Oops, you're using an old version of your browser so some of the features on this page may not be displaying properly.

MINIMAL Requirements: Google Chrome 24+Mozilla Firefox 20+Internet Explorer 11Opera 15–18Apple Safari 7SeaMonkey 2.15-2.23

Poster Display session

224P - Cerebrospinal fluid-based mutation abundance index (MAI) correlated to clinical outcome in leptomeningeal metastasis of non-small cell lung cancer with EGFR mutations

Date

22 Mar 2024

Session

Poster Display session

Topics

Translational Research

Tumour Site

Non-Small Cell Lung Cancer

Presenters

Wenjie Zhu

Citation

Annals of Oncology (2024) 9 (suppl_3): 1-4. 10.1016/esmoop/esmoop102578

Authors

W. Zhu1, H. Xu2

Author affiliations

  • 1 Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing/CN
  • 2 National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing/CN

Resources

Login to get immediate access to this content.

If you do not have an ESMO account, please create one for free.

Abstract 224P

Background

Leptomeningeal metastasis (LM) is a devastating complication of advanced non-small cell lung cancer (NSCLC). Genetic profiling using cell-free DNA (cfDNA) from cerebrospinal fluid (CSF) may serve as a novel method for monitoring of LM. Our study was designed to measure mutations in serially collected CSF specimens and investigate its correlation with clinical outcome in EGFR-mutated (EGFRm) NSCLC.

Methods

From March 2018 to June 2023, patients with cytology-confirmed LM who had EGFRm NSCLC were enrolled. All of them underwent EGFR tyrosine kinase inhibitor (TKI) plus intrathecal therapy as initial treatment for LM disease. cfDNA isolated from CSF was analyzed via gene-panel target-capture next-generation sequencing. Mutation abundance index (MAI) was defined as the average value of mutant allele fractions (AF) which are greater than 5%.

Results

35 patients were included in the final analysis. The median time from diagnosis of NSCLC to LM was 18.3 months (95% confidence interval (CI): 14.1-22.4). Intra- and extra-cranial ORR was 14.3% and 8.6% respectively. The median survival after diagnosis of LM was 18.1 months (95% CI: 11.0-19.4). cfDNA was detectable in all 76 CSF samples. Type of EGFR mutation, presence of TP53 mutation and baseline MAI (MAI 1) were not discriminating factors for OS. For each patient, MAI 2 was defined as the MAI measured while on treatment with EGFR TKI (1-2 months away from baseline). The pattern of MAI change was associated with clinical outcome. Neurological function improvement was identified in 72.7% (8/11) of cases with MAI decrease (MAI 2 < MAI 1, N=11). Patients with MAI decrease had significantly better OS than patients with stable or increased MAI (median OS, 21.3 vs. 14.4 months, p=0.012, HR=0.293).

Table: 224P

Baseline characteristics and treatment patterns of patients with LM in EGFRm NSCLC (N=35)

Characteristics N (%)
Age
<65 13 (37.1)
≥65 22 (62.9)
Sex
Male 12 (34.3)
Female 23 (65.7)
Smoking status
Former/current 12 (34.3)
Never 23 (65.7)
ECOG score
0-1 24 (68.6)
≥2 11 (31.4)
History of surgery
Yes 12 (34.3)
No 23 (65.7)
TNM stage at initial diagnosis
Stage I-III 13 (37.1)
Stage IV 22 (62.9)
Type of EGFR mutation at baseline
Exon 21 L858R 17 (48.5)
Exon 19 deletion 10 (28.6)
Compound mutations 8 (22.9)
Coexisting intraparenchymal brain metastasis
Yes 27 (77.1)
No 8 (22.9)
Previous lines of therapy before LM
0 3 (8.6)
1 23 (65.7)
≥2 9 (25.7)
Intra-cranial response
CR/PR 5 (14.3)
SD 30 (85.7)
PD 0 (0)
Extra-cranial response
CR/PR 3 (8.6)
SD 32 (91.4)
PD 0 (0)
Radiation therapy
Yes 6 (17.1)
No 29 (82.9)

Conclusions

CSF-based MAI might be used as a prognostic indicator in LM in EGFRm NSCLC.

Legal entity responsible for the study

National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.

This site uses cookies. Some of these cookies are essential, while others help us improve your experience by providing insights into how the site is being used.

For more detailed information on the cookies we use, please check our Privacy Policy.

Customise settings
  • Necessary cookies enable core functionality. The website cannot function properly without these cookies, and you can only disable them by changing your browser preferences.