BACKGROUND: Mutation detection in tumours will become increasingly important in pathological diagnosis as 'predictive' mutations are identified. A cheap and reliable test that works on formalin-fixed paraffin-embedded (FFPE) tissue is required. METHODS: The quick-multiplex-consensus (QMC)-PCR protocol was developed to be used with high-resolution melting (HRM) analysis. The assay was compared with Sanger sequencing. Robustness of the assay was tested in DNA from FFPE tissue. RESULTS: QMC-PCR with HRM could detect a minimum of 2.5% of mutant alleles (compared with 20% detectable for Sanger sequencing). Ten mutation hotspots in KRAS, BRAF, PIK3CA and CDC4 were screened in 29 cell lines with 100% sensitivity and specificity. Forty-three FFPE colorectal tumours were sequenced for hotspots in KRAS and PIK3CA and then screened by QMC-PCR. There was 100% sensitivity, although, of 21 mutations detected by QMC-PCR, 16 were confirmed by sequencing (71% specificity, positive predictive value 76%). All 43 samples were then screened for mutations in all 10 hotspots. Of 430 tests, 43 (10%) showed aberrant melting and 36 were confirmed mutant (positive predictive value 84%). As our technique is more sensitive than direct sequencing, the remaining seven tests are probably sequencing false-negatives. Precision tests showed that there was little intra-assay and interassay variation. CONCLUSIONS: QMC-PCR with HRM is a simple, robust and inexpensive technique which had greater sensitivity than Sanger sequencing. It allows multiple mutation hotspots to be rapidly screened and is thus highly suited to mutation detection in DNA derived from FFPE tissues.
BACKGROUND: Mutation detection in tumours will become increasingly important in pathological diagnosis as 'predictive' mutations are identified. A cheap and reliable test that works on formalin-fixed paraffin-embedded (FFPE) tissue is required. METHODS: The quick-multiplex-consensus (QMC)-PCR protocol was developed to be used with high-resolution melting (HRM) analysis. The assay was compared with Sanger sequencing. Robustness of the assay was tested in DNA from FFPE tissue. RESULTS:QMC-PCR with HRM could detect a minimum of 2.5% of mutant alleles (compared with 20% detectable for Sanger sequencing). Ten mutation hotspots in KRAS, BRAF, PIK3CA and CDC4 were screened in 29 cell lines with 100% sensitivity and specificity. Forty-three FFPE colorectal tumours were sequenced for hotspots in KRAS and PIK3CA and then screened by QMC-PCR. There was 100% sensitivity, although, of 21 mutations detected by QMC-PCR, 16 were confirmed by sequencing (71% specificity, positive predictive value 76%). All 43 samples were then screened for mutations in all 10 hotspots. Of 430 tests, 43 (10%) showed aberrant melting and 36 were confirmed mutant (positive predictive value 84%). As our technique is more sensitive than direct sequencing, the remaining seven tests are probably sequencing false-negatives. Precision tests showed that there was little intra-assay and interassay variation. CONCLUSIONS:QMC-PCR with HRM is a simple, robust and inexpensive technique which had greater sensitivity than Sanger sequencing. It allows multiple mutation hotspots to be rapidly screened and is thus highly suited to mutation detection in DNA derived from FFPE tissues.
Authors: David J Panka; Elizabeth Buchbinder; Anita Giobbie-Hurder; Aislyn P Schalck; Laleh Montaser-Kouhsari; Alireza Sepehr; Donald P Lawrence; David F McDermott; Rachel Cohen; Alexander Carlson; Jennifer A Wargo; Ryan Merritt; Virginia J Seery; F Stephen Hodi; Anasuya Gunturi; Dennie Fredrick; Michael B Atkins; A John Iafrate; Keith T Flaherty; James W Mier; Ryan J Sullivan Journal: Mol Cancer Ther Date: 2014-10-15 Impact factor: 6.261
Authors: Jonathan C Dudley; Grzegorz T Gurda; Li-Hui Tseng; Derek A Anderson; Guoli Chen; Janis M Taube; Christopher D Gocke; James R Eshleman; Ming-Tseh Lin Journal: Mol Diagn Ther Date: 2014-08 Impact factor: 4.074
Authors: Hersh A Ham-Karim; Henry Okuchukwu Ebili; Kirsty Manger; Wakkas Fadhil; Narmeen S Ahmad; Susan D Richman; Mohammad Ilyas Journal: Mol Diagn Ther Date: 2019-06 Impact factor: 4.074
Authors: Jesus Gonzalez-Bosquet; Jacob Calcei; Jun S Wei; Montserrat Garcia-Closas; Mark E Sherman; Stephen Hewitt; Joseph Vockley; Jolanta Lissowska; Hannah P Yang; Javed Khan; Stephen Chanock Journal: PLoS One Date: 2011-01-17 Impact factor: 3.240
Authors: Saleh Al-Ghamdi; Abdulkader Albasri; Julien Cachat; Salih Ibrahem; Belal A Muhammad; Darryl Jackson; Abdolrahman S Nateri; Karin B Kindle; Mohammad Ilyas Journal: PLoS One Date: 2011-06-16 Impact factor: 3.240