EGFR-mutant Lung Adenocarcinoma Research Articles

Prognostic value of combining clinical factors, 18F-FDG PET-based intensity, volumetric features, and deep learning predictor in patients with EGFR-mutated lung adenocarcinoma undergoing targeted therapies: a cross-scanner and temporal validation study.

To investigate the prognostic value of 18F-FDG PET-based intensity, volumetric features, and deep learning (DL) across different generations of PET scanners in patients with epidermal growth factor receptor (EGFR)-mutated lung adenocarcinoma receiving tyrosine kinase inhibitor (TKI) treatment. We retrospectively analyzed the pre-treatment 18F-FDG PET of 217 patients with advanced-stage lung adenocarcinoma and actionable EGFR mutations who received TKI as first-line treatment. Patients were separated into analog (n = 166) and digital (n = 51) PET cohorts. 18F-FDG PET-derived intensity, volumetric features, ResNet-50 DL of the primary tumor, and clinical variables were used to predict progression-free survival (PFS). Independent prognosticators were used to develop prediction model. Model was developed and validated in the analog and digital PET cohorts, respectively. In the analog PET cohort, female sex, stage IVB status, exon 19 deletion, SUVmax, metabolic tumor volume, and positive DL prediction independently predicted PFS. The model devised from these six prognosticators significantly predicted PFS in the analog (HR = 1.319, p < 0.001) and digital PET cohorts (HR = 1.284, p = 0.001). Our model provided incremental prognostic value to staging status (c-indices = 0.738 vs. 0.558 and 0.662 vs. 0.598 in the analog and digital PET cohorts, respectively). Our model also demonstrated a significant prognostic value for overall survival (HR = 1.198, p < 0.001, c-index = 0.708 and HR = 1.256, p = 0.021, c-index = 0.664 in the analog and digital PET cohorts, respectively). Combining 18F-FDG PET-based intensity, volumetric features, and DL with clinical variables may improve the survival stratification in patients with advanced EGFR-mutated lung adenocarcinoma receiving TKI treatment. Implementing the prediction model across different generations of PET scanners may be feasible and facilitate tailored therapeutic strategies for these patients.

EGFR-Mutated Lung Adenocarcinoma with Li-Fraumeni Syndrome: The Imperative for Germline Testing in Patients with a Family History, A Case Report

EGFR-Mutated Lung Adenocarcinoma with Li-Fraumeni Syndrome: The Imperative for Germline Testing in Patients with a Family History, A Case Report

Transformation of adenocarcinoma into small cell lung cancer as one of the mechanisms of acquired resistance to anti-EGFR tyrosine kinase inhibitors

Transformation of adenocarcinoma into small cell lung cancer (SCLC) is a rare and unique biological property of a cancer cell that is responsible for the mechanism of acquired resistance to EGFR tyrosine kinase inhibitors. There are very few clinical observations of phenotypic cellular transformation during metastatic progression of lung cancer in the literature. The aim of the work is to demonstrate clinical observation of phenotypic transformation of metastatic EGFR-mutated adenocarcinoma into small cell lung cancer with neuroendocrine differentiation during therapy with tyrosine kinase inhibitors. Case report. Due to the rarity of this biological phenomenon, we describe our own observation of the transformation of EGFR-mutated metastatic adenocarcinoma into DCLC with neuroendocrine differentiation, which occurred in a 42-year-old woman during treatment with gefitinib. Conclusions. Transformation and changes in cell phenotype during tyrosine kinase inhibitor therapy were the cause of resistance and failure of further treatment with osimertinib in the second line. It was concluded that it is necessary to consider this mechanism of resistance in clinical practice and to perform repeat biopsies during metastatic progression in patients with EGFR-mutated lung adenocarcinoma.

Simultaneous Acquisition of T790M Mutation and SCLC Transformation during Targeted Therapy in EGFR-Mutated Lung Adenocarcinoma: A Rare Case Report

Simultaneous Acquisition of T790M Mutation and SCLC Transformation during Targeted Therapy in EGFR-Mutated Lung Adenocarcinoma: A Rare Case Report

Identification of risk factors of EGFR-TKIs primary resistance in lung adenocarcinoma patients and construction of a risk predictive model: a case-control study.

Lung cancer is one of the malignancies with the highest incidence and mortality rates. Epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) are recommended as the first-line treatment for patients with EGFR-mutated lung adenocarcinoma (LUAD). However, some patients with EGFR-sensitive mutations develop primary resistance to EGFR-TKIs. This study aims to analyze the clinical characteristics of LUAD patients with primary resistance to EGFR-TKIs, identify independent risk factors for primary resistance, and establish a risk predictive model to provide reference for clinical decision-making. We collected data from LUAD patients with EGFR-sensitive mutations (19del/21L858R) who were hospitalized in our institution between 2020 and 2022 and received first-generation EGFR-TKIs with follow-up exceeding 6 months. These patients were categorized into primary resistance and sensitive groups based on treatment outcomes. We compared general clinical data, laboratory tests, and tumor-related characteristics between the two groups, analyzed risk factors for primary resistance to EGFR-TKIs, and constructed a risk predictive model. The model's predictive value was comprehensively assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curves. Serum neuron-specific enolase (NSE) concentration (P=0.03), serum pro-gastrin-releasing peptide (ProGRP) concentration (P=0.01), and Ki67 expression (P<0.001) were identified as independent risk factors for primary resistance to EGFR-TKIs in LUAD. The combined presence of these three risk factors had the highest predictive value [area under the curve (AUC) =0.975, P<0.001]. We constructed a predictive model for the risk of primary resistance to EGFR-TKIs in LUAD patients, incorporating these three parameters, and represented it through a visually interpretable nomogram. The calibration curve of the nomogram demonstrated its strong predictive ability. Further decision curve analysis indicated the model's clinical utility. Based on a single-center retrospective case-control study, we identified serum NSE concentration, ProGRP concentration, and Ki67 expression as independent risk factors for primary resistance to EGFR-TKIs in LUAD patients. We constructed and validated a risk predictive model based on these findings. This predictive model holds promise for clinical application, aiding in the development of personalized treatment strategies and providing a scientific basis for early identification of primary resistance patients.

Abstract 1221: Selective translational activation of PBK (PDZ- binding kinase) reveals a molecular vulnerability of drug-tolerant persister cells to targeted therapies in EGFR-mutant lung adenocarcinoma

Abstract In lung adenocarcinoma (LUAD), EGFR-targeted therapies often result in incomplete tumor responses followed by disease progression caused by acquired resistance. As EGFR mutations are truncal (i.e., present in every cell of a tumor), it remains unclear why a fraction of tumor cells can survive in the presence of drug treatment. It is increasingly recognized that drug-tolerant persister cells (DTPCs) can escape selective drug pressure and are important drivers of therapy failure and tumor relapse. The mechanisms underlying tumor cell adaptation and survival of DTPCs during therapy are not fully understood.Using EGFR-mutant LUAD cell lines treated with osimertinib, we unexpectedly observed that DTPCs display uncoupled mRNA and protein variations of PBK (PDZ Binding Kinase), a spindle assembly serine/threonine protein kinase. Mechanistically we discovered that although global protein synthesis is decreased upon osimertinib treatment, PBK translation is selectively maintained in DTPCs.The establishment and survival of DTPCs following EGFR inhibition is critically dependent on PBK, as genetic depletion of PBK reduces persistence to osimertinib treatment in vitro. PBK knockout leads to suppression of ERK1/2 reactivation following EGFR inhibition, and results in decreased expression of ZEB1 and Vimentin, key effectors of epithelial-to-mesenchymal transition (EMT), a hallmark of the DTPC phenotype. Consistently, combined treatment with osimertinib and OTS514 (PBK inhibitor) in vitro, reduces the DTPC fraction and decreases the enrichment of EMT-related transcriptional signatures. Similar results were obtained in LUAD patient-derived organoids, used to recapitulate the phenotype of residual disease in patients. In PDX treated with osimertinib, PBK is activated at both residual disease and acquired resistance. Concordantly, combined EGFR/PBK pharmacological inhibition was also effective in reverting osimertinib acquired resistance in vitro. Finally, in matched diagnosis and relapse samples from 7 EGFR-mutant LUAD patients treated with EGFR inhibitors, we observed increased PBK activation at the time of acquired resistance in 5 cases, including 3 EGFRT790M-positive cases, suggesting that PBK activation may co-occur with genetic resistant alterations.Our findings unveil a novel mechanism by which EGFR-mutant lung cancer DTPCs selectively translate PBK mRNA as an adaptive survival mechanism to persist during osimertinib treatment; and provide a therapeutic target of non-genetic drug resistance otherwise unlooked-for in routine transcriptomic analyses. A deeper understanding on the mRNA translational reprogramming in DTPCs is currently performed to uncover therapeutic vulnerabilities to reduce residual disease and delay or revert the emergence of acquired resistance. Citation Format: Camille Leonce, Anne-Laure Désage, Nour El-Houda Mourksi, Geneviève De Souza, Béatrice Vanbervliet, Camille Charrondière, Constance Nicq, Jérémy Néri, Aurélie Swalduz, Laurie Tonon, Eric Cumunel, Nicolas Gadot, Gabriel Ichim, Jean-Jacques Diaz, Christine Lovly, Julien Mazières, Mayeul Tabutin, Maurice Pérol, Sylvie Lantuejoul, Olivier Calvayrac, Fabien Forest, Virginie Marcel, Pierre Saintigny, Sandra Ortiz-Cuaran. Selective translational activation of PBK (PDZ- binding kinase) reveals a molecular vulnerability of drug-tolerant persister cells to targeted therapies in EGFR-mutant lung adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1221.

Abstract 1226: Genomically encoded lineage plasticity drives resistance to EGFR targeted therapy in lung adenocarcinoma

Abstract EGFR-mutant lung adenocarcinoma (LUAD) represents 20% of all non-small cell lung carcinomas, with most patients presenting with incurable metastatic disease. Treatment with mutant-selective EGFR tyrosine kinase inhibitor (TKI) therapies such as osimertinib, the current standard of care for metastatic EGFR-mutant LUAD, results in greater overall and progression-free survival. However, all patients eventually relapse. Uncovering the mechanisms driving primary and acquired resistance to osimertinib is therefore critical to improving disease management. Here, we use clinical genomic sequencing (n=47) and single-nucleus RNA (snRNA) sequencing (n=62) to profile a cohort of unmatched treatment-naïve (n=26), on-treatment (n=6), and post-treatment relapsed (n=30) EGFR-mutant LUADs treated with osimertinib. Relapsed tumors are marked by increased tumor mutation burden, along with elevated rates of genome doubling and loss-of-heterozygosity. We derived expression-based signatures of LUAD, lung squamous cell carcinoma (LUSC), and small cell lung carcinoma (SCLC) and applied them to tumor cells across our cohort. Relapsed tumors had a marked decrease in LUAD gene signature expression compared to untreated tumors and accompanying increases in epithelial-mesenchymal transition (EMT) and stemness markers, consistent with dedifferentiation. Notably, tumors harboring secondary mutations to EGFR, MET, or other MAPK pathway genes and showing sustained MAPK signaling retained a more differentiated state. Patients lacking these secondary on-target or bypass mutations were more likely to experience relapse with histological transdifferentiation, marked by complete loss of LUAD signatures, and accompanying increases in LUSC or SCLC signatures. Phenotype matching of tumor cells to normal cells from the developing fetal lung revealed enrichment of airway progenitor populations in non-histologically transformed treatment-resistant patients, in contrast to a proportion of late bud-tip and club-like epithelial cells which predominated in treatment-naïve samples. In rare cases, we observed subpopulations of basal stem-like progenitors in otherwise well-differentiated pre-treatment tumors. In summary, single-cell mapping of histological and developmental phenotypes has revealed divergent evolutionary trajectories during the acquisition of resistance to osimertinib, defined by MAPK signaling reactivation or by loss of LUAD identity and histological transformation respectively. Citation Format: Matthew Zatzman, Alvaro Quintanal-Villalonga, Sohrab Salehi, Christina Falcon, Nicholas Ceglia, Sohrab P. Shah, Charles M. Rudin, Helena A. Yu. Genomically encoded lineage plasticity drives resistance to EGFR targeted therapy in lung adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1226.

Abstract 2004: CDC7 inhibition prevents neuroendocrine transformation in the lung and prostate through MYC degradation

Abstract Neuroendocrine (NE) transformation occurs as a mechanism of resistance to targeted therapy in up to 14% and 30% of EGFR-mutant lung and AR-dependent prostate adenocarcinomas, respectively, leading to poor prognosis. Even if we know the tumor population at high risk of transformation (TP53/RB1-mutated), no therapies to prevent NE relapse are currently available. To identify therapeutic vulnerabilities for tumors undergoing NE transformation, we performed an in vitro CRISPR screen in a NE-transformed lung tumor model. This screen identified CDC7, involved in DNA replication and DNA damage response, as a potential therapeutic target in this setting. Proteogenomic analyses revealed CDC7 upregulation in lung and prostate clinical samples undergoing NE transformation, detected already in pre-transformation adenocarcinomas. These results indicated that CDC7 expression is induced already at early steps of transformation. Consistently, TP53/RB1-mutated lung and prostate adenocarcinomas exhibited higher CDC7 expression than their double wild-type counterparts. Combined ChIP-seq and promoter reporter assays indicated that CDC7 expression was directly regulated by TP53 and RB1 inactivation. Importantly, TP53/RB1-inactivation induced sensitivity to the CDC7 inhibitor simurosertib, unraveling a therapeutic vulnerability in tumors at high risk of NE transformation. Thus, we tested the combination of simurosertib with targeted therapy in vivo in different lung and prostate patient-derived models of NE transformation, namely TP53/RB1-knock out adenocarcinomas known to undergo NE transformation on targeted therapy. In these, simurosertib was able to suppress NE transformation and dramatically delay tumor relapse. Trajectory analysis on single-cell transcriptomic data for such models revealed a NE transformation transcriptional program occurring already in the untreated tumors before transformation. Remarkably, simurosertib treatment reverted this transcriptomic state and induced a reversion to the original adenocarcinoma transcriptomic profile. CDC7 inhibition led to increased proteasomal activity and degradation of MYC, a stemness transcription factor involved in NE transformation. Ectopic overexpression of MYCT58A, a proteasome degradation-resistant MYC isoform, rescued the NE phenotype in these transformation models, suggesting that CDC7 inhibition-induced MYC degradation is the mechanism by which NE transformation is prevented. In sum, CDC7 inhibition may suppress, or at least dramatically delay NE transformation in patients with lung and prostate adenocarcinomas at high risk of transformation, by inducing MYC proteasomal degradation. The clinical availability of CDC7 inhibitors, currently in phase II clinical trials after demonstrating tolerability and preliminary efficacy, will allow rapid translation of these results into the clinics. Citation Format: Alvaro Quintanal-Villalonga, Fathema Uddin, Kenta Kawasaki, Esther Redin, Vidushi Durani, Amin Sabet, Wouter Karthaus, Yingqian A. Zhan, Samir Zaidi, Moniquetta Shaffer, Harsha Sridhar, Juan Qiu, Parvathy Manoj, Elisa De Stanchina, Michael C. Haffner, Charles L. Sawyers, Charles M. Rudin. CDC7 inhibition prevents neuroendocrine transformation in the lung and prostate through MYC degradation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2004.

Abstract 5853: Regulatory network inference of lung adenocarcinoma drug-tolerant persister cells

Abstract Despite the effectiveness of the latest generation of cancer drugs, partial tumor response and subsequent disease relapse is commonly observed in patients. Recent evidence suggests that treatment resistance emerges from drug-tolerant persister cells (DTPC) that survive through non-genetic tumor cell adaptation. Although DTPC are mostly slow-cycling, a rare subset can re-enter the cell cycle under constitutive presence of treatment. Understanding how DTPC dynamically remodel their molecular portraits at the single-cell level may provide high-resolution insights into the molecular circuits associated with adaptive survival to therapy.Here, we use single-cell RNA sequencing (scRNA-seq) to identify potential mechanisms that promote survival of DTPC and decipher their underlying gene regulatory networks (GRNs), in a model of EGFR-mutant lung adenocarcinoma treated with osimertinib (EGFR inhibitor). Gene expression analysis revealed fewer cell states in DTP compared to treatment-naïve cells (TN). We confirmed the acquisition of DTPC hallmarks (e.g., high epithelial-mesenchymal transition, slow-cycling phenotype, deficient DNA repair). We also identified subpopulations of cells that display intermediate transcriptional states: a pre-existing DTP-like state in a bulk of TN cells, and DTPC with enriched cell cycle signatures, evoking a phenotype of cycling DTPC. To characterize the GRN that govern TN cells, DTPC and the intermediate cell states, we applied the network inference tool PYSCENIC, which associates transcription factors (TFs) to their candidate target genes (TGs) on the basis of the scRNA-seq data and enrichment of TF binding motifs in the genomic regions around TGs. The resulting (GRN) consisted of 5 TF modules clustered on the basis of correlated TF activity.This analysis revealed that, compared to TN cells, DTPC and the intermediate cell states display a marked decreased expression of TFs and TGs involved in mRNA splicing, and more specifically in the initiation of spliceosome assembly through E-complex and A-complex formation. Interestingly, the splicing-related TFs all appear to have affinity for binding to a GCCxC consensus motif or close variant in genes (i.e., SNRPB and SNRPE) that code for key effectors of these initiation complexes. This pilot study highlights that scRNA-seq analyses coupled with inference of regulatory networks might enable the identification of molecular mechanisms that potentially trigger cell state transitions during drug-tolerance. The role of altered mRNA splicing in persistence to EGFR-targeted therapies will be explored experimentally in patient-derived cell lines and 3D organoid cultures. Citation Format: Lisa Chabrier, Camille Leonce, Raphael Schneider, Cyril Degletagne, Pierre Saintigny, Anton Crombach, Sandra Ortiz-Cuaran. Regulatory network inference of lung adenocarcinoma drug-tolerant persister cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5853.

