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Comprehensive genomic profiling on metastatic Melanoma: results from a network screening from 7 Italian Cancer Centres.

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Title: Comprehensive genomic profiling on metastatic Melanoma: results from a network screening from 7 Italian Cancer Centres.
Authors: Pallocca, Matteo1 (AUTHOR) matteo.pallocca@ifo.it, Molineris, Ivan2,3 (AUTHOR), Berrino, Enrico3,4 (AUTHOR), Marcozzi, Benedetta1 (AUTHOR), Betti, Martina1 (AUTHOR), Levati, Lauretta5 (AUTHOR), D'Atri, Stefania5 (AUTHOR), Menin, Chiara6 (AUTHOR), Madonna, Gabriele7 (AUTHOR), Ghiorzo, Paola8,9 (AUTHOR), Bulgarelli, Jenny10 (AUTHOR), Ferraresi, Virgina11 (AUTHOR), Venesio, Tiziana3 (AUTHOR), Rodolfo, Monica12 (AUTHOR), Rivoltini, Licia12 (AUTHOR), Lanfrancone, Luisa13 (AUTHOR), Ascierto, Paolo Antonio6 (AUTHOR), Mazzarella, Luca14 (AUTHOR), Pelicci, Pier Giuseppe13,15 (AUTHOR), De Maria, Ruggero14 (AUTHOR)
Source: Journal of Translational Medicine. 1/6/2024, Vol. 22 Issue 1, p1-7. 7p.
Subject Terms: *MACHINE learning, *SINGLE nucleotide polymorphisms, *MEDICAL screening, *MELANOMA, *RANDOM forest algorithms, *PROGRESSION-free survival
Abstract: Background: The current therapeutic algorithm for Advanced Stage Melanoma comprises of alternating lines of Targeted and Immuno-therapy, mostly via Immune-Checkpoint blockade. While Comprehensive Genomic Profiling of solid tumours has been approved as a companion diagnostic, still no approved predictive biomarkers are available for Melanoma aside from BRAF mutations and the controversial Tumor Mutational Burden. This study presents the results of a Multi-Centre Observational Clinical Trial of Comprehensive Genomic Profiling on Target and Immuno-therapy treated advanced Melanoma. Methods: 82 samples, collected from 7 Italian Cancer Centres of FFPE-archived Metastatic Melanoma and matched blood were sequenced via a custom-made 184-gene amplicon-based NGS panel. Sequencing and bioinformatics analysis was performed at a central hub. Primary analysis was carried out via the Ion Reporter framework. Secondary analysis and Machine Learning modelling comprising of uni and multivariate, COX/Lasso combination, and Random Forest, was implemented via custom R/Python scripting. Results: The genomics landscape of the ACC-mela cohort is comparable at the somatic level for Single Nucleotide Variants and INDELs aside a few gene targets. All the clinically relevant targets such as BRAF and NRAS have a comparable distribution thus suggesting the value of larger scale sequencing in melanoma. No comparability is reached at the CNV level due to biotechnological biases and cohort numerosity. Tumour Mutational Burden is slightly higher in median for Complete Responders but fails to achieve statistical significance in Kaplan–Meier survival analysis via several thresholding strategies. Mutations on PDGFRB, NOTCH3 and RET were shown to have a positive effect on Immune-checkpoint treatment Overall and Disease-Free Survival, while variants in NOTCH4 were found to be detrimental for both endpoints. Conclusions: The results presented in this study show the value and the challenge of a genomics-driven network trial. The data can be also a valuable resource as a validation cohort for Immunotherapy and Target therapy genomic biomarker research. [ABSTRACT FROM AUTHOR]
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  Data: Comprehensive genomic profiling on metastatic Melanoma: results from a network screening from 7 Italian Cancer Centres.
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Translational+Medicine%22">Journal of Translational Medicine</searchLink>. 1/6/2024, Vol. 22 Issue 1, p1-7. 7p.
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– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Background: The current therapeutic algorithm for Advanced Stage Melanoma comprises of alternating lines of Targeted and Immuno-therapy, mostly via Immune-Checkpoint blockade. While Comprehensive Genomic Profiling of solid tumours has been approved as a companion diagnostic, still no approved predictive biomarkers are available for Melanoma aside from BRAF mutations and the controversial Tumor Mutational Burden. This study presents the results of a Multi-Centre Observational Clinical Trial of Comprehensive Genomic Profiling on Target and Immuno-therapy treated advanced Melanoma. Methods: 82 samples, collected from 7 Italian Cancer Centres of FFPE-archived Metastatic Melanoma and matched blood were sequenced via a custom-made 184-gene amplicon-based NGS panel. Sequencing and bioinformatics analysis was performed at a central hub. Primary analysis was carried out via the Ion Reporter framework. Secondary analysis and Machine Learning modelling comprising of uni and multivariate, COX/Lasso combination, and Random Forest, was implemented via custom R/Python scripting. Results: The genomics landscape of the ACC-mela cohort is comparable at the somatic level for Single Nucleotide Variants and INDELs aside a few gene targets. All the clinically relevant targets such as BRAF and NRAS have a comparable distribution thus suggesting the value of larger scale sequencing in melanoma. No comparability is reached at the CNV level due to biotechnological biases and cohort numerosity. Tumour Mutational Burden is slightly higher in median for Complete Responders but fails to achieve statistical significance in Kaplan–Meier survival analysis via several thresholding strategies. Mutations on PDGFRB, NOTCH3 and RET were shown to have a positive effect on Immune-checkpoint treatment Overall and Disease-Free Survival, while variants in NOTCH4 were found to be detrimental for both endpoints. Conclusions: The results presented in this study show the value and the challenge of a genomics-driven network trial. The data can be also a valuable resource as a validation cohort for Immunotherapy and Target therapy genomic biomarker research. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Translational Medicine is the property of BioMed Central and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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