Dataset Information

Comprehensive genomic and clinical analyses identify APOBEC mutational signatures as a brain metastasis risk factor in lung adenocarcinoma patients.

ABSTRACT:

Background

Lung adenocarcinoma is the most common source of brain metastasis (BM), resulting in significant morbidity and mortality. We aimed to identify patients with high BM risk who possibly benefit from brain-penetrant drugs, prophylactic cranial irradiation, or close brain magnetic resonance imaging surveillance.

Methods

Metastatic lung adenocarcinoma patients with extracranial tumor samples profiled by a next-generation sequencing panel targeting 425 tumor-related genes were retrospectively enrolled between February 2008 and July 2021. We compared BM and non-BM patients' genomic and clinical features and studied their associations with BM risk. Two external cohorts were used for result validation and molecular mechanisms investigation, respectively.

Results

We included 174 eligible patients, including 90 having developed BM by the end of follow-up. Age≤60, EGFR activating mutations, and high-level apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like (APOBEC) mutational signatures were associated with elevated BM risk. Similar findings in BM-free survival were obtained by fitting Fine-Gray subdistribution hazard models addressing competing risks. Increased BM risk related to APOBEC mutational signatures was validated in an external cohort (N = 440). RNA sequencing data analyses performed in another external cohort (N = 230) revealed that expressions of metastasis-related pathways such as transforming growth factor (TGF)β and epithelial-mesenchymal transition (EMT) were upregulated in the patients with high-level APOBEC mutational signatures.

Conclusion

APOBEC mutational signatures related to upregulated TGFβ and EMT, could serve as an independent risk factor for BM and BM-free survival in metastatic lung adenocarcinoma patients. Further investigations are warranted to tailor personalized treatments to improve the susceptible patient's outcomes.

SUBMITTER: Li Q

PROVIDER: S-EPMC10904272 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Comprehensive genomic and clinical analyses identify APOBEC mutational signatures as a brain metastasis risk factor in lung adenocarcinoma patients.

Li Qiang Q Jiang Meng M Hong Shiqiang S Yang Jing J Wu Xiaoying X Pang Jiaohui J Chen Yedan Y Zhao Xiaotian X Ding Xiao X

Translational oncology 20240224

<h4>Background</h4>Lung adenocarcinoma is the most common source of brain metastasis (BM), resulting in significant morbidity and mortality. We aimed to identify patients with high BM risk who possibly benefit from brain-penetrant drugs, prophylactic cranial irradiation, or close brain magnetic resonance imaging surveillance.<h4>Methods</h4>Metastatic lung adenocarcinoma patients with extracranial tumor samples profiled by a next-generation sequencing panel targeting 425 tumor-related genes were ...[more]

PMID: 38402722

Similar Datasets

Project description:Adenosquamous carcinoma (ASC) of the lung is a relatively rare tumor with strong aggressiveness and poor prognosis. The analysis of mutational signatures is becoming routine in cancer genomics and has implications for pathogenesis, classification, and prognosis. However, the distribution of mutational signatures in ASC patients has not been evaluated. In this study, we sought to reveal the landscape of genomic mutations and mutational signatures in ASC. Next-generation sequencing (NGS) technology was used to retrieve genomic information for 124 ASC patients. TP53 and EGFR were the most prevalent somatic mutations observed, and were present in 66.9% and 54.8% of patients, respectively. CDKN2A (21%), TERT (21%), and LRP1B (18.5%) mutations were also observed. An analysis of gene fusion/rearrangement characteristics revealed a total of 64 gene fusions. The highest frequency of variants was determined for ALK fusions, with six ALK-EML4 classical and two intergenic ALK fusions, followed by three CD74-ROS1 fusions and one ROS1-SYN3 fusion. EGFR 19del (45.6%), and EGFR L858R (38.2%) and its amplification (29.4%) were the top three EGFR mutations. We extracted mutational signatures from NGS data and then performed a statistical analysis in order to search for genomic and clinical features that could be linked to mutation signatures. Amongst signatures cataloged at COSMIC, the most prevalent, high-frequency base changes were for C > T; and the five most frequent signatures, from highest to lowest, were 2, 3, 1, 30, and 13. Signatures 1 and 6 were determined to be associated with age and tumor stage, respectively, and Signatures 22 and 30 were significantly related to smoking. We additionally evaluated the correlation between tumor mutational burden (TMB) and genomic variations. We found that mutations ARID2, BRCA1, and KEAP1 were associated with high TMB. The homologous recombination repair (HRR) pathway-related gene mutation displayed a slightly higher TMB than those without mutations. Our study is the first to report comprehensive genomic features and mutational signatures in Chinese ASC patients. Results obtained from our study will help the scientific community better understand signature-related mutational processes in ASC.

Project description:BackgroundLung adenocarcinoma (LUAD) is the most common type of non-small cell lung cancer (NSCLC) with poor survival in advanced stage. Nowadays the rate of nonsmoking patients has dramatically increased and may be associated with the presence of driver mutations. Better understanding of the mutation profile data of nonsmoking LUAD patients are critical to predict survival and provide greater benefits to more patients. The apolipoprotein B mRNA editing enzyme catalytic polypeptide-like (APOBEC) has been shown to play an important role in molecular tumorigenesis of NSCLC. However, the clinical relevance of APOBEC in nonsmoking LUAD remains to be understood.MethodsLUAD patients with somatic mutation and RNA sequencing data obtained from The Cancer Genome Atlas (TCGA) were assessed and screened in the Gene Expression Omnibus. Transcriptome data and mutational signatures were analyzed using R package. Then, we used the least absolute shrinkage and selection operator (LASSO) regression model to construct the APOBEC3 score (APOBEC3 score) model. The prognostic value was evaluated using Kaplan-Meier analysis. Finally, the functional enrichment analysis of differential expressed genes (DEGs) and the immune-related features were also estimated using R package.ResultsBy analyzing the mutational profile data of NSCLC in the TCGA database, we found that different mutation patterns existed between smoking and nonsmoking patients, and the APOBEC3 family played an important role in the mutation pattern of nonsmoking patients with LUAD. We established an APOBEC3 score and found that TCW (W = A or T) mutation counts were significantly greater in the high APOBEC3 score group than in the low APOBEC3 score group. Furthermore, there were different immune feathers and prognostic values between the high and low APOBEC3 score patients, suggesting an independent prognostic factor of APOBEC3 in nonsmoking LUAD patients.ConclusionsWe established a comprehensive view of APOBEC3 mutations in nonsmoking LUAD patients. Our review provides new insights into using the APOBEC3 mutation to predict prognosis and improve the immunotherapy response for future applications.

Dataset Information

Comprehensive genomic and clinical analyses identify APOBEC mutational signatures as a brain metastasis risk factor in lung adenocarcinoma patients.

Background

Methods

Results

Conclusion

Publications

Comprehensive genomic and clinical analyses identify APOBEC mutational signatures as a brain metastasis risk factor in lung adenocarcinoma patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets