Epidermal Growth Factor Receptor Mutation Status Research Articles

CT-based decision tree model for predicting EGFR mutation status in synchronous multiple primary lung cancers.

The current study aimed to construct a computed tomography (CT)-based decision tree algorithm (DTA) model to predict the epidermal growth factor receptor (EGFR) mutation status in synchronous multiple primary lung cancers (SMPLCs). The demographic and CT findings of 85 patients with molecular profiling for surgically resected SMPLCs were reviewed retrospectively. Least absolute shrinkage and selection operator (LASSO) regression was used to select the potential predictors of EGFR mutation, and a CT-DTA model was developed. Multivariate logistic regression analysis and receiver operating characteristic (ROC) curve analysis were performed to assess the performance of this CT-DTA model. The CT-DTA model was applied to predict the EGFR mutant that had ten binary split, of which eight parameters to accurately categorize the lesions as follows: the presence of bubble-like vacuole sign (19.4% importance in the development of the model), presence of air bronchogram sign (17.4% importance), smoking status (15.7% importance), types of the lesions (14.8% importance), histology (12.6% importance), presence of pleural indentation sign (7.6% importance), gender (6.9% importance), and presence of lobulation sign (5.6% importance). The ROC analysis achieved an area under the curve (AUC) of 0.854. Multivariate logistic regression analysis demonstrated that this CT-DTA model was an independent predictor of EGFR mutation (P<0.001). CT-DTA model is a simple tool to predict the status of EGFR mutation in SMPLC patients and could be considered for treatment decision-making.

Five years after PACIFIC: update on multimodal treatment efficacy based on real-world reports

ABSTRACT Introduction The growing body of real-life data on maintenance treatment with durvalumab suggests that immunological markers of the cancer host interplay may have significant effects on the efficacy of multimodal therapy in patients with unresectable stage III NSCLC. Areas covered We summarize real-world clinical data regarding this new tri-modal approach and report on potential biomarker landscape. Expert opinion The obvious question posed in this context of a very heterogeneous inoperable stage III NSCLC disease is: How can we augment an ability to predict checkpoint inhibition success or failure? Which tools and biomarkers, which clinical metadata and genetic background are relevant and feasible? No single biomarker will ever fully dominate the unresectable stage III NSCLC space, so we advocate multilevel and multivariate analysis of biomarkers. In this particular opinion piece, we explore the impact of PD-L1 expression on tumor cells, neutrophil-to-lymphocyte ratio, EGFR and STK11 mutational status, interferon-gamma signature, and tumor-infiltrating lymphocytes among others.

Association Analysis of Maximum Standardized Uptake Values Based on 18F-FDG PET/CT and EGFR Mutation Status in Lung Adenocarcinoma.

(1) Background: To investigate the association between maximum standardized uptake value (SUVmax) based on 18F-FDG PET/CT and EGFR mutation status in lung adenocarcinoma. (2) Methods: A total of 366 patients were retrospectively collected and divided into the EGFR mutation group (n = 228) and EGFR wild-type group (n = 138) according to their EGFR mutation status. The two groups' general information and PET/CT imaging parameters were compared. A hierarchical binary logistic regression model was used to assess the interaction effect on the relationship between SUVmax and EGFR mutation in different subgroups. Univariate and multivariate logistic regression was used to analyze the association between SUVmax and EGFR mutation. After adjusting for confounding factors, a generalized additive model and smooth curve fitting were applied to address possible non-linearities. (3) Results: Smoking status significantly affected the relationship between SUVmax and EGFR mutation (p for interaction = 0.012), with an interaction effect. After adjusting for age, gender, nodule type, bronchial sign, and CEA grouping, in the smoking subgroup, curve fitting results showed that the relationship between SUVmax and EGFR mutation was approximately linear (df = 1.000, c2 = 3.897, p = 0.048); with the increase in SUVmax, the probability of EGFR mutation gradually decreased, and the OR value was 0.952 (95%CI: 0.908-0.999; p = 0.045). (4) Conclusions: Smoking status can affect the relationship between SUVmax and EGFR mutation status in lung adenocarcinoma, especially in the positive smoking history subgroup. Fully understanding the effect of smoking status will help to improve the accuracy of SUVmax in predicting EGFR mutations.

