scholarly journals Mutational monitoring of EGFR T790M in cfDNA for clinical outcome prediction in EGFR-mutant lung adenocarcinoma

PLoS ONE ◽  
2018 ◽  
Vol 13 (11) ◽  
pp. e0207001 ◽  
Author(s):  
Kang-Yi Su ◽  
Jeng-Sen Tseng ◽  
Keng-Mao Liao ◽  
Tsung-Ying Yang ◽  
Kun-Chieh Chen ◽  
...  
2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e20588-e20588
Author(s):  
Linping Gu ◽  
Bei Zhang ◽  
Ding Zhang ◽  
Hong Jian

e20588 Background: Transformation from non-small cell lung cancer (NSCLC) to small cell lung cancer (SCLC) is one of the resistance mechanism of EGFR tyrosine kinase inhibitors. However, the clinical course of transformed SCLC and the difference of genomic profiling between de novo SCLC patients and transformed SCLC patients are still poorly characterized. Methods: Patients from our hospital diagnosed with SCLC were enrolled retrospectively in this study, including de novo SCLC patients and SCLC patients transformed from EGFR-mutant lung adenocarcinomas. Genomic profiling was performed on formalin-fixed paraffin-embedded tumor samples by next generation sequencing (NGS). In statistical analysis, fisher ‘exact test was used. All tests were bilateral, with P<0.05 indicating significant statistical difference. Results: In total, 16 patients with SCLC transformed from EGFR-mutant lung adenocarcinomas and 230 de novo SCLC patients were included in our study. Transformed SCLC patients were more in younger (p=0.007), female (p<0.001) and non-smokers (p<0.001) than de novo SCLC patients. In transformed SCLC patients, 12 patients (75%) occurred SCLC transformation within 2 years after the lung adenocarcinomas diagnosis. Median transformation time was 20 months. During the treatment of adenocarcinomas, the overall response rate (ORR) was 75% and the median progression-free survival was 12 months. After the initiation of SCLC therapy, the ORR of 1st line chemotherapy was 40%. For the genomic profiling, EGFR mutations, including exon 19 deletion (56%), L858R (38%), and others (6%), were detected. 11 patients with acquired resistance were received EGFR T790M test, 82% of patients had acquired EGFR T790M mutation. 11 patients after transformation to SCLC had NGS test, 100% maintained their founder EGFR mutation, and other recurrent mutations included TP53, RB1 and EGFR amplification. Compared with the genetic alterations in de novo SCLC patients, TP53 mutations were significantly decreased (p=0.006) while EGFR mutations were significantly elevated (p<0.001) in transformed SCLC patients. However, no significant difference on RB1, ALK and ROS1 mutations were observed. Interestingly, a 60-year-old woman in our transformed SCLC cohort harbored EGFR 19 del mutant at allele frequency of 50.39%,she received osimertinib plus epirubicin/cyclophosphamide as 1st line treatment and reached partial response, with survival of 4 years to date. Conclusions: We demonstrated the clinical and genetic characteristics of EGFR-mutant lung adenocarcinoma transformed SCLC and found one patient still benefited from EGFR-TKI. Our study suggested that SCLC patients with EGFR mutation who transformed from lung adenocarcinoma may be potential benefit population using EGFR inhibitors.


2022 ◽  
Vol 123 ◽  
pp. 102230
Author(s):  
Shuchao Pang ◽  
Matthew Field ◽  
Jason Dowling ◽  
Shalini Vinod ◽  
Lois Holloway ◽  
...  

2016 ◽  
Vol 27 (2) ◽  
pp. 336-351 ◽  
Author(s):  
Akram Shalabi ◽  
Masato Inoue ◽  
Johnathan Watkins ◽  
Emanuele De Rinaldis ◽  
Anthony CC Coolen

When data exhibit imbalance between a large number d of covariates and a small number n of samples, clinical outcome prediction is impaired by overfitting and prohibitive computation demands. Here we study two simple Bayesian prediction protocols that can be applied to data of any dimension and any number of outcome classes. Calculating Bayesian integrals and optimal hyperparameters analytically leaves only a small number of numerical integrations, and CPU demands scale as O(nd). We compare their performance on synthetic and genomic data to the mclustDA method of Fraley and Raftery. For small d they perform as well as mclustDA or better. For d = 10,000 or more mclustDA breaks down computationally, while the Bayesian methods remain efficient. This allows us to explore phenomena typical of classification in high-dimensional spaces, such as overfitting and the reduced discriminative effectiveness of signatures compared to intra-class variability.


2015 ◽  
Vol 61 (1) ◽  
pp. 227-242 ◽  
Author(s):  
Arman Rahmim ◽  
C Ross Schmidtlein ◽  
Andrew Jackson ◽  
Sara Sheikhbahaei ◽  
Charles Marcus ◽  
...  

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