Treatment modes for EGFR mutations in patients with brain metastases from non-small cell lung cancer: controversy, causes, and solutions

Zhuang, Hong; Shi, Siyu; Chang, Joe Y.

doi:10.21037/tlcr.2019.07.03

Cited by 11 publications

(7 citation statements)

References 51 publications

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“…Platinum compounds (cisplatin and carboplatin) and pemetrexed, alone or in combination (etoposide, paclitaxel, and radiotherapy) are the most commonly used chemotherapy regimens against BMs from NSCLC (Mehta et al, 2010 ; Barlesi et al, 2011 ; Bailon et al, 2012 ; Shi et al, 2017 ; Yousefi et al, 2017 ; Franchino et al, 2018 ). Since about 33% of patients with non-small cell lung cancer (NSCLC) and EGFR mutations develop BMs, different generations of tyrosine kinase inhibitors (TKIs) were commonly used to target BMs (Burel-Vandenbos et al, 2013 ; Sekine and Satoh, 2017 ; Zhuang et al, 2019 ). Gefitinib is the most typical first-generation TKI and AZD3759 is characterized by its strong ability to effectively penetrate the BBB (Tan et al, 2017 ; Hochmair, 2018 ).…”

Section: Resultsmentioning

confidence: 99%

Proteomic Reveals Reasons for Acquired Drug Resistance in Lung Cancer Derived Brain Metastasis Based on a Newly Established Multi-Organ Microfluidic Chip Model

Wang

Duan

et al. 2020

Front. Bioeng. Biotechnol.

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Anti-tumor drugs can effectively shrink the lesions of primary lung cancer; however, it has limited therapeutic effect on patients with brain metastasis (BM). A BM preclinical model based on a multi-organ microfluidic chip has been established proficiently in our previous work. In this study, the BM subpopulation (PC9-Br) derived from the parental PC9 cell line was isolated from the chip model and found to develop obvious resistance to antineoplastic drugs including chemotherapeutic agents (cisplatin, carboplatin, pemetrexed) and tyrosine kinase inhibitors (TKIs) which target epidermal growth factor receptor (EGFR); this suggested that the acquisition of drug-resistance by brain metastatic cells was attributable to the intrinsic changes in PC9-Br. Hence, we performed proteomic and revealed a greatly altered spectrum of BM protein expression compared with primary lung cancer cells. We identified the hyperactive glutathione (GSH) metabolism pathway with the overexpression of various GSH metabolism-related enzymes (GPX4, RRM2, GCLC, GPX1, GSTM4, GSTM1). Aldehyde dehydrogenases (ALDH1A1, ALDH3A1) were also found to be upregulated in BM. What's more, loss of EGFR and phosphorylated EGFR in PC9-Br gave reasons for the TKIs resistance. Collectively, our findings indicated potential mechanisms for the acquirement of drug resistance occurred in BM, providing new strategies to overcome therapeutic resistance in lung cancer BM.

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Section: Resultsmentioning

confidence: 99%

Proteomic Reveals Reasons for Acquired Drug Resistance in Lung Cancer Derived Brain Metastasis Based on a Newly Established Multi-Organ Microfluidic Chip Model

Wang

Duan

et al. 2020

Front. Bioeng. Biotechnol.

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“…Emerging evidence has revealed that patients with BM could benefit from targeted therapy and immunotherapy. 8 , 9 Therefore, we identified patient subgroups stratified by survival outcomes based on the patient’s intrinsic characteristics that were associated with the combination of treatment strategies. Patients wild type for mutations aside from radiotherapy underwent treatment with mono-chemotherapy according to guidelines for elderly people.…”

Section: Discussionmentioning

confidence: 99%

Estimating Survival in Patients with Non-Small-Cell Lung Cancer and Brain Metastases: A Verification of the Graded Prognostic Assessment for Lung Cancer Using Molecular Markers (Lung-molGPA)

Li¹,

Wang²,

Zhai³

et al. 2021

OTT

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A new tool based on clinical characteristics and molecular factors (Lung-molGPA) was developed to predict the survival of patients with non-small-cell lung cancer but was has not been validated. This study aims to validate the feasibility of the Lung-molGPA in NSCLC. Patients and Methods: Patients diagnosed NSCLC between Feb 2012 and July 2018 were retrospectively reviewed and scored using the Lung-molGPA tool to compare clinical outcomes. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated by Cox regression analyses. Results: A total of 618 patients (524 adenocarcinoma [ADC], 94 non-adenocarcinoma [non-ADC]) were collected. For all patients, the median survival time (MST) was 33.0 months (33.6 and 28 months in the ADC and non-ADC groups, respectively; p = 0.21). In the ADC group, the MST for patients with a Lung-molGPA score of 3.5 to 4 was more than 4 years, while the MST was only 25 months in patients scoring 0-1, 30.0 months in patients scoring 1.5-2, and 35.0 months for scores of 2.5-3 (p = 0.048). For the non-ADC group, the MST for scores 0-1, 1.5-2, 2.5-3, and 3.5-4 were 12.0, 20.2, 29.0, and 33.0 months, respectively (p = 0.017). Conclusion:Our findings provided evidence validating the Lung-molGPA score as a useful tool to determine treatment strategies and to predict prognosis. The model is still exploratory and needs to be evaluated further in combination with additional prognostic markers.

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“…This goal may be achieved with the introduction of novel targeted systemic agents including tyrosine kinase inhibitors and checkpoint inhibitors. However, these agents are mainly used for patients with non-small cell lung cancer (NSCLC) rather than for patients with SCLC (10)(11)(12)(13)(14). For patients with cerebral metastases from SCLC, WBI alone still is the most frequently used type of treatment, particularly for elderly patients who may not be able to tolerate novel systemic agents that can cause considerable side effects including severe inflammatory reactions (5).…”

Section: Discussionmentioning

confidence: 99%

Development of a multivariable prediction model to estimate the remaining lifespan of elderly patients with cerebral metastases from small-cell lung cancer

Rades

Nguyen

Schild

2020

Transl Lung Cancer Res

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Background: Prognostic tools estimating survival of elderly patients with cerebral metastases from smallcell lung cancer (SCLC) improve treatment personalization. A specific tool for these patients was developed and compared to existing instruments.Methods: One-hundred-and-forty elderly patients (≥65 years) receiving whole-brain irradiation (WBI) for cerebral metastases from SCLC were retrospectively evaluated. WBI-program, age, gender, Karnofsky performance score, number of cerebral lesions, extracerebral metastases, and interval between SCLCdiagnosis and WBI were investigated. Characteristics significantly associated with survival in the multivariate analysis were used for the tool. Scoring points were calculated by dividing 6-month survival rates (%) by 10 and added for patient scores. The tool was compared to existing diagnosis-specific instruments including updated diagnosis-specific graded prognostic assessment (DS-GPA), Rades-SCLC and WBRT-30-SCLC.Results: In the multivariate analysis, KPS (P<0.001), number of cerebral lesions (P=0.013) and extracerebral metastases (P=0.049) were significantly associated with survival. Patient scores of 2 (n=37), 5 (n=69), 8 (n=20) and 11 (n=14) points were obtained; 6-month survival rates were 0%, 9%, 50% and 79% (P<0.001). The positive predictive value (PPV) of the worst group (2 points) to identify patients dying ≤6 months was 100%; PPVs of updated DS-GPA, Rades-SCLC and WBRT-30-SCLC were 94%, 100% and 94%. PPV of the best group (11 points) to identify patients surviving ≥6 months was 79%; PPVs of updated DS-GPA, Rades-SCLC and WBRT-30-SCLC were 86%, 79% and 100%. Conclusions:The most precise instruments were the new tool and Rades-SCLC for identification of patients dying ≤6 months, and the WBRT-30-SCLC to identify patients surviving ≥6 months.

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Treatment modes for EGFR mutations in patients with brain metastases from non-small cell lung cancer: controversy, causes, and solutions

Cited by 11 publications

References 51 publications

Proteomic Reveals Reasons for Acquired Drug Resistance in Lung Cancer Derived Brain Metastasis Based on a Newly Established Multi-Organ Microfluidic Chip Model

Proteomic Reveals Reasons for Acquired Drug Resistance in Lung Cancer Derived Brain Metastasis Based on a Newly Established Multi-Organ Microfluidic Chip Model

Estimating Survival in Patients with Non-Small-Cell Lung Cancer and Brain Metastases: A Verification of the Graded Prognostic Assessment for Lung Cancer Using Molecular Markers (Lung-molGPA)

Development of a multivariable prediction model to estimate the remaining lifespan of elderly patients with cerebral metastases from small-cell lung cancer

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