Abstract 5935: Phenotype profiling of tumor microenvironment in EGFR mutant lung adenocarcinoma with multi-omics data

Background: The relationship between ABO blood and EGFR mutations in lung adenocarcinoma is still unclear. The purpose of this study was to evaluate the association between ABO blood and EGFR mutations percentage in patients with lung adenocarcinoma. Subject and method: A cross-sectional descriptive study, 276 lung adenocarcinoma patients were tested for EGFR mutations and ABO blood from January 2021 to March 2023. The relationship between the ratio of EGFR mutations with ABO blood and clinical, paraclinical characteristics was analyzed univariate and multivariate. Result: Median age of patients was 64 years old, male/female ratio was 3.5/1 and 73.6% of patients had a history of smoking. The percentage of EGFR mutations was 34.8%. Blood group O accounted for the highest percentage with 50%, followed by group B with 25% and group A 21%, only 4% of patients with group AB. Univariate analysis showed that the rate of EGFR mutations in patients with group B was 23.2%, lower than the rate of EGFR mutations in patients with non-B group, the difference was statistically significant with p=0.02. There was no association between groups O, A and AB with the ratio of EGFR mutations (p>0.05). Female and smoking history were also two factors associated with the ratio of EGFR mutations in univariate analysis. However, multivariate analysis showed that only female and non-B blood were the two independent factors associated with the EGFR mutations with OR = 3.4, p=0.037 and OR = 2.07, p=0.03, respectively. Conclusion: Blood group B can be a prognostic factor for the EGFR mutations in patients with lung adenocarcinoma. Further studies need to be conducted to further elucidate the prognostic role of ABO blood in lung cancer patients.

PurposeEpidermal growth factor receptor(EGFR) mutation is one of the most critical biomarkers in non-small cell lung cancer (NSCLC), holding significant clinical implications for guiding targeted therapy selection and prognostic assessment in patients. This study aims to evaluate the predictive value of spectral CT parameters, artificial intelligence (AI)-derived parameters, and clinical indicators for EGFR mutation in lung adenocarcinoma.MethodsThis retrospective study analyzed 150 patients with pathologically confirmed lung adenocarcinoma. All patients underwent EGFR genotyping, non-contrast CT, and spectral contrast-enhanced CT. Spectral parameters included spectral curve slope (λHU), iodine concentration (IC), water concentration (WC), Effective atomic number (Effective-Z), and CT values at 70 keV. An AI-assisted diagnostic system automatically extracted quantitative AI parameters: The three-dimensional (3D) radiomic features(including long-axis diameter, short-axis diameter, surface area, 3D long-axis diameter, maximum cross-sectional area, volume), CT attenuation histogram features(including solid component percentage, mean CT value, median CT value, CT value standard deviation, maximum CT values, minimum CT values, kurtosis, skewness, energy, and entropy)and morphological characteristics(including compactness, sphericity). Correlations between spectral CT parameters, AI parameters, clinical variables, and EGFR mutation status were assessed. Independent predictors were identified via multivariate analysis to construct a predictive model.ResultsUnivariate analysis revealed associations between EGFR mutation and gender (P = 0.013), smoking history (P = 0.001), λHU (P = 0.049), and tumor surface area (P = 0.043). Multivariate analysis identified smoking history (P = 0.012), λHU (P = 0.015), and surface area (P = 0.029) as independent predictors. The predictive model integrating these three factors achieved an AUC of 0.713 (95% CI: 0.628–0.797), a specificity of 0.754, and a sensitivity of 0.600, demonstrating moderate diagnostic accuracy. Calibration curves indicated good agreement between predicted and observed probabilities, while decision curve analysis confirmed clinical utility.ConclusionThe integration of spectral CT and AI-derived quantitative parameters with clinical indicators demonstrates significant potential for noninvasive prediction of EGFR mutation in lung adenocarcinoma. This non-invasive predictive approach could reduce unnecessary invasive biopsies. Particularly in patients with contraindications to invasive procedures, this model offers a viable alternative.

