Targeted sequencing and intracranial outcomes of patients with lung adenocarcinoma brain metastases treated with radiotherapy

Factors associated with the local control of brain metastases: a systematic search and machine learning application

BACKGROUND

Enhancing Local Control (LC) of brain metastases is pivotal for improving overall survival, which makes the prediction of local treatment failure a crucial aspect of treatment planning. Understanding the factors that influence LC of brain metastases is imperative for optimizing treatment strategies and subsequently extending overall survival. Machine learning algorithms may help to identify factors that predict outcomes.

METHODS

This paper systematically reviews these factors associated with LC to select candidate predictor features for a practical application of predictive modeling. A systematic literature search was conducted to identify studies in which the LC of brain metastases is assessed for adult patients. EMBASE, PubMed, Web-of-Science, and the Cochrane Database were searched up to December 24, 2020. All studies investigating the LC of brain metastases as one of the endpoints were included, regardless of primary tumor type or treatment type. We first grouped studies based on primary tumor types resulting in lung, breast, and melanoma groups. Studies that did not focus on a specific primary cancer type were grouped based on treatment types resulting in surgery, SRT, and whole-brain radiotherapy groups. For each group, significant factors associated with LC were identified and discussed. As a second project, we assessed the practical importance of selected features in predicting LC after Stereotactic Radiotherapy (SRT) with a Random Forest machine learning model. Accuracy and Area Under the Curve (AUC) of the Random Forest model, trained with the list of factors that were found to be associated with LC for the SRT treatment group, were reported.

RESULTS

The systematic literature search identified 6270 unique records. After screening titles and abstracts, 410 full texts were considered, and ultimately 159 studies were included for review. Most of the studies focused on the LC of the brain metastases for a specific primary tumor type or after a specific treatment type. Higher SRT radiation dose was found to be associated with better LC in lung cancer, breast cancer, and melanoma groups. Also, a higher dose was associated with better LC in the SRT group, while higher tumor volume was associated with worse LC in this group. The Random Forest model predicted the LC of brain metastases with an accuracy of 80% and an AUC of 0.84.

CONCLUSION

This paper thoroughly examines factors associated with LC in brain metastases and highlights the translational value of our findings for selecting variables to predict LC in a sample of patients who underwent SRT. The prediction model holds great promise for clinicians, offering a valuable tool to predict personalized treatment outcomes and foresee the impact of changes in treatment characteristics such as radiation dose.

Non-small cell lung cancer with MET amplification: review of epidemiology, associated disease characteristics, testing procedures, burden, and treatments

Introduction

Mesenchymal-epidermal transition factor gene amplification (METamp) is being investigated as a therapeutic target in advanced non-small cell lung cancer (NSCLC). We reviewed the epidemiology and disease characteristics associated with primary and secondary METamp, as well as the testing procedures used to identify METamp, in advanced NSCLC. Economic and humanistic burdens, and the practice patterns and treatments under investigation for METamp were also examined.

Methods

Embase and Medline (via ProQuest), ClinicalTrials.gov, and Cochrane Controlled Register of Trials (2015-2022) were systematically searched. Conference abstracts were searched via Embase and conference proceedings websites (2020-2022). The review focused on evidence from the United States; global evidence was included for identified evidence gaps.

Results

The median rate of primary METamp in NSCLC across the references was 4.8% (n=4 studies) and of secondary METamp (epidermal growth factor receptor [EGFR]-mutant NSCLC) was 15% (n=10). Next-generation sequencing (NGS; n=12) and/or fluorescence in situ hybridization (FISH; n=11) were most frequently used in real-world studies and FISH testing most frequently used in clinical trials (n=9/10). METamp definitions varied among clinical trials using ISH/FISH testing (MET to chromosome 7 centromere ratio of ≥1.8 to ≥3.0; or gene copy number [GCN] ≥5 to ≥10) and among trials using NGS (tissue testing: GCN ≥6; liquid biopsy: MET copy number ≥2.1 to >5). Limited to no data were identified on the economic and humanistic burdens, and real-world treatment of METamp NSCLC. Promising preliminary results from trials enrolling patients with EGFR-mutated, METamp advanced NSCLC progressing on an EGFR-tyrosine kinase inhibitor (TKI) were observed with MET-TKIs (i.e., tepotinib, savolitinib, and capmatinib) in combination with EGFR-TKIs (i.e., gefitinib and osimertinib). For metastatic NSCLC and high-level METamp, monotherapy with capmatinib, crizotinib, and tepotinib are recommended in the 2022 published NSCLC NCCN Guidelines.

Conclusion

Primary METamp occurs in approximately 5% of NSCLC cases, and secondary METamp in approximately 15% of cases previously treated with an EGFR inhibitor. Variability in testing methods (including ISH/FISH and NGS) and definitions were observed. Several treatments are promising in treating METamp NSCLC. Additional studies evaluating the clinical, economic, and humanistic burdens are needed.

A PI3K gene expression signature predicts for recurrence in early-stage non-small cell lung cancer treated with stereotactic body radiation therapy

INTRODUCTION

Increasingly, early-stage non-small cell lung cancer (NSCLC) is treated with stereotactic body radiation therapy (SBRT). Although treatment is generally effective, a small subset of tumors will recur because of radioresistance. Preclinical studies suggested PI3K-AKT-mTOR activation mediates radioresistance. This study sought to validate this finding in tumor samples from patients who underwent SBRT for NSCLC.

METHODS

Patients with T1-3N0 NSCLC treated with SBRT at our institution were included. Total RNA of formalin-fixed paraffin-embedded tumor biopsy specimens (pretherapy) was isolated and analyzed using the Clariom D assay. Risk scores from a PI3K activity signature and four published NSCLC signatures were generated and dichotomized by the median. Kaplan-Meier curves and Cox regressions were used to analyze their association with recurrence and overall survival (OS). The PI3K signature was also tested in a data set of resected NSCLC for additional validation.

RESULTS

A total of 92 patients were included, with a median follow-up of 18.3 months for living patients. There was no association of any of the four published gene expression signatures with recurrence or OS. However, high PI3K risk score was associated with higher local recurrence (hazard ratio [HR], 11.72; 95% CI, 1.40-98.0; p = .023) and worse disease-free survival (DFS) (HR, 3.98; 95% CI, 1.57-10.09; p = .0035), but not OS (p = .49), regional recurrence (p = .15), or distant recurrence (p = .85). In the resected NSCLC data set (n = 361), high PI3K risk score was associated with decreased OS (log-rank p = .013) but not DFS (p = 0.54).

CONCLUSIONS

This study validates that higher PI3K activity, measured by gene expression, is associated with local recurrence and worse DFS in early-stage NSCLC patients treated with SBRT. This may be useful in prognostication and/or tailoring treatment, and merits further validation.