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Updated: Sep 12, 2025
A Combined 3D Tissue Engineered In Vitro/In Silico Lung Tumor Model for Predicting Drug Effectiveness in Specific Mutational Backgrounds
Published on: April 6, 2016
Unlocking the potential: tissue mutation abundance as a predictor for third-generation EGFR-TKI efficacy in NSCLC
Ruiqi Wang1, Hongfei Wei2, Chunjing Qu3
1Department of Hematology and Oncology, China-Japan Union Hospital of Jilin University, Changchun 130033, China; Department of Hematology, the First Hospital of Jilin University, Changchun 130021, China.
Background:
Third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) are recommended as first-line treatment for patients with unresectable non-small cell lung cancer (NSCLC) with EGFR-sensitive mutations, but few studies have explored the role of tissue mutation abundance in predicting their efficacy. To optimize targeted treatments, this study compares the efficacy of first-line third-generation EGFR-TKIs in unresectable NSCLC patients with EGFR-sensitive mutations, focusing on tissue mutation abundance.
Methods:
The study retrospectively analyzed clinical data from 697 patients, ultimately including 159 after screening. Differences in treatment response and median progression-free survival (mPFS) between these groups were examined, and risk factors for mPFS were identified through univariate and multivariate analyses. The disease progression patterns of the two groups were also compared.
Results:
There was no notable difference in complete and partial response rates between the groups. However, the high-abundance group had significantly higher objective response rate (88 % vs. 66.7 %, p = 0.032) and disease control rates (97.2 % vs. 80.4 %, p < 0.001). The mPFS was also longer in the high-abundance group (22 months vs. 17 months, p = 0.024). In the high-abundance group, factors like mutation site, metastasis types and co-existing PI3KCA mutations affected mPFS in univariate analysis, but not in multivariate analysis. In the low-abundance group, ECOG PS and tumor site influenced mPFS. Both groups showed similar patterns of disease progression, including in situ tumor, visceral, bone, and brain metastasis, without statistical significance.
Conclusions:
In unresectable NSCLC with EGFR-sensitive mutations, tissue mutation abundance predicts the efficacy of third-generation TKIs. Patients with high mutation abundance consistently experience longer mPFS. Those with low abundance and peripheral lung cancer also have relatively long mPFS, but other low abundance cases show quick resistance and progression. Further research is needed to create more precise, personalized treatments for these patients.
