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APOBEC3B and APOBEC mutational signature as potential predictive markers for immunotherapy response in non-small cell lung cancer.

ABSTRACT: Non-small cell lung cancer (NSCLC) is known to carry heavy mutation load. Besides smoking, cytidine deaminase APOBEC3B plays a key role in the mutation process of NSCLC. APOBEC3B is also reported to be upregulated and predicts bad prognosis in NSCLC. However, targeting APOBEC3B high NSCLC is still a big challenge. Here we show that APOBEC3B upregulation is significantly associated with immune gene expression, and APOBEC3B expression positively correlates with known immunotherapy response biomarkers, including: PD-L1 expression and T-cell infiltration in NSCLC. Importantly, APOBEC mutational signature is specifically enriched in NSCLC patients with durable clinical benefit after immunotherapy and APOBEC mutation count can be better than total mutation in predicting immunotherapy response. In together, this work provides evidence that APOBEC3B upregulation and APOBEC mutation count can be used as novel predictive markers in guiding NSCLC checkpoint blockade immunotherapy.

SUBMITTER: Wang S

PROVIDER: S-EPMC6053356 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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APOBEC3B and APOBEC mutational signature as potential predictive markers for immunotherapy response in non-small cell lung cancer.

Wang Shixiang S Jia Mingming M He Zaoke Z Liu Xue-Song XS

Oncogene 20180426 29

Non-small cell lung cancer (NSCLC) is known to carry heavy mutation load. Besides smoking, cytidine deaminase APOBEC3B plays a key role in the mutation process of NSCLC. APOBEC3B is also reported to be upregulated and predicts bad prognosis in NSCLC. However, targeting APOBEC3B high NSCLC is still a big challenge. Here we show that APOBEC3B upregulation is significantly associated with immune gene expression, and APOBEC3B expression positively correlates with known immunotherapy response biomark ...[more]

PMID: 29695832

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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.

Project description:BackgroundAPOBEC family play an important role in cancer mutagenesis and tumor development. The role of APOBEC family in lung adenocarcinoma (LUAD) has not been studied comprehensively.Materials and methodsThe expression data of pan-cancer as well as LUAD was obtained from public databases. The expression level of APOBEC family genes was analyzed in different normal and cancer tissues. APOBEC mutagenesis enrichment score (AMES) was utilized to evaluate the APOBEC-induced mutations and the relation of APOBEC with genomic instability. Gene set enrichment analysis was used to identify differentially enriched pathways. Univariate Cox regression and Lasso regression were applied to screen key prognostic genes. The immune cell infiltration was estimated by CIBERSORT. RT-qPCR assay, CCK-8 and Transwell assay were conducted to explore gene expression and lung cancer cell invasion.ResultsCancer tissues had significantly altered expression of APOBEC family genes and the expression patterns of APOBEC family were different in different cancer types. APOBEC3B was the most aberrantly expressed in most cancer types. In LUAD, we observed a significantly positive correlation of AMES with intratumor heterogeneity (ITH), tumor neoantigen burden (TNB), and tumor mutation burden (TMB). High AMES group had high mutation counts of DNA damage repair pathways, and high enrichment of cell cycle and DNA repair pathways. We identified four prognostic genes (LYPD3, ANLN, MUC5B, and FOSL1) based on AMES, and constructed an AMES-related gene signature. The expressions of four genes were enhanced and accelerated the invasion ability and viability of lung cancer cells. Furthermore, we found that high group increased oxidative stress level.ConclusionsAPOBEC family was associated with genomic instability, DNA damage-related pathways, and cell cycle in LUAD. The AMES-related gene signature had a great potential to indicate the prognosis and guide immunotherapy/chemotherapy for patients suffering from LUAD.

Project description:BackgroundLung cancer is the leading cause of cancer death worldwide. With the growing number of targeted therapies and the introduction of immuno-oncology (IO), personalized medicine has become standard of care in patients with metastatic disease. The development of predictive and prognostic biomarkers is of great importance. Mutational signatures harbor potential clinical value as predictors of therapy response in cancer. Here we set out to investigate particular mutational processes by assessing mutational signatures and associations with clinical features, tumor mutational burden (TMB) and targetable mutations.MethodsIn this retrospective study, we studied tumor DNA from patients with non-small cell lung cancer (NSCLC) irrespective of stage. The samples were sequenced using a 2 megabase (Mb) gene panel. On each sample TMB was determined and defined as the total number of single nucleotide mutations per Mb (mut/Mb) including non-synonymous mutations. Mutational signature profiling was performed on tumor samples in which at least 30 somatic single base substitutions (SBS) were detected.ResultsIn total 195 samples were sequenced. Median total TMB was 10.3 mut/Mb (range 0-109.3). Mutational signatures were evaluated in 76 tumor samples (39%; median TMB 15.2 mut/Mb). SBS signature 4 (SBS4), associated with tobacco smoking, was prominently present in 25 of 76 samples (33%). SBS2 and/or SBS13, both associated with activity of the AID/APOBEC family of cytidine deaminases, were observed in 11 of 76 samples (14%). SBS4 was significantly more present in early stages (I and II) versus advanced stages (III and IV; P = .005).ConclusionIn a large proportion of NSCLC patients tissue panel sequencing with a 2 Mb panel can be used to determine the mutational signatures. In general, mutational signature SBS4 was more often found in early versus advanced stages of NSCLC. Further studies are needed to determine the clinical utility of mutational signature analyses.

Dataset Information

APOBEC3B and APOBEC mutational signature as potential predictive markers for immunotherapy response in non-small cell lung cancer.

Publications

APOBEC3B and APOBEC mutational signature as potential predictive markers for immunotherapy response in non-small cell lung cancer.

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