Routine EGFR molecular analysis in non-small-cell lung cancer patients is feasible: exons 18-21 sequencing results of 753 patients and subsequent clinical outcomes

Machine learning in prediction of epidermal growth factor receptor status in non-small cell lung cancer brain metastases: a systematic review and meta-analysis

BACKGROUND

Epidermal growth factor receptor (EGFR) mutations are present in 10-60% of all non-small cell lung cancer (NSCLC) patients and are associated with dismal prognosis. Lung cancer brain metastases (LCBM) are a common complication of lung cancer. Predictions of EGFR can help physicians in decision-making and, through optimizing treatment strategies, can result in more favorable outcomes. This systematic review and meta-analysis evaluated the predictive performance of machine learning (ML)-based models in EGFR status in NSCLC patients with brain metastasis.

METHODS

On December 20, 2024, the four electronic databases, Pubmed, Embase, Scopus, and Web of Science, were systematically searched. Studies that evaluated EGFR status in patients with brain metastasis from NSCLC were included.

RESULTS

Twenty studies with 3517 patients with 6205 NSCLC brain metastatic lesions were included. The majority of the best-performance models were ML-based (70%, 7/10), and deep learning (DL)-based models comprised 30% (6/20) of models. The area under the curve (AUC) and accuracy (ACC) of the best-performance models ranged from 0.765 to 1 and 0.69 to 0.93, respectively. The meta-analysis of the best-performance model revealed a pooled AUC of 0.91 (95%CI: 0.88-0.93) and ACC of 0.82 (95%CI: 0.79-0.86) along with a pooled sensitivity of 0.87 (95%CI: 0.83-0.9), specificity of 0.86 (95%CI: 0.79-0.9), and diagnostic odds ratio (DOR) of 35.2 (95%CI: 21.2-58.4). The subgroup analysis did not show significant differences between ML and DL models.

CONCLUSION

ML-based models demonstrated promising predictive outcomes in predicting EGFR status. Applying ML-based models in daily clinical practice can optimize treatment strategies and enhance clinical and radiological outcomes.

Long-Term Outcomes in Patients with EGFR Positive Lung Adenocarcinoma and Subgroup Analysis Based on Presence of Liver Metastases

Lung cancer represents the most common cause of cancer related death. Patients with non-small cell lung cancer (NSCLC) and liver metastases (LM) have worse prognosis with an overall survival (OS) of three to six months. The aim of this study was to investigate long-term outcomes in patients with EGFR mutated (EGFRmut) lung adenocarcinoma as well as the presence of LM. (A total of 105 patients were included in the analysis). They were divided into two groups based on the presence of LM. OS was 13 months for the whole group and also 13 months for patients with and without LM. The 9-year survival rate for patients with and without LM was 12.5% and 3.4%, respectively. Further, the 9-year survival rate for the whole group of patients was 4.8%. There are few data about survival rates beyond 5 years for patients with locally advanced and metastatic EGFRmut NSCLC, mainly because patients with lung cancer rarely live for such a long time. Regarding patients with liver metastases, the results of our study showed similar outcomes compared to patients without LM. As these patients represent a significant number of patients, we need a wider range of therapeutic options. It might be that combination therapies represent a better therapeutic option.

Habitat-Based Radiomics for Predicting EGFR Mutations in Exon 19 and 21 From Brain Metastasis

RATIONALE AND OBJECTIVES

To explore and externally validate habitat-based radiomics for preoperative prediction of epidermal growth factor receptor (EGFR) mutations in exon 19 and 21 from MRI imaging of non-small cell lung cancer (NSCLC)-originated brain metastasis (BM).

METHODS

A total of 170, 62 and 61 patients from center 1, center 2 and center 3, respectively were included. All patients underwent contrast-enhanced T1-weighted (T1CE) and T2-weighted (T2W) MRI scans. Radiomics features were extracted from the tumor active (TA) and peritumoral edema (PE) regions in each MRI slice. The most important features were selected by the least absolute shrinkage and selection operator regression to develop radiomics signatures based on TA (RS-TA), PE (RS-PE) and their combination (RS-Com). Receiver operating characteristic (ROC) curve analysis was performed to access performance of radiomics models for both internal and external validation cohorts.

RESULTS

10, four and six most predictive features were identified to be strongly associated with the EGFR mutation status, exon 19 and exon 21, respectively. The RSs derived from the PE region outperformed those from the TA region for predicting the EGFR mutation, exon 19 and exon 21. The RS-Coms generated the highest performance in the primary training (AUCs, RS-EGFR-Com vs. RS-exon 19-Com vs. RS-exon 21-Com, 0.955 vs. 0.946 vs. 0.928), internal validation (AUCs, RS-EGFR-Com vs. RS-exon 19-Com vs. RS-exon 21-Com, 0.879 vs. 0.819 vs. 0.882), external validation 1 (AUCs, RS-EGFR-Com vs. RS-exon 19-Com vs. RS-exon 21-Com, 0.830 vs. 0.825 vs. 0.822), and external validation 2 (AUCs, RS-EGFR-Com vs. RS-exon 19-Com vs. RS-exon 21-Com, 0.812 vs. 0.818 vs. 0.800) cohort.

CONCLUSION

The developed habitat-based radiomics model can be used to accurately predict the EGFR mutation subtypes, which may potentially guide personalized treatments for NSCLC patients with BM.

Real-world applications of the new grading system in lung adenocarcinoma: A study of 907 patients focusing on revealing the relationship between pathologic grade and genetic status

BACKGROUND

The status of the lung adenocarcinoma (LUAD) grading system and the association between LUAD differentiation, driver genes, and clinicopathological features remain to be elucidated.

METHODS

We included patients with invasive non-mucinous LUAD, evaluated their differentiation, and collected available clinicopathological information, gene mutations, and analyzed clinical outcomes.

RESULTS

Among the 907 patients with invasive non-mucinous LUAD, 321 (35.4 %) were poorly differentiated, 422 (46.5 %) were moderately differentiated, and 164 (18.1 %) were well differentiated. EGFR mutation was more common in the LUADs accompanied without CGP (complex glandular pattern) than LUADs with CGP (p < 0.001). Correlation analysis between mutations and clinical characteristics showed that EGFR gene mutation (p < 0.001), KRAS gene mutation (p < 0.05), and ALK gene rearrangement (p < 0.001) were significantly related to the degree of tumor differentiation, and the KRAS and ALK gene mutation frequencies were higher in the low-differentiation group than in the high and medium differentiation groups. The EGFR mutation frequency was higher in the well/moderately differentiated adenocarcinoma group.

CONCLUSIONS

Our study adds to the evidence regarding the role of the grading system in prognosis. EGFR, KRAS, and ALK are related to the degree of tumor differentiation.

The predictive value of [18F]FDG PET/CT radiomics combined with clinical features for EGFR mutation status in different clinical staging of lung adenocarcinoma

BACKGROUND

This study aims to construct radiomics models based on [¹⁸F]FDG PET/CT using multiple machine learning methods to predict the EGFR mutation status of lung adenocarcinoma and evaluate whether incorporating clinical parameters can improve the performance of radiomics models.

METHODS

A total of 515 patients were retrospectively collected and divided into a training set (n = 404) and an independent testing set (n = 111) according to their examination time. After semi-automatic segmentation of PET/CT images, the radiomics features were extracted, and the best feature sets of CT, PET, and PET/CT modalities were screened out. Nine radiomics models were constructed using logistic regression (LR), random forest (RF), and support vector machine (SVM) methods. According to the performance in the testing set, the best model of the three modalities was kept, and its radiomics score (Rad-score) was calculated. Furthermore, combined with the valuable clinical parameters (gender, smoking history, nodule type, CEA, SCC-Ag), a joint radiomics model was built.

RESULTS

Compared with LR and SVM, the RF Rad-score showed the best performance among the three radiomics models of CT, PET, and PET/CT (training and testing sets AUC: 0.688, 0.666, and 0.698 vs. 0.726, 0.678, and 0.704). Among the three joint models, the PET/CT joint model performed the best (training and testing sets AUC: 0.760 vs. 0.730). The further stratified analysis found that CT_RF had the best prediction effect for stage I-II lesions (training set and testing set AUC: 0.791 vs. 0.797), while PET/CT joint model had the best prediction effect for stage III-IV lesions (training and testing sets AUC: 0.722 vs. 0.723).

CONCLUSIONS

Combining with clinical parameters can improve the predictive performance of PET/CT radiomics model, especially for patients with advanced lung adenocarcinoma.

Identification of Activating Mutations in the Transmembrane and Extracellular Domains of EGFR

The epidermal growth factor receptor (EGFR) is frequently mutated in human cancer, most notably non-small-cell lung cancer and glioblastoma. While many frequently occurring EGFR mutations are known to confer constitutive EGFR activation, the situation is less clear for rarely detected variants. In fact, more than 1000 distinct EGFR mutations are listed in the Catalogue of Somatic Mutations in Cancer (COSMIC), but for most of them, the functional consequence is unknown. To identify additional, previously unknown activating mutations in EGFR, we screened a randomly mutated EGFR library for constitutive EGFR phosphorylation using a recently developed high-throughput approach termed PhosphoFlowSeq. Enrichment of the well-known activating mutations S768I, T790M, and L858R validated the experimental approach. Importantly, we also identified the activating mutations S442I and L658Q located in the extracellular and transmembrane domains of EGFR, respectively. To the best of our knowledge, neither S442I nor L658Q has been associated with an activating phenotype before. However, both have been detected in cancer samples. Interestingly, molecular dynamics (MD) simulations suggest that the L658Q mutation located in the hydrophobic transmembrane region forms intermolecular hydrogen bonds, thereby promoting EGFR dimerization and activation. Based on these findings, we screened the COSMIC database for additional hydrophilic mutations in the EGFR transmembrane region and indeed detected moderate constitutive activation of EGFR-G652R. Together, this study demonstrates that unbiased screening for activating mutations in EGFR not only yields well-established substitutions located in the kinase domain but also activating mutations in other regions of EGFR, including the extracellular and transmembrane domains.

Development and validation of MRI-based radiomics signatures as new markers for preoperative assessment of EGFR mutation and subtypes from bone metastases

Background

This study aimed to develop and externally validate contrast-enhanced (CE) T1-weighted MRI-based radiomics for the identification of epidermal growth factor receptor (EGFR) mutation, exon-19 deletion and exon-21 L858R mutation from MR imaging of spinal bone metastasis from primary lung adenocarcinoma.

Methods

A total of 159 patients from our hospital between January 2017 and September 2021 formed a primary set, and 24 patients from another center between January 2017 and October 2021 formed an independent validation set. Radiomics features were extracted from the CET1 MRI using the Pyradiomics method. The least absolute shrinkage and selection operator (LASSO) regression was applied for selecting the most predictive features. Radiomics signatures (RSs) were developed based on the primary training set to predict EGFR mutations and differentiate between exon-19 deletion and exon-21 L858R. The RSs were validated on the internal and external validation sets using the Receiver Operating Characteristic (ROC) curve analysis.

Results

Eight, three, and five most predictive features were selected to build RS-EGFR, RS-19, and RS-21 for predicting EGFR mutation, exon-19 deletion and exon-21 L858R, respectively. The RSs generated favorable prediction efficacies for the primary (AUCs, RS-EGFR vs. RS-19 vs. RS-21, 0.851 vs. 0.816 vs. 0.814) and external validation (AUCs, RS-EGFR vs. RS-19 vs. RS-21, 0.807 vs. 0.742 vs. 0.792) sets.

Conclusions

Radiomics features from the CE MRI could be used to detect the EGFR mutation, increasing the certainty of identifying exon-19 deletion and exon-21 L858R mutations based on spinal metastasis MR imaging.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09985-4.

Prevalence of Epidermal Growth Factor Receptor Exon 20 Insertion Mutations in Non-small-Cell Lung Cancer in Europe: A Pragmatic Literature Review and Meta-analysis

Background

Information on the epidemiology of uncommon EGFR mutations including exon 20 insertions amongst non-small-cell lung cancer (NSCLC) is lacking.

Objective

The objective of this pragmatic literature review (PLR) and meta-analysis was to generate robust prevalence and incidence estimates based on ranges of exon 20 insertion mutations reported in the literature.

Materials and methods

Searches of MEDLINE, Embase, congresses and reference lists for articles published from 2013 in key European countries of interest (Belgium, France, Germany, Italy, The Netherlands, Spain, Sweden, Switzerland, United Kingdom) were performed. Articles were reviewed against pre-specified criteria and their quality was appraised using a published checklist. Prevalence estimates were synthesised by random-effects meta-analyses.

Results

Eighty unique studies of moderate-to-high quality were included in the PLR. The meta-analysed prevalence for EGFR mutations was 12.5% (95% confidence interval [CI]: 11.0, 14.1) in any stage NSCLC and 14.8% (12.8, 17.1) in advanced/metastatic NSCLC. The prevalence of exon 20 insertions was 0.7% (0.4, 1.1) in any stage NSCLC and 6.1% (4.0, 9.4) in any stage EGFR-positive NSCLC. Mutation status was primarily measured using direct sequencing or a combination of methods. One study reporting exon 20 insertions in advanced/metastatic disease was identified, which reported a prevalence of 0.5% in overall NSCLC and 4.0% in EGFR-positive NSCLC.

Conclusions

EGFR exon 20 insertion mutations are rare in NSCLC. There is a high unmet need in patients with exon 20 insertions, including effective therapies. Prospective cohort studies are needed to better clinically characterise these patients.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11523-022-00868-z.

Uncommon EGFR mutations in non-small-cell lung cancer: A systematic literature review of prevalence and clinical outcomes

Mutations in exons 18-21 of the epidermal growth factor receptor gene (EGFR) can confer sensitivity to EGFR-tyrosine kinase inhibitors (EGFR-TKIs) in patients with non-small-cell lung cancer (NSCLC). Deletions in exon 19 or the exon 21 L858R substitution comprise approximately 85% of mutations, but comparatively few data are available on the remaining "uncommon" mutations. We conducted a systematic literature review to identify evidence on uncommon EGFR mutations in locally advanced/metastatic NSCLC (PROSPERO registration number: CRD42019126583). Electronic screening and congress searches identified studies published in 2012-2020 including patients with locally advanced/metastatic NSCLC and uncommon EGFR mutations (excluding T790M). We assessed the prevalence of uncommon mutations (in studies using direct sequencing of exons 18-21), and compared response to treatment and progression-free survival (PFS) in patients with common versus uncommon mutations and in those with exon 20 mutations versus other uncommon mutations. We identified 64 relevant studies. Uncommon mutations constituted 1.0-18.2% of all EGFR mutations, across 10 studies. The most frequently reported uncommon mutations were G719X (0.9-4.8% of all EGFR mutations), exon 20 insertions (Ex20ins; 0.8-4.2%), L861X (0.5-3.5%), and S768I (0.5-2.5%). Patients with common mutations typically experienced better treatment response and longer PFS on EGFR-TKIs than patients with uncommon mutations; Ex20ins mutations were associated with less favourable outcomes than other uncommon mutations. This review shows that uncommon mutations may comprise a clinically significant proportion of the EGFR mutations occurring in NSCLC, and highlights disparities in EGFR-TKI sensitivity between different uncommon mutations.

Worldwide Prevalence of Epidermal Growth Factor Receptor Mutations in Non-Small Cell Lung Cancer: A Meta-Analysis

Background

Identification of variable epidermal growth factor receptor (EGFR) gene mutations in non-small cell lung cancer (NSCLC) is important for the selection of appropriate targeted therapies. This meta-analysis was conducted to provide a worldwide overview of EGFR mutation and submutation (specifically exon 19 deletions, exon 21 L858R substitutions, and others) prevalence, and identify important covariates that influence EGFR mutation status in patients with advanced NSCLC to address this clinical data gap.

Methods

Embase^® and MEDLINE^® in Ovid were searched for studies published between 2004 and 2019 with cohorts of ≥ 50 adults with EGFR mutations, focusing on stage III/IV NSCLC (≤ 20% of patients with stage I/II NSCLC). Linear mixed-effects models were fitted to EGFR mutation endpoints using logistic transformation (logit), assuming a binomial distribution. The model included terms for an intercept reflecting European studies and further additive terms for other continents. EGFR submutations examined were exon 19 deletions, exon 21 L858R substitutions, and others.

Results

Of 3969 abstracts screened, 57 studies were included in the overall EGFR mutation analysis and 74 were included in the submutation analysis relative to the overall EGFR mutation population (Europe, n = 12; Asia, n = 51; North America, n = 5; Central America, n = 1; South America, n = 1; Oceania, n = 1; Global, n = 3). The final overall EGFR mutations model estimated Asian and European prevalence of 49.1% and 12.8%, respectively, and included an additive covariate for the proportion of male patients in a study. There were no significant covariates in the submutation analyses. Most submutations were actionable: exon 19 deletions (49.2% [Asia]; 48.4% [Europe]); exon 21 L858R substitutions (41.1% [Asia]; 29.9% [Europe]).

Conclusions

Although EGFR mutation prevalence was higher in Asian than Western countries, data support worldwide testing for EGFR overall and submutations to inform appropriate targeted treatment decisions.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40291-021-00563-1.

Value of CT features for predicting EGFR mutations and ALK positivity in patients with lung adenocarcinoma

The aim of this study was to identify the relationships of epidermal growth factor receptor (EGFR) mutations and anaplastic large-cell lymphoma kinase (ALK) status with CT characteristics in adenocarcinoma using the largest patient cohort to date. In this study, preoperative chest CT findings prior to treatment were retrospectively evaluated in 827 surgically resected lung adenocarcinomas. All patients were tested for EGFR mutations and ALK status. EGFR mutations were found in 489 (59.1%) patients, and ALK positivity was found in 57 (7.0%). By logistic regression, the most significant independent prognostic factors of EGFR effective mutations were female sex, nonsmoker status, GGO air bronchograms and pleural retraction. For EGFR mutation prediction, receiver operating characteristic (ROC) curves yielded areas under the curve (AUCs) of 0.682 and 0.758 for clinical only or combined CT features, respectively, with a significant difference (p < 0.001). Furthermore, the exon 21 mutation rate in GGO was significantly higher than the exon 19 mutation rate(p = 0.029). The most significant independent prognostic factors of ALK positivity were age, solid-predominant-subtype tumours, mucinous lung adenocarcinoma, solid tumours and no air bronchograms on CT. ROC curve analysis showed that for predicting ALK positivity, the use of clinical variables combined with CT features (AUC = 0.739) was superior to the use of clinical variables alone (AUC = 0.657), with a significant difference (p = 0.0082). The use of CT features for patients may allow analyses of tumours and more accurately predict patient populations who will benefit from therapies targeting treatment.

A clinically practical radiomics-clinical combined model based on PET/CT data and nomogram predicts EGFR mutation in lung adenocarcinoma

OBJECTIVES

This study aims to develop a clinically practical model to predict EGFR mutation in lung adenocarcinoma patients according to radiomics signatures based on PET/CT and clinical risk factors.

METHODS

This retrospective study included 583 lung adenocarcinoma patients, including 295 (50.60%) patients with EGFR mutation and 288 (49.40%) patients without EGFR mutation. The clinical risk factors associated with lung adenocarcinoma were collected at the same time. We developed PET/CT, CT, and PET radiomics models for the prediction of EGFR mutation using multivariate logistic regression analysis, respectively. We also constructed a combined PET/CT radiomics-clinical model by nomogram analysis. The diagnostic performance and clinical net benefit of this risk-scoring model were examined via receiver operating characteristic (ROC) curve analysis while the clinical usefulness of this model was evaluated by decision curve analysis (DCA).

