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Updated: Dec 30, 2025
Author Spotlight: Advancements in Molecular Biomarker Testing for Non-Squamous Non-Small Cell Lung Cancer
Published on: September 8, 2023
Identification of a small mutation panel of coding sequences to predict the efficacy of immunotherapy for lung
Ying Li1, Wenbin Jiang1, Tianhao Li1
1College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150086, China.
Background:
Immune checkpoint inhibitors are effective in some cases of lung adenocarcinoma (LUAD). Whole-exome sequencing has revealed that the tumour mutation burden (TMB) is associated with clinical benefits among patients from immune checkpoint inhibitors. Several commercial mutation panels have been developed for estimating the TMB regardless of the cancer type. However, different cancer types have different mutational landscapes; hence, this study aimed to develop a small cancer-type-specific mutation panel for high-accuracy estimation of the TMB of LUAD patients.
Methods:
We developed a small cancer-type-specific mutation panel based on coding sequences (CDSs) rather than genes, for LUAD patients. Using somatic CDSs mutation data from 486 LUAD patients in The Cancer Genome Atlas (TCGA) database, we pre-selected a set of CDSs with mutation states significantly correlated with the TMB, from which we selected a CDS mutation panel with a panel-score most significantly correlated with the TMB, using a genetic algorithm.
Results:
A mutation panel containing 106 CDSs of 100 genes with only 0.34 Mb was developed, whose length was much shorter than current commercial mutation panels of 0.80-0.92 Mb. The correlation of this panel with the TMB was validated in two independent LUAD datasets with progression-free survival data for patients treated with nivolumab plus ipilimumab and pembrolizumab immunotherapies, respectively. In both test datasets, survival analyses revealed that patients with a high TMB predicted via the 106-CDS mutation panel with a cut-point of 6.20 mutations per megabase, median panel score in the training dataset, had a significantly longer progression-free survival than those with a low predicted TMB (log-rank p = 0.0018, HR = 3.35, 95% CI 1.51-7.42; log-rank p = 0.0020, HR = 5.06, 95% CI 1.63-15.69). This small panel better predicted the efficacy of immunotherapy than current commercial mutation panels.
Conclusions:
The small-CDS mutation panel of only 0.34 Mb is superior to current commercial mutation panels and can better predict the efficacy of immunotherapy for LUAD patients, and its low cost and time-intensiveness make it more suitable for clinical applications.
Insights
A new, small mutation panel for lung adenocarcinoma (LUAD) accurately predicts immunotherapy response. This cost-effective tool enhances prediction of treatment efficacy for LUAD patients.
Area of Science:
- Oncology
- Genomics
- Immunotherapy
Background:
- Immune checkpoint inhibitors show efficacy in lung adenocarcinoma (LUAD).
- Tumor mutation burden (TMB) correlates with treatment benefits from immune checkpoint inhibitors.
- Existing commercial mutation panels for TMB estimation lack cancer-type specificity.
Purpose of the Study:
- To develop a small, cancer-type-specific mutation panel for accurate TMB estimation in LUAD patients.
- To improve prediction of immunotherapy efficacy in LUAD.
Main Methods:
- Developed a mutation panel targeting coding sequences (CDSs) for LUAD.
- Utilized somatic mutation data from 486 LUAD patients (TCGA database).
- Employed a genetic algorithm to select a CDS mutation panel with high TMB correlation.
Main Results:
- A 106-CDS mutation panel (0.34 Mb) was developed, significantly shorter than commercial panels.
- The panel accurately predicted progression-free survival in independent LUAD cohorts treated with immunotherapy.
- High TMB predicted by the panel correlated with significantly longer progression-free survival (log-rank p < 0.002).
Conclusions:
- The developed small-CDS mutation panel outperforms commercial panels for predicting LUAD immunotherapy efficacy.
- Its smaller size, lower cost, and reduced time requirements make it suitable for clinical application.
- This panel offers a more precise tool for patient stratification in LUAD immunotherapy.
