Meta-analysis of Epidermal Growth Factor Receptor and KRAS Gene Status between Primary and Corresponding Metastatic Tumours of Non-small Cell Lung Cancer

Wang, S.; Wang, Z.

doi:10.1016/j.clon.2014.09.014

Cited by 28 publications

(22 citation statements)

References 37 publications

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“…In another study, Westood and colleagues analyzed 12 databases and verified EGFR mutation status in NSCLCs (Westwood et al, 2014). Consistent with Wang and Wang’s (2015) observation they also did not find any greater accuracy for EGFR mutation as a diagnostic measure. However, some positive correlations of EGFR with breast cancer metastasis are evident.…”

Section: Approaches Used To Detect Metastatic Lesions (On a Clinicsupporting

confidence: 80%

“…In a recent study, Wang and Wang systematically performed a meta-analysis to define EGFR mutations in primary and matching metastatic nonsmall cell lung cancer (NSCLC) and found that EGFR mutations are present both in primary and metastatic NSCLC lesion, and therefore routine analysis of EGFR is not recommended in primary and metastatic tumors (Wang & Wang, 2015). In another study, Westood and colleagues analyzed 12 databases and verified EGFR mutation status in NSCLCs (Westwood et al, 2014).…”

Section: Approaches Used To Detect Metastatic Lesions (On a Clinicmentioning

confidence: 99%

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Detecting Tumor Metastases

Menezes

Das

Minn

et al. 2016

Advances in Cancer Research

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Metastasis is the complex process by which primary tumor cells migrate and establish secondary tumors in an adjacent or distant location in the body. Early detection of metastatic disease and effective therapeutic options for targeting these detected metastases remain impediments to effectively treating patients with advanced cancers. If metastatic lesions are identified early, patients might maximally benefit from effective early therapeutic interventions. Further, monitoring patients whose primary tumors are effectively treated for potential metastatic disease onset is also highly valuable. Finally, patients with metastatic disease can be monitored for efficacy of specific therapeutic interventions through effective metastatic detection techniques. Thus, being able to detect and visualize metastatic lesions is key and provides potential to greatly improve overall patient outcomes. In order to achieve these objectives, researchers have endeavored to mechanistically define the steps involved in the metastatic process as well as ways to effectively detect metastatic progression. We presently overview various preclinical and clinical in vitro and in vivo assays developed to more efficiently detect tumor metastases, which provides the foundation for developing more effective therapies for this invariably fatal component of the cancerous process.

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Section: Approaches Used To Detect Metastatic Lesions (On a Clinicsupporting

confidence: 80%

Section: Approaches Used To Detect Metastatic Lesions (On a Clinicmentioning

confidence: 99%

Detecting Tumor Metastases

Menezes

Das

Minn

et al. 2016

Advances in Cancer Research

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show abstract

“…Indeed, cancer invasiveness is stimulated by numerous mechanisms, including activating EGFR mutations [33]. Furthermore, a recent meta-analysis by Wang and Wang [34] exploring the correlation of EGFR status between primary tumors and metastases revealed that EGFR mutations should occur before metastasis, suggesting that EGFR mutations play a role in this process.…”

Section: Discussionmentioning

confidence: 99%

EGFR and KRAS Mutations Predict the Incidence and Outcome of Brain Metastases in Non-Small Cell Lung Cancer