RESULTS

The ROC analysis showed predictive performance for the PET/CT radiomics model (AUC = 0.76), better than the PET model (AUC = 0.71, Delong test: Z = 3.03, p value = 0.002) and the CT model (AUC = 0.74, Delong test: Z = 1.66, p value = 0.098). Also, the PET/CT radiomics-clinical combined model has a better performance (AUC = 0.84) to predict EGFR mutation than the PET/CT radiomics model (AUC = 0.76, Delong test: D = 2.70, df = 790.81, p value < 0.001) or the clinical model (AUC = 0.81, Delong test: Z = 3.46, p value < 0.001).

CONCLUSIONS

We demonstrated that the combined PET/CT radiomics-clinical model has an advantage to predict EGFR mutation in lung adenocarcinoma.

KEY POINTS

• Radiomics from lung tumor increase the efficiency of the prediction for EGFR mutation in clinical lung adenocarcinoma on PET/CT. • A radiomic nomogram was developed to predict EGFR mutation. • Combining PET/CT radiomics-clinical model has an advantage to predict EGFR mutation.

3D radiomics predicts EGFR mutation, exon-19 deletion and exon-21 L858R mutation in lung adenocarcinoma

BACKGROUND

To establish a radiomic approach to identify epidermal growth factor receptor (EGFR) mutation status in lung adenocarcinoma patients based on CT images, and to distinguish exon-19 deletion and exon-21 L858R mutation.

METHODS

Two hundred sixty-three patients who underwent pre-surgical contrast-enhanced CT and molecular testing were included, and randomly divided into the training (80%) and test (20%) cohort. Tumor images were three-dimensionally segmented to extract 1,672 radiomic features. Clinical features (age, gender, and smoking history) were added to build classification models together with radiomic features. Subsequently, the top-10 most relevant features were used to establish classifiers. For the classifying tasks including EGFR mutation, exon-19 deletion, and exon-21 L858R mutation, four logistic regression models were established for each task.

RESULTS

The training and test cohort consisted of 210 and 53 patients, respectively. Among the established models, the highest accuracy and sensitivity among the four models were 75.5% (61.7-86.2%) and 92.9% (76.5-99.1%) to classify EGFR mutation, respectively. The highest specificity values were 86.7% (69.3-96.2%) and 70.4% (49.8-86.3%) to classify exon-19 deletion and exon-21 L858R mutation, respectively.

CONCLUSIONS

CT radiomics can sensitively identify the presence of EGFR mutation, and increase the certainty of distinguishing exon-19 deletion and exon-21 L858R mutation in lung adenocarcinoma patients. CT radiomics may become a helpful non-invasive biomarker to select EGFR mutation patients for invasive sampling.

CT features associated with EGFR mutations and ALK positivity in patients with multiple primary lung adenocarcinomas

Background

In multiple primary lung adenocarcinomas (MPLAs), the relationship between imaging and gene mutations remains unclear. This retrospective study aimed to identify the correlation of epidermal growth factor receptor (EGFR) mutations and anaplastic lymphoma kinase (ALK) status with CT characteristics in MPLA patients.

Methods

Sixty-seven patients (135 lesions) with MPLAs confirmed by pathology were selected from our institution. All subjects were tested for EGFR mutations and ALK status and underwent chest CT prior to any treatment. The criteria for MPLA definitions closely adhered to the comprehensive histologic assessment (CHA).

Results

Among MPLA patients, EGFR mutations were more common in females (p = 0.002), in those who had never smoked (p = 0.010), and in those with less lymph node metastasis (p < 0.001), and the tumours typically presented with ground-glass opacity (GGO) (p = 0.003), especially mixed GGO (p < 0.001), and with air bronchograms (p = 0.012). Logistics regression analysis showed that GGO (OR = 6.550, p = 0.010) was correlated with EGFR mutation, while air bronchograms were not correlated with EGFR mutation (OR = 3.527, p = 0.060). A receiver operating characteristic (ROC) curve yielded area under the curve (AUC) values of 0.647 and 0.712 for clinical-only or combined CT features, respectively, for prediction of EGFR mutations, and a significant difference was found between them (p = 0.0344). ALK-positive status was found most frequently in MPLA patients who were younger (p = 0.002) and had never smoked (p = 0.010). ALK positivity was associated with solid nodules or masses in MPLAs (p < 0.004) on CT scans. Logistics regression analysis showed that solid nodules (OR = 6.550, p = 0.010) were an independent factor predicting ALK positivity in MPLAs. For prediction of ALK positivity, the ROC curve yielded AUC values of 0.767 and 0.804 for clinical-only or combined CT features, respectively, but no significant difference was found between them (p = 0.2267).

Conclusion

Among MPLA patients, nonsmoking women with less lymph node metastasis and patients with lesions presenting GGO or mixed GGO and air bronchograms on CT were more likely to exhibit EGFR mutations. In nonsmoking patients, young patients with solid lesions on CT are recommended to undergo an ALK status test.

Clinical Impact of Rare and Compound Mutations of Epidermal Growth Factor Receptor in Patients With Non-Small-Cell Lung Cancer

BACKGROUND

Standard therapy of advanced non-small-cell lung cancer harboring an activating mutation in the epidermal growth factor receptor (EGFR) gene is treatment with tyrosine kinase inhibitors (TKI). However, for rare and compound mutations of the EGFR gene, the clinical evidence of TKI therapy is still unclear.

PATIENTS AND METHODS

A total of 2906 lung cancer samples were analyzed for EGFR mutations during routine analysis between 2010 and 2017. The samples have been investigated by Sanger sequencing and since 2014 by next-generation sequencing.

RESULTS

We detected EGFR mutations in 408 specimens (14%). Among these, we found 41 samples with rare and 22 with compound mutations. In these 63 samples, 56 different rare EGFR mutations occurred. Information about the clinical outcome was available for 37. Among those with rare mutations, only one patient harboring the mutation p.G874D had disease that responded to first-generation TKI therapy. In contrast, the disease of all patients with compound mutations responded to first- or second-generation TKI therapy. Furthermore, we collected data on clinical relevance regarding TKI therapy from different databases and from an additional literature search, and only found data for 36 of the 56 detected rare mutations.

CONCLUSION

Information about the clinical outcome of patients with rare and compound EGFR mutations remains limited. At present, second- and third-generation TKIs are available, which may represent new treatment strategies for these patients. Therefore, it is becoming increasingly important to maintain databases concerning rare EGFR mutations.

Radiomics signature: A potential and incremental predictor for EGFR mutation status in NSCLC patients, comparison with CT morphology

OBJECTIVES

To compare the predictive performance of radiomics signature and CT morphological features for epidermal growth factor receptor (EGFR) mutation status; then further to develop and compare the different predictive models for EGFR mutation in non-small cell lung cancer (NSCLC) patients.

MATERIALS AND METHODS

This retrospective study involved 404 patients with NSCLC (243 cases in the training cohort and 161 cases in the validation cohort). Radiomics features were extracted from preoperative non-contrast CT images of the entire tumor. Correlations between the EGFR mutation status and candidate predictors were assessed using Mann-Whitney U test or Chi-square test. Unsupervised consensus clustering was used to analyze the representativeness and reduce the redundancy of radiomics features. Multivariable logistic regression analysis was performed to build radiomics signature and develop predictive models of EGFR mutation. ROC curve analysis and Delong test were used to compare the predictive performance among individual features and models.

RESULTS

Of the 234 radiomics features, 93 radiomics features with high repeatability and high predictive significance were selected. The radiomics signature, which was built with one histogram and two textural features, showed the best predictive performance (AUC = 0.762 and 0.775 in the training and validation cohort) in comparison with all the clinical characteristics and conventional CT morphological features to differentiate EGFR mutation status (P < 0.05). The integrated model was developed with maximum diameter, location, sex and radiomics signature. In the training and validation cohort, the integrated model showed the most optimal predictive performance (AUC = 0.798, 0.818 in the training and validation cohort) compared with the clinical models.

CONCLUSION

The radiomics signature showed better performance for predicting EGFR mutant than all the clinical and morphological features. Moreover, the integrated model built with radiomics signature, clinical and morphological features outperformed the clinical models, which is helpful for physicians to determine the targeted therapy.

Gefitinib provides similar effectiveness and improved safety than erlotinib for advanced non-small cell lung cancer: A meta-analysis

BACKGROUND

The epidermal growth factor receptor tyrosine kinase inhibitors gefitinib and erlotinib are effective for advanced non-small cell lung cancer (NSCLC). This meta-analysis compared their effectiveness and safety.

METHODS

We searched systematically in PubMed, ScienceDirect, The Cochrane Library, Scopus, Ovid MEDLINE, EMBASE, Web of Science, and Google Scholar for relevant clinical trials regarding gefitinib versus erlotinib for NSCLC. Antitumor effectiveness (overall survival [OS], progression-free survival [PFS], objective response rate [ORR] and disease control rate [DCR]) and adverse effects [AEs]) were assessed.

RESULTS

Forty studies comprising 9376 participants were included. The results suggested that gefitinib and erlotinib are effective for advanced NSCLC with comparable PFS (95% confidence intervals [CI]: 0.98-1.11, P = .15), OS (95% CI: 0.93-1.19, P = .45), ORR (95% CI: 0.99-1.16, P = .07), and DCR (95% CI: 0.92-1.03, P = .35). For erlotinib, dose reduction was significantly more frequent (95% CI: 0.10-0.57, P = .001) as were grade 3 to 5 AEs (95% CI: 0.36-0.79, P = .002). In the subgroup analysis, the erlotinib group had a significant higher rate and severity of skin rash, nausea/vomiting, fatigue, and stomatitis.

CONCLUSIONS

Gefitinib was proven to be the better choice for advanced NSCLC, with equal antitumor effectiveness and fewer AEs compared with erlotinib. Further large-scale, well-designed randomized controlled trials are warranted to confirm our validation.

Prognostic and predictive role of EGFR pathway alterations in biliary cancer patients treated with chemotherapy and anti-EGFR

The association of anti-EGFR to gemcitabine and oxaliplatin (GEMOX) chemotherapy did not improve survival in biliary tract carcinoma (BTC) patients. Multiple mechanisms might be involved in the resistance to anti-EGFR. Here, we explored the mutation profile of EGFR extracellular domain (ECD), of tyrosine kinase domain (TKD), and its amplification status. EGFR mutational status of exons 12, 18–21 was analyzed in 57 tumors by Sanger sequencing. EGFR amplification was evaluated in 37 tumors by Fluorescent In Situ Hybridization (FISH). Kaplan-Meier curves were calculated using the log-rank test. Six patients had mutations in exon 12 of EGFR ECD and 7 in EGFR TKD. Neither EGFR ECD nor TKD mutations affected progression free survival (PFS) or overall survival (OS) in the entire population. In the panitumumab plus GEMOX (P-GEMOX) arm, ECD mutated patients had a worse OS, while EGFR TKD mutated patients had a trend towards shorter PFS and OS. Overall, the presence of mutations in EGFR or in its transducers did not affect PFS or OS, while the extrahepatic cholangiocarcinoma (ECC) mutated patients had a worse prognosis compared to WT. Nineteen out of 37 tumors were EGFR amplified, but the amplification did not correlate with survival. ECC EGFR amplified patients had improved OS, whereas the amplification significantly correlated with poor PFS (p = 0.03) in gallbladder carcinoma patients. The high molecular heterogeneity is a predominant feature of BTC: the alterations found in this work seem to have a prognostic impact rather than a predictive role towards anti-EGFR therapy.

Prevalence of EGFR Mutations in Lung Cancer in Uruguayan Population

BACKGROUND

Incorporation of molecular analysis of the epidermal growth factor receptor (EGFR) gene into routine clinical practice represents a milestone for personalized therapy of the non-small-cell lung cancer (NSCLC). However, the genetic testing of EGFR mutations has not yet become a routine clinical practice in developing countries. In view of different prevalence of such mutations among different ethnicities and geographic regions, as well as the limited existing data from Latin America, our aim was to study the frequency of major types of activating mutations of the EGFR gene in NSCLC patients from Uruguay.

METHODS

We examined EGFR mutations in exons 18 through 21 in 289 NSCLC Uruguayan patients by PCR-direct sequencing.

RESULTS

EGFR mutations were detected in 53 of the 289 (18.3%) patients, more frequently in women (23.4%) than in men (14.5%). The distribution by exon was similar to that generally reported in the literature.

CONCLUSIONS

This first epidemiological study of EGFR mutations in Uruguay reveals a wide spectrum of mutations and an overall prevalence of 18.3%. The background ethnic structure of the Uruguayan population could play an important role in explaining our findings.

Structural basis of mutant-selectivity and drug-resistance related to CO-1686

Non-small-cell lung cancers (NSCLCs) caused by activating mutations in the kinase domain of epidermal growth factor receptor (EGFR) initially respond to first-generation reversible drugs gefitinib and erlotinib. However, clinical efficacy is limited due to the development of drug-resistance that in more than half of the cases are driven by the secondary T790M mutation. CO-1686 is one of the third generation irreversible inhibitors that inhibits EGFR activating mutants, including those with concurrent T790M, while avoiding the off-target toxicity owing to inhibition of wild-type EGFR in treating EGFR mutation-positive NSCLCs. Despite the remarkable success, the experimentally determined structure of this agent in complex with EGFR T790M remains unknown. In this study, we determined crystal structures of EGFR T790M or L858R mutants covalently bound by CO-1686. Based on these structural data, we can explain why CO-1686 irreversibly inhibits EGFR and selectively prefers T790M, which may help improving this or similar compounds, and explain why EGFR L718Q and L844V mutations incur resistance to this agent.

