Dataset Information

A Combined Two-mRNA Signature Associated With PD-L1 and Tumor Mutational Burden for Prognosis of Lung Adenocarcinoma.

ABSTRACT: Due to biological heterogeneity, lung adenocarcinoma (LUAD) patients with the same stage may exhibit variable responses to immunotherapy and a wide range of outcomes. It is urgent to seek a biomarker that can predict the prognosis and response to immunotherapy in these patients. In this study, we identified two genes (ANLN and ARNTL2) from multiple gene expression data sets, and developed a two-mRNA-based signature that can effectively distinguish high- and low-risk patients and predict patients' response to immunotherapy. Furthermore, taking full advantage of the complementary value of clinical and molecular features, we combined the immune prognostic signature with clinical features to construct and validate a nomogram that can predict the probability of high tumor mutational burden (>10 mutations per megabyte). This may improve the estimation of immunotherapy response in LUAD patients, and provide a new perspective for clinical screening of immunotherapy beneficiaries.

SUBMITTER: Song C

PROVIDER: S-EPMC7875126 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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A Combined Two-mRNA Signature Associated With PD-L1 and Tumor Mutational Burden for Prognosis of Lung Adenocarcinoma.

Song Congkuan C Wu Zhiquan Z Wang Qingwen Q Wang Yujin Y Guo Zixin Z Li Sheng S Hu Weidong W

Frontiers in cell and developmental biology 20210126

Due to biological heterogeneity, lung adenocarcinoma (LUAD) patients with the same stage may exhibit variable responses to immunotherapy and a wide range of outcomes. It is urgent to seek a biomarker that can predict the prognosis and response to immunotherapy in these patients. In this study, we identified two genes (ANLN and ARNTL2) from multiple gene expression data sets, and developed a two-mRNA-based signature that can effectively distinguish high- and low-risk patients and predict patients ...[more]

PMID: 33585490

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Project description:BackgroundThe prognostic implications of tumor mutational burden (TMB) and programmed death ligand 1 (PD-L1) expression are poorly studied in hematologic malignancies.ObjectivesThis study aimed to better understand the characteristics and prognostic value of TMB and PD-1/PD-L1 in hematologic malignancies.DesignThis real-world study was conducted among patients with hematologic malignancies who had next-generation sequencing (NGS) (Foundation Medicine) at the University of California San Diego Moores Cancer Center (2014-2018).MethodsTMB was measured by NGS. PD-L1 expression (tumor proportion score, TPS) was measured by immunohistochemistry (classified as high (⩾50%), low (1-49%), and negative (<1%)). Data was curated from the electronic medical records.ResultsIn 388 evaluable patients, the most common diagnoses were B-cell non-Hodgkin lymphoma (NHL) (35%) and Philadelphia chromosome-negative myeloproliferative disorders (16%). Median TMB was 1.6 mutations/Mb (range, 0-46.83). Forty-eight patients (12%) had TMB ⩾10 mutations/Mb, 90% of which were B-cell or T-cell NHL. In 85 samples with available PD-L1 scores, 11 were high; 26, low; and 48, no tumor cell expression. PD-L1 TPS positive (⩾1%) was most common in T-cell NHL (7/9 (77%) cases) followed by B-cell NHL (21/51 (41%) cases). TMB ⩾4 mutations/Mb and PD-L1 score ⩾1% were significantly associated with shorter overall survival (OS) from diagnosis, with hazard ratio (HR) = 1.46 (p = 0.02, 95% confidence interval (CI) 1.05-2.03) and HR = 2.11 (p = 0.04, 95% CI 1.04-4.30), respectively; the relationship was more pronounced when PD-L1 ⩾50% versus <50% was used (HR = 2.80, p = 0.02, 95% CI 1.19-6.59). Higher TMB and higher PD-L1 positivity correlation were significant but weak (Pearson correlation coefficient R 2 = 0.04, p = 0.04).ConclusionTMB ⩾4 mutations/Mb and positive PD-L1 TPS are poor prognostic factors, correlating with shorter OS across hematologic malignancies.Trial registrationClinicalTrials.gov NCT02478931.

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

A Combined Two-mRNA Signature Associated With PD-L1 and Tumor Mutational Burden for Prognosis of Lung Adenocarcinoma.

Publications

A Combined Two-mRNA Signature Associated With PD-L1 and Tumor Mutational Burden for Prognosis of Lung Adenocarcinoma.

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