J 2022

Next-Generation Sequencing in Lung Cancer Patients: A Comparative Approach in NSCLC and SCLC Mutational Landscapes

POP-BICA, Cecilia, Cristina Alexandra CIOCAN, Cornelia BRAICU, Antonia HARANGUS, Marioara SIMON et. al.

Základní údaje

Originální název

Next-Generation Sequencing in Lung Cancer Patients: A Comparative Approach in NSCLC and SCLC Mutational Landscapes

Autoři

POP-BICA, Cecilia, Cristina Alexandra CIOCAN, Cornelia BRAICU, Antonia HARANGUS, Marioara SIMON, Andreea NUTU, Laura Ancuta POP, Ondřej SLABÝ (203 Česká republika, garant, domácí), Atanas G ATANASOV, Radu PIRLOG, Al Hajjar NADIM a Ioana BERINDAN-NEAGOE

Vydání

Journal of Personalized Medicine, Basel, MDPI, 2022, 2075-4426

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

30218 General and internal medicine

Stát vydavatele

Švýcarsko

Utajení

není předmětem státního či obchodního tajemství

Odkazy

Impakt faktor

Impact factor: 3.508 v roce 2021

Kód RIV

RIV/00216224:14740/22:00128637

Organizační jednotka

Středoevropský technologický institut

UT WoS

000776366700001

Klíčová slova anglicky

non-small-cell lung cancer; small-cell lung cancer; targeted sequencing; patients

Štítky

Příznaky

Mezinárodní význam, Recenzováno
Změněno: 14. 2. 2023 15:22, Mgr. Pavla Foltynová, Ph.D.

Anotace

V originále

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.