Multi-dimensional scaling techniques unveiled gain1q&loss13q co-occurrence in Multiple Myeloma patients with specific genomic, transcriptional and adverse clinical features
Abstract The complexity of Multiple Myeloma (MM) is driven by several genomic aberrations, interacting with disease-related and/or -unrelated factors and conditioning patients’ clinical outcome. Patient’s prognosis is hardly predictable, as commonly employed MM risk models do not precisely partition...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-02-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-024-45000-z |
| _version_ | 1797274048591298560 |
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| author | Carolina Terragna Andrea Poletti Vincenza Solli Marina Martello Elena Zamagni Lucia Pantani Enrica Borsi Ilaria Vigliotta Gaia Mazzocchetti Silvia Armuzzi Barbara Taurisano Nicoletta Testoni Giulia Marzocchi Ajsi Kanapari Ignazia Pistis Paola Tacchetti Katia Mancuso Serena Rocchi Ilaria Rizzello Michele Cavo |
| author_facet | Carolina Terragna Andrea Poletti Vincenza Solli Marina Martello Elena Zamagni Lucia Pantani Enrica Borsi Ilaria Vigliotta Gaia Mazzocchetti Silvia Armuzzi Barbara Taurisano Nicoletta Testoni Giulia Marzocchi Ajsi Kanapari Ignazia Pistis Paola Tacchetti Katia Mancuso Serena Rocchi Ilaria Rizzello Michele Cavo |
| author_sort | Carolina Terragna |
| collection | DOAJ |
| description | Abstract The complexity of Multiple Myeloma (MM) is driven by several genomic aberrations, interacting with disease-related and/or -unrelated factors and conditioning patients’ clinical outcome. Patient’s prognosis is hardly predictable, as commonly employed MM risk models do not precisely partition high- from low-risk patients, preventing the reliable recognition of early relapsing/refractory patients. By a dimensionality reduction approach, here we dissect the genomic landscape of a large cohort of newly diagnosed MM patients, modelling all the possible interactions between any MM chromosomal alterations. We highlight the presence of a distinguished cluster of patients in the low-dimensionality space, with unfavorable clinical behavior, whose biology was driven by the co-occurrence of chromosomes 1q CN gain and 13 CN loss. Presence or absence of these alterations define MM patients overexpressing either CCND2 or CCND1, fostering the implementation of biology-based patients’ classification models to describe the different MM clinical behaviors. |
| first_indexed | 2024-03-07T14:52:49Z |
| format | Article |
| id | doaj.art-b0670f38bd1042f68b22b11a9e85ac10 |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-03-07T14:52:49Z |
| publishDate | 2024-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-b0670f38bd1042f68b22b11a9e85ac102024-03-05T19:38:02ZengNature PortfolioNature Communications2041-17232024-02-0115111810.1038/s41467-024-45000-zMulti-dimensional scaling techniques unveiled gain1q&loss13q co-occurrence in Multiple Myeloma patients with specific genomic, transcriptional and adverse clinical featuresCarolina Terragna0Andrea Poletti1Vincenza Solli2Marina Martello3Elena Zamagni4Lucia Pantani5Enrica Borsi6Ilaria Vigliotta7Gaia Mazzocchetti8Silvia Armuzzi9Barbara Taurisano10Nicoletta Testoni11Giulia Marzocchi12Ajsi Kanapari13Ignazia Pistis14Paola Tacchetti15Katia Mancuso16Serena Rocchi17Ilaria Rizzello18Michele Cavo19IRCCS Azienda Ospedaliero-Universitaria di Bologna—Istituto di Ematologia “Seràgnoli”IRCCS Azienda Ospedaliero-Universitaria di Bologna—Istituto di Ematologia “Seràgnoli”IRCCS Azienda Ospedaliero-Universitaria di Bologna—Istituto di Ematologia “Seràgnoli”IRCCS Azienda Ospedaliero-Universitaria di Bologna—Istituto di Ematologia “Seràgnoli”IRCCS Azienda Ospedaliero-Universitaria di Bologna—Istituto di Ematologia “Seràgnoli”IRCCS Azienda Ospedaliero-Universitaria di Bologna—Istituto di Ematologia “Seràgnoli”IRCCS Azienda Ospedaliero-Universitaria di Bologna—Istituto di Ematologia “Seràgnoli”IRCCS Azienda