Relationships between EGFR mutation status of lung cancer and preoperative factors - are they predictive?

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.

Histopathologic Basis for a Chest CT Deep Learning Survival Prediction Model in Patients with Lung Adenocarcinoma

Background A preoperative CT-based deep learning (DL) prediction model was proposed to estimate disease-free survival in patients with resected lung adenocarcinoma. However, the black-box nature of DL hinders interpretation of its results. Purpose To provide histopathologic evidence underpinning the DL survival prediction model and to demonstrate the feasibility of the model in identifying patients with histopathologic risk factors through unsupervised clustering and a series of regression analyses. Materials and Methods For this retrospective study, data from patients who underwent curative resection for lung adenocarcinoma without neoadjuvant therapy from January 2016 to September 2020 were collected from a tertiary care center. Seven histopathologic risk factors for the resected adenocarcinoma were documented: the aggressive adenocarcinoma subtype (cribriform, morular, solid, or micropapillary-predominant subtype); mediastinal nodal metastasis (pN2); presence of lymphatic, venous, and perineural invasion; visceral pleural invasion (VPI); and EGFR mutation status. Unsupervised clustering using 80 DL model-driven CT features was performed, and associations between the patient clusters and the histopathologic features were analyzed. Multivariable regression analyses were performed to investigate the added value of the DL model output to the semantic CT features (clinical T category and radiologic nodule type [ie, solid or subsolid]) for histopathologic associations. Results A total of 1667 patients (median age, 64 years [IQR, 57-71 years]; 975 women) were evaluated. Unsupervised patient clusters 3 and 4 were associated with all histopathologic risk factors (P < .01) except for EGFR mutation status (P = .30 for cluster 3). After multivariable adjustment, model output was associated with the aggressive adenocarcinoma subtype (odds ratio [OR], 1.03; 95% CI: 1.002, 1.05; P = .03), venous invasion (OR, 1.03; 95% CI: 1.004, 1.06; P = .02), and VPI (OR, 1.08; 95% CI: 1.06, 1.10; P < .001), independently of the semantic CT features. Conclusion The deep learning model extracted CT imaging surrogates for the histopathologic profiles of lung adenocarcinoma. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Yanagawa in this issue.

Molecular typing of lung adenocarcinoma with computed tomography and CT image-based radiomics: a narrative review of research progress and prospects

Objective

The purpose of this paper was to perform a narrative review of current research evidence on conventional computed tomography (CT) imaging features and CT image-based radiomic features for predicting gene mutations in lung adenocarcinoma and discuss how to translate the research findings to guide future practice.

Background

Lung cancer, especially lung adenocarcinoma, is the leading cause of cancer-related deaths. With advances in the diagnosis and treatment of lung adenocarcinoma with the emergence of molecular testing, the prediction of oncogenes and even drug resistance gene mutations have become key to individualized and precise clinical treatment in order to prolong survival and improve quality of life. The progress of imageological examination includes the development of CT and radiomics are promising quantitative methods for predicting different gene mutations in lung adenocarcinoma, especially common mutations, such as epidermal growth factor receptor (EGFR) mutation, anaplastic lymphoma kinase (ALK) mutation and Kirsten rat sarcoma viral oncogene (KRAS) mutation.

Methods

The PubMed electronic database was searched along with a set of terms specific to lung adenocarcinoma, radiomics (including texture analysis), CT, computed tomography, EGFR, ALK, KRAS, rearranging transfection (RET) rearrangement and c-ros oncogene 1 (ROS-1), v-raf murine sarcoma viral oncogene homolog B1 (BRAF), and human epidermal growth factor receptor 2 (HER2) mutations et al. This review has been reported in compliance with the Narrative Review checklist guidelines. From each full-text article, information was extracted regarding a set of terms above.

Conclusions

Research on the application of conventional CT features and CT image-based radiomic features for predicting the gene mutation status of lung adenocarcinoma is still in a preliminary stage. Noninvasively determination of mutation status in lung adenocarcinoma before targeted therapy with conventional CT features and CT image-based radiomic features remains both hopes and challenges. Before radiomics could be applied in clinical practice, more work needs to be done.

High-resolution computed tomography findings independently predict epidermal growth factor receptor mutation status in ground-glass nodular lung adenocarcinoma

BACKGROUND

For lung adenocarcinoma with epidermal growth factor receptor (EGFR) gene mutation, small molecule tyrosine kinase inhibitors are more effective. Some patients could not obtain enough histological specimens for EGFR gene mutation detection. Specific imaging features can predict EGFR mutation status to a certain extent.

AIM

To assess the associations of EGFR mutations with high-resolution computerized tomography (HRCT) features in ground-glass nodular lung adenocarcinoma.

METHODS

This study retrospectively assessed patients with ground-glass nodular lung adenocarcinoma diagnosed between January 2011 and March 2017. EGFR gene mutations in exons 18-21 were detected. The patients were classified into mutant EGFR and wild-type groups, and general data and HRCT image characteristics were assessed.

RESULTS

Among 98 patients, 31 (31.6%) and 67 (68.4%) had mutated and wild-type EGFR in exons 18-21, respectively. Gender, age, smoking history, location of lesions, morphology, edges, borders, pleural indentations, and associations of nodules with bronchus and blood vessels were comparable in both groups (all P > 0.05). Patients with mutant EGFR had larger nodules than those with the wild-type (17.19 ± 6.79 and 14.37 ± 6.30 mm, respectively; P = 0.047). Meanwhile, the vacuole/honeycomb sign was more frequent in the mutant EGFR group (P = 0.011). The logistic regression prediction model included the combination of nodule size and vacuole/honeycomb sign (OR = 1.120, 95%CI: 1.023-1.227, P = 0.014) revealed a sensitivity of 83.9%, a specificity of 52.2% and an AUC of 0.698 (95%CI: 0.589-0.806; P = 0.002).

CONCLUSION

Nodule size and vacuole/honeycomb features could independently predict EGFR mutation status in ground-glass nodular lung adenocarcinoma.

Molecular Alterations in Lung Adenocarcinoma With Ground-Glass Nodules: A Systematic Review and Meta-Analysis

Background and Aims

Nodular ground-glass lesions have become increasingly common with the increased use of computed tomography (CT), while the genomic features of ground-glass opacities (GGOs) remain unclear. This study aims to comprehensively investigate the molecular alterations of GGOs and their correlation with radiological progression.

Methods

Studies from PubMed, Embase, Cochrane Library, and Web of Science, using PCR, targeted panel sequencing, whole exosome sequencing, and immunohistochemistry, and reporting genomic alterations or PD-L1 expressions in lung nodules presenting as GGOs until January 21, 2021 were included in this study. Chi-square test, random-effects model, and Z-test analysis were adopted to analyze the data.

