Prognostic Significance of SPARC Expression in Breast Cancer: A Meta-Analysis and Bioinformatics Analysis
Secreted protein, acidic and rich in cysteine (SPARC, also known as osteonectin), is a small molecule glycoprotein associated with cell secretions. The purpose of our research is to clarify the clinicopathological and prognostic significance of SPARC expression in breast cancer. In this study, we pe...
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| creator | Shi, Shuai Ma, Hong-Yan Han, Xin-Ying Sang, Yin-Zhou Yang, Ming-Yue Zhang, Zhi-Gang |
| description | Secreted protein, acidic and rich in cysteine (SPARC, also known as osteonectin), is a small molecule glycoprotein associated with cell secretions. The purpose of our research is to clarify the clinicopathological and prognostic significance of SPARC expression in breast cancer. In this study, we performed a meta-analysis and bioinformatics analysis using the PubMed, Web of Science, Wanfang Data, and CNKI databases. The meta-analysis showed that SPARC expression was elevated in breast cancer tissue, compared with normal tissue, while SPARC expression in tumor stromal cells was higher than that of tumor cells. The expression of SPARC was positively correlated with histological grade and TNM staging. The Kaplan-Meier plotter showed that low SPARC expression was negatively correlated with the overall, postprogression, and distant metastasis survival rates of patients. According to Oncomine database, SPARC expression was upregulated in breast cancer than normal tissues. In TCGA database, univariate analysis showed that lymph node metastasis, distant metastasis, and TNM staging were negatively correlated with patient prognosis in breast cancers. Cox multivariate analysis showed that age, lymph node metastasis, distant metastasis, and TNM staging were important factors affecting the survival time of breast cancer patients. SPARC expression can be employed as a good indicator of prognosis of breast cancer patients, which will provide new methods and ideas of preventive treatment. |
| doi_str_mv | 10.1155/2022/8600419 |
| format | Article |
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The purpose of our research is to clarify the clinicopathological and prognostic significance of SPARC expression in breast cancer. In this study, we performed a meta-analysis and bioinformatics analysis using the PubMed, Web of Science, Wanfang Data, and CNKI databases. The meta-analysis showed that SPARC expression was elevated in breast cancer tissue, compared with normal tissue, while SPARC expression in tumor stromal cells was higher than that of tumor cells. The expression of SPARC was positively correlated with histological grade and TNM staging. The Kaplan-Meier plotter showed that low SPARC expression was negatively correlated with the overall, postprogression, and distant metastasis survival rates of patients. According to Oncomine database, SPARC expression was upregulated in breast cancer than normal tissues. In TCGA database, univariate analysis showed that lymph node metastasis, distant metastasis, and TNM staging were negatively correlated with patient prognosis in breast cancers. Cox multivariate analysis showed that age, lymph node metastasis, distant metastasis, and TNM staging were important factors affecting the survival time of breast cancer patients. SPARC expression can be employed as a good indicator of prognosis of breast cancer patients, which will provide new methods and ideas of preventive treatment.</description><identifier>ISSN: 2314-6133</identifier><identifier>EISSN: 2314-6141</identifier><identifier>DOI: 10.1155/2022/8600419</identifier><identifier>PMID: 35211625</identifier><language>eng</language><publisher>United States: Hindawi</publisher><subject>Bioinformatics ; Biomedical materials ; Breast cancer ; Breast Neoplasms - metabolism ; Cancer ; Cell adhesion & migration ; Computational Biology ; Disease Progression ; Extracellular matrix ; Female ; Gene expression ; Genetic aspects ; Glycoproteins ; Health aspects ; Humans ; Lymph nodes ; Lymphatic system ; Medical prognosis ; Meta-analysis ; Metastases ; Metastasis ; Multivariate analysis ; Oncology, Experimental ; Osteonectin ; Osteonectin - metabolism ; Pancreatic cancer ; Patients ; Phosphorylation ; Prognosis ; Protein biosynthesis ; Proteins ; Review ; Secretions ; Software ; Stromal cells ; Survival ; Tissues ; Tumor cells ; Tumors ; Vascular endothelial growth factor</subject><ispartof>BioMed research international, 2022, Vol.2022 (1), p.8600419-8600419</ispartof><rights>Copyright © 2022 Shuai Shi et al.</rights><rights>COPYRIGHT 2022 John Wiley & Sons, Inc.</rights><rights>Copyright © 2022 Shuai Shi et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0</rights><rights>Copyright © 2022 Shuai Shi et al. 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c476t-36299c7f6965184542b2c546aa01195e32fd01f44312b08790c971e36a9b33a23</citedby><cites>FETCH-LOGICAL-c476t-36299c7f6965184542b2c546aa01195e32fd01f44312b08790c971e36a9b33a23</cites><orcidid>0000-0002-1674-5176</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8863438/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8863438/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,4010,27900,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35211625$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Aziz, Aziz ur Rehman</contributor><creatorcontrib>Shi, Shuai</creatorcontrib><creatorcontrib>Ma, Hong-Yan</creatorcontrib><creatorcontrib>Han, Xin-Ying</creatorcontrib><creatorcontrib>Sang, Yin-Zhou</creatorcontrib><creatorcontrib>Yang, Ming-Yue</creatorcontrib><creatorcontrib>Zhang, Zhi-Gang</creatorcontrib><title>Prognostic Significance of SPARC Expression in