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  Title	Neoadjuvant Aumolertinib for unresectable stage III EGFR -mutant non-small cell lung cancer: a single-arm phase II trial
  ID	8125030
  External ID	7672885880
  Author	Unknown
  Published Date	April 1, 2025, 7:32 p.m.
  Summary	Baseline characteristics Between December 2021 and June 2023, a total of 56 unresectable NSCLCm patients in stage III were enrolled in this trial (Fig. 1). Among them, 5 patients withdrew their infor
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  URL	https://www.nature.com/articles/s41467-025-58435-9
  Sentiment	Negative: 0.17302    Neutral: 0.79657    Positive: 0.03041
  Relevance	0.00465

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  Content ID	5430276
  Key	1e87126f-e897-45a0-bcce-2a6f608d8f89
  Content	Baseline characteristics Between December 2021 and June 2023, a total of 56 unresectable NSCLCm patients in stage III were enrolled in this trial (Fig. 1). Among them, 5 patients withdrew their informed consents, leaving 51 participants who received neoadjuvant Aumolertinib treatment as the intention-to-treat (ITT) population, as detailed in Table 1. The average diagnostic age was 62.6 years (range, 40–76 years), with a majority of participants being female (28/51, 54.9%), never-smokers (35/51, 68.6%), and having an ECOG performance status of 0 (30/51, 58.8%). Within the ITT population, 22 participants (43.1%) had the Ex19-Del mutation, while 27 (52.9%) had the Ex21-L858R mutation. There were 2 participants harboring uncommon EGFR mutations (Supplementary Table 1). Most participants were categorized as having stage N2 disease (25/51, 49.0%). The distribution of disease stages included 24 participants (47.1%) with stage IIIA, 22 (43.1%) with stage IIIB, and 5 (9.8%) with stage IIIC. The mean maximum target-lesions dimension (TLD) on CT was 50.0 mm (range, 17–113 mm) and the mean maximum standardized uptake value (SUVmax) for glucose metabolism of the primary tumor on PET-CT was 11.7 (range, 3.5–26.8). Fig. 1 The clinical trial (LungMate 007) design. Full size image Table 1 Baseline characteristics of neoadjuvant Aumolertinib treated patients (n = 51) Full size table Efficacy The efficacy of neoadjuvant Aumolertinib treatment was demonstrated in Table 2. After a median of 4 cycles (range, 2–6 cycles) of neoadjuvant treatment, ORR, the primary endpoint, was 70.6% (95% CI: 58–84%). The disease control rate (DCR) was 100%. The waterfall plots illustrating the responses were shown in Fig. 2a. Table 2 Evaluation of efficacy of neoadjuvant Aumolertinib (n = 51) Full size table Fig. 2: Radiological and pathological outcomes of participants. a Waterfall plots of radiological regression of all participants’ TLD after neoadjuvant Aumolertinib treatment. b Waterfall plots of surgical treated pathological regression. TLD target-lesions dimension, SD stable disease, PR partial response, MPR major pathological response, pCR complete pathological response. Source data are provided as a Source Data file. Full size image For the secondary endpoints, 23 participants proceeded from neoadjuvant treatment to radical surgery, resulting in a surgical conversion rate of 45.1% (23/51). All participants who underwent surgery achieved complete (R0) resection. The major pathological response (MPR) was assessed in these cases (Fig. 2b). Among five participants who achieved MPR (MPR rate: 21.7%, 95% CI: 4–40%), three participants achieved pathologic complete response (pCR) (pCR rate: 13.0%, 95% CI: 2–28%). Additionally, the mean percentage of residual tumor cells in the primary tumor was 45.9% (range, 0% to 100%). The average duration of postoperative hospital stay was 5.6 days (range, 4 to 14 days). During surgery, the mean operation time was 116.1 min (range, 60 to 242 min), with mean blood loss of 96.5 mL (range, 20 to 1000 mL). All 23 participants who underwent surgery received adjuvant treatment postoperatively, including EGFR-TKI monotherapy (n = 20), platinum-based chemotherapy (n = 2), and combination of EGFR-TKI and chemotherapy (n = 1). There were 19 (82.6%) patients received adjuvant target-therapy long-term or until the disease progresses. Sub-group analyses for mutation subtypes The baseline characteristics between participants with Ex19-Del and Ex21-L858R mutations were demonstrated in Table 1. Participants harboring Ex19-Del had a significantly higher N-stage compared to those who with Ex21-L858R mutation (N3: 45.4% vs 18.5%, p = 0.037). In addition, no significant differences were observed in demographic, radiologic, and oncologic characteristics between the two sub-groups. As shown in Table 2, there was no difference in the number of neoadjuvant treatment cycles between Ex19-Del and Ex21-L858R participants (median treatment cycle: 4 cycles vs 4 cycles, p = 0.397). The conversion rate of radical surgery was not significantly different between the Ex19-Del group (9/22, 40.9%) and the Ex21-L858R group (14/27, 51.9%). Among those who underwent surgery, participants with Ex19-Del had a significantly higher MPR rate compared to those with Ex21-L858R (44.4% vs 7.1%, p = 0.034), and the proportion of residual tumor cell was significantly lower in the Ex19-Del group (19.8% vs 63.5%, p = 0.015). Based on imaging analysis, significant reductions were observed after neoadjuvant treatment in both Ex19-Del and Ex21-L858R participants. The reductions were noted in target-lesions dimension (TLD) on CT, and primary tumor SUVmax (PT-S) on PET-CT (Fig. 3a, c). Notably, compared with Ex21-L858R participants, those with Ex19-Del exhibited significantly deeper reductions in TLD (TLD: 45.8% vs 31.2%, p = 0.003; Cohen’s d effect size: 1.31 vs 0.76) after neoadjuvant Aumolertinib treatment (Fig. 3b). Fig. 3: Imaging omics for the changing of participants on CT and PET/CT between 2 common mutant subtypes. The trend of radiological changes in (a) TLD via CT (Ex19-Del, n = 22; Ex21-L858R, n = 27), (c) PT-S via PET-CT (Ex19-Del, n = 7; Ex21-L858R, n = 15) in paired participants pre- and post-treatment between 2 common mutant subtypes. The degree of radiological changes in (b) TLD via CT (Ex19-Del, n = 22; Ex21-L858R, n = 27), (d) PT-S via PET-CT (Ex19-Del, n = 7; Ex21-L858R, n = 15) in participants pre- and post-treatment between 2 common mutant subtypes. Centers, boxes, whiskers, and dots indicate medians, quantiles, minima/maxima, and outliers, respectively. For difference comparisons in matched samples (a and c), two-sided paired Wilcoxon test was used. For difference comparisons in two independent samples (b and d), two-sided unpaired Wilcoxon test was used. TLD: target-lesions dimension; PT-S: primary tumor SUVmax. Source data are provided as a Source Data file. Full size image Safety Treatment-related adverse events (TRAEs) are listed in Table 3. Forty-nine participants (96.1%) experienced TRAEs, but no grade 5 TRAEs observed. The most common TRAE of any grade was fatigue, which occurred in 25 (49.0%) of 51 participants. Increases in alanine aminotransferase concentration (ALT) (20, 39.2%), rash (18, 35.3%), hyponatremia (14, 27.5%), acrodynia (12, 23.5%), stomatitis (11, 21.6%), and thrombocytopenia (11, 21.6%) were also common treatment-related adverse events. Grade 3/4 TRAEs occurred in 5 patients (9.8%), with cases of ALT concentration elevation, aspartate aminotransferase (AST) concentration elevation, pneumonia, thromboembolic event, and ischemia cerebrovascular disease. Discontinuation of Aumolertinib was necessary for two participants due to increased ALT concentration and rash, respectively. Table 3 Adverse events in neoadjuvant therapy and surgery Full size table Surgery-related complications were minimal, with one participant experiencing a bronchopleural fistula postoperatively (1/23, 4.3%). No surgery-related death occurred within 90 days postoperatively. Survival analysis As of the cut-off date of January 1st 2025, the median follow-up duration for all participants was 24.0 months (interquartile range (IQR), 22.0–26.0 months). The median EFS and OS were not reached. The one and two-year EFS rate were 88.2% and 58.8% respectively. Besides, the one and two-year OS rate were 98.0% and 90.2% respectively. Female patients (p = 0.002), never smokers (p = 0.004), and surgical treated patients (p = 0.039) had significantly better EFS. No significant difference in EFS was observed between the participants harboring Ex19-Del and Ex21-L858R (p = 0.702). While, EFS of sensitive mutations demonstrated significantly superior than participants with uncommon mutant-subtypes (Ex18-G719X and Ex20-S768I) (p < 0.001 for both) (Supplementary Fig. 1). As the last follow-up, 22 participants experienced events (Supplementary Fig. 2). Of these, seven underwent radical surgery, with three developing central nervous system (CNS) metastasis postoperatively (42.9%). The remaining 15 participants who experienced events did not receive surgery. Among these, primary tumor progression occurred in 14 participants (93.3%) and CNS metastasis in one participant (6.7%). Additionally, TRAEs led to treatment regimen adjustments in two non-surgery participants. Exploratory analysis To explore the molecular characteristics of