UMMS Affiliation

Department of Molecular, Cell and Cancer Biology

Publication Date


Document Type



Computational Biology | Genetics | Genomics | Medical Genetics | Oncology | Therapeutics


AIM: Develop and apply a comprehensive and accurate next-generation sequencing based assay to help clinicians to match oncology patients to therapies.

MATERIALS and METHODS: The performance of the CANCERPLEX(R) assay was assessed using DNA from well-characterized routine clinical formalin-fixed paraffin-embedded (FFPE) specimens and cell lines.

RESULTS: The maximum sensitivity of the assay is 99.5% and its accuracy is virtually 100% for detecting somatic alterations with an allele fraction of as low as 10%. Clinically actionable variants were identified in 93% of patients (930 of 1000) who underwent testing.

CONCLUSION: The test's capacity to determine all of the critical genetic changes, tumor mutation burden, microsatellite instability status and viral associations has important ramifications on clinical decision support strategies, including identification of patients who are likely to benefit from immune checkpoint blockage therapies.


analytical validation, diagnostics, gene-panels, next-generation sequencing (NGS), precision oncology

Rights and Permissions

Copyright © 2017 KEW Inc

DOI of Published Version



Per Med. 2017 Jul;14(4):309-325. doi: 10.2217/pme-2017-0011. Epub 2017 May 26. Link to article on publisher's site

Journal/Book/Conference Title

Personalized medicine

Related Resources

Link to Article in PubMed

PubMed ID


Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.



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