18F-FDG uptake and EGFR mutations in patients with non-small cell lung cancer: a single-institution retrospective analysis

The HIF-1α/PKM2 Feedback Loop in Relation to EGFR Mutational Status in Lung Adenocarcinoma

OBJECTIVE

Gene mutations in tumor cells can lead to several unique metabolic phenotypes, which are crucial for the proliferation of cancer cells. EGFR mutation (EGFR-mt) is the main oncogenic driving mutation in lung adenocarcinoma (LUAD). HIF-1 α and PKM2 are two key metabolic regulatory proteins that can form a feedback loop and promote cancer growth by promoting glycolysis. Here, the linkage between EGFR mutational status and HIF-1α/PKM2 feedback loop in LUAD were evaluated.

METHODS

Retrospective study were performed on LUAD patients (n = 89) undergoing first-time therapeutic surgical resection. EGFR mutation was analyzed by real-time PCR. Immunohistochemistry was used to measure the expressions of HIF-1α and PKM2.

RESULTS

We found that the protein expressions of HIF-1α and PKM2 were significantly higher in LUAD than normal lung tissues. In adenocarcinomas, the two protein expressions were both correlated with worse pTNM stage. Moreover, the correlation between the proteins of HIF-1α/PKM2 feedback loop and the EGFR mutational status were also analyzed. We found that EGFR-mt tumors showed higher HIF-1α and PKM2 proteins compared to tumors with EGFR wild-type. Meanwhile, HIF-1α expression was significantly correlated with higher pTNM stage, and PKM2 showed a similar trend, only in EGFR-mutated tumors. The expression of HIF-1α was positively correlated with PKM2 in LUAD, furthermore, this correlation was mainly in patients with EGFR-mt.

CONCLUSION

Different expression and clinical features of HIF-1α/PKM2 feedback loop was existed between LUAD and normal lung tissues, especially in EGFR mutational tumors, supporting the relationship between EGFR mutation and the key related proteins of aerobic glycolysis (HIF-1α and PKM2) in lung adenocarcinomas.

Exploring the correlation between HER2 alterations and 18F-FDG PET/CT metabolic parameters and their prognostic value in EGFR-negative non-small-cell lung cancer patients

PURPOSE

Our study intended to explore the correlation between HER2 alterations and 18F-FDG PET/CT metabolic parameters and their prognostic value in EGFR-negative non-small-cell lung cancer (NSCLC) patients detected by next-generation sequencing (NGS).

METHODS

NGS assay was performed in 1737 NSCLC patients, a total of 88 HER2 alterations and 176 negative HER2 with EGFR-negative patients were randomly selected for this study.

RESULTS

When the HER2 status with EGFR-negative group was analyzed, multivariate analysis showed that smoking status, primary tumor SUVmax (pSUVmax) < 13.03 and stage were the independent deterministic factors of HER2 alterations. Multivariate cox regression analysis revealed that HER2 status, age, smoking status and stage were independent risk factors for overall survival (OS) in EGFR-negative NSCLC patients with different HER2 status. When the HER2 alterations group was separately analyzed, multivariate analysis demonstrated that low pSUVmax < 15.32 and histology were the independent deterministic factors of HER2 mutation. Multivariate cox regression analysis revealed that pSUVmax, smoking status, nodal involvement and treatment methods were independent risk factors for OS in EGFR-negative NSCLC patients with HER2 alterations.

CONCLUSION

The study revealed that low pSUVmax was associated with HER2 alterations in EGFR-negative NSCLC patients, moreover HER2 mutation and HER2 amplification exhibited distinct 18F-FDG metabolic and clinical characteristics. Furthermore, it explored the prognostic value of HER2 alterations and 18F-FDG PET/CT metabolic parameters of pSUVmax in EGFR-negative NSCLC patients.

Identification of EGFR mutation status in male patients with non-small-cell lung cancer: role of 18F-FDG PET/CT and serum tumor markers CYFRA21-1 and SCC-Ag

BACKGROUND

The high incidence of epidermal growth factor receptor (EGFR) mutations is usually found in female patients with lung adenocarcinoma who have never-smoked. However, reports concerning male patients are scarce. Thus, this study aimed to explore a novel approach based on ¹⁸F-fluoro-2-deoxy-2-deoxyglucose (¹⁸F-FDG) PET/CT and serum tumor markers (STMs) to determine EGFR mutation status in male patients with non-small-cell lung cancer (NSCLC).

METHODS

A total of 121 male patients with NSCLC were analyzed between October 2019 and March 2022. All patients underwent ¹⁸F-FDG PET/CT scan before treatment and monitored 8 STMs (cytokeratin 19 fragment [CYFRA21-1], squamous cell carcinoma-related antigen [SCC-Ag], carcinoembryonic antigen [CEA], neuron-specific enolase [NSE], carbohydrate antigen [CA] 50, CA125, CA72-4, and ferritin). A comparison was done between EGFR mutant and wild-type patients in terms of the maximum standardized uptake value of primary tumors (pSUV_max) and 8 STMs. We performed receiver operating characteristic (ROC) curve and multiple logistic regression analyses to determine predictors for EGFR mutation status.

RESULTS

EGFR mutations were detected in 39 patients (32.2%). Compared with patients with EGFR wild-type, EGFR-mutant patients had lower concentrations of serum CYRFA21-1 (2.65 vs. 4.01, P = 0.002) and SCC-Ag (0.67 vs. 1.05, P = 0.006). No significant differences of CEA, NSE, CA 50, CA125, CA72-4 and ferritin were found between the two groups. The presence of EGFR mutations was significantly associated with low pSUV_max (< 8.75), low serum SCC-Ag (< 0.79 ng/mL) and CYFRA21-1 (< 2.91 ng/mL) concentrations. The area under ROC curve values were 0.679, 0.655, 0.685 and 0.754, respectively, for low CYFRA21-1, SCC-Ag, pSUV_max and the combination of these three factors.

CONCLUSIONS

We demonstrated that low concentrations of CYFRA21-1 and SCC-Ag, as well as low pSUV_max, were associated with EGFR mutations, and that the combination of these factors resulted in a higher differentiation of EGFR mutation status in male patients with NSCLC.

A Review of the Correlation Between Epidermal Growth Factor Receptor Mutation Status and 18F-FDG Metabolic Activity in Non-Small Cell Lung Cancer

PET/CT with 18F-2-fluoro-2-deoxyglucose (18F-FDG) has been proposed as a promising modality for diagnosing and monitoring treatment response and evaluating prognosis for patients with non-small cell lung cancer (NSCLC). The status of epidermal growth factor receptor (EGFR) mutation is a critical signal for the treatment strategies of patients with NSCLC. Higher response rates and prolonged progression-free survival could be obtained in patients with NSCLC harboring EGFR mutations treated with tyrosine kinase inhibitors (TKIs) when compared with traditional cytotoxic chemotherapy. However, patients with EGFR mutation treated with TKIs inevitably develop drug resistance, so predicting the duration of resistance is of great importance for selecting individual treatment strategies. Several semiquantitative metabolic parameters, e.g., maximum standard uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG), measured by PET/CT to reflect 18F-FDG metabolic activity, have been demonstrated to be powerful in predicting the status of EGFR mutation, monitoring treatment response of TKIs, and assessing the outcome of patients with NSCLC. In this review, we summarize the biological and clinical correlations between EGFR mutation status and 18F-FDG metabolic activity in NSCLC. The metabolic activity of 18F-FDG, as an extrinsic manifestation of NSCLC, could reflect the mutation status of intrinsic factor EGFR. Both of them play a critical role in guiding the implementation of treatment modalities and evaluating therapy efficacy and outcome for patients with NSCLC.

Predictive value of multiple metabolic and heterogeneity parameters of 18F-FDG PET/CT for EGFR mutations in non-small cell lung cancer

OBJECTIVES

To explore the value of multiple metabolic and heterogeneity parameters of 2-deoxy-2-[fluorine-18] fluoro-D-glucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) in predicting epidermal growth factor receptor gene (EGFR) mutations in non-small cell lung cancer (NSCLC).

MATERIALS AND METHODS

A retrospective analysis was performed by reviewing 98 patients with NSCLC who underwent EGFR mutation testing and ¹⁸F-FDG PET/CT examination in our hospital between March 2016 and March 2021. Patients were divided into an EGFR-mutant group and a wild-type group. A multivariate logistic regression analysis was performed to screen and construct a prediction model. The diagnostic performance of the model was evaluated using a receiver-operating characteristic (ROC) curve.

RESULTS

The study found that EGFR mutations were more likely to occur in women, non-smokers, and patients with peripheral lesions, shorter maximum tumor diameter, adenocarcinoma, and T1 stage cancer. Low maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), metabolic tumor volume, total lesion glycolysis, and high coefficient of variation (COV) were significantly correlated with EGFR mutations, and the area under the ROC curve (AUC) was 0.622, 0.638, 0.679, 0.687, and 0.672, respectively. Multivariate logistic regression analysis indicated that non-smokers (odds ratio (OR) = 0.109, P = 0.014), peripheral lesions (OR = 6.917, P = 0.022), low SUVmax (≤ 7.85, OR = 5.471, P = 0.001), SUVmean (≤ 5.34, OR = 0.044, P = 0.000), and high COV (≥ 106.08, OR = 0.996, P = 0.045) were independent predictors of EGFR mutations. The AUC of the prediction model established by combining the above factors was 0.926; the diagnostic efficiency was significantly higher than that of a single parameter.

CONCLUSION

Among the metabolic and heterogeneity parameters of ¹⁸F-FDG PET/CT, low SUVmax, SUVmean, and high COV were significantly associated with EGFR mutations, and the predictive value of EGFR mutations could be enhanced when combined with clinicopathological features.

Can 18F-FDG PET/CT predict EGFR status in patients with non-small cell lung cancer? A systematic review and meta-analysis

OBJECTIVES

This study aimed to explore the diagnostic significance of ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography (PET)/CT for predicting the presence of epidermal growth factor receptor (EGFR) mutations in patients with non-small cell lung cancer (NSCLC).

DESIGN

A systematic review and meta-analysis.

DATA SOURCES

The PubMed, EMBASE and Cochrane library databases were searched from the earliest available date to December 2020.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

The review included primary studies that compared the mean maximum of standard uptake value (SUV_max) between wild-type and mutant EGFR, and evaluated the diagnostic value of ¹⁸F-FDG PET/CT using SUV_max for prediction of EGFR status in patients with NSCLC.

DATA EXTRACTION AND SYNTHESIS

The main analysis was to assess the sensitivity and specificity, the positive diagnostic likelihood ratio (DLR+) and DLR-, as well as the diagnostic OR (DOR) of SUV_max in prediction of EGFR mutations. Each data point of the summary receiver operator characteristic (SROC) graph was derived from a separate study. A random effects model was used for statistical analysis of the data, and then diagnostic performance for prediction was further assessed.

RESULTS

Across 15 studies (3574 patients), the pooled sensitivity for ¹⁸F-FDG PET/CT was 0.70 (95% CI 0.60 to 0.79) with a pooled specificity of 0.59 (95% CI 0.52 to 0.66). The overall DLR+ was 1.74 (95% CI 1.49 to 2.03) and DLR- was 0.50 (95% CI 0.38 to 0.65). The pooled DOR was 3.50 (95% CI 2.37 to 5.17). The area under the SROC curve was 0.68 (95% CI 0.64 to 0.72). The likelihood ratio scatter plot based on average sensitivity and specificity was in the lower right quadrant.

CONCLUSION

Meta-analysis results showed ¹⁸F-FDG PET/CT had low pooled sensitivity and specificity. The low DOR and the likelihood ratio scatter plot indicated that ¹⁸F-FDG PET/CT should be used with caution when predicting EGFR mutations in patients with NSCLC.

The diagnostic and predictive efficacy of 18F-FDG PET/CT metabolic parameters for EGFR mutation status in non-small-cell lung cancer: A meta-analysis

PURPOSE

To investigate the predictive performance of the maximum standardized uptake value (SUV_max) and mean standardized uptake value (SUV_mean) of primary lesions based on 18 F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) for EGFR mutation status in patients with non-small cell lung cancer (NSCLC).

METHODS

The PubMed/Medline, Embase, Cochrane Library and Web of Science databases were searched as of January 1, 2021. Studies whose reported data could be used to construct contingency tables were included. Study characteristics were extracted, and methodological quality assessment was conducted by two separate reviewers using the Quality Assessment of Diagnostic Accuracy Studies. The pooled sensitivity, specificity and area under the summary receiver operating characteristic curve (AUROC) were calculated. The possible causes of heterogeneity were analysed by meta-regression.

RESULTS

The 18 included studies had a total of 4024 patients. The majority of the studies showed a low to unclear risk of bias and concerns of applicability. For differentiating EGFR-mutant NSCLC from wild-type NSCLC, the pooled sensitivity and specificity were 71 % and 60 % for SUV_max and 64 % and 63 % for SUV_mean, respectively. The summary AUROCs of SUV_max and SUV_mean were 0.69 (95 % CI, 0.65-0.73) and 0.68 (95 % CI, 0.64-0.72), respectively. The meta-regression analysis indicated that blindness to EGFR mutation test results, the number of readers and the number of PET/CT scanners were possible causes of heterogeneity.

CONCLUSIONS

Our meta-analysis implied that SUV_max and SUV_mean of primary lesions from ¹⁸F-FDG PET/CT harboured moderate predictive efficacy for the EGFR mutation status of NSCLC.

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

Purpose

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

Methods

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

Results

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

Conclusion

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

Non-invasive decision support for NSCLC treatment using PET/CT radiomics

Two major treatment strategies employed in non-small cell lung cancer, NSCLC, are tyrosine kinase inhibitors, TKIs, and immune checkpoint inhibitors, ICIs. The choice of strategy is based on heterogeneous biomarkers that can dynamically change during therapy. Thus, there is a compelling need to identify comprehensive biomarkers that can be used longitudinally to help guide therapy choice. Herein, we report a ¹⁸F-FDG-PET/CT-based deep learning model, which demonstrates high accuracy in EGFR mutation status prediction across patient cohorts from different institutions. A deep learning score (EGFR-DLS) was significantly and positively associated with longer progression free survival (PFS) in patients treated with EGFR-TKIs, while EGFR-DLS is significantly and negatively associated with higher durable clinical benefit, reduced hyperprogression, and longer PFS among patients treated with ICIs. Thus, the EGFR-DLS provides a non-invasive method for precise quantification of EGFR mutation status in NSCLC patients, which is promising to identify NSCLC patients sensitive to EGFR-TKI or ICI-treatments.

EGFR mutations are common in non-small cell lung cancer and patients with these mutations are treated with tyrosine kinase inhibitors. Here, the authors show that EGFR mutation status can be predicted from ¹⁸F-FDG-PET/CT images, which may enable the stratification of patients for treatment.

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

Purpose

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

Methods

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

Results

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

Conclusion

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

Relationship of radiometabolic biomarkers to KRAS mutation status and ALK rearrangements in cases of lung adenocarcinoma

PURPOSE

Rapid diagnosis of genetic mutations is important for targeted therapies such as EGFR tyrosine kinase inhibitors. KRAS mutation and ALK rearrangement are also important in determining treatment. The purpose of our study was to evaluate the diagnostic value of 18F-FDG PET to predict KRAS mutation and ALK rearrangement in order to determine the frequency of these genetic markers in our lung adenocarcinoma cases and contribute to forthcoming meta-analysis studies.

METHODS

A total of 218 patients with lung adenocarcinoma (EGFR analyzed) who were seen at our clinic between 2012 and 2014 were included in the study. The results of the 18 F-FDG-PET scans for each patient were retrospectively recorded with the associated medical documents. ALK rearrangements were analyzed in 166 of the 218 patients, while 50 of the 218 patients were analyzed for KRAS mutational status. SPSS 15.0 for Windows was used for statistical analysis.

RESULTS

FDG avidity was higher in cases with KRAS mutations and ALK rearrangements than those without, but the difference was not significant. ALK rearrangements were more common in younger, female, and nonsmoking patients with lung adenocarcinoma.

CONCLUSIONS

The small numbers of KRAS mutations and ALK rearrangements are the limitation of this study for evaluation of diagnostic imaging. The frequency of these genetic alterations was as reported in the literature. We believe that our work will contribute to future meta-analysis.

Predictive models for patients with lung carcinomas to identify EGFR mutation status via an artificial neural network based on multiple clinical information

PURPOSE

Epidermal growth factor receptor (EGFR) mutation testing has several limitations. Therefore, we built predictive models to determine the EGFR mutation status of patients and guide therapeutic decision-making.

METHODS

We collected data from 320 patients with lung carcinoma, including sex, age, smoking history, serum tumour marker levels, maximum standardized uptake value, pathological results, computed tomography images, and EGFR mutation status. Artificial neural network (ANN) models based on multiple clinical characteristics were proposed to predict EGFR mutation status.

