Abstract 471: Reference materials for tumor mutational burden transcriptome profiling
| Autor: | Jessica Dickens, Yves Konigshofer, Matthew G. Butler, Bharathi Anekella |
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| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | Cancer Research. 81:471-471 |
| ISSN: | 1538-7445 0008-5472 |
| DOI: | 10.1158/1538-7445.am2021-471 |
| Popis: | Immune Checkpoint Inhibitor (ICI) therapies continue to revolutionize treatment of advanced malignancies. However, identification of individuals who respond to ICI treatment remains challenging. Along with programmed death ligand 1(PD-L1 aka CD274) expression and microsatellite instability, tumor mutational burden (TMB), defined as the number of nonsynonymous mutations per megabase of genome, has emerged as a promising biomarker for differentiating responders from non-responders, especially in non-small cell lung cancer. Although promising, TMB is not a perfect biomarker for ICI efficacy with some individuals responding conversely to expectations. The imperfection of TMB as a prognostic biomarker may result from it being a proxy measurement of potential neoantigens. Indeed, all mutations that contribute to TMB will not be expressed as neoantigens and not all neoantigens will illicit immune responses. In refining ICI response prediction, tumor abundance of nonsynonymous mutations has aided in neoantigen prediction. In order to begin development of quality reference materials for neoantigen prediction, we have characterized the transcriptomes of four tumor cell lines that were previously used to formulate TMB reference materials. Sequencing libraries were prepared with the TruSeq Stranded Total RNA with Illumina Ribo-Zero Plus rRNA Depletion Kit and Invitrogen Collibri Stranded RNA Library Prep Kit from Illumina with Collibri H/M/R rRNA Depletion Kit. The resultant transcriptome libraries were sequenced on an Illumina NextSeq2000 platform and relative transcript counts were determined. Broad ranges of expression were observed among transcripts containing nonsynonymous mutations in each of the tumor cell lines tested. These datasets will serve as benchmarks for others attempting to combine TMB and tumor abundance in predicting neoantigen potential. Citation Format: Matthew G. Butler, Yves Konigshofer, Jessica Dickens, Bharathi Anekella. Reference materials for tumor mutational burden transcriptome profiling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 471. |
| Databáze: | OpenAIRE |
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