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Ye Q, Raese RA, Luo D, Feng J, Xin W, Dong C, Qian Y, Guo NL. MicroRNA-Based Discovery of Biomarkers, Therapeutic Targets, and Repositioning Drugs for Breast Cancer. Cells 2023; 12:1917. [PMID: 37508580 PMCID: PMC10378316 DOI: 10.3390/cells12141917] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 07/14/2023] [Accepted: 07/19/2023] [Indexed: 07/30/2023] Open
Abstract
Breast cancer treatment can be improved with biomarkers for early detection and individualized therapy. A set of 86 microRNAs (miRNAs) were identified to separate breast cancer tumors from normal breast tissues (n = 52) with an overall accuracy of 90.4%. Six miRNAs had concordant expression in both tumors and breast cancer patient blood samples compared with the normal control samples. Twelve miRNAs showed concordant expression in tumors vs. normal breast tissues and patient survival (n = 1093), with seven as potential tumor suppressors and five as potential oncomiRs. From experimentally validated target genes of these 86 miRNAs, pan-sensitive and pan-resistant genes with concordant mRNA and protein expression associated with in-vitro drug response to 19 NCCN-recommended breast cancer drugs were selected. Combined with in-vitro proliferation assays using CRISPR-Cas9/RNAi and patient survival analysis, MEK inhibitors PD19830 and BRD-K12244279, pilocarpine, and tremorine were discovered as potential new drug options for treating breast cancer. Multi-omics biomarkers of response to the discovered drugs were identified using human breast cancer cell lines. This study presented an artificial intelligence pipeline of miRNA-based discovery of biomarkers, therapeutic targets, and repositioning drugs that can be applied to many cancer types.
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Affiliation(s)
- Qing Ye
- West Virginia University Cancer Institute/Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA
| | - Rebecca A Raese
- West Virginia University Cancer Institute/Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA
| | - Dajie Luo
- West Virginia University Cancer Institute/Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA
| | - Juan Feng
- West Virginia University Cancer Institute/Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA
| | - Wenjun Xin
- West Virginia University Cancer Institute/Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA
| | - Chunlin Dong
- West Virginia University Cancer Institute/Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA
| | - Yong Qian
- Health Effects Laboratory Division, National Institute for Occupational and Safety & Health, Morgantown, WV 26505, USA
| | - Nancy Lan Guo
- West Virginia University Cancer Institute/Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA
- Department of Occupational and Environmental Health Sciences, School of Public Health, West Virginia University, Morgantown, WV 26506, USA
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Ye Q, Wang J, Ducatman B, Raese RA, Rogers JL, Wan YW, Dong C, Padden L, Pugacheva EN, Qian Y, Guo NL. Expression-Based Diagnosis, Treatment Selection, and Drug Development for Breast Cancer. Int J Mol Sci 2023; 24:10561. [PMID: 37445737 DOI: 10.3390/ijms241310561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 06/06/2023] [Accepted: 06/21/2023] [Indexed: 07/15/2023] Open
Abstract
There is currently no gene expression assay that can assess if premalignant lesions will develop into invasive breast cancer. This study sought to identify biomarkers for selecting patients with a high potential for developing invasive carcinoma in the breast with normal histology, benign lesions, or premalignant lesions. A set of 26-gene mRNA expression profiles were used to identify invasive ductal carcinomas from histologically normal tissue and benign lesions and to select those with a higher potential for future cancer development (ADHC) in the breast associated with atypical ductal hyperplasia (ADH). The expression-defined model achieved an overall accuracy of 94.05% (AUC = 0.96) in classifying invasive ductal carcinomas from histologically normal tissue and benign lesions (n = 185). This gene signature classified cancer development in ADH tissues with an overall accuracy of 100% (n = 8). The mRNA expression patterns of these 26 genes were validated using RT-PCR analyses of independent tissue samples (n = 77) and blood samples (n = 48). The protein expression of PBX2 and RAD52 assessed with immunohistochemistry were prognostic of breast cancer survival outcomes. This signature provided significant prognostic stratification in The Cancer Genome Atlas breast cancer patients (n = 1100), as well as basal-like and luminal A subtypes, and was associated with distinct immune infiltration and activities. The mRNA and protein expression of the 26 genes was associated with sensitivity or resistance to 18 NCCN-recommended drugs for treating breast cancer. Eleven genes had significant proliferative potential in CRISPR-Cas9/RNAi screening. Based on this gene expression signature, the VEGFR inhibitor ZM-306416 was discovered as a new drug for treating breast cancer.
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Affiliation(s)
- Qing Ye
- West Virginia University Cancer Institute/Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA
| | - Jiajia Wang
- West Virginia University Cancer Institute/Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA
| | - Barbara Ducatman
- Department of Pathology, West Virginia University, Morgantown, WV 26506, USA
| | - Rebecca A Raese
- West Virginia University Cancer Institute/Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA
| | - Jillian L Rogers
- West Virginia University Cancer Institute/Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA
| | - Ying-Wooi Wan
- West Virginia University Cancer Institute/Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA
| | - Chunlin Dong
- West Virginia University Cancer Institute/Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA
| | - Lindsay Padden
- West Virginia University Cancer Institute/Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA
| | - Elena N Pugacheva
- West Virginia University Cancer Institute/Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA
- Department of Biochemistry and Molecular Medicine, School of Medicine, West Virginia University, Morgantown, WV 26506, USA
- Department of Radiation Oncology, School of Medicine, West Virginia University, Morgantown, WV 26506, USA
| | - Yong Qian
- Pathology and Physiology Research Branch, National Institute for Occupational Safety and Health, Morgantown, WV 26505, USA
| | - Nancy Lan Guo
- West Virginia University Cancer Institute/Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA
- Department of Occupational and Environmental Health Sciences, School of Public Health, West Virginia University, Morgantown, WV 26506, USA
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Guo NL, Dowlati A, Raese RA, Dong C, Chen G, Beer DG, Shaffer J, Singh S, Bokhary U, Liu L, Howington J, Hensing T, Qian Y. A Predictive 7-Gene Assay and Prognostic Protein Biomarkers for Non-small Cell Lung Cancer. EBioMedicine 2018; 32:102-110. [PMID: 29861409 PMCID: PMC6020749 DOI: 10.1016/j.ebiom.2018.05.025] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Revised: 05/09/2018] [Accepted: 05/21/2018] [Indexed: 12/31/2022] Open
Abstract
PURPOSE This study aims to develop a multi-gene assay predictive of the clinical benefits of chemotherapy in non-small cell lung cancer (NSCLC) patients, and substantiate their protein expression as potential therapeutic targets. PATIENTS AND METHODS The mRNA expression of 160 genes identified from microarray was analyzed in qRT-PCR assays of independent 337 snap-frozen NSCLC tumors to develop a predictive signature. A clinical trial JBR.10 was included in the validation. Hazard ratio was used to select genes, and decision-trees were used to construct the predictive model. Protein expression was quantified with AQUA in 500 FFPE NSCLC samples. RESULTS A 7-gene signature was identified from training cohort (n = 83) with accurate patient stratification (P = 0.0043) and was validated in independent patient cohorts (n = 248, P < 0.0001) in Kaplan-Meier analyses. In the predicted benefit group, there was a significantly better disease-specific survival in patients receiving adjuvant chemotherapy in both training (P = 0.035) and validation (P = 0.0049) sets. In the predicted non-benefit group, there was no survival benefit in patients receiving chemotherapy in either set. The protein expression of ZNF71 quantified with AQUA scores produced robust patient stratification in separate training (P = 0.021) and validation (P = 0.047) NSCLC cohorts. The protein expression of CD27 quantified with ELISA had a strong correlation with its mRNA expression in NSCLC tumors (Spearman coefficient = 0.494, P < 0.0088). Multiple signature genes had concordant DNA copy number variation, mRNA and protein expression in NSCLC progression. CONCLUSIONS This study presents a predictive multi-gene assay and prognostic protein biomarkers clinically applicable for improving NSCLC treatment, with important implications in lung cancer chemotherapy and immunotherapy.
