Mutational profiling of lung adenocarcinoma in China detected by next-generation sequencing
Purpose NSCLC is the most common type of lung cancers. The purpose of this study is to screen cancer-related mutations in early LUAD in China through NGS technology, determine their correlation with clinical characteristics and provide basis for treatment decisions. Methods In this study, we perform...
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Veröffentlicht in: | Journal of cancer research and clinical oncology 2020-09, Vol.146 (9), p.2277-2287 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Purpose
NSCLC is the most common type of lung cancers. The purpose of this study is to screen cancer-related mutations in early LUAD in China through NGS technology, determine their correlation with clinical characteristics and provide basis for treatment decisions.
Methods
In this study, we performed a 583 gene panel to detect the mutational spectrum of the tumors which were collected from 98 LUAD patients. The sequencing data and clinical characteristics were analyzed.
Results
Mutations were identified in 94.9% of patients.
EGFR
had the highest mutation frequency which was detected in 66% of the patients and was significantly associated with female gender and non-smoking history. Other genes with high mutation frequency were
TP53
(37%),
ERBB2
(24%),
BCOR
(22%),
ZFHX3
(19%),
BTG1
(17%),
ATR
(16%),
WWTR1
(15%), etc.
TP53
mutations were significantly associated with medium and low differentiation of tumors;
BCOR
and
BLM
mutations with gender;
WWTR1
mutations with age; and
ATR
mutations with visceral pleura invasion were observed. 61% of the patients harbored at less one actionable alteration associated with FDA-recognized or investigational drugs.
Conclusion
Multiple mutations in LUAD patients in this study have not previously been reported in NSCLC. Moreover, mutations in driver genes including
EGFR
,
TP53
,
BCOR, BLM
,
WWTR1
, and
ATR
were significantly related to clinical features. The panel used in this study is an effective approach for molecular analysis and can be applied in personalized treatment decision-making and drug development. |
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ISSN: | 0171-5216 1432-1335 |
DOI: | 10.1007/s00432-020-03284-w |