Results

A total of 22 studies describing mutations in lung adenocarcinoma (LUAD) with GGOs were analyzed. EGFR was the most frequently mutative gene (51%, 95%CI 47%-56%), followed by TP53 (18%, 95%CI 6%-31%), HER2 (10%, 95%CI 0%-21%), ROS1 (6%, 95%CI 0%-18%), and KRAS (6%, 95%CI 3%-9%). The correlation between the frequency of EGFR mutation and radiological was observed and the differences were found to be not statistically significant in the subgroups, which are listed as below: radiological: gGGO 47.40%, 95%CI [38.48%; 56.40%]; sGGO 51.94%, 95%CI [45.15%; 58.69%]. The differences of the frequency of KRAS mutation in the different subgroups were also consistent with this conclusion, which are listed as: radiological gGGO 3.42, 95%CI [1.35%; 6.13%]; sGGO 12.27%, 95%CI [3.89%; 23.96%]. The pooled estimated rate of PD-L1 was 8.82%, 95%CI [5.20%-13.23%]. A total of 11.54% (3/26) of the SMGGNs were confirmed to be intrapulmonary spread by WES.

Conclusions

Somatic genetic alterations are considered in early-stage GGO patients without distinct changes of the frequency following the progress of the tumor. This review sheds insight on molecular alterations in LUAD with GGOs.

Multi-channel multi-task deep learning for predicting EGFR and KRAS mutations of non-small cell lung cancer on CT images

BACKGROUND

Predicting the mutation statuses of 2 essential pathogenic genes [epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma (KRAS)] in non-small cell lung cancer (NSCLC) based on CT is valuable for targeted therapy because it is a non-invasive and less costly method. Although deep learning technology has realized substantial computer vision achievements, CT imaging being used to predict gene mutations remains challenging due to small dataset limitations.

METHODS

We propose a multi-channel and multi-task deep learning (MMDL) model for the simultaneous prediction of EGFR and KRAS mutation statuses based on CT images. First, we decomposed each 3D lung nodule into 9 views. Then, we used the pre-trained inception-attention-resnet model for each view to learn the features of the nodules. By combining 9 inception-attention-resnet models to predict the types of gene mutations in lung nodules, the models were adaptively weighted, and the proposed MMDL model could be trained end-to-end. The MMDL model utilized multiple channels to characterize the nodule more comprehensively and integrate patient personal information into our learning process.

RESULTS

We trained the proposed MMDL model using a dataset of 363 patients collected by our partner hospital and conducted a multi-center validation on 162 patients in The Cancer Imaging Archive (TCIA) public dataset. The accuracies for the prediction of EGFR and KRAS mutations were, respectively, 79.43% and 72.25% in the training dataset and 75.06% and 69.64% in the validation dataset.

CONCLUSIONS

The experimental results demonstrated that the proposed MMDL model outperformed the latest methods in predicting EGFR and KRAS mutations in NSCLC.

Genomic landscape of ground glass opacities (GGOs) in East Asians

Background

Understanding the genomic landscape of early-stage lung adenocarcinoma (LUAD) may provide new insights into the molecular evolution in the early stages of LUAD.

Methods

Through sequencing of 79 spatially distinct regions from 37 patients with ground glass opacities (GGOs), we provided a comprehensive mutational landscape of GGOs, highlighting the importance of ancestry differences.

Results

Our study had several interesting features. First, epidermal growth factor receptor (EGFR), BRAF (v-RAF murine sarcoma viral oncogene homologue B1), and ERBB2 (Erb-B2 Receptor Tyrosine Kinase 2, also known as HER2) were more frequently mutated in our study, which supports the notion that EGFR is considered to be a major driver and tends to drive the occurrence of LUAD. Second, Signature 1, Signature 3, and Signature 6 were identified in patients with GGOs. Our results further suggested that Signature 1 was more prominent among early mutations. Third, compared with LUADs, GGOs exhibited significantly lower levers of arm-level copy number variation (CNV)—which alter the diploid status of DNA, and lower focal CNVs.

Conclusions

In our study, 79 samples of patients were included to analyze the GGO gene profile, revealing the genetic heterogeneity of GGO in East Asian population, and providing guidance for prognosis analysis of GGO patients by comparison with LUAD. Our study revealed that GGOs had fewer genomic alterations and simpler genomic profiles than LUADs. The most commonly altered processes were related to the receptor tyrosine kinase (RTK)/Ras/phosphatidylinositol-3-kinase (PI3K) signaling pathways in GGOs, and EGFR alterations were the dominant genetic changes across all targetable somatic changes.

Biological Significance of 18F-FDG PET/CT Maximum Standard Uptake Value for Predicting EGFR Mutation Status in Non-Small Cell Lung Cancer Patients

Purpose

To investigate the potential of maximum standardized uptake value (SUVmax) in predicting epidermal growth factor receptor (EGFR) mutation status in non-small cell lung cancer (NSCLC) patients.

Methods

Clinical data of 311 NSCLC patients who had undergone both EGFR mutation test and ¹⁸F-FDG PET/CT scans between January 2013 and December 2017 at our hospital were retrospectively analyzed. Patients were sub-grouped by their origin of SUVmax. Univariate and multivariate analyses were performed to investigate the association between clinical factors and EGFR mutations. Receiver operating characteristic curve (ROC) analysis was performed to confirm the predictive value of clinical factors. In vitro experiments were performed to confirm the correlation between EGFR mutations and glycolysis.

Results

EGFR-mutant patients had higher SUVmax than the wild-type patients in both primary tumors and metastases. In the multivariate analysis, SUVmax, gender and histopathologic type were determined as independent predictors of EGFR mutation status for patients whose SUVmax were obtained from the primary tumors; while for patients whose SUVmax were obtained from the metastases, SUVmax, smoking status and histopathologic type were regarded as independent predictors. ROC analysis showed that SUVmax of the primary tumors (cut off >10.92), not of the metastases, has better predictive value than other clinical factors in predicting EGFR mutation status. The predict performance was improved after combined SUVmax with other independent predictors. In addition, our in vitro experiments demonstrated that lung cancer cells with EGFR mutations have higher aerobic glycolysis level than wild-type cells.

Conclusion

SUVmax of the primary tumors has the potential to serve as a biomarker to predict EGFR mutation status in NSCLC patients.

Clinical and radiological predictors of epidermal growth factor receptor mutation in nonsmall cell lung cancer

Purpose

To determine the prognostic factors of epidermal growth factor receptor (EGFR) mutation status in a group of patients with nonsmall cell lung cancer (NSCLC) by analyzing their clinical and radiological features.

Materials and methods

Patients with NSCLC who underwent EGFR mutation detection between 2014 and 2017 were included. Clinical features and general imaging features were collected, and radiomic features were extracted from CT data by 3D Slicer software. Prognostic factors of EGFR mutation status were selected by least absolute shrinkage and selection operator (LASSO) logistic regression analysis, and receiver operating characteristic (ROC) curves were drawn for each prediction model of EGFR mutation.

Results

A total of 118 patients were enrolled in this study. The smoking index (P = 0.028), pleural retraction (P = 0.041), and three radiomic features were significantly associated with EGFR mutation status. The areas under the ROC curve (AUCs) for prediction models of clinical features, general imaging features, and radiomic features were 0.284, 0.703, and 0.815, respectively, and the AUC for the combined prediction model of the three models was 0.894. Finally, a nomogram was established for individualized EGFR mutation prediction.

Conclusions

The combination of radiomic features with clinical features and general imaging features can enable discrimination of EGFR mutation status better than the use of any group of features alone. Our study may help develop a noninvasive biomarker to identify EGFR mutation status by using a combination of the three group features.

Nomogram based on preoperative CT imaging predicts the EGFR mutation status in lung adenocarcinoma

•

Tyrosine kinase inhibitors (TKIs) provide clinical benefits to the lung cancer patients with epidermal growth factor receptor (EGFR) mutations.

•

Non-invasively determine EGFR mutation status in patients before targeted therapy remains a challenge.

•

The personalized nomogram model of CT features and clinical risk factors can easily and noninvasively predict the EGFR mutation status before surgery.

Tyrosine kinase inhibitors (TKIs) provide clinical benefits to the lung cancer patients with epidermal growth factor receptor (EGFR) mutations. However, non-invasively determine EGFR mutation status in patients before targeted therapy remains a challenge. This study aimed to develop and validate a nomogram for preoperative prediction of EGFR mutation status in patients with lung adenocarcinoma. The medical records of 403 patients with lung adenocarcinoma confirmed by histology from January 2016 to June 2020 were retrospectively collected. We combined CT features and clinical risk factors and used them to build a prediction nomogram. The performance of the nomogram was evaluated in terms of calibration, discrimination, and clinical usefulness. The nomogram was further validated in an independent external cohort. Finally, a nomogram that contained CT features and clinical risk factors, which could conveniently and non-invasively predict EGFR mutation status in patients with lung adenocarcinoma before surgery.

Relationship of EGFR Mutation to Glucose Metabolic Activity and Asphericity of Metabolic Tumor Volume in Lung Adenocarcinoma

Purpose

EGFR-mutation (EGFR-mt) is a major oncogenic driver mutation in lung adenocarcinoma (ADC) and is more often observed in Asian population. In lung ADC, some radiomics parameters of FDG PET have been reported to be associated with EGFR-mt. Here, the associations between EGFR-mt and PET parameters, particularly asphericity (ASP), were evaluated in Asian population.

Methods

Lung ADC patients who underwent curative surgical resection as the first treatment were retrospectively enrolled. EGFR mutation was defined as exon 19 deletion and exon 21 point mutation and was evaluated using surgical specimens. On FDG PET, image parameters of maximal standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and ASP were obtained. The parameters were compared between EGFR-mt and wild type (EGFR-wt) groups, and the relationships between these PET parameters and EGFR-mt were evaluated.

Results

A total of 64 patients (median age 66 years, M:F = 34:30) were included in the analysis, and 29 (45%) patients showed EGFR-mt. In EGFR-mt group, all the image parameters of SUVmax, MTV, TLG, and ASP were significantly lower than in EGFR-wt group (all adjusted P < 0.050). In univariable logistic regression, SUVmax (P = 0.003) and ASP (P = 0.010) were significant determinants for EGFR-mt, whereas MTV was not (P = 0.690). Multivariate analysis revealed that SUVmax and ASP are independent determinants for EGFR-mt, regardless of inclusion of MTV in the analysis (P < 0.05).

Conclusion

In Asian NSCLC/ADC patients, SUVmax, MTV, and ASP on FDG PET are significantly related to EGFR mutation status. Particularly, low SUVmax and ASP are independent determinants for EGFR-mt.

A novel radiomic nomogram for predicting epidermal growth factor receptor mutation in peripheral lung adenocarcinoma

To predict the epidermal growth factor receptor (EGFR) mutation status in patients with lung adenocarcinoma using quantitative radiomic biomarkers and semantic features. We analyzed the computed tomography (CT) images and medical record data of 104 patients with lung adenocarcinoma who underwent surgical excision and EGFR mutation detection from 2016 to 2018 at our center. CT radiomic and semantic features that reflect the tumors' heterogeneity and phenotype were extracted from preoperative non-enhanced CT scans. The least absolute shrinkage and selection operator method was applied to select the most distinguishable features. Three logistic regression models were built to predict the EGFR mutation status by combining the CT semantic with clinicopathological characteristics, using the radiomic features alone, and by combining the radiomic and clinicopathological features. Receiver operating characteristic (ROC) curve analysis was performed using five-fold cross-validation and the mean area under the curve (AUC) values were calculated and compared between the models to obtain the optimal model for predicting EGFR mutation. Furthermore, radiomic nomograms were constructed to demonstrate the performance of the model. In total, 1025 radiomic features were extracted and reduced to 13 features as the most important predictors to build the radiomic signature. The combined radiomic and clinicopathological features model was developed based on the radiomic signature, sex, smoking, vascular infiltration, and pathohistological type. The AUC was 0.90  ±  0.02 for the training, 0.88  ±  0.11 for the verification, and 0.894 for the test dataset. This model was superior to the other prediction models that used the combined CT semantic and clinicopathological features (AUC for the test dataset: 0.768) and radiomic features alone (AUC for the test dataset: 0.837). The prediction model built by radiomic biomarkers and clinicopathological features, including the radiomic signature, sex, smoking, vascular infiltration, and pathological type, outperformed the other two models and could effectively predict the EGFR mutation status in patients with peripheral lung adenocarcinoma. The radiomic nomogram of this model is expected to become an effective biomarker for patients with lung adenocarcinoma requiring adjuvant targeted treatment.

Utility of CT radiomics for prediction of PD-L1 expression in advanced lung adenocarcinomas

Background

We aimed to assess if quantitative radiomic features can predict programmed death ligand 1 (PD‐L1) expression in advanced stage lung adenocarcinoma.

Methods

This retrospective study included 153 patients who had advanced stage (>IIIA by TNM classification) lung adenocarcinoma with pretreatment thin section computed tomography (CT) images and PD‐L1 expression test results in their pathology reports. Clinicopathological data were collected from electronic medical records. Visual analysis and radiomic feature extraction of the tumor from pretreatment CT were performed. We constructed two models for multivariate logistic regression analysis (one based on clinical variables, and the other based on a combination of clinical variables and radiomic features), and compared c‐statistics of the receiver operating characteristic curves of each model to identify the model with the higher predictability.

Results

Among 153 patients, 53 patients were classified as PD‐L1 positive and 100 patients as PD‐L1 negative. There was no significant difference in clinical characteristics or imaging findings on visual analysis between the two groups (P > 0.05 for all). Rad‐score by radiomic analysis was higher in the PD‐L1 positive group than in the PD‐L1 negative group with a statistical significance (−0.378 ± 1.537 vs. −1.171 ± 0.822, P = 0.0008). A prediction model that uses clinical variables and CT radiomic features showed higher performance compared to a prediction model that uses clinical variables only (c‐statistic = 0.646 vs. 0.550, P = 0.0299).

Conclusions

Quantitative CT radiomic features can predict PD‐L1 expression in advanced stage lung adenocarcinoma. A prediction model composed of clinical variables and CT radiomic features may facilitate noninvasive assessment of PD‐L1 expression.

Key points

Significant findings of the study

Quantitative CT radiomic features can help predict PD‐L1 expression, whereas none of the qualitative imaging findings is associated with PD‐L1 positivity.

What this study adds

A prediction model composed of clinical variables and CT radiomic features may facilitate noninvasive assessment of PD‐L1 expression.

Association of radiomic features with epidermal growth factor receptor mutation status in non-small cell lung cancer and survival treated with tyrosine kinase inhibitors

Since the discovery of the fact that tyrosine kinase inhibitors could improve progression-free survival for patients with advanced non-small cell lung cancer compared with traditional chemotherapy, it has been extremely important to identify epidermal growth factor receptor mutation status in treatment stratification. Although lack of sufficient biopsy samples limit the precise detection of epidermal growth factor receptor mutation status in clinical practice, and it is difficult to identify the sensitive patients who confer favorable response to tyrosine kinase inhibitors. An increasing number of scholars tried to deal with these problems using methods based on the non-invasive imaging including computed tomography and PET to find the association with epidermal growth factor receptor mutation status and survival treated with tyrosine kinase inhibitor in non-small cell lung cancer. Although the conclusions have not reached a consensus, quantitative and high-throughput radiomics have brought us a new direction and might successfully help identify patients undergoing tyrosine kinase inhibitors who could get significant benefits.

CT and clinical characteristics that predict risk of EGFR mutation in non-small cell lung cancer: a systematic review and meta-analysis

INTRODUCTION

To systematically analyze CT and clinical characteristics to find out the risk factors of epidermal growth factor receptor (EGFR) mutation in non-small cell lung cancer (NSCLC). Then the significant characteristics were used to set up a mathematic model to predict EGFR mutation in NSCLC.

MATERIALS AND METHODS

PubMed, Web of Knowledge and EMBASE up to August 17, 2018 were systematically searched for relevant studies that investigated the evidence of association between CT and clinical characteristics and EGFR mutation in NSCLC. After study selection, data extraction, and quality assessment, the pooled odds ratios (ORs) were calculated. Then from May 2017 to August 2018, all NSCLC received EGFR mutation examination and CT examination in our hospital were chosen to test the prediction model by receiver operating characteristic (ROC) curves.

RESULTS

Seventeen original studies met the inclusion criteria. The results showed that the ORs of ground-glass opacity (GGO), air bronchogram, pleural retraction, vascular convergence, smoking history, female gender were, respectively, 1.93 (P = 0.003), 2.09 (P = 0.03), 1.59 (P < 0.01), 1.61 (P = 0.001), 0.28 (P < 0.01), 0.35 (P < 0.01). The result of speculation, cavitation/bubble-like lucency, lesion shape, margin, pathological stage were, respectively, 1.19 (P = 0.32), 0.99 (P = 0.97), 0.82 (P = 0.42), 1.02 (P = 0.90), 0.77 (P = 0.30). 121 NSCLC received EGFR mutation test were included to test the prediction model. The mathematical model based on the results of meta-analysis was: 0.74 × air bronchogram + 0.46 × pleural retraction + 0.48 × vascular convergence - 1.27 × non-smoking history - 1.05 × female. The area under the ROC curve was 0.68.

CONCLUSION

Based on the current evidence, GGO presence, air bronchogram, pleural retraction, vascular convergence were significant risk factors of EGFR mutation in NSCLC. And the prediction model can help to predict EGFR mutation status.

Correlation between high-resolution computed tomography lung nodule characteristics and EGFR mutation in lung adenocarcinomas

Background

The aim of this study was to investigate the correlation of EGFR mutation on the high-resolution computed tomography (HRCT) features in lung adenocarcinoma.

Patients and methods

A total of 121 patients were diagnosed with lung adenocarcinoma from January 2014 to December 2016. The correlation of indexes (gender, age, tumor diameter, and EGFR mutation) was analyzed based on the HRCT characteristics of lung adenocarcinoma.

Results

There were 73 cases of EGFR mutation and 48 cases of wild-type EGFR. One hundred and three cases had pleural indentation that was significant in patients with EGFR mutation than those with wild-type EGFR (P=0.038). Forty-two out of 121 cases exhibited the bronchus cutoff sign. Patients with EGFR mutation were likely to develop the bronchus cutoff sign (P=0.017). Sixty-one out of 121 cases exhibited the lobulation sign, which was significant in patients with EGFR mutation than those with wild-type EGFR (P<0.001). A significant correlation was found between lobulation sign and tumor diameter (P=0.024). Forty-eight out of 121 and 23 out of 121 cases showed the vessel and vacuole signs, respectively. However, patients with EGFR mutation did not exert a significant correlation on either of these signs (P=0.555 and P=0.372, respectively). A statistical significance was not observed in indexes such as age, gender, and tumor diameter on pleural indentation, bronchus cutoff sign, vessel sign, and vacuole sign (P>0.05). Age and gender did not vary significantly in the lobulation sign (P>0.05).

Conclusion

HRCT characteristics such as pleural indentation, bronchus cutoff sign, and lobulation sign in lung adenocarcinoma with EGFR mutation were significantly greater than those with wild-type EGFR; however, further study is essential in determining the predictive ability of computed tomography (CT) for EGFR mutations in lung adenocarcinoma.

Prediction of EGFR mutations by conventional CT-features in advanced pulmonary adenocarcinoma

OBJECTIVE

This study assessed the ability of conventional computed tomography (CT) features (including primary tumors, metastatic lesions, lymph nodes, and emphysema) to predict epidermal growth factor receptor (EGFR) mutations in advanced pulmonary adenocarcinoma.