Characterization of common and rare mutations in EGFR and associated clinicopathological features in a large population of Chinese patients with lung cancer

Lung cancer with EGFR mutation is often associated pathological characteristics and good responses to EGFR tyrosine kinase inhibitors (TKIs). However, certain types of rare EGFR mutations have be linked to cases with poor response to EGFR TKIs. Therefore, extensive molecular screening and pathological characterization are essential for accurate diagnosis and selection of effective treatment plans. Although a large body of studies have established the rate of EGFR mutations as a whole entity, the rates of each individual types of mutations, especially those rare ones, have not been precisely determined in large patient populations with uniform genetic background. To address this issue, we assembled a large cohort of 456 Chinese patients with lung cancers to determine the rate of both common and rare forms of EGFR mutations and associated clinicopathological features in this retrospective study. We have found single or double EGFR mutations in 200 (43.9%) patients, including exon 19 deletions (E19del) (20%), exon 21 L858R (17.1%) and L861Q (1.5%) point mutations, exon 20 T790M (1.3%) and other mutations (1,3%), exon 18 mutations (1.3%), and double mutations (1.3%). EGFR mutation as well as its subtypes E19del, L858R, or double mutations were associated with female patients or never-smokers. In contrast, rare mutations, especially EGFR TKI resistant exon 20 mutations, were not statistically associated with any clinicopathological features, implicating that tumorigenesis driven by different EGFR mutations were mechanistically different. In summary, we have determined occurring rate of EGFR subtype mutations and demonstrated that different mutations showed different clinicopathological manifestations in lung cancer.

Comparison of gefitinib, erlotinib and afatinib in non-small cell lung cancer: A meta-analysis

Gefitinib, erlotinib and afatinib are three widely used epidermal growth factor receptor tyrosine kinase inhibitors (EGFR TKIs) for treating advanced non-small cell lung cancer (NSCLC) with proven efficacy. We undertook a systematic review and meta-analysis to synthesize existing studies with direct comparisons of EGFR TKIs in NSCLC in terms of both efficacy and safety. Eight randomized trials and 82 cohort studies with a total of 17,621 patients were included for analysis. Gefitinib and erlotinib demonstrated comparable effects on progression-free survival (hazard ratio [HR], 1.00; 95% confidence interval [CI], 0.95 to 1.04), overall survival (HR, 0.99; 95% CI, 0.93 to 1.06), overall response rate (risk ratio [RR], 1.05; 95% CI, 1.00 to 1.11), and disease control rate (RR, 0.98; 95% CI, 0.96 to 1.01), which did not vary considerably with EGFR mutation status, ethnicity, line of treatment, and baseline brain metastasis status. Gefitinib was associated with more grade 3/4 liver dysfunction, but tended to cause lower rates of dose reduction, treatment discontinuation, total grade 3/4 adverse events (RR, 0.78; 95% CI 0.65 to 0.94), and a number of specific adverse events such as rash and diarrhea. No solid evidence was found that afatinib had greater efficacy than gefitinib or erlotinib in first-line treatment of EGFR-mutant NSCLC. However, afatinib was more effective than erlotinib as second-line treatment of patients with advanced squamous cell carcinoma. The grade 3/4 adverse events rate of afatinib was comparable to that of erlotinib but higher than that of gefitinib.

Prospective Comprehensive Molecular Characterization of Lung Adenocarcinomas for Efficient Patient Matching to Approved and Emerging Therapies

Tumor genetic testing is standard of care for patients with advanced lung adenocarcinoma, but the fraction of patients who derive clinical benefit remains undefined. Here, we report the experience of 860 patients with metastatic lung adenocarcinoma analyzed prospectively for mutations in >300 cancer-associated genes. Potentially actionable genetic events were stratified into one of four levels based upon published clinical or laboratory evidence that the mutation in question confers increased sensitivity to standard or investigational therapies. Overall, 37.1% (319/860) of patients received a matched therapy guided by their tumor molecular profile. Excluding alterations associated with standard-of-care therapy, 14.4% (69/478) received matched therapy, with a clinical benefit of 52%. Use of matched therapy was strongly influenced by the level of preexistent clinical evidence that the mutation identified predicts for drug response. Analysis of genes mutated significantly more often in tumors without known actionable mutations nominated STK11 and KEAP1 as possible targetable mitogenic drivers.Significance: An increasing number of therapies that target molecular alterations required for tumor maintenance and progression have demonstrated clinical activity in patients with lung adenocarcinoma. The data reported here suggest that broader, early testing for molecular alterations that have not yet been recognized as standard-of-care predictive biomarkers of drug response could accelerate the development of targeted agents for rare mutational events and could result in improved clinical outcomes. Cancer Discov; 7(6); 596-609. ©2017 AACR.See related commentary by Liu et al., p. 555This article is highlighted in the In This Issue feature, p. 539.

Determining EGFR-TKI sensitivity of G719X and other uncommon EGFR mutations in non-small cell lung cancer: Perplexity and solution (Review)

Mutations in epidermal growth factor receptor (EGFR) play critical roles in the pathogenesis of non-small cell lung cancer (NSCLC), and they are highly associated with sensitivity to tyrosine kinase inhibitors (TKIs). While the pathogenic and pharmacological characteristics of common mutations in EGFR have been thoroughly investigated, those of uncommon mutations remain to be elucidated. Traditional approaches to study common mutations by randomized controlled trials are not feasible for uncommon mutations owing to their rarity. Therefore, by systematically reviewing laboratory and clinical studies of the G719X mutation, one of the uncommon mutations, we concluded that the G719X mutation was intermediately sensitive to TKIs, with an average response rate of 35.1% (47/134). Moreover, accordingly, we proposed a comprehensive model to investigate uncommon mutations in EGFR. The model involves both basic and clinical components, composed of structural analyses, functional alterations, cell viabilities and animal models with various types of clinical studies. In this review, we systematically reviewed studies of the G719X mutation and put forward a research model that could be generalized to explore uncommon mutations in diseases associated with gene mutations.

New developments in the management of non-small-cell lung cancer, focus on rociletinib: what went wrong?

