The Prognostic and Predictive Role of ATM Expression in Patients with Metastatic Non-Small Cell Lung Cancer Receiving Pembrolizumab Monotherapy or Combination with Chemotherapy

Background/Objectives: This study aimed to investigate the prognostic and predictive significance of ATM expression in patients with metastatic non-small cell lung cancer (NSCLC) treated with pembrolizumab. Methods: A retrospective analysis was conducted on 49 patients with metastatic NSCLC who received first-line pembrolizumab as a single agent or in combination with chemotherapy. Immunohistochemistry was used to assess ATM expression in archival pathology specimens. Nuclear staining was considered positive. ATM expression was categorized into low and high groups based on a combined score of staining intensity and percentage of positive cells. Therafter, prognostic and predictive value of ATM expression was evaluated. Results: The median age was 64 years (range, 45-81). Most patients (91.8%) were male. The majority of patients (75.5%) had adenocarcinoma. The objective response rate (ORR) was 69.4%. ATM expression was high in 75.5% of patients. Patients with low ATM expression had significantly longer progression-free survival (PFS) compared to those with high expression (51 vs. 5.7 months, p=0.004). In multivariate analysis, ATM expression was the only independent prognostic factor for PFS. Moreover, patients with high ATM expression had significantly shorter overall survival (OS) compared to those with low expression (51 vs. 8.9 months, p=0.013), as was statistically significant in multivariate analysis (HR 2.48, p=0.041). Logistic regression analysis showed that ATM expression was significantly associated with response to treatment (p=0.006, OR:0.16, 95% CI: 0.08-0.48), as were the presence of bone metastasis and absence of liver metastasis Conclusions: Our findings showed that lower ATM expression was associated with better prognosis and better pembrolizumab treatment response. This suggests that ATM expression may be a valuable biomarker for predicting disease progression and treatment response.