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In-Silico Multi-Omics Analysis of the Functional Significance of Calmodulin 1 in Multiple Cancers
Aberrant activation of calmodulin 1 (CALM1) has been reported in human cancers. However, comprehensive understanding of the role of CALM1 in most cancer types has remained unclear. We systematically analyzed the expression landscape, DNA methylation, gene alteration, immune infiltration, clinical re...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8790318/ https://www.ncbi.nlm.nih.gov/pubmed/35096010 http://dx.doi.org/10.3389/fgene.2021.793508 |
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author | Yao, Maolin Fu, Lanyi Liu, Xuedong Zheng, Dong |
author_facet | Yao, Maolin Fu, Lanyi Liu, Xuedong Zheng, Dong |
author_sort | Yao, Maolin |
collection | PubMed |
description | Aberrant activation of calmodulin 1 (CALM1) has been reported in human cancers. However, comprehensive understanding of the role of CALM1 in most cancer types has remained unclear. We systematically analyzed the expression landscape, DNA methylation, gene alteration, immune infiltration, clinical relevance, and molecular pathway of CALM1 in multiple cancers using various online tools, including The Cancer Genome Atlas, cBioPortal and the Human Protein Atlas databases. Kaplan–Meier and receiver operating characteristic (ROC) curves were plotted to explore the prognostic and diagnostic potential of CALM1 expression. Multivariate analyses were used to evaluate whether the CALM1 expression could be an independent risk factor. A nomogram predicting the overall survival (OS) of patients was developed, evaluated, and compared with the traditional Tumor-Node-Metastasis (TNM) model using decision curve analysis. R language was employed as the main tool for analysis and visualization. Results revealed CALM1 to be highly expressed in most cancers, its expression being regulated by DNA methylation in multiple cancers. CALM1 had a low mutation frequency (within 3%) and was associated with immune infiltration. We observed a substantial positive correlation between CALM1 expression and macrophage and neutrophil infiltration levels in multiple cancers. Different mutational forms of CALM1 hampered immune cell infiltration. Additionally, CALM1 expression had high diagnostic and prognostic potential. Multivariate analyses revealed CALM1 expression to be an independent risk factor for OS. Therefore, our newly developed nomogram had a higher clinical value than the TNM model. The concordance index, calibration curve, and time-dependent ROC curves of the nomogram exhibited excellent performance in terms of predicting the survival rate of patients. Moreover, elevated CALM1 expression contributes to the activation of cancer-related pathways, such as the WNT and MAPK pathways. Overall, our findings improved our understanding of the function of CALM1 in human cancers. |
format | Online Article Text |
id | pubmed-8790318 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-87903182022-01-27 In-Silico Multi-Omics Analysis of the Functional Significance of Calmodulin 1 in Multiple Cancers Yao, Maolin Fu, Lanyi Liu, Xuedong Zheng, Dong Front Genet Genetics Aberrant activation of calmodulin 1 (CALM1) has been reported in human cancers. However, comprehensive understanding of the role of CALM1 in most cancer types has remained unclear. We systematically analyzed the expression landscape, DNA methylation, gene alteration, immune infiltration, clinical relevance, and molecular pathway of CALM1 in multiple cancers using various online tools, including The Cancer Genome Atlas, cBioPortal and the Human Protein Atlas databases. Kaplan–Meier and receiver operating characteristic (ROC) curves were plotted to explore the prognostic and diagnostic potential of CALM1 expression. Multivariate analyses were used to evaluate whether the CALM1 expression could be an independent risk factor. A nomogram predicting the overall survival (OS) of patients was developed, evaluated, and compared with the traditional Tumor-Node-Metastasis (TNM) model using decision curve analysis. R language was employed as the main tool for analysis and visualization. Results revealed CALM1 to be highly expressed in most cancers, its expression being regulated by DNA methylation in multiple cancers. CALM1 had a low mutation frequency (within 3%) and was associated with immune infiltration. We observed a substantial positive correlation between CALM1 expression and macrophage and neutrophil infiltration levels in multiple cancers. Different mutational forms of CALM1 hampered immune cell infiltration. Additionally, CALM1 expression had high diagnostic and prognostic potential. Multivariate analyses revealed CALM1 expression to be an independent risk factor for OS. Therefore, our newly developed nomogram had a higher clinical value than the TNM model. The concordance index, calibration curve, and time-dependent ROC curves of the nomogram exhibited excellent performance in terms of predicting the survival rate of patients. Moreover, elevated CALM1 expression contributes to the activation of cancer-related pathways, such as the WNT and MAPK pathways. Overall, our findings improved our understanding of the function of CALM1 in human cancers. Frontiers Media S.A. 2022-01-12 /pmc/articles/PMC8790318/ /pubmed/35096010 http://dx.doi.org/10.3389/fgene.2021.793508 Text en Copyright © 2022 Yao, Fu, Liu and Zheng. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Yao, Maolin Fu, Lanyi Liu, Xuedong Zheng, Dong In-Silico Multi-Omics Analysis of the Functional Significance of Calmodulin 1 in Multiple Cancers |
title | In-Silico Multi-Omics Analysis of the Functional Significance of Calmodulin 1 in Multiple Cancers |
title_full | In-Silico Multi-Omics Analysis of the Functional Significance of Calmodulin 1 in Multiple Cancers |
title_fullStr | In-Silico Multi-Omics Analysis of the Functional Significance of Calmodulin 1 in Multiple Cancers |
title_full_unstemmed | In-Silico Multi-Omics Analysis of the Functional Significance of Calmodulin 1 in Multiple Cancers |
title_short | In-Silico Multi-Omics Analysis of the Functional Significance of Calmodulin 1 in Multiple Cancers |
title_sort | in-silico multi-omics analysis of the functional significance of calmodulin 1 in multiple cancers |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8790318/ https://www.ncbi.nlm.nih.gov/pubmed/35096010 http://dx.doi.org/10.3389/fgene.2021.793508 |
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