P1.01-38 Clinical Significance According to EGFR Mutation Subtypes in Lung Adenocarcinoma: Korean Multicenter Experience

Clinical activity of afatinib in patients with advanced non-small-cell lung cancer harbouring uncommon EGFR mutations: a combined post-hoc analysis of LUX-Lung 2, LUX-Lung 3, and LUX-Lung 6

The histologic heterogeneity of lung adenocarcinoma is well known. Many histologic subtypes have been described, and recently their prognostic and predictive value has emerged. Laser capture microdissection may aid in the isolation of cancer cells from distinct subtypes of lung adenocarcinoma, thus enabling the description of their specific molecular features. Characterization of epidermal growth factor receptor (EGFR) mutations in histologic subtypes of lung adenocarcinoma has become an important issue. The purpose of this study was to analyze EGFR mutations in exons 18-21 in single histologic subtypes of lung adenocarcinoma after laser capture microdissection. A revision and reclassification of a series of 208 non-small cell lung cancers was conducted, and 62 adenocarcinomas with a total of 119 histologic component subtypes were identified. Laser capture microdissection of each subtype was performed. EGFR mutations in exons 18-21 were detected using polymerase chain reaction single-strand conformation polymorphism and direct DNA sequencing. EGFR mutations were detected only in 3 out of the 62 adenocarcinomas analyzed. Two adenocarcinomas harbored EGFR mutations in exon 19 (the E746-T751 deletion VA insertion and the LREAT deletion) and one adenocarcinoma the EGFR exon 21 L858R missense point mutation. EGFR mutations were observed in all component subtypes. This suggests that, in a patient with lung adenocarcinoma, EGFR mutations are not associated with particular component histologic subtypes and probably occur at an early stage of tumorigenesis. Notably, 2 out of the 3 mutated adenocarcinomas had a bronchioloalveolar component, whereas the third mutated adenocarcinoma had a papillary subtype. Although we detected EGFR mutations only in 3 out of 62 adenocarcinomas and EGFR mutations were present in every subtype of each mutated adenocarcinoma, our research might represent a basis for further studies in characterizing molecular profiles of different component subtypes of lung adenocarcinoma.

Purpose: Up to 50% of Asian patients with NSCLC have EGFR gene mutations, indicating that selecting eligible patients for EGFR-TKIs treatments is clinically important. The aim of the study is to develop and validate radiomics-based nomograms, integrating radiomics, CT features and clinical characteristics, to non-invasively predict EGFR mutation status and subtypes.Materials and Methods: We included 637 patients with lung adenocarcinomas, who performed the EGFR mutations analysis in the current study. The whole dataset was randomly split into a training dataset (n = 322) and validation dataset (n = 315). A sub-dataset of EGFR-mutant lesions (EGFR mutation in exon 19 and in exon 21) was used to explore the capability of radiomic features for predicting EGFR mutation subtypes. Four hundred seventy-five radiomic features were extracted and a radiomics sore (R-score) was constructed by using the least absolute shrinkage and selection operator (LASSO) regression in the training dataset. A radiomics-based nomogram, incorporating clinical characteristics, CT features and R-score was developed in the training dataset and evaluated in the validation dataset.Results: The constructed R-scores achieved promising performance on predicting EGFR mutation status and subtypes, with AUCs of 0.694 and 0.708 in two validation datasets, respectively. Moreover, the constructed radiomics-based nomograms excelled the R-scores, clinical, CT features alone in terms of predicting EGFR mutation status and subtypes, with AUCs of 0.734 and 0.757 in two validation datasets, respectively.Conclusions: Radiomics-based nomogram, incorporating clinical characteristics, CT features and radiomic features, can non-invasively and efficiently predict the EGFR mutation status and thus potentially fulfill the ultimate purpose of precision medicine. The methodology is a possible promising strategy to predict EGFR mutation subtypes, providing the support of clinical treatment scenario.

