Literature DB >> 21811765

Correlation between computed tomography findings and epidermal growth factor receptor and KRAS gene mutations in patients with pulmonary adenocarcinoma.

Masayuki Sugano1, Kimihiro Shimizu, Tetsuhiro Nakano, Seiichi Kakegawa, Yohei Miyamae, Kyoichi Kaira, Takuya Araki, Mitsuhiro Kamiyoshihara, Osamu Kawashima, Izumi Takeyoshi.   

Abstract

We examined the correlation between computed tomography (CT) findings and the incidence of epidermal growth factor receptor (EGFR) and KRAS mutations in lung adenocarcinoma. We analyzed the tumors of 136 patients with surgically resected primary lung adenocarcinoma. CT scans were evaluated for the presence of ground grass opacity (GGO), spiculation and the maximum diameter of the tumor was measured. SMart Amplification Process (ver. 2) was used to detect the presence of EGFR and KRAS mutations. EGFR and KRAS mutations were found in 56 (41.1%) and 25 (18.4%) of the 136 cases, respectively. Although no significant association was found between GGO and EGFR mutations (p=0.07), the EGFR mutation occurred more frequently in male patients with GGO than in those without GGO (p=0.04). The KRAS mutation occurred more frequently in patients whose tumor diameter was ≥ 31 mm than in those whose tumor diameter was <30 mm (p=0.003). Evaluation of CT findings may be helpful for determining the presence of EGFR and KRAS mutations, particularly when it is not possible to obtain a tumor specimen.

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Year:  2011        PMID: 21811765     DOI: 10.3892/or.2011.1412

Source DB:  PubMed          Journal:  Oncol Rep        ISSN: 1021-335X            Impact factor:   3.906


  21 in total

1.  Association Between Computed Tomographic Features and Kirsten Rat Sarcoma Viral Oncogene Mutations in Patients With Stage I Lung Adenocarcinoma and Their Prognostic Value.

Authors:  Hua Wang; Matthew B Schabath; Ying Liu; Olya Stringfield; Yoganand Balagurunathan; John J Heine; Steven A Eschrich; Zhaoxiang Ye; Robert J Gillies
Journal:  Clin Lung Cancer       Date:  2015-11-12       Impact factor: 4.785

2.  Proposals for revisions of the classification of lung cancers with multiple pulmonary sites: the radiologist's, thoracic surgeon's and oncologist's point of view.

Authors:  Stefania Rizzo; Francesco Petrella; Antonio Passaro; Filippo de Marinis; Massimo Bellomi
Journal:  J Thorac Dis       Date:  2016-08       Impact factor: 2.895

3.  The natural course of incidentally detected, small, subsolid lung nodules-is follow-up needed beyond current guideline recommendations?

Authors:  Benedikt H Heidinger; Mario Silva; Constance de Margerie-Mellon; Paul A VanderLaan; Alexander A Bankier
Journal:  Transl Lung Cancer Res       Date:  2019-12

Review 4.  Pulmonary ground-glass opacity: computed tomography features, histopathology and molecular pathology.

Authors:  Jian-Wei Gao; Stefania Rizzo; Li-Hong Ma; Xiang-Yu Qiu; Arne Warth; Nobuhiko Seki; Mizue Hasegawa; Jia-Wei Zou; Qian Li; Marco Femia; Tang-Feng Lv; Yong Song
Journal:  Transl Lung Cancer Res       Date:  2017-02

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

Authors:  Aiqi Shi; Jianling Wang; Yuzhu Wang; Guorong Guo; Chouchou Fan; Jiangyan Liu
Journal:  Ann Nucl Med       Date:  2022-01-27       Impact factor: 2.668

6.  CT Features Associated with Epidermal Growth Factor Receptor Mutation Status in Patients with Lung Adenocarcinoma.

Authors:  Ying Liu; Jongphil Kim; Fangyuan Qu; Shichang Liu; Hua Wang; Yoganand Balagurunathan; Zhaoxiang Ye; Robert J Gillies
Journal:  Radiology       Date:  2016-03-03       Impact factor: 11.105

7.  Predicting EGFR mutation status in lung cancer:Proposal for a scoring model using imaging and demographic characteristics.

Authors:  Ali Sabri; Madiha Batool; Zhaolin Xu; Drew Bethune; Mohamed Abdolell; Daria Manos
Journal:  Eur Radiol       Date:  2016-03-30       Impact factor: 5.315

8.  Establishment and Evaluation of EGFR Mutation Prediction Model Based on Tumor Markers and CT Features in NSCLC.

Authors:  Hao Zhang; Meng He; Ren'an Wan; Liangming Zhu; Xiangpeng Chu
Journal:  J Healthc Eng       Date:  2022-04-05       Impact factor: 2.682

9.  Computed tomography and clinical features associated with epidermal growth factor receptor mutation status in stage I/II lung adenocarcinoma.

Authors:  Jiawei Zou; Tangfeng Lv; Suhua Zhu; Zhenfeng Lu; Qin Shen; Leilei Xia; Jie Wu; Yong Song; Hongbing Liu
Journal:  Thorac Cancer       Date:  2017-04-06       Impact factor: 3.500

10.  Computer-Aided Nodule Assessment and Risk Yield (CANARY) may facilitate non-invasive prediction of EGFR mutation status in lung adenocarcinomas.

Authors:  Ryan Clay; Benjamin R Kipp; Sarah Jenkins; Ron A Karwoski; Fabien Maldonado; Srinivasan Rajagopalan; Jesse S Voss; Brian J Bartholmai; Marie Christine Aubry; Tobias Peikert
Journal:  Sci Rep       Date:  2017-12-15       Impact factor: 4.379

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