BackgroundTo introduce a three-dimensional convolutional neural network (3D CNN) leveraging transfer learning for fusing PET/CT images and clinical data to predict EGFR mutation status in lung adenocarcinoma (LADC).MethodsRetrospective data from 516 LADC patients, encompassing preoperative PET/CT images, clinical information, and EGFR mutation status, were divided into training (n = 404) and test sets (n = 112). Several deep learning models were developed utilizing transfer learning, involving CT-only and PET-only models. A dual-stream model fusing PET and CT and a three-stream transfer learning model (TS_TL) integrating clinical data were also developed. Image preprocessing includes semi-automatic segmentation, resampling, and image cropping. Considering the impact of class imbalance, the performance of the model was evaluated using ROC curves and AUC values.ResultsTS_TL model demonstrated promising performance in predicting the EGFR mutation status, with an AUC of 0.883 (95%CI = 0.849–0.917) in the training set and 0.730 (95%CI = 0.629–0.830) in the independent test set. Particularly in advanced LADC, the model achieved an AUC of 0.871 (95%CI = 0.823–0.919) in the training set and 0.760 (95%CI = 0.638–0.881) in the test set. The model identified distinct activation areas in solid or subsolid lesions associated with wild and mutant types. Additionally, the patterns captured by the model were significantly altered by effective tyrosine kinase inhibitors treatment, leading to notable changes in predicted mutation probabilities.ConclusionPET/CT deep learning model can act as a tool for predicting EGFR mutation in LADC. Additionally, it offers clinicians insights for treatment decisions through evaluations both before and after treatment.

Human lung cancer is a constellation of tumors with various histological and molecular properties. To build a preclinical platform that covers this broad disease spectrum, we obtained lung cancer specimens from multiple sources, including sputum and circulating tumor cells, and generated a living biobank consisting of 43 lines of patient-derived lung cancer organoids. The organoids recapitulated the histological and molecular hallmarks of the original tumors. Phenotypic screening of niche factor dependency revealed that EGFR mutations in lung adenocarcinoma are associated with the independence from Wnt ligands. Gene engineering of alveolar organoids reveals that constitutive activation of EGFR-RAS signaling provides Wnt independence. Loss of the alveolar identity gene NKX2-1 confers Wnt dependency, regardless of EGFR signal mutation. Sensitivity to Wnt-targeting therapy can be stratified by the expression status of NKX2-1. Our results highlight the potential of phenotype-driven organoid screening and engineering for the fabrication of therapeutic strategies to combat cancer.

Purpose: EGFR tyrosine kinase inhibitor (EGFR TKI) was approved as a first line treatment for EGFR mutant lung adenocarcinoma (LADC) with advanced stage. YAP1 (Yes-associated protein 1) is a main effector of hippo pathway, related with adverse prognosis and EGFR TKI modulation of non-small cell lung cancer. This study aimed to clarify a prognostic role of YAP1 in EGFR mutant LADC and efficacy for EGFR TKI through the course of EGFR TKI. Materials and Methods: 41 patients with paired lung cancer specimen before and after EGFR TKI were enrolled in this study. The expression of YAP1 protein was evaluated by immunohistochemistry. Results: 15 cases (36.6%) with high YAP1 expression was found in pre-EGFR TKI LADC, while high YAP1 expression in 21 cases (52.5%) was detected after EGFR-TKI. The transitional level of YAP1 between pre- and post-EGFR TKI was significantly upregulated (P=0.002). High YAP1 before EGFR TKI was related with shorter OS (P=0.023) and PFS (P=0.041). In addition, high YAP1 before EGFR TKI in T790M mutant LADC was related with poor OS (P<0.001). Conclusion: YAP1 burden before EGFR TKI was crucial role in prognosis of EGFR mutant LADC treated by EGFR TKI. Citation Format: Soon Auck Hong, Jin-Hyoung Kang, Sook Hee Hong. Overexpression of YAP1 of EGFR-mutant lung adenocarcinoma before tyrosine kinase inhibitor is associated with poor survival [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2609.

