Pregled bibliografske jedinice broj: 839661
Computational screening for non-small cell lung carcinoma biomarker candidates
Computational screening for non-small cell lung carcinoma biomarker candidates // Biochemia Medica 2012 ; (22/3):A176-177
Dubrovnik, Hrvatska, 2012. str. P18-05 (poster, međunarodna recenzija, sažetak, znanstveni)
CROSBI ID: 839661 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Computational screening for non-small cell lung carcinoma biomarker candidates
Autori
Dundović, Sandra ; Debeljak, Željko ; Šerić, Vatroslav
Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni
Izvornik
Biochemia Medica 2012 ; (22/3):A176-177
/ - , 2012, P18-05
Skup
2nd European Joint Congress of EFLM and UEMS
Mjesto i datum
Dubrovnik, Hrvatska, 10.10.2012. - 13.10.2012
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Non small cell lung cancer; computational screening
Sažetak
Lung cancer is one of the main causes of death among malignant diseases. There are two main histological types: a small cell lung cancer (SCLC) and a non-small cell lung cancer (NSCLC). NSCLC is the most common type of lung cancer. NSCLC is comprised of three major histological subtypes, adenocarcinoma, squamous cell carcinoma and large cell carcinoma. At the time establishment of diagnosis the disease is localized only in 20% of all lung cancer patients, whereas 75% of patients here metastases in regional lymph nodes. Therefore, lung cancer is a significant diagnostic problem with a generally unfavourable prognosis. However, an early and reliable laboratory diagnosis would enable start of treatment on time, and thereby reduce mortality. Unfortunately, the existing lung cancer blood markers do not have sufficient sensitivity and / or specificity that are essential for an early diagnosis of this disease. Microarray technology enables determination of tens of thousands gene expressions in one experiment. Comparison of gene expressions obtained from control and patients population samples based on univariate or multivariate statistical and computational methods allows selection of relevant genes and their protein products and enables microarray based screening for new diagnostic markers.
Izvorni jezik
Engleski
Znanstvena područja
Kliničke medicinske znanosti
POVEZANOST RADA
Ustanove:
Klinički bolnički centar Osijek