scholarly journals Next-generation sequencing and clinical outcomes of patients with lung adenocarcinoma treated with stereotactic body radiotherapy

Cancer ◽  
2017 ◽  
Vol 123 (19) ◽  
pp. 3681-3690 ◽  
Author(s):  
Richard J. Cassidy ◽  
Xinyan Zhang ◽  
Pretesh R. Patel ◽  
Joseph W. Shelton ◽  
Chase E. Escott ◽  
...  
2019 ◽  
Vol 24 (10) ◽  
pp. 1368-1374 ◽  
Author(s):  
Ze‐Rui Zhao ◽  
Yao‐Bin Lin ◽  
Calvin S.H. Ng ◽  
Rong Zhang ◽  
Xue Wu ◽  
...  

Cancers ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2707
Author(s):  
Maria Gabriela O. Fernandes ◽  
Natália Cruz-Martins ◽  
Conceição Souto Moura ◽  
Susana Guimarães ◽  
Joana Pereira Reis ◽  
...  

Background: Analysis of circulating tumor DNA (ctDNA) has remarkable potential as a non-invasive lung cancer molecular diagnostic method. This prospective study addressed the clinical value of a targeted-gene amplicon-based plasma next-generation sequencing (NGS) assay to detect actionable mutations in ctDNA in patients with newly diagnosed advanced lung adenocarcinoma. Methods: ctDNA test performance and concordance with tissue NGS were determined, and the correlation between ctDNA findings, clinical features, and clinical outcomes was evaluated in 115 patients with paired plasma and tissue samples. Results: Targeted-gene NGS-based ctDNA and NGS-based tissue analysis detected 54 and 63 genomic alterations, respectively; 11 patients presented co-mutations, totalizing 66 hotspot mutations detected, 51 on both tissue and plasma, 12 exclusively on tissue, and 3 exclusively on plasma. NGS-based ctDNA revealed a diagnostic performance with 81.0% sensitivity, 95.3% specificity, 94.4% PPV, 83.6% NPV, test accuracy of 88.2%, and Cohen’s Kappa 0.764. PFS and OS assessed by both assays did not significantly differ. Detection of ctDNA alterations was statistically associated with metastatic disease (p = 0.013), extra-thoracic metastasis (p = 0.004) and the number of organs involved (p = 0.010). Conclusions: This study highlights the potential use of ctDNA for mutation detection in newly diagnosed NSCLC patients due to its high accuracy and correlation with clinical outcomes.


2017 ◽  
Vol 142 (3) ◽  
pp. 353-357 ◽  
Author(s):  
Mitra Mehrad ◽  
Somak Roy ◽  
Humberto Trejo Bittar ◽  
Sanja Dacic

Context.— Different testing algorithms and platforms for EGFR mutations and ALK rearrangements in advanced-stage lung adenocarcinoma exist. The multistep approach with single-gene assays has been challenged by more efficient next-generation sequencing (NGS) of a large number of gene alterations. The main criticism of the NGS approach is the detection of genomic alterations of uncertain significance. Objective.— To determine the best testing algorithm for patients with lung cancer in our clinical practice. Design.— Two testing approaches for metastatic lung adenocarcinoma were offered between 2012–2015. One approach was reflex testing for an 8-gene panel composed of DNA Sanger sequencing for EGFR, KRAS, PIK3CA, and BRAF and fluorescence in situ hybridization for ALK, ROS1, MET, and RET. At the oncologist's request, a subset of tumors tested by the 8-gene panel was subjected to a 50-gene Ion AmpliSeq Cancer Panel. Results.— Of 1200 non–small cell lung carcinomas (NSCLCs), 57 including 46 adenocarcinomas and NSCLCs, not otherwise specified; 7 squamous cell carcinomas (SCCs); and 4 large cell neuroendocrine carcinomas (LCNECs) were subjected to Ion AmpliSeq Cancer Panel. Ion AmpliSeq Cancer Panel detected 9 potentially actionable variants in 29 adenocarcinomas that were wild type by the 8-gene panel testing (9 of 29, 31.0%) in the following genes: ERBB2 (3 of 29, 10.3%), STK11 (2 of 29, 6.8%), PTEN (2 of 29, 6.8%), FBXW7 (1 of 29, 3.4%), and BRAF G469A (1 of 29, 3.4%). Four SCCs and 2 LCNECs showed investigational genomic alterations. Conclusions.— The NGS approach would result in the identification of a significant number of actionable gene alterations, increasing the therapeutic options for patients with advanced NSCLCs.


PLoS ONE ◽  
2019 ◽  
Vol 14 (11) ◽  
pp. e0224379 ◽  
Author(s):  
You Jin Chun ◽  
Jae Woo Choi ◽  
Min Hee Hong ◽  
Dongmin Jung ◽  
Hyeonju Son ◽  
...  

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