Novel metabolomics-biohumoral biomarkers model for predicting survival of metastatic soft-tissue sarcomas
Summary: Soft tissue sarcomas (STSs) are rare malignant tumors that are difficult to prognosticate using currently available instruments. Omics sciences could provide more accurate and individualized survival predictions for patients with metastatic STS. In this pilot, hypothesis-generating study, w...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-10-01
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| Series: | iScience |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589004223017558 |
| _version_ | 1827781759837667328 |
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| author | Alessia Vignoli Gianmaria Miolo Leonardo Tenori Angela Buonadonna Davide Lombardi Agostino Steffan Simona Scalone Claudio Luchinat Giuseppe Corona |
| author_facet | Alessia Vignoli Gianmaria Miolo Leonardo Tenori Angela Buonadonna Davide Lombardi Agostino Steffan Simona Scalone Claudio Luchinat Giuseppe Corona |
| author_sort | Alessia Vignoli |
| collection | DOAJ |
| description | Summary: Soft tissue sarcomas (STSs) are rare malignant tumors that are difficult to prognosticate using currently available instruments. Omics sciences could provide more accurate and individualized survival predictions for patients with metastatic STS. In this pilot, hypothesis-generating study, we integrated clinicopathological variables with proton nuclear magnetic resonance (1H NMR) plasma metabolomic and lipoproteomic profiles, capturing both tumor and host characteristics, to identify novel prognostic biomarkers of 2-year survival. Forty-five metastatic STS (mSTS) patients with prevalent leiomyosarcoma and liposarcoma histotypes receiving trabectedin treatment were enrolled. A score combining acetate, triglycerides low-density lipoprotein (LDL)-2, and red blood cell count was developed, and it predicts 2-year survival with optimal results in the present cohort (84.4% sensitivity, 84.6% specificity). This score is statistically significant and independent of other prognostic factors such as age, sex, tumor grading, tumor histotype, frailty status, and therapy administered. A nomogram based on these 3 biomarkers has been developed to inform the clinical use of the present findings. |
| first_indexed | 2024-03-11T15:23:20Z |
| format | Article |
| id | doaj.art-9c2bcc1a4d4b4a6fb7305b01edc3ff10 |
| institution | Directory Open Access Journal |
| issn | 2589-0042 |
| language | English |
| last_indexed | 2024-03-11T15:23:20Z |
| publishDate | 2023-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | iScience |
| spelling | doaj.art-9c2bcc1a4d4b4a6fb7305b01edc3ff102023-10-28T05:08:08ZengElsevieriScience2589-00422023-10-012610107678Novel metabolomics-biohumoral biomarkers model for predicting survival of metastatic soft-tissue sarcomasAlessia Vignoli0Gianmaria Miolo1Leonardo Tenori2Angela Buonadonna3Davide Lombardi4Agostino Steffan5Simona Scalone6Claudio Luchinat7Giuseppe Corona8Magnetic Resonance Center (CERM) and Department of Chemistry “Ugo Schiff”, University of Florence, 50019 Sesto Fiorentino, ItalyMedical Oncology and Cancer Prevention Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, ItalyMagnetic Resonance Center (CERM) and Department of Chemistry “Ugo Schiff”, University of Florence, 50019 Sesto Fiorentino, Italy; Consorzio Interuniversitario Risonanze Magnetiche MetalloProteine (CIRMMP), 50019 Sesto Fiorentino, ItalyMedical Oncology and Cancer Prevention Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, ItalyMedical Oncology and Cancer Prevention Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, ItalyImmunopathology and Cancer Biomarkers Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, ItalyMedical Oncology and Cancer Prevention Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, ItalyConsorzio Interuniversitario Risonanze Magnetiche MetalloProteine (CIRMMP), 50019 Sesto Fiorentino, Italy; GiottoBiotech s.r.l, Sesto Fiorentino, ItalyImmunopathology and Cancer Biomarkers Unit, Centro di Riferimento Oncologico di Aviano (CRO), IRCCS, 33081 Aviano, Italy; Corresponding authorSummary: Soft tissue sarcomas (STSs) are rare malignant tumors that are difficult to prognosticate using currently available instruments. Omics sciences could provide more accurate and individualized survival predictions for patients with metastatic STS. In this pilot, hypothesis-generating study, we integrated clinicopathological variables with proton nuclear magnetic resonance (1H NMR) plasma metabolomic and lipoproteomic profiles, capturing both tumor and host characteristics, to identify novel prognostic biomarkers of 2-year survival. Forty-five metastatic STS (mSTS) patients with prevalent leiomyosarcoma and liposarcoma histotypes receiving trabectedin treatment were enrolled. A score combining acetate, triglycerides low-density lipoprotein (LDL)-2, and red blood cell count was developed, and it predicts 2-year survival with optimal results in the present cohort (84.4% sensitivity, 84.6% specificity). This score is statistically significant and independent of other prognostic factors such as age, sex, tumor grading, tumor histotype, frailty status, and therapy administered. A nomogram based on these 3 biomarkers has been developed to inform the clinical use of the present findings.http://www.sciencedirect.com/science/article/pii/S2589004223017558Systems biologyCancerMetabolomics |
| spellingShingle | Alessia Vignoli Gianmaria Miolo Leonardo Tenori Angela Buonadonna Davide Lombardi Agostino Steffan Simona Scalone Claudio Luchinat Giuseppe Corona Novel metabolomics-biohumoral biomarkers model for predicting survival of metastatic soft-tissue sarcomas iScience Systems biology Cancer Metabolomics |
| title | Novel metabolomics-biohumoral biomarkers model for predicting survival of metastatic soft-tissue sarcomas |
| title_full | Novel metabolomics-biohumoral biomarkers model for predicting survival of metastatic soft-tissue sarcomas |
| title_fullStr | Novel metabolomics-biohumoral biomarkers model for predicting survival of metastatic soft-tissue sarcomas |
| title_full_unstemmed | Novel metabolomics-biohumoral biomarkers model for predicting survival of metastatic soft-tissue sarcomas |
| title_short | Novel metabolomics-biohumoral biomarkers model for predicting survival of metastatic soft-tissue sarcomas |
| title_sort | novel metabolomics biohumoral biomarkers model for predicting survival of metastatic soft tissue sarcomas |
| topic | Systems biology Cancer Metabolomics |
| url | http://www.sciencedirect.com/science/article/pii/S2589004223017558 |
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