Epidermal Growth Factor Receptor Mutant Lung Cancer Research Articles

A Real-World Study of Patient Characteristics and Clinical Outcomes in EGFR Mutated Lung Cancer Treated with First-Line Osimertinib: Expanding the FLAURA Trial Results into Routine Clinical Practice.

Osimertinib is a tyrosine kinase inhibitor of the epidermal growth factor receptor (EGFR) that is used for first-line therapy in EGFR mutated non-small cell lung cancer (NSCLC) based on the results of the randomized FLAURA trial (ClinicalTrials.gov number NCT02296125). We performed a retrospective analysis of baseline characteristics and clinical outcomes in 56 real-world patients treated with osimertinib. In total, 45% of patients were determined to be FLAURA-eligible and 55% were FLAURA-ineligible based on the published inclusion/exclusion criteria of the aforementioned trial. For clinical outcomes, the median osimertinib time to treatment discontinuation (TTD) for all patients was 16.9 months (95% CI: 12.6-35.1), whereas the median TTD was 31.1 months (95% CI: 14.9-not reached) in the FLAURA-eligible cohort and the median TTD was 12.2 months (95% CI: 8.1-34.6 months) in the FLAURA-ineligible cohort. Re-biopsy at acquired resistance disclosed both on- and off-target mechanisms. The most common therapies following osimertinib included local therapies followed by post-progression osimertinib, platinum-doublet chemotherapy with or without osimertinib, and osimertinib combinatory targeted therapies. The median overall survival for all patients was 32.0 months (95% CI: 15.7-not reached), the median survival was not reached for the FLAURA-eligible cohort, and it was 16.5 months for the FLAURA-ineligible cohort. Our data support the use of osimertinib in real-word settings and highlight the need for designing registration trials that are more inclusive of patient/disease characteristics seen in routine clinical practice. It is yet to be determined if the use of evolving first-line EGFR inhibitor combination strategies (either platinum-doublet chemotherapy plus osimertinib or amivantamab plus lazertinib) will similarly translate from clinical trials to real-word settings.

Clinical characteristics of patients treated with immune checkpoint inhibitors in EGFR-mutant non-small cell lung cancer: CS-Lung-003 prospective observational registry study

PurposeImmune checkpoint inhibitors (ICIs) are ineffective against epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC). This study aimed to investigate the clinical characteristics of patients who were treated or not treated with ICIs, and of those who benefit from immunotherapy in EGFR-mutant NSCLC.MethodsWe analyzed patients with unresectable stage III/IV or recurrent NSCLC harboring EGFR mutations using a prospective umbrella-type lung cancer registry (CS-Lung-003).ResultsA total of 303 patients who met the eligibility criteria were analyzed. The median age was 69 years; 116 patients were male, 289 had adenocarcinoma, 273 had major mutations, and 67 were treated with ICIs. The duration of EGFR-TKI treatment was longer in the Non-ICI group than in the ICI group (17.1 vs. 12.7 months, p < 0.001). Patients who received ICIs for more than 6 months were categorized into the durable clinical benefit (DCB) group (24 patients), and those who received ICIs for less than 6 months into the Non-DCB group (43 patients). The overall survival in the DCB group exhibited longer than the Non-DCB group (69.3 vs. 47.1 months), and an equivalent compared to that in the Non-ICI group (69.3 vs. 68.9 months). Multivariate analysis for time to next treatment (TTNT) of ICIs showed that a poor PS was associated with a shorter TTNT [hazard ratio (HR) 3.309; p < 0.001]. Patients who were treated with ICIs and chemotherapy combination were associated with a longer TTNT (HR 0.389; p = 0.003). In addition, minor EGFR mutation was associated with a long TTNT (HR 0.450; p = 0.046).ConclusionICIs were administered to only 22% of patients with EGFR-mutated lung cancer, and they had shorter TTNT of EGFR-TKI compared to other patients. ICI treatment should be avoided in EGFR mutated lung cancer with poor PS but can be considered for lung cancer with EGFR minor mutations. Pathological biomarker to predict long-term responders to ICI are needed.

The Importance of Screening for EGFR Mutation in Lung Cancer

Lung cancer is one of the cancers with the most cases occurring in both men and women. It was found that a number of patients with lung cancer had mutations in the epidermal growth factor receptor (EGFR). The EGFR mutation is a somatic mutation associated with non-small cell lung cancer (NSCLC), which can be identified using real-time PCR or Next Generation Sequencing (NGS) in a sample obtained from formalin-fixed paraffin-embedded tissue. The presence of EGFR mutation in lung cancer tissue has revealed an opportunity to treat this disease with anti-EGFR therapy. First-generation EGFR inhibitors work by reversibly inhibiting the EGFR tyrosine kinase. However, it does not work with the T790M mutation which needs a third-generation EGFR inhibitor that can irreversibly inhibit both active and inactive variants of EGFR. Screening of EGFR mutation in NSCLC has been mandatory to reveal an opportunity for treating with EGFR inhibitor.

Is oligoprogression a potentially curable disease in epidermal growth factor receptor mutant lung adenocarcinoma?

Third-generation epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) have shown impressive results in EGFR mutant lung cancer (LC) patients in terms of disease control rate with a positive impact on overall survival. Nevertheless, after months of treatment with targeted therapy, progression inevitably occurs. Some patients develop oligoprogression and local treatment is required for optimal disease control while maintaining EGFR-TKIs. This work features a clinical case of a patient harboring an EGFR mutant LC undergoing oligoprogression to EGFR-TKIs, first into the brain and afterward to the primary tumor, requiring local ablative strategies, including primary tumor resection three years after the start of osimertinib. Currently, the patient is still alive and continues with a complete response upon EGFR-TKIs maintenance. Hence, oligoprogression, even in driven oncogenic tumors, represents a distinct biological entity and potential curative disease that deserves particular consideration in multidisciplinary tumor boards. In this case, tumor primary resection after three years of the initial diagnosis represents a paradigm shift in the treatment of EGFR mutant patients.

Tissue and Plasma-Based Highly Sensitive Blocker Displacement Amplicon Nanopore Sequencing for EGFR Mutations in Lung Cancer.

The epidermal growth factor receptor (EGFR) mutation is a widely prevalent oncogene driver in non-small cell lung cancer (NSCLC) in East Asia. The detection of EGFR mutations is a standard biomarker test performed routinely in patients with NSCLC for the selection of targeted therapy. Here, our objective was to develop a portable new technique for detecting EGFR (19Del, T790M, and L858R) mutations based on Nanopore sequencing. The assay employed a blocker displacement amplification (BDA)-based polymerase chain reaction (PCR) technique combined with Nanopore sequencing to detect EGFR mutations. Mutant and wild-type EGFR clones were generated from DNA from H1650 (19Del heterozygous) and H1975 (T790M and L858R heterozygous) lung cancer cell lines. Then, they were mixed to assess the performance of this technique for detecting low variant allele frequencies (VAFs). Subsequently, formalin-fixed, paraffin-embedded (FFPE) tissue and cell-free DNA (cfDNA) from patients with NSCLC were used for clinical validation. The assay can detect low VAF at 0.5% mutant mixed in wild-type EGFR. Using FFPE DNA, the concordance rates of EGFR 19Del, T790M, and L858R mutations between our method and Cobas real-time PCR were 98.46%, 100%, and 100%, respectively. For cfDNA, the concordance rates of EGFR 19Del, T790M, and L858R mutations between our method and droplet digital PCR were 94.74%, 100%, and 100%, respectively. The BDA amplicon Nanopore sequencing is a highly accurate and sensitive method for the detection of EGFR mutations in clinical specimens.

Clinical Efficacy and Safety of First- or Second-Generation EGFR-TKIs after Osimertinib Resistance for EGFR Mutated Lung Cancer: A Prospective Exploratory Study.

Osimertinib monotherapy is a common treatment for epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC); however, standard treatment strategies for acquired resistance to this drug have not been established. In addition, the clinical significance of first-generation (1G) or second-generation (2G) EGFR-tyrosine kinase inhibitors (TKI) in patients with EGFR-mutant NSCLC and osimertinib resistance has not yet been fully evaluated. We aimed to conduct a prospective multicenter observational study to evaluate the efficacy and safety of 1G and 2G EGFR-TKIs after the development of osimertinib resistance. Patients with EGFR-mutant NSCLC who received 1G or 2G EGFR-TKIs after developing resistance to osimertinib monotherapy were prospectively assessed at eight institutions in Japan. The primary endpoint was progression-free survival (PFS). A total of 29 patients with advanced or recurrent EGFR-mutant NSCLC were analyzed. The objective response and disease control rates were 6.9% (2/29) and 58.6% (17/29), respectively. The median PFS was 1.9 months [95% confidence interval (CI): 1.3-5.3]. There was no significant difference in PFS between the 1G and 2G EGFR-TKI groups (3.7 versus 1.5 months, log-rank test p = 0.20). However, patients with normal cytokeratin 19 fragment (CYFRA 21-1) and pro-gastrin-releasing peptide (ProGRP) levels experienced longer PFS than those with elevated CYFRA 21-1 and/or ProGRP (5.5 versus 1.3 months, log-rank test p < 0.001). Administration of 1G or 2G EGFR-TKIs after the development of osimertinib resistance has limited efficacy in patients with EGFR-mutant NSCLC. Moreover, normal CYFRA 21-1 and ProGRP levels could be promising indicators for 1G and 2G EGFR-TKI administration after osimertinib resistance development. UMIN000044049.

Germline EGFR mutations in lung cancer (Review).

Lung cancer is the leading cause of cancer-related death and familial lung cancer is a potential contributing factor. Epidermal growth factor receptor (EGFR) mutations are important events in carcinogenesis. The present study summarized the common germline mutations of EGFR, including T790M, V843I, R776H and P848L, and provided detailed information regarding each mutation site and potential treatment strategies. Individuals with germline mutations may develop lung cancer upon exposure to environmental stimuli such as smoking, air pollution or radiological contamination, or due to the occurrence of another somatic mutation. The present study recommends regular physical examinations as well as population-wide germline mutation screening for early detection and diagnosis of lung cancer.

Abstract 6141: Mechanisms by which Mito-lonidamine inhibits EGFR mutant lung cancer

Abstract Lung cancer remains the leading cause of cancer mortality. Efficacious targeted therapy options are urgently needed for lung cancer prevention and treatment. Epidermal growth factor receptor (EGFR) mutant lung cancer represents about 15% of lung cancer cases generally occurring in patients with minimal to no smoking history and with higher prevalence in females. Linkages to environmental exposures have been postulated. Our group synthesized Mito-lonidamine (Mito-LND), a mitochondrial targeted analog of lonidamine which inhibits aerobic glycolysis in cancer cells. We previously identified that Mito-LND induces mitophagy in KRAS mutant lung cells and inhibits lung tumorigenesis and brain metastasis in vivo. Yet, the cancer inhibitory capacity of Mito-LND in EGFR mutant lung cancer has not been investigated. Viability staining assessed Mito-LND induced cell death in EGFR mutant cell lines PC9 (parent) and PC9BrM3 (brain metastatic). Transcriptomic profiling was conducted following Mito-LND treatment and results analyzed in Metacore to assess molecular changes. Deconvolution analysis interrogated alterations in immune cell populations. To discern cell death mechanisms, we evaluated FDA-approved inhibitors for autophagy (chloroquine, CQ), mitophagy/apoptosis (cyclosporin A, CsA) and necrosis (Ponatinib) in EGFR mutant cell lines using viability assays with Mito-LND treatment. In PC9 cells, the IC50 for Mito-LND at 24h and 48h was 1.5µM and 0.5µM, respectively and in PC9BrM3 cells at 24h and 48h was 1.5µM and 0.7µM, respectively. These data support that EGFR mutant cell lines are &amp;gt;2-fold more sensitive to Mito-LND induced cell death compared to KRAS mutant lung cell lines H2030 and H2030BrM3. Transcriptomic profiling results show that Mito-LND treatment upregulated pathway maps linked to heat shock protein and HIF-1A signaling in both PC9 and PC9BrM3 cells. Process networks linked to unfolded protein response, response to hypoxia and oxidative stress, apoptosis and the immune response were upregulated with Mito-LND treatment. Deconvolution analysis revealed monocytes and macrophages were upregulated in Mito-LND treated EGFR mutant cell lines, with CD8+ T cells increased in PC9BrM3 cells and regulatory T cells increased in PC9 cells. Last, CsA significantly inhibited Mito-LND induced cell death in both cell lines, while CQ had no effect suggesting blocking apoptosis, but not late autophagy inhibits cell death induction in EGFR mutant cell lines. Further, necrosis inhibition with Ponatinib synergistically increased Mito-LND induced cell death in EGFR mutant cell lines. These results begin to define the cancer inhibitory mechanisms of Mito-LND in EGFR mutant lung cancer cells which appear to differ from those observed in KRAS mutant lung cancer cells. Future directions include dissecting apoptotic and necrosis driven Mito-LND induced cell death using additional pharmacological inhibitors and genetic approaches. Citation Format: Katherine M. Weh, Connor Howard, Yun Zhang, Jean-Jack Riethoven, Jennifer Clarke, Gang Cheng, Balaraman Kalyanaraman, Ming You, Laura Kresty. Mechanisms by which Mito-lonidamine inhibits EGFR mutant lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6141.

Using stacked deep learning models based on PET/CT images and clinical data to predict EGFR mutations in lung cancer.

PurposeTo determine whether stacked deep learning models based on PET/CT images and clinical data can help to predict epidermal growth factor receptor (EGFR) mutations in lung cancer.MethodsWe analyzed data from two public datasets of patients who underwent 18F-FDG PET/CT. Three PET deep learning ResNet models and one CT deep learning ResNet model were trained as low-level predictors based on PET and CT images, respectively. A high-level Support Vector Machine model (Stack PET/CT and Clinical model) was trained using the prediction results of the low-level predictors and clinical data. The clinical data included sex, age, smoking history, SUVmax and SUVmean of the lesion. Fivefold cross-validation was used in this study to validate the prediction performance of the models. The predictive performance of the models was evaluated by receiver operator characteristic (ROC) curves. The area under the curve (AUC) was calculated.ResultsOne hundred forty-seven patients were included in this study. Among them, 37/147 cases were EGFR mutations, and 110/147 cases were EGFR wild-type. The ROC analysis showed that the Stack PET/CT & Clinical model had the best performance (AUC = 0.85 ± 0.09), with 0.76, 0.85 and 0.83 in sensitivity, specificity and accuracy, respectively. Three ResNet PET models had relatively higher AUCs (0.82 ± 0.07, 0.80 ± 0.08 and 0.79 ± 0.07) and outperformed the CT model (AUC = 0.58 ± 0.12).ConclusionUsing stack generalization, the deep learning model was able to efficiently combine the anatomic and biological imaging information gathered from PET/CT images with clinical data. This stacked deep learning model showed a strong ability to predict EGFR mutations with high accuracy.

64 (PB054) - BDTX-1535, a fourth generation EGFR inhibitor, targeting intrinsic and acquired resistance mutations in NSCLC

Background: The classical mutations of the epidermal growth factor receptor (EGFR) in NSCLC are the exon 19 del and exon 21 (L858R) mutations. The 3rd generation EGFR tyrosine kinase inhibitor (TKI), osimertinib, has become the first-line treatment of choice for NSCLC patients with these mutations. Resistance to 3rd generation TKIs can be driven by gain of secondary EGFR alterations, e.g., substitution at cysteine-797 to serine (C797S). Real world evidence shows that in addition to C797S, other EGFR alterations are also acquired upon osimertinib treatment, including kinase domain mutations (e.g., S768I), extracellular domain alterations (e.g., EGFRvIII, A289X), and EGFR amplification. In addition to the classical mutations, NSCLC tumors express a wide spectrum of primary kinase domain mutations including G719X in exon 18, S768I in exon 20, and L861Q in exon 21, which confer intrinsic resistance to approved TKIs. NCCN guidelines recommend the use of afatinib or osimertinib, however, there remains a need for an EGFR TKI that targets these mutations with high potency, good tolerability, and CNS penetration. Our MAP platform allowed us to select MasterKey inhibitor BDTX-1535, a 4th-generation CNS penetrant EGFR TKI, that potently and selectively targets multiple intrinsic and acquired resistance EGFR alterations. Materials and Methods: BDTX-1535 preclinical exposure was evaluated across species, and PK and Kpuu values were calculated in brain and plasma. Antitumor activity was assessed across a broad range of mouse PDX and allograft models. Results: BDTX-1535 is a potent and selective, CNS penetrant, wild type sparing, irreversible EGFR TKI targeting Exon 18–21 alterations which are associated with intrinsic or acquired resistance to 3rd generation EGFR inhibitors. These include a broad range of kinase domain EGFR mutations (e.g., C797S, L718Q, G724S, S768I), extracellular domain alterations (e.g., EGFRvIII, A289X), and EGFR amplification. Mouse xenograft and allograft studies showed that BDTX-1535 consistently achieves regression of tumors carrying these mutations at well tolerated doses without significant EGFR wild type associated toxicities. BDTX-1535 is orally bioavailable with a CNS Kpuu of 0.55 and 0.48 in rat and dog, respectively, and active in an intracranial PDX model. Conclusions: BDTX-1535 is a 4th generation CNS penetrant EGFR TKI discovered using the MAP platform which allows MasterKey targeting of EGFR alterations associated with intrinsic or acquired resistance to 3rd generation EGFR TKIs, while sparing wild type EGFR. This broad spectrum coverage of resistance mutations in conjunction with CNS penetration properties allows BDTX-1535 to address a key unmet medical need in EGFR mutant lung cancer. BDTX-1535 is currently under phase I clinical investigation (NCT05256290). Conflict of interest: Ownership: Black Diamond Therapeutics

