Open AccessThe interplay between cancer type, panel size and tumor mutational burden threshold in patient selection for cancer immunotherapy
Author(s) -
Mahdi Golkaram,
Chen Zhao,
Kristina M. Kruglyak,
Shile Zhang,
Sven Bilke
Publication year - 2020
Publication title -
plos computational biology/plos computational biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.628
H-Index - 182
eISSN - 1553-7358
pISSN - 1553-734X
DOI - 10.1371/journal.pcbi.1008332
Subject(s) - cancer , immunotherapy , cancer immunotherapy , computational biology , oncology , biomarker , medicine , selection (genetic algorithm) , bioinformatics , biology , computer science , genetics , machine learning
The tumor mutational burden (TMB) is increasingly recognized as an emerging biomarker that predicts improved outcomes or response to immune checkpoint inhibitors in cancer. A multitude of technical and biological factors make it difficult to compare TMB values across platforms, histologies, and treatments. Here, we present a mechanistic model that explains the association between panel size, histology, and TMB threshold with panel performance and survival outcome and demonstrate the limitations of existing methods utilized to harmonize TMB across platforms.