Tomasini

Serdjebi

Khobta

et al. 2016

IJMS

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Background: Lung cancer is the leading cause of brain metastases (BM). The identification of driver oncogenes and matched targeted therapies has improved outcome in non-small cell lung cancer (NSCLC) patients; however, a better understanding of BM molecular biology is needed to further drive the process in this field. Methods: In this observational study, stage IV NSCLC patients tested for EGFR and KRAS mutations were selected, and BM incidence, recurrence and patients’ outcome were assessed. Results: A total of 144 patients (142 Caucasian and two Asian) were selected, including 11.27% with EGFR-mutant and 33.10% with KRAS-mutant tumors, and 57.04% patients had developed BM. BM incidence was more frequent in patients with EGFR mutation according to multivariate analyses (MVA) (Odds ratio OR = 8.745 [1.743–43.881], p = 0.008). Among patients with treated BM, recurrence after local treatment was less frequent in patients with KRAS mutation (OR = 0.234 [0.078–0.699], p = 0.009). Among patients with untreated BM, overall survival (OS) was shorter for patients with KRAS mutation according to univariate analysis (OR = 7.130 [1.240–41.012], p = 0.028), but not MVA. Conclusions: EGFR and KRAS mutations have a predictive role on BM incidence, recurrence and outcome in Caucasian NSCLC patients. These results may impact the routine management of disease in these patients. Further studies are required to assess the influence of other biomarkers on NSCLC BM.

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“…Non‐small cell lung cancer (NSCLC) is reported to account for up to 90% of all lung cancer cases . Mutation in the EGFR gene is the most common genetic event in NSCLC, especially in adenocarcinoma (AC) . Thus, EGFR is now one of the main targets of genotype‐directed therapy for NSCLC.…”

Section: Introductionmentioning

confidence: 99%

“…2 Mutation in the EGFR gene is the most common genetic event in NSCLC, especially in adenocarcinoma (AC). 3 Thus, EGFR is now one of the main targets of genotype-directed therapy for NSCLC. Phase III trials have shown that tyrosine kinase inhibitors (TKIs) targeting EGFR, such as gefitinib and erlotinib, could improve the clinical outcomes of patients with advanced EGFR-mutated NSCLC.…”

Section: Introductionmentioning

confidence: 99%

Development and validation of a model to predict tyrosine kinase inhibitor‐sensitive EGFR mutations of non‐small cell lung cancer based on multi‐institutional data

Chang

Liu

et al. 2018

Thoracic Cancer

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BackgroundNon‐small cell lung cancer (NSCLC) with different EGFR mutation types shows distinct sensitivity to tyrosine kinase inhibitors (TKIs). This study developed a patho‐clinical profile‐based prediction model of TKI‐sensitive EGFR mutations.MethodsThe records of 1121 Chinese patients diagnosed with NSCLC from November 2008 to October 2014 (the development set) were reviewed. Multivariate logistic regression was conducted to identify any association between potential predictors and the classic sensitive EGFR mutations (exon 19 deletion and exon 21 L858R point mutation). A prediction index was created by assigning weighted scores to each factor proportional to a regression coefficient. Validation was made in an independent cohort consisting of 864 patients who were consecutively enrolled between November 2014 and January 2017 (the validation set).ResultsSeven independent predictors were identified: gender (female vs. male), adenocarcinoma (yes vs. no), smoking history (no vs. yes), N stage (N+ vs. N0), M stage (M1 vs. M0), brain metastasis (yes vs. no), and elevated Cyfra 21‐1 (no vs. yes). Each was assigned a number of points. In the validation set, the area under curve of the prediction index appeared as 0.698 (95% confidence interval 0.663–0.733). The sensitivity, specificity, positive and negative predictive values, and concordance were 95.0%, 32.3%, 61.4%, 85.1%, and 65.6%, respectively.ConclusionWe developed a patho‐clinical profile‐based model for predicting TKI‐sensitive EGFR mutations. Our model may represent a noninvasive, economical choice for clinicians to inform TKI therapy.

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Meta-analysis of Epidermal Growth Factor Receptor and KRAS Gene Status between Primary and Corresponding Metastatic Tumours of Non-small Cell Lung Cancer

Cited by 28 publications

References 37 publications

Detecting Tumor Metastases

Detecting Tumor Metastases

EGFR and KRAS Mutations Predict the Incidence and Outcome of Brain Metastases in Non-Small Cell Lung Cancer

Development and validation of a model to predict tyrosine kinase inhibitor‐sensitive EGFR mutations of non‐small cell lung cancer based on multi‐institutional data

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