MOREOVER: multiomics MR-guided radiotherapy optimization in locally advanced rectal cancer.
Circulating tumor DNA
Gut microbioma
Magnetic resonance guided Radiation Therapy
Radiomics
Rectal cancer
Journal
Radiation oncology (London, England)
ISSN: 1748-717X
Titre abrégé: Radiat Oncol
Pays: England
ID NLM: 101265111
Informations de publication
Date de publication:
25 Jul 2024
25 Jul 2024
Historique:
received:
10
07
2024
accepted:
18
07
2024
medline:
26
7
2024
pubmed:
26
7
2024
entrez:
25
7
2024
Statut:
epublish
Résumé
Complete response prediction in locally advanced rectal cancer (LARC) patients is generally focused on the radiomics analysis of staging MRI. Until now, omics information extracted from gut microbiota and circulating tumor DNA (ctDNA) have not been integrated in composite biomarkers-based models, thereby omitting valuable information from the decision-making process. In this study, we aim to integrate radiomics with gut microbiota and ctDNA-based genomics tracking during neoadjuvant chemoradiotherapy (nCRT). The main hypothesis of the MOREOVER study is that the incorporation of composite biomarkers with radiomics-based models used in the THUNDER-2 trial will improve the pathological complete response (pCR) predictive power of such models, paving the way for more accurate and comprehensive personalized treatment approaches. This is due to the inclusion of actionable omics variables that may disclose previously unknown correlations with radiomics. Aims of this study are: - to generate longitudinal microbiome data linked to disease resistance to nCRT and postulate future therapeutic strategies in terms of both type of treatment and timing, such as fecal microbiota transplant in non-responding patients. - to describe the genomics pattern and ctDNA data evolution throughout the nCRT treatment in order to support the prediction outcome and identify new risk-category stratification agents. - to mine and combine collected data through integrated multi-omics approaches (radiomics, metagenomics, metabolomics, metatranscriptomics, human genomics, ctDNA) in order to increase the performance of the radiomics-based response predictive model for LARC patients undergoing nCRT on MR-Linac. The objective of the MOREOVER project is to enrich the phase II THUNDER-2 trial (NCT04815694) with gut microbiota and ctDNA omics information, by exploring the possibility to enhance predictive performance of the developed model. Longitudinal ctDNA genomics, microbiome and genomics data will be analyzed on 7 timepoints: prior to nCRT, during nCRT on a weekly basis and prior to surgery. Specific modelling will be performed for data harvested, according to the TRIPOD statements. We expect to find differences in fecal microbiome, ctDNA and radiomics profiles between the two groups of patients (pCR and not pCR). In addition, we expect to find a variability in the stability of the considered omics features over time. The identified profiles will be inserted into dedicated modelling solutions to set up a multiomics decision support system able to achieve personalized treatments.
Sections du résumé
BACKGROUND
BACKGROUND
Complete response prediction in locally advanced rectal cancer (LARC) patients is generally focused on the radiomics analysis of staging MRI. Until now, omics information extracted from gut microbiota and circulating tumor DNA (ctDNA) have not been integrated in composite biomarkers-based models, thereby omitting valuable information from the decision-making process. In this study, we aim to integrate radiomics with gut microbiota and ctDNA-based genomics tracking during neoadjuvant chemoradiotherapy (nCRT).
METHODS
METHODS
The main hypothesis of the MOREOVER study is that the incorporation of composite biomarkers with radiomics-based models used in the THUNDER-2 trial will improve the pathological complete response (pCR) predictive power of such models, paving the way for more accurate and comprehensive personalized treatment approaches. This is due to the inclusion of actionable omics variables that may disclose previously unknown correlations with radiomics. Aims of this study are: - to generate longitudinal microbiome data linked to disease resistance to nCRT and postulate future therapeutic strategies in terms of both type of treatment and timing, such as fecal microbiota transplant in non-responding patients. - to describe the genomics pattern and ctDNA data evolution throughout the nCRT treatment in order to support the prediction outcome and identify new risk-category stratification agents. - to mine and combine collected data through integrated multi-omics approaches (radiomics, metagenomics, metabolomics, metatranscriptomics, human genomics, ctDNA) in order to increase the performance of the radiomics-based response predictive model for LARC patients undergoing nCRT on MR-Linac.
EXPERIMENTAL DESIGN
METHODS
The objective of the MOREOVER project is to enrich the phase II THUNDER-2 trial (NCT04815694) with gut microbiota and ctDNA omics information, by exploring the possibility to enhance predictive performance of the developed model. Longitudinal ctDNA genomics, microbiome and genomics data will be analyzed on 7 timepoints: prior to nCRT, during nCRT on a weekly basis and prior to surgery. Specific modelling will be performed for data harvested, according to the TRIPOD statements.
DISCUSSION
CONCLUSIONS
We expect to find differences in fecal microbiome, ctDNA and radiomics profiles between the two groups of patients (pCR and not pCR). In addition, we expect to find a variability in the stability of the considered omics features over time. The identified profiles will be inserted into dedicated modelling solutions to set up a multiomics decision support system able to achieve personalized treatments.
Identifiants
pubmed: 39054479
doi: 10.1186/s13014-024-02492-9
pii: 10.1186/s13014-024-02492-9
doi:
Substances chimiques
Circulating Tumor DNA
0
Biomarkers, Tumor
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
94Subventions
Organisme : Fondazione AIRC per la ricerca sul cancro ETS
ID : Next Generation Clinician Scientist_ID 28614
Organisme : Fondazione AIRC per la ricerca sul cancro ETS
ID : Next Generation Clinician Scientist_ID 28614
Organisme : Fondazione AIRC per la ricerca sul cancro ETS
ID : Next Generation Clinician Scientist_ID 28614
Organisme : Fondazione AIRC per la ricerca sul cancro ETS
ID : Next Generation Clinician Scientist_ID 28614
Organisme : Fondazione AIRC per la ricerca sul cancro ETS
ID : Next Generation Clinician Scientist_ID 28614
Organisme : Fondazione AIRC per la ricerca sul cancro ETS
ID : Next Generation Clinician Scientist_ID 28614
Organisme : Fondazione AIRC per la ricerca sul cancro ETS
ID : Next Generation Clinician Scientist_ID 28614
Organisme : Fondazione AIRC per la ricerca sul cancro ETS
ID : Next Generation Clinician Scientist_ID 28614
Organisme : Fondazione AIRC per la ricerca sul cancro ETS
ID : Next Generation Clinician Scientist_ID 28614
Organisme : Fondazione AIRC per la ricerca sul cancro ETS
ID : Next Generation Clinician Scientist_ID 28614
Organisme : Fondazione AIRC per la ricerca sul cancro ETS
ID : Next Generation Clinician Scientist_ID 28614
Organisme : Fondazione AIRC per la ricerca sul cancro ETS
ID : Next Generation Clinician Scientist_ID 28614
Organisme : Fondazione AIRC per la ricerca sul cancro ETS
ID : Next Generation Clinician Scientist_ID 28614
Organisme : Fondazione AIRC per la ricerca sul cancro ETS
ID : Next Generation Clinician Scientist_ID 28614
Organisme : Fondazione AIRC per la ricerca sul cancro ETS
ID : Next Generation Clinician Scientist_ID 28614
Organisme : Fondazione AIRC per la ricerca sul cancro ETS
ID : Next Generation Clinician Scientist_ID 28614
Organisme : Fondazione AIRC per la ricerca sul cancro ETS
ID : Next Generation Clinician Scientist_ID 28614
Informations de copyright
© 2024. The Author(s).
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