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Tuly KF, Hossen MB, Islam MA, Kibria MK, Alam MS, Harun-Or-Roshid M, Begum AA, Hasan S, Mahumud RA, Mollah MNH. Robust Identification of Differential Gene Expression Patterns from Multiple Transcriptomics Datasets for Early Diagnosis, Prognosis, and Therapies for Breast Cancer. MEDICINA (KAUNAS, LITHUANIA) 2023; 59:1705. [PMID: 37893423 PMCID: PMC10608013 DOI: 10.3390/medicina59101705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 09/07/2023] [Accepted: 09/20/2023] [Indexed: 10/29/2023]
Abstract
Background and Objectives: Breast cancer (BC) is one of the major causes of cancer-related death in women globally. Proper identification of BC-causing hub genes (HubGs) for prognosis, diagnosis, and therapies at an earlier stage may reduce such death rates. However, most of the previous studies detected HubGs through non-robust statistical approaches that are sensitive to outlying observations. Therefore, the main objectives of this study were to explore BC-causing potential HubGs from robustness viewpoints, highlighting their early prognostic, diagnostic, and therapeutic performance. Materials and Methods: Integrated robust statistics and bioinformatics methods and databases were used to obtain the required results. Results: We robustly identified 46 common differentially expressed genes (cDEGs) between BC and control samples from three microarrays (GSE26910, GSE42568, and GSE65194) and one scRNA-seq (GSE235168) dataset. Then, we identified eight cDEGs (COL11A1, COL10A1, CD36, ACACB, CD24, PLK1, UBE2C, and PDK4) as the BC-causing HubGs by the protein-protein interaction (PPI) network analysis of cDEGs. The performance of BC and survival probability prediction models with the expressions of HubGs from two independent datasets (GSE45827 and GSE54002) and the TCGA (The Cancer Genome Atlas) database showed that our proposed HubGs might be considered as diagnostic and prognostic biomarkers, where two genes, COL11A1 and CD24, exhibit better performance. The expression analysis of HubGs by Box plots with the TCGA database in different stages of BC progression indicated their early diagnosis and prognosis ability. The HubGs set enrichment analysis with GO (Gene ontology) terms and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways disclosed some BC-causing biological processes, molecular functions, and pathways. Finally, we suggested the top-ranked six drug molecules (Suramin, Rifaximin, Telmisartan, Tukysa Tucatinib, Lynparza Olaparib, and TG.02) for the treatment of BC by molecular docking analysis with the proposed HubGs-mediated receptors. Molecular docking analysis results also showed that these drug molecules may inhibit cancer-related post-translational modification (PTM) sites (Succinylation, phosphorylation, and ubiquitination) of hub proteins. Conclusions: This study's findings might be valuable resources for diagnosis, prognosis, and therapies at an earlier stage of BC.
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Affiliation(s)
- Khanis Farhana Tuly
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (K.F.T.); (M.B.H.); (M.A.I.); (M.K.K.); (M.S.A.); (M.H.-O.-R.); (A.A.B.)
| | - Md. Bayazid Hossen
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (K.F.T.); (M.B.H.); (M.A.I.); (M.K.K.); (M.S.A.); (M.H.-O.-R.); (A.A.B.)
| | - Md. Ariful Islam
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (K.F.T.); (M.B.H.); (M.A.I.); (M.K.K.); (M.S.A.); (M.H.-O.-R.); (A.A.B.)
| | - Md. Kaderi Kibria
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (K.F.T.); (M.B.H.); (M.A.I.); (M.K.K.); (M.S.A.); (M.H.-O.-R.); (A.A.B.)
- Department of Statistics, Hajee Mohammad Danesh Science & Technology University, Dinajpur 5200, Bangladesh
| | - Md. Shahin Alam
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (K.F.T.); (M.B.H.); (M.A.I.); (M.K.K.); (M.S.A.); (M.H.-O.-R.); (A.A.B.)
| | - Md. Harun-Or-Roshid
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (K.F.T.); (M.B.H.); (M.A.I.); (M.K.K.); (M.S.A.); (M.H.-O.-R.); (A.A.B.)
| | - Anjuman Ara Begum
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (K.F.T.); (M.B.H.); (M.A.I.); (M.K.K.); (M.S.A.); (M.H.-O.-R.); (A.A.B.)
| | - Sohel Hasan
- Molecular and Biomedical Health Science Lab, Department of Biochemistry and Molecular Biology, University of Rajshahi, Rajshahi 6205, Bangladesh;
| | - Rashidul Alam Mahumud
- NHMRC Clinical Trials Centre, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia;
| | - Md. Nurul Haque Mollah
- Bioinformatics Lab, Department of Statistics, University of Rajshahi, Rajshahi 6205, Bangladesh; (K.F.T.); (M.B.H.); (M.A.I.); (M.K.K.); (M.S.A.); (M.H.-O.-R.); (A.A.B.)
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Hirano H, Abe Y, Nojima Y, Aoki M, Shoji H, Isoyama J, Honda K, Boku N, Mizuguchi K, Tomonaga T, Adachi J. Temporal dynamics from phosphoproteomics using endoscopic biopsy specimens provides new therapeutic targets in stage IV gastric cancer. Sci Rep 2022; 12:4419. [PMID: 35338158 PMCID: PMC8956597 DOI: 10.1038/s41598-022-08430-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2021] [Accepted: 03/08/2022] [Indexed: 11/09/2022] Open
Abstract
Phosphoproteomic analysis expands our understanding of cancer biology. However, the feasibility of phosphoproteomic analysis using endoscopically collected tumor samples, especially with regards to dynamic changes upon drug treatment, remains unknown in stage IV gastric cancer. Here, we conducted a phosphoproteomic analysis using paired endoscopic biopsy specimens of pre- and post-treatment tumors (Ts) and non-tumor adjacent tissues (NATs) obtained from 4 HER2-positive gastric cancer patients who received trastuzumab-based treatment and from pre-treatment Ts and NATs of 4 HER2-negative gastric cancer patients. Our analysis identified 14,622 class 1 phosphosites with 12,749 quantified phosphosites and revealed molecular changes by HER2 positivity and treatment. An inhibitory signature of the ErbB signaling was observed in the post-treatment HER2-positive T group compared with the pre-treatment HER2-positive T group. Phosphoproteomic profiles obtained by a case-by-case review using paired pre- and post-treatment HER2-positive T could be utilized to discover predictive or resistant biomarkers. Furthermore, these data nominated therapeutic kinase targets which were exclusively activated in the patient unresponded to the treatment. The present study suggests that a phosphoproteomic analysis of endoscopic biopsy specimens provides information on dynamic molecular changes which can individually characterize biologic features upon drug treatment and identify therapeutic targets in stage IV gastric cancer.
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Affiliation(s)
- Hidekazu Hirano
- Laboratory of Proteome Research, National Institute of Biomedical Innovation, Health and Nutrition, Osaka, 567-0085, Japan.,Laboratory of Proteomics for Drug Discovery, Center for Drug Design Research, National Institute of Biomedical Innovation, Health and Nutrition, Osaka, 567-0085, Japan.,Gastrointestinal Medical Oncology Division, National Cancer Center Hospital, Tokyo, 104-0045, Japan.,Department of Medicine, Keio University Graduate School of Medicine, Tokyo, 160-8582, Japan
| | - Yuichi Abe
- Laboratory of Proteome Research, National Institute of Biomedical Innovation, Health and Nutrition, Osaka, 567-0085, Japan.,Laboratory of Proteomics for Drug Discovery, Center for Drug Design Research, National Institute of Biomedical Innovation, Health and Nutrition, Osaka, 567-0085, Japan.,Division of Molecular Diagnostics, Aichi Cancer Center Research Institute, Nagoya, 464-8681, Japan
| | - Yosui Nojima
- Laboratory of Bioinformatics, Artificial Intelligence Center for Health and Biomedical Research (ArCHER), National Institutes of Biomedical Innovation, Health and Nutrition, Osaka, 567-0085, Japan.,Center for Mathematical Modeling and Data Science, Osaka University, Osaka, 560-8531, Japan
| | - Masahiko Aoki
- Gastrointestinal Medical Oncology Division, National Cancer Center Hospital, Tokyo, 104-0045, Japan.,Kyoto Innovation Center for Next Generation Clinical Trials and iPS Cell Therapy (Ki-CONNECT), Kyoto University Hospital, Kyoto, 606-8507, Japan
| | - Hirokazu Shoji
- Gastrointestinal Medical Oncology Division, National Cancer Center Hospital, Tokyo, 104-0045, Japan
| | - Junko Isoyama
- Laboratory of Proteome Research, National Institute of Biomedical Innovation, Health and Nutrition, Osaka, 567-0085, Japan.,Laboratory of Proteomics for Drug Discovery, Center for Drug Design Research, National Institute of Biomedical Innovation, Health and Nutrition, Osaka, 567-0085, Japan
| | - Kazufumi Honda
- Department of Biomarkers for Early Detection of Cancer, National Cancer Center Research Institute, Tokyo, 104-0045, Japan.,Department of Bioregulation, Nippon Medical School, Bunkyo-ku, Tokyo, 113-8602, Japan
| | - Narikazu Boku
- Gastrointestinal Medical Oncology Division, National Cancer Center Hospital, Tokyo, 104-0045, Japan.,Department of Medical Oncology and General Medicine, IMSUT Hospital, Institute of Medical Science, University of Tokyo, Tokyo, 108-8639, Japan
| | - Kenji Mizuguchi
- Laboratory of Bioinformatics, Artificial Intelligence Center for Health and Biomedical Research (ArCHER), National Institutes of Biomedical Innovation, Health and Nutrition, Osaka, 567-0085, Japan.,Institute for Protein Research, Osaka University, Osaka, 565-0871, Japan
| | - Takeshi Tomonaga
- Laboratory of Proteome Research, National Institute of Biomedical Innovation, Health and Nutrition, Osaka, 567-0085, Japan. .,Laboratory of Proteomics for Drug Discovery, Center for Drug Design Research, National Institute of Biomedical Innovation, Health and Nutrition, Osaka, 567-0085, Japan.
| | - Jun Adachi
- Laboratory of Proteome Research, National Institute of Biomedical Innovation, Health and Nutrition, Osaka, 567-0085, Japan. .,Laboratory of Proteomics for Drug Discovery, Center for Drug Design Research, National Institute of Biomedical Innovation, Health and Nutrition, Osaka, 567-0085, Japan. .,Laboratory of Clinical and Analytical Chemistry, Center for Drug Design Research, National Institute of Biomedical Innovation, Health and Nutrition, Osaka, 567-0085, Japan.
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Sivakumar Harish T, Ramesh Babu P, Shrestha A, Balasubramanian B, Chinnathambi A, Ali Alharbi S. Development of a Model System to Study Expression Profile of RAC2 Gene in Breast Cancer MDA-MB-231 Cell Line. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE : ECAM 2022; 2022:2077850. [PMID: 35368753 PMCID: PMC8970810 DOI: 10.1155/2022/2077850] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/08/2022] [Accepted: 02/19/2022] [Indexed: 12/24/2022]
Abstract
The RAC2 gene encoding GTPases involve cellular signaling of actin polymerization, cell migration, and formation of the phagocytic NADPH oxidase complex. Oncogenic mutations in the RAC2 gene have been identified in various cancers, and extensive research is in progress to delineate its signaling pathways and identify potential therapeutic targets in breast cancers. This paper explored developing a bioinformatics model system to understand the RAC2 gene expression pattern concerning estrogenic receptor status in breast cancers. We have used the MDA-MB-231 breast cancer cell line to identify RAC2 gene expression. To simplify the development of model system with one dataset, we retrieved the microarray dataset GSE27515 from the Gene Expression Omnibus (GEO) for the differential gene expression analysis. Then, network analysis, pathway enrichment analysis, volcano plot, ORA, and the up/downregulated genes were used to highlight genes involved in signaling network pathways. We observed that the RAC2 gene is upregulated in the GSM679722, GSM676923, and GSM679724 downregulated in the samples GSM676925, GSM676926, and GSM676927 from the GEO dataset. Our observation found that the RAC2 gene is upregulated in the estrogen receptor (ER) negative breast cancers and downregulated in ER-positive breast cancer, involving pathways such as focal adhesion, MAPK signaling, axon guidance, and VEGF signaling pathway.
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Affiliation(s)
- Thogulva Sivakumar Harish
- Department of Genetic Engineering, Bharath Institute of Higher Education and Research, Selaiyur, Chennai-73, India
| | - Polani Ramesh Babu
- Center for Materials Engineering and Regenerative Medicine, Bharath Institute of Higher Education and Research, Selaiyur, Chennai-73, India
| | - Anupama Shrestha
- Department of Biotechnology, School of Science, Kathmandu University, P.O Box: 6250, Dhulikhel, Nepal
| | | | - Arunachalam Chinnathambi
- Department of Botany and Microbiology, College of Science, King Saud University, PO Box-2455, Riyadh 11451, Saudi Arabia
| | - Sulaiman Ali Alharbi
- Department of Botany and Microbiology, College of Science, King Saud University, PO Box-2455, Riyadh 11451, Saudi Arabia
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Kim HE, Kim J, Maeng S, Oh B, Hwang KT, Kim BS. Microbiota of Breast Tissue and Its Potential Association with Regional Recurrence of Breast Cancer in Korean Women. J Microbiol Biotechnol 2021; 31:1643-1655. [PMID: 34584037 PMCID: PMC9705848 DOI: 10.4014/jmb.2106.06039] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 08/31/2021] [Accepted: 09/23/2021] [Indexed: 12/15/2022]
Abstract
Recent studies have reported dysbiosis of the microbiome in breast tissue collected from patients with breast cancer and the association between the microbiota and disease progression. However, the role of the microbiota in breast tissue remains unclear, possibly due to the complexity of breast cancer and various factors, including racial and geographical differences, influencing microbiota in breast tissue. Here, to determine the potential role of microbiota in breast tumor tissue, we analyzed 141 tissue samples based on three different tissue types (tumor, adjacent normal, and lymph node tissues) from the same patients with breast cancer in Korea. The microbiota was not simply distinguishable based on tissue types. However, the microbiota could be divided into two cluster types, even within the same tissue type, and the clinicopathologic factors were differently correlated in the two cluster types. Risk of regional recurrence was also significantly different between the microbiota cluster types (p = 0.014). In predicted function analysis, the pentose and glucuronate interconversions were significantly different between the cluster types (q < 0.001), and Enterococcus was the main genus contributing to these differences (q < 0.01). Results showed that the microbiota of breast tissue could interact with the host and influence the risk of regional recurrence. Although further studies would be recommended to validate our results, this study could expand our understanding on the breast tissue microbiota, and the results might be applied to develop novel prediction methods and treatments for patients with breast cancer.
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Affiliation(s)
- Hyo-Eun Kim
- Department of Life Science, Multidisciplinary Genome Institute, Hallym University, Chuncheon, Gangwon-do 24252, Republic of Korea
| | - Jongjin Kim
- Department of Surgery, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul 07061, Republic of Korea
| | - Sejung Maeng
- Department of Surgery, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul 07061, Republic of Korea
| | - Bumjo Oh
- Department of Family Medicine, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul 07061, Republic of Korea
| | - Ki-Tae Hwang
- Department of Surgery, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul 07061, Republic of Korea,Corresponding authors K.T. Hwang Phone: +82-2-870-2275 Fax: +82-2-831-2826 E-mail:
| | - Bong-Soo Kim
- Department of Life Science, Multidisciplinary Genome Institute, Hallym University, Chuncheon, Gangwon-do 24252, Republic of Korea,The Korean Institute of Nutrition, Hallym University, Chuncheon, Gangwon-do 24252, Republic of Korea,
B.S. Kim Phone: +82-33-248-2093 Fax: +82-33-256-3420 E-mail:
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Liu Y, Teng L, Fu S, Wang G, Li Z, Ding C, Wang H, Bi L. Highly heterogeneous-related genes of triple-negative breast cancer: potential diagnostic and prognostic biomarkers. BMC Cancer 2021; 21:644. [PMID: 34053447 PMCID: PMC8165798 DOI: 10.1186/s12885-021-08318-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Accepted: 05/04/2021] [Indexed: 02/07/2023] Open
Abstract
Background Triple-negative breast cancer (TNBC) is a highly heterogeneous subtype of breast cancer, showing aggressive clinical behaviors and poor outcomes. It urgently needs new therapeutic strategies to improve the prognosis of TNBC. Bioinformatics analyses have been widely used to identify potential biomarkers for facilitating TNBC diagnosis and management. Methods We identified potential biomarkers and analyzed their diagnostic and prognostic values using bioinformatics approaches. Including differential expression gene (DEG) analysis, Receiver Operating Characteristic (ROC) curve analysis, functional enrichment analysis, Protein-Protein Interaction (PPI) network construction, survival analysis, multivariate Cox regression analysis, and Non-negative Matrix Factorization (NMF). Results A total of 105 DEGs were identified between TNBC and other breast cancer subtypes, which were regarded as heterogeneous-related genes. Subsequently, the KEGG enrichment analysis showed that these genes were significantly enriched in ‘cell cycle’ and ‘oocyte meiosis’ related pathways. Four (FAM83B, KITLG, CFD and RBM24) of 105 genes were identified as prognostic signatures in the disease-free interval (DFI) of TNBC patients, as for progression-free interval (PFI), five genes (FAM83B, EXO1, S100B, TYMS and CFD) were obtained. Time-dependent ROC analysis indicated that the multivariate Cox regression models, which were constructed based on these genes, had great predictive performances. Finally, the survival analysis of TNBC subtypes (mesenchymal stem-like [MSL] and mesenchymal [MES]) suggested that FAM83B significantly affected the prognosis of patients. Conclusions The multivariate Cox regression models constructed from four heterogeneous-related genes (FAM83B, KITLG, RBM24 and S100B) showed great prediction performance for TNBC patients’ prognostic. Moreover, FAM83B was an important prognostic feature in several TNBC subtypes (MSL and MES). Our findings provided new biomarkers to facilitate the targeted therapies of TNBC and TNBC subtypes. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-021-08318-1.
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Affiliation(s)
- Yiduo Liu
- School of Integrated Chinese and Western Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing, 210023, Jiangsu, China
| | - Linxin Teng
- School of Integrated Chinese and Western Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing, 210023, Jiangsu, China
| | - Shiyi Fu
- School of Integrated Chinese and Western Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing, 210023, Jiangsu, China
| | - Guiyang Wang
- School of Integrated Chinese and Western Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing, 210023, Jiangsu, China
| | - Zhengjun Li
- College of Health Economics Management, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing, 210023, Jiangsu, China
| | - Chao Ding
- School of Integrated Chinese and Western Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing, 210023, Jiangsu, China
| | - Haodi Wang
- School of Integrated Chinese and Western Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing, 210023, Jiangsu, China
| | - Lei Bi
- School of Integrated Chinese and Western Medicine, Nanjing University of Chinese Medicine, 138 Xianlin Road, Nanjing, 210023, Jiangsu, China.
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Identification of Hub Genes to Regulate Breast Cancer Spinal Metastases by Bioinformatics Analyses. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2021; 2021:5548918. [PMID: 34055036 PMCID: PMC8133842 DOI: 10.1155/2021/5548918] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 03/17/2021] [Accepted: 03/29/2021] [Indexed: 12/24/2022]
Abstract
Breast cancer (BC) had been one of the deadliest types of cancers in women worldwide. More than 65% of advanced-stage BC patients were identified to have bone metastasis. However, the molecular mechanisms involved in the BC spinal metastases remained largely unclear. This study screened dysregulated genes in the progression of BC spinal metastases by analyzing GSE22358. Moreover, we constructed PPI networks to identify key regulators in this progression. Bioinformatics analysis showed that these key regulators were involved in regulating the metabolic process, cell proliferation, Toll-like receptor and RIG-I-like receptor signaling, and mRNA surveillance. Furthermore, our analysis revealed that key regulators, including C1QB, CEP55, HIST1H2BO, IFI6, KIAA0101, PBK, SPAG5, SPP1, DCN, FZD7, KRT5, and TGFBR3, were correlated to the OS time in BC patients. In addition, we analyzed TCGA database to further confirm the expression levels of these hub genes in breast cancer. Our results showed that these regulators were significantly differentially expressed in breast cancer, which were consistent with GSE22358 dataset analysis. Furthermore, our analysis demonstrated that CEP55 was remarkably upregulated in the advanced stage of breast cancer compared to the stage I breast cancer sample and was significantly upregulated in triple-negative breast cancers (TNBC) compared to other types of breast cancers, including luminal and HER2-positive cancers, demonstrating CEP55 may have a regulatory role in TNBC. Finally, our results showed that CEP55 was the most highly expressed in Basal-like 1 TNBC and Basal-like 2 TNBC samples but the most lowly expressed in mesenchymal stem-like TNBC samples. Although more studies are still needed to understand the functions of key regulators in BC, this study provides useful information to understand the mechanisms underlying BC spinal metastases.
