Comparative survival outcomes between EGFR-wildtype and EGFR-mutant lung adenocarcinoma following neoadjuvant chemoimmunotherapy: a retrospective cohort study from national cancer center in China

Introduction

Lung cancer persists as the leading cause of cancer-related mortality globally, with approximately 2.2 million new cases and 1.8 million deaths reported in 2020 (1). Non-small cell lung cancer (NSCLC), particularly adenocarcinoma, constitutes over 85% of cases, with distinct molecular heterogeneity influencing therapeutic strategies (2). In Asian populations, epidermal growth factor receptor (EGFR) mutations occur in 31% of NSCLC patients, significantly higher than the 15% observed in Caucasians, primarily driven by exon 19 deletions (ex19del) and exon 21 L858R substitutions (3). These mutations constitutively activate EGFR signaling, promoting tumor proliferation and metastasis (4). While EGFR tyrosine kinase inhibitors (EGFR-TKIs) have revolutionized outcomes for advanced EGFR-mutant NSCLC, extending progression-free survival (PFS) and overall survival (OS) (5), the optimal neoadjuvant approach for resectable stage I–III lung adenocarcinoma (LUAD) remains contentious, necessitating integration of targeted therapies, chemoimmunotherapy, and precision surgery (6).

Conventional neoadjuvant chemotherapy, though effective in reducing tumor burden, achieves pathological complete response (pCR) rates below 5% and offers limited survival benefits for EGFR-mutant patients (7). Emerging strategies, such as neoadjuvant targeted therapy (NTT) with EGFR-TKIs (e.g., osimertinib), demonstrate objective response rates (ORR) of 30–50% in phase II trials, yet pathological responses [e.g., major pathological response (MPR) ≤10% viable tumor] remain suboptimal (5–15%) and fail to mitigate postoperative recurrence risks (8,9). Conversely, neoadjuvant chemoimmunotherapy (NCI)—combining immune checkpoint inhibitors (ICIs) like programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) inhibitors with platinum-based chemotherapy—has shown remarkable efficacy in driver-negative NSCLC, achieving MPR rates of 36.9% (10). However, EGFR-mutant tumors often exhibit an immunologically “cold” microenvironment characterized by low PD-L1 expression and diminished T-cell infiltration, potentially limiting ICI efficacy (11).

In addition, though the bulk of clinical trials of neoadjuvant or/and adjuvant ICIs excluded patients harboring an EGFR or other driver mutations, a previous study found unexpected survival benefits of perioperative ICIs in resectable EGFR mutant NSCLC with limited data. The possible underlying mechanism for the paradoxical results remains unexplored (12). Critical knowledge gaps persist regarding the differential efficacy of NCI between EGFR-mutant and wildtype subgroups, particularly in pathological response, survival outcomes, and recurrence patterns.

This retrospective cohort study represents the first comprehensive comparison of therapeutic efficacy (assessed by pathological response rates and radiological evaluations), perioperative outcomes, and long-term survival outcomes between EGFR-mutant and EGFR-wildtype clinically stage I–III LUAD patients. The results may facilitate molecular subtype-guided clinical management by delineating outcome disparities across genetically stratified subgroups. We present this article in accordance with the STROBE reporting checklist (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-594/rc).

Methods

Study design and population selection

We retrospectively collected 485 patients who underwent therapeutic surgery following treatment with NCI at the Cancer Hospital, Chinese Academy of Medical Sciences (CHCAMS) in China between July 2017 and April 2024. The inclusion criteria for the study comprised: (I) patients diagnosed with stage I–III LUAD confirmed by pathological examination; (II) patients who underwent radical surgery following NCI; and (III) patients with complete baseline data (including imaging studies, pathology reports, and genetic testing results). Exclusion criteria included: (I) the pathological diagnosis of the tumor was non-LUAD (n=364); (II) the pathological diagnosis of the tumor was anaplastic lymphoma kinase (ALK)-mutation or other non-EGFR mutation (n=2); (III) the pathological diagnosis of the tumor was stage IV (n=3); (IV) incomplete clinical data information (n=19) (Figure 1). To ensure accurate tumor staging and evaluate surgical feasibility, all patients underwent systematic multidisciplinary evaluation before and after treatment. Before neoadjuvant therapy, comprehensive perioperative assessments were performed, including enhanced chest computed tomography (CT), whole-body positron emission tomography-CT (PET-CT), brain magnetic resonance imaging (MRI), and pathological biopsy [endobronchial ultrasound/transbronchial needle aspiration (EBUS/TBNA) or CT-guided lung puncture]. A multidisciplinary clinical team (MDCT) consisting of specialists in thoracic surgery, medical oncology, radiology, and pathology collectively reviewed all imaging and pathology results to ensure accurate staging. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Medical Ethics Committee of the Cancer Hospital, Chinese Academy of Medical Sciences (CHCAMS) (approval No. 22/492-3694) and individual consent for this retrospective analysis was waived.