Applications of radiomics-based analysis pipeline for predicting epidermal growth factor receptor mutation status

BackgroundThis study aimed to develop a pipeline for selecting the best feature engineering-based radiomic path to predict epidermal growth factor receptor (EGFR) mutant lung adenocarcinoma in 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT).MethodsThe study enrolled 115 lung adenocarcinoma patients with EGFR mutation status from June 2016 and September 2017. We extracted radiomics features by delineating regions-of-interest around the entire tumor in 18F-FDG PET/CT images. The feature engineering-based radiomic paths were built by combining various methods of data scaling, feature selection, and many methods for predictive model-building. Next, a pipeline was developed to select the best path.ResultsIn the paths from CT images, the highest accuracy was 0.907 (95% confidence interval [CI]: 0.849, 0.966), the highest area under curve (AUC) was 0.917 (95% CI: 0.853, 0.981), and the highest F1 score was 0.908 (95% CI: 0.842, 0.974). In the paths based on PET images, the highest accuracy was 0.913 (95% CI: 0.863, 0.963), the highest AUC was 0.960 (95% CI: 0.926, 0.995), and the highest F1 score was 0.878 (95% CI: 0.815, 0.941). Additionally, a novel evaluation metric was developed to evaluate the comprehensive level of the models. Some feature engineering-based radiomic paths obtained promising results.ConclusionsThe pipeline is capable of selecting the best feature engineering-based radiomic path. Combining various feature engineering-based radiomic paths could compare their performances and identify paths built with the most appropriate methods to predict EGFR-mutant lung adenocarcinoma in 18FDG PET/CT. The pipeline proposed in this work can select the best feature engineering-based radiomic path.

Healthcare coverage affects survival of EGFR-mutant Thai lung cancer patients.

Despite significant benefits of epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI) treatment in patients with EGFR-mutated NSCLC, access remains limited in Thailand and elsewhere. Retrospective analysis of patients with locally advanced/recurrent NSCLC and known EGFR mutation (EGFRm) status treated at Ramathibodi Hospital (2012-2017). Prognostic factors for overall survival (OS), including treatment type and healthcare coverage, were analyzed using Cox regression. Of 750 patients, 56.3% were EGFRm-positive. After first-line therapy (n=646), 29.4% received no subsequent (second-line) treatment. EGFR-TKI-treated EGFRm-positive patients survived significantly longer than EGFRm-negative patients without EGFR-TKIs (median OS [mOS] 36.4 vs. 11.9 months; hazard ratio HR=0.38 [95%CI 0.32-0.46], P<0.001). Cox regression indicated significantly longer OS in patients with comprehensive healthcare coverage that included reimbursement of EGFR-TKIs, versus basic coverage (mOS 27.2 vs. 18.3 months; adjusted HR=0.73 [95%CI 0.59-0.90]). Compared with best supportive care (BSC; reference), EGFR-TKI-treated patients survived significantly longer (mOS 36.5 months; adjusted HR (aHR)=0.26 [95%CI 0.19-0.34]), and versus chemotherapy alone (14.5 months; aHR=0.60 [95%CI 0.47-0.78]). In EGFRm-positive patients (n=422), relative survival benefit of EGFR-TKI treatment remained highly significant (aHR[EGFR-TKI]=0.19 [95%CI 0.12-0.29]; aHR(chemotherapy only)=0.50 [95%CI 0.30-0.85]; reference:BSC), indicating that healthcare coverage (reimbursement) affected treatment choice and survival. Our analysis describes EGFRm prevalence and survival benefit of EGFR-TKI therapy for EGFRm-positive NSCLC patients treated from 2012-2017, one of the largest such Thai datasets. Together with research by others, these findings contributed evidence supporting the decision to broaden erlotinib access on healthcare schemes in Thailand from 2021, demonstrating the value of local real-world outcome data for healthcare policy decision-making.

Comparison of the radiomics-based predictive models using machine learning and nomogram for epidermal growth factor receptor mutation status and subtypes in lung adenocarcinoma.

The purpose of this study is to develop the predictive models for epidermal growth factor receptor (EGFR) mutation status and subtypes [exon 21-point mutation (L858R) and exon 19 deletion mutation (19Del)] and evaluate their clinical usefulness. Total 172 patients with lung adenocarcinoma were retrospectively analyzed. The analysis of variance and the least absolute shrinkage were used for feature selection from plain computed tomography images. Then, radiomic score (rad-score) was calculated for the training and test cohorts. Two machine learning (ML) models with 5-fold were applied to construct the predictive models with rad-score, clinical features, and the combination of rad-score and clinical features. The nomogram was developed using rad-score and clinical features. The prediction performance was evaluated by the area under the receiver operating characteristic curve (AUC). Finally, decision curve analysis (DCA) was performed using the best ML and nomogram models. In the test cohorts, the AUC of the best ML and the nomogram model were 0.73 (95% confidence interval, 0.59-0.87) and 0.79 (0.65-0.92) in the EGFR mutation groups, 0.83 (0.67-0.99) and 0.85 (0.72-0.97) in the L858R mutation groups, as well as 0.77 (0.58-0.97) and 0.77 (0.60-0.95) in the 19Del groups. The DCA showed that the nomogram models have comparable results with ML models. We constructed two predictive models for EGFR mutation status and subtypes. The nomogram models had comparable results to the ML models. Because the superiority of the performance of ML and nomogram models varied depending on the prediction groups, appropriate model selection is necessary.

Clinical correlations with EGFR circulating tumor DNA testing in all-stage lung adenocarcinoma.

Information on genetic alterations, notably EGFR mutations, is important for guiding non-small-cell lung cancer (NSCLC) treatment. Circulating tumor DNA (ctDNA) analysis represents a less invasive alternative to tissue biopsy for analyzing mutation status, but its clinical value may vary across disease stages. To explore clinical correlates of ctDNA and tissue/plasma-based EGFR mutation (EGFRm) status across all NSCLC stages. Ninety patients were analyzed, representing three cohorts: newly-diagnosed early-stage, advanced-stage, and recurrent NSCLC. Relationships among clinical/surgical parameters, ctDNA, EGFRm status, and survival outcomes were analyzed. Plasma/tissue EGFRm concordance was lower in early-stage (58.6%) than in advanced-stage patients (87.5%). In early-stage patients, ctDNA levels were variable and not significantly associated with clinical/surgical parameters. In advanced-stage patients, time to EGFR-TKI treatment failure (TTF), but not overall survival (OS), was significantly longer in EGFRm-positive vs. EGFRm-negative patients. In patients with recurrent disease, 40% of plasma samples were EGFRT790M-positive at recurrence. In T790M-positive patients, we noted slight trends toward longer OS with vs. without osimertinib treatment and longer OS and TTF with second-line vs. later-line osimertinib. Our results affirm the use of ctDNA testing in advanced-stage and recurrent NSCLC. Further studies on osimertinib as early-line therapy, clinical correlates and the utility of plasma-based testing in early-stage NSCLC are warranted.

Clinicopathological Features and Significance of Epidermal Growth Factor Receptor Mutation in Surgically Resected Early-Stage Lung Adenocarcinoma.

The clinicopathological presentation of early-stage lung adenocarcinoma patients with epidermal growth factor receptor (EGFR) mutations has been seldom studied. Our study enrolled patients with stage I and II lung adenocarcinoma between January 2014 and December 2017 at the National Taiwan University Hospital. Clinicopathological features and prognosis were retrospectively reviewed and analyzed depending on EGFR mutation status. EGFR mutations were detected in 622 (60%) out of 1034 patients. Compared to the group without EGFR mutations, the group with EGFR mutations had more patients above 65 years of age (p < 0.001), more non-lepidic histological subtypes (p < 0.001), higher CEA levels (p = 0.044), higher grade of pleural (p = 0.02) and lymphovascular (p = 0.001) invasion, higher histological grade (p < 0.001), and a more advanced pathological stage (p = 0.022). In multivariate analysis, there was no significant difference in PFS or OS between the EGFR mutant and wild-type groups. In subtype analysis, the tumors with an L858R mutation had a more lepidic predominant histological type (p = 0.019) and less lymphovascular invasion (p = 0.011). No significant differences in PFS or OS were detected between the exon 19 deletion and L858R mutation groups. In early-stage lung adenocarcinoma, EGFR mutation may be considered as a treatment response predictor for tyrosine kinase inhibitors, instead of a predictor of clinical prognosis.

Ten-Year Follow-up Results of Pure Ground-Glass Opacity–Featured Lung Adenocarcinomas After Surgery

Previously, we have demonstrated that the 5-year recurrence-free survival after surgery of pure ground-glass opacity (GGO)-featured lung adenocarcinoma is 100%. This study aimed to reveal the long-term outcomes of these patients 10 years after surgery. Lung adenocarcinoma patients who underwent surgery between December 2007 and December 2013 were reviewed. Patients with pure GGO-featured lung adenocarcinoma were enrolled. Postoperative survival and the risk of developing second primary lung cancer were analyzed. Overall, 308 cases of pure GGO-featured lung adenocarcinomas were included. Of these patients, 226 (73.4%) were female, 268 (87.0%) were nonsmokers, and 187 (60.7%) underwent sublobar resection. The median follow-up period after surgery was 112 months. The 10-year recurrence-free survival rate of these patients was 100%, and 10-year overall survival rate was 96.9%. Both 5-year and 10-year lung cancer-specific survival were 100%. There was no difference in 10-year recurrence-free survival rates between patients who underwent lobectomy or sublobar resection (P= .697). EGFR mutations were detected in 55.6% (84 of 151) of patients who underwent mutational analysis. The risk of developing secondary primary lung cancer for pure GGO-featured lung adenocarcinoma patients at 10 years after resection was 2.4%, and was not correlated with EGFR mutation status (P= .452). No recurrence was observed in patients with pure GGO-featured lung adenocarcinomas 10 years after surgery, even when pathologically evaluated as invasive adenocarcinoma. Pure GGO can be cured by surgery. Surgery is recommended for the appropriate time window with the view to cure. Our study emphasizes that radiologic pure GGO-featured lung adenocarcinomas should be distinguished from other lung adenocarcinomas.

Real-world analysis of the prognostic value of EGFR mutation detection in plasma ctDNA from patients with advanced non-small cell lung cancer.

The plasma sample has emerged as a promising surrogate sample for EGFR mutation detection in advanced non-small cell lung cancer (NSCLC). In clinical practice, whether EGFR variants in baseline plasma ctDNA of advanced NSCLC can predict prognosis in addition to guiding targeted therapy remains to be further explored. In total, 315 NSCLC patients were retrospectively enrolled. EGFR mutation data from tissue detected by ARMS-PCR and paired plasma samples within 1 month of admission detected by SuperARMS or ARMS-PCR were collected. The correlation between baseline plasma ctDNA EGFR mutation status and survival was compared. EGFR mutation detection rates in tumor samples and plasma samples were 65.1% (205/315) and 43.8% (138/315). Referred to tissue results, the consistent rate of test ctDNA EGFR alteration by SuperARMS was higher than that detected by ARMS (79.5% vs. 69.0%, p=0.04), either in stage I-IIIA patients (85.7% vs. 50.0%, p=0.4) or stage IIIB-IV patients (79.1% vs. 69.4%, p=0.04). Patients' treatment status and pathological subtype were the two factors that affected plasma ctDNA EGFR alteration detection accuracy. The concordance in non-adenocarcinoma patients was obviously higher than that in adenocarcinoma (p=0.02), and the concordance in treatment naïve patients was significantly higher than that in relapse patients (p=0.047). In treatment naïve patients, the median PFS (mPFS) in plasma ctDNA EGFR-positive patients was shorter than that in plasma ctDNA EGFR negative patients (7.0 vs. 10.0 months, p=0.01). In relapsed patients, the mPFS in plasma ctDNA EGFR-positive patients was 9.0months versus 11.0months in plasma ctDNA EGFR negative patients (p=0.1). A plasma sample could be an alternative for a molecular test when tissue samples was unavailable. The SuperARMS-PCR detection method has high sensitivity in real-world clinical practice. Furthermore, in patients with stage IIIB-IV, baseline plasma ctDNA EGFR mutation positivity not only guides targeted therapy but also predicts a worse prognosis.

Comparison of Treatment Outcome in EGFR Positive and Negative Patients with Non Small Cell Lung Cancer: A Longitudinal Study

Introduction: Lung cancer is one of the most common malignancies to occur worldwide. Two main subtypes of lung cancer include small cell lung cancer and Non Small Cell Lung Cancer (NSCLC). Patients with advanced stage NSCLC who achieve good response with Tyrosine Kinase Inhibitors (TKI) have been found to have Epidermal Growth Factor Receptor (EGFR) mutation. The first biomarker identified for targeted treatment in lung cancer was EGFR and patients of NSCLC with EGFR mutation have superior survival outcome when treated with targeted therapy as compared to conventional chemotherapy. Aim: To compare the outcome of targeted therapy to mutation to EGFR and conventional therapy in non mutant lung cancer patient of NSCLC. Materials and Methods: The present longitudinal study was conducted in the Department of TB and Respiratory Diseases, Jawaharlal Nehru Medical College and Hospital, Aligarh, Uttar Pradesh, India from July 2017 to November 2019 on a sample size of 80. Patients diagnosed with NSCLC and EGFR mutation status were included in the study. They were started on TKI if tumour was EGFR positive and on conventional chemotherapy (cisplatin plus paclitaxel) if no mutation was detected on histopathology. Among the study group, 35 patients were EGFR positive and started on geftinib (group I), 45 were EGFR negative and received platinum-based chemotherapy (group II). Outcomes were measured in terms of progression-free survival, Overall Survival (OS), and toxicities. Statistical analysis of data was done using Statistical Package for the Social Sciences (SPSS) version 20.0. Results: Among the study group, 35 patients were EGFR positive and started on geftinib (Group I), 45 were EGFR negative and received platinum-based chemotherapy (group II). The mean age of EGFR positive patients was 58.91 years and for EGFR negative patients was 60.11 years. In group I, there was no complete response while 28.5% had partial response, 45.5% had stable disease and 25.7% had progressive disease. In group II, 15.5% patients had complete response, 33.3% had partial response,17.7% had stable disease and 33.3% had progressive disease. Mean progression-free survival in group I (5.65 months) was significantly higher than group II (4.26 months). The mean OS in group I (7.85 months) was slightly higher than group II (6.72 months). Both haematological and non haemaotlogical toxicities were significantly higher in group II. Conclusion: Patients with EGFR positive expression subjected to Gefitinib had significant mean progression-free survival with an acceptable range of non haematological toxicities and no haematological toxicities, as compared to the EGFR negative patients on conventional chemotherapy.

Is there an advantage of monitoring via exosome-based detection of EGFR mutations during treatment in non-small cell lung cancer patients?

We know that detection of EGFR mutations is very important for individual therapy. Nowadays FFPE samples are commonly using to detect the EGFR mutation status. But it has a few handicaps such as, tumor heterogeneity and non-repeatable, it is need to examine mutation statues of EGFR after each treatment regimen for individually treatment of NSCLC patients. Therefore, there is still need to develop non-invasive and useable over and over again approach for monitoring EGFR mutation statues and other genes for individual therapy. So, we aim to examine whether exosomes are good target for detection of EGFR mutation status or not. Pyrosequencing was used to detect, EGFR mutation in FFPE and exosome samples in some NSCLC patients. For the patients given different chemotherapy regime (n=28), PFS was evaluated before and after treatment. In patients who were EGFR positive before treatment, the median PFS for EGFR mutation-positive patients after treatment was 101.7 weeks (95% CI: 0.09-3.21), while for patients who were negative after treatment, the median PFS was 42.43 weeks (95% CI: 0.31- 10.52). Likewise, in patients who were EGFR negative before treatment and EGFR mutation negative after treatment, the PFS was median 52 weeks (95% CI: 0.17-2.84), while in patients who were positive after treatment, the median PFS was 27.57 weeks (95% CI: 0.35-5.58). We show that exosomes are good tools for monitoring EGFR mutation status and exosomes can be use as semi-invasive method for isolation of tumor DNAs for detection of mutation statues for individually treatment of NSCLC patients.

Benchmarking Outcomes for Molecularly Characterized Synchronous Oligometastatic Non-Small-Cell Lung Cancer Reveals EGFR Mutations to Be Associated With Longer Overall Survival.

Local consolidative therapy (LCT) for patients with synchronous oligometastatic non-small-cell lung cancer is an evolving treatment strategy, but outcomes following LCT stratified by genetic mutations have not been reported. We sought to identify genomic associations with overall survival (OS) and progression-free survival (PFS) for these patients. We identified all patients presenting between 2000 and 2017 with stage IV non-small-cell lung cancer and ≤ 3 synchronous metastatic sites. Patients were grouped according to mutational statuses. Primary outcomes included OS and PFS following initial diagnosis. Of 194 included patients, 121 received comprehensive LCT to all sites of disease with either surgery or radiation. TP53 mutations were identified in 40 of 78 (55%), KRAS in 32 of 95 (34%), EGFR in 24 of 109 (22%), and STK11 in nine of 77 (12%). At median follow-up of 96 months, median OS and PFS were 26 (95% CI, 23 to 31) months and 11 (95% CI, 9 to 13) months, respectively. On multivariable analysis, patients with EGFR mutations had lower mortality risk (hazard ratio [HR], 0.53; 95% CI, 0.29 to 0.98; P = .044) compared with wild-type patients, and patients with STK11 mutations had higher risk of progression or mortality (HR, 2.32; 95% CI, 1.12 to 4.79; P = .023) compared with wild-type patients. TP53 and KRAS mutations were not associated with OS or PFS. Among 71 patients with known EGFR mutational status who received comprehensive LCT, EGFR mutations were associated with lower mortality compared with wild-type (HR, 0.45; 95% CI, 0.22 to 0.94; P = .032). When compared with wild-type patients, those with EGFR and STK11 mutations had longer OS and shorter PFS, respectively. EGFR mutations were associated with longer OS among oligometastatic patients treated with comprehensive LCT in addition to systemic therapy.