EP08.02-003 Aumolertinib Plus Chemotherapy as 1st Line Treatment in Advanced Lung Cancer EGFR Mutation andctDNA Cleared Analysis

Aumolertinib is a novel third-generation epidermal growth factor receptor (EGFR)-targeted oral tyrosine kinase inhibitor (TKIs). The positive phase III trial (AENEAS) reported objective response rate (ORR) was 73.8% and medium progression-free survival (mPFS) was 19.3 months which aumolertinib as 1st line treatment of patients with EGFR mutation Non-Small Cell Lung Cancer (NSCLC). An improved efficacy of the combination of first-generation EGFR-TKI and carboplatin plus pemetrexed was confirmed in NEJ009 study.

Amivantamab and Mobocertinib in Exon 20 insertions EGFR Mutant Lung Cancer, Challenge To The Current Guidelines

In 2021, the US Food and Drug Administration (FDA) approved two drugs targeting exon 20 directly: amivantamab and mobocertinib, under the accelerated approval pathway, for adult patients with locally advanced or metastatic non-small cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) exon 20 insertion mutations, whose disease has progressed on or after platinum-based chemotherapy. Here we discuss questions regarding the core question of an “unmet need” within the accelerated approval pathway, contending that equipoise remain between the new compounds and previously existing options. Second, the NCCN's guidelines are currently recommending to sequence both drugs, a recommendation that is not based on any data. Last, post-marketing requirements may not shed clarity in the setting of these approvals. Our analysis has implications beyond patients with exon 20 insertion. In an era with growing identification of new and rarer molecular entities, misguided incorporation of new compounds into practice may obstruct trial enrollment in decisive clinical trials.

Explainable Machine Learning Model to Prediction EGFR Mutation in Lung Cancer.

ObjectivesThe aim of this study is to determine whether the clinical features including blood markers can establish an explainable machine learning model to predict epidermal growth factor receptor (EGFR) mutation in lung cancer.MethodsWe retrospectively analyzed 7,413 patients with lung adenocarcinoma (LA) diagnosed by gene sequencing in West China Hospital of the Sichuan University from April 2015 to June 2019. The machine learning algorithms (MLAs) included logistic regression (LR), random forest (RF), LightGBM, support vector machine (SVM), multi-layer perceptron (MLP), extreme gradient boosting (XGBoost), and decision tree (DT). Demographic characteristics, personal history, and blood markers were taken into. The area under the receiver operating characteristic curve (AUC) and SHapley Additive exPlanation (SHAP) value were used to explain the prediction models.ResultsOf the 7,413 patients with LA (47.6%), 3,527 were identified with EGFR mutation; RF achieved greatest performance in predicting EGFR mutation AUC [0.771, 95% confidence interval (CI): 0.770, 0.772], which was like XGBoost with AUC (0.740, 95% CI: 0.739, 0.741). The five most influential features were smoking consumption, sex, cholesterol, age, and albumin globulin ratio. The SHAP summary and dependence plot have been used to explain the affection of the 12 features to this model and how a single feature influences the output, respectively.ConclusionWe established EGFR mutation prediction models by MLAs and revealed that the RF was preferred, AUC (0.771, 95% CI: 0.770, 0.772), which was better than the traditional models. Therefore, the artificial intelligence–based MLA predicting model may become a practical tool to guide in diagnosis and therapy of LA.

Bruceine H Mediates EGFR-TKI Drug Persistence in NSCLC by Notch3-Dependent β-Catenin Activating FOXO3a Signaling

Tyrosine kinase inhibitors (TKIs) targeting epidermal growth factor receptor (EGFR) protein serve as a critical pillar in the treatment of non-small cell lung cancer (NSCLC), but resistance is universal. Identifying the potential key factors of drug resistance to EGFR-TKIs is essential to treat patients with EGFR mutant lung cancer. Our research here shows that bruceine H suppressed the proliferation, migration, and invasion of lung cancer cells; inhibited the growth of human NSCLC cell xenografts; and enhanced the therapeutic effects of gefitinib in the PC-9/GR xenograft models, possibly by inhibiting Notch3. In order to analyze the potential targets of the combination of Notch3 and EGFR-TKIs on resistance to EGFR, we analyzed the differences of gene expression between NSCLC tissues and EGFR-driven gefitinib-resistant tumoral groups and then identify through the WGCNA key genes that may provide therapeutic targets for TKI-resistant lung cancer xenograft models. We confirmed that EGFR-TKI in combination with Notch3 inhibitor can inhibit the expression of β-catenin and enhance the level of FOXO3a, leading to improved recurrence-free survival and overall survival of the xenotransplantation model. These results support that the combination of gefitinib and bruceine H may provide a promising alternative strategy for treating acquired EGFR-TKI resistance in patients with NSCLC.