Recently, the development of the third-generation epidermal growth factor receptor-small molecule inhibitor (EGFR-TKI) rociletinib had failed. In this review, the wide-ranging aspects of the evolution of EGFR-TKIs were collected, with a special focus on rociletinib. The influence of different oncogenic mutations on EGFR activity was also discussed. Resistance to the first (erlotinib, gefitinib)- and second (afatinib)-generation EGFR-TKIs provided the rationale behind the development of the third-generation inhibitors (rociletinib, osimertinib). On the basis of these data, a comparison of their efficacy on the different mutated EGFRs and the respective resistance mechanisms is further reported. Moreover, the evolution and results of the clinical trials of rociletinib (TIGER trials) are compared with the trials on osimertinib, another third-generation EGFR-TKI that now has been granted US Food and Drug Administration approval. The reasons behind the arrest in the further development of rociletinib are put in the perspective of future drug development.

Comparison of next generation sequencing, SNaPshot assay and real-time polymerase chain reaction for lung adenocarcinoma EGFR mutation assessment

BACKGROUND

The epidermal growth factor receptor (EGFR) mutation status assessment has become increasingly important given the significant impact of tyrosine kinase inhibitors in lung cancer management. Our aim was to compare real life operational characteristics for three EGFR mutation assays - two targeted approaches and a next generation sequencing (NGS) technique.

METHODS

EGFR mutation status was assessed for lung adenocarcinoma samples (formalin fixed- paraffin embedded samples) using qPCR, SNaPshot and NGS (Ion Torrent™) techniques.

RESULTS

A total of 15 high clinical significance mutations were identified by at least one technique from the total of 64 samples. All mutations were identified by the TaqMan qPCR technique while SNaPshot in conjunction with fragment analysis identified 11 EGFR mutations. The NGS approach followed by an automatic analysis using the default calling parameters identified 10 mutations from the SNaPshot/qPCR panel and other three insertions, five point mutations and 58 silent variants; manual data review identified all 15 high significance mutations.

CONCLUSIONS

Performance was similar for high tumor content samples but careful data analysis and post hoc variant calling filter alterations were necessary in order to obtain robust results from low tumor content samples by NGS. NGS is able to generate a comprehensive mutational profile albeit at a higher cost and workload. Result interpretation should take into account not only general run parameters such as mean read depth but also relative coverage and read distribution; currently there is an acute need to define firm recommendations/standards concerning NGS data interpretation and quality control.

Radiomic Features Are Associated With EGFR Mutation Status in Lung Adenocarcinomas

BACKGROUND

In this study we retrospectively evaluated the capability of computed tomography (CT)-based radiomic features to predict epidermal growth factor receptor (EGFR) mutation status in surgically-resected peripheral lung adenocarcinomas in an Asian cohort of patients.

PATIENTS AND METHODS

Two hundred ninety-eight patients with surgically resected peripheral lung adenocarcinomas were investigated in this institutional review board-approved retrospective study with requirement waived to obtain informed consent. Two hundred nineteen quantitative 3-D features were extracted from segmented volumes of each tumor, and 59 of these, which were considered independent features, were included in the analysis. Clinical and pathological information was obtained from the institutional database.

RESULTS

Mutant EGFR was significantly associated with female sex (P = .0005); never smoker status (P < .0001), lepidic predominant adenocarcinomas (P = .017), and low or intermediate pathologic grade (P = .0002). Statistically significant differences were found in 11 radiomic features between EGFR mutant and wild type groups in univariate analysis. Mutant EGFR status could be predicted by a set of 5 radiomic features that fell into 3 broad groups: CT attenuation energy, tumor main direction, and texture defined according to wavelets and Laws (area under the curve [AUC], 0.647). A multiple logistic regression model showed that adding radiomic features to a clinical model resulted in a significant improvement of predicting power, because the AUC increased from 0.667 to 0.709 (P < .0001).

CONCLUSION

Computed tomography-based radiomic features of peripheral lung adenocarcinomas can capture useful information regarding tumor phenotype, and the model we built can be useful to predict the presence of EGFR mutations in peripheral lung adenocarcinoma in Asian patients when mutational profiling is not available or possible.

A novel microfluidic device that integrates nucleic acid extraction, amplification, and detection to identify an EGFR mutation in lung cancer tissues

A novel microfluidic to detect a EGFR mutation in 40 min in an easy way for personalized medicine.

Cancer Genomics: Diversity and Disparity Across Ethnicity and Geography

Ethnic and geographic differences in cancer incidence, prognosis, and treatment outcomes can be attributed to diversity in the inherited (germline) and somatic genome. Although international large-scale sequencing efforts are beginning to unravel the genomic underpinnings of cancer traits, much remains to be known about the underlying mechanisms and determinants of genomic diversity. Carcinogenesis is a dynamic, complex phenomenon representing the interplay between genetic and environmental factors that results in divergent phenotypes across ethnicities and geography. For example, compared with whites, there is a higher incidence of prostate cancer among Africans and African Americans, and the disease is generally more aggressive and fatal. Genome-wide association studies have identified germline susceptibility loci that may account for differences between the African and non-African patients, but the lack of availability of appropriate cohorts for replication studies and the incomplete understanding of genomic architecture across populations pose major limitations. We further discuss the transformative potential of routine diagnostic evaluation for actionable somatic alterations, using lung cancer as an example, highlighting implications of population disparities, current hurdles in implementation, and the far-reaching potential of clinical genomics in enhancing cancer prevention, diagnosis, and treatment. As we enter the era of precision cancer medicine, a concerted multinational effort is key to addressing population and genomic diversity as well as overcoming barriers and geographical disparities in research and health care delivery.

EGFR Mutations and Resistance to Irreversible Pyrimidine-Based EGFR Inhibitors

PURPOSE

Mutant selective irreversible pyrimidine-based EGFR kinase inhibitors, including WZ4002, CO-1686, and AZD9291, are effective in preclinical models and in lung cancer patients harboring the EGFR T790M gefitinib/erlotinib resistance mutation. However, little is known about how cancers develop acquired resistance to this class of EGFR inhibitors. We sought to identify and study EGFR mutations that confer resistance to this class of agents.

EXPERIMENTAL DESIGN

We performed an N-ethyl-N-nitrosourea (ENU) mutagenesis screen in EGFR-mutant (sensitizing alone or with concurrent EGFR T790M) Ba/F3 cells and selected drug-resistant clones. We evaluated the sensitivity of EGFR inhibitors in models harboring drug-resistant EGFR mutations.

RESULTS

We identified 3 major drug resistance mutations. EGFR L718Q, L844V, and C797S cause resistance to both WZ4002 and CO-1686 while, in contrast, only EGFR C797S leads to AZD9291 resistance. Cells containing an EGFR-sensitizing mutation, Del 19 or L858R, in conjunction with L718Q, L844V, or C797S retain sensitivity to quinazoline-based EGFR inhibitors, gefitinib and afatinib. The C797S mutation, in the presence of Del 19 or L858R and T790M, causes resistance to all current EGFR inhibitors, but L858R/T790M/C797S remains partially sensitive to cetuximab which leads to disruption of EGFR dimerization.