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Zhao B, Xu Y, Zhao Y, Shen S, Sun Q. Identification of Potential Key Genes Associated With the Pathogenesis, Metastasis, and Prognosis of Triple-Negative Breast Cancer on the Basis of Integrated Bioinformatics Analysis. Front Oncol 2020; 10:856. [PMID: 32596149 PMCID: PMC7304260 DOI: 10.3389/fonc.2020.00856] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Accepted: 04/30/2020] [Indexed: 12/13/2022] Open
Abstract
Objective: Breast cancer is the most common solid tumor affecting women and the second leading cause of cancer-related death worldwide, and triple-negative breast cancer (TNBC) is the most lethal subtype of breast cancer. We aimed to identify potential TNBC-specific therapeutic targets by performing an integrative analysis on previously published TNBC transcriptome microarray data. Methods: Differentially expressed genes (DEGs) between TNBC and normal breast tissues were screened using six Gene Expression Omnibus (GEO) datasets, and DEGs between metastatic TNBC and non-metastatic TNBC were screened using one GEO dataset. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were performed on the overlapping DEGs. The Cancer Genome Atlas (TCGA) TNBC data were used to identify candidate genes that were strongly associated with survival. Expression of the candidate genes in TNBC cell lines was blocked or augmented using a lentivirus system, and transwell assays were used to determine their effect on TNBC migration. Results: Eight upregulated genes and nine downregulated genes were found to be differentially expressed both between TNBC and normal breast tissues and between metastatic TNBC and non-metastatic TNBC. Among them, S100P and SDC1 were identified as poor prognostic genes. Furthermore, compared with control cells, SDC1-overexpressing TNBC cells showed enhanced migration ability, whereas SDC1 knockdown markedly reduced the migration of TNBC cells. Conclusion: Our study determined that S100P and SDC1 may be potential treatment targets as well as prognostic biomarkers of TNBC.
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Affiliation(s)
- Bin Zhao
- Department of Breast Surgery, Peking Union Medical College Hospital, Beijing, China
| | - Yali Xu
- Department of Breast Surgery, Peking Union Medical College Hospital, Beijing, China
| | - Yang Zhao
- Department of Surgery, Peking Union Medical College Hospital, Beijing, China
| | - Songjie Shen
- Department of Breast Surgery, Peking Union Medical College Hospital, Beijing, China
| | - Qiang Sun
- Department of Breast Surgery, Peking Union Medical College Hospital, Beijing, China
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Chen J, Liu C, Cen J, Liang T, Xue J, Zeng H, Zhang Z, Xu G, Yu C, Lu Z, Wang Z, Jiang J, Zhan X, Zeng J. KEGG-expressed genes and pathways in triple negative breast cancer: Protocol for a systematic review and data mining. Medicine (Baltimore) 2020; 99:e19986. [PMID: 32358373 PMCID: PMC7440132 DOI: 10.1097/md.0000000000019986] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND The incidence of triple negative breast cancer (TNBC) is at a relatively high level, and our study aimed to identify differentially expressed genes (DEGs) in TNBC and explore the key pathways and genes of TNBC. METHODS The gene expression profiling (GSE86945, GSE86946 and GSE102088) data were obtained from Gene Expression Omnibus Datasets, DEGs were identified by using R software, Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of DEGs were performed by the Database for Annotation, Visualization and Integrated Discovery (DAVID) tools, and the protein-protein interaction (PPI) network of the DEGs was constructed by the STRING database and visualized by Cytoscape software. Finally, the survival value of hub DEGs in breast cancer patients were performed by the Kaplan-Meier plotter online tool. RESULTS A total of 2998 DEGs were identified between TNBC and health breast tissue, including 411 up-regulated DEGs and 2587 down-regulated DEGs. GO analysis results showed that down-regulated DEGs were enriched in gene expression (BP), extracellular exosome (CC), and nucleic acid binding, and up-regulated were enriched in chromatin assembly (BP), nucleosome (CC), and DNA binding (MF). KEGG pathway results showed that DEGs were mainly enriched in Pathways in cancer and Systemic lupus erythematosus and so on. Top 10 hub genes were picked out from PPI network by connective degree, and 7 of top 10 hub genes were significantly related with adverse overall survival in breast cancer patients (P < .05). Further analysis found that only EGFR had a significant association with the prognosis of triple-negative breast cancer (P < .05). CONCLUSIONS Our study showed that DEGs were enriched in pathways in cancer, top 10 DEGs belong to up-regulated DEGs, and 7 gene connected with poor prognosis in breast cancer, including HSP90AA1, SRC, HSPA8, ESR1, ACTB, PPP2CA, and RPL4. These can provide some guidance for our research on the diagnosis and prognosis of TNBC, and further research is needed to evaluate their value in the targeted therapy of TNBC.
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Affiliation(s)
| | - Chong Liu
- Department of Spine and Osteopathy Ward
| | | | - Tuo Liang
- Department of Spine and Osteopathy Ward
| | - Jiang Xue
- Department of Spine and Osteopathy Ward
| | | | | | | | | | | | | | - Jie Jiang
- Department of Spine and Osteopathy Ward
| | | | - Jian Zeng
- Department of Gastrointestinal Gland Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, People's Republic of China
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