Development of tumor mutation burden as an immunotherapy biomarker: utility for the oncology clinic
By Timothy A. Chan, M. Yarchoan, E. Jaffee, C. Swanton, Sergio A. Quezada, A. Stenzinger, Solange Peters. Annals of Oncology, 2018
2,243 citations recorded by the source corpus.
Abstract Background Treatment with immune checkpoint blockade (ICB) with agents such as anti-programmed cell death protein 1 (PD-1), anti-programmed death-ligand 1 (PD-L1), and/or anti-cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) can result in impressive response rates and durable disease remission but only in a subset of patients with cancer. Expression of PD-L1 has demonstrated utility in selecting patients for response to ICB and has proven to be an important biomarker for patient selection. Tumor mutation burden (TMB) is emerging as a potential biomarker. However, refinement of interpretation and contextualization is required. Materials and methods In this review, we outline the evolution of TMB as a biomarker in oncology, delineate how TMB can be applied in the clinic, discuss current limitations as a diagnostic test, and highlight mechanistic insights unveiled by the study of TMB. We review available data to date studying TMB as a biomarker for response to ICB by tumor type, focusing on studies proposing a threshold for TMB as a predictive biomarker for ICB activity. Results High TMB consistently selects for benefit with ICB therapy. In lung, bladder and head and neck cancers, the current predictive TMB thresholds proposed approximate 200 non-synonymous somatic mutations by whole exome sequencing (WES). PD-L1 expression influences response to ICB in high TMB tumors with single agent PD-(L)1 antibodies; however, response may not be dependent on PD-L1 expression in the setting of anti-CTLA4 or anti-PD-1/CTLA-4 combination therapy. Disease-specific TMB thresholds for effective prediction of response in various other malignancies are not well established. Conclusions TMB, in concert with PD-L1 expression, has been demonstrated to be a useful biomarker for ICB selection across some cancer types; however, further prospective validation studies are required. TMB determination by selected targeted panels has been correlated with WES. Calibration and harmonization will be required for optimal utility and alignment across all platforms currently used internationally. Key challenges will need to be addressed before broader use in different tumor types.
Subfields: Cancer Research, Oncology, Radiology, Nuclear Medicine and Imaging
View Paper: https://www.semanticscholar.org/paper/62b8d2d8b6d916d64ab7229262e7fac707e9d88f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cancer Research
In Oncology
In Radiology, Nuclear Medicine and Imaging
Citations in the corpus
- Machine learning-based integration develops an immune-derived lncRNA signature for improving outcomes in colorectal cancer (2022, methodology): “Ultimately, 109 signatures (including mRNA and lncRNA signatures) were enroled (Supplementary Data 4).”
- Artificial Intelligence in Cancer Research and Precision Medicine (2021, background): “Tumor mutation burden (TMB) is another important bio-marker of response to checkpoint immunotherapy (42).”