Tyrosin kinase inhibitors are still are relatively new group of drugs in oncology. But in the past few years they have gained an increasing importance due to the major and long lasting clinical benefit they induce in a subgroup of tumor patients. This success of tyrosin kinase inhibitors is based on the exquisite importance of tyrosin kinases for growth and survival of tumor cells. Prominent examples of such an oncogene dependency are the BCR-ABL fusion in chronic myeloid leukemia or EGFR mutations in lung adenocarcinoma. Many further tumor entities with clinically tractable oncogene dependencies can be expected in the upcoming years. An intense interaction between clinical science in clinical trials, preclinical research and excellent molecular quality controlled diagnostics is crucial for the further development.

To assess the frequency of human cytomegalovirus (HCMV), Epstein-Barr virus (EBV), and high-risk types of human papillomavirus (HPV16 and HPV18) infections in lung adenocarcinoma samples.Lung adenocarcinoma cytological smears and their DNA isolates were obtained from patients hospitalized at the Department for Lung Diseases Jordanovac, Zagreb, in 2016 and 2017. Overall, 67 lung adenocarcinoma samples were examined: 34 with epidermal growth factor receptor gene (EGFR) mutations and 33 without EGFR mutations. The EGFR mutation status and virus presence were assessed with a polymerase chain reaction, and random samples were additionally tested for EBV with Sanger sequencing. HCMV, EBV, HPV16, and HPV18 infections were evaluated in relation to EGFR mutation, smoking status, and sex. A meta-analysis of available data about HPV infection in non-small cell lung cancer was performed.More frequent HCMV, EBV, HPV16, and HPV18 infections were observed in lung adenocarcinoma samples with EGFR mutations than in samples without these mutations. Coinfection of the investigated viruses was observed only in lung adenocarcinoma samples with mutated EGFR. In the group with EGFR mutations, smoking was significantly associated with HPV16 infection. The meta-analysis showed that non-small cell lung cancer patients with EGFR mutations had a higher odds of HPV infection.HCMV, EBV, and high-risk HPV infections are more frequent in EGFR-mutated lung adenocarcinomas, which indicates a possible viral impact on the etiology of this lung cancer subtype.

Recent clinical trials of lung adenocarcinoma with immune checkpoint inhibitors revealed that lung adenocarcinoma patients with EGFR mutations have a poor response to immunotherapy. However, the mechanisms have not been addressed. We performed immunohistochemistry analyses of resected lung adenocarcinoma tissues with and without EGFR mutations to investigate and compare the characteristics of the tumor microenvironment (TME). We retrospectively enrolled a total of 323 lung adenocarcinoma patients (164 had EGFR mutations), and their corresponding tissue samples were analyzed by the EGFR mutation test and immunohistochemistry. We selected the markers of the immune checkpoint molecule (PD1, PD-L1, and LAG-3) and immune cell (CD3, CD4, CD8, and Foxp3) as markers of the tumor microenvironment. Our results revealed that patients had a distinct tumor microenvironment between EGFR-mutant and wild-type lung adenocarcinomas; the expression of CD3, CD4, PD-L1, and Foxp3 in EGFR-mutant tumors was significantly higher than that in wild-type tumors, while the expression of LAG3 and PD-1 showed a positive correlation with EGFR-wild-type tumors. In survival analysis, EGFR-wild-type patients had longer disease-free survival (DFS) than EGFR-mutant patients (P = 0.0065). Our research demonstrates significant differences in tumor microenvironment composition between EGFR-mutant and wild-type patients. Our findings provide novel evidence that contributes to understanding the mechanism underlying the poor efficacy of immune checkpoint inhibitors.

