Bibliographic Details
| Title: |
Panels and models for accurate prediction of tumor mutation burden in tumor samples |
| Authors: |
Elizabeth Martínez-Pérez, Miguel Angel Molina-Vila, Cristina Marino-Buslje |
| Source: |
npj Precision Oncology, Vol 5, Iss 1, Pp 1-8 (2021) |
| Publisher Information: |
Nature Portfolio, 2021. |
| Publication Year: |
2021 |
| Collection: |
LCC:Neoplasms. Tumors. Oncology. Including cancer and carcinogens |
| Subject Terms: |
Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282 |
| More Details: |
Abstract Immune checkpoint blockade (ICB) is becoming standard-of-care in many types of human malignancies, but patient selection is still imperfect. Tumor mutation burden (TMB) is being evaluated as a biomarker for ICB in clinical trials, but most of the sequencing panels used to estimate it are inadequately designed. Here, we present a bioinformatics-based method to select panels and mathematical models for accurate TMB prediction. Our method is based on tumor-specific, forward-step selection of genes, generation of panels using a linear regression algorithm, and rigorous internal and external validation comparing predicted with experimental TMB. As a result, we propose cancer-specific panels for 14 malignancies which can offer reliable, clinically relevant estimates of TMBs. Our work facilitates a better prediction of TMB that can improve the selection of patients for ICB therapy. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
2397-768X |
| Relation: |
https://doaj.org/toc/2397-768X |
| DOI: |
10.1038/s41698-021-00169-0 |
| Access URL: |
https://doaj.org/article/1b76c4e637d44f018df09d860ec13ed7 |
| Accession Number: |
edsdoj.1b76c4e637d44f018df09d860ec13ed7 |
| Database: |
Directory of Open Access Journals |