Breast Cancer: A Meta-Analysis and Bioinformatics Analysis</title><title>BioMed research international</title><addtitle>Biomed Res Int</addtitle><description>Secreted protein, acidic and rich in cysteine (SPARC, also known as osteonectin), is a small molecule glycoprotein associated with cell secretions. The purpose of our research is to clarify the clinicopathological and prognostic significance of SPARC expression in breast cancer. In this study, we performed a meta-analysis and bioinformatics analysis using the PubMed, Web of Science, Wanfang Data, and CNKI databases. The meta-analysis showed that SPARC expression was elevated in breast cancer tissue, compared with normal tissue, while SPARC expression in tumor stromal cells was higher than that of tumor cells. The expression of SPARC was positively correlated with histological grade and TNM staging. The Kaplan-Meier plotter showed that low SPARC expression was negatively correlated with the overall, postprogression, and distant metastasis survival rates of patients. According to Oncomine database, SPARC expression was upregulated in breast cancer than normal tissues. In TCGA database, univariate analysis showed that lymph node metastasis, distant metastasis, and TNM staging were negatively correlated with patient prognosis in breast cancers. Cox multivariate analysis showed that age, lymph node metastasis, distant metastasis, and TNM staging were important factors affecting the survival time of breast cancer patients. SPARC expression can be employed as a good indicator of prognosis of breast cancer patients, which will provide new methods and ideas of preventive treatment.</description><subject>Bioinformatics</subject><subject>Biomedical materials</subject><subject>Breast cancer</subject><subject>Breast Neoplasms - metabolism</subject><subject>Cancer</subject><subject>Cell adhesion & migration</subject><subject>Computational Biology</subject><subject>Disease Progression</subject><subject>Extracellular matrix</subject><subject>Female</subject><subject>Gene expression</subject><subject>Genetic aspects</subject><subject>Glycoproteins</subject><subject>Health aspects</subject><subject>Humans</subject><subject>Lymph nodes</subject><subject>Lymphatic system</subject><subject>Medical prognosis</subject><subject>Meta-analysis</subject><subject>Metastases</subject><subject>Metastasis</subject><subject>Multivariate analysis</subject><subject>Oncology, Experimental</subject><subject>Osteonectin</subject><subject>Osteonectin - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>BioMed research international</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Shi, Shuai</au><au>Ma, Hong-Yan</au><au>Han, Xin-Ying</au><au>Sang, Yin-Zhou</au><au>Yang, Ming-Yue</au><au>Zhang, Zhi-Gang</au><au>Aziz, Aziz ur Rehman</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Prognostic Significance of SPARC Expression in Breast Cancer: A Meta-Analysis and Bioinformatics Analysis</atitle><jtitle>BioMed research international</jtitle><addtitle>Biomed Res Int</addtitle><date>2022</date><risdate>2022</risdate><volume>2022</volume><issue>1</issue><spage>8600419</spage><epage>8600419</epage><pages>8600419-8600419</pages><issn>2314-6133</issn><eissn>2314-6141</eissn><abstract>Secreted protein, acidic and rich in cysteine (SPARC, also known as osteonectin), is a small molecule glycoprotein associated with cell secretions. The purpose of our research is to clarify the clinicopathological and prognostic significance of SPARC expression in breast cancer. In this study, we performed a meta-analysis and bioinformatics analysis using the PubMed, Web of Science, Wanfang Data, and CNKI databases. The meta-analysis showed that SPARC expression was elevated in breast cancer tissue, compared with normal tissue, while SPARC expression in tumor stromal cells was higher than that of tumor cells. The expression of SPARC was positively correlated with histological grade and TNM staging. The Kaplan-Meier plotter showed that low SPARC expression was negatively correlated with the overall, postprogression, and distant metastasis survival rates of patients. According to Oncomine database, SPARC expression was upregulated in breast cancer than normal tissues. In TCGA database, univariate analysis showed that lymph node metastasis, distant metastasis, and TNM staging were negatively correlated with patient prognosis in breast cancers. Cox multivariate analysis showed that age, lymph node metastasis, distant metastasis, and TNM staging were important factors affecting the survival time of breast cancer patients. SPARC expression can be employed as a good indicator of prognosis of breast cancer patients, which will provide new methods and ideas of preventive treatment.</abstract><cop>United States</cop><pub>Hindawi</pub><pmid>35211625</pmid><doi>10.1155/2022/8600419</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0002-1674-5176</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Bioinformatics Biomedical materials Breast cancer Breast Neoplasms - metabolism Cancer Cell adhesion & migration Computational Biology Disease Progression Extracellular matrix Female Gene expression Genetic aspects Glycoproteins Health aspects Humans Lymph nodes Lymphatic system Medical prognosis Meta-analysis Metastases Metastasis Multivariate analysis Oncology, Experimental Osteonectin Osteonectin - metabolism Pancreatic cancer Patients Phosphorylation Prognosis Protein biosynthesis Proteins Review Secretions Software Stromal cells Survival Tissues Tumor cells Tumors Vascular endothelial growth factor |
| title | Prognostic Significance of SPARC Expression in Breast Cancer: A Meta-Analysis and Bioinformatics Analysis |
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