Unique characteristics of G719X and S768I compound double mutations of epidermal growth factor receptor (EGFR) gene in lung cancer of coal-producing areas of East Yunnan in Southwestern China Article Swipe
YOU?
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· 2022
· Open Access
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· DOI: https://doi.org/10.1186/s41021-022-00248-z
Background The principal objective of this project was to investigate the Epidermal Growth Factor Receptor ( EGFR ) gene mutation characteristics of lung cancer patients, which can provide a molecular basis for explaining the clinicopathological features, epidemiology and use of targeted therapy in lung cancer patients in the coal-producing areas of East Yunnan. Methodology We collected 864 pathologically confirmed lung cancer patients’ specimens in First People’s Hospital of Qujing City of Yunnan Province from September 2016 to September 2021. We thereafter employed Next Generation Sequencing (NGS) technology to detect all exons present in the EGFR gene. Results The overall mutation frequency of the EGFR gene was 47.22%. The frequency of EGFR gene mutations in the tissue, plasma, and cytology samples were found to be 53.40%, 23.33%, and 62.50%, respectively. Univariate analysis indicated that the coal-producing areas and Fuyuan county origin were significantly associated with relatively low EGFR gene mutation frequency. Female, non-smoking history, adenocarcinoma, non-brain metastasis, and tissue specimens were found to be related to high EGFR gene mutation frequency. Multivariate logistic regression analysis suggested the lung cancer patients in the central area of Qujing City, stage Ia, non-coal-producing areas, non-Fuyuan origin, and non-Xuanwei origin were more likely to develop EGFR gene mutations. The most common mutations were L858R point mutation (33.09%) and exon 19 deletion (19-del) (21.32%). Interestingly, the mutation frequency of G719X ( p = 0.001) and G719X + S768I ( p = 0.000) in the coal-producing areas were noted to be more significant than those in non-coal-producing regions. Conclusion This findings of this study might be important in establishing the correlation between routine using NGS for EGFR gene mutation diagnosis and clinical practice in the lung cancer patients.
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- article
- Language
- en
- Landing Page
- https://doi.org/10.1186/s41021-022-00248-z
- https://genesenvironment.biomedcentral.com/track/pdf/10.1186/s41021-022-00248-z
- OA Status
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- Cited By
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- References
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- Related Works
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- OpenAlex ID
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- OpenAlex ID
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https://openalex.org/W4281285811Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1186/s41021-022-00248-zDigital Object Identifier
- Title
-
Unique characteristics of G719X and S768I compound double mutations of epidermal growth factor receptor (EGFR) gene in lung cancer of coal-producing areas of East Yunnan in Southwestern ChinaWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2022Year of publication
- Publication date
-
2022-05-23Full publication date if available
- Authors
-
Junling Wang, Yudong Fu, Yanhong Gao, Xiuping Li, Qian Xiong, Rui Li, Bo Hou, Ruo-Shan Huang, Junfeng Wang, Jiankun Zhang, Jialing Lv, Chao Zhang, Hong-Wei LiList of authors in order
- Landing page
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https://doi.org/10.1186/s41021-022-00248-zPublisher landing page
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https://genesenvironment.biomedcentral.com/track/pdf/10.1186/s41021-022-00248-zDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://genesenvironment.biomedcentral.com/track/pdf/10.1186/s41021-022-00248-zDirect OA link when available
- Concepts
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Epidermal growth factor receptor, Lung cancer, Exon, Gene mutation, Adenocarcinoma, Mutation, Mutation frequency, Point mutation, Cancer research, Cancer, Oncology, Gene, Biology, Internal medicine, Pathology, Medicine, GeneticsTop concepts (fields/topics) attached by OpenAlex
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15Total citation count in OpenAlex
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2025: 1, 2024: 1, 2023: 12, 2022: 1Per-year citation counts (last 5 years)
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61Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.objective | 4 |
| abstract_inverted_index.patients, | 25 |
| abstract_inverted_index.patients. | 281 |
| abstract_inverted_index.principal | 3 |
| abstract_inverted_index.specimens | 63, 159 |
| abstract_inverted_index.suggested | 175 |
| abstract_inverted_index.Background | 1 |
| abstract_inverted_index.Conclusion | 252 |
| abstract_inverted_index.Generation | 84 |
| abstract_inverted_index.People’s | 66 |
| abstract_inverted_index.Sequencing | 85 |
| abstract_inverted_index.Univariate | 130 |
| abstract_inverted_index.associated | 143 |
| abstract_inverted_index.explaining | 33 |
| abstract_inverted_index.frequency. | 150, 170 |
| abstract_inverted_index.mutations. | 203 |
| abstract_inverted_index.non-Fuyuan | 191 |
| abstract_inverted_index.regression | 173 |
| abstract_inverted_index.relatively | 145 |
| abstract_inverted_index.technology | 87 |
| abstract_inverted_index.thereafter | 81 |
| abstract_inverted_index.Methodology | 54 |
| abstract_inverted_index.correlation | 264 |
| abstract_inverted_index.investigate | 10 |
| abstract_inverted_index.metastasis, | 156 |
| abstract_inverted_index.non-Xuanwei | 194 |
| abstract_inverted_index.non-smoking | 152 |
| abstract_inverted_index.patients’ | 62 |
| abstract_inverted_index.significant | 246 |
| abstract_inverted_index.Multivariate | 171 |
| abstract_inverted_index.epidemiology | 37 |
| abstract_inverted_index.establishing | 262 |
| abstract_inverted_index.respectively. | 129 |
| abstract_inverted_index.significantly | 142 |
| abstract_inverted_index.Interestingly, | 219 |
| abstract_inverted_index.coal-producing | 49, 135, 239 |
| abstract_inverted_index.pathologically | 58 |
| abstract_inverted_index.adenocarcinoma, | 154 |
| abstract_inverted_index.characteristics | 21 |
| abstract_inverted_index.non-coal-producing | 189, 250 |
| abstract_inverted_index.clinicopathological | 35 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 13 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.8799999952316284 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.91415901 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |