Whole-genome profiling to identify chromosomal instability as a distinct feature of lung cancer brain metastases.

e20554 Background: Brain metastases in lung cancer are associated with substantial clinical heterogeneity and poor outcomes, yet underlying molecular mechanisms remain incompletely understood. Previous studies on brain metastases have been limited by the scarcity of in-depth whole-genome sequencing (WGS) data , resulting in insufficient characterization of chromosomal instability (CIN) and fine-scale genomic architecture. This knowledge gap has significantly hindered our understanding of brain metastasis initiation, evolutionary trajectories, and inter-lesion heterogeneity. Methods: Patients diagnosed with lung cancer and brain metastases were retrospectively identified, and frozen samples from these brain metastases, with or withou primary tumors, were available for analysis. High depth whole-genome sequencing (WGS) at 200× coverage was performed to characterize somatic driver alterations and chromosomal instability (CIN). CIN was assessed using genome-wide copy number alteration burden, whole-genome doubling (WGD), and structural variation profiles. Genomic differences between brain metastases and non-brain lesions were evaluated through comparative analyses, with exploratory links to clinical features examined. Results: Whole-genome sequencing of 83 lung cancer brain metastases revealed a high prevalence of chromosomal instability. Among these tumors, 26 were near-diploid, while 57 exhibited whole-genome doubling (WGD; 68.7%). Biallelic inactivation of CDKN2A/2B was common, primarily via homozygous deletion (22/83, 26.5%). Additionally, chromothripsis-like events identified in 33 tumors (39.8%), and high-level focal amplifications( > 10 copies gain) of oncogenic drivers, including EGFR, CDK4, ERBB2, MET, MDM2, MYC and CCNE1, were observed in 30 cases (36.1%). Ongoing analyses integrate transcriptomic and single-cell data to further expand these findings. Conclusions: Comprehensive whole-genome profiling reveals chromosomal instability as a prominent genomic feature of lung cancer brain metastases, supporting its potential role in shaping brain-specific tumor evolution and inter-metastatic heterogeneity, and providing a rational foundation for future biomarker development and clinical practice.

Authors

Institutions

Publication Details

Journal
Journal of Clinical Oncology
Published
2026-05-28
DOI
https://doi.org/10.1200/jco.2026.44.16_suppl.e20554
Primary Topic
Lung Cancer Treatments and Mutations
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Whole-genome profiling to identify chromosomal instability as a distinct feature of lung cancer brain metastases.

Wu Gan, Shuilian Zhang, Dexiang Zhou, Guo Weibang et al.
Journal of Clinical Oncology
Lung Cancer Treatments and Mutations
article

Whole-genome profiling to identify chromosomal instability as a distinct feature of lung cancer brain metastases.

Wu Gan, Shuilian Zhang, Dexiang Zhou, Guo Weibang, Zhaoyang Qian, Xie Zhi, Yang Jinji, Sun H, Xue−Ning Yang, Danxia Lu, Xue Pan, Ming Lu, Xiaofeng Lin, Dong Zhou, Wenqing Yan, Chang Lu, Xuchao Zhang, Zhiyi Lv, Yu Chen
article en

Abstract

e20554 Background: Brain metastases in lung cancer are associated with substantial clinical heterogeneity and poor outcomes, yet underlying molecular mechanisms remain incompletely understood. Previous studies on brain metastases have been limited by the scarcity of in-depth whole-genome sequencing (WGS) data , resulting in insufficient characterization of chromosomal instability (CIN) and fine-scale genomic architecture. This knowledge gap has significantly hindered our understanding of brain metastasis initiation, evolutionary trajectories, and inter-lesion heterogeneity. Methods: Patients diagnosed with lung cancer and brain metastases were retrospectively identified, and frozen samples from these brain metastases, with or withou primary tumors, were available for analysis. High depth whole-genome sequencing (WGS) at 200× coverage was performed to characterize somatic driver alterations and chromosomal instability (CIN). CIN was assessed using genome-wide copy number alteration burden, whole-genome doubling (WGD), and structural variation profiles. Genomic differences between brain metastases and non-brain lesions were evaluated through comparative analyses, with exploratory links to clinical features examined. Results: Whole-genome sequencing of 83 lung cancer brain metastases revealed a high prevalence of chromosomal instability. Among these tumors, 26 were near-diploid, while 57 exhibited whole-genome doubling (WGD; 68.7%). Biallelic inactivation of CDKN2A/2B was common, primarily via homozygous deletion (22/83, 26.5%). Additionally, chromothripsis-like events identified in 33 tumors (39.8%), and high-level focal amplifications( > 10 copies gain) of oncogenic drivers, including EGFR, CDK4, ERBB2, MET, MDM2, MYC and CCNE1, were observed in 30 cases (36.1%). Ongoing analyses integrate transcriptomic and single-cell data to further expand these findings. Conclusions: Comprehensive whole-genome profiling reveals chromosomal instability as a prominent genomic feature of lung cancer brain metastases, supporting its potential role in shaping brain-specific tumor evolution and inter-metastatic heterogeneity, and providing a rational foundation for future biomarker development and clinical practice.

Journal of Clinical OncologyVol. 44(16_suppl)
Guangdong General Hospital (CN), Chinese University of Hong Kong, Shenzhen (CN), Guangdong Academy of Medical Sciences (CN), Guangdong Provincial People's Hospital (CN), Guangdong 999 Brain Hospital (CN), Southern Medical University (CN)
No poverty
Openalex Percentile: Top 6%
Lung Cancer Treatments and Mutations
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.