Evidence map›Paper›PMID 41076478›Full record

ArticleMikrochimica acta2025

Mismatch-introduced crRNA guided PCR-CRISPR/Cas12a platform improves EGFR point mutation detection in single tumor cell.

Meng Wu, Fang Wang, Yu Wang, Ya-Xian Wu, Bo-Yu Tian, Xin-Yuan Ou, Qin-Chen Xu, Xiao-Yan Wu, Chao Han, Wan-Li Liu and 1 more

Abstract read
In one paragraph

Article in Mikrochimica acta, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Meng Wu *Department of Clinical Laboratory, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Fang Wang *Department of Molecular Diagnostics, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Yu WangDepartment of Clinical Laboratory, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Ya-Xian WuDepartment of Clinical Laboratory, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Bo-Yu TianDepartment of Clinical Laboratory, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Xin-Yuan OuDepartment of Clinical Laboratory, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Qin-Chen XuDepartment of Clinical Laboratory, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Xiao-Yan WuDepartment of Molecular Diagnostics, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Chao HanLab of Research and Engineering of Cell Therapy Technology, Hangzhou Institute of Medicine Chinese Academy of Sciences, Hangzhou, 310018, China. chao.han@outlook.com.
Wan-Li LiuDepartment of Clinical Laboratory, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, China. liuwl@sysucc.org.cn.
Shan XingDepartment of Clinical Laboratory, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-Sen University Cancer Center, Guangzhou, China. xingshan@sysucc.org.cn.

Funding

the Guangdong Basic and Applied Basic Research Foundation 2021B1515230006
6 · The paper itself

Abstract

Dynamic monitoring of epidermal growth factor receptor (EGFR) mutations is essential for the early identification of resistance and treatment adaptation. Single-cell heterogeneity analysis is crucial for precision cancer medicine, yet sensitive and specific detection methods for individual tumor cells remain challenging. Here, we develop a PCR-CRISPR/Cas12a platform enhanced by the incorporation of mismatched base in crRNA at specific site for single-cell point mutation detection. This platform demonstrated high specificity and sensitivity, detecting point mutation at a frequency of 0.1% and in as low as 1.02 ng of genomic DNA, which represents an improvement over the amplification-refractory mutation system PCR (ARMS-PCR). Notably, the accuracy of the platform is highly consistent with next-generation sequencing (NGS), as evidenced by Kappa test values surpassing 0.9. By utilizing a conical-pore membrane with optimized porosity for single circulating tumor cell (CTC) enrichment, our platform enables point mutations detection in individual tumor cells, offering potential enhancements in precision and reliability for EGFR mutation analysis. This novel methodology holds potential for more accurate and personalized cancer treatment strategies.

Indexed as

CRISPR-Cas SystemsPoint MutationPolymerase Chain ReactionSingle-Cell AnalysisBase Pair MismatchCell Line, TumorDNA Mutational AnalysisErbB ReceptorsHumansNeoplastic Cells, CirculatingEGFR protein, humanErbB ReceptorsClustered Regularly Interspaced Short Palindromic Repeat (CRISPR)Epidermal growth factor receptor (EGFR)MicrofluidicsPoint mutationSingle tumor cell

Identifiers

PMID41076478
PMCPMC12515118

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.