METHODS

Patients who were diagnosed with advanced pulmonary adenocarcinoma between January 2017 and August 2017 and had undergone a chest CT and EGFR mutation testing were enrolled in this retrospective study. Qualitative and quantitative CT-features and clinical characteristics evaluated in this study included: primary tumor location, size, and morphology (including degree of lobulation, density, calcification, cavitation, vacuole sign, and air bronchogram), size and distribution of lung and pleural metastatic nodules, size and status of hilar and mediastinal lymph nodes, emphysema, organs with distant metastasis, and patient age, sex, and smoking history.

RESULTS

Of 201 patients, 107 (53.23%) were EGFR-mutation positive. The multivariate logistic regression indicated that EGFR mutations were significantly associated with smaller lymph nodes, a lower percentage of deep lobulation of the primary tumor and partial fusion of lymph nodes, and absence of emphysema. The area under the curve of logistic regression model for predicting EGFR mutations was 0.898.

CONCLUSIONS

Conventional CT-features, including emphysema, degree of primary tumor lobulation, and lymph node size and status, help to predict the presence or absence of EGFR mutations in advanced pulmonary adenocarcinoma. Additionally, these same CT-features demonstrated that the CT manifestations of the EGFR mutant group were of relatively lower malignancy and less invasive as compared to the wild-type EGFR group.

Significance of the epidermal growth factor receptor mutation status and differences among molecular subgroups in surgically resected lung microinvasive adenocarcinoma

Lung microinvasive adenocarcinoma (MIA) is a newly-defined subtype of early stage non-small cell lung cancer (NSCLC). However, its epidermal growth factor receptor (EGFR) mutation status and clinical significance remain unclear. The present study aimed to determine EGFR mutation characteristics and identify their significance in patients with resected lung MIA. The present study also analyzed clinicopathological differences between EGFR molecular subgroups defined as 19Del and L858R. The present study examined EGFR mutations in 79 consecutive lung MIA resection specimens and compared the differences in clinicopathological features between the EGFR wild-type and mutation groups, as well as between the 19Del and L858R subgroups. EGFR mutations were detected in 60 (75.95%) tumors. The most common mutations were 19Del (28 cases; 35.44%) and L858R (30 cases; 37.97%). Two patients harbored rare mutations and one of them had a concomitant double mutation. EGFR mutations were significantly associated with microinvasion component, thyroid transcription factor 1 (TTF-1) expression, intratumoral fibrosis and inflammatory cell infiltration. Subgroup evaluation indicated that there was a significant association between 19Del and tumor size, maximum diameter of microinvasion, presence of intratumoral fibrosis and inflammatory cell infiltration. Similar associations were observed for the L858R subgroup, and L858R was associated with TTF-1 expression. In particular, 19Del occurred more frequently in MIA with a smaller size, with a smaller microinvasive area, without TTF-1 expression, and lacking intratumoral fibrosis and inflammatory cell infiltration. By contrast, L858R was detected more frequently in MIA with entirely different tumor features. In conclusion, the results of the present study indicated that surgically resected MIA cases harboring different EGFR gene statuses exhibit distinct clinicopathological features. Significant differences in pathological features associated with the tumor microenvironment were identified in MIA with 19Del or L858R mutations. Therefore, the present study proposed that MIA should be classified into molecular subgroups based on EGFR mutation subtypes. The molecular sub-classification should be taken into account for prognostic evaluation and clinical management of MIA.

Impact of the epidermal growth factor receptor mutation status on the prognosis of recurrent adenocarcinoma of the lung after curative surgery

Background

The prognosis of patients with epidermal growth factor receptor (EGFR) mutant adenocarcinoma of the lung (Mt) and EGFR wild-type adenocarcinoma (Wt) after complete resection of the lung differ; however, the mechanisms responsible for these differences remain unclear. The present study examined the post-operative prognosis of recurrent pulmonary adenocarcinoma patients to evaluate the clinicopathological nature of Mt and contribution of EGFR - tyrosine kinase inhibitors (TKI) to the prognosis of patients.

Methods

The subjects were 237 patients with recurrent pulmonary adenocarcinoma who underwent EGFR mutation analysis, and consisted of 108 patients with recurrent Mt and 129 with recurrent Wt. Multivariate analyses were performed to investigate whether the EGFR status is a prognostic factor for relapse-free survival (RFS) and post-relapse survival (PRS).

Results

RFS was significantly better in Mt than in Wt patients; median RFS were 20.2 and 13.3 months, respectively (p < 0.001). The multivariate analysis identified EGFR mutation as an independent prognostic factor for a favorable RFS (hazard ratio = 0.68; 95% confidence interval, 0.52–0.89). Although, no significant differences were observed in PRS between Mt and Wt patients (median PRS were 33.9 and 28.2 months, respectively; p = 0.360), PRS was significantly better in Mt with EGFR - TKI than in Wt and Mt patients without EGFR - TKI (p = 0.008 and p < 0.001, respectively). PRS was also significantly better in Wt than in Mt patients without EGFR - TKI (p < 0.001). The multivariate analysis identified the administration of EGFR - TKI as an independent prognostic factor for PRS (hazard ratio = 0.60; 95% confidence interval, 0.40–0.89).

Conclusions

EGFR mutation tumors were associated with a significantly better RFS for recurrent pulmonary adenocarcinoma after curative resection of the lung, which represented the less aggressive nature of Mt tumors. However, patients with Mt did not have a favorable prognosis after recurrence unless they received EGFR - TKI.

EGFR-TKI-sensitive mutations in lung carcinomas: are they related to clinical features and CT findings?

Background

Epidermal growth factor receptor (EGFR) mutation testing is restricted to several limitations. In this study, we examined the relationship between EGFR mutation status and clinicoradiological characteristics in a Chinese cohort of patients.

Materials and methods

The data of patients who were diagnosed with lung carcinoma and underwent both EGFR testing and chest computed tomography (CT) at our hospital between January 1, 2011, and November 31, 2015, were retrospectively analyzed. The age, sex, and smoking index of the patients, the size, margin, and density of the tumor, and the presence of specific signs visible on the CT images were assessed.

Results

The results showed a higher rate of EGFR-tyrosine kinase inhibitor (TKI)-sensitive group than nonsensitive group in female patients and patients with a low smoking index (P<0.001, both). In logistic regression analyses, tumor size (P<0.001), smooth margins (P=0.015), and angular margins (P<0.001) were independent negative predictors of EGFR-TKI-sensitive group. Pleural indentation (P<0.001) and air bronchogram (P=0.025) were independent positive predictors of EGFR-TKI-sensitive group. Patients with squamous cell carcinoma had fewer sensitive mutations than those with either adenocarcinoma (P<0.001) or adenosquamous carcinoma (P<0.001).

Conclusion

Clinical and CT characteristics differed significantly between EGFR-TKI-sensitive and nonsensitive groups. Our findings may be useful in deciding therapeutic strategies for patients in whom EGFR testing is not possible.