FBXO32 targets PHPT1 for ubiquitination to regulate the growth of EGFR mutant lung cancer.

Phosphohistidine phosphatase 1 (PHPT1) is an oncogene that has been reported to participate in multiple tumorigenic processes. As yet, however, the role of PHPT1 in lung cancer development remains uncharacterized. RNA sequencing assay and 18 pairs of tumor and normal tissues from patients were analyzed to reveal the upregulation of PHPT1 in lung cancer, followed by confirming the biological function in vitro and in vivo. Next, Gene Set Enrichment Analysis, lung cancer samples, apoptosis assay, mass spectrometry experiments and western blotting were used to investigate the molecular mechanism underlying PHPT1 driven progression in epidermal growth factor receptor (EGFR)-mutant lung cancer. Finally, we performed cellular and animal experiments to explore the tumor suppressive function of F-box protein 32 (FBXO32). We found that PHPT1 is overexpressed in lung cancer patients and correlates with a poor overall survival. In addition, we found that the expression of PHPT1 is elevated in EGFR-mutant lung cancer cells and primary patient samples. Inhibition of PHPT1 expression in EGFR mutant lung cancer cells significantly decreased their proliferation and clonogenicity, and suppressed their in vitro tumor growth. Mechanistic studies revealed that activation of the ERK/MAPK pathway is driven by PHPT1. PHPT1 is required for maintaining drug resistance to erlotinib in EGFR mutant lung cancer cells. We found that FBXO32 acts as an E3 ubiquitin ligase for PHPT1, and that knockdown of FBXO32 leads to PHPT1 accumulation, activation of the ERK/MAPK pathway and promotion of the proliferation, clonogenicity and growth of lung cancer cells. Our findings indicate that PHPT1 may serve as a biomarker and therapeutic target for acquired erlotinib resistance in lung cancer patients carrying EGFR mutations.

Concordance of Epidermal Growth Factor Receptor Mutation from Tissue Biopsy and Plasma Circulating Tumor DNA in Treatment-Naïve Lung Adenocarcinoma Patients

Background: Prevalence of Epidermal Growth Factor Receptor (EGFR) mutation in ctDNA in treatment-naïve individuals are not well established in Indonesia. In recent years, ctDNA as a specific and sensitive blood-based biomarker had been developed to detect the mutation. The study was done to understand the concordance and acceptance levels of ctDNA in detecting the gene mutation in lung adenocarcinoma patients. &#x0D; Methods: This study used cross-sectional approach with purposive sampling design in 100 treatment-naïve NSCLC, adenocarcinoma patients. Samples were obtained from bronchoscopy, and blood, which were examined to detect the mutation in formalin-fixed, paraffin-embedded (FFPE) specimens or plasma samples using QIAampDNA Micro Kit. Mutation was calculated by droplet digital PCR (ddPCR). &#x0D; Results: A hundred subjects with primary tumor tissue samples were compared with the plasma samples and mutation was detected in 20 patients (20.0%), 12 (12.0%) on exon 19, 7 (7.0%) on exon 21 and 1 (1.0%) on both exon 19 and 21. Within the plasma samples, mutation was found in 15 patients (15%) with mutation on exon 19 and 21 in 12 (12.0%) and 3 (3.0%) patients, respectively. Within the two samples, concordance of EGFR mutation was 83.0% (83/100, P&lt;0.001; correlation index: 0.42). Assuming presence of mutation as the benchmark, the accuracy of mutation presence in plasma DNA was 60.0% (9/15). Kappa test showed a weak agreement between the mutation in tissues and plasma, with a coefficient of 0.414 (95% CI). &#x0D; Conclusion: Tissue biopsy was still considered as the main option to detect EGFR mutation in lung cancer. More research on ctDNA as the standardized tools to detect the mutation are required.

A Quarter-split Domain-adaptive Network for EGFR Gene Mutation Prediction in Lung Cancer by Standardizing Heterogeneous CT image.

