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Identification of New Key Genes and Their Association with Breast Cancer Occurrence and Poor Survival Using In Silico and In Vitro Methods

Breast cancer is one of the most prevalent types of cancer diagnosed globally and continues to have a significant impact on the global number of cancer deaths. Despite all efforts of epidemiological and experimental research, therapeutic concepts in cancer are still unsatisfactory. Gene expression d...

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Autores principales: Ali, Rafat, Sultan, Armiya, Ishrat, Romana, Haque, Shafiul, Khan, Nida Jamil, Prieto, Miguel Angel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10216146/
https://www.ncbi.nlm.nih.gov/pubmed/37238942
http://dx.doi.org/10.3390/biomedicines11051271
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author Ali, Rafat
Sultan, Armiya
Ishrat, Romana
Haque, Shafiul
Khan, Nida Jamil
Prieto, Miguel Angel
author_facet Ali, Rafat
Sultan, Armiya
Ishrat, Romana
Haque, Shafiul
Khan, Nida Jamil
Prieto, Miguel Angel
author_sort Ali, Rafat
collection PubMed
description Breast cancer is one of the most prevalent types of cancer diagnosed globally and continues to have a significant impact on the global number of cancer deaths. Despite all efforts of epidemiological and experimental research, therapeutic concepts in cancer are still unsatisfactory. Gene expression datasets are widely used to discover the new biomarkers and molecular therapeutic targets in diseases. In the present study, we analyzed four datasets using R packages with accession number GSE29044, GSE42568, GSE89116, and GSE109169 retrieved from NCBI-GEO and differential expressed genes (DEGs) were identified. Protein–protein interaction (PPI) network was constructed to screen the key genes. Subsequently, the GO function and KEGG pathways were analyzed to determine the biological function of key genes. Expression profile of key genes was validated in MCF-7 and MDA-MB-231 human breast cancer cell lines using qRT-PCR. Overall expression level and stage wise expression pattern of key genes was determined by GEPIA. The bc-GenExMiner was used to compare expression level of genes among groups of patients with respect to age factor. OncoLnc was used to analyze the effect of expression levels of LAMA2, TIMP4, and TMTC1 on the survival of breast cancer patients. We identified nine key genes, of which COL11A1, MMP11, and COL10A1 were found up-regulated and PCOLCE2, LAMA2, TMTC1, ADAMTS5, TIMP4, and RSPO3 were found down-regulated. Similar expression pattern of seven among nine genes (except ADAMTS5 and RSPO3) was observed in MCF-7 and MDA-MB-231 cells. Further, we found that LAMA2, TMTC1, and TIMP4 were significantly expressed among different age groups of patients. LAMA2 and TIMP4 were found significantly associated and TMTC1 was found less correlated with breast cancer occurrence. We found that the expression level of LAMA2, TIMP4, and TMTC1 was abnormal in all TCGA tumors and significantly associated with poor survival.
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spelling pubmed-102161462023-05-27 Identification of New Key Genes and Their Association with Breast Cancer Occurrence and Poor Survival Using In Silico and In Vitro Methods Ali, Rafat Sultan, Armiya Ishrat, Romana Haque, Shafiul Khan, Nida Jamil Prieto, Miguel Angel Biomedicines Article Breast cancer is one of the most prevalent types of cancer diagnosed globally and continues to have a significant impact on the global number of cancer deaths. Despite all efforts of epidemiological and experimental research, therapeutic concepts in cancer are still unsatisfactory. Gene expression datasets are widely used to discover the new biomarkers and molecular therapeutic targets in diseases. In the present study, we analyzed four datasets using R packages with accession number GSE29044, GSE42568, GSE89116, and GSE109169 retrieved from NCBI-GEO and differential expressed genes (DEGs) were identified. Protein–protein interaction (PPI) network was constructed to screen the key genes. Subsequently, the GO function and KEGG pathways were analyzed to determine the biological function of key genes. Expression profile of key genes was validated in MCF-7 and MDA-MB-231 human breast cancer cell lines using qRT-PCR. Overall expression level and stage wise expression pattern of key genes was determined by GEPIA. The bc-GenExMiner was used to compare expression level of genes among groups of patients with respect to age factor. OncoLnc was used to analyze the effect of expression levels of LAMA2, TIMP4, and TMTC1 on the survival of breast cancer patients. We identified nine key genes, of which COL11A1, MMP11, and COL10A1 were found up-regulated and PCOLCE2, LAMA2, TMTC1, ADAMTS5, TIMP4, and RSPO3 were found down-regulated. Similar expression pattern of seven among nine genes (except ADAMTS5 and RSPO3) was observed in MCF-7 and MDA-MB-231 cells. Further, we found that LAMA2, TMTC1, and TIMP4 were significantly expressed among different age groups of patients. LAMA2 and TIMP4 were found significantly associated and TMTC1 was found less correlated with breast cancer occurrence. We found that the expression level of LAMA2, TIMP4, and TMTC1 was abnormal in all TCGA tumors and significantly associated with poor survival. MDPI 2023-04-25 /pmc/articles/PMC10216146/ /pubmed/37238942 http://dx.doi.org/10.3390/biomedicines11051271 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
Ali, Rafat
Sultan, Armiya
Ishrat, Romana
Haque, Shafiul
Khan, Nida Jamil
Prieto, Miguel Angel
Identification of New Key Genes and Their Association with Breast Cancer Occurrence and Poor Survival Using In Silico and In Vitro Methods
title Identification of New Key Genes and Their Association with Breast Cancer Occurrence and Poor Survival Using In Silico and In Vitro Methods
title_full Identification of New Key Genes and Their Association with Breast Cancer Occurrence and Poor Survival Using In Silico and In Vitro Methods
title_fullStr Identification of New Key Genes and Their Association with Breast Cancer Occurrence and Poor Survival Using In Silico and In Vitro Methods
title_full_unstemmed Identification of New Key Genes and Their Association with Breast Cancer Occurrence and Poor Survival Using In Silico and In Vitro Methods
title_short Identification of New Key Genes and Their Association with Breast Cancer Occurrence and Poor Survival Using In Silico and In Vitro Methods
title_sort identification of new key genes and their association with breast cancer occurrence and poor survival using in silico and in vitro methods
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10216146/
https://www.ncbi.nlm.nih.gov/pubmed/37238942
http://dx.doi.org/10.3390/biomedicines11051271
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