RESULTS

A training set (n = 200) was used to develop predictive models of the EGFR mutation status (Model 1: area under the receiver operating characteristic curve [AUROC] = 0.910, 95% CI 0.861-0.945; Model 2: AUROC = 0.859, 95% CI 0.803-0.904; Model 3: AUROC = 0.711, 95% CI 0.643-0.773). A testing set (n = 50) and temporal validation data set (n = 70) were used to evaluate the generalisation performance of the established models (testing set: Model 1, AUROC = 0.845, 95% CI 0.715-0.932; Model 2, AUROC = 0.882, 95% CI 0.759-0.956; Model 3, AUROC = 0.817, 95% CI 0.682-0.912; temporal validation dataset: Model 1, AUROC = 0.909, 95% CI 0.816-0.964; Model 2, AUROC = 0.855, 95% CI 0.751-0.928; Model 3, AUROC = 0.831, 95% CI 0.723-0.910). The predictive abilities of the three ANN models were superior to that of a previous logistic regression model (P < 0.001, 0.027, and 0.050, respectively).

CONCLUSIONS

ANN models provide a non-invasive and readily available method for EGFR mutation status prediction.

Association between EGFR mutation and ageing, history of pneumonia and gastroesophageal reflux disease among patients with advanced lung cancer

BACKGROUND

Epidermal growth factor receptor (EGFR) mutation is the most frequently encountered oncogenic driver in lung cancer. Risk factors for EGFR mutation may help prevention, surveillance and diagnosis strategies of EGFR-mutated lung cancer.

PATIENTS AND METHODS

A nationwide, retrospective, longitudinal, cohort study was performed between January 2002 and December 2015. Patient data were collected from the Korean National Health Insurance Database. The lung cancer group included EGFR tyrosine kinase inhibitor (TKI)-treated patients. Controls were randomly selected from people without a history of lung cancer and determined to be four times the number of patients with EGFR-mutated advanced lung cancer. The risk model of developing EGFR-mutated lung cancer was constructed by multiple logistic regression analysis.

RESULTS

Among the 2010 new cases of lung cancer treated in 2010-2015, 214 cases were classified as EGFR-mutated advanced lung cancer. The risk of developing EGFR-mutated advanced lung cancer was higher in patients in their 50s (odds ratio [OR]: 3.42; 95% confidence interval [CI]: 1.68-6.93), 60s (OR: 7.04; 95% CI: 3.35-14.77) and 70s (OR: 10.27; 95% CI: 4.73-22.30) and in those aged >80 years (OR: 5.98; 95% CI: 2.25-15.92) than those in their 40s. The risk of developing EGFR-mutated lung cancer was also higher in hospitalised patients with a history of pneumonia (OR: 5.22; 95% CI: 1.88-14.46) and those with gastroesophageal reflux disease (OR: 2.02; 95% CI: 1.32-3.07).

CONCLUSIONS

Patients with EGFR-mutated advanced lung cancer were associated with ageing, history of being hospitalised for pneumonia and gastroesophageal reflux disease.

Predictive Power of a Radiomic Signature Based on 18F-FDG PET/CT Images for EGFR Mutational Status in NSCLC

Radiomics has become an area of interest for tumor characterization in ¹⁸F-Fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) imaging. The aim of the present study was to demonstrate how imaging phenotypes was connected to somatic mutations through an integrated analysis of 115 non-small cell lung cancer (NSCLC) patients with somatic mutation testings and engineered computed PET/CT image analytics. A total of 38 radiomic features quantifying tumor morphological, grayscale statistic, and texture features were extracted from the segmented entire-tumor region of interest (ROI) of the primary PET/CT images. The ensembles for boosting machine learning scheme were employed for classification, and the least absolute shrink age and selection operator (LASSO) method was used to select the most predictive radiomic features for the classifiers. A radiomic signature based on both PET and CT radiomic features outperformed individual radiomic features, the PET or CT radiomic signature, and the conventional PET parameters including the maximum standardized uptake value (SUVmax), SUVmean, SUVpeak, metabolic tumor volume (MTV), and total lesion glycolysis (TLG), in discriminating between mutant-type of epidermal growth factor receptor (EGFR) and wild-type of EGFR- cases with an AUC of 0.805, an accuracy of 80.798%, a sensitivity of 0.826 and a specificity of 0.783. Consistently, a combined radiomic signature with clinical factors exhibited a further improved performance in EGFR mutation differentiation in NSCLC. In conclusion, tumor imaging phenotypes that are driven by somatic mutations may be predicted by radiomics based on PET/CT images.

New insight on the correlation of metabolic status on 18F-FDG PET/CT with immune marker expression in patients with non-small cell lung cancer

BACKGROUND

Metabolic information obtained through ¹⁸F-flurodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) is used to evaluate malignancy by calculating the glucose uptake rate, and these parameters play important roles in determining the prognosis of non-small cell lung cancer (NSCLC). The expression of immune-related markers in tumor tissue reflects the immune status in the tumor microenvironment. However, there is lack of reports on the association between metabolic variables and intra-tumor immune markers. Herein, we investigate the correlation between metabolic status on ¹⁸F-FDG PET/CT and intra-tumor immunomarkers' expression in NSCLC patients.

METHODS

From April 2008 to August 2014, 763 patients were enrolled in the analysis to investigate the role of maximum standardized uptake value (SUVmax) in lung cancer. One hundred twenty-two tumor specimens were analyzed by immunohistochemistry (IHC) to intra-tumor immune cells and programmed death protein ligand 1(PD-L1) expression on tumor cells. The correlation between metabolic variables and the expression of tissue immune markers were analyzed.

RESULTS

SUVmax values have significant variations in different epidermal growth factor receptor (EGFR) statuses (wild type vs mutant type), high/low neutrophil-to-lymphocyte ratio (NLR) groups, and high/low platelets-to-lymphocyte ratio (PLR) groups (p < 0.001, p < 0.001, p = 0.003, respectively). SUVmax was an independent prognostic factor in lung cancer patients (p = 0.013). IHC demonstrated a statistically significant correlation between SUVmax and the expression of CD8 tumor-infiltrating lymphocytes (p = 0.015), CD163 tumor-associated macrophages (TAMs) (p = 0.003), and Foxp3-regulatory T cells (Tregs) (p = 0.004), as well as PD-1 and PD-L1 (p = 0.003 and p = 0.012, respectively). With respect to patient outcomes, disease stage, BMI, SUVmax, metabolic tumor volume (MTV), TLG (tumor lesion glycolysis), CD163-TAMs, CD11c-dendritic cells (DCs), PD-L1, and Tregs showed a statistically significant correlation with progression-free survival (PFS) (p < 0.001, 0.023, < 0.001, 0.007, 0.005, 0.004, 0.008, 0.048, and 0.014, respectively), and disease stage, SUVmax, MTV, TLG, CD163-TAMs, CD11c-DCs, and PD-L1 showed a statistically significant correlation with overall survival (OS) (p < 0.001, < 0.001, 0.014, 0.012, < 0.001, 0.001, and < 0.001, respectively).

CONCLUSION

This study revealed an association between metabolic variable and immune cell expression in the tumor microenvironment and suggests that SUVmax on ¹⁸F-FDG PET/CT could be a potential predictor for selecting candidates for immunotherapy.

Correlations Study Between 18F-FDG PET/CT Metabolic Parameters Predicting Epidermal Growth Factor Receptor Mutation Status and Prognosis in Lung Adenocarcinoma

Purpose: This study assessed the ability of metabolic parameters from ¹⁸Fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) and clinicopathological data to predict epidermal growth factor receptor (EGFR) expression/mutation status in patients with lung adenocarcinoma and to develop a prognostic model based on differences in EGFR expression status, to enable individualized targeted molecular therapy. Patients and Methods: Metabolic parameters and clinicopathological data from 200 patients diagnosed with lung adenocarcinoma between July 2009 and November 2016, who underwent ¹⁸F-FDG PET/CT and EGFR mutation testing, were retrospectively evaluated. Multivariate logistic regression was applied to significant variables to establish a prediction model for EGFR mutation status. Overall survival for both mutant and wild-type EGFR was analyzed to establish a multifactor Cox regression model. Results: Of the 200 patients, 115 (58%) exhibited EGFR mutations and 85 (42%) were wild-type. Among selected metabolic parameters, metabolic tumor volume (MTV) demonstrated a significant difference between wild-type and mutant EGFR mutation status, with an area under the receiver operating characteristic curve (AUC) of 0.60, which increased to 0.70 after clinical data (smoking status) were combined. Survival analysis of wild-type and mutant EGFR yielded mean survival times of 34.451 (95% CI 28.654-40.249) and 53.714 (95% CI 44.331-63.098) months, respectively. Multivariate Cox regression revealed that mutation type, tumor stage, and thyroid transcription factor-1 (TTF-1) expression status were the main factors influencing patient prognosis. The hazard ratio for mutant EGFR was 0.511 (95% CI 0.303-0.862) times that of wild-type, and the risk of death was lower for mutant EGFR than for wild-type. The risk of death was lower in TTF-1-positive than in TTF-1-negative patients. Conclusion: ¹⁸F-FDG PET/CT metabolic parameters combined with clinicopathological data demonstrated moderate diagnostic efficacy in predicting EGFR mutation status and were associated with prognosis in mutant and wild-type EGFR non-small-cell lung cancer (NSCLC), thus providing a reference for individualized targeted molecular therapy.

Value of 18F-FDG PET/CT for predicting EGFR mutations and positive ALK expression in patients with non-small cell lung cancer: a retrospective analysis of 849 Chinese patients

PURPOSE

Epidermal growth factor receptor (EGFR) mutations and the anaplastic lymphoma kinase (ALK) rearrangement are the two most common druggable targets in non-small cell lung cancer (NSCLC). However, genetic testing is sometimes unavailable. Previous studies regarding the predictive role of 18F-FDG PET/CT for EGFR mutations in NSCLC patients are conflicting. We investigated whether or not 18F-FDG PET could be a valuable noninvasive method to predict EGFR mutations and ALK positivity in NSCLC using the largest patient cohort to date.

METHODS

We retrospectively reviewed and included 849 NSCLC patients who were tested for EGFR mutations or ALK status and subjected to 18F-FDG PET/CT prior to treatment. The differences in several clinical characteristics and three parameters based on 18F-FDG PET/CT, including the maximal standard uptake value (SUVmax) of the primary tumor (pSUVmax), lymph node (nSUVmax) and distant metastasis (mSUVmax), between the different subgroups were analyzed. Multivariate logistic regression analysis was performed to identify predictors of EGFR mutations and ALK positivity.

RESULTS

EGFR mutations were identified in 371 patients (45.9%). EGFR mutations were found more frequently in females, non-smokers, adenocarcinomas and stage I disease. Low pSUVmax, nSUVmax and mSUVmax were significantly associated with EGFR mutations. Multivariate analysis demonstrated that pSUVmax < 7.0, female sex, non-smoker status and adenocarcinoma were predictors of EGFR mutations. The receiver operating characteristic (ROC) curve yielded area under the curve (AUC) values of 0.557 and 0.697 for low pSUVmax alone and the combination of the four factors, respectively. ALK-positive patients tended to have a high nSUVmax. Younger age and distant metastasis were the only two independent predictors of ALK positivity.

CONCLUSION

We demonstrated that low pSUVmax is associated with mutant EGFR status and could be integrated with other clinical factors to enhance the discriminability on the EGFR mutation status in some NSCLC patients whose EGFR testing is unavailable.

Non-invasive tumor genotyping using radiogenomic biomarkers, a systematic review and oncology-wide pathway analysis

With targeted treatments playing an increasing role in oncology, the need arises for fast non-invasive genotyping in clinical practice. Radiogenomics is a rapidly evolving field of research aimed at identifying imaging biomarkers useful for non-invasive genotyping. Radiogenomic genotyping has the advantage that it can capture tumor heterogeneity, can be performed repeatedly for treatment monitoring, and can be performed in malignancies for which biopsy is not available. In this systematic review of 187 included articles, we compiled a database of radiogenomic associations and unraveled networks of imaging groups and gene pathways oncology-wide. Results indicated that ill-defined tumor margins and tumor heterogeneity can potentially be used as imaging biomarkers for 1p/19q codeletion in glioma, relevant for prognosis and disease profiling. In non-small cell lung cancer, FDG-PET uptake and CT-ground-glass-opacity features were associated with treatment-informing traits including EGFR-mutations and ALK-rearrangements. Oncology-wide gene pathway analysis revealed an association between contrast enhancement (imaging) and the targetable VEGF-signalling pathway. Although the need of independent validation remains a concern, radiogenomic biomarkers showed potential for prognosis prediction and targeted treatment selection. Quantitative imaging enhanced the potential of multiparametric radiogenomic models. A wealth of data has been compiled for guiding future research towards robust non-invasive genomic profiling.

Relation of EGFR Mutation Status to Metabolic Activity in Localized Lung Adenocarcinoma and Its Influence on the Use of FDG PET/CT Parameters in Prognosis

OBJECTIVE

The purposes of this study were to assess the relation between epidermal growth factor receptor (EGFR) mutation status and FDG PET/CT findings and to evaluate the influence of this relation on the use of FDG PET/CT parameters to establish a prognosis in cases of localized lung adenocarcinoma.

MATERIALS AND METHODS

Patients with stage I and II lung adenocarcinomas were retrospectively enrolled. At the initial FDG PET/CT examination, maximum and peak standardized uptake, tumor-to-background ratio, and volumetric parameters of metabolic tumor volume and total lesion glycolysis were measured.

RESULTS

The values of all the metabolic and volumetric FDG PET/CT parameters were significantly lower in EGFR mutant than in EGFR wild-type lung adenocarcinomas. All parameters were statistically significant for predicting recurrence-free survival. In multivariate analyses, peak standardized uptake and total lesion glycolysis were more significant prognostic factors than was TNM stage (p < 0.001). Optimal cutoff values of parameters for predicting recurrence-free survival were slightly different between the two groups.

CONCLUSION

EGFR mutation is related to low metabolic activity of localized lung adenocarcinoma at FDG PET/CT. Because of differences in the metabolic activity of EGFR mutant and wild-type tumors, EGFR mutation status must be considered when FDG PET/CT parameters are used for prognosis.

The role of metabolic tumor volume (MTV) measured by [18F] FDG PET/CT in predicting EGFR gene mutation status in non-small cell lung cancer

Many noninvasive methods have been explored to determine the mutation status of the epidermal growth factor receptor (EGFR) gene, which is important for individualized treatment of non-small cell lung cancer (NSCLC). We evaluated whether metabolic tumor volume (MTV), a parameter measured by [18F] fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) might help predict EGFR mutation status in NSCLC. Overall, 87 patients who underwent EGFR genotyping and pretreatment PET/CT between January 2013 and September 2016 were reviewed. Clinicopathologic characteristics and metabolic parameters including MTV were evaluated. Univariate and multivariate analyses were used to assess the independent variables that predict mutation status to create prediction models. Forty-one patients (41/87) were identified as having EGFR mutations. The multivariate analysis showed that patients with lower MTV (MTV≤11.0 cm3, p=0.001) who were non-smokers (p=0.037) and had a peripheral tumor location (p=0.033) were more likely to have EGFR mutations. Prediction models using these criteria for EGFR mutation yielded a high AUC (0.805, 95% CI 0.712–0.899), which suggests that the analysis had good discrimination. In conclusion, NSCLC patients with EGFR mutations showed significantly lower MTV than patients with wild-type EGFR. Prediction models based on MTV and clinicopathologic characteristics could provide more information for the identification of EGFR mutations.

Value of combining serum carcinoembryonic antigen and PET/CT in predicting EGFR mutation in non-small cell lung cancer

Background

We sought to investigate the associations between pretreatment serum Carcinoembryonic antigen (CEA) level, ¹⁸F-Fluoro-2-deoxyglucose (¹⁸F-FDG) uptake value of primary tumor and epidermal growth factor receptor (EGFR) mutation status in non-small cell lung cancer (NSCLC).

Methods

We retrospectively reviewed medical records of 210 NSCLC patients who underwent EGFR mutation test and ¹⁸F-FDG positron emission tomography/computed tomography (PET/CT) scan before anti-tumor therapy. The associations between EGFR mutations and patients' characteristics, serum CEA, PET/CT imaging characteristics maximal standard uptake value (SUVmax) of the primary tumor were analyzed. Receiver-operating characteristic (ROC) curve was used to assess the predictive value of these factors.

Results

EGFR mutations were found in 70 patients (33.3%). EGFR mutations were more common in high CEA group (CEA ≥7.0 ng/mL) than in low CEA group (CEA <7.0 ng/mL) (40.4% vs. 27.6%; P=0.05). Females (P<0.001), non-smokers (P<0.001), patients with adenocarcinoma (P<0.001) and SUVmax <9.0 (P=0.001) were more likely to be EGFR mutation-positive. Multivariate analysis revealed that gender, tumor histology, pretreatment serum CEA level, and SUVmax were the most significant predictors for EGFR mutations. The ROC curve revealed that combining these four factors yielded a higher calculated AUC (0.80).

Conclusions

Gender, histology, pretreatment serum CEA level and SUVmax are significant predictors for EGFR mutations in NSCLC. Combining these factors in predicting EGFR mutations has a moderate diagnostic accuracy, and is helpful in guiding anti-tumor treatment.