Brain metastasis magnetic resonance imaging-based deep learning for predicting epidermal growth factor receptor (EGFR) mutation and subtypes in metastatic non-small cell lung cancer.

The preoperative identification of epidermal growth factor receptor (EGFR) mutations and subtypes based on magnetic resonance imaging (MRI) of brain metastases (BM) is necessary to facilitate individualized therapy. This study aimed to develop a deep learning model to preoperatively detect EGFR mutations and identify the location of EGFR mutations in patients with non-small cell lung cancer (NSCLC) and BM. We included 160 and 72 patients who underwent contrast-enhanced T1-weighted (T1w-CE) and T2-weighted (T2W) MRI at Liaoning Cancer Hospital and Institute (center 1) and Shengjing Hospital of China Medical University (center 2) to form a training cohort and an external validation cohort, respectively. A multiscale feature fusion network (MSF-Net) was developed by adaptively integrating features based on different stages of residual network (ResNet) 50 and by introducing channel and spatial attention modules. The external validation set from center 2 was used to assess the performance of MSF-Net and to compare it with that of handcrafted radiomics features. Receiver operating characteristic (ROC) curves, accuracy, precision, recall, and F1-score were used to evaluate the effectiveness of the models. Gradient-weighted class activation mapping (Grad-CAM) was used to demonstrate the attention of the MSF-Net model. The developed MSF-Net generated a better diagnostic performance than did the handcrafted radiomics in terms of the microaveraged area under the curve (AUC) (MSF-Net: 0.91; radiomics: 0.80) and macroaveraged AUC (MSF-Net: 0.90; radiomics: 0.81) for predicting EGFR mutations and subtypes. This study provides an end-to-end and noninvasive imaging tool for the preoperative prediction of EGFR mutation status and subtypes based on BM, which may be helpful for facilitating individualized clinical treatment plans.

Oncogenic driver mutations in Vietnamese patients with lung adenocarcinoma

Mutation profiles of oncogenes play essential roles in cancer therapy, but data on the prevalence of lung cancer oncogenic driver mutations in Vietnamese patients are limited. This study aims to evaluate the mutation status of EGFR, ALK, ROS1, RET and MET and analyze the association of gene mutations with clinicopathological characteristics of lung adenocarcinoma. Of the 179 lung adenocarcinoma tissues, EGFR, ALK, ROS1, RET and MET mutation frequencies were 44.6; 7.9; 3.0; 3.0 and 2.0 percent, respectively. EGFR, ALK, ROS1 and RET alterations tended to be higher in females. Moreover, rearrangements of ALK, ROS and RET were more prevalent in younger lung adenocarcinoma, but skipping at exon 14 MET was more frequent in male and older patients. Stages III and IV seem to accumulate more ALK, RET and MET abnormalities. These findings identified the variation of frequencies of Vietnamese lung adenocarcinoma with different clinicopathological characteristics and established the pioneer data for oncogenic diver mutation of lung cancer in Vietnam.

Rapid determination of the presence of EGFR mutations with DNA-based nanocalipers.