Background Most patients with EGFR-driven NSCLC harbor exon 19 deletions or exon 20 L858R point mutations, which have established sensitivity to tyrosine kinase inhibitors (TKI) with a median overall survival (OS) of several years. However, the outcome of patients with other EGFR alterations is variable and not well-defined.

Detection of EGFR mutation in lung adenocarcinoma and paired plasma

Lung cancer is the top cancer killer worldwide. Tyrosine kinase inhibitors (TKIs), for example erlotinib, are commonly used to target epidermal growth factor receptor (EGFR)-mutated lung adenocarcinoma (ADC). Autophagy is a cellular response to stress, serving as a protective mechanism during anticancer therapy. The tumor microenvironment (TME) is composed of non-tumor cells that include fibroblasts. Our study aimed to investigate the effect of TME on autophagy and TKI sensitivity. Following cell sorting after direct co-culturing, autophagy and cytokine production were observed in both HCC827 and MRC-5 cells. The synergistic combination of erlotinib and chloroquine (autophagy inhibitor) was observed under TME. Tumor growth was significantly suppressed with combined erlotinib/chloroquine compared with erlotinib in HCC827 xenografts.

Lung cancer is the leading cause of cancer-related deaths worldwide. EGFR mutations, which account for about 25% of lung cancer cases, are more commonly associated with lung cancer in never smokers. Although response rates to EGFR tyrosine kinase inhibitors (TKI) used as a first line therapy are high, acquired resistance inevitably occurs. Elevated tumor mutation burden in EGFR mutant lung cancer is associated with a shorter progression free survival, and worse overall survival with both first and second generation TKIs. Increasing our understanding of drivers of mutagenesis in lung cancer is critical in our efforts to prevent tumor reoccurrence and resistance. APOBEC-driven mutagenesis has been shown to occur in multiple cancer types including lung adenocarcinoma. Using the TCGA and TRACERx datasets we have demonstrated that APOBEC3B is significantly upregulated when compared with other APOBEC family members in EGFR mutant lung adenocarcinoma, and that the APOBEC mutation signature is enriched in a subset of patients with EGFR mutant lung adenocarcinoma. To model APOBEC mutagenesis in lung cancer, we have developed a novel lung cancer mouse model, by crossing the ROSA26LSL-APOBEC3B (A3B) mouse model with several different EGFR mutant mouse models. Using these models, we find that APOBEC3B expression is selected for post-TKI and contributes to resistance to TKI therapy. Citation Format: Deborah Caswell, Manasi Mayekar, Emily Law, William Hill, Eva Gronroos, Reuben Harris, Trever Bivona, Charles Swanton. APOBEC3B and TKI resistance in EGFR mutant lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2938.

The molecular landscape of lung adenocarcinoma (LUAD) is often summarized as a "pie chart" of driver oncogenes, suggesting identification and targeting of oncogenic drivers is the best clinical approach. However, this model oversimplifies LUAD biology. Patients with identical RAS or RAF mutations exhibit heterogeneous signaling influenced by co-mutations, transcriptional programs, and lineage context. We propose a hierarchical framework integrating oncogenes within cellular context by examining canonical EGFR mutations. We defined an EGFR mutation signature (mSig) by identifying differentially expressed genes in EGFR -mutant LUADs. Semi-supervised clustering and machine learning models were used to test performance and reproducibility across independent datasets. We analyzed molecular subtypes, lineage markers, co-occurring mutations, and candidate drug targets in EGFR mSig positive (+) versus negative (-) tumors. The EGFR mSig showed robust classification performance across datasets (AUROC = 0.83 - 0.95; mean NPV = 96.3%). Validated unsupervised gene expression subtypes and lung lineage markers were closely aligned with EGFR mSig status. mSig(+) tumors were identified, even in tumors without EGFR mutations. A subset of canonical RAS mutations mirrored the EGFR mutation pattern. EGFR -mutant/mSig(-) tumors were enriched for non-Bronchioid subtypes and had co-mutations in TP53 or RAS. Coordinated mutations were identified including RAS, KEAP1 , STK11 , TP53 , and CDKN2A , supportive of prior reports. In sum, novel EGFR mSig that captures the transcriptional footprint of EGFR activation, revealed a subset of EGFR wildtype LUADs with "mutant-like" features. Lineage-informed classification highlights subtype-dependent oncogene activity and supports new therapeutic strategies. A context-specific association between RAS mutation and expression of the dual-specificity phosphatase gene DUSP4 may have therapeutic potential.

