Other formats:
BibTeX
LaTeX
RIS
@article{2255517,
author = {PopandBica, Cecilia and Ciocan, Cristina Alexandra and Braicu, Cornelia and Harangus, Antonia and Simon, Marioara and Nutu, Andreea and Pop, Laura Ancuta and Slabý, Ondřej and Atanasov, Atanas G and Pirlog, Radu and Nadim, Al Hajjar and BerindanandNeagoe, Ioana},
article_location = {Basel},
article_number = {3},
doi = {http://dx.doi.org/10.3390/jpm12030453},
keywords = {non-small-cell lung cancer; small-cell lung cancer; targeted sequencing; patients},
language = {eng},
issn = {2075-4426},
journal = {Journal of Personalized Medicine},
title = {Next-Generation Sequencing in Lung Cancer Patients: A Comparative Approach in NSCLC and SCLC Mutational Landscapes},
url = {https://www.mdpi.com/2075-4426/12/3/453},
volume = {12},
year = {2022}
}
TY - JOUR
ID - 2255517
AU - Pop-Bica, Cecilia - Ciocan, Cristina Alexandra - Braicu, Cornelia - Harangus, Antonia - Simon, Marioara - Nutu, Andreea - Pop, Laura Ancuta - Slabý, Ondřej - Atanasov, Atanas G - Pirlog, Radu - Nadim, Al Hajjar - Berindan-Neagoe, Ioana
PY - 2022
TI - Next-Generation Sequencing in Lung Cancer Patients: A Comparative Approach in NSCLC and SCLC Mutational Landscapes
JF - Journal of Personalized Medicine
VL - 12
IS - 3
SP - 453
EP - 453
PB - MDPI
SN - 20754426
KW - non-small-cell lung cancer
KW - small-cell lung cancer
KW - targeted sequencing
KW - patients
UR - https://www.mdpi.com/2075-4426/12/3/453
N2 - 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.
ER -
POP-BICA, Cecilia, Cristina Alexandra CIOCAN, Cornelia BRAICU, Antonia HARANGUS, Marioara SIMON, Andreea NUTU, Laura Ancuta POP, Ondřej SLABÝ, Atanas G ATANASOV, Radu PIRLOG, Al Hajjar NADIM and Ioana BERINDAN-NEAGOE. Next-Generation Sequencing in Lung Cancer Patients: A Comparative Approach in NSCLC and SCLC Mutational Landscapes. \textit{Journal of Personalized Medicine}. Basel: MDPI, 2022, vol.~12, No~3, p.~453-473. ISSN~2075-4426. Available from: https://dx.doi.org/10.3390/jpm12030453.
|
