Bioinformatski pristopi analize izražanja genov za iskanje možnih molekularnih označevalcev pri raku debelega črevesa in danke (rdčd)

Planinc, Rebeka

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Title:	Bioinformatski pristopi analize izražanja genov za iskanje možnih molekularnih označevalcev pri raku debelega črevesa in danke (rdčd)
Authors:	ID Planinc, Rebeka (Author) ID Glavač, Damjan (Mentor) More about this mentor... ID Fister, Iztok (Comentor)
Files:	MAG_Planinc_Rebeka_2022.pdf (1,66 MB) MD5: 3A173CBFE14A806C5A963BC1145CA2BB
Language:	Slovenian
Work type:	Master's thesis/paper
Typology:	2.09 - Master's Thesis
Organization:	FZV - Faculty of Health Sciences
Abstract:	Razvoj raka debelega črevesa in danke je večstopenjski proces, pri katerem se karcinom razvije skozi leta iz sprememb na steni črevesa – polipov. Nove raziskave se osredotočajo na posebne strategije za diagnozo in odkrivanje RDČD, kot je iskanje molekularnih označevalcev. Za opravljanje takšnih genetskih raziskav, med katere spada analiza diferenčnega izražanja genov, uporabljamo metode in algoritme bioinformatike. V okviru empiričnega dela smo opravili raziskavo, ki je temeljila tako na kvantitativni kot kvalitativni metodologiji raziskovanja. Iz podatkovne baze Omnibus smo s pomočjo programskega jezika Python in R identificirali diferenčno izražene gene pri RDČD. Izbira kandidatnih genov je bila izvedena s pomočjo bioinformatskih programov The human protein atlas, KEGG, DAVID in Enrichr. Kot možne molekularne označevalce smo izbrali gene REG4, AQP8, SLC4A4, TAOK1, IL1RN in INSL5, za raziskavo katerih je sledilo praktično laboratorijsko delo. V svoji študiji smo uporabili klinične vzorce 97 pacientov s spremenjeno patologijo in 25 pacientov z normalno sluznico, iz katerih se je izolirala RNK in izvedla RT-PCR z uporabo sond TaqMan. Rezultati analize ekspresije genov so odkrili gene AQP8, SLC4A4, TAOK1 in REG4 kot potencialne nove biološke označevalce pri RDČD. Zanje je bila odkrita statistično značilna razlika v izražanju pri patološkem tkivu polipov v primerjavi z normalno sluznico. Gena IL1RN in INSL5 se nista pokazala za primerna biološka označevalca. Bioinformatika raka in iskanje novih molekularnih označevalcev je eden najbolj kritičnih in uporabnih pristopov k medicini za klinične raziskave ter izboljšanje rezultatov bolnikov z RDČD.
Keywords:	rak debelega črevesa in danke, presejanje, diferenčno izražanje genov, molekularni biološki označevalec, bioinformatika.
Place of publishing:	Maribor
Publisher:	[R. Planinc]
Year of publishing:	2022
PID:	20.500.12556/DKUM-82984
UDC:	575.112:616.345-006(043.2)
COBISS.SI-ID:	130867971
Publication date in DKUM:	19.12.2022
Views:	866
Downloads:	107
Metadata:
Categories:	FZV
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Licences

License:	CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

Link:	http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:	The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:	12.09.2022

Secondary language

Language:	English
Title:	Bioinformatics approaches for the analysis of gene expression to find molecular biomarkers in colorectal cancer (crc)
Abstract:	The development of colorectal cancer is a multistage process in which carcinoma develops over the years from changes on the intestinal wall - polyps. New research is focusing on specific strategies for the diagnosis and detection of CRC, such as the search for molecular biomarkers. We use bioinformatics methods and algorithms to perform such genetic research, which includes differential gene expression analysis. As part of the empirical work, we conducted research based on both quantitative and qualitative research methodology. Using the Python and R programming languages, differentially expressed genes in CRC were identified from the Omnibus database. The selection of candidate genes was carried out using the bioinformatics programs The human protein atlas, KEGG, DAVID and Enrichr. We selected the genes REG4, AQP8, SLC4A4, TAOK1, IL1RN and INSL5 as possible molecular biomarkers, for the research of which practical laboratory work followed. In our study, we used clinical samples from 97 patients with altered pathology and 25 patients with normal mucosa, from which RNA was isolated and RT-PCR was performed using TaqMan probes. The results of gene expression analysis identified AQP8, SLC4A4, TAOK1 and REG4 genes as potential new biomarkers in CRC. A statistically significant difference in expression was found for them in pathological polyp tissue compared to normal mucosa. IL1RN and INSL5 genes did not prove to be suitable biomarkers.Cancer bioinformatics and the search for new molecular biomarkers is one of the most critical and useful approaches to medicine for clinical research and improving the outcomes of patients with CRC.
Keywords:	colorectal cancer, screening, differential gene expression, molecular biomarkers, bioinformatics

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