EGFR Mutation Subtypes Influence Survival Outcomes following First-Line Gefitinib Therapy in Advanced Asian NSCLC Patients

Clinicopathological and molecular characterization of resected lung adenocarcinoma: Correlations with histopathological grading systems in Chinese patients

PURPOSE

Driver mutations inform lung adenocarcinoma (LUAD) targeted therapy. Association of histopathological attributes and molecular profiles facilitates clinically viable testing platforms. We assessed correlations between LUAD clinicopathological features, mutational landscapes, and two grading systems among Chinese cases.

METHODS

79 Chinese LUAD patients undergoing resection were subjected to targeted sequencing. 68 were invasive nonmucinous adenocarcinoma (INMA), graded via: predominant histologic pattern-based grading system (P-GS) or novel IASLC grading system (I-GS). Driver mutation distributions were appraised and correlated with clinical and pathological data.

RESULTS

Compared to INMA, non-INMA exhibited smaller, well-differentiated tumors with higher mucin content. INMA grade correlated with size, lymph invasion (P-GS), and driver/EGFR mutations. Mutational spectra varied markedly between grades, with EGFR p.L858R and exon 19 deletion mutations predominating in lower grades; while high-grade P-GS tumors often harbored EGFR copy number variants and complex alterations alongside wild-type cases. I-GS upgrade of P-GS grade 2 to grade 3 was underpinned by ≥20 % high-grade regions bearing p.L858R or ALK fusions. Both systems defined tumors of distinctive phenotypic attributes and molecular genotypes.

CONCLUSIONS

INMA represent larger, mucin-poor, molecularly heterogeneous LUAD with divergent grade-specific mutation profiles. Stronger predictor of clinicopathological attributes and driver mutations, P-GS stratification offers greater accuracy for molecular testing. A small panel encompassing EGFR and ALK captures the majority of P-GS grade 1/2 mutations whereas expanded panels are optimal for grade 3.

RELAY, Erlotinib Plus Ramucirumab in Untreated, EGFR-Mutated, Metastatic NSCLC: Outcomes by EGFR Exon 19 Deletion Variants

Introduction

EGFR gene mutations are drivers of NSCLC. The RELAY double-blind, placebo (PBO)-controlled phase 3 study revealed superior progression-free survival (PFS) for ramucirumab plus erlotinib (RAM + ERL) versus PBO (PBO + ERL) in patients with untreated advanced NSCLC and an EGFR-activating mutation. This exploratory analysis evaluated potential associations between EGFR exon 19 deletion (ex19del) variants and clinical outcomes.

Methods

Patients (N = 449) were randomized (1:1) to RAM plus ERL or PBO plus ERL. Plasma samples were collected at baseline, on treatment, and at 30-day post-study treatment discontinuation follow-up. Baseline and treatment-emergent gene alterations were investigated by Guardant360 next-generation sequencing. Patients with a valid baseline plasma sample and ex19del were included (RAM + ERL, n = 62; PBO + ERL, n = 72).

Results

The most common ex19del variant was E746_A750del (67.2%); EGFR E746 deletions (E746del) occurred more frequently than L747 deletions (74.6% versus 25.4%, respectively). TP53 mutations were the most frequently co-occurring baseline gene alterations. With treatment arms combined, median PFS was 18.0 months versus 12.5 months for patients with uncommon (non-E746_A750del, n = 44) versus common (E746_A750del, n = 90) ex19del variants (hazard ratio [HR] = 1.657 [95% confidence interval or CI:1.044-2.630]). Median PFS was longer with RAM plus ERL versus PBO plus ERL for patients with the common (15.2 versus 9.9 mo; HR = 0.564 [95% CI: 0.344-0.926]) and E746del (15.4 versus 9.9 mo; HR = 0.587 [95% CI: 0.363-0.951]) variants. Treatment-emergent post-progression EGFR T790M rates were higher in the common versus uncommon and E746del versus L747 deletion subgroups.

Conclusions

RAM plus ERL provides benefit and improves treatment outcomes for patients with metastatic NSCLC with EGFR ex19del variants.

Value of multi-center 18 F-FDG PET/CT radiomics in predicting EGFR mutation status in lung adenocarcinoma

BACKGROUND

Accurate, noninvasive, and reliable assessment of epidermal growth factor receptor (EGFR) mutation status and EGFR molecular subtypes is essential for treatment plan selection and individualized therapy in lung adenocarcinoma (LUAD). Radiomics models based on 18 F-FDG PET/CT have great potential in identifying EGFR mutation status and EGFR subtypes in patients with LUAD. The validation of multi-center data, model visualization, and interpretation are significantly important for the management, application and trust of machine learning predictive models. However, few EGFR-related research involved model visualization and interpretation, and multi-center trial.

PURPOSE

To develop explainable optimal predictive models based on handcrafted radiomics features (HRFs) extracted from multi-center 18 F-FDG PET/CT to predict EGFR mutation status and molecular subtypes in LUAD.

METHODS

Baseline 18 F-FDG PET/CT images of 383 LUAD patients from three hospitals and one public data set were collected. Further, 1808 HRFs were extracted from the primary tumor regions using Pyradiomics. Predictive models were built based on cross-combination of seven feature selection methods and seven machine learning algorithms. Yellowbrick and explainable artificial intelligence technology were used for model visualization and interpretation. Receiver operating characteristic curve, classification report and confusion matrix were used for model performance evaluation. Clinical applicability of the optimal models was assessed by decision curve analysis.

RESULTS

STACK feature selection method combined with light gradient boosting machine (LGBM) reached optimal performance in identifying EGFR mutation status ([area under the curve] AUC = 0.81 in the internal test cohort; AUC = 0.62 in the external test cohort). Random forest feature selection method combined with LGBM reached optimal performance in predicting EGFR mutation molecular subtypes (AUC = 0.89 in the internal test cohort; AUC = 0.61 in the external test cohort).

CONCLUSIONS

Explainable machine learning models combined with radiomics features extracted from multi-center/scanner 18 F-FDG PET/CT have certain potential to identify EGFR mutation status and subtypes in LUAD, which might be helpful to the treatment of LUAD.

Brain metastasis, EGFR mutation subtype and generation of EGFR-TKI jointly influence the treatment outcome of patient with EGFR-mutant NSCLC

Non-small cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) mutation is brain metastasis (BM)-prone. We determined the impact of this hallmark, along with EGFR subtype and generation of tyrosine kinase inhibitor (TKI) treatment, on patients' outcome. 553 metastatic EGFR-mutant NSCLC patients received front-line EGFR-TKI treatment. Progression-free survival (PFS), overall survival (OS) and secondary T790M rate were analysed. BM was observed in 211 (38.2%) patients. BM (HR 1.20 [95% CI 0.99-1.48]; p = 0.053), ECOG PS 0-1 (HR 0.71 [95% CI 0.54-0.93]; p = 0.014) and afatinib treatment (HR 0.81 [95% CI 0.66-0.99]; p = 0.045) were associated with PFS. Afatinib-treated patients without BM demonstrated a significantly longer PFS (16.3 months) compared to afatinib-treated patients with BM (13.7 months) and to gefitinib/erlotinib-treated patients with (11.1 months) or without BM (14.2 months; p < 0.001). CNS-only progression trended higher in afatinib-treated patients. ECOG PS 0-1 (HR 0.41 [95% CI 0.31-0.56]; p < 0.001) and EGFR L858R mutation (HR 1.46 [95% CI 1.13-1.88]; p = 0.003), but not BM, were the predictors for OS. BM (OR 2.02 [95% CI 1.02-4.08]; p = 0.040), afatinib treatment (OR 0.26 [95% CI 0.12-0.50]; p < 0.001) and EGFR L858R mutation (OR 0.55 [95% CI 0.28-1.05]; p = 0.070) were associated with secondary T790M rate. In BM patients, gefitinib/erlotinib-treated ones with 19 deletion mutation and afatinib-treated ones with L858R mutation had the highest and the lowest T790M rate (94.4% vs. 27.3%, p < 0.001), respectively. BM and generation of EGFR-TKI jointly impact PFS and secondary T790M rate in patients with EGFR-mutant NSCLC, whereas OS was mainly associated with EGFR subtype.

Clinical outcomes of advanced NSCLC patients with different EGFR exon 19 deletion subtypes treated with first-line tyrosine kinase inhibitors: A single-center ambispective cohort study

BACKGROUND

Clinical significance of various subtypes of epidermal growth factor receptor (EGFR) exon 19 deletion (ex19del) mutation in non-small cell lung cancer (NSCLC) remains unclear.

METHODS

We analyzed EGFR ex19del subtypes in NSCLC patients receiving first-line tyrosine kinase inhibitor (TKI) therapy at our center (January 2018-June 2022) and correlated them with median progression-free survival (mPFS) and median overall survival (mOS).

RESULTS

We identified 17 different EGFR ex19del variants in 101 patients. Between the classic (E746_A750del, 64.4%) and nonclassic groups (the rest variants), no significant difference was observed in mPFS (13.5 vs. 19.3 months, p = 0.18) or mOS (44.1 vs. 77.0 months, p = 0.06). mPFS showed no significant difference between ex19del subgroups classified based on the presence of insertion (ex19delins), starting position or length of deletion. However, patients with ex19delins starting at E746 showed longer mPFS than the others (29.7 vs. 12.5 months, p = 0.04), and patients with ex19del of 15 nucleotides had shorter mOS than the others (44.1 vs. 77.0 months, p = 0.03). In multivariate analysis, ex19delins independently predicted a better PFS (HR = 0.311, p = 0.03); however, 15 nucleotide deletion was no longer associated with OS (HR = 0.181, p = 0.11). Secondary T790M mutation incidence was significantly higher in the ex19del subgroup starting at E746 than the others (64.7% vs. 30.8%, p = 0.04).