Selecting 1st-line treatment for lung cancer is currently a binary choice, either chemotherapy or targeted medicine, depending on whether EGFR mutations exist. Next-generation sequencing is fully capable of accurately identifying EGFR mutations and guiding the usage of tyrosine kinase inhibitors, but it is highly expensive. Moreover, as the sequencing is not helpful for patients with wild-type EGFR, the long wait for sequencing may delay the chemotherapy and correspondingly increase the risks of cancer progression. To address this issue, a new method for rapidly determining the presence of EGFR mutations is developed in this study. A series of DNA origami-engineered nanocalipers are designed and constructed to determine the EGFR spatial distribution of either mutated EGFR or wild-type EGFR lung cancer cells. The experimental results on cancer cell lines and 9 clinical tissue samples show that compared with wild-type EGFR cells, mutated EGFR cells have narrower EGFR spacing. Hence, the DNA nanocalipers are demonstrated to be capable of determining the presence of EGFR mutations and shrinking the detection period from weeks to hours, compared with sequencing. For determining EGFR mutation status in 9 clinical samples, DNA nanocalipers show 100% consistency with next-generation sequencing.

MRI features and whole-lesion apparent diffusion coefficient histogram analysis of brain metastasis from non-small cell lung cancer for differentiating epidermal growth factor receptor mutation status

To explore the utility of magnetic resonance imaging (MRI) characteristics and whole-lesion apparent diffusion coefficient histogram analysis of brain metastasis from non-small cell lung cancer (NSCLC) in the differentiation of epidermal growth factor receptor (EGFR) mutation status. Forty-eight patients with brain metastases from NSCLC were enrolled in this retrospective study. Patients were subtyped into EGFR mutation (23 cases) and wild-type (25 cases) groups. Whole-lesion histogram metrics were derived from the apparent diffusion coefficient (ADC) maps, and imaging features were evaluated according to conventional MRI. Student's t-test or Mann-Whitney U-test, chi-squared test, and receiver operating characteristic (ROC) curve analysis were performed to discriminate the two groups and to determine the diagnostic efficacy of ADC histogram parameters. EGFR mutation group had more multiple brain metastases, less peritumoural brain oedema (PTBO), and lower peritumoural brain oedema index (PTBO-I) than EGFR wild-type group (all p<0.05). In addition, 90th and 75th percentiles of ADC and maximum ADC in the EGFR mutation group were significantly higher than in the EGFR wild-type group (all p<0.05). Ninetieth percentile of ADC had the highest area under the curve (AUC; 0.711), and it was found to outperform 75th percentile of ADC (AUC, 0.662; p=0.039) and maximum ADC (AUC, 0.681). Whole-lesion ADC histogram analysis and MRI features of brain metastasis from NSCLC are expected to be potential biomarkers to non-invasively differentiate the EGFR mutation status.

Correlation Analysis of Ki67 Expression and EGFR Mutation on the Risk of Recurrence and Metastasis in Postoperative Patients with Stage I Lung Adenocarcinoma

The prognosis of stage I non-small cell lung cancer (NSCLC) is generally good. However, some of the stage I NSCLC patients still may have early recurrence and metastasis, and there is no standard method to screen this part of the population. The aim of this study is to investigate the relationship between Ki67 expression as well as epidermal growth factor receptor (EGFR) mutation and the risk of recurrence in postoperative patients with stage I lung adenocarcinoma. We retrospectively enrolled 118 postoperative patients with stage I lung adenocarcinoma. EGFR mutation was tested using amplification refractory mutation system polymerase chain reaction (ARMS-PCR) , and Ki67 level was detected by immunohistochemistry (IHC), followed by the collection of the patients' clinical characteristics. Kaplan-Meier method, Log-rank test, and Cox proportional hazards regression model were used for the prognostic statistical analysis. Among the 118 patients, the rate of high Ki67 expression was 43.22% (51/118), which is related to gender, smoking status, surgical method, differentiation degree, and postoperative stage (P<0.05). Meanwhile, EGFR mutation rate was 61.02% (72/118), of which EGFR exon 19 deletion mutation rate was 19.49% (23/118), and the EGFR exon 21 L858R mutation rate was 41.53% (49/118). However, Ki67 expression was not associated with EGFR mutation status (χ2=1.412, P=0.235). Survival analysis showed that high Ki67 expression was inversely associated with disease-free survival (DFS) and overall survival (OS) in stage I lung adenocarcinoma (P<0.05), but EGFR mutation status was not significantly associated with DFS and OS (P>0.05). In the subgroup analysis, the DFS of the EGFR exon 19 deletion group was significantly decreased compared with the EGFR exon 21 L858R mutation group (P=0.031), but there was no significant difference in OS (P=0.308). Multivariate analysis showed that there was statistical significance between Ki67 expression (P=0.001) and DFS in stage I lung adenocarcinoma; Ki67 expression (P=0.03) and gender (P=0.015) were associated with OS in stage I lung adenocarcinoma. Ki67 expression is an independent influencing factor for postoperative recurrence and OS of stage I lung adenocarcinoma and it is not significantly associated with EGFR mutation. There is no significant difference between EGFR mutation status and the prognostis of stage I lung adenocarcinoma. However, the prognosis differed in EGFR mutation types; the patients with EGFR exon 19 deletion are at higher risk of recurrence than EGFR exon 21 L858R mutation.

