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Torres-Bustamante MI, Vazquez-Urrutia JR, Solorzano-Ibarra F, Ortiz-Lazareno PC. The Role of miRNAs to Detect Progression, Stratify, and Predict Relevant Clinical Outcomes in Bladder Cancer. Int J Mol Sci 2024; 25:2178. [PMID: 38396855 PMCID: PMC10889402 DOI: 10.3390/ijms25042178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 02/01/2024] [Accepted: 02/07/2024] [Indexed: 02/25/2024] Open
Abstract
Bladder cancer (BC) is one of the most common types of cancer worldwide, with significant differences in survival depending on the degree of muscle and surrounding tissue invasion. For this reason, the timely detection and monitoring of the disease are important. Surveillance cystoscopy is an invasive, costly, and uncomfortable procedure to monitor BC, raising the need for new, less invasive alternatives. In this scenario, microRNAs (miRNAs) represent attractive prognostic tools given their role as gene regulators in different biological processes, tissue expression, and their ease of evaluation in liquid samples. In cancer, miRNA expression is dynamically modified depending on the tumor type and cancer staging, making them potential biomarkers. This review describes the most recent studies in the last five years exploring the utility of miRNA-based strategies to monitor progression, stratify, and predict relevant clinical outcomes of bladder cancer. Several studies have shown that multimarker miRNA models can better predict overall survival, recurrence, and progression in BC patients than traditional strategies, especially when combining miRNA expression with clinicopathological variables. Future studies should focus on validating their use in different cohorts and liquid samples.
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Affiliation(s)
| | - Jorge Raul Vazquez-Urrutia
- Department of Medicine, The Pennsylvania State University College of Medicine, The Pennsylvania State University, Hershey, PA 17033, USA;
| | - Fabiola Solorzano-Ibarra
- Instituto de Investigación en Enfermedades Crónico Degenerativas, Departamento de Biología Molecular y Genómica, Centro Universitario de Ciencias de la Salud (CUCS), Universidad de Guadalajara, Guadalajara 44340, Mexico;
- Estancias Posdoctorales por México, Consejo Nacional de Humanidades, Ciencias y Tecnologías (CONACYT), México City 03940, Mexico
| | - Pablo Cesar Ortiz-Lazareno
- División de Inmunología, Centro de Investigación Biomédica de Occidente, Instituto Mexicano del Seguro Social, Guadalajara 44340, Mexico
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Jordan-Alejandre E, Campos-Parra AD, Castro-López DL, Silva-Cázares MB. Potential miRNA Use as a Biomarker: From Breast Cancer Diagnosis to Metastasis. Cells 2023; 12:cells12040525. [PMID: 36831192 PMCID: PMC9954167 DOI: 10.3390/cells12040525] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 01/27/2023] [Accepted: 01/31/2023] [Indexed: 02/08/2023] Open
Abstract
Breast cancer is the most common cancer in women. Despite advances in diagnosis and prognosis, distal metastases occur in these patients in up to 15% of cases within 3 years of diagnosis. The main organs in which BC metastasises are the bones, lungs, liver, and brain. Unfortunately, 90% of metastatic patients will die, making this an incurable disease. Researchers are therefore seeking biomarkers for diagnosis and metastasis in different organs. Optimally, such biomarkers should be easy to detect using, preferably, non-invasive methods, such as using miRNA molecules, which are small molecules of about 22 nt that have as their main function the post-transcriptional regulation of genes. Furthermore, due to their uncomplicated detection and reproducibility in the laboratory, they are a tool of complementary interest for diagnosis, prognosis, and treatment. With this in mind, in this review, we focus on describing the most current studies that propose using miRNA independently as a potential biomarker for the diagnosis and prediction of brain, lung, liver, and bone metastases, as well as to open a window of opportunity to deepen this area of study to eventually use miRNAs molecules in clinical practice for the benefit of BC patients.
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Affiliation(s)
- Euclides Jordan-Alejandre
- Posgrado en Ciencias Genómicas, Universidad Autónoma de la Ciudad de México, Ciudad de México 03100, Mexico
| | - Alma D. Campos-Parra
- Subdirección de Investigación Básica, Instituto Nacional de Cancerología, Ciudad de México 14080, Mexico
| | - Dora Luz Castro-López
- Facultad de Ingeniería, Universidad Autónoma de San Luis Potosí, San Luis Potosí 78290, Mexico
| | - Macrina Beatriz Silva-Cázares
- Coordinación Académica Región Altiplano, Universidad Autónoma de San Luis Potosí, San Luis Potosí 78760, Mexico
- Correspondence:
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Selecting optimum miRNA panel for miRNA signature-based companion diagnostic model to predict the response of R-CHOP treatment in diffuse large B-cell lymphoma. J Biosci Bioeng 2023; 135:341-347. [PMID: 36732209 DOI: 10.1016/j.jbiosc.2023.01.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 12/21/2022] [Accepted: 01/11/2023] [Indexed: 02/01/2023]
Abstract
Diffuse large B-cell lymphoma (DLBCL) is the most common type of malignant lymphoma. Although the first-line treatment, R-CHOP treatment, shows efficacy in approximately 80% of patients with DLBCL, some patients have refractory disease or relapse after the initial response to therapy, resulting in a significantly poorer prognosis. In this study, we developed a microRNA (miRNA) signature-based companion diagnostic model to predict the response of patients with DLBCL to R-CHOP treatment by integrating two clinical study datasets. To select the optimum miRNA combination as a panel, we examined three feature selection methods (p-value-based ranking, stepwise method, and Boruta), together with 11 types of classifiers systematically. Boruta selection enabled a higher area under the curve (AUC) with a lower number of miRNAs compared with other feature selection methods, leading to an AUC of 0.751 via the random forest classifier using 36 miRNAs. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis suggested that Boruta avoided multiple selection of miRNAs with similar functions, thereby preventing the decrease in diagnostic ability via collinearity. The AUC value first increased with an increasing number of miRNAs and then became almost constant at approximately 30 miRNAs, suggesting the existence of the optimum number of miRNAs as a panel for future clinical translation of multiple miRNA-based diagnostics.