Epidermal growth factor receptor (EGFR) gene mutation status is crucial for the treatment planning of lung cancer. The gold standard for detecting EGFR mutation status relies on invasive tumor biopsy and expensive gene sequencing. Recently, computed tomography (CT) images and deep learning have shown promising results in non-invasively predicting EGFR mutation in lung cancer. However, CT scanning parameters such as slice thickness vary largely between different scanners and centers, making the deep learning models very sensitive to noise and therefore not robust in clinical practice. In this study, we propose a novel QuarterNetadaptive model to predict EGFR mutation in lung cancer, which is robust to CT images of different thicknesses. We propose two components: 1) a quarter-split network to sequentially learn local lung features from different lung lobes and global lung features; 2) a domain adaptive strategy to learn CT thickness-invariant features. Furthermore, we collected a large dataset including 1413 patients with both EGFR gene sequencing and CT images of various thicknesses to evaluate the performance of the proposed model. Finally, the QuarterNetadaptive model achieved AUC over 0.88 regarding CT images of different thicknesses, which improves largely than state-of-the-art methods.Clinical relevance-We proposed a non-invasive model to detect EGFR gene mutation in lung cancer, which is robust to CT images of different thicknesses and can assist lung cancer treatment planning.

Alterations in HLA Class I-Presented Immunopeptidome and Class I-Interactome upon Osimertinib Resistance in EGFR Mutant Lung Adenocarcinoma.

Simple SummaryWe sought to identify molecular mechanisms of lower efficacy of immunotherapy in epidermal growth factor receptor (EGFR) mutant lung adenocarcinoma and the differences in those mechanisms with the emergence of tyrosine kinase inhibitor (TKI)-resistance. To this end, we conducted affinity purification and quantitative mass spectrometry-based proteomic profiling of human leukocyte antigen (HLA) Class I-presented immunopeptides and Class I-interacting proteins. This large-scale dataset revealed that the Class I-presented immunopeptidome was suppressed in two third-generation EGFR TKI, osimertinib-resistant lung adenocarcinoma cell lines compared to their isogenic TKI-sensitive counterparts. The whole-cell proteomic profiling show that antigen presentation complex proteins and immunoproteasome were downregulated upon EGFR TKI resistance. Furthermore, HLA class I-interactome profiling demonstrated altered interaction with key apoptosis and autophagy pathway proteins. In summary, our comprehensive multi-proteomic characterization in antigen presentation machinery provides potentially novel evidence of poor immune response in osimertinib-resistant lung adenocarcinoma.Immune checkpoint inhibitor (ICI) therapy has been a paradigm shift in the treatment of cancer. ICI therapy results in durable responses and survival benefit for a large number of tumor types. Osimertinib, a third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) has shown great efficacy treating EGFR mutant lung cancers; however, all patients eventually develop resistance. ICI therapy has not benefitted EGFR mutant lung cancer. Herein, we employed stable isotope labeling by amino acids in cell culture (SILAC) quantitative mass spectrometry-based proteomics to investigate potential immune escape molecular mechanisms in osimertinib resistant EGFR mutant lung adenocarcinoma by interrogating the alterations in the human leukocyte antigen (HLA) Class I-presented immunopeptidome, Class I-interactome, and the whole cell proteome between isogenic osimertinib-sensitive and -resistant human lung adenocarcinoma cells. Our study demonstrates an overall reduction in HLA class I-presented immunopeptidome and downregulation of antigen presentation core complex (e.g., TAP1 and ERAP1/2) and immunoproteasome in osimertinib resistant lung adenocarcinoma cells. Several key components in autophagy pathway are differentially altered. S100 proteins and SLC3A2 may play critical roles in reduced antigen presentation. Our dataset also includes ~1000 novel HLA class I interaction partners and hundreds of Class I-presented immunopeptides in EGFR mutant lung adenocarcinoma. This large-scale unbiased proteomics study provides novel insights and potential mechanisms of immune evasion of EGFR mutant lung adenocarcinoma.

Effective degradation of EGFRL858R+T790M mutant proteins by CRBN-based PROTACs through both proteosome and autophagy/lysosome degradation systems.

