Next-Generation Sequencing in Lung Cancer Patients: A Comparative Approach in NSCLC and SCLC Mutational Landscapes
Identifikátory výsledku
Kód výsledku v 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>
Nalezeny alternativní kódy
RIV/00216224:14740/22:00128637
Výsledek na webu
<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>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Next-Generation Sequencing in Lung Cancer Patients: A Comparative Approach in NSCLC and SCLC Mutational Landscapes
Popis výsledku v původním jazyce
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.
Název v anglickém jazyce
Next-Generation Sequencing in Lung Cancer Patients: A Comparative Approach in NSCLC and SCLC Mutational Landscapes
Popis výsledku anglicky
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.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
30204 - Oncology
Návaznosti výsledku
Projekt
—
Návaznosti
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Ostatní
Rok uplatnění
2022
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
JOURNAL OF PERSONALIZED MEDICINE
ISSN
2075-4426
e-ISSN
2075-4426
Svazek periodika
12
Číslo periodika v rámci svazku
3
Stát vydavatele periodika
CH - Švýcarská konfederace
Počet stran výsledku
21
Strana od-do
453
Kód UT WoS článku
000776366700001
EID výsledku v databázi Scopus
2-s2.0-85127554374