Integrative Genomic and Transcriptomic Profiling Reveals a Differential Molecular Signature in Uterine Leiomyoma versus Leiomyosarcoma
The absence of standardized molecular profiling to differentiate uterine leiomyosarcomas versus leiomyomas represents a current diagnostic challenge. In this study, we aimed to search for a differential molecular signature for these myometrial tumors based on artificial intelligence. For this purpos...
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MDPI AG
2022-02-01
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| Series: | International Journal of Molecular Sciences |
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| Online Access: | https://www.mdpi.com/1422-0067/23/4/2190 |
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| author | Alba Machado-Lopez Roberto Alonso Victor Lago Jorge Jimenez-Almazan Marta Garcia Javier Monleon Susana Lopez Francisco Barcelo Amparo Torroba Sebastian Ortiz Santiago Domingo Carlos Simon Aymara Mas |
| author_facet | Alba Machado-Lopez Roberto Alonso Victor Lago Jorge Jimenez-Almazan Marta Garcia Javier Monleon Susana Lopez Francisco Barcelo Amparo Torroba Sebastian Ortiz Santiago Domingo Carlos Simon Aymara Mas |
| author_sort | Alba Machado-Lopez |
| collection | DOAJ |
| description | The absence of standardized molecular profiling to differentiate uterine leiomyosarcomas versus leiomyomas represents a current diagnostic challenge. In this study, we aimed to search for a differential molecular signature for these myometrial tumors based on artificial intelligence. For this purpose, differential exome and transcriptome-wide research was performed on histologically confirmed leiomyomas (<i>n</i> = 52) and leiomyosarcomas (<i>n</i> = 44) to elucidate differences between and within these two entities. We identified a significantly higher tumor mutation burden in leiomyosarcomas vs. leiomyomas in terms of somatic single-nucleotide variants (171,863 vs. 81,152), indels (9491 vs. 4098), and copy number variants (8390 vs. 5376). Further, we discovered alterations in specific copy number variant regions that affect the expression of some tumor suppressor genes. A transcriptomic analysis revealed 489 differentially expressed genes between these two conditions, as well as structural rearrangements targeting ATRX and RAD51B. These results allowed us to develop a machine learning approach based on 19 differentially expressed genes that differentiate both tumor types with high sensitivity and specificity. Our findings provide a novel molecular signature for the diagnosis of leiomyoma and leiomyosarcoma, which could be helpful to complement the current morphological and immunohistochemical diagnosis and may lay the foundation for the future evaluation of malignancy risk. |
| first_indexed | 2024-03-09T21:43:57Z |
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| institution | Directory Open Access Journal |
| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-03-09T21:43:57Z |
| publishDate | 2022-02-01 |
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| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-4aaec40fce2545c1a9fb4733eade82e12023-11-23T20:21:23ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672022-02-01234219010.3390/ijms23042190Integrative Genomic and Transcriptomic Profiling Reveals a Differential Molecular Signature in Uterine Leiomyoma versus LeiomyosarcomaAlba Machado-Lopez0Roberto Alonso1Victor Lago2Jorge Jimenez-Almazan3Marta Garcia4Javier Monleon5Susana Lopez6Francisco Barcelo7Amparo Torroba8Sebastian Ortiz9Santiago Domingo10Carlos Simon11Aymara Mas12Igenomix Foundation, INCLIVA Biomedical Research Institute, 46980 Valencia, SpainIgenomix Foundation, INCLIVA Biomedical Research Institute, 46980 Valencia, SpainGynecologic Oncology Department, University Hospital La Fe, 46026 Valencia, SpainResearch and Development Department, Igenomix SL, 46980 Paterna, SpainResearch and Development Department, Igenomix SL, 46980 Paterna, SpainDepartment