Biomarker and Prognostic Value of Super-ARMS Detection for EGFR Mutation in Advanced NSCLC

Abstract

Background: ctDNA is a non-invasive and convenient method for detecting EGFR mutations in non-small cell lung cancer (NSCLC). However, its sensitivity is lower than that of tissue-based testing. To enhance ctDNA detection efficiency, we identified the patient population most suitable for ctDNA testing, assessed the relationship between ctDNA and tumor markers, and examined the clinical significance of ctDNA in medical practice.

Methods: A single-center retrospective study was conducted, including 135 patients with NSCLC who underwent histological and liquid Super-ARMS tests. Of these, 92 patients with EGFR mutations detected in both tumor tissue and plasma were classified into the EGFR^{t+, p+} group, while 43 patients with EGFR mutations detected only in tumor tissue were classified into the EGFR^{t+, p-} group. The clinical features and outcomes between these two groups were compared.

Results: The positivity rate of Super-ARMS test was 68.1% (92/135). The presence of EGFR^{t+, p+} in the Super-ARMS test was significantly associated with pleural effusion, bone, liver, and multiple organ metastases. Compared to the EGFR^{t+, p+} group, the EGFR^{t+, p-} group had a significantly better PFS (P < 0.01). Carcinoembryonic antigen (CEA) levels demonstrated a strong predictive value for identifying plasma EGFR-mutated patients (AUC 0.828, sensitivity 68.8%, specificity 84.4%), while Maximum Standardized Uptake Value (SUV_max) also showed diagnostic value for plasma EGFR-mutated patients (AUC 0.78). Additionally, combination of TP53 and EGFR mutations in plasma provided improved risk stratification for PFS (P < 0.001).

Conclusion: Patients exhibiting metastasis, elevated levels of tumor markers and SUV_max are more suitable for plasma EGFR mutation testing in clinical NSCLC management. Moreover, a positive plasma ctDNA test not only guides targeted therapy but also predicts a worse prognosis.

Keywords: CEA; EGFR mutation; NSCLC; ctDNA; prognosis.

Figure 1

ROC curve analyses and PFS of patients. (A) The sensitivity and specificity of tumor markers for predicting the presence of plasm EGFR mutation in patients with NSCLC. (B) PFS of patients in CEA≥15.1 group and<15.1 group. (C) PFS of patients in CA125≥44.3 group and<44.3 group. (D) PFS of patients in CFRA21-1≥3.16 group and<3.16 group. The cutoff value is defined based on the Youden index.

Figure 2

ROC curve analyses and PFS of patients. (A) The sensitivity and specificity of SUV_max for predicting the presence of plasm EGFR mutation in patients with NSCLC. (B) PFS of patients in SUV_max(M)<4.8 group and SUV_max(M)≥ 4.8 group. The cutoff value is defined based on the Youden index.

Figure 3

PFS and ORR of patients. (A) PFS of patients in the EGFR^{t+, p+} group and EGFR^{t+, p−} group. (B) ORR of patients in the EGFR^{t+, p+} group and EGFR^{t+, p−} group.

Figure 4

A forest plot of HRs for PFS.

Figure 5

Risk stratification by EGFRm status and TP53. (A) PFS of patients in the TP53 mutation group and TP53 wild type group. (B) PFS of patients in the EGFR^{t+, p+} TP53 mutation group, EGFR^{t+, p+} TP53 wild group, EGFR^{t+, p−} TP53 mutation group and EGFR^{t+, p−} TP53 wild group. (C) PFS of patients between the EGFR^{t+, p+} TP53 mutation group and others.