Next-Generation Sequencing in Lung Cancer Patients: A Comparative Approach in NSCLC and SCLC Mutational Landscapes
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00209805%3A_____%2F22%3A00078970" target="_blank" >RIV/00209805:_____/22:00078970 - isvavai.cz</a>
Alternative codes found
RIV/00216224:14740/22:00128637
Result on the web
<a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8955273/pdf/jpm-12-00453.pdf" target="_blank" >https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8955273/pdf/jpm-12-00453.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/jpm12030453" target="_blank" >10.3390/jpm12030453</a>
Alternative languages
Result language
angličtina
Original language name
Next-Generation Sequencing in Lung Cancer Patients: A Comparative Approach in NSCLC and SCLC Mutational Landscapes
Original language description
Background: Lung cancer remains one of the most diagnosed malignancies, being the second most diagnosed cancer, while still being the leading cause of cancer-related deaths. Late diagnosis remains a problem, alongside the high mutational burden encountered in lung cancer. Methods: We assessed the genetic profile of cancer genes in lung cancer using The Cancer Genome Atlas (TCGA) datasets for mutations and validated the results in a separate cohort of 32 lung cancer patients using tumor tissue and whole blood samples for next-generation sequencing (NGS) experiments. Another separate cohort of 32 patients was analyzed to validate some of the molecular alterations depicted in the NGS experiment. Results: In the TCGA analysis, we identified the most commonly mutated genes in each lung cancer dataset, with differences among the three histotypes analyzed. NGS analysis revealed TP53, CSF1R, PIK3CA, FLT3, ERBB4, and KDR as being the genes most frequently mutated. We validated the c.1621A>C mutation in KIT. The correlation analysis indicated negative correlation between adenocarcinoma and altered PIK3CA (r = -0.50918; p = 0.0029). TCGA survival analysis indicated that NRAS and IDH2 (LUAD), STK11 and TP53 (LUSC), and T53 (SCLC) alterations are correlated with the survival of patients. Conclusions: The study revealed differences in the mutational landscape of lung cancer histotypes.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
30204 - Oncology
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
JOURNAL OF PERSONALIZED MEDICINE
ISSN
2075-4426
e-ISSN
2075-4426
Volume of the periodical
12
Issue of the periodical within the volume
3
Country of publishing house
CH - SWITZERLAND
Number of pages
21
Pages from-to
453
UT code for WoS article
000776366700001
EID of the result in the Scopus database
2-s2.0-85127554374