Abstract

Identification of targetable molecular changes is essential for selecting appropriate treatment in patients with advanced lung adenocarcinoma. Methods: In this study, a Sanger sequencing plus Fluorescence In Situ Hybridization (FISH) sequential approach was compared with a Next-Generation Sequencing (NGS)-based approach for the detection of actionable genomic mutations in an experimental cohort (EC) of 117 patients with advanced lung adenocarcinoma. Its applicability was assessed in small biopsies and cytology specimens previously tested for epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK) mutational status, comparing the molecular changes identified and the impact on clinical outcomes. Subsequently, an NGS-based approach was applied and tested in an implementation cohort (IC) in clinical practice. Using Sanger and FISH, patients were classified as EGFR-mutated (n = 22, 18.8%), ALK-mutated (n = 9, 7.7%), and unclassifiable (UC) (n = 86, 73.5%). Retesting the EC with NGS led to the identification of at least one gene variant in 56 (47.9%) patients, totaling 68 variants among all samples. Still, in the EC, combining NGS plus FISH for ALK, patients were classified as 23 (19.7%) EGFR; 20 (17.1%) KRAS; five (4.3%) B-Raf proto-oncogene (BRAF); one (0.9%) Erb-B2 Receptor Tyrosine Kinase 2 (ERBB2); one (0.9%) STK11; one (0.9%) TP53, and nine (7.7%) ALK mutated. Only 57 (48.7%) remained genomically UC, reducing the UC rate by 24.8%. Fourteen (12.0%) patients presented synchronous alterations. Concordance between NGS and Sanger for EGFR status was very high (κ = 0.972; 99.1%). In the IC, a combined DNA and RNA NGS panel was used in 123 patients. Genomic variants were found in 79 (64.2%). In addition, eight (6.3%) EML4-ALK, four (3.1%), KIF5B-RET, four (3.1%) CD74-ROS1, one (0.8%) TPM3-NTRK translocations and three (2.4%) exon 14 skipping MET Proto-Oncogene (MET) mutations were detected, and 36% were treatable alterations. Conclusions: This study supports the use of NGS as the first-line test for genomic profiling of patients with advanced lung adenocarcinoma.

Highlights

  • Lung cancer is the most common cause of cancer-related death worldwide [1], being frequently diagnosed in an advanced stage when curative treatment is no longer possible

  • The experimental cohort (EC) presented a median overall survival (OS) of 13.0 months: 24 months

  • (1.6%), with no statistically significant differences in the sequence rate according four (3.2%) cases and in these cases, epidermal growth factor receptor (EGFR) was analyzed by Sanger sequencing

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Summary

Introduction

Lung cancer is the most common cause of cancer-related death worldwide [1], being frequently diagnosed in an advanced stage when curative treatment is no longer possible. Recent advances in the knowledge of NSCLC biology, especially on the discovery of oncogenic molecular changes leading to aberrant activation of intracellular signalling associated with the sustained growth of lung cancer cells, led to the development of genotype-targeted therapies, with significant improvement in patients outcomes. Tissue samples are often small histological fragments or cytological specimens obtained by bronchoscopy or transthoracic biopsy These samples should be analyzed for histopathology, which includes the programmed death-ligand 1 (PD-L1) test for immunotherapy selection and molecular testing [9]. We tested an NGS-based approach for the detection of actionable genomic mutations in a cohort of patients with advanced lung adenocarcinoma, previously tested sequentially for EGFR and ALK mutational status, and evaluated the clinical impact of the NGS-based approach. The results from the clinical implementation of a combined NGS DNA plus RNA panel are presented

Design
Tumor Specimens
Library and Template Preparation for Next-Generation Sequencing
Next-Generation Sequencing and Bioinformatic Analysis
Statistical Analysis
Clinicopathologic Characteristics and Mutational Profile
Next-Generation Sequencing Results
Concurrent Genomic Alterations
Concordance Between Sanger and NGS for the EGFR Status
Concordant Results
NGS Results from the Implementation
Discussion
Conclusions
Full Text
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