Abstract 209P
Background
Patients (pts) with lung cancer had high rates of brain metastasis (BM). Genetic alterations were associated with the metastatic spread of lung cancer cells in recent study, lung cancer driver genes, such as EGFR, ALK, and RET are risk factors for brain metastasis in advanced lung cancer pts. The number of CNV regions was markedly higher in the secondary metastatic tumor than the primary tumor in the lung. However, the precise mechanisms in BM were still unclear. In this study, we explored the clinical and molecular features of lung cancer with brain metastases in Chinese real word.
Methods
This study retrospectively analyzed the genomic alteration of Chinese lung cancer with brain metastases pts during 2019-2022. Next-generation sequencing (NGS) was performed to detect gene mutations in tumor. Lung cancer driver genes set, as EGFR, ALK, ROS1, BRAF, ERBB2, MET, KRAS and RET were evaluated in those pts.
Results
193 lung cancer with brain metastases pts were enrolled. Male:Female ratio: 128:65. Median age 61 years(Min-Max: 38-78). 79% of pts had CNV, and tumors with CNV had higher TMB values than those without CNV (7.7 vs. 2.8, p<0.001). The top3 amplification genes were: EGFR(n=25), MYC(n=11), ERBB2(n=10), and the three most frequently deletion genes were: CDKN2A (n=69), CDKN2B (n=69), PTEN (n=15). Among pts with TMB≥10, the proportion of pts with CNV was higher than that of pts without CNV (24% vs. 5%, χ2=7.22, p < 0.05). The numbers of pts with driver gene mutation and pts without driver gene mutation were 145 and 48, respectively, and there was no significant difference in age between the two groups. Pts with CNV and no driver gene mutation had higher TMB values (average TMB=9.6). The proportion of pts that carrying CNV in driver gene mutation tumors was similar to those without driver gene mutation (82% vs. 68%).
Conclusions
79% of pts with brain metastases had CNV. The top3 amplification genes were: EGFR, MYC, ERBB2, and the three most frequently deletion genes were: CDKN2A, CDKN2B, PTEN. The proportion of pts that carrying CNV in driver gene mutation tumors was similar to those without driver gene mutation. Pts with CNV and no driver gene mutation had higher TMB values, indicating the pts may have more clinical benefits from immunotherapy.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
Xianfeng Zhang.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
144P - Artificial intelligence supported treatment decisions for precision oncology
Presenter: Damian Rieke
Session: Poster session 01
145P - Identification of biomarkers of survival across multiple cancer types using eXplainable artificial intelligence
Presenter: Francesca Angileri
Session: Poster session 01
147P - Non-small cell lung cancer: Artificial intelligence enables the identification of survival signatures complementary to an Immunologically active gene expression signature involving previous therapies
Presenter: Pierre Saintigny
Session: Poster session 01
149P - Assessing the effect of single dose trastuzumab and pertuzumab (HP) on biological changes and pathological complete response (pCR) in ERBB2+ Breast Cancer: Results from the neoadjuvant BionHER study
Presenter: Nadia Gomez Serra
Session: Poster session 01
150P - Validation of a genomic assay in early-stage HER2+ breast cancer (BC) treated with trastuzumab and pertuzumab (HP): A correlative analysis from PHERGain phase II trial
Presenter: Antonio Llombart Cussac
Session: Poster session 01
152P - Efficacy of olaparib in advanced cancers with germline or somatic tumor mutations in BRCA1, BRCA2, CHEK2 and ATM: A Belgian precision tumor-agnostic phase II study
Presenter: Sofie Joris
Session: Poster session 01
153P - Descriptive analysis of the location of point mutations in BRCA and the risk of breast or ovarian cancer diagnosis
Presenter: Pablo Torres-Mozas
Session: Poster session 01
154P - Highly sensitive serum volatolomic biomarkers for pancreatic cancer diagnosis and prognosis
Presenter: Alfredo Martínez
Session: Poster session 01