CONCLUSIONS

Our findings provide insights into resistance mechanisms to irreversible pyrimidine-based EGFR inhibitors and identify specific genomic contexts in which sensitivity is retained to existing clinical EGFR inhibitors. These findings will guide the development of new strategies to inhibit EGFR.

Epidermal growth factor receptor in non-small cell lung cancer

Following the identification of a group of patients in the initial tyrosine kinase inhibitor (TKI) trials for lung cancer, there has been detailed focus on which patients may benefit from inhibitor therapy. This article reviews the background, genetics and prevalence of epidermal growth factor mutations in non-small cell lung cancer (NSCLC). Additionally, the prevalence in unselected patients is compared against various other reviews.

Liver metastasis predicts poorer prognosis in stage IV lung adenocarcinoma patients receiving first-line gefitinib

OBJECTIVES

Gefitinib is currently used as a first-line therapy in patients of advanced non-small cell lung cancer (NSCLC) with susceptible epidermal growth factor receptor (EGFR) mutations. However, treatment outcomes of these patients vary. This study was conducted to evaluate the impact of specific metastatic sites on treatment outcomes of patients with stage IV lung adenocarcinoma with susceptible EGFR mutations receiving first-line gefitinib, focusing on the impact of liver metastasis.

MATERIALS AND METHODS

Between October 2009 and April 2014, patients of stage IV lung adenocarcinoma harboring EGFR mutation in exon 19 or 21, who received first-line gefitinib treatment, were enrolled in two hospitals and followed until December 22, 2014. The impacts of various clinical features, including sex, age, smoking history, performance status, EGFR mutation site, metastatic sites, etc., on progression-free survival (PFS) and overall survival (OS) were analyzed.

RESULTS

A total of 148 patients were eligible for analysis. Patients with liver metastasis on initial diagnosis (n=19) had shorter PFS and OS than those without liver metastasis did (median of PFS, 6.7 vs. 11.2 months, p<0.0001; median of OS, 9.2 vs. 17.5 months, p<0.0001). Multivariable Cox regression analysis showed liver metastasis was an independent poor prognostic factor for PFS (HR=2.939 [95% CI: 1.729-4.997], p<0.0001) and OS (HR=3.300 [95% CI: 1.708-6.373], p=0.0004).

CONCLUSION

Liver metastasis predicts poorer PFS and OS in stage IV lung adenocarcinoma patients with susceptible gene mutations receiving first-line gefitinib. Further study is warranted to elucidate the underlying mechanisms and find treatment modalities to improve prognosis of these patients.

Expression of EGFR and molecules downstream to PI3K/Akt, Raf-1-MEK-1-MAP (Erk1/2), and JAK (STAT3) pathways in invasive lung adenocarcinomas resected at a single institution

Therapies targeting EGFR are effective in treating tumors that harbor molecular alterations; however, there is heterogeneity in long-term response to these therapies. We retrospectively analyzed protein expression of EGFR, Stat3, phospho-Akt, and phospho-Erk1/2 by immunohistochemistry in a series of resected cases from a single institution, correlated with clinicopathological variables. There were 96 patients, with the majority of cases being of low stage tumors (17 pT1a, 23 pT1b, 30 pT2a, and 18 pT2b). Histologic subtypes were 45 acinar predominant, 2 cribriform, 25 solid, 7 papillary, 11 lepidic, and 4 mucinous tumors. The EGFR score was higher in tumors with vascular invasion (P = 0.013), in solid and cribriform acinar histology, and in high stage tumors (P = 0.006 and P = 0.01). EGFR was more likely overexpressed in solid compared to lepidic tumors (P = 0.02). Acinar tumors had the highest rate of ERK1/2 positivity (19%). There was a strong correlation among positivity for ERCC1 and other markers, including STAT3 (P = 0.003), Akt (P = 0.02), and ERK1/ERK2 (P = 0.0005). Expression of molecules downstream to EGFR varied from 12% to 31% of tumors; however, the expression did not directly correlate to EGFR expression, which may suggest activation of the cascades through different pathways. The correlation of protein expression and the new lung adenocarcinoma classification may help in the understanding of activated pathways of each tumor type, which may act in the oncogenesis and drug resistance of these tumors.

Lentiviral vector-mediated RBM5 overexpression downregulates EGFR expression in human non-small cell lung cancer cells

Background

RNA binding motif 5 (RBM5) is a tumor suppressor gene that modulates apoptosis through the regulation of alternative splicing of apoptosis-related genes. Our previous studies suggested that RBM5 expression was negatively correlated with the expression of epidermal growth factor receptor (EGFR) in non-small cell lung cancer (NSCLC) tissues. This study was aimed at determining whether RBM5 is able to regulate EGFR expression.

Methods

Both in vitro and in vivo studies were carried out to determine the effect of RBM5 on the expression of EGFR. Lentiviral vector-mediated RBM5 overexpression was employed in lung adenocarcinoma cell line A549. A549 xenograft mice were treated with recombinant RBM5 plasmid carried by attenuated Salmonella typhi Ty21a. Real-time quantitative polymerase chain reaction and Western blot were carried out to detect RBM5 and EGFR expression.

Results

Both in vivo and in vitro studies indicated that the expression of EGFR mRNA and protein was decreased significantly in the RBM5 overexpression group compared to control groups as shown by real-time PCR and Western blot analysis. We identified that RBM5 overexpression inhibited EGFR expression both in A549 cells and in A549 xenograft mice model.

Conclusions

Our study demonstrated that EGFR expression is regulated by RBM5 in lung adenocarcinomas cells either in a direct or indirect way, which might be meaningful with regards to target therapy in lung cancer.

Epidermal growth factor receptor mutations in lung adenocarcinoma

Despite tremendous progress in the last decade, lung adenocarcinoma still represents a tumor with unfavorable prognosis when detected at advanced clinical stage. High-stage tumors are not amenable to surgical resection, and therefore systemic therapies are needed to control these tumors to prolong patient survival. In the era of molecular and personalized therapeutics, the discovery of mutations in epidermal growth factor receptor (EGFR) in 15-20% of lung adenocarcinomas and the associated response to EGFR-targeting tyrosine kinase (TK) inhibitors have provided a successful avenue of attack in high-stage adenocarcinomas. In this review, we will provide an overview of the EGFR pathway, review the significant somatic EGFR alterations in lung adenocarcinoma and highlight their implications for treatment. In addition, we will examine pathways by which tumors resist EGFR TK therapy, both as primary nonresponders and by acquired resistance. In doing so, we will examine other oncogenic pathways whose status in tumor samples may impact therapeutic responses despite presence of activating EGFR mutations.