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

Caicedo, Carlos; Velloso, María José García; Lozano, Marı́a D.; Labiano, Tania; Díaz, Carmen Vigil; López-Picazo, José M.; Gúrpide, Alfonso; Zulueta, Javier J.; Echevarría, J.A. Richter; Perez-Gracia, José Luis

doi:10.1007/s00259-014-2833-4

Cited by 78 publications

(69 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, we also found that the feature distributions between KRAS1 and KRASwere not significantly different for any of the PET features. However, these differences may also be attributed to the different cohort size because we investigated the association between PET imaging features and mutation status in 348 tumors, whereas the study by Caicedo et al (19) investigated 102 tumors.…”

Section: Discussionmentioning

confidence: 97%

“…Caicedo et al (19) investigated whether SUV measures, including maximum, peak, and average SUV, could predict EGFR and KRAS mutation status in 102 patients with NSCLC. Unlike our results, they found that KRAS1 tumors had significantly higher values in SUV measures than both EGFR mutants and KRAS-EGFR WTs.…”

Section: Discussionmentioning

confidence: 99%

“…In addition, increased glucose transport and glycolysis have been observed in KRAS-mutated colorectal and pancreatic cancer cell lines (16,17). Thus, previous studies have investigated the associations between these mutations and SUV measures from PET images; however, there have been conflicting findings (18)(19)(20)(21)(22). These inconsistent reports may be due to the fact that simple SUV measures fail to capture the spatial relationships between image voxels, which may be more informative of the biology of these mutations and describe the degree of tumor heterogeneity (23,24).…”

mentioning

confidence: 99%

See 2 more Smart Citations

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

et al. 2016

View full text Add to dashboard Cite

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 18 F-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 18 F-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 [EGFR1] 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 5 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 5 0.01-0.10). One radiomic feature (normalized inverse difference moment) outperformed all other features in predicting EGFR mutation status (EGFR1 vs. EGFR-negative, AUC 5 0.67, FDR Noether 5 0.0032), as well as differentiating between KRAS-positive and EGFR1 (AUC 5 0.65, FDR Noether 5 0.05). None of the features was associated with or predictive of KRAS mutation status (KRAS-positive vs. KRAS-negative, AUC 5 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.

show abstract

Section: Discussionmentioning

confidence: 97%

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

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

et al. 2016

View full text Add to dashboard Cite

show abstract

“…Alternative noninvasive strategies, such as PET/CT, for predicting the mutation profile would therefore be of great value. Several studies have demonstrated that PET/CT has the potential to predict the phenotype of a tumor (8)(9)(10)(11), such as the KRAS status in colorectal cancer (9,10) and the lactate dehydrogenase A expression level in lung adenocarcinoma (12), the latter being useful for treatment strategies involving lactate dehydrogenase A inhibitor. 18 F-FDG PET/CT has been widely used for diagnosis, monitoring of treatment response, surveillance, and prognostication in a variety of cancers (13)(14)(15).…”

mentioning

confidence: 99%

Relationship Between ¹⁸F-FDG PET/CT Findings and HER2 Expression in Gastric Cancer

Chen

Zhou

et al. 2016

J Nucl Med

View full text Add to dashboard Cite

18 F-FDG PET has been widely used in the management of malignant tumors. In gastric cancer, the status of human epidermal growth factor receptor 2 (HER2) predicts the response to anti-HER2 antibody therapy, and testing of HER2 expression is now routine in the management of gastric cancer patients. However, to date, the relationship between 18 F-FDG uptake and HER2 expression has not, to our knowledge, been investigated. In this study, we aimed to investigate whether HER2 expression is associated with 18 F-FDG uptake and whether 18 F-FDG PET/CT can be used to predict the HER2 status of gastric cancer. Methods: A retrospective analysis was performed on 64 gastric cancer patients who had undergone 18 F-FDG PET/CT before surgical resection. Tumor SUV max was calculated from the level of 18 F-FDG uptake. Results: No significant correlation was found between SUV max and HER2 expression in gastric cancer. However, when signet-ring cell carcinoma was excluded, SUV max was significantly higher in the HER2-negative group than in the HER2-positive group (8.619 ± 5.878 vs. 3.789 ± 2.613, respectively; P 5 0.021). Multivariate analysis indicated that SUV max and tumor differentiation remained significantly associated with HER2 expression (P 5 0.048 and P 5 0.028, respectively). HER2 expression was predicted with an accuracy of 64.4% when an SUV max cutoff of 6.2 was used. Conclusion: 18 F-FDG uptake by gastric cancer is associated with HER2 expression. 18 F-FDG PET/CT may be useful for predicting the HER2 status of gastric cancer and for determining the therapeutic strategy.

show abstract

“…The study by Kawada et al (8) was the first clinical study showing the causal relationship between KRAS mutations and 18 F-FDG accumulation using 18 F-FDG PET/CT scans in a variety of cancers. There is also emerging evidence from other groups that 18 F-FDG accumulation reflects KRAS mutational status of CRC and non-small cell lung cancer (11)(12)(13). However, the clinical utility of these findings has been limited because endoscopic biopsy for KRAS mutational testing is safe and feasible only in primary CRC.…”

mentioning

confidence: 99%

Relationship Between ¹⁸F-FDG PET/CT Scans and KRAS Mutations in Metastatic Colorectal Cancer

et al. 2015

View full text Add to dashboard Cite

Several studies have shown that KRAS mutations in colorectal cancer (CRC) result in the lack of response to anti-epidermal growth factor receptor-based therapy; thus, KRAS mutational testing has been incorporated into routine clinical practice. However, 1 limitation of this test is the heterogeneity of KRAS status, which can be either intratumoral heterogeneity within an individual primary CRC or discordant KRAS status between a primary CRC and its corresponding metastases. We previously reported that 18 F-FDG accumulation was significantly higher in primary CRCs with mutated KRAS than in those with wild-type KRAS. However, the clinical utility of the previous report has been limited because endoscopic biopsy for testing KRAS status is safe and feasible only in primary CRC. The purpose of this study was to investigate whether KRAS status is associated with 18 F-FDG accumulation in metastatic CRC and whether 18 F-FDG PET/CT scans can be used to predict the KRAS status of metastatic CRC. Methods: A retrospective analysis was performed on 55 metastatic CRC tumors that were identified by 18 F-FDG PET/CT before surgical resection. Maximum standardized uptake value (SUV max ) of the respective metastatic tumor was calculated from 18 F-FDG accumulation. Results: From the analysis with the 55 tumors, no significant correlation was found between SUV max and KRAS status. We next analyzed only tumors larger than 10 mm to minimize the bias of partial-volume effect and found that SUV max was significantly higher in the KRAS-mutated group than in the wild-type group (8.3 ± 4.1 vs. 5.7 ± 2.4, respectively; P 5 0.03). Multivariate analysis indicated that SUV max remained significantly associated with KRAS mutations (P 5 0.04). KRAS status could be predicted with an accuracy of 71.4% when an SUV max cutoff value of 6.0 was used. Conclusion: 18 F-FDG accumulation into metastatic CRC was associated with KRAS status. 18 F-FDG PET/ CT scans may be useful for predicting the KRAS status of metastatic CRC and help in determining the therapeutic strategies against metastatic CRC.

show abstract

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

Cited by 78 publications

References 35 publications

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

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

Relationship Between ¹⁸F-FDG PET/CT Findings and HER2 Expression in Gastric Cancer

Relationship Between ¹⁸F-FDG PET/CT Scans and KRAS Mutations in Metastatic Colorectal Cancer

Contact Info

Product

Resources

About

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

Cited by 78 publications

References 35 publications

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

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

Relationship Between 18F-FDG PET/CT Findings and HER2 Expression in Gastric Cancer

Relationship Between 18F-FDG PET/CT Scans and KRAS Mutations in Metastatic Colorectal Cancer

Contact Info

Product

Resources

About

Relationship Between ¹⁸F-FDG PET/CT Findings and HER2 Expression in Gastric Cancer

Relationship Between ¹⁸F-FDG PET/CT Scans and KRAS Mutations in Metastatic Colorectal Cancer