Clinical characteristics and MRI based radiomics nomograms can predict iPFS and short-term efficacy of third-generation EGFR-TKI in EGFR-mutated lung adenocarcinoma with brain metastases

BackgroundPredicting short-term efficacy and intracranial progression-free survival (iPFS) in epidermal growth factor receptor gene mutated (EGFR-mutated) lung adenocarcinoma patients with brain metastases who receive third-generation epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) therapy was of great significance for individualized treatment. We aimed to construct and validate nomograms based on clinical characteristics and magnetic resonance imaging (MRI) radiomics for predicting short-term efficacy and intracranial progression free survival (iPFS) of third-generation EGFR-TKI in EGFR-mutated lung adenocarcinoma patients with brain metastases.MethodsOne hundred ninety-four EGFR-mutated lung adenocarcinoma patients with brain metastases who received third-generation EGFR-TKI treatment were included in this study from January 1, 2017 to March 1, 2023. Patients were randomly divided into training cohort and validation cohort in a ratio of 5:3. Radiomics features extracted from brain MRI were screened by least absolute shrinkage and selection operator (LASSO) regression. Logistic regression analysis and Cox proportional hazards regression analysis were used to screen clinical risk factors. Single clinical (C), single radiomics (R), and combined (C + R) nomograms were constructed in short-term efficacy predicting model and iPFS predicting model, respectively. Prediction effectiveness of nomograms were evaluated by calibration curves, Harrell’s concordance index (C-index), receiver operating characteristic (ROC) curves and decision curve analysis (DCA). Kaplan-Meier analysis was used to compare the iPFS of high and low iPFS rad-score patients in the predictive iPFS R model and to compare the iPFS of high-risk and low-risk patients in the predictive iPFS C + R model.ResultsOverall response rate (ORR) was 71.1%, disease control rate (DCR) was 91.8% and median iPFS was 12.67 months (7.88–20.26, interquartile range [IQR]). There were significant differences in iPFS between patients with high and low iPFS rad-scores, as well as between high-risk and low-risk patients. In short-term efficacy model, the C-indexes of C + R nomograms in training cohort and validation cohort were 0.867 (0.835-0.900, 95%CI) and 0.803 (0.753–0.854, 95%CI), while in iPFS model, the C-indexes were 0.901 (0.874–0.929, 95%CI) and 0.753 (0.713–0.793, 95%CI).ConclusionsThe third-generation EGFR-TKI showed significant efficacy in EGFR-mutated lung adenocarcinoma patients with brain metastases, and the combined line plot of C + R can be utilized to predict short-term efficacy and iPFS.

Comparing the Efficacy of Two Generations of EGFR-TKIs: An Integrated Drug-Disease Mechanistic Model Approach in EGFR-Mutated Lung Adenocarcinoma.

Mutationsin epidermal growth factor receptor (EGFR) are found in approximately 48% of Asian and 19% of Western patients with lung adenocarcinoma (LUAD), leading to aggressive tumor growth. While tyrosine kinase inhibitors (TKIs) like gefitinib and osimertinib target this mutation, treatments often face challenges such as metastasis and resistance. To address this, we developed physiologically based pharmacokinetic (PBPK) models for both drugs, simulating their distribution within the primary tumor and metastases following oral administration. These models, combined with a mechanistic knowledge-based disease model of EGFR-mutated LUAD, allow us to predict the tumor's behavior under treatment considering the diversity within the tumor cells due to different mutations. The combined model reproduces the drugs' distribution within the body, as well as the effects of both gefitinib and osimertinib on EGFR-activation-induced signaling pathways. In addition, the disease model encapsulates the heterogeneity within the tumor through the representation of various subclones. Each subclone is characterized by unique mutation profiles, allowing the model to accurately reproduce clinical outcomes, including patients' progression, aligning with RECIST criteria guidelines (version 1.1). Datasets used for calibration came from NEJ002 and FLAURA clinical trials. The quality of the fit was ensured with rigorous visual predictive checks and statistical tests (comparison metrics computed from bootstrapped, weighted log-rank tests: 98.4% (NEJ002) and 99.9% (FLAURA) similarity). In addition, the model was able to predict outcomes from an independent retrospective study comparing gefitinib and osimertinib which had not been used within the model development phase. This output validation underscores mechanistic models' potential in guiding future clinical trials by comparing treatment efficacies and identifying patients who would benefit most from specific TKIs. Our work is a step towards the design of a powerful tool enhancing personalized treatment in LUAD. It could support treatment strategy evaluations and potentially reduce trial sizes, promising more efficient and targeted therapeutic approaches. Following its consecutive prospective validations with the FLAURA2 and MARIPOSA trials (validation metrics computed from bootstrapped, weighted log-rank tests: 94.0% and 98.1%, respectively), the model could be used to generate a synthetic control arm.

