ArticleOncology letters2020
A robust method for the rapid detection of microsatellite instability in colorectal cancer.
Article in Oncology letters, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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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.
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Who cites it
9 citing papers in PubMed.
- Leveraging Radiomics and Hybrid Quantum-Classical Convolutional Networks for Non-Invasive Detection of Microsatellite Instability in Colorectal Cancer.Molecular imaging and biology · 2025Article
- Performance assessment of computational tools to detect microsatellite instability.Briefings in bioinformatics · 2024Article
- Detecting Microsatellite Instability in Endometrial, Colon, and Stomach Cancers Using Targeted NGS.Cancers · 2023Article
- Microsatellite instability assessment is instrumental for Predictive, Preventive and Personalised Medicine: status quo and outlook.The EPMA journal · 2023Review
- A new strategy in molecular typing: the accuracy of an NGS panel for the molecular classification of endometrial cancers.Annals of translational medicine · 2022Article
- MEM: An Algorithm for the Reliable Detection of Microsatellite Instability (MSI) on a Small NGS Panel in Colorectal Cancer.Cancers · 2021Article
- Detection of Microsatellite Instability: State of the Art and Future Applications in Circulating Tumour DNA (ctDNA).Cancers · 2021Review
- Article
- Sensitive detection of microsatellite instability in tissues and liquid biopsies: Recent developments and updates.Computational and structural biotechnology journal · 2021Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although several computational tools using next-generation sequencing (NGS) data have been proposed to detect microsatellite instability (MSI) status, they still have limitations and need improvement. We developed a NovoPM-MSI method to detect MSI status based on NGS data. This method evaluated target mononucleotide microsatellite loci that were sequenced during targeted gene enrichment analysis and reported sample instability score as the fraction of unstable loci within the target set after assessing locus instability by comparing length distribution in paired tumor-normal samples. We validated this method against the conventional MSI-PCR method in 113 paired colorectal cancer (CRC) specimens and compared the performance of NovoPM-MSI to that of mSINGS and MANTIS in accuracy and runtime efficiency. By using the MSI status from MSI-PCR as the gold standard, the three computational methods showed the same sensitivity of 88.9% but different specificities (NovoPM-MSI 97.1%, MANTIS 86.5% and mSINGS 99.0%). Only NovoPM-MSI could greatly improve both the sensitivity and specificity by setting an ambiguous interval. MANTIS had the shortest average runtime (16.3 sec), followed by NovoPM-MSI (18.3 sec) and mSINGS (109.0 sec). In short, the NovoPM-MSI method provides a fast and reliable MSI detection method with accuracy comparable to MSI-PCR in paired CRC samples.
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