Non-Small Cell Lung Cancer (NSCLC) in Young Adults, Age < 50, Is Associated with Late Stage at Presentation and a Very Poor Prognosis in Patients That Do Not Have a Targeted Therapy Option: A Real-World Study

(1) Background: Non-small cell lung cancer (NSCLC) in young patients is uncommon. Real-world evidence on the outcomes of these patients is limited. (2) Methods: We conducted a retrospective cohort study of young NSCLC patients, age < 50 years at diagnosis, who were treated between 2011−2020 in South-East-London cancer centres. Clinicopathological characteristics, treatment and outcomes were analysed. (3) Results: Of 248 NSCLC patients, median age was 46 years, 50% (n = 125) female, 58% (n = 145) white, 18% (n = 45) black and 4% (n = 10) Asian ethnicity. Amongst patients with a documented smoking history, 30% (n = 64) were never-smokers. Most patients had adenocarcinoma (77%, n = 191) and presented with metastatic disease (67%, n = 166). Only 31% (n = 76) had treatment with curative intent. In patients who presented or developed metastatic non-squamous NSCLC (n = 179), EGFR mutation status was known in 88% (n = 157) and mutation present in 19% (n = 34), ALK was known in 66% (n = 118) with a translocation in 10% (n = 18), ROS1 status was known in 57% (n = 102) with a translocation in 4% (n = 8), and KRAS status was known in 66% (n = 119) with a mutation in 12% (n = 22). Overall, 76% (n = 152) patients with metastatic NSCLC received first-line systemic anti-cancer therapy. Median overall survival in metastatic NSCLC was 9.0 months (95% CI 6.5−11.6 months), with superior median overall survival in those with a targeted therapy option (28.7 months) compared to those without (6.6 months; p < 0.001). (4) Conclusion: Young patients contribute a significant proportion of those presenting with lung cancer. They present with advanced stage at diagnosis and have a poor prognosis. Identification of a targeted therapy option is associated with improved survival. However, most patients do not have a known genomic driver, which is in part due to limited testing, particularly in the early years of this study period. These findings highlight the particular importance of rapid-turnaround comprehensive genomic profiling in this age group and the need to identify strategies to facilitate earlier diagnosis in young NSCLC patients.

Dietary factors and the risk of lung cancer by epidermal growth factor receptor mutation status and histological subtypes.

Previous studies have reported differential associations of certain dietary factors such as soy consumption by epidermal growth factor receptor mutant (EGFR +) subtype of non-small cell lung cancer (NSCLC). However, whether the other dietary factors including meat, fruits, and vegetables have differential risks on different histological and molecular subtypes of lung cancer remains unclear. Therefore, we conducted a case-control study to evaluate these associations. A total of 3,170 cases and 4,238 controls from three different studies (Genes and Environment in Lung Cancer Study, Lung Cancer Consortium Singapore Study, and Multi-ethnic Cohort Study) were included. Information on demographics, lifestyle, and dietary consumption was obtained using questionnaires. Diet was assessed by using the number of standard servings of each item consumed per week. Multivariable logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between meat, vegetables, and fruits consumption with lung cancer risk after adjusting for potential confounders. We identified a significant inverse association between higher consumption of fruits and the risk of lung cancer (2nd tertile: OR = 0.54, 95%CI = 0.46-0.65; 3rd tertile: OR = 0.77, 95%CI = 0.65-0.91), compared with the lower (1st tertile) consumption of fruits. Higher vegetable consumption was significantly associated with a lower risk of EGFR + lung cancer (OR = 0.69, 95% CI = 0.54-0.88), however, this association was not significant among EGFR wild-type (-) lung cancer. Conversely, higher consumption of total meat (OR = 2.10, 95%CI = 1.58-2.79) was significantly associated with higher lung cancer risk, as compared with the lower consumption group. Differential associations between vegetable consumption with EGFR mutation status in NSCLC were found. Further prospective studies are warranted to assess this association and elucidate the biological mechanisms.