Figure 1 Flow chart of patient selection. ALK, anaplastic lymphoma kinase; CHCAMS, Cancer Hospital, Chinese Academy of Medical Sciences; EGFR, ​epidermal growth factor receptor; LUAD, lung adenocarcinoma; NSCLC, non-small cell lung cancer; PSM, propensity score matching.

Preoperative neoadjuvant therapy and pathological parameters

All patients underwent 2–4 cycles (21-day per cycle) of NCI consisting of programmed death-1 inhibitors (200 mg camrelizumab, nivolumab, sintilimab, tislelizumab, or pembrolizumab) combined with platinum-based chemotherapy [cisplatin 75 mg/m² or carboplatin area under the curve (AUC) 5] plus 260 mg/m² nanoparticle albumin-bound paclitaxel. According to the EGFR mutation status, the patients were divided into two groups (EGFR-mutant and EGFR-wildtype groups). Comprehensive imaging assessments, including enhanced chest CT, whole-body PET-CT, and brain MRI, were conducted before and after treatment. Tumor staging followed the 8^th edition of the International Association for the Study of Lung Cancer (IASLC) tumor node metastasis (TNM) classification (13). Radiological responses were evaluated using Response Evaluation Criteria in Solid Tumors (RECIST v1.1) (14), categorized as: complete response (CR), partial response (PR), stable disease (SD), or progressive disease (PD) (9). For pathological evaluation, biopsies and postoperative specimens underwent standardized processing. EGFR mutation status was determined by next-generation sequencing (NGS; Illumina platform), covering exons 18–21. pCR was defined as no viable tumor cells in the tumor bed or lymph nodes (LNs) post-treatment. Pathological stage 0 (pStage 0) was defined as pCR with no viable tumor cells in the primary tumor bed or LNs following NCI and surgical resection. MPR was defined as ≤10% viable tumor cells in the tumor bed. Two experienced pathologists independently assessed pathological responses. Discrepancies were resolved by a third pathologist, with final determination by majority consensus. For unresectable cases due to disease progression, alternative therapies (e.g., radiotherapy or systemic therapy) were provided. Operable patients underwent either open radical surgery or video-assisted thoracoscopic surgery (VATS). Both approaches included systematic lymphadenectomy (≥3 N2 LN stations). Postoperative follow-up included chest CT and tumor marker assessments within 4 weeks, with imaging confirmation of resolution/progression for baseline suspicious lesions. Follow-up chest CTs were conducted every 1–3 months, and a minimum of 1 year of monitoring or until treatment cessation (due to progression or death).

Analyses of preoperative and postoperative outcomes

Demographic variables included age, gender, surgical approach, smoking history, pathological stage, family history of cancer, tumor location, body mass index (BMI), and resection type. Preoperative comorbidities were assessed using the Charlson Comorbidity Index (CCI) (15), and postoperative complications were classified according to the Clavien-Dindo classification system (15). Postoperative outcomes included: intensive care unit (ICU) stay duration, operative time, intraoperative blood loss, and postoperative hospital stay length.

Follow-up, survival, and recurrence

OS was calculated from the date of surgery to either the date of death confirmation or the last follow-up date (for censored cases). Recurrence-free survival (RFS) was defined as the time from the surgery date to either confirmed cancer relapse or the last follow-up date. Locoregional recurrence (LR) included bronchial stump recurrence, ipsilateral mediastinal disease. Distant recurrence (DR) was defined as recurrence in the supraclavicular LN, pleural recurrence, contralateral lung, or extra-thoracic organs (brain, liver, or other distant sites).

Statistical analysis

Continuous variables were presented as medians with interquartile ranges (IQRs), and comparisons were performed using the Wilcoxon rank-sum test. Categorical variables were summarized as frequencies (percentages), and intergroup differences were assessed using Fisher’s exact test. Propensity scores matching (PSM) with a 2:1 ratio was used to balance baseline covariates that could potentially influence surgical outcomes. Multivariate Cox models included EGFR status and all variables with P<0.1 in univariate analysis. RFS and OS were estimated via the Kaplan-Meier method, with stratified log-rank tests used to compare between-group differences, and median follow-up duration calculated using the reverse Kaplan-Meier estimator. All analyses were performed using R software (version 4.2.0; R Foundation for Statistical Computing, Vienna, Austria). Two-sided P values <0.05 were considered statistically significant.

Results

Patient’s characteristics

A total of 97 patients with clinically stage I–III LUAD receiving NCI were included in the study, comprising 65 patients in the EGFR-wildtype group and 32 patients in the EGFR-mutant group (Table 1). After PSM, the baseline characteristics of the two groups were balanced. As detailed in Table 1, the proportion of pathological stage III patients was 37.5% (EGFR-wildtype group: 38.0% vs. EGFR-mutant group: 36.6%). The proportion of clinical III patients was 72.5% (EGFR-wildtype group: 72.0% vs. EGFR-mutant group: 73.3%). There were no significant differences between the two groups regarding age, gender, surgical approach, smoking history, pathological stage, family history of cancer, tumor location, CCI score, BMI, clinical stage, type of resection, adjuvant therapy, visceral pleural invasion, spread through air spaces, vascular invasion, nerve invasion, or tumor thrombosis.

Response to neoadjuvant therapy of EGFR-mutant and EGFR-wildtype groups

Among the 80 patients who underwent neoadjuvant therapy, 30 patients with EGFR-mutant, while 50 patients with EGFR-wildtype. The radiological and pathological responses of the different neoadjuvant treatment regimens (EGFR-mutant vs. EGFR-wildtype) are illustrated in Figure 2. The radiological response results (Table 2) showed that after PSM, 12 patients (40.0%) in the EGFR-mutant group achieved PR/CR, 25 patients (50.0%) in the EGFR-wildtype group achieved PR/CR, exhibiting no statistically significant difference (P=0.24). In terms of pathological response, there was no statistically significant difference between the EGFR-mutant and EGFR-wildtype groups (P=0.21). Additionally, the EGFR-wildtype group demonstrated a higher incidence rate of node (N)-stage downstaging compared to the EGFR-mutant group (64.0% vs. 36.7%, P=0.02). The EGFR-mutant group demonstrated a higher carcinoembryonic antigen (CEA) value of post-NCI (4.1% vs. 2.7%, P=0.04).

Figure 2 Efficacy of neoadjuvant therapy. (A) Radiologic response in different neoadjuvant therapy modalities. (B) Pathologic response in different neoadjuvant therapy modalities. CR, complete response; EGFR, epidermal growth factor receptor; MPR, major pathologic response; pCR, pathologic complete response; PR, partial response; SD, stable disease.

Postoperative outcomes of EGFR-mutant and EGFR-wildtype groups

We conducted a comparative analysis of surgical difficulty indicators and postoperative outcomes between patients receiving EGFR-mutant (n=30) and EGFR-wildtype (n=50). There were no significant differences between the two groups regarding operation time (EGFR-wildtype group: 143.50 minutes vs. EGFR-mutant group: 142.07 minutes, P=0.89) and intraoperative blood loss (median 10 vs. 10 mL, P=0.83). Postoperative complications, including persistent pulmonary leakage (>7 d), did not differ significantly between the groups (P>0.99). Additionally, no statistically significant differences were identified in length of postoperative hospital stay (4 vs. 4 d, P=0.17), ICU stay after surgery (2.0% vs. 0.0%, P>0.99) (Table 2).

Survival analysis between EGFR-mutant and EGFR-wildtype in the matched cohort

At the time of data cutoff (February 2025), the median follow-up time for the EGFR-wildtype group was 34.4 months, while the median follow-up time for the EGFR-mutant group was 36.2 months. The results indicated that there were no significant differences in 3-year OS and 3-year RFS between EGFR-mutant and EGFR-wildtype groups. The OS hazard ratio (HR) for the EGFR-mutant group was 0.86 [95% confidence interval (CI): 0.16–4.70, P=0.86], and the RFS HR was 0.88 (95% CI: 0.42–1.83, P=0.73) (Figure 3). Multivariate analysis showed that smoking history, pneumonectomy, and visceral pleural invasion had significantly higher OS risk. Pneumonectomy and longer postoperative hospital stay were risk factors for RFS (Table 3).

Figure 3 Overall survival for patients with EGFR-wildtype versus EGFR-mutant before (A) and after (C) PSM. Recurrence-free survival curves of the patients with EGFR-wildtype versus EGFR-mutant before (B) and after (D) PSM. EGFR, epidermal growth factor receptor; PSM, propensity score matching.

Recurrence patterns between EGFR-mutant and EGFR-wildtype groups

According to the recurrence pattern analysis in Figure 4, there were some differences in the distribution of recurrence sites between the EGFR-wildtype group and the EGFR-mutant group. In terms of LR, the rate of LR in the EGFR-mutant group was significantly higher than that in the EGFR-wildtype group (16.7% vs. 2.0%, P=0.049). There were no statistically significant differences in mediastinal LN recurrence (10.0% vs. 0.0%, P=0.10) and bronchial stump recurrence (6.7% vs. 2.0%, P=0.65). Regarding distant metastasis, no significant differences were observed in supraclavicular LN (3.3% vs. 6.0%, P>0.99), pleural metastasis (0.0% vs. 4.0%, P=0.71), liver metastasis (0.0% vs. 2.0%, P>0.99), brain metastasis (3.3% vs. 10.0%, P=0.51), lung metastasis (3.3% vs. 4.0%, P>0.99), and multiple organ metastasis (10.0% vs. 8.0%, P>0.99) between the EGFR-mutant group and the EGFR-wildtype group (Table 4).

Figure 4 Recurrence pattern between the EGFR-wildtype group and the EGFR-mutant group. (A) The recurrence rate of the EGFR-wildtype and EGFR-mutant group. (B,C) The tumor recurrence site of the EGFR-wildtype and EGFR-mutant groups. EGFR, epidermal growth factor receptor; LN, lymph node.

Subgroup analysis among EGFR-wildtype, EGFR-mutant with adjuvant TKI (+), and EGFR-mutant with adjuvant TKI (−)

We performed a subgroup analysis of LR among EGFR-wildtype, EGFR-mutant with adjuvant TKI (+), and EGFR-mutant with adjuvant TKI (−). The results demonstrated no significant differences in local recurrence rates among these three groups (Table S1). In addition, analysis of the three groups [EGFR-wildtype, EGFR-mutant with adjuvant TKI (+), and EGFR-mutant with adjuvant TKI (−)] revealed no significant differences in 3-year OS (P=0.39) or 3-year RFS (P=0.77) (Figure S1).

Subgroup analysis between EGFR-mutant and EGFR-wildtype in clinically stage II-III LUAD patients

Subgroup analysis of patients with clinical stage II–III revealed no significant differences between the two groups (EGFR-mutant vs. EGFR-wildtype) in 3-year OS (P=0.78), 3-year RFS (P=0.53) (Figure S2), and pathological response (P=0.23) (Table S2).

Discussion

This retrospective cohort study represents the first comprehensive comparison of survival outcomes and recurrence patterns between EGFR-mutant and EGFR-wildtype stage I–III LUAD patients undergoing NCI. Our findings demonstrate no significant differences in 3-year OS or RFS between the two groups, despite the EGFR-mutant cohort exhibiting a significantly higher rate of LR (16.7% vs. 2.0%, P=0.049). These results suggest that while long-term survival outcomes remain comparable, EGFR mutation status may influence post-treatment recurrence dynamics, warranting tailored surveillance and adjuvant strategies for genetically distinct subgroups.

The absence of survival disparities between EGFR-mutant and wildtype groups contrasts with prior studies highlighting the immunologically “cold” nature of EGFR-mutant tumors, characterized by low PD-L1 expression and reduced T-cell infiltration, which theoretically limits immunotherapy efficacy (11,16). However, our results align with emerging evidence suggesting that even modest immune activation in combination with chemotherapy may mitigate intrinsic resistance mechanisms in EGFR-mutant NSCLC (17). The comparable OS and RFS observed here may also reflect the synergistic effects of platinum-based chemotherapy, which could suppress residual micrometastases independent of EGFR status, or the potential benefits of subsequent adjuvant targeted therapies in mutation-positive patients (18). A previous study showed that constitutive EGFR activation downregulates major histocompatibility complex (MHC) class I expression and upregulates immunosuppressive cytokines [e.g., vascular endothelial growth factor (VEGF), transforming growth factor beta (TGF-β)], further impairing T-cell recognition and infiltration. Preclinical models suggest EGFR-TKIs can transiently enhance MHC-I expression, but this effect is insufficient to synergize with ICIs in neoadjuvant settings without optimized sequencing (19). The NEOTIDE/CTONG2104 trial reported a 75% MPR rate with neoadjuvant anti-PD-1 blockade plus chemotherapy, despite limited subgroup sample size. The mechanisms underlying deep pathological responses in locally advanced EGFR-mutant NSCLC remain unclear; they hypothesize that the chemotherapy regimen may be a key determinant of enhanced clinical efficacy (20). A previous multicenter retrospective study had also demonstrated the potential clinical feasibility of neoadjuvant immunotherapy in resectable localized oncogene-mutant NSCLC, particularly EGFR-mutant subtypes, highlighting its emerging role in molecularly defined cohorts (21). In the IMpower 010 trial (22), the subgroup analyses also indicated that in the stage II–IIIA population, the disease-specific survival (DFS) benefit of adjuvant atezolizumab was comparable among patients with EGFR-positive, EGFR-negative, and unknown EGFR status, with corresponding HRs of 0.99, 0.79, and 0.70, respectively. These results revealed unexpected survival benefits associated with perioperative ICIs in patients with resectable EGFR-mutant NSCLC. However, these findings must be interpreted cautiously given the limited sample size of EGFR-positive cases, and large-scale randomized controlled trials are required to validate the differential efficacy between ICIs and placebo in this molecular subgroup (12). The reduced N-stage downstaging in EGFR-mutant patients (36.7% vs. 64.0%, P=0.02) may reflect chemotherapy-resistant LN metastases. EGFR-mutant tumors often exhibit desmoplastic stromal changes post-NCI, complicating complete surgical resection and increasing residual micrometastasis risk (23). In addition, pCR and MPR rates were low in this study across the board. The possible reasons for these differences are as follows: this cohort had a significantly higher proportion of stage III patients (72.5% clinical stage III pre-PSM versus trials like CheckMate-816 (stage IB–IIIA) (10) and KEYNOTE-671 (stage II/IIIA/B) (24). Advanced stages (especially IIIB/IIIC) are associated with lower pathological response rates due to larger tumor burden and complex tumor microenvironments. This study exclusively enrolled LUAD patients—a population characterized by a high prevalence of driver mutations (e.g., EGFR) that typically confers an ‘immune-cold’ phenotype. Supporting our findings, the previous study (NEOTIDE/CTONG2104) demonstrated a 0% pCR rate and 44% MPR rate in EGFR-mutant patients receiving NCI, significantly lower than in driver-negative populations (20).

The higher LR rate in EGFR-mutant patients underscores the need for improved local control strategies. This phenomenon may stem from residual tumor cells resistant to NCI due to EGFR-driven survival pathways or incomplete surgical resection of desmoplastic or fibrotic lesions post-neoadjuvant therapy (25). Notably, the EGFR-wildtype group exhibited greater N-stage downstaging (64.0% vs. 36.7%, P=0.02), suggesting that NCI may more effectively debulk LN metastases in tumors lacking driver mutations. However, this differential response did not translate into survival advantages, possibly due to the efficacy of salvage therapies for recurrent disease or the limited sample size. Pathological response rates (MPR: 13.3% vs. 14.0%, P>0.99) were similarly low in both groups, consistent with prior reports of suboptimal pathological responses to EGFR-TKIs or immunotherapy in EGFR-mutant LUAD (9,20). These findings highlight the unmet need for novel neoadjuvant regimens, such as combining EGFR-TKIs with immunotherapy or dual checkpoint inhibition, to enhance tumor immunogenicity and pathological response in mutation-positive populations. As reported by Schoenfeld et al. (26), the incidence of interstitial lung disease (ILD) reached 13% when ICIs were sequentially administered prior to osimertinib, a toxicity profile that may offset survival benefits. However, preclinical evidence indicates that TKIs can reverse the immunosuppressive tumor microenvironment, while ICI-activated T cells may eliminate TKI-resistant clones (16). Notably, in patients with PD-L1 expression ≥50% or STK11 wild-type status, the response rate to combination therapy exceeded 70% (17), with the ILD risk remaining below 5% among younger patients with normal pulmonary function. In addition, our study observed higher LR in EGFR-mutant patients (16.7% vs. 2.0%, P=0.049) despite comparable OS/RFS. Historical underuse of adjuvant TKIs likely contributed to excess LR in EGFR-mutant patients. The LAURA trial demonstrated that adjuvant osimertinib reduces central nervous system (CNS) progression risk by 83% (HR =0.17) and systemic progression by 84% (HR =0.16) in stage III patients (27). EGFR-mutant tumors exhibit inherent radioresistance and immunosuppressive microenvironments (low PD-L1/CD8⁺ T cells), limiting NCI efficacy (28). Adjuvant osimertinib counteracts this by directly targeting residual micrometastases. All resected EGFR-mutant patients should receive adjuvant osimertinib unless contraindicated. This study analyzed the prognosis comparison of patients with EGFR mutations who received or did not receive adjuvant TKI after surgery. This study provided more clinical evidence for clinical practice.