Bevacizumab improved prognosis for advanced EGFR-mutant lung adenocarcinoma with brain metastasis receiving cerebral radiotherapy.

This study aimed to determine whether the combined use of bevacizumab could improve overall survival (OS) in patients with brain metastasis (BM), epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC) undergoing cerebral radiotherapy. A total of 237 patients with EGFR-mutant lung adenocarcinoma and BM met the inclusion criteria for this retrospective study, including 102 patients in the bevacizumab treatment group and 135 in the non-bevacizumab group. The Kaplan-Meier method was used for survival analysis. Univariate and multivariate analyses were performed to identify EGFR-mutated BM prognostic factors for these patients. At the end of the last follow-up period, 176 patients (74.3%) had died, and the median overall survival (OS) was 34.2months. We observed a significant difference in the median OS between the bevacizumab and non-bevacizumab groups (45.8months vs 30.0months, P < 0.0001). Among the 178 (75.1%) patients who received cerebral radiotherapy, the median OS of patients in the bevacizumab + cerebral radiotherapy group was 45.8months versus 32.0months in the non-bevacizumab + cerebral radiotherapy group, respectively (P = 0.0007). Patients treated with bevacizumab after cerebral radiotherapy had a longer median OS than patients treated with bevacizumab before cerebral radiotherapy (59.4months vs 33.7months, P = 0.0198). In the univariate analysis, smoking status, Lung-molGPA scores, and bevacizumab therapy showed correlations (HR = 1.450, P = 0.045; HR = 0.700, P = 0.023; HR = 0.499, P < 0.001). Multivariate analysis showed that bevacizumab therapy alone (hazard ratio [HR] = 0.514; P < 0.001) was independently associated with improved OS. In patients with BM from EGFR-mutated NSCLC, cerebral radiotherapy with bevacizumab markedly improved OS. This improvement was more evident after cerebral radiotherapy.

NEAT1_1 confers gefitinib resistance in lung adenocarcinoma through promoting AKR1C1-mediated ferroptosis defence

Gefitinib is one of the most extensively utilized epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) for treating advanced lung adenocarcinoma (LUAD) patients harboring EGFR mutation. However, the emergence of drug resistance significantly compromised the clinical efficacy of EGFR-TKIs. Gaining further insights into the molecular mechanisms underlying gefitinib resistance holds promise for developing novel strategies to overcome the resistance and improve the prognosis in LUAD patients. Here, we identified that the inhibitory efficacy of gefitinib on EGFR-mutated LUAD cells was partially dependent on the induction of ferroptosis, and ferroptosis protection resulted in gefitinib resistance. Among the ferroptosis suppressors, aldo-keto reductase family 1 member C1 (AKR1C1) exhibited significant upregulation in gefitinib-resistant strains of LUAD cells and predicted poor progression-free survival (PFS) and overall survival (OS) of LUAD patients who received first-generation EGFR-TKI treatment. Knockdown of AKR1C1 partially reversed drug resistance by re-sensitizing the LUAD cells to gefitinib-mediated ferroptosis. The decreased expression of miR-338-3p contributed to the aberrant upregulation of AKR1C1 in gefitinib-resistant LUAD cells. Furthermore, upregulated long non-coding RNA (lncRNA) nuclear paraspeckle assembly transcript 1_1 (NEAT1_1) sponged miR-338-3p to neutralize its suppression on AKR1C1. Dual-luciferase reporter assay and miRNA rescue experiment confirmed the NEAT1_1/miR-338-3p/AKR1C1 axis in EGFR-mutated LUAD cells. Gain- and loss-of-function assays demonstrated that the NEAT1_1/miR-338-3p/AKR1C1 axis promoted gefitinib resistance, proliferation, migration, and invasion in LUAD cells. This study reveals the effects of NEAT1_1/miR-338-3p/AKR1C1 axis-mediated ferroptosis defence in gefitinib resistance in LUAD. Thus, targeting NEAT1_1/miR-338-3p/AKR1C1 axis might be a novel strategy for overcoming gefitinib resistance in LUAD harboring EGFR mutation.

EGFR-mutated lung adenocarcinoma with choroidal oligometastasis during treatment with gefitinib: a case report

AbstractThe patient was a 74-year-old woman who was diagnosed with lung adenocarcinoma, clinical Stage IIIA. Induction chemoradiation was performed followed by right upper lobectomy and lymph node dissection. Because of positive pleural effusion cytology, which was proven after surgery, the patient was diagnosed with pathological Stage IVA with EGFR L858R mutation. At 17 months after the administration of gefitinib, left choroidal metastasis appeared. Stereotactic irradiation and ruthenium small-beam radiation were effective; however, the metastatic lesion showed regrowth 7 months after these treatments. Because the patient’s choroidal oligometastasis was resistant to conservative therapy, left ophthalmectomy was performed. EGFR mutations (L858R and E709K) were detected in the resected choroidal tumor. The patient continued to take gefitinib. However, a neoplastic lesion developed on the optic nerve adjacent to the resected posterior eye segment. The lesion was treated with stereotactic radiation, gefitinib was switched to afatinib 30 mg, and the patient remains alive and disease free for 11 months.

Efficacy of Definitive Radiotherapy for Patients with Clinical Stage IIIB or IIIC Lung Adenocarcinoma and Epidermal Growth Factor Receptor (EGFR) Mutations Treated Using First- or Second-Generation EGFR Tyrosine Kinase Inhibitors.

The effectiveness of definitive radiotherapy (RT) for patients with clinical stage IIIB or IIIC lung adenocarcinoma and epidermal growth factor receptor (EGFR) mutations who received first- or second-generation EGFR tyrosine kinase inhibitors (TKIs) is unclear. Taiwan Cancer Registry data were used in this retrospective cohort study to identify adult patients diagnosed with EGFR-mutated stage IIIB or IIIC lung adenocarcinoma between 2011 and 2020. Patients treated with first- or second-generation EGFR TKIs were classified into RT and non-RT groups. Propensity score (PS) weighting was applied to balance covariates between groups. The primary outcome was overall survival (OS), and the incidence of lung cancer mortality (ILCM) was considered as a supplementary outcome. Additional supplementary analyses were conducted to assess the robustness of the findings. Among 270 eligible patients, 41 received RT and 229 did not. After a median follow-up of 46 months, PS-weighted analysis showed the PS-weighted hazard ratio of death for the RT group compared to the non-RT group was 0.94 (95% CI: 0.61-1.45, p = 0.78). ILCM rates did not differ significantly between the two groups. Supplementary analyses yielded consistent results. The addition of definitive RT to first- or second-generation EGFR TKI treatment does not significantly improve OS of patients with EGFR-mutated stage IIIB or IIIC lung adenocarcinoma. NCT03521154NCT05167851.

Transfer learning–based PET/CT three-dimensional convolutional neural network fusion of image and clinical information for prediction of EGFR mutation in lung adenocarcinoma

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.

MET overexpression correlated with prognosis of EGFR-mutant treatment‑naïve advanced lung adenocarcinoma: a real‑world retrospective study.