of Obstetrics and Gynecology, Hospital Universitario La Fe, 46026 Valencia, SpainDepartment of Pathology, Hospital Universitario La Fe, 46026 Valencia, SpainDepartment of Gynecology and Obstetrics, Gynecology Oncology Unit, Hospital Universitario Virgen de la Arrixaca, 30120 Murcia, SpainPathology Service, Hospital Clínico Universitario Virgen de la Arrixaca, 30120 Murcia, SpainDepartment of Pathology, Complejo Hospitalario de Cartagena, 30202 Murcia, SpainGynecologic Oncology Department, University Hospital La Fe, 46026 Valencia, SpainIgenomix Foundation, INCLIVA Biomedical Research Institute, 46980 Valencia, SpainIgenomix Foundation, INCLIVA Biomedical Research Institute, 46980 Valencia, SpainThe absence of standardized molecular profiling to differentiate uterine leiomyosarcomas versus leiomyomas represents a current diagnostic challenge. In this study, we aimed to search for a differential molecular signature for these myometrial tumors based on artificial intelligence. For this purpose, differential exome and transcriptome-wide research was performed on histologically confirmed leiomyomas (<i>n</i> = 52) and leiomyosarcomas (<i>n</i> = 44) to elucidate differences between and within these two entities. We identified a significantly higher tumor mutation burden in leiomyosarcomas vs. leiomyomas in terms of somatic single-nucleotide variants (171,863 vs. 81,152), indels (9491 vs. 4098), and copy number variants (8390 vs. 5376). Further, we discovered alterations in specific copy number variant regions that affect the expression of some tumor suppressor genes. A transcriptomic analysis revealed 489 differentially expressed genes between these two conditions, as well as structural rearrangements targeting ATRX and RAD51B. These results allowed us to develop a machine learning approach based on 19 differentially expressed genes that differentiate both tumor types with high sensitivity and specificity. Our findings provide a novel molecular signature for the diagnosis of leiomyoma and leiomyosarcoma, which could be helpful to complement the current morphological and immunohistochemical diagnosis and may lay the foundation for the future evaluation of malignancy risk.https://www.mdpi.com/1422-0067/23/4/2190leiomyomaleiomyosarcomaexome/transcriptomemutational patterndifferential gene expressionintegrative analysis |
| spellingShingle | Alba Machado-Lopez Roberto Alonso Victor Lago Jorge Jimenez-Almazan Marta Garcia Javier Monleon Susana Lopez Francisco Barcelo Amparo Torroba Sebastian Ortiz Santiago Domingo Carlos Simon Aymara Mas Integrative Genomic and Transcriptomic Profiling Reveals a Differential Molecular Signature in Uterine Leiomyoma versus Leiomyosarcoma International Journal of Molecular Sciences leiomyoma leiomyosarcoma exome/transcriptome mutational pattern differential gene expression integrative analysis |
| title | Integrative Genomic and Transcriptomic Profiling Reveals a Differential Molecular Signature in Uterine Leiomyoma versus Leiomyosarcoma |
| title_full | Integrative Genomic and Transcriptomic Profiling Reveals a Differential Molecular Signature in Uterine Leiomyoma versus Leiomyosarcoma |
| title_fullStr | Integrative Genomic and Transcriptomic Profiling Reveals a Differential Molecular Signature in Uterine Leiomyoma versus Leiomyosarcoma |
| title_full_unstemmed | Integrative Genomic and Transcriptomic Profiling Reveals a Differential Molecular Signature in Uterine Leiomyoma versus Leiomyosarcoma |
| title_short | Integrative Genomic and Transcriptomic Profiling Reveals a Differential Molecular Signature in Uterine Leiomyoma versus Leiomyosarcoma |
| title_sort | integrative genomic and transcriptomic profiling reveals a differential molecular signature in uterine leiomyoma versus leiomyosarcoma |
| topic | leiomyoma leiomyosarcoma exome/transcriptome mutational pattern differential gene expression integrative analysis |
| url | https://www.mdpi.com/1422-0067/23/4/2190 |
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