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Transcriptome profiling revealed multiple genes and ECM-receptor interaction pathways that may be associated with breast cancer
BACKGROUND: Exploration of the genes with abnormal expression during the development of breast cancer is essential to provide a deeper understanding of the mechanisms involved. Transcriptome sequencing and bioinformatics analysis of invasive ductal carcinoma and paracancerous tissues from the same p...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6554968/ https://www.ncbi.nlm.nih.gov/pubmed/31182966 http://dx.doi.org/10.1186/s11658-019-0162-0 |
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author | Bao, Yulong Wang, Li Shi, Lin Yun, Fen Liu, Xia Chen, Yongxia Chen, Chen Ren, Yanni Jia, Yongfeng |
author_facet | Bao, Yulong Wang, Li Shi, Lin Yun, Fen Liu, Xia Chen, Yongxia Chen, Chen Ren, Yanni Jia, Yongfeng |
author_sort | Bao, Yulong |
collection | PubMed |
description | BACKGROUND: Exploration of the genes with abnormal expression during the development of breast cancer is essential to provide a deeper understanding of the mechanisms involved. Transcriptome sequencing and bioinformatics analysis of invasive ductal carcinoma and paracancerous tissues from the same patient were performed to identify the key genes and signaling pathways related to breast cancer development. METHODS: Samples of breast tumor tissue and paracancerous breast tissue were obtained from 6 patients. Sequencing used the Illumina HiSeq platform. All. Only perfectly matched clean reads were mapped to the reference genome database, further analyzed and annotated based on the reference genome information. Differentially expressed genes (DEGs) were identified using the DESeq R package (1.10.1) and DEGSeq R package (1.12.0). Using KOBAS software to execute the KEGG bioinformatics analyses, enriched signaling pathways of DEGs involved in the occurrence of breast cancer were determined. Subsequently, quantitative real time PCR was used to verify the accuracy of the expression profile of key DEGs from the RNA-seq result and to explore the expression patterns of novel cancer-related genes on 8 different clinical individuals. RESULTS: The transcriptomic sequencing results showed 937 DEGs, including 487 upregulated and 450 downregulated genes in the breast cancer specimens. Further quantitative gene expression analysis was performed and captured 252 DEGs (201 downregulated and 51 upregulated) that showed the same differential expression pattern in all libraries. Finally, 6 upregulated DEGs (CST2, DRP2, CLEC5A, SCD, KIAA1211, DTL) and 6 downregulated DEGs (STAC2, BTNL9, CA4, CD300LG, GPIHBP1 and PIGR), were confirmed in a quantitative real time PCR comparison of breast cancer and paracancerous breast tissues from 8 clinical specimens. KEGG analysis revealed various pathway changes, including 20 upregulated and 21 downregulated gene enrichment pathways. The extracellular matrix–receptor (ECM-receptor) interaction pathway was the most enriched pathway: all genes in this pathway were DEGs, including the THBS family, collagen and fibronectin. These DEGs and the ECM-receptor interaction pathway may perform important roles in breast cancer. CONCLUSION: Several potential breast cancer-related genes and pathways were captured, including 7 novel upregulated genes and 76 novel downregulated genes that were not found in other studies. These genes are related to cell proliferation, movement and adhesion. They may be important for research into breast cancer mechanisms, particularly CST2 and CA4. A key signaling pathway, the ECM-receptor interaction signal pathway, was also identified as possibly involved in the development of breast cancer. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s11658-019-0162-0) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6554968 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-65549682019-06-10 Transcriptome profiling revealed multiple genes and ECM-receptor interaction pathways that may be associated with breast cancer Bao, Yulong Wang, Li Shi, Lin Yun, Fen Liu, Xia Chen, Yongxia Chen, Chen Ren, Yanni Jia, Yongfeng Cell Mol Biol Lett Research BACKGROUND: Exploration of the genes with abnormal expression during the development of breast cancer is essential to provide a deeper understanding of the mechanisms involved. Transcriptome sequencing and bioinformatics analysis of invasive ductal carcinoma and paracancerous tissues from the same patient were performed to identify the key genes and signaling pathways related to breast cancer development. METHODS: Samples of breast tumor tissue and paracancerous breast tissue were obtained from 6 patients. Sequencing used the Illumina HiSeq platform. All. Only perfectly matched clean reads were mapped to the reference genome database, further analyzed and annotated based on the reference genome information. Differentially expressed genes (DEGs) were identified using the DESeq R package (1.10.1) and DEGSeq R package (1.12.0). Using KOBAS software to execute the KEGG bioinformatics analyses, enriched signaling pathways of DEGs involved in the occurrence of breast cancer were determined. Subsequently, quantitative real time PCR was used to verify the accuracy of the expression profile of key DEGs from the RNA-seq result and to explore the expression patterns of novel cancer-related genes on 8 different clinical individuals. RESULTS: The transcriptomic sequencing results showed 937 DEGs, including 487 upregulated and 450 downregulated genes in the breast cancer specimens. Further quantitative gene expression analysis was performed and captured 252 DEGs (201 downregulated and 51 upregulated) that showed the same differential expression pattern in all libraries. Finally, 6 upregulated DEGs (CST2, DRP2, CLEC5A, SCD, KIAA1211, DTL) and 6 downregulated DEGs (STAC2, BTNL9, CA4, CD300LG, GPIHBP1 and PIGR), were confirmed in a quantitative real time PCR comparison of breast cancer and paracancerous breast tissues from 8 clinical specimens. KEGG analysis revealed various pathway changes, including 20 upregulated and 21 downregulated gene enrichment pathways. The extracellular matrix–receptor (ECM-receptor) interaction pathway was the most enriched pathway: all genes in this pathway were DEGs, including the THBS family, collagen and fibronectin. These DEGs and the ECM-receptor interaction pathway may perform important roles in breast cancer. CONCLUSION: Several potential breast cancer-related genes and pathways were captured, including 7 novel upregulated genes and 76 novel downregulated genes that were not found in other studies. These genes are related to cell proliferation, movement and adhesion. They may be important for research into breast cancer mechanisms, particularly CST2 and CA4. A key signaling pathway, the ECM-receptor interaction signal pathway, was also identified as possibly involved in the development of breast cancer. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s11658-019-0162-0) contains supplementary material, which is available to authorized users. BioMed Central 2019-06-06 /pmc/articles/PMC6554968/ /pubmed/31182966 http://dx.doi.org/10.1186/s11658-019-0162-0 Text en © The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Bao, Yulong Wang, Li Shi, Lin Yun, Fen Liu, Xia Chen, Yongxia Chen, Chen Ren, Yanni Jia, Yongfeng Transcriptome profiling revealed multiple genes and ECM-receptor interaction pathways that may be associated with breast cancer |
title | Transcriptome profiling revealed multiple genes and ECM-receptor interaction pathways that may be associated with breast cancer |
title_full | Transcriptome profiling revealed multiple genes and ECM-receptor interaction pathways that may be associated with breast cancer |
title_fullStr | Transcriptome profiling revealed multiple genes and ECM-receptor interaction pathways that may be associated with breast cancer |
title_full_unstemmed | Transcriptome profiling revealed multiple genes and ECM-receptor interaction pathways that may be associated with breast cancer |
title_short | Transcriptome profiling revealed multiple genes and ECM-receptor interaction pathways that may be associated with breast cancer |
title_sort | transcriptome profiling revealed multiple genes and ecm-receptor interaction pathways that may be associated with breast cancer |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6554968/ https://www.ncbi.nlm.nih.gov/pubmed/31182966 http://dx.doi.org/10.1186/s11658-019-0162-0 |
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