A newly developed capture-based sequencing panel for genomic assay of lung cancer.
Genes Genomics
; 42(7): 751-759, 2020 07.
Article
in En
| MEDLINE
| ID: mdl-32449066
ABSTRACT
BACKGROUND:
The increase in genetic alterations targeted by specific chemotherapy in lung cancer has led to the need for universal use of more comprehensive genetic testing, which has highlighted the development of a lung cancer diagnostic panel using next-generation sequencing.OBJECTIVE:
We developed a hybridization capture-based massively parallel sequencing assay named Friendly, Integrated, Research-based, Smart and Trustworthy (FIRST)-lung cancer panel (LCP), and evaluated its performance.METHODS:
FIRST-LCP comprises 64 lung cancer-related genes to test for various kinds of genetic alterations including single nucleotide variations (SNVs), insertions and deletions (indels), copy number variations (CNVs), and structural variations. To assess the performance of FIRST-LCP, we compiled test sets using HapMap samples or tumor cell lines with disclosed genetic information, and also tested our clinical lung cancer samples whose genetic alterations were known by conventional methods.RESULTS:
FIRST-LCP accomplished high sensitivity (99.4%) and specificity (100%) of the detection of SNVs. High precision was also achieved, with intra- or inter-run concordance rate of 0.99, respectively. FIRST-LCP detected indels and CNVs close to the expected allele frequency and magnitude, respectively. Tests with samples from lung cancer patients also identified all SNVs, indels and fusions.CONCLUSION:
Based on the current state of the art, continuous application of the panel design and analysis pipeline following up-to-date knowledge could ensure precision medicine for lung cancer patients.Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Polymorphism, Genetic
/
Sequence Analysis, DNA
/
High-Throughput Nucleotide Sequencing
/
Lung Neoplasms
/
Mutation
/
Neoplasm Proteins
Type of study:
Diagnostic_studies
/
Prognostic_studies
Limits:
Humans
Language:
En
Journal:
Genes Genomics
Year:
2020
Document type:
Article