Computed tomography characteristics of lung adenocarcinomas with epidermal growth factor receptor mutation: A propensity score matching study

OBJECTIVES

We investigated the relationship between computed tomography (CT) characteristics and epidermal growth factor receptor (EGFR) mutations in a large Asian cohort who received surgical resection of invasive lung adenocarcinoma.

MATERIALS AND METHODS

We retrospectively included 864 patients (524 with EGFR mutation and 340 with EGFR wild-type) who received surgical resections for invasive lung adenocarcinomas. After applying propensity score matching, 312 patients with mutated EGFR were matched with 312 patients with wild-type EGFR. CT characteristics, predominant histologic subtype, and CT measurement parameters (volume and estimated diameter of the total tumor and inner solid portion and ground-glass opacity [GGO] proportion) were compared within matched pairs.

RESULTS

Tumors in the EGFR mutation group showed higher proportions of pure ground-glass nodules (4.1% vs 1.3%), GGO-predominant (23.7% vs 14.7%), and solid-predominant part-solid nodules (37.2% vs 31.7%) CT characteristics, whereas EGFR wild-type tumors predominantly presented as pure solid nodules (34.6% vs 52.2%, P < 0.0001). EGFR mutation tumors more frequently had a lepidic-predominant subtype than did EGFR wild-type tumors (20.2% and 11.9%; P < 0.0001), and showed a smaller whole tumor size and solid portion (P < 0.0001) with a higher GGO proportion (P < 0.0001). Tumors with exon 21 missense mutations showed the highest GGO proportion and the smallest inner solid portion size, followed by tumors harboring an exon 19 deletion, compared with EGFR wild-type tumors (posthoc P < 0.01).

CONCLUSION

Adenocarcinomas with EGFR mutations had a higher GGO proportion than those with wild-type EGFR after matching of clinical variables. Lesions with an exon 21 mutation had a higher GGO proportion than lesions with other mutations.

A novel ARMS-based assay for the quantification of EGFR mutations in patients with lung adenocarcinoma

Quantification of epidermal growth factor receptor (EGFR) mutations is important for the prediction of tyrosine kinase inhibitor (TKI) efficacy in patients with non-small cell lung cancer (NSCLC). However, clinicians lack a sensitive and convenient method to quantify EGFR mutant abundance. The present study introduces a novel method, namely amplification refractory mutation system (ARMS)-Plus, for the quantitative analysis of EGFR exon 19 deletion (19Del), L858R and T790M mutations. Formalin-fixed paraffin-embedded tumor samples were collected from 77 patients with lung adenocarcinoma. DNA was extracted and analyzed for EGFR mutations using ARMS-Plus. The performance of ARMS-Plus was then compared with that of conventional ARMS-polymerase chain reaction (ARMS-PCR) and droplet digital PCR (ddPCR). The results demonstrated that the concordance rate of EGFR mutation testing between ARMS-Plus and ddPCR was 98.7% (76/77, Kappa=0.9739). 19Del and L858R mutations were detected in 23 and 12 patients, respectively. There was a significant difference between ARMS-Plus and ddPCR in the evaluation of 19Del mutant abundance (P=0.0002); however, not in that of L858R mutant abundance (P=0.7334). The ARMS-Plus results in L858R mutant abundance were concordant with that of ddPCR (R2=0.8081). These results indicated that the sensitivity and specificity of ARMS-Plus in identifying EGFR mutations were similar to that of ddPCR. For quantitative analysis, the results of ARMS-Plus in evaluating L858R mutant abundance revealed a positive correlation with the ddPCR results. Thus, ARMS-Plus provides an alternative method, which is reliable and cost-effective, to quantify EGFR mutations and thereby, aid treatment decisions in patients with lung adenocarcinoma.

Associations between clinical data and computed tomography features in patients with epidermal growth factor receptor mutations in lung adenocarcinoma

BACKGROUND

To analyse the differences in computed tomography (CT) features between patients with lung adenocarcinoma who have epidermal growth factor receptor (EGFR) mutations and those who have wild-type EGFR.

METHODS

Patients with lung adenocarcinoma (n = 156) were enrolled from October 2013 to March 2016, including 56 patients with wild-type EGFR and 100 patients with EGFR mutations. Two independent radiologists evaluated patient characteristics and imaging features. Chi-squared test, Fisher's exact test or ANOVA was applied to discriminate clinical and CT characteristics between the genotypes. A prediction tool for EGFR mutation was devised from principal component analysis.

RESULTS

The proportion of females and non-smokers in the exon 19 deletion and exon 21 missense groups was higher than in the wild-type group (P < 0.01). Severe emphysema was higher in the wild-type group than in the exon 19 deletion group (P < 0.01). The maximum diameter in the mediastinal window (MaxD_mediastinal) in the wild-type group was longer than in the exon 19 deletion and exon 21 missense groups. The minimum diameter in the mediastinal window (MinD_mediastinal) in the wild-type group was also longer than in the exon 21 missense group, with a significant difference (P < 0.05). The tumor shadow disappearance rate (TDR) in the exon 19 deletion group was higher than in the wild-type group. Ground glass opacity (GGO) appeared to be more common in the exon 19 deletion group (P = 0.010). The prediction score for exon 19 deletion mutation was: 0.305 × gender + 0.254 × smoking history + 0.198 × MaxD_mediastinal + TDR × 0.254 + 0.280 × GGO + 0.095 × emphysema. The sensitivity and specificity for predicting exon 19 deletion were 59.09 and 76.79%, respectively. The prediction score for the exon 21 missense mutation was: 0.354 × gender + 0.291 × smoking history + 0.410 × MaxD_mediastinal + 0.408 × MinD_mediastinal. The sensitivity and specificity for predicting exon 21 missense mutation were 72.34 and 78.57%, respectively.

CONCLUSION

As well as gender, smoking history and GGO, adenocarcinomas with EGFR mutation were significantly associated with emphysema, TDR, and the diameter in the mediastinal window. As exon 19 deletion and 21 missense mutations might be predicted by those features, the scoring system might be valuable for clinical diagnosis.

CT characteristics in pulmonary adenocarcinoma with epidermal growth factor receptor mutation

Comprehensively investigate the association of CT morphology and clinical findings of adenocarcinoma with EGFR mutation status. Retrospectively included 282 patients who was pathologically proved as lung adenocarcinoma with known EGFR mutation status (mutations: 138 patients, female: 86, median age: 66 years; wildtype: 144 patients, female: 67, median age: 62 years) and their pre-treatment CT scans were analyzed. CT findings and clinical information were collected. Univariate and multivariable logistic regression analysis were performed. Adjusted for age, gender and smoking history of two groups, significantly more patients with pleural tags, pleural and liver metastases were found in the EGFR mutated group (P = 0.007, 0.004, and 0.043, respectively). Multivariable logistic regression analysis found that the model included age, gender, smoking history, air bronchogram, pleural tags, pleural and liver metastasis had a moderate predictive value for EGFR mutation status (AUC = 0.741, P < .0001). Exon-19 deletion was associated with air bronchogram which adjusted for age, gender and smoking history (P = 0.007, OR: 2.91, 95%CI: 1.25–7.79). The evidence of pleural tags, pleural and liver metastases go along with a higher probability of EGFR mutation in adenocarcinoma patients and air bronchogram is positively associated with Exon-19 deletion mutation.

