Urinary Metabolic Signatures Detect Recurrences in Non-Muscle Invasive Bladder Cancer
Patients with non-muscle invasive bladder cancer (NMIBC) undergo lifelong monitoring based on repeated cystoscopy and urinary cytology due to the high recurrence rate of this tumor. Nevertheless, these techniques have some drawbacks, namely, low accuracy in detection of low-grade tumors, omission of...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-06-01
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| Series: | Cancers |
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| Online Access: | https://www.mdpi.com/2072-6694/11/7/914 |
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| author | Alba Loras M. Carmen Martínez-Bisbal Guillermo Quintás Salvador Gil Ramón Martínez-Máñez José Luis Ruiz-Cerdá |
| author_facet | Alba Loras M. Carmen Martínez-Bisbal Guillermo Quintás Salvador Gil Ramón Martínez-Máñez José Luis Ruiz-Cerdá |
| author_sort | Alba Loras |
| collection | DOAJ |
| description | Patients with non-muscle invasive bladder cancer (NMIBC) undergo lifelong monitoring based on repeated cystoscopy and urinary cytology due to the high recurrence rate of this tumor. Nevertheless, these techniques have some drawbacks, namely, low accuracy in detection of low-grade tumors, omission of pre-neoplastic lesions and carcinomas in situ (CIS), invasiveness, and high costs. This work aims to identify a urinary metabolomic signature of recurrence by proton Nuclear Magnetic Resonance (<sup>1</sup>H NMR) spectroscopy for the follow-up of NMIBC patients. To do this, changes in the urinary metabolome before and after transurethral resection (TUR) of tumors are analyzed and a Partial Least Square Discriminant Analysis (PLS-DA) model is developed. The usefulness of this discriminant model for the detection of tumor recurrences is assessed using a cohort of patients undergoing monitoring. The trajectories of the metabolomic profile in the follow-up period provide a negative predictive value of 92.7% in the sample classification. Pathway analyses show taurine, alanine, aspartate, glutamate, and phenylalanine perturbed metabolism associated with NMIBC. These results highlight the potential of <sup>1</sup>H NMR metabolomics to detect bladder cancer (BC) recurrences through a non-invasive approach. |
| first_indexed | 2024-03-12T08:03:12Z |
| format | Article |
| id | doaj.art-a538f95c412f4aba9470c8d631162602 |
| institution | Directory Open Access Journal |
| issn | 2072-6694 |
| language | English |
| last_indexed | 2024-03-12T08:03:12Z |
| publishDate | 2019-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Cancers |
| spelling | doaj.art-a538f95c412f4aba9470c8d6311626022023-09-02T19:46:31ZengMDPI AGCancers2072-66942019-06-0111791410.3390/cancers11070914cancers11070914Urinary Metabolic Signatures Detect Recurrences in Non-Muscle Invasive Bladder CancerAlba Loras0M. Carmen Martínez-Bisbal1Guillermo Quintás2Salvador Gil3Ramón Martínez-Máñez4José Luis Ruiz-Cerdá5Unidad Mixta de Investigación en Nanomedicina y Sensores, Universitat Politècnica de València-Instituto de Investigación Sanitaria La Fe, 46026 Valencia, SpainUnidad Mixta de Investigación en Nanomedicina y Sensores, Universitat Politècnica de València-Instituto de Investigación Sanitaria La Fe, 46026 Valencia, SpainAnalytical Unit, Instituto de Investigación Sanitaria La Fe, 46026 Valencia, SpainInstituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico, Universitat Politècnica de València, Universitat de València, 46022 Valencia, SpainUnidad Mixta de Investigación en Nanomedicina y Sensores, Universitat Politècnica de València-Instituto de Investigación Sanitaria La Fe, 46026 Valencia, SpainUnidad Mixta de Investigación en Nanomedicina y Sensores, Universitat Politècnica de València-Instituto de Investigación Sanitaria La Fe, 46026 Valencia, SpainPatients with non-muscle invasive bladder cancer (NMIBC) undergo lifelong monitoring based on repeated cystoscopy and urinary cytology due to the high recurrence rate of this tumor. Nevertheless, these techniques have some drawbacks, namely, low accuracy in detection of low-grade tumors, omission of pre-neoplastic lesions and carcinomas in situ (CIS), invasiveness, and high costs. This work aims to identify a urinary metabolomic signature of recurrence by proton Nuclear Magnetic Resonance (<sup>1</sup>H NMR) spectroscopy for the follow-up of NMIBC patients. To do this, changes in the urinary metabolome before and after transurethral resection (TUR) of tumors are analyzed and a Partial Least Square Discriminant Analysis (PLS-DA) model is developed. The usefulness of this discriminant model for the detection of tumor recurrences is assessed using a cohort of patients undergoing monitoring. The trajectories of the metabolomic profile in the follow-up period provide a negative predictive value of 92.7% in the sample classification. Pathway analyses show taurine, alanine, aspartate, glutamate, and phenylalanine perturbed metabolism associated with NMIBC. These results highlight the potential of <sup>1</sup>H NMR metabolomics to detect bladder cancer (BC) recurrences through a non-invasive approach.https://www.mdpi.com/2072-6694/11/7/914bladder cancerrecurrence predictionbiomarkermetabolitemetabolomicsmetabolic pathwaysnuclear magnetic resonance |
| spellingShingle | Alba Loras M. Carmen Martínez-Bisbal Guillermo Quintás Salvador Gil Ramón Martínez-Máñez José Luis Ruiz-Cerdá Urinary Metabolic Signatures Detect Recurrences in Non-Muscle Invasive Bladder Cancer Cancers bladder cancer recurrence prediction biomarker metabolite metabolomics metabolic pathways nuclear magnetic resonance |
| title | Urinary Metabolic Signatures Detect Recurrences in Non-Muscle Invasive Bladder Cancer |
| title_full | Urinary Metabolic Signatures Detect Recurrences in Non-Muscle Invasive Bladder Cancer |
| title_fullStr | Urinary Metabolic Signatures Detect Recurrences in Non-Muscle Invasive Bladder Cancer |
| title_full_unstemmed | Urinary Metabolic Signatures Detect Recurrences in Non-Muscle Invasive Bladder Cancer |
| title_short | Urinary Metabolic Signatures Detect Recurrences in Non-Muscle Invasive Bladder Cancer |
| title_sort | urinary metabolic signatures detect recurrences in non muscle invasive bladder cancer |
| topic | bladder cancer recurrence prediction biomarker metabolite metabolomics metabolic pathways nuclear magnetic resonance |
| url | https://www.mdpi.com/2072-6694/11/7/914 |
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