About 50-60% treatment-naïve advanced non-small-cell lung cancers were coexistence of epidermal growth factor receptor (EGFR) and mesenchymal epithelial transition (MET) overexpression. However, few studies demonstrated the prognostic value of MET protein expression in untreated EGFR-mutant lung adenocarcinoma (LUAD). A total of 235 EGFR-mutant untreated advanced LUAD patients were retrospectively enrolled. MET expression was determined using immunohistochemistry, and MET positivity was defined as 2 + or 3 + using the METmab scoring algorithm. Progression-free survival (PFS) and overall survival (OS) were analysed according to MET expression status. Independent factors predicting prognosis were identified using multivariate Cox regression analyses. Of the 235 patients, 113 (48.1%) harboured exon 19 deletion (19_del), 103 (43.8%) had exon 21 L858R mutations, and 19 (8.1%) had other mutation types, including exon 21 L861Q, exon 18 G719A/C, exon 20 S768I, and L858R/19_del double mutations. MET-positive expression was observed in 192 (81.7%) cases. There was no significant difference in baseline clinicopathological characteristics between MET positivity and MET negativity groups. Patients were stratified by different EGFR mutation subtypes. MET-positive patients in the L858R mutation subgroup had markedly shorter PFS and OS than MET-negative patients (median PFS: 13 versus 27.5months, p < 0.001; median OS: 29 versus not reached, p = 0.008), but no significant difference was observed in the 19_del subgroup. Multivariate Cox regression analyses indicated that MET positivity was an independent predictor for poor PFS and OS in L858R subgroup (PFS: HR = 3.059, 95% CI 1.552-6.029, p = 0.001; OS: HR = 3.511, 95% CI 1.346-9.160, p = 0.010). Additionally, an inferior survival outcome of MET positivity was observed in the L858R mutation subgroup when treated with EGFR-tyrosine kinase inhibitor (TKI) monotherapy as the first-line regimen (median PFS: 13 versus 36.5months, p < 0.001; median OS: 29 versus not reached, p = 0.012) but not with EGFR-TKI plus platinum doublet chemotherapy. MET positive expression was an independent predictor of poor outcomes in untreated EGFR L858R mutation advanced LUAD patients treated with first-line EGFR-TKI monotherapy.

Induction of Multiple Alternative Mitogenic Signaling Pathways Accompanies the Emergence of Drug-Tolerant Cancer Cells.

Drug resistance can evolve from a subpopulation of cancer cells that initially survive drug treatment and then gradually form a pool of drug-tolerant cells. Several studies have pinpointed the activation of a specific bypass pathway that appears to provide the critical therapeutic target for preventing drug tolerance. Here, we take a systems-biology approach, using proteomics and genomics to examine the development of drug tolerance to EGFR inhibitors in EGFR-mutant lung adenocarcinoma cells and BRAF inhibitors in BRAF-mutant melanoma cells. We found that there are numerous alternative mitogenic pathways that become activated in both cases, including YAP, STAT3, IGFR1, and phospholipase C (PLC)/protein kinase C (PKC) pathways. Our results suggest that an effective therapeutic strategy to prevent drug tolerance will need to take multiple alternative mitogenic pathways into account rather than focusing on one specific pathway.

Chemotherapy versus personalized therapy for EGFR mutant lung adenocarcinoma resistance to EGFR-tyrosine kinase inhibitors: a retrospective dual-center study.

Advanced lung adenocarcinoma patients often develop resistance to EGFR tyrosine kinase inhibitors (EGFR-TKIs), leaving uncertainties regarding subsequent treatment strategies. Although personalized therapy targeting individual acquired resistances (ARs) shows promise, its efficacy has not been systematically compared with platinum-containing doublet chemotherapy, a widely accepted treatment after EGFR-TKIs failure. A retrospective dual-center study was conducted involving patients with advanced lung adenocarcinoma and EGFR mutations who developed resistance to EGFR-TKIs between January 2017 and December 2022. Eligible patients were adults aged 18years or older with an Eastern Cooperative Oncology Group score of 0-1, normal organ function, and no prior chemotherapy. Patients were divided into the chemotherapy group (CG) or personalized therapy group (PG) based on the treatment received after disease progression. The primary endpoints were progression-free survival (PFS) and objective response rate (ORR). Of the 144 patients enrolled, there were 53 patients in the PG and 91 patients in the CG. The PG acquired resistance to EGFR-TKIs through the MET amplification (27, 50%) and small cell lung cancer transformation (16, 30%) and 18% of them reported multiple resistance mechanisms. The ORR of the PG was similar to that of the CG (34% vs. 33%, P = 1.0) and the PFS of the PG patients was not statistically different from that of their CG counterparts [4.2months (95% CI: 3.6-4.8months) vs. 5.3months (95% CI: 4.6-6.0months), P = 0.77]. These findings suggest that the therapeutic efficacy of chemotherapy approximates to that of personalized therapy, which signifies that chemotherapy is still a reliable choice for patients who develop resistance to EGFR-TKIs and that further research is awaited to explore the benefit of personalized treatment.

ASCL1 Drives Tolerance to Osimertinib in EGFR Mutant Lung Cancer in Permissive Cellular Contexts.

Analysis of residual disease following tyrosine kinase inhibitor treatment identified heterogeneous and context-specific mechanisms of drug tolerance in lung cancer that could lead to the development of strategies to forestall drug resistance. See related commentary by Rumde and Burns, p. 1188.