C Santos1, D Azuara2, J M Viéitez3, D Páez4, E Falcó5, E Élez6, C López-López7, M Valladares8, L Robles-Díaz9, P García-Alfonso10, C Bugés11, G Durán12, A Salud13, V Navarro14, G Capellá2, E Aranda15, R Salazar16. 1. Translational Research Laboratory, Institut Català d'Oncologia Oncobell Program-IDIBELL, L'Hospitalet de Llobregat; Department of Medical Oncology, Institut Català d'Oncologia Oncobell Program-IDIBELL, CIBERONC, L'Hospitalet de Llobregat. 2. Translational Research Laboratory, Institut Català d'Oncologia Oncobell Program-IDIBELL, L'Hospitalet de Llobregat. 3. Department of Medical Oncology, Hospital Universitario Central de Asturias, Oviedo. 4. Department of Medical Oncology, Hospital de la Santa Creu i Sant Pau, Barcelona. 5. Department of Medical Oncology, Hospital Son Llàtzer, Palma de Mallorca. 6. Department of Medical Oncology, Hospital Vall d'Hebrón, Barcelona. 7. Department of Medical Oncology, Hospital Universitario Marqués de Valdecilla, Santander. 8. Department of Medical Oncology, Hospital Universitario de A Coruña, A Coruña. 9. Department of Medical Oncology, Hospital Universitario 12 de Octubre, Madrid. 10. Department of Medical Oncology, Hospital General Universitario Gregorio Marañón, Madrid. 11. Department of Medical Oncology, Institut Català d'Oncologia-Hospital Germans Trias i Pujol, Badalona, Institut Català d'Oncologia-Hospital Germans Trias i Pujol. 12. Department of Medical Oncology, Hospital Universitario Virgen de la Victoria, Málaga. 13. Department of Medical Oncology, Hospital Universitari Arnau de Vilanova, Lleida. 14. Clinical Research Unit, Institut Català d'Oncologia, L'Hospitalet de Llobregat. 15. Department of Medical Oncology, IMIBIC, Hospital Universitario Reina Sofía, Universidad de Córdoba, CIBERONC, Córdoba, Spain. 16. Translational Research Laboratory, Institut Català d'Oncologia Oncobell Program-IDIBELL, L'Hospitalet de Llobregat; Department of Medical Oncology, Institut Català d'Oncologia Oncobell Program-IDIBELL, CIBERONC, L'Hospitalet de Llobregat. Electronic address: ramonsalazar@iconcologia.net.
Abstract
BACKGROUND: Several studies show the importance of accurately quantifying not only KRAS and other low-abundant mutations because benefits of anti-EGFR therapies may depend on certain sensitivity thresholds. We assessed whether ultra-selection of patients using a high-sensitive digital PCR (dPCR) to determine KRAS, NRAS, BRAF and PIK3CA status can improve clinical outcomes of panitumumab plus FOLFIRI. PATIENTS AND METHODS: This was a single-arm phase II trial that analysed 38 KRAS, NRAS, BRAF and PIK3CA hotspots in tumour tissues of irinotecan-resistant metastatic colorectal cancer patients who received panitumumab plus FOLFIRI until disease progression or early withdrawal. Mutation profiles were identified by nanofluidic dPCR and correlated with clinical outcomes (ORR, overall response rate; PFS, progression-free survival; OS, overall survival) using cut-offs from 0% to 5%. A quantitative PCR (qPCR) analysis was also performed. RESULTS: Seventy-two evaluable patients were enrolled. RAS (KRAS/NRAS) mutations were detected in 23 (32%) patients and RAS/BRAF mutations in 25 (35%) by dPCR, while they were detected in 7 (10%) and 11 (15%) patients, respectively, by qPCR. PIK3CA mutations were not considered in the analyses as they were only detected in 2 (3%) patients by dPCR and in 1 (1%) patient by qPCR. The use of different dPCR cut-offs for RAS (KRAS/NRAS) and RAS/BRAF analyses translated into differential clinical outcomes. The highest ORR, PFS and OS in wild-type patients with their lowest values in patients with mutations were achieved with a 5% cut-off. We observed similar outcomes in RAS/BRAF wild-type and mutant patients defined by qPCR. CONCLUSIONS: High-sensitive dPCR accurately identified patients with KRAS, NRAS, BRAF and PIK3CA mutations. The optimal RAS/BRAF mutational cut-off for outcome prediction is 5%, which explains that the predictive performance of qPCR was not improved by dPCR. The biological and clinical implications of low-frequent mutated alleles warrant further investigations. CLINICALTRIALS.GOV NUMBER: NCT01704703. EUDRACT NUMBER: 2012-001955-38.
BACKGROUND: Several studies show the importance of accurately quantifying not only KRAS and other low-abundant mutations because benefits of anti-EGFR therapies may depend on certain sensitivity thresholds. We assessed whether ultra-selection of patients using a high-sensitive digital PCR (dPCR) to determine KRAS, NRAS, BRAF and PIK3CA status can improve clinical outcomes of panitumumab plus FOLFIRI. PATIENTS AND METHODS: This was a single-arm phase II trial that analysed 38 KRAS, NRAS, BRAF and PIK3CA hotspots in tumour tissues of irinotecan-resistant metastatic colorectal cancerpatients who received panitumumab plus FOLFIRI until disease progression or early withdrawal. Mutation profiles were identified by nanofluidic dPCR and correlated with clinical outcomes (ORR, overall response rate; PFS, progression-free survival; OS, overall survival) using cut-offs from 0% to 5%. A quantitative PCR (qPCR) analysis was also performed. RESULTS: Seventy-two evaluable patients were enrolled. RAS (KRAS/NRAS) mutations were detected in 23 (32%) patients and RAS/BRAF mutations in 25 (35%) by dPCR, while they were detected in 7 (10%) and 11 (15%) patients, respectively, by qPCR. PIK3CA mutations were not considered in the analyses as they were only detected in 2 (3%) patients by dPCR and in 1 (1%) patient by qPCR. The use of different dPCR cut-offs for RAS (KRAS/NRAS) and RAS/BRAF analyses translated into differential clinical outcomes. The highest ORR, PFS and OS in wild-type patients with their lowest values in patients with mutations were achieved with a 5% cut-off. We observed similar outcomes in RAS/BRAF wild-type and mutant patients defined by qPCR. CONCLUSIONS: High-sensitive dPCR accurately identified patients with KRAS, NRAS, BRAF and PIK3CA mutations. The optimal RAS/BRAF mutational cut-off for outcome prediction is 5%, which explains that the predictive performance of qPCR was not improved by dPCR. The biological and clinical implications of low-frequent mutated alleles warrant further investigations. CLINICALTRIALS.GOV NUMBER: NCT01704703. EUDRACT NUMBER: 2012-001955-38.
Authors: Fabio Gentilini; Christopher J Palgrave; Michal Neta; Raimondo Tornago; Tommaso Furlanello; Jennifer S McKay; Federico Sacchini; Maria E Turba Journal: Front Vet Sci Date: 2022-05-31