Autor: |
Marika L Forsythe, Akram Alwithenani, Drew Bethune, Mathieu Castonguay, Arik Drucker, Gordon Flowerdew, Daniel French, John Fris, Wenda Greer, Harry Henteleff, Mary MacNeil, Paola Marignani, Wojciech Morzycki, Madelaine Plourde, Stephanie Snow, Zhaolin Xu |
Jazyk: |
angličtina |
Rok vydání: |
2020 |
Předmět: |
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Zdroj: |
PLoS ONE, Vol 15, Iss 8, p e0236580 (2020) |
Druh dokumentu: |
article |
ISSN: |
1932-6203 |
DOI: |
10.1371/journal.pone.0236580 |
Popis: |
Lung cancer is generally treated with conventional therapies, including chemotherapy and radiation. These methods, however, are not specific to cancer cells and instead attack every cell present, including normal cells. Personalized therapies provide more efficient treatment options as they target the individual's genetic makeup. The goal of this study was to identify the frequency of causal genetic mutations across a variety of lung cancer subtypes in the earlier stages. 833 samples of non-small cell lung cancer from 799 patients who received resection of their lung cancer, were selected for molecular analysis of six known mutations, including EGFR, KRAS, BRAF, PIK3CA, HER2 and ALK. A SNaPshot assay was used for point mutations and fragment analysis searched for insertions and deletions. ALK was evaluated by IHC +/- FISH. Statistical analysis was performed to determine correlations between molecular and clinical/pathological patient data. None of the tested variants were identified in most (66.15%) of cases. The observed frequencies among the total samples vs. only the adenocarcinoma cases were notable different, with the highest frequency being the KRAS mutation (24.49% vs. 35.55%), followed by EGFR (6.96% vs. 10.23%), PIK3CA (1.20% vs. 0.9%), BRAF (1.08% vs. 1.62%), ALK (0.12% vs. 0.18%), while the lowest was the HER2 mutation (0% for both). The statistical analysis yielded correlations between presence of a mutation with gender, cancer type, vascular invasion and smoking history. The outcome of this study will provide data that helps stratify patient prognosis and supports development of more precise treatments, resulting in improved outcomes for future lung cancer patients. |
Databáze: |
Directory of Open Access Journals |
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