Several limitations must be acknowledged. First, the retrospective design introduces inherent limitations, such as potential selection bias and incomplete data collection. Second, the small sample size (n=97) and short median follow-up (34–36 months) may underpower the detection of subtle survival differences or late recurrences. Third, heterogeneity in PD-1 inhibitor types and chemotherapy regimens could confound outcomes. The lack of molecular and immune biomarkers (e.g., PD-L1 expression, tumor mutational burden, CD8⁺ T-cell infiltration) limits mechanistic insights into EGFR mutation-immunotherapy interactions. Radiological and pathological assessments were constrained by RECIST v1.1’s limited predictive value for pathological responses, and residual tumor molecular profiling (e.g., resistant clonal evolution) was not dynamically monitored. Future studies should adopt prospective designs, incorporate multicenter collaborations, standardize treatment protocols, and integrate multi-omics dynamic monitoring [e.g., circulating tumor DNA (ctDNA), spatial transcriptomics] to address these limitations and refine EGFR subtype-specific therapeutic strategies. Fourth, this study exclusively analyzed patients who successfully underwent surgery after NCI, potentially introducing selection bias. We acknowledge the critical absence of data regarding EGFR-mutant versus wildtype patients who failed to complete NCI or became inoperable due to disease progression. A previous study suggested EGFR-mutant NSCLC may exhibit distinct biological behaviors under immunotherapy, including higher rates of hyperprogression (29). If such events disproportionately occurred in EGFR-mutant patients, their exclusion would artificially inflate the observed survival metrics for this subgroup. Future prospective trials must systematically capture outcomes across the entire treatment continuum—from NCI initiation to surgery—to validate our findings. Fifth, despite rigorous propensity score matching (PSM), residual clinical stage imbalance persisted between groups. After matching, the EGFR-mutant cohort exclusively comprised clinical stage IIB–IIIC patients (30/30, 100%), whereas the EGFR-wildtype group included clinical stage IB–IIA cases (6/50, 12%). This reason may be only one clinical stage IB EGFR-mutant patient existed pre-PSM, excluded during matching. Consequently, our comparison contrasts early-to-advanced (IB–IIIC) wildtype versus exclusively advanced (IIB–IIIC) mutant disease. Since advanced clinical stage intrinsically correlate with elevated recurrence risk, this imbalance may partially confound the observed LR disparity. Future studies should implement stage-stratified randomization or matched analyses focusing on stage-homogeneous cohorts.

Conclusions

In conclusion, EGFR mutation status may not independently predict survival outcomes after NCI, it could influence recurrence patterns, with EGFR-mutant patients requiring intensified locoregional surveillance. Future prospective trials should explore optimized neoadjuvant strategies, such as integrating EGFR-TKIs with immunotherapy or radiotherapy, to improve pathological responses and reduce recurrence risk in mutation-positive cohorts. Additionally, molecular profiling of residual tumors post-NCI may identify resistance mechanisms guiding personalized adjuvant therapies.

Acknowledgments

The authors thank the National Cancer Center, Cancer Hospital, Chinese Academy of Medical Sciences (CHCAMS) for providing the research environment.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-594/rc

Data Sharing Statement: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-594/dss

Peer Review File: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-594/prf

Funding: This work was supported by the CAMS Innovation Fund for Medical Sciences (CIFMS) (Nos. 2021-I2M-1-015, 2024-I2M-C&T-C-008 and 2024-I2M-ZH-005), National Natural Science Foundation of China (No. 82273129), and Central Health Research Key Projects (No. 2022ZD17).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-594/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Medical Ethics Committee of the Cancer Hospital, Chinese Academy of Medical Sciences (CHCAMS) (approval No. 22/492-3694) and individual consent for this retrospective analysis was waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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