
Pu, Mingyu
Wang, Xiaowei
Zhang, Jiangyan
Hu, Yuanjing
Liu, Pengfei
Multi gene mutation signatures in colorectal cancer patients: predict for the diagnosis, pathological classification, staging and prognosis
title Multi gene mutation signatures in colorectal cancer patients: predict for the diagnosis, pathological classification, staging and prognosis
title_full Multi gene mutation signatures in colorectal cancer patients: predict for the diagnosis, pathological classification, staging and prognosis
title_fullStr Multi gene mutation signatures in colorectal cancer patients: predict for the diagnosis, pathological classification, staging and prognosis
title_full_unstemmed Multi gene mutation signatures in colorectal cancer patients: predict for the diagnosis, pathological classification, staging and prognosis
title_short Multi gene mutation signatures in colorectal cancer patients: predict for the diagnosis, pathological classification, staging and prognosis
title_sort multi gene mutation signatures in colorectal cancer patients: predict for the diagnosis, pathological classification, staging and prognosis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8034139/
https://www.ncbi.nlm.nih.gov/pubmed/33836681
http://dx.doi.org/10.1186/s12885-021-08108-9
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