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Cattelani L, Ghosh A, Rintala TJ, Fortino V. A Comprehensive Evaluation Framework for Benchmarking Multi-Objective Feature Selection in Omics-Based Biomarker Discovery. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2024; 21:2432-2446. [PMID: 39401114 DOI: 10.1109/tcbb.2024.3480150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/17/2024]
Abstract
Machine learning algorithms have been extensively used for accurate classification of cancer subtypes driven by gene expression-based biomarkers. However, biomarker models combining multiple gene expression signatures are often not reproducible in external validation datasets and their feature set size is often not optimized, jeopardizing their translatability into cost-effective clinical tools. We investigated how to solve the multi-objective problem of finding the best trade-offs between classification performance and set size applying seven algorithms for machine learning-driven feature subset selection and analyse how they perform in a benchmark with eight large-scale transcriptome datasets of cancer, covering both training and external validation sets. The benchmark includes evaluation metrics assessing the performance of the individual biomarkers and the solution sets, according to their accuracy, diversity, and stability of the composing genes. Moreover, a new evaluation metric for cross-validation studies is proposed that generalizes the hypervolume, which is commonly used to assess the performance of multi-objective optimization algorithms. Biomarkers exhibiting 0.8 of balanced accuracy on the external dataset for breast, kidney and ovarian cancer using respectively 4, 2 and 7 features, were obtained. Genetic algorithms often provided better performance than other considered algorithms, and the recently proposed NSGA2-CH and NSGA2-CHS were the best performing methods in most cases.
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Xu J, Wu F, Zhu Y, Wu T, Cao T, Gao W, Liu M, Qian W, Feng G, Xi X, Hou S. ANGPTL4 regulates ovarian cancer progression by activating the ERK1/2 pathway. Cancer Cell Int 2024; 24:54. [PMID: 38311733 PMCID: PMC10838463 DOI: 10.1186/s12935-024-03246-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 01/25/2024] [Indexed: 02/06/2024] Open
Abstract
BACKGROUND Ovarian cancer (OC) has the highest mortality rate among all gynecological malignancies. A hypoxic microenvironment is a common feature of solid tumors, including ovarian cancer, and an important driving factor of tumor cell survival and chemo- and radiotherapy resistance. Previous research identified the hypoxia-associated gene angiopoietin-like 4 (ANGPTL4) as both a pro-angiogenic and pro-metastatic factor in tumors. Hence, this work aimed to further elucidate the contribution of ANGPTL4 to OC progression. METHODS The expression of hypoxia-associated ANGPTL4 in human ovarian cancer was examined by bioinformatics analysis of TCGA and GEO datasets. The CIBERSORT tool was used to analyze the distribution of tumor-infiltrating immune cells in ovarian cancer cases in TCGA. The effect of ANGPTL4 silencing and overexpression on the proliferation and migration of OVCAR3 and A2780 OC cells was studied in vitro, using CCK-8, colony formation, and Transwell assays, and in vivo, through subcutaneous tumorigenesis assays in nude mice. GO enrichment analysis and WGCNA were performed to explore biological processes and genetic networks associated with ANGPTL4. The results obtained were corroborated in OC cells in vitro by western blotting. RESULTS Screening of hypoxia-associated genes in OC-related TCGA and GEO datasets revealed a significant negative association between ANGPTL4 expression and patient survival. Based on CIBERSORT analysis, differential representation of 14 distinct tumor-infiltrating immune cell types was detected between low- and high-risk patient groups. Silencing of ANGPTL4 inhibited OVCAR3 and A2780 cell proliferation and migration in vitro and reduced the growth rate of xenografted OVCAR3 cells in vivo. Based on results from WGCNA and previous studies, western blot assays in cultured OC cells demonstrated that ANGPTL4 activates the Extracellular signal-related kinases 1 and 2 (ERK1/2) pathway and this results in upregulation of c-Myc, Cyclin D1, and MMP2 expression. Suggesting that the above mechanism mediates the pro-oncogenic actions of ANGPTL4T in OC, the pro-survival effects of ANGPTL4 were largely abolished upon inhibition of ERK1/2 signaling with PD98059. CONCLUSIONS Our work suggests that the hypoxia-associated gene ANGPTL4 stimulates OC progression through activation of the ERK1/2 pathway. These findings may offer a new prospect for targeted therapies for the treatment of OC.
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Affiliation(s)
- Jiaqi Xu
- Department of Obstetrics and Gynecology, The Affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University; Suzhou Municipal Hospital, No.26, Daoqian Street, Suzhou, 215002, Jiangsu, China
| | - Fei Wu
- Department of Obstetrics and Gynecology, The Affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University; Suzhou Municipal Hospital, No.26, Daoqian Street, Suzhou, 215002, Jiangsu, China
| | - Yue Zhu
- Department of Breast and Thyroid Surgery, The Affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University; Suzhou Municipal Hospital, No.26, Daoqian Street, Suzhou, 215002, Jiangsu, China
| | - Tiantian Wu
- State Key Laboratory of Reproductive Medicine and Offspring Health, Department of Histology and Embryology, Nanjing Medical University, Nanjing, China
| | - Tianyue Cao
- Department of Obstetrics and Gynecology, The Affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University; Suzhou Municipal Hospital, No.26, Daoqian Street, Suzhou, 215002, Jiangsu, China
| | - Wenxin Gao
- State Key Laboratory of Reproductive Medicine and Offspring Health, Department of Histology and Embryology, Nanjing Medical University, Nanjing, China
| | - Meng Liu
- Department of Obstetrics and Gynecology, The Affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University; Suzhou Municipal Hospital, No.26, Daoqian Street, Suzhou, 215002, Jiangsu, China
| | - Weifeng Qian
- Department of Breast and Thyroid Surgery, The Affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University; Suzhou Municipal Hospital, No.26, Daoqian Street, Suzhou, 215002, Jiangsu, China
| | - Guannan Feng
- Department of Obstetrics and Gynecology, The Affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University; Suzhou Municipal Hospital, No.26, Daoqian Street, Suzhou, 215002, Jiangsu, China
| | - Xiaoxue Xi
- Department of Obstetrics and Gynecology, The Affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University; Suzhou Municipal Hospital, No.26, Daoqian Street, Suzhou, 215002, Jiangsu, China.
| | - Shunyu Hou
- Department of Obstetrics and Gynecology, The Affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University; Suzhou Municipal Hospital, No.26, Daoqian Street, Suzhou, 215002, Jiangsu, China.
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