Epithelial-mesenchymal transition (EMT) was recently discovered related to the efficacy of epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) in NSCLC patients and cell lines. In this study, we aimed to explore the association among the E-cadherin gene (CDH1) genetic variants, TK-domain mutations of EGFR, and clinicopathologic characteristics in patients with lung adenocarcinoma. A total of 280 patients with lung adenocarcinoma were recruited between years 2012 and 2015. All subjects underwent the analysis of CDH1 genetic variants (rs16260 and rs9929218) by real-time polymerase chain reaction (PCR) genotyping. The results showed that CA and CA + AA genotypes of CDH1 single nucleotide polymorphism (SNP) rs16260 were significantly reverse associated with EGFR mutation type (Adjusted odds ratio (AOR) = 0.43, 95% CI = 0.20-0.92 and AOR = 0.46, 95% CI = 0.22-0.96, respectively) in female lung adenocarcinoma patients. Moreover, the significantly reverse associations between CA and CA + AA genotypes of CDH1 rs16260 and EGFR hotspot mutations, namely L858R mutation and exon 19 in-frame deletion, were also demonstrated among female patients. Besides, CA + AA genotype of CDH1 rs16260 was noted significantly reverse associated with the tumor sizes (OR = 0.31, 95% CI = 0.12-0.80; p = 0.012). In conclusion, our results suggested that CDH1 variants are significantly reverse associated with mutation of EGFR tyrosine kinase, especially among the female patients with lung adenocarcinoma. The CDH1 variants might contribute to pathological development in lung adenocarcinoma.

22105 Background: EGFR copy number has been shown to correlate with the presence of EGFR mutations and response to tyrosine kinase inhibitors (TKIs) in patients with lung adenocarcinoma. Fluorescent in situ hybridization (FISH) for EGFR has been more widely used than chromogenic in situ hybridization (CISH) but the latter offers some advantages in terms of equipment, ease of implementation and preservation of results. We compared CISH and FISH for EGFR in a series of lung adenocarcinomas and correlated the findings with EGFR and KRAS mutation status and EGFR expression by immunohistochemistry (IHC). Methods: A tissue microarray was constructed containing triplicate cores of 28 EGFR mutated lung adenocarcinomas and 31 EGFR non-mutated cases, the latter including 8 KRAS mutated cases. For both ISH methods, nuclear counts of 5 or more signals were scored as positive. The criteria for FISH include polysomy or high copy number. EGFR IHC was scored from 0–3 with 0 and 1 counted as negative and 2 and 3 as positive. Results: Overall correlation of CISH and FISH was excellent. 20 of 59 (33%) cases were amplified by CISH and 23 of 59 (37%) were amplified by FISH, with 18 (30%) positive and 34 (57%) negative by both methods (p<0.0001). Discordant cases included 5 negative by CISH and positive by FISH and 2 positive by CISH and negative by FISH. Of 20 EGFR CISH positive cases, 15 (75%) were mutated (p=0.003) and of the 23 FISH positive cases, 16 (70%) were mutated (p=0.007). One case called positive by FISH, negative by CISH showed a KRAS mutation. No other KRAS mutant case was scored as EGFR-amplified by either method. EGFR was positive by IHC in 28 cases, of which 15 were positive by CISH (p=0.003) and 16 by FISH (p=0.007). There was no correlation with IHC and mutations status. Conclusions: EGFR CISH and FISH show excellent concordance in scoring EGFR amplification, which shows a highly significant association with EGFR mutation. No significant financial relationships to disclose.