Pulmonary ground-glass opacity: computed tomography features, histopathology and molecular pathology

The incidence of pulmonary ground-glass opacity (GGO) lesions is increasing as a result of the widespread use of multislice spiral computed tomography (CT) and the low-dose CT screening for lung cancer detection. Besides benign lesions, GGOs can be a specific type of lung adenocarcinomas or their preinvasive lesions. Evaluation of pulmonary GGO and investigation of the correlation between CT imaging features and lung adenocarcinoma subtypes or driver genes can be helpful in confirming the diagnosis and in guiding the clinical management. Our review focuses on the pathologic characteristics of GGO detected at CT, involving histopathology and molecular pathology.

CT characteristics of non-small cell lung cancer with epidermal growth factor receptor mutation: a systematic review and meta-analysis

Background

To systematically investigate the relationship between CT morphological features and the presence of epidermal growth factor receptor (EGFR) mutations in non-small cell lung cancer (NSCLC).

Methods

All studies about the CT morphological features of NSCLC with EGFR mutations published between January 1, 2000 and March 15, 2015 were searched in the PubMed and EMBASE databases. Qualified studies were selected according to inclusion criteria. The frequency of EGFR mutations and CT features of ground-glass opacity (GGO) content, tumor size, cavitation, air-bronchogram, lobulation, and spiculation were extracted. The relationship between EGFR mutations and each of these CT features was tested based upon the weighted mean difference or inverse variance in the form of an odds ratio at a 95% confidence interval using Forest Plots. The publication bias was examined using Egger’s test.

Results

A total of 13 studies, consisting of 2146 NSCLC patients, were included, and 51.12% (1097/2146) of patients had EGFR mutations. The EGFR mutations were present in NSCLC with part-solid GGO in contrast to nonsolid GGO (OR = 0.49, 95% CI = 0.25–0.96, P = 0.04). Other CT features such as tumor size, cavitation, air-bronchogram, lobulation and spiculation did not demonstrate statistically significant correlation with EGFR mutations individually (P = 0.91; 0.67; 0.12; 0.45; and 0.36, respectively). No publication bias among the selected studies was noted in this meta-analysis (Egger’s tests, P > 0.05 for all).

Conclusion

This meta-analysis demonstrated that NSCLC with CT morphological features of part-solid GGO tended to be EGFR mutated, which might provide an important clue for the correct selection of patients treated with molecular targeted therapies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12880-016-0175-3) contains supplementary material, which is available to authorized users.

The Association of EGFR Mutations with Stage at Diagnosis in Lung Adenocarcinomas

Background

The prognostic role of epidermal growth factor receptor (EGFR) mutations in patients with lung adenocarcinomas remains controversial and the association between EGFR mutations and stage at the time of the initial diagnosis is debatable. In this study, we evaluated the association of EGFR mutations with stage at diagnosis in lung adenocarcinomas.

Materials and Methods

We retrospectively analyzed 1004 consecutive patients who were diagnosed with lung adenocarcinomas and tested for EGFR mutations between June 2011 and December 2014.

Results

EGFR mutations were detected in 49.2% of 1004 patients with lung adenocarcinomas. In multivariable analysis, EGFR mutations were significantly associated with early stage disease (stage I to II) at diagnosis (odds ratio [OR], 0.65; 95% confidence interval [CI], 0.49–0.87; P = 0.003). When adjusted for age, sex, smoking status, and screening, the adjusted proportion of EGFR mutations significantly decreased according to stage. The adjusted proportions of EGFR mutations were 57.6% (95% CI, 51.7%–63.3%) for stage I, 47.9% (95% CI, 36.9%–59.0%) for stage II, 47.5% (95% CI, 39.6%–55.5%) for stage III, and 43.4% (95% CI, 38.3%–48.6%) for stage IV (P = 0.0082).

Conclusions

The presence of EGFR mutations is significantly associated with early stage disease at initial diagnosis in lung adenocarcinomas after adjusting for age, sex, smoking status, and screening. This finding implies that EGFR mutations may play a role as a positive prognostic marker.

Serum carcinoembryonic antigen levels before initial treatment are associated with EGFR mutations and EML4- ALK fusion gene in lung adenocarcinoma patients

BACKGROUND

Epidermal growth factor receptor (EGFR) mutations and echinoderm microtubule associated protein like 4-anaplastic lymphoma kinase (EML4-ALK) define specific molecular subsets of lung adenocarcinomas with distinct clinical features. Our purpose was to analyze clinical features and prognostic value of EGFR gene mutations and the EML4-ALK fusion gene in lung adenocarcinoma.

PATIENTS AND METHODS

EGFR gene mutations and the EML4-ALK fusion gene were detected in 92 lung adenocarcinoma patients in China. Tumor marker levels before first treatment were measured by electrochemiluminescence immunoassay.

RESULTS

EGFR mutations were found in 40.2% (37/92) of lung adenocarcinoma patients, being identified at high frequencies in never-smokers (48.3% vs. 26.5% in smokers; P=0.040) and in patients with abnormal serum carcinoembryonic antigen (CEA) levels before the initial treatment (58.3% vs. 28.6%, P=0.004). Multivariate analysis revealed that a higher serum CEA level before the initial treatment was independently associated with EGFR gene mutations (95%CI: 1.476~11.343, P=0.007). We also identified 8 patients who harbored the EML4-ALK fusion gene (8.7%, 8/92). In concordance with previous reports, younger age was a clinical feature for these (P=0.008). Seven of the positive cases were never smokers, and no coexistence with EGFR mutation was discovered. In addition, the frequency of the EML4-ALK fusion gene among patients with a serum CEA concentration below 5 ng/ml seemed to be higher than patients with a concentration over 5 ng/ml (P=0.021). No significant difference was observed for time to progression and overall survival between EML4-ALK-positive group and EML4-ALK-negative group or between patients with and without an EGFR mutation.

CONCLUSIONS

The serum CEA level before the initial treatment may be helpful in screening population for EGFR mutations or EML4-ALK fusion gene presence in lung adenocarcinoma patients.

KRAS Mutation as a Biomarker for Survival in Patients with Non-Small Cell Lung Cancer, A Meta-Analysis of 12 Randomized Trials

BACKGROUND

Because there is no clear consensus for the prognostic implication of KRAS mutations in patients with non-small cell lung cancer (NSCLC), we conducted a meta-analysis based on 12 randomized trials to draw a more accurate conclusion.

MATERIALS AND METHODS

A systematic computer search of articles from inception to May 1, 2014 using the PubMed, EMBASE, and Cochrane databases was conducted. The enrollment of articles and extraction of data were independently performed by two authors.

RESULTS

Our analysis was based on the endpoints overall survival (OS) and progression-free survival (PFS). Nine records (All for OS, 7 for PFS) comprising 12 randomized trials were identified with 3701 patients who underwent a test for KRAS mutations. In the analysis of the pooled hazard ratios (HRs) for OS (HR: 1.39; 95% confidence interval [CI] 1.23-1.56) and PFS (HR: 1.33; 95% CI 1.17-1.51), we found that KRAS mutations are related to poor survival benefit for NSCLC. According to a subgroup analysis stratified by disease stage and line of therapy, the combined HRs for OS and PFS coincided with the finding that the presence of a KRAS mutation is a dismal prognostic factor. However, the prognostic role of KRAS mutations are not statistically significant in a subgroup analysis of patients treated with chemotherapy in combination with cetuximab based on the endpoints OS (P=0.141) and PFS (P=0.643).

CONCLUSIONS

Our results indicate that KRAS mutations are associated with inferior survival benefits for NSCLC but not for those treated with chemotherapies integrating cetuximab.

Association between histopathological subtype, 18F-fluorodeoxyglucose uptake and epidermal growth factor receptor mutations in lung adenocarcinoma

The aim of the present study was to investigate the association between histopathological subtypes, epidermal growth factor receptor (EGFR) mutations and ¹⁸F-fluorodeoxyglucose (FDG) uptake in patients with lung adenocarcinoma (ADC). The cases of 97 patients with lung ADC who underwent ¹⁸F-FDG positron emission tomography-computed tomography prior to surgical resection were retrospectively reviewed. The patients were stratified according to the International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society (IASLC/ATS/ERS) classification, and graded using a histopathological scoring system. EGFR mutations were identified. Clinicopathological characteristics associated with EGFR mutation status were evaluated using univariate and multivariate analyses. EGFR mutation was identified in 45.4% of the patients and was associated with gender, smoking history, maximum standardized uptake value (SUVmax) and histopathological score. ADC patients with a low SUVmax were more likely to exhibit EGFR mutations compared with patients with a high SUVmax (P=0.018). Patients with a lower histopathological score possessed a significantly lower SUVmax compared with patients with a higher score (P<0.001). Furthermore, the histopathological score and smoking history of the patients were identified to be independent predictors for EGFR mutations, according to multivariate logistic regression analysis. In conclusion, SUVmax and EGFR mutations were associated with lung ADC patients stratified according to the IASLC/ATS/ERS classification. Overall, SUVmax has the potential to be a useful marker in stratifying pre-operative patients with lung ADC and identifying EGFR mutations.

Epidermal growth factor receptor mutations in Japanese men with lung adenocarcinomas

BACKGROUND

Epidermal growth factor receptor (EGFR) mutations play a vital role in the prognosis of patients with lung adenocarcinoma. Such somatic mutations are more common in women who are non-smokers with adenocarcinoma and are of Asian origin. However, to our knowledge, there are few studies that have focused on men.

MATERIALS AND METHODS

One hundred and eighty-four consecutive patients (90 men and 94 women) of resected lung adenocarcinoma were studied retrospectively.

RESULTS

EGFR mutations were positive in 48.9% and negative (wild type) in 51.1%. Overall mutation was significant in women (66.0% vs. 32.2%) compared with men (p<0.001). For overall patients, EGFR mutation status was associated with gender, pStage, pT status, lepidic dominant histologic subtype, pure or mixed ground-glass nodule type on computed tomography and smoking status. However, in men, EGFR mutation status was only associated with lepidic dominant histologic subtype and not the other variables. Interestingly, the Brinkman index of men with mutant EGFR also did not differ from that for the wild type (680.0±619.3 vs. 813.1±552.1 p=0.1077).

CONCLUSIONS

The clinical characteristics of men with lung adenocarcinoma related to EGFR mutation are not always similar to that of overall patients. Especially we failed to find the relationship between EGFR mutations and smoking status in men.

Therapeutic effects and adverse drug reactions are affected by icotinib exposure and CYP2C19 and EGFR genotypes in Chinese non-small cell lung cancer patients

BACKGROUND

The aim of this study was to evaluate how CYP2C19 affects icotinib and metabolite' exposure, and to determine whether the exposure and EGFR genotype influences survival time, tumor metastasis and adverse drug reactions.

MATERIALS AND METHODS

274 NSCLC patients who accepted 125 mg icotinib/t.i.d. were chosen from a phase III study. Blood samples were obtained in 672 nd (4th week) and 1,680 th hours (10th week), and plasma was used to quantify the concentration of icotinib and blood cells were sampled to check the genotypes. Clinical data were also collected at the same time, including EGFR genotypes. Plasma concentrations were assessed by HPLC-MS/MS and genotype by sequencing. All data were analyzed through SPSS 17.0 and SAS 9.2.

RESULTS

CYP 2C19 genotypes affected bio-transformation from icotinib to M24 and M26, especially in poor-metabolisers. Higher icotinib concentrations (>1000 ng/mL) not only increased patient PFS and OS but also reduced tumor metastasis. Patients with mutant EGFR experienced a higher median PFS and OS (234 and 627 days), especially those with the 19del genotype demonstrating higher PR ratio. Patients who suffered grade II skin toxicity had a higher icotinib exposure than those with grade I skin toxicity or no adverse effects. Liver toxic reactions might occur in patients with greater M20 and M23 plasma concentrations.

CONCLUSIONS

CYP2C19 polymorphisms significantly affect icotinib, M24 and M26 exposure. Patients with mutant EGFR genotype and higher icotinib concentration might have increased PFS and OS and lower tumor metastasis. Liver ADR events and serious skin effects might be respectively induced by greater M20, M23 and icotinib concentrations.

[Treatment progress for EGFR wild-type advanced non-small cell lung cancer]

Lung cancer is the leading cause of death from cancer in the world. The treatment remains one of the most challenging tasks in the medical world. The discovery and development of epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI) have had a major impact in the treatment of non small cell lung cancer (NSCLC). But the efficacy of EGFR-TKI in EGFR wild-type patients is limited, and the limited EGFR mutation incidence also prompts researchers to study what is the best treatment choice for patients with NSCLC who are negative for EGFR mutations. This review will discuss the research status in treatment choice for EGFR wild-type NSCLC.