Targeted therapy of treating patients with specific tyrosine kinase inhibitors (TKIs) is currently the standard care for epidermal growth factor receptor (EGFR) mutant non-small cell lung cancer. However, the inevitably developed drug resistance in patients to EGFR TKIs is the biggest obstacle for cancer targeted therapy. About 60% of drug resistance to the 1st generation of EGFR TKIs was resulted from an acquired T790M mutation in the kinase domain of EGFR protein. Proteolysis targeting chimera (PROTAC) is a lately-developed technology to target point of interest proteins for degradation. Because EGFR-mutant lung cancers are highly dependent on EGFR proteins, designing specific PROTAC molecules to degrade EGFR proteins from cancer cells provides a very promising strategy to treat such patients and eradicate drug resistance. Currently, there is no cereblon (CRBN)-based PROTAC reported able to degrade T790M-containing EGFR resistant proteins. In this study, we synthesized two novel CRBN-based EGFR PROTACs, SIAIS125 and SIAIS126, based on EGFR inhibitor canertinib and cereblon ligand pomalidomide. These two degraders displayed potent and selective antitumor activities in EGFR TKI resistant lung cancer cells. Firstly, they could selectively degrade EGFRL858R+T790M resistant proteins in H1975cells at the concentration of 30-50nM, and EGFREx19del proteins in PC9 cells. But they did not degrade EGFREx19del+T790M mutant proteins in PC9Brca1 cells or wild type EGFR in A549 lung cancer cells. They could also selectively inhibit the growth of EGFR mutant lung cancer cells but not that of normal cells or A549cells. Secondly, the degradation of EGFRL858R+T790M proteins was long lasting up to 72h. Thirdly, these degraders displayed better inhibition of EGFR phosphorylation in H1975cells and PC9Brca1 cells comparing to canertinib. Finally, these degraders could also induce significant apoptosis and cell cycles arrest in H1975cells. Pre-incubation with canertinib, pomalidomide or ubiquitination inhibitor MLN4924 totally blocked EGFR degradation by PROTACs. Mechanistic studies showed that PROTAC could induce autophagy in lung cancer cells. PROTAC-induced EGFR degradation acted through both ubiquitin/proteosome system and ubiquitin/autophagy/lysosome system. Elevating autophagy activities enhanced EGFR degradation and cell apoptosis induced by PROTACs. Our research not only offered a novel PROTAC tool to target EGFR TKI drug resistance in lung cancer, but also firstly demonstrated that the involvement of autophagy/lysosome system in PROTAC- mediated target protein degradation.

P76.09 A Comparison of Sequential EGFR-TKI Therapy Versus First-Line Osimertinib in NSCLC: A Multi-Center, Retrospective Study

Lung cancer remains the deadliest form of cancer. Several driver mutations have been identified of which targeted tyrosine kinase inhibitors (TKIs) have shown favorable response. Epidermal growth factor receptor (EGFR) is the most common driver mutation and is present in approximately 15% of adenocarcinomas. There are currently several TKIs approved for the use of EGFR mutated lung cancer. The FLAURA trial showed a progression free survival (PFS) and overall survival (OS) benefit with osimertinib compared to first generation EGFR TKIs. There is a paucity of data to support using a first or second generation EGFR TKI after progression on osimertinib. In this study, we aim to assess the outcomes of EGFR mutated lung cancer patients being treated with a first or second generation EGFR TKI compared to osimertinib. An IRB approved, multi-center, retrospective review of lung cancer patients receiving EGFR TKIs between 2014 and 2019 was conducted. Patients were included in this review if they had received an EGFR TKI for metastatic lung cancer in the front line setting. Patients were excluded if they had an active concomitant cancer, de novo T790M mutation, no EGFR mutations, or who were treated with chemotherapy as first line therapy. EGFR TKI was dichotomized as osimertinib vs all other EGFR TKIs. PFS and OS was estimated using the Kaplan-Meier product-limit method and first line EGFR TKI was compared using the log-rank test. A Cox proportional hazards model was used to examine the association between PFS and OS and EGFR TKI and various patient factors. A total of 172 were included in the analysis, 52 (30.2%) received osimertinib and 120 (69.8%) received another EGFR TKI (afatinib=25, gefitinib=1, erlotinib=94) as first line treatment. All but three of these patients (98%) were never or former smokers and 35% of patients had baseline brain metastasis. Sixty percent of patients had an exon 19 deletion, 33% exon 21 mutation and 7% had another EGFR mutation. The PFS rates at 12 and 18 months were 79.5% and 69.8% in the osimertinib group and 64.2% and 39.3% in the other EGFR TKI groups, respectively (p<0.0036). The adjusted Hazard Ratio (HR) for PFS (reference: osimertinib) was 2.59 (95% CI: 1.31 to 5.11) p<0.0064. Estimated OS at 12 and 18 months were 94.2% and 80.2% in the osimertinib group and 93.9% and 84.1% in the other EGFR TKI groups, respectively (p<0.6382). The adjusted HR for OS was 0.95 (95% CI, 0.37 to 2.44) p<0.9128. In this single institution retrospective review, osimertinib demonstrated a greater PFS compared to other EGFR TKIs at 12 and 18 months. Estimated OS were no different between the two groups. Additional follow up is needed to solidify the real world OS benefit of osimertinib to other EGFR TKIs.