Ospedaliero-Universitaria di Bologna—Istituto di Ematologia “Seràgnoli”IRCCS Azienda Ospedaliero-Universitaria di Bologna—Istituto di Ematologia “Seràgnoli”IRCCS Azienda Ospedaliero-Universitaria di Bologna—Istituto di Ematologia “Seràgnoli”IRCCS Azienda Ospedaliero-Universitaria di Bologna—Istituto di Ematologia “Seràgnoli”IRCCS Azienda Ospedaliero-Universitaria di Bologna—Istituto di Ematologia “Seràgnoli”IRCCS Azienda Ospedaliero-Universitaria di Bologna—Istituto di Ematologia “Seràgnoli”IRCCS Azienda Ospedaliero-Universitaria di Bologna—Istituto di Ematologia “Seràgnoli”IRCCS Azienda Ospedaliero-Universitaria di Bologna—Istituto di Ematologia “Seràgnoli”IRCCS Azienda Ospedaliero-Universitaria di Bologna—Istituto di Ematologia “Seràgnoli”IRCCS Azienda Ospedaliero-Universitaria di Bologna—Istituto di Ematologia “Seràgnoli”IRCCS Azienda Ospedaliero-Universitaria di Bologna—Istituto di Ematologia “Seràgnoli”IRCCS Azienda Ospedaliero-Universitaria di Bologna—Istituto di Ematologia “Seràgnoli”IRCCS Azienda Ospedaliero-Universitaria di Bologna—Istituto di Ematologia “Seràgnoli”Abstract The complexity of Multiple Myeloma (MM) is driven by several genomic aberrations, interacting with disease-related and/or -unrelated factors and conditioning patients’ clinical outcome. Patient’s prognosis is hardly predictable, as commonly employed MM risk models do not precisely partition high- from low-risk patients, preventing the reliable recognition of early relapsing/refractory patients. By a dimensionality reduction approach, here we dissect the genomic landscape of a large cohort of newly diagnosed MM patients, modelling all the possible interactions between any MM chromosomal alterations. We highlight the presence of a distinguished cluster of patients in the low-dimensionality space, with unfavorable clinical behavior, whose biology was driven by the co-occurrence of chromosomes 1q CN gain and 13 CN loss. Presence or absence of these alterations define MM patients overexpressing either CCND2 or CCND1, fostering the implementation of biology-based patients’ classification models to describe the different MM clinical behaviors.https://doi.org/10.1038/s41467-024-45000-z |
| spellingShingle | Carolina Terragna Andrea Poletti Vincenza Solli Marina Martello Elena Zamagni Lucia Pantani Enrica Borsi Ilaria Vigliotta Gaia Mazzocchetti Silvia Armuzzi Barbara Taurisano Nicoletta Testoni Giulia Marzocchi Ajsi Kanapari Ignazia Pistis Paola Tacchetti Katia Mancuso Serena Rocchi Ilaria Rizzello Michele Cavo Multi-dimensional scaling techniques unveiled gain1q&loss13q co-occurrence in Multiple Myeloma patients with specific genomic, transcriptional and adverse clinical features Nature Communications |
| title | Multi-dimensional scaling techniques unveiled gain1q&loss13q co-occurrence in Multiple Myeloma patients with specific genomic, transcriptional and adverse clinical features |
| title_full | Multi-dimensional scaling techniques unveiled gain1q&loss13q co-occurrence in Multiple Myeloma patients with specific genomic, transcriptional and adverse clinical features |
| title_fullStr | Multi-dimensional scaling techniques unveiled gain1q&loss13q co-occurrence in Multiple Myeloma patients with specific genomic, transcriptional and adverse clinical features |
| title_full_unstemmed | Multi-dimensional scaling techniques unveiled gain1q&loss13q co-occurrence in Multiple Myeloma patients with specific genomic, transcriptional and adverse clinical features |
| title_short | Multi-dimensional scaling techniques unveiled gain1q&loss13q co-occurrence in Multiple Myeloma patients with specific genomic, transcriptional and adverse clinical features |
| title_sort | multi dimensional scaling techniques unveiled gain1q loss13q co occurrence in multiple myeloma patients with specific genomic transcriptional and adverse clinical features |
| url | https://doi.org/10.1038/s41467-024-45000-z |
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