CONCLUSIONS

Our study revealed potential differences in TKI efficacy, resistance mechanism, and prognosis of various EGFR ex19del subtypes in NSCLC, underscoring the need for precise selection of first-line therapy.

Efficacy of Osimertinib in Patients with Lung Cancer Positive for Uncommon EGFR Exon 19 Deletion Mutations

PURPOSE

The uncommon EGFR exon 19 deletion (ex19del), L747_A750>P, demonstrates reduced sensitivity to osimertinib compared with the common ex19del, E746_A750del in preclinical models. The clinical efficacy of osimertinib in patients with non-small cell lung cancer harboring L747_A750>P and other uncommon ex19dels is not known.

EXPERIMENTAL DESIGN

The AACR GENIE database was interrogated to characterize the frequency of individual ex19dels relative to other variants, and a multicenter retrospective cohort was used to compare clinical outcomes for patients with tumors harboring E746_A750del, L747_A750>P, and other uncommon ex19dels who received osimertinib in the first line (1L) or in second or later lines of therapy and were T790M+ (≥2L).

RESULTS

ex19dels comprised 45% of EGFR mutations, with 72 distinct variants ranging in frequency from 28.1% (E746_A750del) to 0.03%, with L747_A750>P representing 1.8% of the EGFR mutant cohort. In our multi-institutional cohort (N = 200), E746_A750del was associated with significantly prolonged progression-free survival (PFS) with 1L osimertinib versus L747_A750>P [median 21.3 months (95% confidence interval, 17.0-31.7) vs. 11.7 months (10.8-29.4); adjusted HR 0.52 (0.28-0.98); P = 0.043]. Osimertinib efficacy in patients with other uncommon ex19dels varied on the basis of the specific mutation present.

CONCLUSIONS

The ex19del L747_A750>P is associated with inferior PFS compared with the common E746_A750del mutation in patients treated with 1L osimertinib. Understanding differences in osimertinib efficacy among EGFR ex19del subtypes could alter management of these patients in the future.

Different treatment efficacies and T790M acquisition of EGFR-TKIs on NSCLC patients with variable Del-19 subtypes of EGFR

EGFR exon 19 deletion (Del-19) comprises multiple advanced NSCLC subtypes. EGFR-tyrosine kinase inhibitor (TKI) efficacy and T790M acquisition in various Del-19 subtypes is unknown. We prospectively collected tissue samples from patients harboring NSCLC with Del-19 between 2006 and 2020. We evaluated EGFR-TKI treatment effectiveness among the different Del-19 subtypes. We collected 1391 NSCLC samples from 892 patients with Del-19, and the most common subtype was del E746-A750 (67.5%). 741 patients had taken first- or second-generation EGFR-TKIs. There were no significant differences in response rates between patients with different Del-19 subtypes (P = .630). Patients with indel E746 had the longest median PFS (14.6 months), but those with non-LRE deletions had the shortest PFS (8.9 months; P = .002). For OS analysis, patients with indel E746 also had the longest OS (34.1 months), but those with non-LRE deletions had the shortest OS (21.1 months; P = .046). Patients with different Del-19 subtypes showed no significant differences in the T790M acquisition rates (P = .443). Among the 151 patients with acquired T790M who received third-generation EGFR-TKIs, the Del-19 subtype was not associated with different RR and PFS. In vitro cellular viability and activation of the EGFR pathway analysis were consistent with the clinical findings. In conclusion, compared with del E746-A750, indel E746 was associated with longer PFS and OS, but the non-LRE subtype was correlated with shorter survival prognosis. There were no significant differences in the acquired T790M rate and treatment effectiveness of subsequent third-generation EGFR-TKIs between various Del-19 subgroups.

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

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

The efficacy of neoadjuvant EGFR-TKI therapy combined with radical surgery for stage IIIB lung adenocarcinoma harboring EGFR mutations: A retrospective analysis based on single center

Background

Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) could provide survival benefits for locally advanced EGFR-mutant (EGFRm) non-small cell lung cancer (NSCLC). However, the role of radical surgery for EGFR-TKI treated stage IIIB EGFRm NSCLC remains controversial. This study attempted to assess the feasibility of neoadjuvant EGFR-TKI followed by radical surgery for stage IIIB EGFRm NSCLC.

Patients and Methods

Between 2013 and 2020, EGFRm lung adenocarcinoma (LUAD) patients in clinical stage IIIB undergoing neoadjuvant EGFR-TKI followed by surgery (T-S-Arm) and EGFR-TKI alone (T-Arm) were reviewed retrospectively in Shanghai Pulmonary Hospital (SPH). The chi-square test, Student's t-test or Fisher's exact test was performed for analysis of baseline characteristics. Progression-free survival (PFS) was estimated using the Kaplan-Meier analysis. Multivariate Cox regression analysis was used to identify independent predictors of progression.

Results

A total of 43 patients were divided into T-S-Arm (n = 21) and T-Arm (n = 22). Patients were well-balanced between the two arms. The majority of patients were female (n = 25, 58.1%), non-smokers (n = 35, 81.4%), first-generation of EGFR-TKI treatment (n = 39, 90.7%), and exon 19 deletions (19-DEL) (n = 26, 60.5%). The median diagnostic age was 63.0 years [interquartile range (IQR), 54.0-67.5 years). At the cut-off date with June 30th 2022, median follow-up time was 28 months (IQR, 20-39 months). Neoadjuvant EGFR-TKI treatment followed by radical surgery could significantly improve the median PFS compared with patients underwent EGFR-TKI alone (23.0 months vs 14.5 months, P = 0.002). Multivariate Cox regression analysis demonstrated that radical surgery (T-S-Arm vs. T-Arm, HR: 0.406; 95% CI: 0.207-0.793, P = 0.027) was the only independent predictor for disease progression. The stratified analysis demonstrated patients with N2 disease could benefit from radical surgery (HR, 0.258; 95% CI, 0.107-0.618), especially for patients harboring L858R mutation (HR, 0.188; 95% CI, 0.059-0.604).

Conclusions

For stage IIIB EGFRm NSCLC patients, the prognosis might be improved by neoadjuvant EGFR-TKI followed by radical surgery versus EGFR-TKI alone, especially for those with N2 disease and harboring L858R mutation.

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

BACKGROUND

Information on genetic alterations, notably EGFR mutations, is important for guiding non-small-cell lung cancer (NSCLC) treatment. Circulating tumor DNA (ctDNA) analysis represents a less invasive alternative to tissue biopsy for analyzing mutation status, but its clinical value may vary across disease stages.

OBJECTIVE

To explore clinical correlates of ctDNA and tissue/plasma-based EGFR mutation (EGFRm) status across all NSCLC stages.

METHODS

Ninety patients were analyzed, representing three cohorts: newly-diagnosed early-stage, advanced-stage, and recurrent NSCLC. Relationships among clinical/surgical parameters, ctDNA, EGFRm status, and survival outcomes were analyzed.

RESULTS

Plasma/tissue EGFRm concordance was lower in early-stage (58.6%) than in advanced-stage patients (87.5%). In early-stage patients, ctDNA levels were variable and not significantly associated with clinical/surgical parameters. In advanced-stage patients, time to EGFR-TKI treatment failure (TTF), but not overall survival (OS), was significantly longer in EGFRm-positive vs. EGFRm-negative patients. In patients with recurrent disease, 40% of plasma samples were EGFRT790M-positive at recurrence. In T790M-positive patients, we noted slight trends toward longer OS with vs. without osimertinib treatment and longer OS and TTF with second-line vs. later-line osimertinib.

CONCLUSIONS

Our results affirm the use of ctDNA testing in advanced-stage and recurrent NSCLC. Further studies on osimertinib as early-line therapy, clinical correlates and the utility of plasma-based testing in early-stage NSCLC are warranted.

Correlation of EGFR mutation subtypes and survival in surgically treated brain metastasis from non-small-cell lung cancer

OBJECTIVE

Epidermal growth factor receptor (EGFR) mutation is a positive prognostic factor for survival in patients with non-small-cell lung cancer (NSCLC). In such patients, brain metastasis signifies negative outcomes. Patients with NSCLC brain metastasis that may benefit from neurosurgery is under investigation. We aim to investigate the impact of different mutation loci in surgically treated NSCLC brain metastasis patients.

METHODS

This retrospective cohort study included patients with NSCLC brain metastasis who underwent brain lesionectomy, followed by radiotherapy and chemotherapy or targeted therapy. Demographics and tumor characteristics were compared between the EGFR mutant type and wild type groups. Postoperative survival and risk factors were analyzed using log rank and Cox regression methods.

RESULTS

Overall, 101 patients were included, with 57 belonging to the EGFR mutant type group and 44 to the EGFR wild type group. The median postoperative survival was 17 months for the entire cohort, with the duration being 19 and 14 months for EGFR mutant type and wild type patients (p = 0.013), respectively. Multivariate analysis revealed that exon 19 del (p = 0.02) and a high Karnofsky Performance Scale score (p < 0.01) were independent positive prognostic factors to predict survival. The timing of development of the brain metastasis or the location of the intracranial metastasis was not associated with EGFR mutations.

CONCLUSION

EGFR mutations are associated with better survival outcomes in patients with NSCLC brain metastasis suitable for surgical treatment. This advantage was attributed to patients having a specific mutation of exon 19 deletion.

Biochemical and structural basis for differential inhibitor sensitivity of EGFR with distinct exon 19 mutations

Tyrosine kinase inhibitors (TKIs) are used to treat non-small cell lung cancers (NSCLC) driven by epidermal growth factor receptor (EGFR) mutations in the tyrosine kinase domain (TKD). TKI responses vary across tumors driven by the heterogeneous group of exon 19 deletions and mutations, but the molecular basis for these differences is not understood. Using purified TKDs, we compared kinetic properties of several exon 19 variants. Although unaltered for the second generation TKI afatinib, sensitivity varied significantly for both the first and third generation TKIs erlotinib and osimertinib. The most sensitive variants showed reduced ATP-binding affinity, whereas those associated with primary resistance retained wild type ATP-binding characteristics (and low K_{M, ATP}). Through crystallographic and hydrogen-deuterium exchange mass spectrometry (HDX-MS) studies, we identify possible origins for the altered ATP-binding affinity underlying TKI sensitivity and resistance, and propose a basis for classifying uncommon exon 19 variants that may have predictive clinical value.

Advanced Lung Cancer Patients' Use of EGFR Tyrosine Kinase Inhibitors and Overall Survival: Real-World Evidence from Quebec, Canada

EGFR tyrosine kinase inhibitors (EGFR-TKIs) are breakthrough palliative treatments for advanced lung cancer patients with tumors harboring mutations in the EGFR gene. Using healthcare administrative data, three cohorts were created to describe the use of three EGFR-TKIs that are publicly funded in Quebec for specific indications (i.e., 1st-line gefitinib, 1st-line afatinib, and post-EGFR-TKI osimertinib). The main objective was to compare overall survival (OS) among patients receiving these treatments to those in previous experimental and real-world studies. The patients who received EGFR-TKIs for indications of interest between 1 April 2001, and 31 March 2019 (or 31 March 2020, for post-EGFR-TKI osimertinib) were included to estimate the Kaplan-Meier-based median OS for each cohort. An extensive literature search was conducted to include comparable studies. For the gefitinib 1st-line (n = 457), the afatinib 1st-line (n = 80), and the post-EGFR-TKI osimertinib (n = 119) cohorts, we found a median OS (in months) of 18.9 (95%CI: 16.3-21.9), 26.6 (95%CI: 13.7-NE) and 19.9 (95%CI: 17.4-NE), respectively. Out of the 20 studies that we retained from the literature review and where comparisons were feasible, 17 (85%) had similar OS results, which further confirms the value of these breakthrough therapies in real-world clinical practice.

Non-small cell lung cancer in China

In China, lung cancer is a primary cancer type with high incidence and mortality. Risk factors for lung cancer include tobacco use, family history, radiation exposure, and the presence of chronic lung diseases. Most early-stage non-small cell lung cancer (NSCLC) patients miss the optimal timing for treatment due to the lack of clinical presentations. Population-based nationwide screening programs are of significant help in increasing the early detection and survival rates of NSCLC in China. The understanding of molecular carcinogenesis and the identification of oncogenic drivers dramatically facilitate the development of targeted therapy for NSCLC, thus prolonging survival in patients with positive drivers. In the exploration of immune escape mechanisms, programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) inhibitor monotherapy and PD-1/PD-L1 inhibitor plus chemotherapy have become a standard of care for advanced NSCLC in China. In the Chinese Society of Clinical Oncology's guidelines for NSCLC, maintenance immunotherapy is recommended for locally advanced NSCLC after chemoradiotherapy. Adjuvant immunotherapy and neoadjuvant chemoimmunotherapy will be approved for resectable NSCLC. In this review, we summarized recent advances in NSCLC in China in terms of epidemiology, biology, molecular pathology, pathogenesis, screening, diagnosis, targeted therapy, and immunotherapy.

Combination of 18F-Fluorodeoxyglucose PET/CT Radiomics and Clinical Features for Predicting Epidermal Growth Factor Receptor Mutations in Lung Adenocarcinoma

OBJECTIVE

To identify epidermal growth factor receptor (EGFR) mutations in lung adenocarcinoma based on ¹⁸F-fluorodeoxyglucose (FDG) PET/CT radiomics and clinical features and to distinguish EGFR exon 19 deletion (19 del) and exon 21 L858R missense (21 L858R) mutations using FDG PET/CT radiomics.

MATERIALS AND METHODS

We retrospectively analyzed 179 patients with lung adenocarcinoma. They were randomly assigned to training (n = 125) and testing (n = 54) cohorts in a 7:3 ratio. A total of 2632 radiomics features were extracted from the tumor region of interest from the PET (1316) and CT (1316) images. Six PET/CT radiomics features that remained after the feature selection step were used to calculate the radiomics model score (rad-score). Subsequently, a combined clinical and radiomics model was constructed based on sex, smoking history, tumor diameter, and rad-score. The performance of the combined model in identifying EGFR mutations was assessed using a receiver operating characteristic (ROC) curve. Furthermore, in a subsample of 99 patients, a PET/CT radiomics model for distinguishing 19 del and 21 L858R EGFR mutational subtypes was established, and its performance was evaluated.

RESULTS

The area under the ROC curve (AUROC) and accuracy of the combined clinical and PET/CT radiomics models were 0.882 and 81.6%, respectively, in the training cohort and 0.837 and 74.1%, respectively, in the testing cohort. The AUROC and accuracy of the radiomics model for distinguishing between 19 del and 21 L858R EGFR mutational subtypes were 0.708 and 66.7%, respectively, in the training cohort and 0.652 and 56.7%, respectively, in the testing cohort.

CONCLUSION

The combined clinical and PET/CT radiomics model could identify the EGFR mutational status in lung adenocarcinoma with moderate accuracy. However, distinguishing between EGFR 19 del and 21 L858R mutational subtypes was more challenging using PET/CT radiomics.

Artificial intelligence-based prediction of clinical outcome in immunotherapy and targeted therapy of lung cancer

Lung cancer accounts for the main proportion of malignancy-related deaths and most patients are diagnosed at an advanced stage. Immunotherapy and targeted therapy have great advances in application in clinics to treat lung cancer patients, yet the efficacy is unstable. The response rate of these therapies varies among patients. Some biomarkers have been proposed to predict the outcomes of immunotherapy and targeted therapy, including programmed cell death-ligand 1 (PD-L1) expression and oncogene mutations. Nevertheless, the detection tests are invasive, time-consuming, and have high demands on tumor tissue. The predictive performance of conventional biomarkers is also unsatisfactory. Therefore, novel biomarkers are needed to effectively predict the outcomes of immunotherapy and targeted therapy. The application of artificial intelligence (AI) can be a possible solution, as it has several advantages. AI can help identify features that are unable to be used by humans and perform repetitive tasks. By combining AI methods with radiomics, pathology, genomics, transcriptomics, proteomics, and clinical data, the integrated model has shown predictive value in immunotherapy and targeted therapy, which significantly improves the precision treatment of lung cancer patients. Herein, we reviewed the application of AI in predicting the outcomes of immunotherapy and targeted therapy in lung cancer patients, and discussed the challenges and future directions in this field.

Central nervous system efficacy of furmonertinib (AST2818) versus gefitinib as first-line treatment for EGFR mutated non-small cell lung cancer: results from the FURLONG study

INTRODUCTION

Furmonertinib (AST2818) is a pan epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) with central nervous system (CNS) anti-tumor activity. We report the CNS efficacy of furmonertinib compared with gefitinib in untreated EGFR sensitizing mutation positive non-small cell lung cancer (NSCLC) from the FURLONG study.

METHODS

FURLONG was a randomized, double-blind, phase 3 study conducted in 55 hospitals in People's Republic of China. Patients 1:1 randomly received furmonertinib 80mg Qd or gefitinib 250mg Qd treatment. At screening, all the patients underwent brain scan. Patients with asymptomatic steady CNS metastases at baseline constituted this pre-planned CNS subgroup analysis.

RESULTS

A total of 358 patients were enrolled in the FURLONG study. In the 133 (37%) patients who had measurable or non-measurable CNS lesions, CNS progression-free survival (PFS) was 20.8 months (95% confidence interval [95%CI] 15.2, 25.3) in the furmonertinib group and 9.8 months (95%CI 7.2, 18.0) in the gefitinib group (hazard ratio 0.40 [95%CI 0.23, 0.71]; p=0.0011). In the 60 (17%) patients who had measurable CNS lesions, CNS objective response rate (ORR) was 91% (95%CI 72, 99) with furmonertinib and 65% (95%CI 48, 80) with gefitinib (odds ratio 6.82 [95%CI 1.23, 37.67]; p=0.0277). The least square mean difference of CNS depth of response (DepOR) between furmonertinib and gefitinib was 23% (95%CI 10, 37; p=0.0011).

CONCLUSIONS

Furmonertinib first-line treatment showed superior efficacy in CNS PFS, CNS ORR and CNS DepOR compared with gefitinib in EGFR mutated NSCLC patients with CNS metastases.

PET/CT Radiomic Features: A Potential Biomarker for EGFR Mutation Status and Survival Outcome Prediction in NSCLC Patients Treated With TKIs

Backgrounds

Epidermal growth factor receptor (EGFR) mutation profiles play a vital role in treatment strategy decisions for non–small cell lung cancer (NSCLC). The purpose of this study was to evaluate the predictive efficacy of baseline ¹⁸F-FDG PET/CT-based radiomics analysis for EGFR mutation status, mutation site, and the survival benefit of targeted therapy.

Methods

A sum of 313 NSCLC patients with pre-treatment ¹⁸F-FDG PET/CT scans and genetic mutations detection were retrospectively studied. Clinical and PET metabolic parameters were incorporated into independent predictors of determining mutation status and mutation site. The dataset was randomly allocated into the training and the validation sets in a 7:3 ratio. Three-dimensional (3D) radiomics features were extracted from each PET- and CT-volume of interests (VOI) singularly, and then a radiomics signature (RS) associated with EGFR mutation profiles is built by feature selection. Three different prediction models based on support vector machine (SVM), decision tree (DT), and random forest (RF) classifiers were established. Furthermore, nomograms for estimation of overall survival (OS) and progression-free survival (PFS) were established by integrating PET/CT radiomics score (Rad-score), metabolic parameters, and clinical factors. Predictive performance was assessed by the receiver operating characteristic (ROC) analysis and the calibration curve analysis. The decision curve analysis (DCA) was applied to estimate and compare the clinical usefulness of nomograms.

Results

Three hundred thirteen NSCLC patients were classified into a training set (n=218) and a validation set (n=95). Multivariate analysis demonstrated that SUVmax and sex were independent indicators of EGFR mutation status and mutation site. Eight CT-derived RS, six PET-derived RS, and two clinical factors were retained to develop integrated models, which exhibited excellent ability to distinguish between EGFR wild type (EGFR-WT), EGFR 19 mutation type (EGFR-19-MT), and EGFR 21 mutation type (EGFR-21-MT). The SVM model outperformed the RF model and the DT model, yielding training area under the curves (AUC) of EGFR-WT, EGFR-19-WT, and EGFR-21-WT, with 0.881, 0.851, and 0.849, respectively, and validation AUCs of 0.926, 0.805 and 0.859, respectively. For prediction of OS, the integrated nomogram is superior to the clinical nomogram and the radiomics nomogram, with C-indexes of 0.80 in the training set and 0.83 in the validation set, respectively.

Conclusions

The PET/CT-based radiomics analysis might provide a novel approach to predict EGFR mutation status and mutation site in NSCLC patients and could serve as useful predictors for the patients’ survival outcome of targeted therapy in clinical practice.

Evaluating the Efficacy of EGFR-TKIs Combined With Radiotherapy in Advanced Lung Adenocarcinoma Patients With EGFR Mutation: A Retrospective Study

Objective: Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) have been recommended as the first-line treatment for advanced lung adenocarcinoma with epidermal growth factor receptor (EGFR) mutation. This study retrospectively evaluated patients' survival and related prognostic factors from single-center, real-world data. Methods: From January 2015 to December 2020, patients detected with EGFR mutation showing unresectable clinical stages III to IV advanced lung adenocarcinoma and receiving EGFR-TKIs and radiotherapy (RT) were recruited for the study. The overall survival (OS) and progression-free survival (PFS) were statistically analyzed with SPSS 22.0 software. Results: This study included 238 patients who completed their follow-up by December 30, 2020. The 1-, 2-, 3-year and median OS were 84.4%, 59.7%, 38.7%, and 30.3 months for OS, 57.0%, 28.8%, 15.7%, and 14.1 months for progression-free survival (PFS1), and 78.9%, 71.7%, 33.3%, and 25.0 months for PFS2, respectively. Multivariate analysis showed that, the independent factors for OS are age, clinical stage, the sequence of TKI and CT, and the total treatment response, and total response; the independent factors for progression-free survival 1 are clinical stage and total treatment response; the independent factors for PFS2 are clinical stage, type of TKI, sequence of TKI and CT, and total treatment response. The univariate analysis also showed a significant association between RT duration (P = 0.041) and dose (P = 0.026) with PFS1. Conclusion: EGFR-TKIs combined with RT was tolerable and efficient for patients with advanced lung adenocarcinoma. OS and PFS prove CT sequential with TKIs. Better treatment response with CR + PR was associated with a longer duration of OS, PFS1, and PFS2. However, further study is required in a larger sample size to confirm the results.

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.

Impact of angiogenesis inhibitor eligibility on the prognosis of patients with non-small cell lung cancer harboring EGFR mutation

Background

Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR‐TKIs) are currently the primary treatment option for patients with EGFR‐mutant non‐small cell lung cancer (NSCLC). However, the effect of EGFR‐TKIs are eventually weakened due to resistance, and there is also a differential efficacy based on EGFR mutation subtypes. The combination of angiogenesis inhibitor (AI) with EGFR‐TKI has shown better efficacy than EGFR‐TKI monotherapy, regardless of the mutation subtypes. Nevertheless, the effect of AI eligibility on overall survival (OS) and progression‐free survival (PFS) remains to be elucidated. Thus, we assessed this impact on patients with NSCLC harboring EGFR mutation.

Methods

In this study, the data for 450 patients with EGFR‐mutant NSCLC, who were treated with EGFR‐TKI monotherapy, were retrospectively analyzed for AI eligibility. The patients were categorized into AI‐eligible (AI fit) and ineligible groups (AI unfit).

Results

The median PFS of the AI fit group was 12.9 months, compared to 9.6 months in the unfit group (p = 0.007), and OS was also significantly longer in the AI fit group (median OS = 33.0 months) compared to that in the unfit group (18.5 months, p < 0.001). Multivariate analysis indicated that AI ineligibility was associated with shorter PFS and poor prognosis. Also, in the AI fit group, there was no significant difference in the PFS between EGFR L858R mutation and EGFR exon 19 deletion (median PFS = 11.5 months vs. 13.8 months; p = 0.17).

Conclusions

From our study, AI eligibility resulted in longer OS and PFS, and also had different effects on patients with EGFR L858R and exon 19 deletion. Since this selection bias may have affected previous clinical trial data on the efficacy of AI combination therapy, their results should be carefully considered henceforth.

Afatinib treatment in a large real-world cohort of nonsmall cell lung cancer patients with common and uncommon epidermal growth factor receptor mutation

The epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) afatinib improves survival in nonsmall cell lung cancer (NSCLC) patients with EGFR mutation. We analysed the outcome between EGFR mutation subtypes in a large afatinib-treated cohort in which 516 EGFR-mutated NSCLC patients receiving afatinib as front-line treatment. EGFR uncommon mutations include exon 20 insertion, de novo T790M of high or low allele frequency (dT790M_HAF /dT790M_LAF ), non-T790M compound mutation and others, where EGFR exon 20 insertion and dT790M_HAF were defined as type-I and the rest as type-II uncommon mutation. Four hundred and sixty-one (89.3%) and 55 (10.7%) patients were common and uncommon mutation, respectively. Exon 20 insertion and dT790M_HAF patients demonstrated a significantly shortened progression-free survival (PFS) (2.6 and 4.1 months) compared to EGFR common mutation, dT790M_LAF and other uncommon mutation patients (15.1, 27.0 and 18.4 months; P = 3 × 10^-8 ). Type-I uncommon mutation was an independent predictor of PFS (HR 4.46 [95% CI, 2.60-7.64]; P < .001) and OS (HR 2.56 [95% CI, 1.37-4.75]; P = .003). EGFR L858R patients demonstrated a significantly higher CNS progression (cause-specific HR, 3.16; 95% CI 1.24-8.08; P = .016), and type-I uncommon mutation patients exhibited a significantly higher systemic progression (cause-specific HR, 4.95; 95% CI 2.30-10.60; P = 4.3 × 10^-5 ). Tendencies of higher CNS and lower systemic progression were observed in type-II uncommon mutation patients. A PFS ≥ 12 months (OR 2.38 [95% CI, 1.18-4.89]; P = .016) and uncommon EGFR mutation (OR 0.08 [95% CI, 0.01-0.48]; P = .021) were independent predictors of secondary T790M. Afatinib-treated NSCLC patients presented an EGFR genotype-specific pattern of disease progression and outcome.

Survival of Patients with Epidermal Growth Factor Receptor-Mutated Metastatic Non-Small Cell Lung Cancer Treated beyond the Second Line in the Tyrosine Kinase Inhibitor Era

Simple Summary

The identification of activating mutations in specific genes in non-small cell lung cancer (NSCLC) has led to the development of targeted therapies, which are currently part of the algorithm for their management. The recommendations agree on first and second-line metastatic treatments in Epidermal Growth Factor Receptor (EGFR) mutations patients. The aim of our retrospective, longitudinal and analytic study was to analyze the survival of EGFR-mutated patients treated beyond the second line of treatment. We confirmed in a population of 31 patients which received at least three lines of treatment that the Progression Free Survival (PFS) was best if we used chemotherapy in second-line and tyrosine kinase inhibitors (TKI) in third-line. We found no difference in Overall Survival (OS) according to the pattern of treatments. In practice, in the TKI era, chemotherapy can still be used in second-line or third-line of treatment.

Abstract

Background: The identification of activating mutations in specific genes led to the development of targeted therapies for NSCLC. TKI directed against EGFR-mutations were the first to prove their major efficacy. Medical associations recommend their use as first and second-line metastatic treatments in EGFR-mutated patients. Our objective was to analyze the survival of EGFR-mutated patients treated beyond the second line of treatment. Methods: We performed a longitudinal, retrospective and analytical study at APHP (Assistance Publique Hopitaux de Paris) Saint Louis, Paris, France, from 1 January 2010 to 31 December 2020 (11 years), on EGFR-mutated patients with metastatic NSCLC which received TKI or chemotherapy (CT) in third-line. Results: Out of about 107 EGFR-mutated patients, 31 patients who benefited from TKI or CT in the third line of treatment were retained for this study. The mean age was 60.03 ± 11.93 years and the sex ratio male/female was 0.24. Mutations of exon 19, 21 and 20 were found in 21 (67.7%), 7 (22.6%) and 7 (22.6%) patients, respectively. Third-line treatment was CT for 16 patients (51.6%) and TKI for the 15 remaining patients (48.4%). Osimertinib was the most used TKI in third-line (n = 10/15; 66.67%). The median duration of third-line treatment was 5.37 months (range 0.53–37.6) and the median follow-up duration was 40.83 months (range 11.33–88.57). There was a significant difference in PFS between patients treated with TKI and CT in third-line (p = 0.028). For patients treated with CT in second-line, there was a significant difference of PFS (p < 0.001) and OS (p = 0.014) in favor of the use of TKI in third-line. Conclusions: For patients receiving CT in second-line, TKI appears to be a better alternative in third-line compared to CT. Osimertinib may be used in third line treatment if not used before.

Heterochronous Metastases of Lung Adenocarcinoma to Pancreas and Liver: A Case Report from Pathological Perspectives

Immunohistochemistry (IHC) is a vital tool to distinguish tumor metastases from primary lesions in addition to morphologic analysis. In this study, a 64-year-old female with a past surgical history of lung adenocarcinoma 11 years ago was presented with recurrence of liver nodular lesions after multiple surgical procedures, including the Whipple procedure for pancreatic head adenocarcinoma and cytoreductive surgery for liver metastasis. Liver biopsy and review of the previous specimens, based on IHC analyses, suggested heterochronous metastases of lung adenocarcinoma to the digestive systems in a long-time span, instead of primary pancreatic adenocarcinoma. This case demonstrates the potential for misdiagnoses from morphologic analysis alone and suggests the necessity of IHC analyses to avoid misjudgment on tumor phenotypes, when a previous oncologic history is presented.

Machine learning based on clinico-biological features integrated 18F-FDG PET/CT radiomics for distinguishing squamous cell carcinoma from adenocarcinoma of lung

PURPOSE

To develop and validate a clinico-biological features and 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) radiomic-based nomogram via machine learning for the pretherapy prediction of discriminating between adenocarcinoma (ADC) and squamous cell carcinoma (SCC) in non-small cell lung cancer (NSCLC).

METHODS

A total of 315 NSCLC patients confirmed by postoperative pathology between January 2017 and June 2019 were retrospectively analyzed and randomly divided into the training (n = 220) and validation (n = 95) sets. Preoperative clinical factors, serum tumor markers, and PET, and CT radiomic features were analyzed. Prediction models were developed using the least absolute shrinkage and selection operator (LASSO) regression analysis. The performance of the models was evaluated and compared by the area under receiver-operator characteristic (ROC) curve (AUC) and DeLong test. The clinical utility of the models was determined via decision curve analysis (DCA). Then, a nomogram was developed based on the model with the best predictive efficiency and clinical utility and was validated using the calibration plots.

RESULTS

In total, 122 SCC and 193 ADC patients were enrolled in this study. Four independent prediction models were separately developed to differentiate SCC from ADC using clinical factors-tumor markers, PET radiomics, CT radiomics, and their combination. The DeLong test and DCA showed that the Combined Model, consisting of 2 clinical factors, 2 tumor markers, 7 PET radiomics, and 3 CT radiomic parameters, held the highest predictive efficiency and clinical utility in predicting the NSCLC subtypes compared with the use of these parameters alone in both the training and validation sets (AUCs (95% CIs) = 0.932 (0.900-0.964), 0.901 (0.840-0.957), respectively) (p < 0.05). A quantitative nomogram was subsequently constructed using the independently risk factors from the Combined Model. The calibration curves indicated a good consistency between the actual observations and nomogram predictions.

CONCLUSION

This study presents an integrated clinico-biologico-radiological nomogram that can be accurately and noninvasively used for the individualized differentiation SCC from ADC in NSCLC, thereby assisting in clinical decision making for precision treatment.

Longitudinal Tumor Size and Neutrophil-to-Lymphocyte Ratio Are Prognostic Biomarkers for Overall Survival in Patients With Advanced Non-Small Cell Lung Cancer Treated With Durvalumab

Therapy optimization remains an important challenge in the treatment of advanced non-small cell lung cancer (NSCLC). We investigated tumor size (sum of the longest diameters (SLD) of target lesions) and neutrophil-to-lymphocyte ratio (NLR) as longitudinal biomarkers for survival prediction. Data sets from 335 patients with NSCLC from study NCT02087423 and 202 patients with NSCLC from study NCT01693562 of durvalumab were used for model qualification and validation, respectively. Nonlinear Bayesian joint models were designed to assess the impact of longitudinal measurements of SLD and NLR on patient subgrouping (by Response Evaluation Criteria in Solid Tumors 1.1 criteria at 3 months after therapy start), long-term survival, and precision of survival predictions. Various validation scenarios were investigated. We determined a more distinct patient subgrouping and a substantial increase in the precision of survival estimates after the incorporation of longitudinal measurements. The highest performance was achieved using a multivariate SLD and NLR model, which enabled predictions of NSCLC clinical outcomes.

Predictive biomarkers in nonsmall cell carcinoma and their clinico-pathological association

Background:

Lung cancer is the leading cause of cancer-related mortality worldwide. Genome-directed therapy is less toxic, prolongs survival and provides a better quality of life. Predictive biomarker testing, therefore, has become a standard of care in advanced lung cancers. The objective of this study was to relate clinical and pathological features, including response to targeted therapy (TT) and progression-free survival (PFS) with positive driver mutation.

Materials and Methods:

Archival data of nonsmall cell carcinoma patients with Stage IV disease were retrieved. Those who tested positive for one of the four biomarkers (epidermal growth factor receptor [EGFR], anaplastic lymphoma kinase [ALK], MET, and ROS) were included. Patient demographics and clinical features were reviewed. Tumor histomorphology was correlated with oncological drivers. Treatment response, PFS, and overall survival were studied in three subcohorts of patients who received computed tomography (CT), CT followed by TT and those who received TT in the first line.

Results:

A total of 900 patients underwent biomarker evaluation of which 288 tested positive. Frequency of the four biomarkers observed was 26.6% (229/860), 6.6% (51/775), 6.6% (5/75), and 5.1% (3/59) for EGFR, ALK, MET, and ROS-1, respectively. The median PFS for EGFR-mutated cohort was 12 months, whereas it was 21 months for ALK protein overexpressing cases. Patients treated with first-line tyrosine kinase inhibitors performed better compared to those who were switched from chemotherapy to TT or those who received chemotherapy alone (P < 0.05).

Conclusion:

Biomarker testing has improved patient outcome. Genome-directed therapy accords best PFS with an advantage of nearly 10 months over cytotoxic therapy.

Favorable Immune Microenvironment in Patients with EGFR and MAPK Co-Mutations

Purpose

Although EGFR-mutated patients generally do not benefit from checkpoint inhibitors (ICIs), some patients in the KEYNOTE-001 study consistently benefited from this treatment. This study investigated immune microenvironment characteristics to identify the subgroup of patients that may benefit from ICIs.

Materials and Methods

Using data from The Cancer Genome Atlas Program (TCGA) and Cancer Proteome Atlas, TMB and protein level of PD-L1 were explored in the patients with EGFR mutations and wild-type patients. Different patterns of EGFR mutations (according to EGFR co-mutation with different downstream pathway genesets) were used to group EGFR mutation population. Estimated infiltration analyses were used to explore changes in the immune microenvironment.

Results

This study analyzed somatic mutation data from 1287 patients from five cohorts (TCGA, Broad, The Tumour Sequencing Project, Memorial Sloan Kettering Cancer Center, Catalogue Of Somatic Mutations In Cancer database). The probability of EGFR mutation was approximately 14.30% (184/1287) and the co-mutation rate was 11.41% (21/184) in patients with EGFR mutations. Glycosaminoglycan-related pathways were significantly upregulated in the EGFR mutant group. EGFR-mutated patients had lower TMB and PD-L1 protein levels than those in wild-type patients. Increase immature DCs infiltration and decreased NK CD56dim, T gamma delta, cytotoxic, and Th2 cell infiltration were the main immune changes in EGFR-mutated patients. Patients with EGFR-MAPK co-mutations had higher levels of TMB and PD-L1 protein expression. Meanwhile, the co-mutated patients had a similar immune microenvironment as that in wild-type patients.

Conclusion

In this study, we defined a subgroup of patients with EGFR-MAPK co-mutations. These co-mutated patients may benefit from ICI treatment.

The impact of EGFR exon 19 deletion subtypes on clinical outcomes in non-small cell lung cancer

Background

The study investigated the resistant pattern and clinical outcomes of epidermal growth factor receptor (EGFR) exon 19 deletion (19del) subtypes to tyrosine kinase inhibitors (TKIs) in non-small cell lung cancer (NSCLC).

Methods

Two hundred eight treatment naive NSCLC patients detected as EGFR 19del using amplification-refractory mutation system (ARMS) were included. DNA sequencing was used to detect the subtypes. Clinicopathological features as well as patients’ outcomes treated with first-line EGFR-TKIs were analyzed.

Results

Thirteen EGFR 19del subtypes were confirmed in 181 samples (87.0%). Among these, delE746_A750 was the most frequent subtype (130/181, 71.8%). delE746_A750 and deletions starting from E746 were frequently found in female (P=0.003 and P=0.013, respectively) and never smokers (P=0.002 and P=0.014, respectively) than non-delE746_A750 and deletions starting from L747 patients, respectively. T790M was more frequently occurred in delE746_A750 than non-delE746_A750 (P=0.001) and deletions starting from E746 than L747 patients (P=0.006) after first-line EGFR-TKIs resistance. Patients harboring deletions starting from L747 with insertions had significantly shorter progression-free survival (PFS) than deletions starting from L747 without insertion (8.3 vs. 15.0 m, P=0.017), or all other patients (8.3 vs. 12.6 m, P=0.027). Different 19del subtypes with T790M mutation had similar PFS when treated with osimertinib (P=0.102).

Conclusions

Patients with EGFR 19del subtypes had different clinicopathological features, and resistant pattern when treated with first-line TKIs. Patients harboring deletions starting from L747 with insertions had inferior outcomes than other subtypes.

EGFR mutation genotypes affect efficacy and resistance mechanisms of osimertinib in T790M-positive NSCLC patients

Background

Osimertinib is a potent third-generation EGFR tyrosine kinase inhibitor (TKI) with robust activity in advanced EGFR-mutant non-small cell lung cancer (NSCLC), including those with T790M resistance mutation. However, a broad interpatient variability was observed. This study aimed to evaluate whether EGFR-mutant genotypes affect the clinical outcomes and resistance mechanisms in T790M-positive NSCLC patients receiving osimertinib therapy.

Methods

All NSCLC patients treated with osimertinib in our institute were screened. We included those with known EGFR-mutant genotypes and T790M positivity. Clinical outcomes including objective response rate (ORR), clinical benefit rate (CBR), progression-free survival (PFS), and overall survival (OS), were evaluated and compared between different EGFR genotypes. Patients with next-generation sequencing testing or tumor rebiopsy after osimertinib treatment were analyzed for resistance mechanisms.

Results

ORR, CBR, PFS, and OS were all non-significantly different among patients harboring EGFR exon 19 deletion (19Del, n=136), L858R (n=93), and uncommon mutations (n=6). However, a subset of tumors with deletion starting at E746 (ΔE746, n=98), but not non-ΔE746 tumors (n=38), had better clinical outcomes than L858R tumors (n=93). Frequencies of T790M loss and C797S acquisition after osimertinib treatment were similar between 19Del (n=56) and L858R tumors (n=33). However, compared with L858R tumors (n=33), those with 19Del ΔE746 subtype (n=40) had a higher whereas non-ΔE746 subtype (n=16) had a similar frequency of acquired C797S mutation. Combined analysis of our cohort and public cohort confirmed these findings.

Conclusions

Our findings indicate that the EGFR 19Del subtypes affect the clinical outcomes and resistance mechanisms to osimertinib in T790M-positive patients. Identifying patients with relatively worse treatment outcomes may be informative for establishing new therapies for these patients.

Non-small cell lung cancer patients with ex19del or exon 21 L858R mutation: distinct mechanisms, different efficacies to treatments

With the development of antitumor therapies, different treatment methods including monotherapy and combined therapy have achieved clinical efficacy in advanced epidermal growth factor receptor (EGFR) mutant non-small cell lung cancer (NSCLC) patients. Exon 19 deletion (ex19del) and exon 21 L858R mutation are common sensitive subtypes of EGFR mutation. However, potential distinct mechanisms are found from several dimensions including molecular structures, biological behaviors, concomitant mutations, resistance mechanisms and tumor mutation burdens. More evidence indicates the prognostic difference of EGFR subgroups. This review focused on the progress of potential distinct mechanisms and outcomes in clinical trials of advanced NSCLC patients with ex19del or exon 21 L858R mutation.

Predicting EGFR mutation subtypes in lung adenocarcinoma using 18F-FDG PET/CT radiomic features

Background

Identification of epidermal growth factor receptor (EGFR) mutation types is crucial before tyrosine kinase inhibitors (TKIs) treatment. Radiomics is a new strategy to noninvasively predict the genetic status of cancer. In this study, we aimed to develop a predictive model based on ¹⁸F-fluorodeoxyglucose positron emission tomography-computed tomography (¹⁸F-FDG PET/CT) radiomic features to identify the specific EGFR mutation subtypes.

Methods

We retrospectively studied ¹⁸F-FDG PET/CT images of 148 patients with isolated lung lesions, which were scanned in two hospitals with different CT scan setting (slice thickness: 3 and 5 mm, respectively). The tumor regions were manually segmented on PET/CT images, and 1,570 radiomic features (1,470 from CT and 100 from PET) were extracted from the tumor regions. Seven hundred and ninety-four radiomic features insensitive to different CT settings were first selected using the Mann white U test, and collinear features were further removed from them by recursively calculating the variation inflation factor. Then, multiple supervised machine learning models were applied to identify prognostic radiomic features through: (I) a multi-variate random forest to select features of high importance in discriminating different EGFR mutation status; (II) a logistic regression model to select features of the highest predictive value of the EGFR subtypes. The EGFR mutation predicting model was constructed from prognostic radiomic features using the popular Xgboost machine-learning algorithm and validated using 3-fold cross-validation. The performance of predicting model was analyzed using the receiver operating characteristic curve (ROC) and measured with the area under the curve (AUC).

Results

Two sets of prognostic radiomic features were found for specific EGFR mutation subtypes: 5 radiomic features for EGFR exon 19 deletions, and 5 radiomic features for EGFR exon 21 L858R missense. The corresponding radiomic predictors achieved the prediction accuracies of 0.77 and 0.92 in terms of AUC, respectively. Combing these two predictors, the overall model for predicting EGFR mutation positivity was also constructed, and the AUC was 0.87.

Conclusions

In our study, we established predictive models based on radiomic analysis of 18F-FDG PET/CT images. And it achieved a satisfying prediction power in the identification of EGFR mutation status as well as the certain EGFR mutation subtypes in lung cancer.

Conformational Insight on WT- and Mutated-EGFR Receptor Activation and Inhibition by Epigallocatechin-3-Gallate: Over a Rational Basis for the Design of Selective Non-Small-Cell Lung Anticancer Agents

Non-small cell lung cancer (NSCLC) represents a difficult condition to treat, due to epidermal growth factor receptor (EGFR) kinase domain mutations, which lead to ligand-independent phosphorylation. Deletion of five amino acids (ELREA) in exon 19 and mutational change from leucine to arginine at position 858 (L858R) are responsible for tyrosine kinase domain aberrant activation. These two common types of EGFR-mutated forms are clinically associated with high response with Tyrosine Kinase Inhibitors (TKI); however, the secondary T790M mutation within the Tyrosine Kinase Domain (TKD) determines a resistance to these EGFR-TKIs. Using molecular dynamic simulation (MD), the present study investigated the architectural changes of wild-type and mutants EGFR's kinase domains in order to detect any conformational differences that could be associated with a constitutively activated state and thus to evaluate the differences between the wild-type and its mutated forms. In addition, in order to evaluate to which extent the EGFR mutations affect its inhibition, Epigallocatechin 3-Gallate (EGCG) and Erlotinib (Erl), known EGFR-TKI, were included in our study. Their binding modes with the EGFR-TK domain were elucidated and the binding differences between EGFR wild-type and the mutated forms were evidenced. The aminoacids mutations directly influence the binding affinity of these two inhibitors, resulting in a different efficacy of Erl and EGCG inhibition. In particular, for the T790M/L858R EGFR, the binding modes of studied inhibitors were compromised by aminoacidic substitution confirming the experimental findings. These results may be useful for novel drug design strategies targeting the dimerization domain of the EGFR mutated forms, thus preventing receptor activation.

The significance of epidermal growth factor receptor uncommon mutations in non-small cell lung cancer: A systematic review and critical appraisal

Uncommon epidermal growth factor receptor (EGFR) mutations collectively account for 10% of EGFR mutations, harboring heterogeneous molecular alterations within exons 18-21 with clinically variable responses to EGFR tyrosine kinase inhibitors (TKIs) in advanced Non-Small Cell Lung Cancer (NSCLC) patients. In addition, with the introduction of different NGS gene approach an improvement of EGFR mutations detection was reported. Today, no specific studies have prospectively evaluated uncommon sensitizing mutations in detail and no firm standard of care has been established in the first-line setting. The aim of this comprehensive review is to critically consider the clinical role of uncommon EGFR mutations highlighting the results of several in vitro and in vivo studies, which singly evaluated the sensitivity of uncommon mutations to currently European of Medicines Agency (EMA)-approved EGFR TKIs in cell lines, xenograft models and humans, in order to obtain a practical guide for refining the clinical decision-making process.

Clinical significance of EGFR mutation types in lung adenocarcinoma: A multi-centre Korean study

Adenocarcinoma is the most common type of non-small cell lung cancer. Some causative genomic alterations in epidermal growth factor receptor (EGFR), including deletions in exon 19 (E19 dels) and a point mutation in E21, are known to have favourable prognoses due to sensitivity to tyrosine kinase inhibitors; however, the prognoses of other uncommon mutations are unclear. This study analysed the clinical significance of EGFR mutation types in lung adenocarcinoma. We retrospectively reviewed 1,020 subjects (mean age: 66.8 years, female: 41.7%) who were diagnosed with advanced lung adenocarcinoma, had EGFR mutation data, and did not undergo surgery from five medical institutes between 2010 and 2016. Subjects were classified according to EGFR mutation status, particularly for exon-specific mutations. EGFR positivity was defined as the presence of mutation and EGFR negativity was defined as wild-type EGFR. EGFR positivity was 38.0%, with the incidence of mutations in E18, E19, E20, and E21 was 3.6%, 51.0%, 3.4%, and 42.0%, respectively. The EGFR positive group survived significantly longer than the negative group (p<0.001), and there was a significant difference in survival among the four EGFR mutation sites (p = 0.003); E19 dels were the only significant factor that lowered mortality (HR: 0.678, p = 0.002), while an E21 mutation was the prognostic factor associated with the most increased mortality (HR: 1.365, p = 0.015). Amongst EGFR positive subjects, the proportion of E19 dels in TKI-responders was significantly higher and that of E21 mutations significantly lower, compared with non-responders. In TKI treatment, mutations in E18 and E20 were not worse factors than the E21 L858R mutation. In conclusion, the presence of EGFR mutations in advanced lung adenocarcinoma can predict a good prognosis; E19 dels prospect to have a better prognosis than other mutations, while an E21 mutation is expected to increase mortality.

Differential significance of molecular subtypes which were classified into EGFR exon 19 deletion on the first line afatinib monotherapy

BACKGROUND

Epidermal growth factor receptor (EGFR)-sensitizing mutation, exon 19 deletion consists of several molecular variants. Influences of these variants on clinical response to EGFR tyrosine kinase inhibitors remain elusive.

METHODS

West Japan Oncology Group 8114LTR is a prospective, multi-institutional biomarker study. Treatment naïve, advanced non-small-cell lung cancer patients with EGFR-sensitizing mutation received afatinib monotherapy. We conducted a preplanned subset analysis of patients harboring exon 19 deletion. Tumor tissue exon 19 deletion molecular variants were identified by blocking-oligo-dependent polymerase chain reaction (PCR) and by Luminex Technology. Plasma cfDNA was also obtained before and after the treatment and EGFR mutations were detected with multiplexed, pico-droplet digital PCR assay.

RESULTS

Among 57 registered patients, twenty-nine patients were exon 19 deletion. Tissue DNA and cfDNA were available in 26 patients. Among the detected seven molecular variants, the most frequent was p.E746_A750delELREA (65.4%). According to the various classifications of molecular variants, twenty one (80.8%) were classified into 15-nucleotide deletion, one (3.8%) into 18-nucleotide deletion, and four patients (15.4%) into other insertion/substitution variant subgroups. The patient subgroup with 15-nucleotide deletion showed significantly longer progression-free survival than patients in other mixed insertion/substitution variant subgroup (p = 0.0244).

CONCLUSIONS

The clinical significance of molecular variants of exon 19 deletion on the first line afatinib monotherapy is reported here for the first time. Further investigation is needed for development of better therapeutic strategies.

TRIAL REGISTRATION

This trial was registered at UMIN Clinical Trials Registry at 2014/12/4 (UMIN000015847).

Comparison of the SuperARMS and ARMS for detecting EGFR mutations in liquid-based cytology specimens from NSCLC patients

BACKGROUND

Non-surgical cytological specimens are adequate not only for accurate histological subtyping but also for molecular profiling. A modified amplification refractory mutation system polymerase chain reaction (ARMS PCR), known as SuperARMS PCR, was improved by optimizing the primers designation, which provides a higher sensitivity and specificity approach for free plasma DNA detection. It is unclear whether SuperARMS PCR detects epidermal growth factor receptor (EGFR) mutations in cytology samples. The aim of this study was to compare the EGFR mutations detected by ARMS PCR and SuperARMS PCR in cytology samples derived from advanced non-small cell lung cancer (NSCLC) patients.

METHODS

From March 2016 to March 2018, a total of 234 cytological samples were obtained from primary or metastatic lesions of NSCLC, including 144 fine-needle aspirations (FNAs), 36 endobroncheal ultrasonography (EBUS) FNAs, 36 transbronchial needle aspirations (TBNAs) and 18 pleural effusion (PLEs). EGFR mutations were simultaneously detected using an ADx-ARMS EGFR kit (Amoy Diagnostics CO., ltd., Xiamen, China) and an ADx-SuperARMS EGFR kit (Amoy Diagnostics CO., ltd., Xiamen, China). Digital droplet PCR (ddPCR) and next-generation sequencing (NGS) were further used to verify the EGFR mutant inconsistent samples.

RESULTS

All of the 234 patients with advanced or recurrent NSCLC were diagnosed and assessed by two cytopathologists, and their EGFR mutation statuses were successfully detected by ARMS and SuperARMS. Importantly, the SuperARMS and ARMS methods showed a highly concordant result of 94.0% (220/234) (95%CI: 85.0, 95.0%). The positive rate of the SuperARMS was higher than the ARMS in the cytology samples for EGFR detection (46.2% vs. 40.2%). The specific EGFR mutation sites in 16 samples (6.8%) were not completely consistent between the SuperARMS and ARMS. A total of 14 patients showed EGFR mutations when detected by SuperARMS, but by ARMS there were EGFR wild-type. Two patients were detected as having one more EGFR mutation site by SuperARMS than by ARMS. ddPCR and NGS were used to further confirm the EGFR mutations in these inconsistent samples. Eight samples had the same mutation results as the SuperARMS, and 6 samples were not verified because the remaining DNA was insufficient. A total of 78 EGFR mutation patients received Tyrosine Kinase Inhibitor (TKI) treatment. The overall objective response rate (ORR) was 88.5% (69/78) for EGFR TKI treatment.

CONCLUSION

SuperARMS showed a high sensitivity and specificity for EGFR detection and thus, is expected to become a routine test in the clinic to be used as a widely available, easy-to-operate and sensitive method for EGFR mutation detection in liquid-based cytology samples.

Comparison detection methods for EGFR in formalin-fixed paraffin-embedded tissues of patients with NSCLC

Epidermal growth factor receptor (EGFR) is an important gene in the development of lung cancer. Non-small cell lung cancer (NSCLC) is the most common lung cancer. In the present study, the expression of EGFR in 717 patients with NSCLC was detected by Ventana automatic immunohistochemical technique, and the samples was verified by Real-time PCR, and then the results were compared with the data acquired by next-generation sequencing technology (NGS), which is the high throughput, multiple sites for EGFR gene mutation testing. The expression of Ventana EGFR in 717 cases of NSCLC was detected by immunohistochemistry, and the positive rate was 60.70 % (435 / 717). The mutation rate of EGFR was 57.60 % (413/717). The coincidence rate of Ventana EGFR immunohistochemical assay and Real-time PCR assay reached 94.94 %, and the two had high consistency. The coincidence rate of Ventana EGFR immunohistochemical assay and NGS were high correlation. Based on these results, Ventana EGFR automatic immunohistochemical detection has high accuracy, simple operation process, low price and easy interpretation. It can be used as the preferred method for EGFR detection.

Drug resistance to targeted therapeutic strategies in non-small cell lung cancer

Rapidly developing molecular biology techniques have been employed to identify cancer driver genes in specimens from patients with non-small cell lung cancer (NSCLC). Inhibitors and antibodies that specifically target driver gene-mediated signaling pathways to suppress tumor growth and progression are expected to extend the survival time and further improve the quality of life of patients. However, the health of patients with advanced and metastatic NSCLC presents significant challenges due to treatment resistance, mediated by cancer driver gene alteration, epigenetic alteration, and tumor heterogeneity. In this review, we discuss two different resistance mechanisms in NSCLC targeted therapies, namely changes in the targeted oncogenes (on-target resistance) and changes in other related signaling pathways (off-target resistance) in tumor cells. We highlight the conventional mechanisms of drug resistance elicited by the complex heterogeneous microenvironment of NSCLC during targeted therapy, including mutations in epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK), the receptor tyrosine kinase ROS proto-oncogene 1 (ROS1), and the serine/threonine-protein kinase BRAF (v-Raf murine sarcoma viral oncogene homolog B). We also discuss the mechanism of action of less common oncoproteins, as in-depth understanding of these molecular mechanisms is important for optimizing treatment strategies.

Cytoplasmic ERβ1 expression is associated with survival of patients with Stage IV lung adenocarcinoma and an EGFR mutation at exon 21 L858R subsequent to treatment with EGFR-TKIs

The present study assessed whether estrogen receptor (ER)β1 is associated with the survival of patients with advanced lung adenocarcinoma, with or without mutations of the epidermal growth factor receptor (EGFR) following treatment with EGFR-tyrosine kinase inhibitors (TKIs). Pathologically confirmed stage IV lung adenocarcinomas were assessed for EGFR mutations and ERβ1 expression. Progression-free survival (PFS) and overall survival (OS) were estimated using the Kaplan-Meier method and the log-rank test. A total of 122 out of the 201 (60.7%) patients had EGFR mutations, 64 (31.8%) of which were EGFR Del19 and 58 mutations (28.9%) were EGFR exon 21 L858R mutation. The presence of EGFR mutations was significantly increased in female patients compared with male patients (P<0.001) and in non-smokers compared with smokers (P<0.001). Patients with EGFR mutations had a significantly improved PFS and OS compared with patients without EGFR mutations treated with EGFR-TKIs. Furthermore, ERβ1 expression was significantly increased in patients with EGFR mutations compared with patients without EGFR mutations (P=0.001). However, the median PFS (P=0.005) and OS (P=0.002) of patients carrying the EGFR exon 21 L858R mutation was significantly decreased in patients with tumors where ERβ1 cytoplasmic expression was high. The multivariate analysis demonstrated that ERβ1 expression was the only independent predictor of PFS (P=0.002) and OS (P=0.003) in patients carrying the EGFR exon 21 L858R mutation. The data demonstrated that ERβ1 expression may predict outcomes of patients with lung adenocarcinoma treated with EGFR-TKI.

