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Wang YH, Orgueira AM, Lin CC, Yao CY, Lo MY, Tsai CH, de la Fuente Burguera A, Hou HA, Chou WC, Tien HF. Stellae-123 gene expression signature improved risk stratification in taiwanese acute myeloid leukemia patients. Sci Rep 2024; 14:11064. [PMID: 38744924 PMCID: PMC11094146 DOI: 10.1038/s41598-024-61022-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2024] [Accepted: 04/30/2024] [Indexed: 05/16/2024] Open
Abstract
The European Leukemia Net recommendations provide valuable guidance in treatment decisions of patients with acute myeloid leukemia (AML). However, the genetic complexity and heterogeneity of AML are not fully covered, notwithstanding that gene expression analysis is crucial in the risk stratification of AML. The Stellae-123 score, an AI-based model that captures gene expression patterns, has demonstrated robust survival predictions in AML patients across four western-population cohorts. This study aims to evaluate the applicability of Stellae-123 in a Taiwanese cohort. The Stellae-123 model was applied to 304 de novo AML patients diagnosed and treated at the National Taiwan University Hospital. We find that the pretrained (BeatAML-based) model achieved c-indexes of 0.631 and 0.632 for the prediction of overall survival (OS) and relapse-free survival (RFS), respectively. Model retraining within our cohort further improve the cross-validated c-indexes to 0.667 and 0.667 for OS and RFS prediction, respectively. Multivariable analysis identify both pretrained and retrained models as independent prognostic biomarkers. We further show that incorporating age, Stellae-123, and ELN classification remarkably improves risk stratification, revealing c-indices of 0.73 and 0.728 for OS and RFS, respectively. In summary, the Stellae-123 gene expression signature is a valuable prognostic tool for AML patients and model retraining can improve the accuracy and applicability of the model in different populations.
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Affiliation(s)
- Yu-Hung Wang
- Division of Hematology, National Taiwan University Hospital, Taipei, Taiwan
| | - Adrián Mosquera Orgueira
- Department of Hematology, University Hospital of Santiago de Compostela, Santiago de Compostela, Spain
- Group of Computational Hematology and Genomics (GrHeCo-Xen), Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | - Chien-Chin Lin
- Division of Hematology, National Taiwan University Hospital, Taipei, Taiwan.
- Department of Laboratory Medicine, National Taiwan University Hospital, No. 7, Chung-Shan S. Rd., Taipei City, 10002, Taiwan.
| | - Chi-Yuan Yao
- Division of Hematology, National Taiwan University Hospital, Taipei, Taiwan
- Department of Laboratory Medicine, National Taiwan University Hospital, No. 7, Chung-Shan S. Rd., Taipei City, 10002, Taiwan
- Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Min-Yen Lo
- Division of Hematology, National Taiwan University Hospital, Taipei, Taiwan
- Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
- Division of Hematology, Department of Internal Medicine, National Taiwan University Hospital Yunlin Branch, Yunlin, Taiwan
| | - Cheng-Hong Tsai
- Division of Hematology, National Taiwan University Hospital, Taipei, Taiwan
- Department of Medical Education and Research, National Taiwan University Hospital Yunlin Branch, Yunlin, Taiwan
| | | | - Hsin-An Hou
- Division of Hematology, National Taiwan University Hospital, Taipei, Taiwan
| | - Wen-Chien Chou
- Division of Hematology, National Taiwan University Hospital, Taipei, Taiwan
- Department of Laboratory Medicine, National Taiwan University Hospital, No. 7, Chung-Shan S. Rd., Taipei City, 10002, Taiwan
| | - Hwei-Fang Tien
- Division of Hematology, National Taiwan University Hospital, Taipei, Taiwan.
- Department of Internal Medicine, Far-Eastern Memorial Hospital, No. 7, Chung-Shan S. Rd., Taipei City, 10002, Taiwan.