the tumor microenvironment (TME) during Aumolertinib therapy, we performed bulk RNA-sequencing (RNA-seq) on the primary tumor specimens collected at both baseline and post-treatment phases. After quality control, 23 samples from 23 participants were deemed suitable for downstream analyses (Fig. 4a). Fig. 4: The changes of transcriptomic features and immune cell infiltration between pre-treatment and post-treatment tumor samples, and between Ex19-Del and Ex21-L858R tumor samples. a Clinical information related to all Aumolertinib cohort samples. b Differential gene expression between pre-treatment and post-treatment group in response samples, with immune-related genes marked in green. c GSEA results for upregulated pathways in the post-treatment response group. d Heatmap of MCPcounter scores, CIBERSORT scores, cytotoxicity, and HLA molecule expression for all samples (* indicates statistical significance between the pre-treatment group and the post-treatment group within response samples). e Alterations in TME classifications across the pre-treatment non-response, post-treatment non-response, pre-treatment response, and post-treatment response groups. f Variations in PD-1 and PD-L1 expression levels between the pre-treatment group and post-treatment group within response samples. Statistical comparisons were performed using one-sided Wilcoxon tests (left: p = 0.01; right: p = 0.30). g Variations in CCL2 and IL10 expression levels between the pre-treatment group and post-treatment group within response samples. Statistical comparisons were performed using one-sided Wilcoxon tests (left: p = 0.43; right: p = 0.33). h Variations in immune infiltration profiles between the Ex19-Del group and the Ex21-L858R group in the OncoSG Cohort. (two-sided Wilcoxon tests: T cell, p = 0.30; CD8 + T cell, p = 0.60; B cell, p = 0.12; NK cell, p = 0.72; macrophage/monocyte, p = 0.40; myeloid dendritic cell, p = 0.74). i Differential gene expression between the Ex21-L858R group and the Ex19-Del group in post-treatment response samples, with distinct gene categories highlighted in various colors. j GSEA outcomes for the Ex21-L858R group and the Ex19-Del group in post-treatment response samples. k Immune infiltration differences between the Ex19-Del group and the Ex21-L858R group within the post-treatment response samples (values represent relative changes calculated by subtracting each group’s pre-treatment mean from their post-treatment response values) (one-sided Wilcoxon tests: T cell, p = 0.07; CD8 + T cell, p = 0.01; B cells, p = 0.14; NK cell, p = 0.14; macrophage/monocyte, p = 0.005; myeloid dendritic cell, p = 0.03). l Heatmap of PROGENy scores and GSVA scores for DNA repair-related pathways across all samples (* indicates statistical significance between the Ex19-Del group and the Ex21-L858R group within the post-treatment response samples). Centers, boxes, whiskers, and dots indicate medians, quantiles, minima/maxima, and outliers, respectively. NS: p ≥ 0.05; *: 0.01 ≤ p < 0.05; **: 0.001 ≤ p < 0.01; BER: Base Excision Repair; NER: Nucleotide Excision Repair; MMR: Mismatch Repair; HDR: Homology-dependent recombination; NHEJ: Non-homologous End Joining; DR: Direct Repair; TLS: Translesion Synthesis; NP: Nucleotide pools. Source data are provided as a Source Data file. Full size image TME remodeling after Aumolertinib treatment in responders In this trial, TME in non-responders did not show significant changes between baseline and post-treatment phases (Supplementary Fig. 3b, e, f). Consequently, our focus shifted to the dynamics of the TME in responders. Compared to baseline, immune-related genes (such as IL2, LAT, and KLRK1) that are involved in regulating the proliferation and activation of T-cells and NK-cells18,19,20, were significantly upregulated in post-treatment tumors (Fig. 4b). Gene Set Enrichment Analysis (GSEA) revealed significant enrichment in pathways related to NK cells, lymphocytes, leukocytes, and adaptive immune response in responders after therapy, suggesting potential immune activation due to Aumolertinib treatment (Fig. 4c, Supplementary Fig. 3a). Incidentally, pathways related to “Cell Junction Organization” and “Regulation of Cell Substrate Adhesion” were also found to be downregulated in post-treatment samples (Supplementary Fig. 3b). Immune deconvolution analysis using MCPcounter and CIBERSORT algorithm21,22 also identified an increased infiltration of CD8 + T cells, NK cells, and myeloid dendritic cells following Aumolertinib treatment (Fig. 4d). These findings were partially corroborated by quanTIseq23 and TIMER24 