Outcome Differences Between First- and Second-generation EGFR Inhibitors in Advanced EGFR Mutated NSCLC in a Large Population-based Cohort

INTRODUCTION

Second-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) appear superior to first-generation TKIs in clinical trials, but at the cost of greater toxicity. It is unclear whether real-world patients, who often suffer worse outcomes, experience similar survival benefits. Using population-based data, we aim to characterize outcome differences by type of treatment.

PATIENTS AND METHODS

We reviewed all patients with advanced non-small-cell lung cancer who initiated treatment with an EGFR TKI at BC Cancer between 2010 and 2015. A propensity score was generated to account for imbalances in patient characteristics between treatment groups. A Cox proportional hazards model based on the propensity score was then used to estimate effects of treatment on survival.

RESULTS

A total of 484 patients were identified for analysis. Patients in the second-generation cohort were younger (62 vs. 67 years), had less baseline central nervous system metastases (9% vs. 22%), and more uncommon EGFR mutations (13% vs. 7%). Patients receiving a second-generation TKI had an improved overall survival (hazard ratio, 0.69; P = .05), driven by the subgroup with an EGFR exon 19 deletion. Patients with a L858R mutation did not appear to derive benefit from a second-generation TKI (hazard ratio, 0.91; P = .74). Overall, 40% of patients receiving a second-generation TKI required a dose reduction, but only 1% required discontinuation.

CONCLUSIONS

Second-generation TKIs tended to be chosen over first-generation TKIs as frontline therapy in younger patients with uncommon EGFR mutations and without central nervous system metastases. The survival benefit of a second-generation TKI seen in clinical trials appeared to be generalizable to real-world patients and is a reasonable first-line therapy.

Different subtypes of EGFR exon19 mutation can affect prognosis of patients with non-small cell lung adenocarcinoma

Aims

In this study, we determined whether different subtypes of epidermal growth factor receptor (EGFR) exon19 mutation are associated with the therapeutic effect of EGFR-tyrosine kinase inhibitors (TKIs) on advanced non-small cell lung adenocarcinoma.

Methods

A total of 122 patients with stage III or IV non-small cell lung adenocarcinoma were retrospectively reviewed. Clinical characteristics of these patients, including progression-free survival (PFS) outcome for EGFR-TKI treatment, were analyzed.

Results

According to the mutation pattern, we classified the in-frame deletions detected on EGFR Exon19 into three different types: codon deletion (CD), with a deletion of one or more original codons; codon substitution and skipping (CSS), with a deletion of one or two nucleotides but the residues could be translated into a new amino acid without changing following amino acid sequence; CD or CSS plus single nucleotide variant (SNV) (CD/CSS+SNV), exclude CD or CSS, there’s another SNV nearby the deletion region. The clinical characteristics of three groups were analyzed and as a result, no significant difference was found. By comparing the average number of missing bases and amino acids of the three mutation subtypes, it could be discovered that the number of missing bases and amino acids of the three mutation subtypes is diverse, and group CSS> group CD> group CD/CSS+SNV. Finally, survival analysis was performed between three groups of patients. The median PFS of group CD, group CSS and group CD/CSS+SNV was 11 months, 9 months and 14 months respectively. There was a distinct difference in the PFS between group CSS and group CD/CSS+SNV (P = 0.035<0.05), and the PFS of group CD/CSS+SNV was longer.

Conclusions

Different mutation subtypes of EGFR exon19 can predict the therapeutic effect of EGFR-TKIs on advanced non-small cell lung adenocarcinoma.

Treatment effectiveness and tolerability of afatinib at different doses in patients with EGFR-mutated lung adenocarcinoma: How low can we go?

INTRODUCTION

Afatinib is commonly used as the first-line treatment for EGFR-mutated lung adenocarcinoma. However, dose adjustments are frequently required. This study aimed to investigate the treatment effectiveness of afatinib administered at different doses to patients with EGFR-mutated lung adenocarcinoma.

METHODS

Treatment-naïve patients with advanced EGFR-mutated lung adenocarcinoma who received afatinib therapy between May 2014 and September 2016 were enrolled retrospectively. Collected clinical data included age, sex, smoking history, performance status, disease stages, EGFR mutation status, initial doses of afatinib, dose adjustments, treatment responses, progression-free survival and treatment-associated adverse events. The average daily dose was calculated by dividing the summation of all doses of prescribed tablets during the treatment period by the total days of afatinib use. The patients were classified into five treatment groups based on average daily doses: 40 mg, <40 and >30 mg, 30 mg, <30 and ≥ 20 mg and <20 mg.

RESULTS

A total of 254 patients were included. No significant differences were found among these five treatment groups with respect to response rates (69.3%, 68.3%, 70.5%, 77.8% and 66.7%, respectively, p = 0.920) and disease control rates (97.4%, 95.2%, 97.7%, 100% and 100%, respectively, p = 0.749). However, the treatment group with an average daily dose of <20 mg had a significant shorter progression-free survival as compared with the other groups (16.8, 12.4, 13.9, 17.0 and 5.3 months, respectively, p = 0.049).

CONCLUSIONS

Dose reduction may not affect the treatment effectiveness until the average daily dose is below 20 mg. Further prospective studies of afatinib therapy at different daily doses are warranted.

Cumulative smoking dose affects the clinical outcomes of EGFR-mutated lung adenocarcinoma patients treated with EGFR-TKIs: a retrospective study

Background

Although lung adenocarcinoma with activating epidermal growth factor receptor (EGFR) mutations is common in never smokers, one-third of the patients are ever-smokers. We aimed to investigate the effect of cumulative smoking dose(CSD) on clinical outcomes, including progression-free survival (PFS) and overall survival (OS), in patients with EGFR-mutated lung adenocarcinoma receiving EGFR-tyrosine kinase inhibitors (TKIs).

Methods

We retrospectively analyzed 142 patients with EGFR-mutation positive advanced or recurrent lung adenocarcinoma who were administered gefitinib, erlotinib, afatinib, and osimertinib. These patients were classified based on their CSD as never smokers, light smokers (≤10 pack-years [PYs]), moderate smokers (11–30 PYs), and heavy smokers (> 30 PYs). PFS and OS were analyzed according to smoking subgroups via Kaplan-Meier curves.

Results

Among the 142 patients, 91 (64.1%), 12 (8.5%), 22 (15.5%), and 17 (12%) were never, light, moderate, and heavy smokers, respectively. CSD was inversely associated with median PFS in a statistically significant dose-dependent manner (11.8 months (mo), 11.0 mo, 7.4 mo, and 3.9 mo; p < 0.001). Statistically significant negative association was observed between CSD and median OS (33.6 mo, 26.3 mo, 20 mo, and 8.9 mo; p < 0.001). In the multivariate analysis adjusted for age, sex, performance status, stage, and timing of EGFR-TKIs, CSD was an independent predictive factor for disease progression (hazard ratio [HR], 4.00; 95% confidence interval [CI], 1.95–8.23; p = 0.012) and OS (HR, 3.9; 95% CI, 1.84–8.28; p < 0.001).

Conclusion

CSD is an important predictive and prognostic factor in patients with EGFR-mutated lung adenocarcinoma, and associated smoking-related gene signatures might affect the outcomes.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4691-0) contains supplementary material, which is available to authorized users.

Ultrasonic diagnosis combined with targeted ultrasound contrast agent improves diagnostic sensitivity of ultrasonic for non-small cell lung cancer patients

Non-small cell lung cancer (NSCLC) is one of the most prevalent human cancers, which is known for local growth, easily migration, long-distance invasion and reoccurrence. Targeted ultrasound (US) contrast combined with ultrasound for lung cancer diagnosis has been applied in the clinic. In the present study, a novel targeted ultrasound contrast agent containing chistosan/Fe₃O₄-parceled bispecific antibody (TcBab) targeting carcino-embryonic antigen, vascular endothelial growth factor receptor was introduced, and the diagnostic accuracy and sensitivity was investigated in patients with NSCLC. A total of 384 patients with suspected NSCLC were recruited to investigate the accuracy of TcBab-ultrasound (TcBab-US) and ultrasound. Results demonstrated that TcBab-US improved sensitivity and may provide a novel protocol for diagnosing tumors in patients with suspected NSCLC at an early stage. Data analysis demonstrated that TcBab-US diagnosed 154 suspected patients with NSCLC, whereas ultrasound only diagnosed 84 suspected patients with NSCLC out of a total of 384 patients with suspected NSCLC (P<0.01). A dosage experiment revealed that the optimal dose of TcBab was 5 mg/kg for NSCLC patients. Pharmacodynamics analysis showed that TcBab may be metabolized within 16 h in serum of patients. Notably, early diagnosis determined by TcBab-US contributed to improvement of survival for NSCLC patients as determined by a comparison of the survival rate with the survival rate of patients who did not receive TcBab (P<0.05). In conclusion, these investigations suggested that TcBab improves the accuracy and diagnostic confidence of ultrasonic for the diagnosis of early-stage NSCLC, and may have potential application value in the clinic.