Evidence map›Paper›PMID 37249716›Full record

ArticleBiochemical genetics2024

Highly Sensitive Detection of PIK3CA Mutations by Looping-Out Probes-Based Melting Curve Analysis.

Boheng Xu, Yanping Lan, Danjiao Luo, Yangsi Zheng, Runfang Ni, Guoqiang Su, Qiuying Huang, Qingge Li

Abstract read
PubMed Publisher
In one paragraph

Article in Biochemical genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 30% of its field
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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Rapid Detection ofDrug design, development and therapy · 2024
    Article
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

8 authors at 3 institutions in 1 country.

Boheng Xu *Department of Molecular Diagnostics, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, Guangdong, China.
Yanping Lan *Engineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, 361102, Fujian, China.
Danjiao Luo *Engineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, 361102, Fujian, China.
Yangsi ZhengEngineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, 361102, Fujian, China.
Runfang NiEngineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, 361102, Fujian, China.
Guoqiang SuThe First Affiliated Hospital of Xiamen University, Xiamen, 361003, Fujian, China.
Qiuying HuangEngineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, 361102, Fujian, China. hqying@xmu.edu.cn.
Qingge LiEngineering Research Centre of Molecular Diagnostics of the Ministry of Education, State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, 361102, Fujian, China. qgli@xmu.edu.cn.
Xiamen University · CNFirst Affiliated Hospital of Xiamen University · CNSun Yat-sen University Cancer Center · CN

Funding

National Natural Science Foundation of China 81672110
6 · The paper itself

Abstract

PIK3CA mutations have important therapeutic and prognostic implications in various cancer types. However, highly sensitive detection of PIK3CA hotspot mutations in heterogeneous tumor samples remains a challenge in clinical settings. To establish a rapid PCR assay for highly sensitive detection of multiple PIK3CA hotspot mutations. We described a novel melting curve analysis-based assay using looping-out probes that can enrich target mutations in the background of excess wild-type and concurrently reveal the presence of mutations. The analytical and clinical performance of the assay were evaluated. The developed assay could detect 10 PIK3CA hotspot mutations at a mutant allele fraction of 0.05-0.5% within 2 h in a single step. Analysis of 82 breast cancer tissue samples revealed 43 samples with PIK3CA mutations, 28 of which were confirmed by Sanger sequencing. Further testing of 175 colorectal cancer tissue samples showed that 24 samples contained PIK3CA mutations and 19 samples were confirmed by Sanger sequencing. Droplet digital PCR supported that all mutation-containing samples undetected by sequencing contained mutations with a low allele fraction. The rapidity, ease of use, high sensitivity and accuracy make the new assay a potential screening tool for PIK3CA mutations in clinical laboratories.

Indexed as

NeoplasmsClass I Phosphatidylinositol 3-KinasesDNA Mutational AnalysisHumansMutationPolymerase Chain ReactionClass I Phosphatidylinositol 3-KinasesPIK3CA protein, humanBreast cancerColorectal cancerDroplet digital PCRMelting curvePIK3CA mutation

Identifiers

PMID37249716
OpenAlexW4378745372

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.