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Gallez B. The Role of Imaging Biomarkers to Guide Pharmacological Interventions Targeting Tumor Hypoxia. Front Pharmacol 2022; 13:853568. [PMID: 35910347 PMCID: PMC9335493 DOI: 10.3389/fphar.2022.853568] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 06/23/2022] [Indexed: 12/12/2022] Open
Abstract
Hypoxia is a common feature of solid tumors that contributes to angiogenesis, invasiveness, metastasis, altered metabolism and genomic instability. As hypoxia is a major actor in tumor progression and resistance to radiotherapy, chemotherapy and immunotherapy, multiple approaches have emerged to target tumor hypoxia. It includes among others pharmacological interventions designed to alleviate tumor hypoxia at the time of radiation therapy, prodrugs that are selectively activated in hypoxic cells or inhibitors of molecular targets involved in hypoxic cell survival (i.e., hypoxia inducible factors HIFs, PI3K/AKT/mTOR pathway, unfolded protein response). While numerous strategies were successful in pre-clinical models, their translation in the clinical practice has been disappointing so far. This therapeutic failure often results from the absence of appropriate stratification of patients that could benefit from targeted interventions. Companion diagnostics may help at different levels of the research and development, and in matching a patient to a specific intervention targeting hypoxia. In this review, we discuss the relative merits of the existing hypoxia biomarkers, their current status and the challenges for their future validation as companion diagnostics adapted to the nature of the intervention.
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Yerukala Sathipati S, Tsai MJ, Shukla SK, Ho SY, Liu Y, Beheshti A. MicroRNA signature for estimating the survival time in patients with bladder urothelial carcinoma. Sci Rep 2022; 12:4141. [PMID: 35264666 PMCID: PMC8907292 DOI: 10.1038/s41598-022-08082-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Accepted: 03/02/2022] [Indexed: 11/13/2022] Open
Abstract
Bladder urothelial carcinoma (BLC) is one of the most common cancers in men, and its heterogeneity challenges the treatment to cure this disease. Recently, microRNAs (miRNAs) gained promising attention as biomarkers due to their potential roles in cancer biology. Identifying survival-associated miRNAs may help identify targets for therapeutic interventions in BLC. This work aims to identify a miRNA signature that could estimate the survival in patients with BLC. We developed a survival estimation method called BLC-SVR based on support vector regression incorporated with an optimal feature selection algorithm to select a robust set of miRNAs as a signature to estimate the survival in patients with BLC. BLC-SVR identified a miRNA signature consisting of 29 miRNAs and obtained a mean squared correlation coefficient and mean absolute error of 0.79 ± 0.02 and 0.52 ± 0.32 year between actual and estimated survival times, respectively. The prediction performance of BLC-SVR had a better estimation capability than other standard regression methods. In the identified miRNA signature, 14 miRNAs, hsa-miR-432-5p, hsa-let-7e-3p, hsa-miR-652-3p, hsa-miR-629-5p, and hsa-miR-203a-3p, hsa-miR-129-5p, hsa-miR-769-3p, hsa-miR-570-3p, hsa-miR-320c, hsa-miR-642a-5p, hsa-miR-496, hsa-miR-5480-3p, hsa-miR-221-5p, and hsa-miR-7-1-3p, were found to be good biomarkers for BLC diagnosis; and the six miRNAs, hsa-miR-652-5p, hsa-miR-193b-5p, hsa-miR-129-5p, hsa-miR-143-5p, hsa-miR-496, and hsa-miR-7-1-3p, were found to be good biomarkers of prognosis. Further bioinformatics analysis of this miRNA signature demonstrated its importance in various biological pathways and gene ontology annotation. The identified miRNA signature would further help in understanding of BLC diagnosis and prognosis in the development of novel miRNA-target based therapeutics in BLC.
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Affiliation(s)
| | - Ming-Ju Tsai
- Hinda and Arthur Marcus Institute for Aging Research at Hebrew Senior Life, Boston, MA, USA.,Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Sanjay K Shukla
- Center for Precision Medicine Research, Marshfield Clinic Research Institute, Marshfield, WI, 54449, USA
| | - Shinn-Ying Ho
- Institute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan.,College of Health Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Yi Liu
- Biomedical Engineering, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Afshin Beheshti
- KBR, Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA, 94035, USA.,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
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