Mutant-Allele Tumor Heterogeneity, a Favorable Biomarker to Assess Intra-Tumor Heterogeneity, in Advanced Lung Adenocarcinoma

Xiaoxuan Wu; Peng Song; Lei Guo; Jianming Ying; Wenbin Li

doi:10.3389/fonc.2022.888951

Mutant-Allele Tumor Heterogeneity, a Favorable Biomarker to Assess Intra-Tumor Heterogeneity, in Advanced Lung Adenocarcinoma

Front Oncol. 2022 Jul 1:12:888951. doi: 10.3389/fonc.2022.888951. eCollection 2022.

Authors

Xiaoxuan Wu¹, Peng Song², Lei Guo¹, Jianming Ying¹, Wenbin Li¹

Affiliations

¹ Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
² Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Abstract

Background: Intra-tumor heterogeneity (ITH) plays a vital role in drug resistance and recurrence of lung cancer. We used a mutant-allele tumor heterogeneity (MATH) algorithm to assess ITH and investigated its association with clinical and molecular features in advanced lung adenocarcinoma.

Methods: Tissues from 63 patients with advanced lung adenocarcinoma were analyzed by next-generation sequencing (NGS) using a panel targeting 520 cancer-relevant genes. We calculated the MATH values from NGS data and further investigated their correlation with clinical and molecular characteristics.

Results: Among the 63 patients with advanced lung adenocarcinoma, the median value of MATH was 33.06. Patients with EGFR mutation had higher level of MATH score than those with wild-type EGFR status (P = 0.008). Patients with stage IV disease showed a trend to have a higher MATH score than those with stage III (P = 0.052). MATH was higher in patients with disruptive TP53 mutations than in those with non-disruptive mutations (P = 0.036) or wild-type sequence (P = 0.023), but did not differ between tumors with non-disruptive mutations and wild-type TP53 (P = 0.867). High MATH is associated with mutations in mismatch repair (MMR) pathway (P = 0.026) and base excision repair (BER) pathway (P = 0.008). In addition, MATH was found to have a positive correlation with tumor mutational burden (TMB) (Spearman ρ = 0.354; P = 0.004). In 26 patients harboring EGFR mutation treated with first generation EGFR TKI as single-agent therapy, the objective response rate was higher in the Low-MATH group than in the High-MATH group (75% vs. 21%; P = 0.016) and Low-MATH group showed a significantly longer progression-free survival than High-MATH group (median PFS: 13.7 months vs. 10.1 months; P = 0.024).

Conclusions: For patients with advanced lung adenocarcinoma, MATH may serve as a clinically practical biomarker to assess intratumor heterogeneity.

Keywords: TP53; intra-tumor heterogeneity; lung adenocarcinoma; mutant-allele tumor heterogeneity; tumor mutational burden.