Highly multiplexed quantifications of 299 somatic mutations in colorectal cancer patients by automated MALDI-TOF mass spectrometry

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Abstract

Background: Detection of somatic mutations in tumor tissues helps to understand tumor biology and guide treatment selection. Methods such as quantitative PCR can analyze a few mutations with high efficiency, while next generation sequencing (NGS) based methods can analyze hundreds to thousands of mutations. However, there is a lack of cost-effective method for quantitatively analyzing tens to a few hundred mutations of potential biological and clinical significance. Methods: Through a comprehensive database and literature review we selected 299 mutations associated with colorectal cancer. We then designed a highly multiplexed assay panel (8-wells covering 299 mutations in 109 genes) based on an automated MADLI-TOF mass spectrometry (MS) platform. The multiplex panel was tested with a total of 319 freshly frozen tissues and 92 FFPE samples from 229 colorectal cancer patients, with 13 samples also analyzed by a targeted NGS method covering 532 genes. Results: Multiplex somatic mutation panel based on MALDI-TOF MS detected and quantified at least one somatic mutation in 142 patients, with KRAS, TP53 and APC being the most frequently mutated genes. Extensive validation by both capillary sequencing and targeted NGS demonstrated high accuracy of the multiplex MS assay. Out of 35 mutations tested with plasmid constructs, sensitivities of 5 and 10% mutant allele frequency were achieved for 19 and 16 mutations, respectively. Conclusions: Automated MALDI-TOF MS offers an efficient and cost-effective platform for highly multiplexed quantitation of 299 somatic mutations, which may be useful in studying the biological and clinical significance of somatic mutations with large numbers of cancer tissues.

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Xu, C., Peng, D., Li, J., Chen, M., Hu, Y., Hou, M., … Ding, C. (2020). Highly multiplexed quantifications of 299 somatic mutations in colorectal cancer patients by automated MALDI-TOF mass spectrometry. BMC Medical Genomics, 13(1). https://doi.org/10.1186/s12920-020-00804-y

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