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Affiliation(s)
- Nancy Lan Guo
- West Virginia University Cancer Institute, Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506-9300, United States.
| | - Afshin Dowlati
- Case Comprehensive Cancer Center, Case Western Reserve University, 10900 Euclid Ave., Cleveland, OH 44106, United States
| | - Rebecca A Raese
- West Virginia University Cancer Institute, Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506-9300, United States
| | - Chunlin Dong
- West Virginia University Cancer Institute, Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506-9300, United States
| | - Guoan Chen
- Comprehensive Cancer Center, University of Michigan, 1500 East Medical Center Drive, Ann Arbor, MI 48109-0944, United States
| | - David G Beer
- Comprehensive Cancer Center, University of Michigan, 1500 East Medical Center Drive, Ann Arbor, MI 48109-0944, United States
| | - Justine Shaffer
- West Virginia University Cancer Institute, Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506-9300, United States
| | - Salvi Singh
- West Virginia University Cancer Institute, Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506-9300, United States
| | - Ujala Bokhary
- Kellogg Cancer Center, NorthShore University HealthSystem, 2650 Ridge Avenue, Evanston, IL 60201, United States
| | - Lin Liu
- Kellogg Cancer Center, NorthShore University HealthSystem, 2650 Ridge Avenue, Evanston, IL 60201, United States
| | - John Howington
- Kellogg Cancer Center, NorthShore University HealthSystem, 2650 Ridge Avenue, Evanston, IL 60201, United States
| | - Thomas Hensing
- Kellogg Cancer Center, NorthShore University HealthSystem, 2650 Ridge Avenue, Evanston, IL 60201, United States
| | - Yong Qian
- National Institute of Occupational Safety and Health, 1095 Willowdale Road, Morgantown, WV 26505, United States
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Wan YW, Raese RA, Fortney JE, Xiao C, Luo D, Cavendish J, Gibson LF, Castranova V, Qian Y, Guo NL. A smoking-associated 7-gene signature for lung cancer diagnosis and prognosis. Int J Oncol 2012; 41:1387-96. [PMID: 22825454 PMCID: PMC3481011 DOI: 10.3892/ijo.2012.1556] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2012] [Accepted: 05/09/2012] [Indexed: 11/14/2022] Open
Abstract
Smoking is responsible for 90% of lung cancer cases. There is currently no clinically available gene test for early detection of lung cancer in smokers, or an effective patient selection strategy for adjuvant chemotherapy in lung cancer treatment. In this study, concurrent coexpression with multiple signaling pathways was modeled among a set of genes associated with smoking and lung cancer survival. This approach identified and validated a 7-gene signature for lung cancer diagnosis and prognosis in smokers using patient transcriptional profiles (n=847). The smoking-associated gene coexpression networks in lung adenocarcinoma tumors (n=442) were highly significant in terms of biological relevance (network precision = 0.91, FDR<0.01) when evaluated with numerous databases containing multi-level molecular associations. The gene coexpression network in smoking lung adenocarcinoma patients was confirmed in qRT-PCR assays of the identified biomarkers and involved signaling pathway genes in human lung adenocarcinoma cells (H23) treated with 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK). Furthermore, the western blotting results of p53, phospho-p53, Rb and EGFR in NNK-treated H23 and transformed normal human lung epithelial cells (BEAS-2B) support their functional involvement in smoking-induced lung cancer carcinogenesis and progression.
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Affiliation(s)
- Ying-Wooi Wan
- Mary Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA
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