analyses (Supplementary Fig. 3c). Furthermore, we observed dynamic changes in cytotoxic molecules and HLA during treatment (Fig. 4d). Notably, the post-treatment elevation in cytotoxic molecules and HLA suggested a robust activation of cellular immunity, with a pronounced effect on CD8 + T cells. Although this increase was not statistically significant in non-responsive samples, a similar increasing trend was noted (Supplementary Fig. 3d). Spearman correlation analysis also showed a high correlation among CD8 + T cells, NK cells, and myeloid dendritic cells in post-treatment responsive samples (Supplementary Fig. 3e). To further delineate the immune ecosystem of post-treatment tumors in responders, we employed the four conserved TME subtypes (depleted, fibrotic, immune-enriched-nonfibrotic, and immune-enriched-fibrotic) proposed by previous studies25 in our cohort (Supplementary Fig. 3f). These results indicated that the immune-enriched-nonfibrotic subtype, theoretically most favorable for immunotherapy, was absent at baseline but emerged after therapy (Fig. 4e). Notably, PD-1 expression was significantly upregulated in tumors after neoadjuvant Aumolertinib treatment compared to baseline, with an increasing trend in PD-L1 expression (Fig. 4f). In non-response samples, similar trends for PD-1 and PD-L1 were not evident (Supplementary Fig. 3g). Additionally, although continuous TKI administration is associated with elevated levels of CCL2 and IL10, which was reported to suppress anti-tumor immunity26,27, similar results were also observed with an increased trend in either the response or non-response groups following neoadjuvant Aumolertinib treatment (Fig. 4g, Supplementary Fig. 3h). The dynamic differences between Ex19-Del and Ex21-L858R mutations The participants harboring Ex19-Del mutation had significantly higher responsive rates compared to those with Ex21-L858R mutation (91% vs 59%, p = 0.006) after neoadjuvant Aumolertinib treatment (Fig. 2a). This finding prompted an investigation into the differences in the TME between tumors that harbored Ex19-Del mutation and Ex21-L858R mutation. In treatment-naïve tumors (OncoSG cohort)28, there were no significant differences in immune infiltrations between Ex19-Del and Ex21-L858R tumors (Fig. 4h). However, for post-treatment samples, tumors with Ex19-Del mutation exhibited higher expression of immune-related genes compared to those with Ex21-L858R mutation (Fig. 4i). Conversely, cell cycle-related genes (FBXO43, E2F7 and SOX2)29,30,31,32 were up-regulated in tumors with Ex21-L858R mutation (Fig. 4i). Consistent with these observations, GSEA analysis indicated that pathways related to “antigen presentation, cytotoxicity, and tumor necrosis factor production” were significantly upregulated in Ex19-Del samples after neoadjuvant Aumolertinib treatment. In contrast, Ex21-L858R samples after neoadjuvant Aumolertinib treatment showed upregulation in pathways related to “cell cycle transition, DNA replication, and cytoskeletal reconstruction” (Fig. 4j). Immune infiltration analysis revealed that post-treatment Ex19-Del samples exhibited significantly higher immune cell infiltration compared to Ex21-L858R samples, particularly in CD8 + T-cells, myeloid dendritic cells, and macrophages/monocytes (Fig. 4k). Moreover, the marker for alveolar macrophages, PPARG, was also upregulated (Supplementary Fig. 3i). Alveolar macrophages generally function in the cleanup and tissue repair process when there is extensive tumor cell necrosis33. Previous research reports that MAPK pathway activation is correlated with Osimertinib resistance34. Consistently, PROGNEy analysis showed a significant decrease in the MAPK pathway in Ex19-Del samples but not in Ex21-L858R samples after neoadjuvant Aumolertinib treatment (Fig. 4l). It is reported that the efficacy of immunotherapy was positively associated with defective DNA mismatch repair (dMMR)35. The dMMR was notably occurred in Ex19-Del samples, as well as other DNA repair mechanisms, including Nucleotide Excision Repair23, Homology-dependent Recombination (HDR), and Non-homologous End Joining (NHEJ), which were potentially associated with the better responsive rate in Ex19-Del subgroup (Fig. 4l).
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  Publisher Name	Nature
  Publisher URL	https://www.nature.com/
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  Trust Flow Score	61
  Citation Flow Score	58

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  Data Source Name	Quantexa News
  Data Source Type	news
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