Abstract
The response of metastatic colorectal cancer (mCRC) to the first-line conventional combination therapy is highly variable, reflecting the elevated heterogeneity of the disease. The genetic alterations underlying this heterogeneity have been thoroughly characterized through omic approaches requiring elevated efforts and costs. In order to translate the knowledge of CRC molecular heterogeneity into a practical clinical approach, we utilized a simplified Next Generation Sequencing (NGS) based platform to screen a cohort of 77 patients treated with first-line conventional therapy. Samples were sequenced using a panel of hotspots and targeted regions of 22 genes commonly involved in CRC. This revealed 51 patients carrying actionable gene mutations, 22 of which carried druggable alterations. These mutations were frequently associated with additional genetic alterations. To take into account this molecular complexity and assisted by an unbiased bioinformatic analysis, we defined three subgroups of patients carrying distinct molecular patterns. We demonstrated these three molecular subgroups are associated with a different response to first-line conventional combination therapies. The best outcome was achieved in patients exclusively carrying mutations on TP53 and/or RAS genes. By contrast, in patients carrying mutations in any of the other genes, alone or associated with mutations of TP53/RAS, the expected response is much worse compared to patients with exclusive TP53/RAS mutations. Additionally, our data indicate that the standard approach has limited efficacy in patients without any mutations in the genes included in the panel. In conclusion, we identified a reliable and easy-to-use approach for a simplified molecular-based stratification of mCRC patients that predicts the efficacy of the first-line conventional combination therapy.
| Original language | English |
|---|---|
| Journal | Cancers |
| Volume | 11 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - Jan 27 2019 |
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A Simplified Genomic Profiling Approach Predicts Outcome in Metastatic Colorectal Cancer. / Capalbo, Carlo; Belardinilli, Francesca; Raimondo, Domenico; Milanetti, Edoardo; Malapelle, Umberto; Pisapia, Pasquale; Magri, Valentina; Prete, Alessandra; Pecorari, Silvia; Colella, Mariarosaria; Coppa, Anna; Bonfiglio, Caterina; Nicolussi, Arianna; Valentini, Virginia; Tessitore, Alessandra; Cardinali, Beatrice; Petroni, Marialaura; Infante, Paola; Santoni, Matteo; Filetti, Marco; Colicchia, Valeria; Paci, Paola; Mezi, Silvia; Longo, Flavia; Cortesi, Enrico; Marchetti, Paolo; Troncone, Giancarlo; Bellavia, Diana; Canettieri, Gianluca; Giannini, Giuseppe.
In: Cancers, Vol. 11, No. 2, 27.01.2019.Research output: Contribution to journal › Article
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TY - JOUR
T1 - A Simplified Genomic Profiling Approach Predicts Outcome in Metastatic Colorectal Cancer
AU - Capalbo, Carlo
AU - Belardinilli, Francesca
AU - Raimondo, Domenico
AU - Milanetti, Edoardo
AU - Malapelle, Umberto
AU - Pisapia, Pasquale
AU - Magri, Valentina
AU - Prete, Alessandra
AU - Pecorari, Silvia
AU - Colella, Mariarosaria
AU - Coppa, Anna
AU - Bonfiglio, Caterina
AU - Nicolussi, Arianna
AU - Valentini, Virginia
AU - Tessitore, Alessandra
AU - Cardinali, Beatrice
AU - Petroni, Marialaura
AU - Infante, Paola
AU - Santoni, Matteo
AU - Filetti, Marco
AU - Colicchia, Valeria
AU - Paci, Paola
AU - Mezi, Silvia
AU - Longo, Flavia
AU - Cortesi, Enrico
AU - Marchetti, Paolo
AU - Troncone, Giancarlo
AU - Bellavia, Diana
AU - Canettieri, Gianluca
AU - Giannini, Giuseppe
PY - 2019/1/27
Y1 - 2019/1/27
N2 - The response of metastatic colorectal cancer (mCRC) to the first-line conventional combination therapy is highly variable, reflecting the elevated heterogeneity of the disease. The genetic alterations underlying this heterogeneity have been thoroughly characterized through omic approaches requiring elevated efforts and costs. In order to translate the knowledge of CRC molecular heterogeneity into a practical clinical approach, we utilized a simplified Next Generation Sequencing (NGS) based platform to screen a cohort of 77 patients treated with first-line conventional therapy. Samples were sequenced using a panel of hotspots and targeted regions of 22 genes commonly involved in CRC. This revealed 51 patients carrying actionable gene mutations, 22 of which carried druggable alterations. These mutations were frequently associated with additional genetic alterations. To take into account this molecular complexity and assisted by an unbiased bioinformatic analysis, we defined three subgroups of patients carrying distinct molecular patterns. We demonstrated these three molecular subgroups are associated with a different response to first-line conventional combination therapies. The best outcome was achieved in patients exclusively carrying mutations on TP53 and/or RAS genes. By contrast, in patients carrying mutations in any of the other genes, alone or associated with mutations of TP53/RAS, the expected response is much worse compared to patients with exclusive TP53/RAS mutations. Additionally, our data indicate that the standard approach has limited efficacy in patients without any mutations in the genes included in the panel. In conclusion, we identified a reliable and easy-to-use approach for a simplified molecular-based stratification of mCRC patients that predicts the efficacy of the first-line conventional combination therapy.
AB - The response of metastatic colorectal cancer (mCRC) to the first-line conventional combination therapy is highly variable, reflecting the elevated heterogeneity of the disease. The genetic alterations underlying this heterogeneity have been thoroughly characterized through omic approaches requiring elevated efforts and costs. In order to translate the knowledge of CRC molecular heterogeneity into a practical clinical approach, we utilized a simplified Next Generation Sequencing (NGS) based platform to screen a cohort of 77 patients treated with first-line conventional therapy. Samples were sequenced using a panel of hotspots and targeted regions of 22 genes commonly involved in CRC. This revealed 51 patients carrying actionable gene mutations, 22 of which carried druggable alterations. These mutations were frequently associated with additional genetic alterations. To take into account this molecular complexity and assisted by an unbiased bioinformatic analysis, we defined three subgroups of patients carrying distinct molecular patterns. We demonstrated these three molecular subgroups are associated with a different response to first-line conventional combination therapies. The best outcome was achieved in patients exclusively carrying mutations on TP53 and/or RAS genes. By contrast, in patients carrying mutations in any of the other genes, alone or associated with mutations of TP53/RAS, the expected response is much worse compared to patients with exclusive TP53/RAS mutations. Additionally, our data indicate that the standard approach has limited efficacy in patients without any mutations in the genes included in the panel. In conclusion, we identified a reliable and easy-to-use approach for a simplified molecular-based stratification of mCRC patients that predicts the efficacy of the first-line conventional combination therapy.
U2 - 10.3390/cancers11020147
DO - 10.3390/cancers11020147
M3 - Article
C2 - 30691222
VL - 11
JO - Cancers
JF - Cancers
SN - 2072-6694
IS - 2
ER -