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Gene Mutations Associated With Clinical Characteristics in the Tumors of Patients With Breast Cancer

BACKGROUND: Clinical characteristics including estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor 2 (HER2) are important biomarkers in the treatment of breast cancer, but how genomic mutations affect their status is rarely studied. This study aimed at finding genom...

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Autores principales: Hao, Chunfang, Wang, Chen, Lu, Ning, Zhao, Weipeng, Li, Shufen, Zhang, Li, Meng, Wenjing, Wang, Shuling, Tong, Zhongsheng, Zeng, Yanwu, Lu, Leilei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9046571/
https://www.ncbi.nlm.nih.gov/pubmed/35494043
http://dx.doi.org/10.3389/fonc.2022.778511
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author Hao, Chunfang
Wang, Chen
Lu, Ning
Zhao, Weipeng
Li, Shufen
Zhang, Li
Meng, Wenjing
Wang, Shuling
Tong, Zhongsheng
Zeng, Yanwu
Lu, Leilei
author_facet Hao, Chunfang
Wang, Chen
Lu, Ning
Zhao, Weipeng
Li, Shufen
Zhang, Li
Meng, Wenjing
Wang, Shuling
Tong, Zhongsheng
Zeng, Yanwu
Lu, Leilei
author_sort Hao, Chunfang
collection PubMed
description BACKGROUND: Clinical characteristics including estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor 2 (HER2) are important biomarkers in the treatment of breast cancer, but how genomic mutations affect their status is rarely studied. This study aimed at finding genomic mutations associated with these clinical characteristics. METHODS: There were 160 patients with breast cancer enrolled in this study. Samples from those patients were used for next-generation sequencing, targeting a panel of 624 pan-cancer genes. Short nucleotide mutations, copy number variations, and gene fusions were identified for each sample. Fisher’s exact test compared each pair of genes. A similarity score was constructed with the resulting P-values. Genes were clustered with the similarity scores. The identified gene clusters were compared to the status of clinical characteristics including ER, PR, HER2, and a family history of cancer (FH) in terms of the mutations in patients. RESULTS: Gene-by-gene analysis found that CCND1 mutations were positively correlated with ER status while ERBB2 and CDK12 mutations were positively correlated with HER2 status. Mutation-based clustering identified four gene clusters. Gene cluster 1 (ADGRA2, ZNF703, FGFR1, KAT6A, and POLB) was significantly associated with PR status; gene cluster 2 (COL1A1, AXIN2, ZNF217, GNAS, and BRIP1) and gene cluster 3 (FGF3, FGF4, FGF19, and CCND1) were significantly associated with ER status; gene cluster 2 was also negatively associated with a family history of cancer; and gene cluster 4 was significantly negatively associated with age. Patients were classified into four corresponding groups. Patient groups 1, 2, 3, and 4 had 24.1%, 36.5%, 38.7%, and 41.3% of patients with an FDA-recognized biomarker predictive of response to an FDA-approved drug, respectively. CONCLUSION: This study identified genomic mutations positively associated with ER and PR status. These findings not only revealed candidate genes in ER and PR status maintenance but also provided potential treatment targets for patients with endocrine therapy resistance.
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spelling pubmed-90465712022-04-29 Gene Mutations Associated With Clinical Characteristics in the Tumors of Patients With Breast Cancer Hao, Chunfang Wang, Chen Lu, Ning Zhao, Weipeng Li, Shufen Zhang, Li Meng, Wenjing Wang, Shuling Tong, Zhongsheng Zeng, Yanwu Lu, Leilei Front Oncol Oncology BACKGROUND: Clinical characteristics including estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor 2 (HER2) are important biomarkers in the treatment of breast cancer, but how genomic mutations affect their status is rarely studied. This study aimed at finding genomic mutations associated with these clinical characteristics. METHODS: There were 160 patients with breast cancer enrolled in this study. Samples from those patients were used for next-generation sequencing, targeting a panel of 624 pan-cancer genes. Short nucleotide mutations, copy number variations, and gene fusions were identified for each sample. Fisher’s exact test compared each pair of genes. A similarity score was constructed with the resulting P-values. Genes were clustered with the similarity scores. The identified gene clusters were compared to the status of clinical characteristics including ER, PR, HER2, and a family history of cancer (FH) in terms of the mutations in patients. RESULTS: Gene-by-gene analysis found that CCND1 mutations were positively correlated with ER status while ERBB2 and CDK12 mutations were positively correlated with HER2 status. Mutation-based clustering identified four gene clusters. Gene cluster 1 (ADGRA2, ZNF703, FGFR1, KAT6A, and POLB) was significantly associated with PR status; gene cluster 2 (COL1A1, AXIN2, ZNF217, GNAS, and BRIP1) and gene cluster 3 (FGF3, FGF4, FGF19, and CCND1) were significantly associated with ER status; gene cluster 2 was also negatively associated with a family history of cancer; and gene cluster 4 was significantly negatively associated with age. Patients were classified into four corresponding groups. Patient groups 1, 2, 3, and 4 had 24.1%, 36.5%, 38.7%, and 41.3% of patients with an FDA-recognized biomarker predictive of response to an FDA-approved drug, respectively. CONCLUSION: This study identified genomic mutations positively associated with ER and PR status. These findings not only revealed candidate genes in ER and PR status maintenance but also provided potential treatment targets for patients with endocrine therapy resistance. Frontiers Media S.A. 2022-04-14 /pmc/articles/PMC9046571/ /pubmed/35494043 http://dx.doi.org/10.3389/fonc.2022.778511 Text en Copyright © 2022 Hao, Wang, Lu, Zhao, Li, Zhang, Meng, Wang, Tong, Zeng and Lu 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 Oncology
Hao, Chunfang
Wang, Chen
Lu, Ning
Zhao, Weipeng
Li, Shufen
Zhang, Li
Meng, Wenjing
Wang, Shuling
Tong, Zhongsheng
Zeng, Yanwu
Lu, Leilei
Gene Mutations Associated With Clinical Characteristics in the Tumors of Patients With Breast Cancer
title Gene Mutations Associated With Clinical Characteristics in the Tumors of Patients With Breast Cancer
title_full Gene Mutations Associated With Clinical Characteristics in the Tumors of Patients With Breast Cancer
title_fullStr Gene Mutations Associated With Clinical Characteristics in the Tumors of Patients With Breast Cancer
title_full_unstemmed Gene Mutations Associated With Clinical Characteristics in the Tumors of Patients With Breast Cancer
title_short Gene Mutations Associated With Clinical Characteristics in the Tumors of Patients With Breast Cancer
title_sort gene mutations associated with clinical characteristics in the tumors of patients with breast cancer
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9046571/
https://www.ncbi.nlm.nih.gov/pubmed/35494043
http://dx.doi.org/10.3389/fonc.2022.778511
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