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Transcriptional Dysregulations of Seven Non-Differentially Expressed Genes as Biomarkers of Metastatic Colon Cancer

Background: Colon cancer (CC) is common, and the mortality rate greatly increases as the disease progresses to the metastatic stage. Early detection of metastatic colon cancer (mCC) is crucial for reducing the mortality rate. Most previous studies have focused on the top-ranked differentially expres...

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Autores principales: Lv, Xiaoying, Li, Xue, Chen, Shihong, Zhang, Gongyou, Li, Kewei, Wang, Yueying, Duan, Meiyu, Zhou, Fengfeng, Liu, Hongmei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10298541/
https://www.ncbi.nlm.nih.gov/pubmed/37372321
http://dx.doi.org/10.3390/genes14061138
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author Lv, Xiaoying
Li, Xue
Chen, Shihong
Zhang, Gongyou
Li, Kewei
Wang, Yueying
Duan, Meiyu
Zhou, Fengfeng
Liu, Hongmei
author_facet Lv, Xiaoying
Li, Xue
Chen, Shihong
Zhang, Gongyou
Li, Kewei
Wang, Yueying
Duan, Meiyu
Zhou, Fengfeng
Liu, Hongmei
author_sort Lv, Xiaoying
collection PubMed
description Background: Colon cancer (CC) is common, and the mortality rate greatly increases as the disease progresses to the metastatic stage. Early detection of metastatic colon cancer (mCC) is crucial for reducing the mortality rate. Most previous studies have focused on the top-ranked differentially expressed transcriptomic biomarkers between mCC and primary CC while ignoring non-differentially expressed genes. Results: This study proposed that the complicated inter-feature correlations could be quantitatively formulated as a complementary transcriptomic view. We used a regression model to formulate the correlation between the expression levels of a messenger RNA (mRNA) and its regulatory transcription factors (TFs). The change between the predicted and real expression levels of a query mRNA was defined as the mqTrans value in the given sample, reflecting transcription regulatory changes compared with the model-training samples. A dark biomarker in mCC is defined as an mRNA gene that is non-differentially expressed in mCC but demonstrates mqTrans values significantly associated with mCC. This study detected seven dark biomarkers using 805 samples from three independent datasets. Evidence from the literature supports the role of some of these dark biomarkers. Conclusions: This study presented a complementary high-dimensional analysis procedure for transcriptome-based biomarker investigations with a case study on mCC.
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spelling pubmed-102985412023-06-28 Transcriptional Dysregulations of Seven Non-Differentially Expressed Genes as Biomarkers of Metastatic Colon Cancer Lv, Xiaoying Li, Xue Chen, Shihong Zhang, Gongyou Li, Kewei Wang, Yueying Duan, Meiyu Zhou, Fengfeng Liu, Hongmei Genes (Basel) Article Background: Colon cancer (CC) is common, and the mortality rate greatly increases as the disease progresses to the metastatic stage. Early detection of metastatic colon cancer (mCC) is crucial for reducing the mortality rate. Most previous studies have focused on the top-ranked differentially expressed transcriptomic biomarkers between mCC and primary CC while ignoring non-differentially expressed genes. Results: This study proposed that the complicated inter-feature correlations could be quantitatively formulated as a complementary transcriptomic view. We used a regression model to formulate the correlation between the expression levels of a messenger RNA (mRNA) and its regulatory transcription factors (TFs). The change between the predicted and real expression levels of a query mRNA was defined as the mqTrans value in the given sample, reflecting transcription regulatory changes compared with the model-training samples. A dark biomarker in mCC is defined as an mRNA gene that is non-differentially expressed in mCC but demonstrates mqTrans values significantly associated with mCC. This study detected seven dark biomarkers using 805 samples from three independent datasets. Evidence from the literature supports the role of some of these dark biomarkers. Conclusions: This study presented a complementary high-dimensional analysis procedure for transcriptome-based biomarker investigations with a case study on mCC. MDPI 2023-05-24 /pmc/articles/PMC10298541/ /pubmed/37372321 http://dx.doi.org/10.3390/genes14061138 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lv, Xiaoying
Li, Xue
Chen, Shihong
Zhang, Gongyou
Li, Kewei
Wang, Yueying
Duan, Meiyu
Zhou, Fengfeng
Liu, Hongmei
Transcriptional Dysregulations of Seven Non-Differentially Expressed Genes as Biomarkers of Metastatic Colon Cancer
title Transcriptional Dysregulations of Seven Non-Differentially Expressed Genes as Biomarkers of Metastatic Colon Cancer
title_full Transcriptional Dysregulations of Seven Non-Differentially Expressed Genes as Biomarkers of Metastatic Colon Cancer
title_fullStr Transcriptional Dysregulations of Seven Non-Differentially Expressed Genes as Biomarkers of Metastatic Colon Cancer
title_full_unstemmed Transcriptional Dysregulations of Seven Non-Differentially Expressed Genes as Biomarkers of Metastatic Colon Cancer
title_short Transcriptional Dysregulations of Seven Non-Differentially Expressed Genes as Biomarkers of Metastatic Colon Cancer
title_sort transcriptional dysregulations of seven non-differentially expressed genes as biomarkers of metastatic colon cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10298541/
https://www.ncbi.nlm.nih.gov/pubmed/37372321
http://dx.doi.org/10.3390/genes14061138
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