Dataset Information

A non-linear association between blood tumor mutation burden and prognosis in NSCLC patients receiving atezolizumab.

ABSTRACT: A significant association between high blood-based tumor mutational burden (bTMB) and improved progression-free survival (PFS) was observed in advanced non-small cell lung cancer (NSCLC) receiving atezolizumab. However, this result was unrepeatable in a recent prospective study. We hypothesized that there might be a non-linear association between bTMB and survival. This study used the clinical and genetic data from POPLAR (n = 105, training set) and OAK (n = 324, validation set) trials. The non-linear association between bTMB and survival was assessed using restricted cubic spline (RCS). The cutoff values for bTMB were calculated via X-tile software. Non-linear relationships were observed between bTMB and PFS and overall survival (OS) in RCS plots (both P _{non-linearity} < 0.001). The optimal cutoff values of bTMB for predicting PFS and OS were 7 and 14 mutations/Mb, respectively. The median PFS and OS of patients with low and high bTMB were significantly longer than those of patients with medium bTMB in the training, validation, and combined sets. Low and high bTMB were also associated with longer PFS and OS in high-programmed death-ligand 1 (PD-L1) expression population. In conclusion, there was a positive non-linear association between bTMB and survival in NSCLC patients receiving atezolizumab. Patients with low bTMB could also derive benefit from immunotherapy.

SUBMITTER: Nie W

PROVIDER: S-EPMC7051187 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A non-linear association between blood tumor mutation burden and prognosis in NSCLC patients receiving atezolizumab.

Nie Wei W Qian Jie J Xu Mi-Die MD Gu Kai K Qian Fang-Fei FF Hu Min-Juan MJ Lu Jun J Gan Lu L Zhang Xue-Yan XY Cao Shu-Hui SH Li Jing-Wen JW Wang Yue Y Zhang Bo B Wang Shu-Yuan SY Hu Fang F Li Chang-Hui CH Zhong Hua H Han Bao-Hui BH

Oncoimmunology 20200220 1

A significant association between high blood-based tumor mutational burden (bTMB) and improved progression-free survival (PFS) was observed in advanced non-small cell lung cancer (NSCLC) receiving atezolizumab. However, this result was unrepeatable in a recent prospective study. We hypothesized that there might be a non-linear association between bTMB and survival. This study used the clinical and genetic data from POPLAR (n = 105, training set) and OAK (n = 324, validation set) trials. The non- ...[more]

PMID: 32158623

Similar Datasets

Project description:BackgroundAt present, there is a lack of studies focusing on the survival prediction of patients with non-small cell lung cancer (NSCLC) receiving atezolizumab in light of gene mutation characteristic.MethodsPatients with NSCLC receiving atezolizumab from the OAK study were defined as the training group. LASSO Cox regressions were applied to establish the gene mutation signature model to predict the overall survival (OS) rate of the training group. NSCLC patients receiving atezolizumab from the POPLAR study were defined as the testing group to validate the gene mutation signature model. In addition, we compared the OS rate between patients receiving atezolizumab and docetaxel classified according to their risk score based on our gene mutation signature model.ResultsWe successfully established a 5-genomic mutation signature that included CREBBP, KEAP1, RAF1, STK11 and TP53 mutations. We found it was superior to the blood tumor mutation burden (bTMB) score and programmed death ligand 1 (PDL1) expression in the prediction of the OS rate for patients receiving atezolizumab. High-risk patients receiving atezolizumab had a worse OS rate compared with low-risk patients in the training (P = 0.0004) and testing (P = 0.0001) groups. In addition, low-risk patients using atezolizumab had a better OS rate compared with those in use of docetaxel for the training (P <0.0001) and testing groups (P = 0.0095). High-risk patients of the training group (P = 0.0265) using atezolizumab had a better OS rate compared with those using docetaxel. However, the OS difference between atezolizumab and docetaxel was not found in high-risk patients from the testing group (P = 0.6403). Multivariate Cox regression analysis showed that the risk model in light of 5-genomic mutation signature was an independent prognostic factor on OS for patients receiving atezolizumab (P <0.0001). In addition, significant OS benefit could only be found in low-risk patients receiving atezolizumab compared with docetaxel (P <0.0001).ConclusionsThe 5-genomic mutation signature could predict OS benefit for patients with NSCLC receiving atezolizumab. Therefore, the establishment of the 5-genomic mutation panel will guide clinicians to identify optimal patients who could benefit from atezolizumab treatment.

Project description:BackgroundIntrahepatic cholangiocarcinoma (iCCA) is a highly lethal malignancy of the biliary tract. Analysis of somatic mutational profiling can reveal new prognostic markers and actionable treatment targets. In this study, we explored the utility of genomic mutation signature and tumor mutation burden (TMB) in predicting prognosis in iCCA patients.MethodsWhole-exome sequencing and corresponding clinical data were collected from the ICGC portal and cBioPortal database to detect the prognostic mutated genes and determine TMB values. To identify the hub prognostic mutant signature, we used Cox regression and Lasso feature selection. Mutation-related signature (MRS) was constructed using multivariate Cox regression. The predictive performances of MRS and TMB were assessed using Kaplan-Meier (KM) analysis and receiver operating characteristic (ROC). We performed a functional enrichment pathway analysis using gene set enrichment analysis (GSEA) for mutated genes. Based on the MRS, TMB, and the TNM stage, a nomogram was constructed to visualize prognosis in iCCA patients.ResultsThe mutation landscape illustrated distributions of mutation frequencies and types in iCCA, and generated a list of most frequently mutated genes (such as Tp53, KRAS, ARID1A, and IDH1). Thirty-two mutated genes associated with overall survival (OS) were identified in iCCA patients. We obtained a six-gene signature using the Lasso and Cox method. AUCs for the MRS in the prediction of 1-, 3-, and 5-year OS were 0.759, 0.732, and 0.728, respectively. Kaplan-Meier analysis showed a significant difference in prognosis for patients with iCCA having a high and low MRS score (P < 0.001). GSEA was used to show that several signaling pathways, including MAPK, PI3K-AKT, and proteoglycan, were involved in cancer. Conversely, survival analysis indicated that TMB was significantly associated with prognosis. GSEA indicated that samples with high MRS or TMB also showed an upregulated expression of pathways involved in tumor signaling and the immune response. Finally, the predictive nomogram (that included MRS, TMB, and the TNM stage) demonstrated satisfactory performance in predicting survival in patients with iCCA.ConclusionsMutation-related signature and TMB were associated with prognosis in patients with iCCA. Our study provides a valuable prognostic predictor for determining outcomes in patients with iCCA.

Dataset Information

A non-linear association between blood tumor mutation burden and prognosis in NSCLC patients receiving atezolizumab.

Publications

A non-linear association between blood tumor mutation burden and prognosis in NSCLC patients receiving atezolizumab.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets