J Vidal1, B Bellosillo2, C Santos Vivas3, P García-Alfonso4, A Carrato5, M T Cano6, R García-Carbonero7, E Élez8, F Losa9, B Massutí10, M Valladares-Ayerbes11, J M Viéitez12, J L Manzano13, D Azuara3, J Gallego14, S Pairet2, G Capellá15, R Salazar3, J Tabernero8, E Aranda6, C Montagut16. 1. Medical Oncology Department, Hospital del Mar-IMIM, CIBERONC Instituto de Salud Carlos III, Barcelona. 2. Pathology Department, Hospital del Mar, Barcelona. 3. Translational Research Laboratory, Medical Oncology Department, Catalan Institute of Oncology (ICO), ICO-Bellvitge Biomedical Research Institute (IDIBELL)-CIBERONC Instituto de Salud Carlos III, L'Hospitalet de Llobregat, Barcelona. 4. Medical Oncology Department, Hospital Gregorio Marañón, Madrid. 5. Medical Oncology Department, Hospital Ramón y Cajal, IRYCIS, CIBERONC Instituto de Salud Carlos III, Alcala University, Madrid. 6. Medical Oncology Department, IMIBIC, Reina Sofía Hospital, University of Cordoba, CIBERONC Instituto de Salud Carlos III. 7. Oncology Department, Hospital Universitario 12 de Octubre, Instituto de Investigación Sanitaria Hospital 12 de Octubre, (imas12), UCM, CNIO, CIBERONC Instituto de Salud Carlos III, Madrid. 8. Medical Oncology Department, Vall d'Hebron University Hospital and Institute of Oncology (VHIO), CIBERONC Instituto de Salud Carlos III, Universitat Autònoma de Barcelona, Barcelona. 9. Medical Oncology Department, Hospital Sant Joan Despí - Moisés Broggi, Barcelona. 10. Medical Oncology Department, Hospital General Universitario, Alicante. 11. Medical Oncology Department, Complejo Hospitalario Universitario de A Coruña, A Coruña. 12. Medical Oncology Department, Hospital Universitario Central de Asturias, Oviedo. 13. Medical Oncology Department, ICO, Badalona, Barcelona. 14. Medical Oncology Department, Hospital General Universitario de Elche, Alicante. 15. Faculty of Medicine, Department of Clinical Sciences, Translational Research Laboratory, ICO-IDIBELL, L'Hospitalet de Llobregat, University of Barcelona, CIBERONC Instituto de Salud Carlos III, Barcelona, Spain. 16. Medical Oncology Department, Hospital del Mar-IMIM, CIBERONC Instituto de Salud Carlos III, Barcelona. Electronic address: cmontagut@parcdesalutmar.cat.
Abstract
BACKGROUND: Extended RAS analysis is mandatory in metastatic colorectal cancer (mCRC) patients. The optimal threshold of RAS mutated subclones to identify patients most likely to benefit from antiepidermal growth factor receptor (EGFR) therapy is controversial. Our aim was to assess the clinical impact of detecting mutations in RAS, BRAF, PIK3CA and EGFRS492R in basal tissue tumour samples by using a highly sensitive next-generation sequencing (NGS) technology in mCRC patients treated with chemotherapy plus anti-EGFR or anti-vascular endothelial growth factor. PATIENTS AND METHODS: Five hundred and eighty-one tumour samples from untreated mCRC patients from 7 clinical studies were collected. Mutational analysis was carried out by standard-of-care (therascreen pyro) with a sensitivity detection of 5% mutant allele fraction (MAF), and compared with NGS technology using 454GS Junior platform (Roche Applied Science, Germany) with a sensitivity of 1%. Molecular results were correlated with clinical outcomes. RESULTS: After quality assessment, 380 samples were evaluable for molecular analysis. Standard-of-care mutational analysis detected RAS, BRAFV600E or PIK3CA mutations in 56.05% of samples compared with 69.21% by NGS (P = 0.00018). NGS identified coexistence of multiple low-frequency mutant alleles in 96 of the 263 mutated cases (36.5%; range 2-7). Response rate (RR), progression-free survival (PFS) and overall survival (OS) were increasingly improved in patients with RAS wild-type, RAS/BRAF wild-type or quadruple (KRAS/NRAS/BRAF/PIK3CA) wild-type tumours treated with anti-EGFR, assessed by standard-of-care. No additional benefit in RR, PFS or OS was observed by increasing the detection threshold to 1% by NGS. An inverse correlation between the MAF of the most prevalent mutation detected by NGS and anti-EGFR response was observed (P = 0.039). EGFRS492Rmutation was not detected in untreated samples. CONCLUSIONS: No improvement in the selection of patients for anti-EGFR therapy was obtained by adjusting the mutation detection threshold in tissue samples from 5% to 1% MAF. Response to anti-EGFR was significantly better in patients with quadruple wild-type tumours.
BACKGROUND: Extended RAS analysis is mandatory in metastatic colorectal cancer (mCRC) patients. The optimal threshold of RAS mutated subclones to identify patients most likely to benefit from antiepidermal growth factor receptor (EGFR) therapy is controversial. Our aim was to assess the clinical impact of detecting mutations in RAS, BRAF, PIK3CA and EGFRS492R in basal tissue tumour samples by using a highly sensitive next-generation sequencing (NGS) technology in mCRC patients treated with chemotherapy plus anti-EGFR or anti-vascular endothelial growth factor. PATIENTS AND METHODS: Five hundred and eighty-one tumour samples from untreated mCRC patients from 7 clinical studies were collected. Mutational analysis was carried out by standard-of-care (therascreen pyro) with a sensitivity detection of 5% mutant allele fraction (MAF), and compared with NGS technology using 454GS Junior platform (Roche Applied Science, Germany) with a sensitivity of 1%. Molecular results were correlated with clinical outcomes. RESULTS: After quality assessment, 380 samples were evaluable for molecular analysis. Standard-of-care mutational analysis detected RAS, BRAFV600E or PIK3CA mutations in 56.05% of samples compared with 69.21% by NGS (P = 0.00018). NGS identified coexistence of multiple low-frequency mutant alleles in 96 of the 263 mutated cases (36.5%; range 2-7). Response rate (RR), progression-free survival (PFS) and overall survival (OS) were increasingly improved in patients with RAS wild-type, RAS/BRAF wild-type or quadruple (KRAS/NRAS/BRAF/PIK3CA) wild-type tumours treated with anti-EGFR, assessed by standard-of-care. No additional benefit in RR, PFS or OS was observed by increasing the detection threshold to 1% by NGS. An inverse correlation between the MAF of the most prevalent mutation detected by NGS and anti-EGFR response was observed (P = 0.039). EGFRS492Rmutation was not detected in untreated samples. CONCLUSIONS: No improvement in the selection of patients for anti-EGFR therapy was obtained by adjusting the mutation detection threshold in tissue samples from 5% to 1% MAF. Response to anti-EGFR was significantly better in patients with quadruple wild-type tumours.
Authors: Anita Sveen; Bjarne Johannessen; Ina A Eilertsen; Bård I Røsok; Marie Gulla; Peter W Eide; Jarle Bruun; Kushtrim Kryeziu; Leonardo A Meza-Zepeda; Ola Myklebost; Bjørn A Bjørnbeth; Rolf I Skotheim; Arild Nesbakken; Ragnhild A Lothe Journal: Genome Med Date: 2021-09-01 Impact factor: 11.117