Two-round coamplification at lower denaturation temperature-PCR (COLD-PCR)-based sanger sequencing identifies a novel spectrum of low-level mutations in lung adenocarcinoma.
Two-round coamplification at lower denaturation temperature-PCR (COLD-PCR)-based sanger sequencing identifies a novel spectrum of low-level mutations in lung adenocarcinoma.
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DOI:
10.1002/humu.21112
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发表时间:
2009-11
期刊:
影响因子:
3.9
通讯作者:
Makrigiorgos, G. Mike
中科院分区:
文献类型:
--
作者:
Li, Jin;Milbury, Coren A.;Li, Cheng;Makrigiorgos, G. Mike
Reliable identification of cancer-related mutations in TP53 is often problematic as these mutations can be randomly distributed throughout numerous codons and their relative abundance in clinical samples can fall below the sensitivity limits of conventional sequencing. To ensure the highest sensitivity in mutation detection, we adapted the recently described COLD-PCR method to employ two consecutive rounds of COLD-PCR followed by Sanger sequencing. Using this highly sensitive approach we screened 48 non-microdissected lung-adenocarcinoma samples for TP53 mutations. Twenty-four missense/frameshift TP53 mutations throughout exons 5–8 were identified in 23 of 48 (48%) lung-adenocarcinoma samples examined, including 8 low-level mutations at an abundance of ~1–17%, most of which would have been missed using conventional methodologies. The identified alterations include two rare lung-adenocarcinoma mutations, one of which is a ‘disruptive’ mutation currently undocumented in the lung cancer mutation-databases. A sample harboring a low-level mutation (~2% abundance) concurrently with a clonal mutation (80%-abundance) revealed intra-tumoral TP53 mutation heterogeneity. The ability to identify and sequence low-level mutations in the absence of elaborate micro-dissection, via COLD-PCR-based Sanger-sequencing, provides a platform for accurate mutation profiling in clinical specimens and the use of TP53 as a prognostic/predictive biomarker, evaluation of cancer risk, recurrence, and further understanding of cancer biology.
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影响因子:
9.3
作者:
Milbury CA;Li J;Makrigiorgos GM
通讯作者:
Makrigiorgos GM
影响因子:
3.7
作者:
Chen Z;Feng J;Buzin CH;Sommer SS
通讯作者:
Sommer SS
影响因子:
3.9
作者:
Olivier, M;Eeles, R;Hainaut, P
通讯作者:
Hainaut, P
DOI:
10.1073/pnas.0607057103
发表时间:
2006-11-28
影响因子:
11.1
作者:
Bielas, Jason H.;Loeb, Keith R.;Loeb, Lawrence A.
通讯作者:
Loeb, Lawrence A.
影响因子:
7.5
作者:
Delaney, David;Diss, Tim C.;Flanagan, Adrienne M.
通讯作者:
Flanagan, Adrienne M.