[Current Status and Progress in Molecular Imaging of Non-small Cell Lung Cancer for Molecular Targeted EGFR-TKI Treatment Sensitivity and Treatment Tolerance Prediction]

肺癌80%以上为非小细胞肺癌（non-small cell lung cancer, NSCLC），表皮生长因子受体（epidermal growth factor receptor, EGFR）介导的信号通路与NSCLC发生发展密切相关。针对EGFR的小分子EGFR赖氨酸激酶抑制剂（EGFR-tyrosine kinase inhibitor, EGFR-TKI）被应用于NSCLC的临床治疗，正电子发射计算机断层显像（positron emission tomography/computed tomgraphy, PET/CT）能够无创地对NSCLC患者全身EGFR表达及突变状况进行连续动态监测。¹⁸F-FDG PET/CT显像对于EGFR活化突变、EGFR-TKI治疗疗效具有预测价值，并且能够在体直接观察到药物与全身肿瘤病灶EGFR靶向结合的具体情况，通过治疗前后的PET-CT显像，实现治疗前高敏人群筛选和治疗全过程的动态监测、治疗策略指导，对实现NSCLC的EGFR-TKI精准治疗至关重要。

Metabolic characteristics of programmed cell death-ligand 1-expressing lung cancer on 18 F-fluorodeoxyglucose positron emission tomography/computed tomography

Programmed cell death‐1 (PD‐1) and programmed cell death‐ligand 1 (PD‐L1) have been identified as novel targets of immunotherapy of lung cancer. In present study, we evaluated the metabolic characteristics of lung cancer by using ¹⁸F‐fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F‐FDG PET/CT) with regard to PD‐L1 protein expression. PD‐L1 protein expression was evaluated by immunohistochemistry with the antibody clone SP142 in 579 surgically resected primary lung cancer patients. Cases with less than 5% tumor membrane staining were considered negative. We examined the association between the frequency of PD‐L1 protein expression and the maximum standardized uptake value (SUVmax) in preoperative ¹⁸F‐FDG PET/CT. The cut‐off values for SUVmax were determined by receiver operating characteristic curve analyses. The SUVmax was significantly higher in nonsmall cell lung cancer (NSCLC) patients with PD‐L1 protein expression compared with those without PD‐L1 protein expression (P < 0.0001). However, there was no correlation between SUVmax and PD‐L1 protein expression in patients with neuroendocrine tumors (P = 0.6545). Multivariate analysis revealed that smoking, the presence of pleural invasion, and high SUVmax were independent predictors of PD‐L1 positivity. PD‐L1‐expressing NSCLC had a high glucose metabolism. The SUVmax in preoperative ¹⁸F‐FDG PET/CT was a predictor of PD‐L1 protein expression in patients with NSCLC.

Combining PET/CT with serum tumor markers to improve the evaluation of histological type of suspicious lung cancers

OBJECTIVE

Histological type is important for determining the management of patients with suspicious lung cancers. In this study, PET/CT combined with serum tumor markers were used to evaluate the histological type of lung lesions.

MATERIALS AND METHODS

Patients with suspicious lung cancers underwent 18F-FDG PET/CT and serum tumor markers detection. SUVmax of the tumor and serum levels of tumor markers were acquired. Differences in SUVmax and serum levels of tumor markers among different histological types of lung cancers and between EGFR mutation statues of adenocarcinoma were compared. The diagnostic efficiencies of SUVmax alone, each serum tumor marker alone, combined tumor markers and the combination of both methods were further assessed and compared.

RESULTS

SCC had the highest level of SUVmax, followed by SCLC and adenocarcinoma, and benign lesions had a lowest level. CYFRA21-1 and SCC-Ag were significantly higher in SCC, NSE was significantly higher in SCLC (P<0.001), and CEA was higher in adenocarcinoma (P = 0.343). The diagnostic efficiencies in evaluating histological types of suspicious lung cancers were insufficient when using each serum tumor marker or SUVmax alone. When combined, the AUC, sensitivity and specificity increased significantly (P<0.05 for all). Additionally, to adenocarcinoma, no significant difference was found between EGFR mutation statuses in SUVmax or serum tumor markers (P>0.05 for all).

CONCLUSIONS

SUVmax and serum tumor markers show values in evaluating the histological types of suspicious lung cancers. When properly combined, the diagnostic efficiency can increase significantly.

Prediction of EGFR and KRAS mutation in non-small cell lung cancer using quantitative 18F FDG-PET/CT metrics

This study investigated the relationship between epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations in non-small-cell lung cancer (NSCLC) and quantitative FDG-PET/CT parameters including tumor heterogeneity. 131 patients with NSCLC underwent staging FDG-PET/CT followed by tumor resection and histopathological analysis that included testing for the EGFR and KRAS gene mutations. Patient and lesion characteristics, including smoking habits and FDG uptake parameters, were correlated to each gene mutation. Never-smoker (P < 0.001) or low pack-year smoking history (p = 0.002) and female gender (p = 0.047) were predictive factors for the presence of the EGFR mutations. Being a current or former smoker was a predictive factor for the KRAS mutations (p = 0.018). The maximum standardized uptake value (SUV_max) of FDG uptake in lung lesions was a predictive factor of the EGFR mutations (p = 0.029), while metabolic tumor volume and total lesion glycolysis were not predictive. Amongst several tumor heterogeneity metrics included in our analysis, inverse coefficient of variation (1/COV) was a predictive factor (p < 0.02) of EGFR mutations status, independent of metabolic tumor diameter. Multivariate analysis showed that being a never-smoker was the most significant factor (p < 0.001) for the EGFR mutations in lung cancer overall. The tumor heterogeneity metric 1/COV and SUV_max were both predictive for the EGFR mutations in NSCLC in a univariate analysis. Overall, smoking status was the most significant factor for the presence of the EGFR and KRAS mutations in lung cancer.

Correlation of EGFR or KRAS mutation status with 18F-FDG uptake on PET-CT scan in lung adenocarcinoma

Background

¹⁸F-fluoro-2-deoxy-glucose (¹⁸F-FDG) positron emission tomography (PET) is a functional imaging modality based on glucose metabolism. The correlation between EGFR or KRAS mutation status and the standardized uptake value (SUV) of ¹⁸F-FDG PET scanning has not been fully elucidated.

Methods

Correlations between EGFR or KRAS mutation status and clinicopathological factors including SUV_max were statistically analyzed in 734 surgically resected lung adenocarcinoma patients. Molecular causal relationships between EGFR or KRAS mutation status and glucose metabolism were then elucidated in 62 lung adenocarcinomas using cap analysis of gene expression (CAGE), a method to determine and quantify the transcription initiation activities of mRNA across the genome.

Results

EGFR and KRAS mutations were detected in 334 (46%) and 83 (11%) of the 734 lung adenocarcinomas, respectively. The remaining 317 (43%) patients had wild-type tumors for both genes. EGFR mutations were more frequent in tumors with lower SUV_max. In contrast, no relationship was noted between KRAS mutation status and SUV_max. CAGE revealed that 4 genes associated with glucose metabolism (GPI, G6PD, PKM2, and GAPDH) and 5 associated with the cell cycle (ANLN, PTTG1, CIT, KPNA2, and CDC25A) were positively correlated with SUV_max, although expression levels were lower in EGFR-mutated than in wild-type tumors. No similar relationships were noted with KRAS mutations.

Conclusions

EGFR-mutated adenocarcinomas are biologically indolent with potentially lower levels of glucose metabolism than wild-type tumors. Several genes associated with glucose metabolism and the cell cycle were specifically down-regulated in EGFR-mutated adenocarcinomas.

Relationship of Radiometabolic Biomarkers to KRAS Mutation Status and ALK Rearrangements in Cases of Lung Adenocarcinoma

Purpose Rapid diagnosis of genetic mutations is important for targeted therapies such as EGFR tyrosine kinase inhibitors. KRAS mutation and ALK rearrangement are also important in determining treatment. The purpose of our study was to evaluate the diagnostic value of 18F-FDG PET to predict KRAS mutation and ALK rearrangement in order to determine the frequency of these genetic markers in our lung adenocarcinoma cases and contribute to forthcoming meta-analysis studies. Methods A total of 218 patients with lung adenocarcinoma (EGFR analyzed) who were seen at our clinic between 2012 and 2014 were included in the study. The results of the 18 F-FDG-PET scans for each patient were retrospectively recorded with the associated medical documents. ALK rearrangements were analyzed in 166 of the 218 patients, while 50 of the 218 patients were analyzed for KRAS mutational status. SPSS 15.0 for Windows was used for statistical analysis. Results FDG avidity was higher in cases with KRAS mutations and ALK rearrangements than those without, but the difference was not significant. ALK rearrangements were more common in younger, female, and nonsmoking patients with lung adenocarcinoma. Conclusions The small numbers of KRAS mutations and ALK rearrangements are the limitation of this study for evaluation of diagnostic imaging. The frequency of these genetic alterations was as reported in the literature. We believe that our work will contribute to future meta-analysis.

Contribution of ¹⁸Fluorodeoxyglucose positron emission tomography uptake and TTF-1 expression in the evaluation of the EGFR mutation in patients with lung adenocarcinoma

AIM

The aim of this study is to evaluate the diagnostic value of PET-CT scan for the prediction of EGFR mutation status and the contribution of TTF-1 expression to PET-CT scan.

METHODS

We retrospectively studied 218 cases with a diagnosis of pulmonary adenocarcinoma between 2012-2014 which underwent EGFR analysis, TTF-1 and PET-CT before treatment.

RESULTS

The EGFR mutation was present in 28.9% (n= 63) of cases. TTF-1 positivity was 66.9% (n= 105). Standardized uptake value (SUV max) was 16.7 ± 6.8 in EGFR mutant type, 13.8 ± 7.6 in cases having no EGFR mutations. According to our evaluations, high SUVmax is positively correlated with EGFR mutation status. TTF-1 expression in multivariate analysis strengthens the accuracy of detecting an EGFR mutation.

CONCLUSION

PET-CT FDG uptake may, together with TTF-1 expression, help diagnosis in lung adenocarcinoma cases when evaluating for EGFR mutation status.

PET Imaging-Based Phenotyping as a Predictive Biomarker of Response to Tyrosine Kinase Inhibitor Therapy in Non-small Cell Lung Cancer: Are We There Yet?

The increased understanding of the molecular pathology of different malignancies, especially lung cancer, has directed investigational efforts to center on the identification of different molecular targets and on the development of targeted therapies against these targets. A good representative is the epidermal growth factor receptor (EGFR); a major driver of non-small cell lung cancer tumorigenesis. Today, tumor growth inhibition is possible after treating lung tumors expressing somatic mutations of the EGFR gene with tyrosine kinase inhibitors (TKI). This opened the doors to biomarker-directed precision or personalized treatments for lung cancer patients. The success of these targeted anticancer therapies depends in part on being able to identify biomarkers and their patho-molecular make-up in order to select patients that could respond to specific therapeutic agents. While the identification of reliable biomarkers is crucial to predict response to treatment before it begins, it is also essential to be able to monitor treatment early during therapy to avoid the toxicity and morbidity of futile treatment in non-responding patients. In this context, we share our perspective on the role of PET imaging-based phenotyping in the personalized care of lung cancer patients to non-invasively direct and monitor the treatment efficacy of TKIs in clinical practice.

Associations Between Somatic Mutations and Metabolic Imaging Phenotypes in Non-Small Cell Lung Cancer

PET-based radiomics have been used to noninvasively quantify the metabolic tumor phenotypes; however, little is known about the relationship between these phenotypes and underlying somatic mutations. This study assessed the association and predictive power of ¹⁸F-FDG PET-based radiomic features for somatic mutations in non-small cell lung cancer patients. Methods: Three hundred forty-eight non-small cell lung cancer patients underwent diagnostic ¹⁸F-FDG PET scans and were tested for genetic mutations. Thirteen percent (44/348) and 28% (96/348) of patients were found to harbor epidermal growth factor receptor (EGFR) or Kristen rat sarcoma viral (KRAS) mutations, respectively. We evaluated 21 imaging features: 19 independent radiomic features quantifying phenotypic traits and 2 conventional features (metabolic tumor volume and maximum SUV). The association between imaging features and mutation status (e.g., EGFR-positive [EGFR+] vs. EGFR-negative) was assessed using the Wilcoxon rank-sum test. The ability of each imaging feature to predict mutation status was evaluated by the area under the receiver operating curve (AUC) and its significance was compared with a random guess (AUC = 0.5) using the Noether test. All P values were corrected for multiple hypothesis testing by controlling the false-discovery rate (FDR_Wilcoxon, FDR_Noether) with a significance threshold of 10%. Results: Eight radiomic features and both conventional features were significantly associated with EGFR mutation status (FDR_Wilcoxon = 0.01-0.10). One radiomic feature (normalized inverse difference moment) outperformed all other features in predicting EGFR mutation status (EGFR+ vs. EGFR-negative, AUC = 0.67, FDR_Noether = 0.0032), as well as differentiating between KRAS-positive and EGFR+ (AUC = 0.65, FDR_Noether = 0.05). None of the features was associated with or predictive of KRAS mutation status (KRAS-positive vs. KRAS-negative, AUC = 0.50-0.54). Conclusion: Our results indicate that EGFR mutations may drive different metabolic tumor phenotypes that are captured in PET images, whereas KRAS-mutated tumors do not. This proof-of-concept study sheds light on genotype-phenotype interactions, using radiomics to capture and describe the phenotype, and may have potential for developing noninvasive imaging biomarkers for somatic mutations.

18F-FDG uptake for prediction EGFR mutation status in non-small cell lung cancer

Epidermal growth factor receptor (EGFR) mutations in non-small cell lung cancer (NSCLC) are a response to EGFR-tyrosine kinase inhibitor. However, a lack of sufficient tumor tissue has been a limitation for determining EGFR mutation status in clinical practice. The objective of this study was to predict EGFR mutation status in NSCLC patients based on a model including maximum standardized uptake value (SUVmax) and clinical features.We retrospectively reviewed NSCLC patients undergoing EGFR mutation testing and pretreatment positron emission tomography/computed tomography between March 2009 and December 2013. The relationships of EGFR mutations with both SUVmax and patient characteristics were evaluated, and a multivariate logistic regression analysis was performed. The model was assessed by area under the receiver-operating characteristic curve (AUC) and was prospectively validated during January to June 2014.Three hundred and sixteen patients meeting the criteria were enrolled for model construction. The SUVmax values were significantly lower for EGFR mutations (mean, 9.5 ± 5.74) than for EGFR wild-type (mean, 12.7 ± 6.43; P < 0.001). ROC curve analysis showed that the SUVmax cutoff point was 8.1, for which the AUC was 0.65 (95% confidence interval [CI], 0.60-0.72). In addition, multivariate analysis also showed that low SUVmax (≤8.1) was a predictor of EGFR mutations, for which the AUC was 0.77, combining nonsmoking history and primary tumor size (≤5 cm). Eighty-five patients were enrolled to validate the predictive model, and the overall accuracy, sensitivity, and specificity were 77.6%, 64.6% (95% CI 40.7-82.8), and 82.5% (95% CI 70.9-91.0), respectively.The specific FDG uptake value could be considered to effectively predict EGFR mutation status of NSCLC patients by considering smoking history and primary tumor size when genetic tests are not available.

FDG uptake in non-small cell lung cancer is not an independent predictor of EGFR or KRAS mutation status: a retrospective analysis of 206 patients

PURPOSE

Data in the literature regarding the use of F-FDG avidity of non-small cell lung cancer (NSCLC) as an imaging biomarker to predict the status of epidermal growth factor receptor (EGFR) mutation are conflicting. Association between KRAS mutation and FDG avidity of NSCLC on PET/CT is not well known. We assessed whether the EGFR or KRAS mutation status in NSCLC can be predicted by FDG avidity by performing several different subgroup analyses to better compare with various published results.

PATIENTS AND METHODS

After obtaining institutional review board approval, we enrolled patients (1) who had FDG PET/CT performed for staging of NSCLC, (2) with EGFR and KRAS mutational status of tumor identified, and (3) without uncontrolled diabetes. Univariate and multivariate regression analyses were performed to assess the relationship between the independent clinical variables (sex, age, smoking history, tumor histology, tumor size, stage, and SUV-derived variables) and the EGFR and KRAS mutation status. Separate analyses were performed for patients with adenocarcinomas.

RESULTS

There were 206 patients (age, 33-88 years; 148 male/58 female; 71 ever-smokers/135 never-smokers; 135 adenocarcinoma/71 squamous cell carcinoma; 22 stage I-II/184 stage III-IV; tumor size, 1.2-15.0 cm; SUVmax, 2.9-36.4; EGFR mutations present in 47; KRAS mutations present in 20). In multivariate analysis, sex, smoking history, histology, and tumor size were significantly associated with EGFR mutation but none of the SUV-derived variables was. Likewise, no correlation was found between the SUV-derived variables and KRAS mutation.

CONCLUSIONS

Our results suggest that FDG avidity of NSCLC has no significant clinical value in predicting the EGFR or KRAS mutation status.

(18)F-FDG PET/CT imaging in rectal cancer: relationship with the RAS mutational status

OBJECTIVE

Treating metastatic colorectal cancer with anti-EGFR monoclonal antibodies is recommended only for patients whose tumour does not harbour mutations of KRAS or NRAS. The aim of this study was to investigate the biology of rectal cancers and specifically to evaluate the relationship between fluorine-18 fludeoxyglucose ((18)F-FDG) positron emission tomography (PET) intensity and heterogeneity parameters and their mutational status.

METHODS

151 patients with newly diagnosed rectal cancer were included in this retrospective study. All patients underwent a baseline (18)F-FDG PET/CT within a median time interval of 27 days of tumour tissue sampling, which was performed before any treatment. Standardized uptake values (SUVs), volume-based parameters and texture analysis were studied. We retrospectively performed KRAS genotyping on codons 12, 13, 61, 117 and 146, NRAS genotyping on codons 12, 13 and 61 and BRAF on codon 600. Associations between PET/CT parameters and the mutational status were assessed using univariate and multivariate analysis.

RESULTS

83 (55%) patients had an RAS mutation: 74 KRAS and 9 NRAS, while 68 patients had no mutation (wild-type tumours). No patient had BRAF mutation. First-order features based on intensity histogram analysis were significantly associated with RAS mutations: maximum SUV (SUVmax) (p-value = 0.002), mean SUV (p-value = 0.006), skewness (p-value = 0.049), SUV standard deviation (p-value = 0.001) and SUV coefficient of variation (SUVcov) (p-value = 0.001). Both SUVcov and SUVmax showed an area under the curve of 0.65 with sensitivity of 56% and 69%, respectively, and specificity of 64% and 52%, respectively. None of the volume-based (metabolic tumour volume and total lesion glycolysis), nor local or regional textural features were associated with the presence of RAS mutations.

CONCLUSION

Although rectal cancers with KRAS or NRAS mutations display a significantly higher glucose metabolism than wild-type cancers, the accuracy of the currently proposed quantitative metrics extracted from (18)F-FDG PET/CT is not sufficiently high for playing a meaningful clinical role.

ADVANCES IN KNOWLEDGE

RAS-mutated rectal cancers have a significantly higher glucose metabolism. However, the accuracy of (18)F-FDG PET/CT quantitative metrics is not as such as the technique could play a clinical role.

Correlation between EGFR gene mutation, cytologic tumor markers, 18F-FDG uptake in non-small cell lung cancer

Background

EGFR mutation-induced cell proliferation causes changes in tumor biology and tumor metabolism, which may reflect tumor marker concentration and 18F-FDG uptake on PET/CT. Direct aspirates of primary lung tumors contain different concentrations of tumor markers than serum tumor markers, and may correlate better with EGFR mutation than serum tumor markers.

The purpose of this study is to investigate an association between cytologic tumor markers and FDG uptake with EGFR mutation status in non-small cell lung cancer (NSCLC).

Methods

We prospectively collected tumor aspirates of 61 patients who underwent EGFR mutation analysis. Serum and cytologic CYFRA 21-1, CEA, and SCCA levels were measured and correlated with EGFR gene mutations. FDG PET/CT was performed on 58 patients for NSCLC staging, and SUV was correlated with EGFR mutation status.

Results

Thirty (50 %) patients had EGFR mutation and 57 patients had adenocarcinoma subtype. Univariate analysis showed that female gender, never smoker, high levels of cytologic CYFRA 21-1 (c-CYFRA) and lower maximum standard uptake value (SUVmax) were correlated with EGFR mutations. ROC generated cut-off values of 20.8 ng/ml for c-CYFRA and SUVmax of 9.6 showed highest sensitivity for EGFR mutation detection. Multivariate analysis revealed that female gender [hazard ratio (HR): 18.15, p = 0.025], higher levels of c-CYFRA (HR: 7.58, and lower SUVmax (HR: 0.08, p = 0.005) were predictive of harboring EGFR mutation.

Conclusions

The cytologic tumor marker c-CYFRA was positively associated with EGFR mutations in NSCLC. EGFR mutation-positive NSCLCs have relatively lower glycolysis compared with NSCLCs without EGFR mutation.

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

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

Metabolic phenotype of stage IV lung adenocarcinoma: relationship with epidermal growth factor receptor mutation

PURPOSE

Epidermal growth factor receptor (EGFR) mutation status is important in treatment stratification of stage IV lung adenocarcinoma. We evaluated the relationship between the SUV max measured on PET/CT and EGFR mutations and the value of SUV max in predicting EGFR mutations.

PATIENTS AND METHODS

Seventy-one stage IV lung adenocarcinoma patients with verified EGFR mutations (48 EGFR mutant, 23 EGFR wild-type) having pretreatment PET/CT were retrospectively reviewed. SUV max values of the primary tumors (n = 71), nodal (n = 246), and distant metastases (n = 618) were compared between EGFR-mutant and EGFR wild-type adenocarcinoma by Mann-Whitney U test. The receiver operating characteristics curve and logistic regression were performed for factors, SUV max, age, sex, and smoking status. The significant predictors were assessed individually and in combination in discriminating EGFR mutation status. Statistical significance was assumed at P < 0.05 RESULTS: The metastases in EGFR-mutant adenocarcinoma had lower SUV max than EGFR wild-type adenocarcinoma (nodal SUV max 3.4 vs 5.5, distant metastasis SUV max 3.4 vs 4.7, respectively; both P < 0.001). No statistical significant difference was observed in the primary tumors SUV max between the 2 groups (SUV max 7.4 vs 8.1, P = 0.311). A receiver operating characteristics-derived SUV max less than or equal to 7.2 in metastasis could separate EGFR-mutant from EGFR wild-type adenocarcinoma (area under the curve, 0.71-0.74; P < 0.05). SUV max was a significant independent predictor, and when combined with age, sex, and smoking status, it is highly predictive of EGFR mutation status (area under the curve, 0.90).

CONCLUSIONS

Low SUV max in the metastasis favors the presence of EGFR mutations in stage IV lung adenocarcinoma, and SUV max is an independent predictor of EGFR mutations.

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

BACKGROUND

The epidermal growth factor receptor (EGFR) mutation status of lung cancer is important because it means that EGFR-tyrosine kinase inhibitor treatment is indicated. The purpose of this prospective study is to determine whether EGFR mutation status could be identified with reference to preoperative factors.

MATERIALS AND METHODS

One hundred-forty eight patients with lung cancer (111 adenocarcinomas, 25 squamous cell carcinomas and 12 other cell types) were enrolled in this study. The EGFR mutation status of each lung cancer was analyzed postoperatively.

RESULTS

There were 58 patients with mutant EGFR lung cancers (mutant LC) and 90 patients with wild-type EGFR lung cancers (wild-type LC). There were significant differences in gender, smoking status, maximum tumor diameter in chest CT, type of tumor shadow, clinical stage between mutant LC and wild-type LC. EGFR mutations were detected only in adenocarcinomas. Maximum standardized uptake value (SUVmax:3.66±4.53) in positron emission tomography-computed tomography of mutant LC was significantly lower than that (8.26±6.11) of wild-type LC (p<0.0001). Concerning type of tumor shadow, the percentage of mutant LC was 85.7% (6/7) in lung cancers with pure ground glass opacity (GGO), 65.3%(32/49) in lung cancers with mixed GGO and 21.7%(20/92) in lung cancers with solid shadow (p<0.0001). For the results of discriminant analysis, type of tumor shadow (p=0.00036) was most significantly associated with mutant EGFR. Tumor histology (p=0.0028), smoking status (p=0.0051) and maximum diameter of tumor shadow in chest CT (p=0.047) were also significantly associated with mutant EGFR. The accuracy for evaluating EGFR mutation status by discriminant analysis was 77.0% (114/148).

CONCLUSIONS

Mutant EGFR is significantly associated with lung cancer with pure or mixed GGO, adenocarcinoma, never-smoker, smaller tumor diameter in chest CT. Preoperatively, EGFR mutation status can be identified correctly in about 77 % of lung cancers.

Role of [¹⁸F]FDG PET in prediction of KRAS and EGFR mutation status in patients with advanced non-small-cell lung cancer

PURPOSE

The tumour molecular profile predicts the activity of epidermal growth factor receptor (EGFR) inhibitors in non-small-cell lung cancer (NSCLC). However, tissue availability and tumour heterogeneity limit its assessment. We evaluated whether [(18)F]FDG PET might help predict KRAS and EFGR mutation status in NSCLC.

METHODS

Between January 2005 and October 2011, 340 NSCLC patients were tested for KRAS and EGFR mutation status. We identified patients with stage III and IV disease who had undergone [(18)F]FDG PET/CT scanning for initial staging. SUVpeak, SUVmax and SUVmean of the single hottest tumour lesions were calculated, and their association with KRAS and EGFR mutation status was assessed. A receiver operator characteristic (ROC) curve analysis and a multivariate analysis (including SUVmean, gender, age and AJCC stage) were performed to identify the potential value of [(18)F]FDG PET/CT for predicting KRAS mutation.

RESULTS

From 102 patients staged using [(18)F]FDG PET/CT, 28 (27%) had KRAS mutation (KRAS+), 22 (22%) had EGFR mutation (EGFR+) and 52 (51%) had wild-type KRAS and EGFR profiles (WT). KRAS+ patients showed significantly higher [(18)F]FDG uptake than EGFR+ and WT patients (SUVmean 9.5, 5.7 and 6.6, respectively; p < 0.001). No significant differences were observed in [(18)F]FDG uptake between EGFR+ patients and WT patients. ROC curve analysis for KRAS mutation status discrimination yielded an area under the curve of 0.740 for SUVmean (p < 0.001). The multivariate analysis showed a sensitivity and specificity of 78.6% and 62.2%, respectively, and the AUC was 0.773.

CONCLUSION

NSCLC patients with tumours harbouring KRAS mutations showed significantly higher [(18)F]FDG uptake than WT patients, as assessed in terms of SUVpeak, SUVmax and SUVmean. A multivariate model based on age, gender, AJCC stage and SUVmean might be used as a predictive marker of KRAS mutation status in patients with stage III or IV NSCLC.

Value of ¹⁸F-FDG uptake on PET/CT and CEA level to predict epidermal growth factor receptor mutations in pulmonary adenocarcinoma

PURPOSE

The identification of the mutation status of the epidermal growth factor receptor (EGFR) is important for the optimization of treatment in patients with pulmonary adenocarcinoma. The acquisition of adequate tissues for EGFR mutational analysis is sometimes not feasible, especially in advanced-stage patients. The aim of this study was to predict EGFR mutation status in patients with pulmonary adenocarcinoma based on (18)F-fluorodeoxyglucose (FDG) uptake and imaging features in positron emission tomography/computed tomography (PET/CT), as well as on the serum carcinoembryonic antigen (CEA) level.

METHODS

We retrospectively reviewed 132 pulmonary adenocarcinoma patients who underwent EGFR mutation testing, pretreatment FDG PET/CT and serum CEA analysis. The associations between EGFR mutations and patient characteristics, maximal standard uptake value (SUVmax) of primary tumors, serum CEA level and CT imaging features were analyzed. Receiver-operating characteristic (ROC) curve analysis was performed to quantify the predictive value of these factors.

RESULTS

EGFR mutations were identified in 69 patients (52.2 %). Patients with SUVmax ≥6 (p = 0.002) and CEA level ≥5 (p = 0.013) were more likely to have EGFR mutations. The CT characteristics of larger tumors (≥3 cm) (p = 0.023) and tumors with a nonspiculated margin (p = 0.026) were also associated with EGFR mutations. Multivariate analysis showed that higher SUVmax and CEA level, never smoking and a nonspiculated tumor margin were the most significant predictors of EGFR mutation. The combined use of these four criteria yielded a higher area under the ROC curve (0.82), suggesting a good discrimination.

CONCLUSION

The combined evaluation of FDG uptake, CEA level, smoking status and tumor margins may be helpful in predicting EGFR mutation status in patients with pulmonary adenocarcinoma, especially when the tumor sample is inadequate for genetic analysis or genetic testing is not available. Further large-scale prospective studies are needed to validate these results.

Prognostic impact of 18F-FDG uptake on PET in non-small cell lung cancer patients with postoperative recurrence following platinum-based chemotherapy

BACKGROUND

Whether fluorine-18-fluorodeoxyglucose ((18)F-FDG) uptake within tumor cells differs between primary and recurrent lung cancers is unknown. The aim of this study was to investigate the prognostic significance of (18)F-FDG uptake by comparing that measured preoperatively at the primary site to that measured postoperatively at sites of non-small cell lung cancer (NSCLC) recurrence. Only patients with postoperative recurrences who received platinum-based chemotherapy as the initial treatment after recurrence were included in the study.

METHODS

Fifty-two patients underwent (18)F-FDG positron emission tomography (PET) examinations before thoracotomy and at the time of recurrence after curative surgery. All recurrences were treated with platinum-based chemotherapy.

RESULTS

(18)F-FDG uptake in the preoperative primary tumors was significantly higher than that in the recurrent tumors (p=0.028), demonstrating a statistically significant correlation (Pearson's correlation coefficient γ=0.482, p<0.001), especially in adenocarcinoma (AC) patients. Low (18)F-FDG avidity within the primary tumor significantly correlated with the presence of epidermal growth receptor factor (EGFR) mutations. (18)F-FDG uptake in the primary tumors was an independent prognostic factor for predicting outcome in NSCLC patients receiving platinum-based chemotherapy for the treatment of postoperative recurrence.

CONCLUSIONS

In NSCLC patients treated by chemotherapy for recurrence, preoperative measurements of (18)F-FDG uptake may be a more powerful surrogate marker for predicting outcome when measured preoperatively at the primary tumor site rather than postoperatively at sites of recurrence.

New positron emission tomography derived parameters as predictive factors for recurrence in resected stage I non-small cell lung cancer

BACKGROUND

The recurrence rate for stage I non-small cell lung cancer is high, with 20-40% of patients that relapse after surgery. The aim of this study was to evaluate new F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) derived parameters, such as standardized uptake value index (SUVindex), metabolic tumor volume (MTV) and total lesion glycolysis (TLG), as predictive factors for recurrence in resected stage I non-small cell lung cancer.

METHODS

We retrospectively reviewed 99 resected stage I non-small cell lung cancer patients that were grouped by SUVindex, TLG and MTV above or below their median value. Disease free survival was evaluated as primary end point.

RESULTS

The 5-year overall survival and the 5-year disease free survival rates were 62% and 73%, respectively. The median SUVindex, MTL and TLG were 2.73, 2.95 and 9.61, respectively. Patients with low SUVindex, MTV and TLG were more likely to have smaller tumors (p ≤ 0.001). Univariate analysis demonstrated that SUVindex (p = 0.027), MTV (p = 0.014) and TLG (p = 0.006) were significantly related to recurrence showing a better predictive performance than SUVmax (p = 0.031). The 5-year disease free survival rates in patients with low and high SUVindex, MTV and TLG were 84% and 59%, 86% and 62% and 88% and 60%, respectively. The multivariate analysis showed that only TLG was an independent prognostic factor (p = 0.014) with a hazard ratio of 4.782.

CONCLUSION

Of the three PET-derived parameters evaluated, TLG seems to be the most accurate in stratifying surgically treated stage I non-small cell lung cancer patients according to their risk of recurrence.

Metabolic and metastatic characteristics of ALK-rearranged lung adenocarcinoma on FDG PET/CT

INTRODUCTION

ALK rearrangement in lung cancer has been identified as a novel molecular target in lung adenocarcinoma. In this study, we evaluated metabolic and metastatic features of lung adenocarcinoma by using FDG PET/CT, with regard to specific genotypes of ALK and EGFR mutation.

METHODS

Patients with lung adenocarcinoma initially diagnosed and examined with FDG PET/CT and molecular genotyping with biopsy specimen, from September 2009 to September 2011, were selected retrospectively. ALK fluorescence in situ hybridization and EGFR mutations were tested. Maximum standardized uptake value (SUVmax) and metastatic characteristics on FDG PET/CT were analyzed with regard to ALK and EGFR status.

RESULTS

Of the 331 lung adenocarcinoma patients, 18 were ALK positive (ALK(+)), 156 were EGFR mutation positive (EGFR(+)), and 157 were wild type (WT) for both ALK and EGFR mutation. The ALK(+) tumor showed significantly higher SUVmax and more common metastasis to lymph nodes and distant organs than those of other genotypes in overall patients (P<0.01). In a subgroup analysis of advanced stage (stage IIIb and IV), ALK(+) lung cancer showed significantly higher SUVmax (P<0.05) than EGFR(+) tumors. In another subgroup analysis of size matched groups, ALK(+) tumors showed significant difference in SUVmax, lymph node and distant metastasis (P<0.01), particularly in the moderate-sized tumors (1.5-3cm).

CONCLUSION

ALK-rearranged lung adenocarcinoma represents higher glucose metabolism and more rapid metastasis to lymph nodes or distant sites compared with those with EGFR mutation and wild type, which suggests more aggressive features of ALK rearrangement.