P2.13 Topic: Advanced NSCLC Frequency of Uncommon EGFR Mutations in CR

Background: EGFR-directed therapy marked the beginning of personalized medicine in lung adenocarcinoma (LUAD), where a single gene could be effectively targeted by a specific class of drugs, leading to remarkable treatment responses. After additional targets have been identified, the search for other druggable mutations has slowed despite the need to improve clinical outcomes, underscoring the need for new approaches. Hypothesis: We hypothesize that gene expression signatures will predict EGFR mutation status in patients and identify cases with similar signaling pathways but without canonical EGFR mutations. Deciphering the role of the EGFR signature in mutant (mt) and wild-type (WT) cases may provide potential therapeutic and classification strategies for understanding LUAD. Experimental design: To define an EGFR mutation signature (“mSig”) as a predictor of EGFR mutation status, we analyzed gene expression and clinical data from four lung adenocarcinoma cohorts. Microarray data from Memorial Sloan Kettering Cancer Center (MSKCC, n=192) served as the training set. For validation, we used combined microarray data from UNC (n=73) and TSP (n=41) as one dataset, and RNA-seq data from The Cancer Genome Atlas (TCGA, n=486) as another. Multiple model evaluation algorithms tested the performance of the predictor. Other key genetic mutations found in TCGA cohort were included in integrative analysis. Results: Comparing EGFR-mt to EGFR WT tumors identified 1, 020 differentially expressed genes in the training dataset as an EGFR mSig. Semi-supervised clustering visualized molecular profiles in both training and validation data. The EGFR mSig achieved an average negative predictive value (NPV) of 96.3% across datasets and was robust across multiple dataset combinations and six machine learning models (AUROC = 0.83-0.95). The EGFR mSig strongly correlated with LUAD subtypes (Bronchioid, Magnoid, Squamoid), particularly with Bronchioid [odds ratio (OR) = 9.2, p < 0.001]. EGFR mSig-positive EGFR-mt (“EGFR-mt/mSig(+)”) tumors were primarily Bronchioid (OR = 4.5, p < 0.001). Almost 50% of mSig(+) Bronchioid tumors in fact lacked EGFR mutations, often showing EGFR amplifications or RAS mutations. Two lung lineage markers and driver mutations associated with LUAD subtypes and EGFR activation patterns. Interestingly, EGFR-mt/mSig(-) tumors were generally non-Bronchioid, suggesting alternative pathways (e.g., RAS, TP53). RAS/RAF/RTK-mt tumors (EGFR WT or mSig(-)) showed high dual specificity phosphatase 4 (DUSP4) expression, a known repressor of multiple key activated RAS genes. Therefore, DUSP4 represents an attractive novel target in selected LUAD samples. Conclusions: Our results define a novel EGFR mSig that identifies EGFR-mt-like tumors. Identifying patients with driver gene mutations lacking EGFR mutations suggests a new approach of identifying new druggable targets. Citation Format: Minjeong Kim, Wisut Lamlertthon, Heejoon Jo, Yan Cui, Hyo Young Choi, Matthew D. Wilkerson, Liza Makowski, D. Neil Hayes. Lineage markers and driver oncogenes coordinate through gene expression subtypes of lung adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6595.

Mutations in exons 18–21 of the epidermal growth factor receptor gene (EGFR) can confer sensitivity to EGFR-tyrosine kinase inhibitors (EGFR-TKIs) in patients with non-small-cell lung cancer (NSCLC). Deletions in exon 19 or the exon 21 L858R substitution comprise approximately 85% of mutations, but comparatively few data are available on the remaining “uncommon” mutations. We conducted a systematic literature review to identify evidence on uncommon EGFR mutations in locally advanced/metastatic NSCLC (PROSPERO registration number: CRD42019126583). Electronic screening and congress searches identified studies published in 2012–2020 including patients with locally advanced/metastatic NSCLC and uncommon EGFR mutations (excluding T790M). We assessed the prevalence of uncommon mutations (in studies using direct sequencing of exons 18–21), and compared response to treatment and progression-free survival (PFS) in patients with common versus uncommon mutations and in those with exon 20 mutations versus other uncommon mutations. We identified 64 relevant studies. Uncommon mutations constituted 1.0–18.2% of all EGFR mutations, across 10 studies. The most frequently reported uncommon mutations were G719X (0.9–4.8% of all EGFR mutations), exon 20 insertions (Ex20ins; 0.8–4.2%), L861X (0.5–3.5%), and S768I (0.5–2.5%). Patients with common mutations typically experienced better treatment response and longer PFS on EGFR-TKIs than patients with uncommon mutations; Ex20ins mutations were associated with less favourable outcomes than other uncommon mutations. This review shows that uncommon mutations may comprise a clinically significant proportion of the EGFR mutations occurring in NSCLC, and highlights disparities in EGFR-TKI sensitivity between different uncommon mutations.

1231P - Efficacy of first-generation EGFR-TKIs on patients with NSCLC harboring EGFR uncommon mutations: a pooled analysis

Purpose: The aims of this study were to combine CT images with Ki-67 expression to distinguish various subtypes of lung adenocarcinoma and to pre-operatively predict the Ki-67 expression level based on CT radiomic features.Methods: Data from 215 patients with 237 pathologically proven lung adenocarcinoma lesions who underwent CT and immunohistochemical Ki-67 from January 2019 to April 2021 were retrospectively analyzed. The receiver operating curve (ROC) identified the Ki-67 cut-off value for differentiating subtypes of lung adenocarcinoma. A chi-square test or t-test analyzed the differences in the CT images between the negative expression group (n = 132) and the positive expression group (n = 105), and then the risk factors affecting the expression level of Ki-67 were evaluated. Patients were randomly divided into a training dataset (n = 165) and a validation dataset (n = 72) in a ratio of 7:3. A total of 1,316 quantitative radiomic features were extracted from the Analysis Kinetics (A.K.) software. Radiomic feature selection and radiomic classifier were generated through a least absolute shrinkage and selection operator (LASSO) regression and logistic regression analysis model. The predictive capacity of the radiomic classifiers for the Ki-67 levels was investigated through the ROC curves in the training and testing groups.Results: The cut-off value of the Ki-67 to distinguish subtypes of lung adenocarcinoma was 5%. A comparison of clinical data and imaging features between the two groups showed that histopathological subtypes and air bronchograms could be used as risk factors to evaluate the expression of Ki-67 in lung adenocarcinoma (p = 0.005, p = 0.045, respectively). Through radiomic feature selection, eight top-class features constructed the radiomic model to pre-operatively predict the expression of Ki-67, and the area under the ROC curves of the training group and the testing group were 0.871 and 0.8, respectively.Conclusion: Ki-67 expression level with a cut-off value of 5% could be used to differentiate non-invasive lung adenocarcinomas from invasive lung adenocarcinomas. It is feasible and reliable to pre-operatively predict the expression level of Ki-67 in lung adenocarcinomas based on CT radiomic features, as a non-invasive biomarker to predict the degree of malignant invasion of lung adenocarcinoma, and to evaluate the prognosis of the tumor.

BackgroundThe prognostic impact of EGFR mutation as major targetable somatic gene variant on lung adenocarcinoma is controversial. KRAS is another major somatic variant in lung adenocarcinoma, and a therapeutic agent for KRAS G12C became available in clinical settings. These mutations represent clinicopathological features of lung adenocarcinoma and can guide the treatment choice after recurrence. We evaluated the prognostic impact of EGFR and KRAS mutations by considering other clinicopathological recurrence risks in resected pTis-3N0M0 lung adenocarcinoma.MethodsClinicopathological features related to recurrence and genetic status were estimated in consecutive 877 resected cases. Recurrence-free survival (RFS), cumulative recurrence rate (CRR), and overall survival (OS) were compared. Uni- and multivariate analyses for RFS were performed after excluding cases with little or no recurrence risks.ResultsEGFR mutation was more likely to be harbored in female, never-smoker, or patients accompanied by > 5% lepidic component. KRAS mutation was more likely to be harbored in patients with current/ex-smoking history, International Association for the Study of Lung Cancer (IASLC) grade 3, or accompanied lymphatic or vascular invasion. In IASLC grade 2 and 3 patients, EGFR or KRAS mutation cases had significantly worse 5-year RFS than wild type patients (76.9% vs. 85.0%, hazard ratio [HR] = 1.55, 95% confidence interval [CI] = 1.62–6.41, P < 0.001). EGFR or KRAS mutation cases had significantly higher 5-year CRR than wild type patients (17.7% vs. 9.8%, HR = 1.69, 95% CI = 1.44–6.59, P = 0.0038). KRAS mutation cases had higher 5-year CRR than EGFR mutation cases (16.7% vs. 21.4%, HR = 1.62, 95% CI = 0.96–7.19, P = 0.061). There was no significant difference in OS between cohorts. Multivariate analysis revealed that a positive EGFR/KRAS mutation status was risk factor for worse RFS (HR = 2.007, 95% CI = 1.265–3.183, P = 0.003).ConclusionPositive EGFR and KRAS mutation statuses were risk factors for recurrence in resected IASLC grade 2 and 3 patients. KRAS mutations were more likely to be confirmed in cases with an increased risk of recurrence. EGFR and KRAS mutation statuses should be evaluated simultaneously when assessing the risk of recurrence.

EGFR mutations are key oncogenic drivers in lung adenocarcinoma (LUAD), predominantly affecting Asian, nonsmoking, and female populations. Although common mutations, such as exon 19 deletions and L858R, respond well to tyrosine kinase inhibitors (TKIs), uncommon EGFR mutations and compound variants exhibit variable treatment responses. This study aims to compare clinical characteristics and molecular profiles ofpatients with common, uncommon, and compound EGFR mutations, assessing their implications for therapy outcomes. We analyzed a multi-cohort genomic dataset of 19,163 patients with LUAD (5,212 with EGFR mutations), categorizing mutations into common, uncommon, and compound classes. Patient demographics, mutational signatures, and tumor microenvironment factors were assessed, with particular attention to smoking status and concomitant alterations in KRAS and TP53. Treatment outcomes were analyzed by time under treatment as a surrogate measure of TKI efficacy. Uncommon EGFR mutations, comprising 8.9% of EGFR-altered cases, were significantly more frequent among smokers and associated with tobacco-related mutational signatures. Compared with common EGFR-mutant cases, tumors harboring uncommon EGFR mutations reported higher rates of EGFR amplifications, KRAS, and TP53 mutations. Uncommon mutations also exhibited higher tumor mutational burden and distinct transcriptional profiles linked to cell cycle activity. Median time on treatment with TKIs was notably shorter in patients with uncommon mutations (4.1 mo) than those with common and compound mutations (10.9 mo and 12.4 mo, respectively). This study underscores the clinical and molecular heterogeneity of EGFR mutation classes in LUAD, highlighting the unique profile of uncommon mutations, particularly their association with smoking and co-mutations in KRAS and TP53. Comprehensive molecular testing, including next-generation sequencing, is crucial to identify these uncommon mutations and inform therapeutic decisions. Further investigation into the role of immunotherapy in patients with uncommon EGFR mutations is warranted given the tobacco-related molecular signatures and high tumor mutational burden associated with this subgroup.

EGFR L858R mutation is associated with lung adenocarcinoma patients with dominant ground-glass opacity.

1552 Background: The frequencies of known driver mutation in lung adenocarcinoma from patients in the United States have been reported by the NCI’s Lung Cancer Mutation Consortium (LCMC), indicating driver mutations were detected in 54% (280/516) of tumors. In this report, mutations found: EGFR 17%, KRAS 22%, HER2 0.6%, PIK3CA 1.2%, BRAF 2%, MET amplification 0.6%, MAP2K1 0.4%, NRAS 0.4%, AKT 0%, ALK rearrangements 7%. However little is known about ethnic difference of driver mutation frequencies and correlations between driver mutations and histological subtypes in lung adenocarcinoma. Methods: Known driver mutations in tumors from 97 Japanese patients with lung adenocarcinoma who underwent surgical resection between 1999 and 2003 in National Cancer Center Hospital East were analyzed by next-generation sequencing and confirmed by Sanger sequencing. Correlations between driver mutations and histological subtypes were also assessed. Results: Driver mutations were detected in 72% of tumors. Mutations found: EGFR 57%, KRAS9%, HER2 2%, PIK3CA 2%, BRAF 1%, MET amplification 1%, MAP2K1 0%, NRAS 0%, AKT 0%. Due to the limitation of rearrangement detection by exon-sequencing, ALK rearrangements were not analyzed. Compared with the report by LCMC, the frequency of EGFR mutations was high and that of KRAS mutations was low in the present study. All mutations were mutually exclusive. The number of predominant histological subtypes of tumors harbored EGFR mutations were papillary 28, acinar 3, solid 5, lepidic 19. That with KRAS mutations showed papillary 2, acinar 2, solid 2, lepidic 3, and HER2 mutations showed papillary 1 and acinar 1. Two tumors harbored PIK3CA mutations showed both histological acinar pattern. Each of BRAF mutation and MET amplification showed lepidic and papillary pattern, respectively. Conclusions: It was suggested that there should be ethnic difference of driver mutation frequencies in lung adenocarcinoma between Asian and non-Asian patients, although the details of ethnic distribution included in LCMC study has not been opened. In addition, each driver mutations did not correspond to specific histological subtypes of lung adenocarcinoma.

BackgroundSerum carcinoembryonic antigen (CEA) is usually elevated in lung adenocarcinoma patients, but not in all patients. Lung adenocarcinoma subtypes have been defined by the new International Association for the Study...

SummaryLung cancer is an extremely heterogeneous disease, and its treatment remains one of the most challenging tasks in medicine. Few existing laboratory lung cancer models can faithfully recapitulate the diversity of the disease and predict therapy response. Here, we establish 12 patient-derived organoids from the most common lung cancer subtype, lung adenocarcinoma (LADC). Extensive gene and histopathology profiling show that the tumor organoids retain the histological architectures, genomic landscapes, and gene expression profiles of their parental tumors. Patient-derived lung cancer organoids are amenable for biomarker identification and high-throughput drug screening in vitro. This study should enable the generation of patient-derived lung cancer organoid lines, which can be used to further the understanding of lung cancer pathophysiology and to assess drug response in personalized medicine.

EGFR Autophosphorylation but Not Protein Score Correlates With Histologic and Molecular Subtypes in Lung Adenocarcinoma