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Wang X, Yao L, Li Z, Zhang J, Ruan M, Mulati Y, Gan Y, Zhang Q. ZNF471 Interacts with BANP to Reduce Tumour Malignancy by Inactivating PI3K/AKT/mTOR Signalling but is Frequently Silenced by Aberrant Promoter Methylation in Renal Cell Carcinoma. Int J Biol Sci 2024; 20:643-663. [PMID: 38169650 PMCID: PMC10758100 DOI: 10.7150/ijbs.89785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2023] [Accepted: 12/03/2023] [Indexed: 01/05/2024] Open
Abstract
Background: Renal cell carcinoma (RCC) is one of the most common malignant tumours of the urinary system. However, the aetiology and pathogenesis of RCC remain unclear. The C2H2 zinc finger protein (ZNF) family is the largest transcriptional regulatory factor family found in mammals, and Krüppel-associated box domain-containing zinc finger proteins (KRAB-ZFPs) constitute the largest subfamily of the C2H2 zinc finger protein family and play an important role in the occurrence and development of tumours. The aim of this study was to explore the role of abnormal methylation of ZNF471 in the development of renal carcinoma. Methods: In this study, we first used the TCGA and EWAS Data Hub databases to analyse the expression and methylation levels of ZNF471 in renal carcinoma tissues and adjacent normal tissues. Second, we collected samples of renal cancer and adjacent normal tissues at Peking University First Hospital to investigate the expression and methylation level of ZNF471 in renal cancer tissues and the relationships between these levels and the clinicopathological features and prognosis of patients with renal cancer. Next, we investigated the effects of ZNF471 on the proliferation, metastasis, cell cycle progression, and apoptosis of renal cell carcinoma cells by cell biology experiments. Finally, we elucidated the underlying molecular mechanisms of ZNF471 in renal cell carcinoma by transcriptome sequencing, bioinformatics analysis and molecular biology experiments. Results: The expression of ZNF471 in renal carcinoma tissues and cell lines was significantly lower than that in adjacent normal tissues and cell lines due to abnormal promoter CpG methylation. Furthermore, the expression of ZNF471 in renal carcinoma tissues was negatively correlated with tumour stage and grade in patients with renal carcinoma. The results of the cell biology experiments showed that ZNF471 could significantly inhibit the proliferation, migration and cell cycle progression of renal cell carcinoma cells and promote apoptosis in these cells. In addition, ZNF471 could interact with BANP and suppress the malignant phenotype of RCC by inactivating the PI3K/AKT/mTOR signalling pathway. Conclusions: As an important tumour suppressor, ZNF471 can interact with BANP in renal cancer cells and inhibit the activation of the PI3K/AKT/mTOR signalling pathway, thereby inhibiting the occurrence and development of renal cancer.
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Affiliation(s)
- Xiaofei Wang
- Department of Urology, Peking University First Hospital; Institute of Urology, Peking University; Beijing Key Laboratory of Urogenital Diseases (Male) Molecular Diagnosis and Treatment Center, National Urological Cancer Center, Beijing 100034, China
| | - Lin Yao
- Department of Urology, Peking University First Hospital; Institute of Urology, Peking University; Beijing Key Laboratory of Urogenital Diseases (Male) Molecular Diagnosis and Treatment Center, National Urological Cancer Center, Beijing 100034, China
| | - Zheng Li
- Department of Urology, Peking University First Hospital; Institute of Urology, Peking University; Beijing Key Laboratory of Urogenital Diseases (Male) Molecular Diagnosis and Treatment Center, National Urological Cancer Center, Beijing 100034, China
| | - Jiaen Zhang
- Department of Urology, Peking University First Hospital; Institute of Urology, Peking University; Beijing Key Laboratory of Urogenital Diseases (Male) Molecular Diagnosis and Treatment Center, National Urological Cancer Center, Beijing 100034, China
| | - Mingjian Ruan
- Department of Urology, Peking University First Hospital; Institute of Urology, Peking University; Beijing Key Laboratory of Urogenital Diseases (Male) Molecular Diagnosis and Treatment Center, National Urological Cancer Center, Beijing 100034, China
| | - Yelin Mulati
- Department of Urology, Peking University First Hospital; Institute of Urology, Peking University; Beijing Key Laboratory of Urogenital Diseases (Male) Molecular Diagnosis and Treatment Center, National Urological Cancer Center, Beijing 100034, China
| | - Ying Gan
- Department of Urology, Peking University First Hospital; Institute of Urology, Peking University; Beijing Key Laboratory of Urogenital Diseases (Male) Molecular Diagnosis and Treatment Center, National Urological Cancer Center, Beijing 100034, China
| | - Qian Zhang
- Department of Urology, Peking University First Hospital; Institute of Urology, Peking University; Beijing Key Laboratory of Urogenital Diseases (Male) Molecular Diagnosis and Treatment Center, National Urological Cancer Center, Beijing 100034, China
- Peking University Binhai Hospital, Tianjin 300450, China
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