Identification of a Maturation Plasma Cell Index through a Highly Sensitive Droplet Digital PCR Assay Gene Expression Signature Validation in Newly Diagnosed Multiple Myeloma Patients
DNA microarrays and RNA-based sequencing approaches are considered important discovery tools in clinical medicine. However, cross-platform reproducibility studies undertaken so far have highlighted that microarrays are not able to accurately measure gene expression, particularly when they are expres...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-10-01
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| Series: | International Journal of Molecular Sciences |
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| Online Access: | https://www.mdpi.com/1422-0067/23/20/12450 |
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| author | Marina Martello Vincenza Solli Rosalinda Termini Ajsi Kanapari Daniel Remondini Enrica Borsi Andrea Poletti Silvia Armuzzi Barbara Taurisano Ilaria Vigliotta Gaia Mazzocchetti Elena Zamagni Alessandra Merlotti Paola Tacchetti Lucia Pantani Serena Rocchi Ilaria Rizzello Katia Mancuso Michele Cavo Carolina Terragna |
| author_facet | Marina Martello Vincenza Solli Rosalinda Termini Ajsi Kanapari Daniel Remondini Enrica Borsi Andrea Poletti Silvia Armuzzi Barbara Taurisano Ilaria Vigliotta Gaia Mazzocchetti Elena Zamagni Alessandra Merlotti Paola Tacchetti Lucia Pantani Serena Rocchi Ilaria Rizzello Katia Mancuso Michele Cavo Carolina Terragna |
| author_sort | Marina Martello |
| collection | DOAJ |
| description | DNA microarrays and RNA-based sequencing approaches are considered important discovery tools in clinical medicine. However, cross-platform reproducibility studies undertaken so far have highlighted that microarrays are not able to accurately measure gene expression, particularly when they are expressed at low levels. Here, we consider the employment of a digital PCR assay (ddPCR) to validate a gene signature previously identified by gene expression profile. This signature included ten Hedgehog (HH) pathways’ genes able to stratify multiple myeloma (MM) patients according to their self-renewal status. Results show that the designed assay is able to validate gene expression data, both in a retrospective as well as in a prospective cohort. In addition, the plasma cells’ differentiation status determined by ddPCR was further confirmed by other techniques, such as flow cytometry, allowing the identification of patients with immature plasma cells’ phenotype (i.e., expressing CD19+/CD81+ markers) upregulating HH genes, as compared to others, whose plasma cells lose the expression of these markers and were more differentiated. To our knowledge, this is the first technical report of gene expression data validation by ddPCR instead of classical qPCR. This approach permitted the identification of a Maturation Index through the integration of molecular and phenotypic data, able to possibly define upfront the differentiation status of MM patients that would be clinically relevant in the future. |
| first_indexed | 2024-03-09T20:05:42Z |
| format | Article |
| id | doaj.art-4c9f08e932094267b251c9c92b513086 |
| institution | Directory Open Access Journal |
| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-03-09T20:05:42Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-4c9f08e932094267b251c9c92b5130862023-11-24T00:31:54ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672022-10-0123201245010.3390/ijms232012450Identification of a Maturation Plasma Cell Index through a Highly Sensitive Droplet Digital PCR Assay Gene Expression Signature Validation in Newly Diagnosed Multiple Myeloma PatientsMarina Martello0Vincenza Solli1Rosalinda Termini2Ajsi Kanapari3Daniel Remondini4Enrica Borsi5Andrea Poletti6Silvia Armuzzi7Barbara Taurisano8Ilaria Vigliotta9Gaia Mazzocchetti10Elena Zamagni11Alessandra Merlotti12Paola Tacchetti13Lucia Pantani14Serena Rocchi15Ilaria Rizzello16Katia Mancuso17Michele Cavo18Carolina Terragna19IRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia “Seràgnoli”, 40138 Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia “Seràgnoli”, 40138 Bologna, ItalyClinica Universidad de Navarra, Centro de Investigación Médica Aplicada (CIMA), Instituto de Investigacion Sanitaria de Navarra (IDISNA), CCUN, CIBER-ONC Numbers CB16/12/00369, CB16/12/00489, 31001 Pamplona, SpainIRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia “Seràgnoli”, 40138 Bologna, ItalyDepartment of Physics and Astronomy, DIFA—University of Bologna, 40126 Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia “Seràgnoli”, 40138 Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia “Seràgnoli”, 40138 Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia “Seràgnoli”, 40138 Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia “Seràgnoli”, 40138 Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia “Seràgnoli”, 40138 Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia “Seràgnoli”, 40138 Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia “Seràgnoli”, 40138 Bologna, ItalyDepartment of Physics and Astronomy, DIFA—University of Bologna, 40126 Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia “Seràgnoli”, 40138 Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia “Seràgnoli”, 40138 Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia “Seràgnoli”, 40138 Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia “Seràgnoli”, 40138 Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia “Seràgnoli”, 40138 Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia “Seràgnoli”, 40138 Bologna, ItalyIRCCS Azienda Ospedaliero-Universitaria di Bologna, Istituto di Ematologia “Seràgnoli”, 40138 Bologna, ItalyDNA microarrays and RNA-based sequencing approaches are considered important discovery tools in clinical medicine. However, cross-platform reproducibility studies undertaken so far have highlighted that microarrays are not able to accurately measure gene expression, particularly when they are expressed at low levels. Here, we consider the employment of a digital PCR assay (ddPCR) to validate a gene signature previously identified by gene expression profile. This signature included ten Hedgehog (HH) pathways’ genes able to stratify multiple myeloma (MM) patients according to their self-renewal status. Results show that the designed assay is able to validate gene expression data, both in a retrospective as well as in a prospective cohort. In addition, the plasma cells’ differentiation status determined by ddPCR was further confirmed by other techniques, such as flow cytometry, allowing the identification of patients with immature plasma cells’ phenotype (i.e., expressing CD19+/CD81+ markers) upregulating HH genes, as compared to others, whose plasma cells lose the expression of these markers and were more differentiated. To our knowledge, this is the first technical report of gene expression data validation by ddPCR instead of classical qPCR. This approach permitted the identification of a Maturation Index through the integration of molecular and phenotypic data, able to possibly define upfront the differentiation status of MM patients that would be clinically relevant in the future.https://www.mdpi.com/1422-0067/23/20/12450multiple myelomahedgehog signalingself-renewaldigital PCRplasma cell maturationdifferentiation stages |
| spellingShingle | Marina Martello Vincenza Solli Rosalinda Termini Ajsi Kanapari Daniel Remondini Enrica Borsi Andrea Poletti Silvia Armuzzi Barbara Taurisano Ilaria Vigliotta Gaia Mazzocchetti Elena Zamagni Alessandra Merlotti Paola Tacchetti Lucia Pantani Serena Rocchi Ilaria Rizzello Katia Mancuso Michele Cavo Carolina Terragna Identification of a Maturation Plasma Cell Index through a Highly Sensitive Droplet Digital PCR Assay Gene Expression Signature Validation in Newly Diagnosed Multiple Myeloma Patients International Journal of Molecular Sciences multiple myeloma hedgehog signaling self-renewal digital PCR plasma cell maturation differentiation stages |
| title | Identification of a Maturation Plasma Cell Index through a Highly Sensitive Droplet Digital PCR Assay Gene Expression Signature Validation in Newly Diagnosed Multiple Myeloma Patients |
| title_full | Identification of a Maturation Plasma Cell Index through a Highly Sensitive Droplet Digital PCR Assay Gene Expression Signature Validation in Newly Diagnosed Multiple Myeloma Patients |
| title_fullStr | Identification of a Maturation Plasma Cell Index through a Highly Sensitive Droplet Digital PCR Assay Gene Expression Signature Validation in Newly Diagnosed Multiple Myeloma Patients |
| title_full_unstemmed | Identification of a Maturation Plasma Cell Index through a Highly Sensitive Droplet Digital PCR Assay Gene Expression Signature Validation in Newly Diagnosed Multiple Myeloma Patients |
| title_short | Identification of a Maturation Plasma Cell Index through a Highly Sensitive Droplet Digital PCR Assay Gene Expression Signature Validation in Newly Diagnosed Multiple Myeloma Patients |
| title_sort | identification of a maturation plasma cell index through a highly sensitive droplet digital pcr assay gene expression signature validation in newly diagnosed multiple myeloma patients |
| topic | multiple myeloma hedgehog signaling self-renewal digital PCR plasma cell maturation differentiation stages |
| url | https://www.mdpi.com/1422-0067/23/20/12450 |
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