Določanje novih povezav gen-bolezen-zdravilo z analizo zbirke Cancerome

Djurica Potpara, Veronika (author), Kunej, Tanja (mentor)

Osebe s sladkorno boleznijo tipa 1 (DM1) in sladkorno boleznijo tipa 2 (DM2) pogosteje obolijo za boleznimi raka, vendar pa je vpliv genskih dejavnikov na sopojavnost bolezni v veliki meri še neraziskan. Naš cilj je bil ustvariti celovito zbirko vseh genov in SNP-jev povezanih z rakom in DM in določiti molekularne povezave med boleznima. Pripravili smo zbirko Cancerome (zbranih 3685 genov, 5613 SNP-jev) in zbirko genov in SNP-jev povezanih z DM1 (260 genov in 531 SNP-jev) in DM2 (3572 genov in 1965 SNP-jev). Preučevali smo vpliv SNP-jev, SNP-jev s škodljivim učinkom na genski produkt (pSNP-jev), genov in metabolnih poti povezanih z boleznimi raka in DM na sopojavnost bolezni. Preučevali smo tudi vpliv razdalje (< 1 Mb) med geni povezanimi z rakom in DM na sopojavnost bolezni. Kot negativno kontrolo povezanosti med rakom in DM smo uporabili zbirko SNP-jev in genov povezanih z nevroblastomom, saj ta rak v epidemioloških študijah ni kazal povezanosti z DM. Pokazali smo, da lahko na podlagi števila pSNP-jev, genov s spremenjeno funkcionalnostjo (GSF-jev) in analize SNP-jev povezanih z rakom in DM v istih genih sklepamo o povezanosti bolezni. Kot negativno kontrolo sopojavnosti smo uporabili zbirko genov in SNP-jev povezanih z rakom prostate, saj imajo osebe s tem tipom raka manjše tveganje za razvoj DM. Na podlagi kvantitativne analize molekularnih povezav nismo mogli sklepati o sopojavnosti med rakom in DM, a predvidevamo, da bi z natančnejšo analizo alelov povezanih s tipi raka in DM uspeli oceniti tveganje za sopojavnost. Izvedli smo prerazporejanje zdravil in odkrili nove povezave zdravilo-gen-bolezen pri vseh tipih raka in DM. Ta študija je osnova za določanje zanesljivejših biooznačevalcev bolezni raka in DM ter iskanje biooznačevalcev, s katerimi bomo lahko ocenili tveganje za razvoj sopojavnih bolezni.

• Language: Slovenian
• Keywords: genomika, sladkorna bolezen, rak, pridružene bolezni, prerazporejanje zdravil, podatkovna zbirka
• Work type: Master's thesis/paper
• Typology: 2.09 - Master's Thesis
• Organization: BF - Biotechnical Faculty
• Publisher: [V. Djurica Potpara]
• Year: 2020
• PID: 20.500.12556/RUL-118641
• UDC: 575.112:601.4:577.21:606:616-006.6:616.379(043.2)
• COBISS.SI-ID: 26827779
• Publication date in RUL: 29.08.2020

Secondary language

• Language: English
• Title: Determining new interactions between genes, diseases and drugs using Cancerome database analysis

Abstract

Diabetes mellitus type 1 (DM1) and diabetes mellitus type 2 (DM2) patients show higher risk of cancer development. However, little is known about a role of genetic risk factors in comorbidity of cancer and DM. The aim of the study was to develop comprehensive database of SNPs and genes associated with cancer and DM and to identify molecular connections between the diseases. We created Cancerome database (3685 genes, 5613 SNPs), DM1 database (260 genes, 531 SNPs) and DM2 database (3572 genes, 1965 SNPs). We identified SNPs, SNPs with pathogenic consequences (pSNPs), genes and metabolic pathways simultaneously associated with specific type of cancer and DM. We analyzed impact of SNPs and pSNPs in common genes associated with cancer and DMs and impact of common genes’ location in chromosomes on the risk of comorbidity. We used the results of molecular connections’ analysis between DMs and neuroblastoma as a negative control of association between since this cancer type has not been connected to DMs in any epidemiological study. We were able to determine association between diseases based on common SNPs, pSNPs, genes and location of SNPs in genes simultaneously associated with specific type of cancer and DMs. Patients with DMs have lower risk of prostate cancer. We compared the number of molecular connections between prostate cancer and DMs and other cancer types and DMs to determine if we can determine the comorbidity of diseases based on quantitative analysis. We did not achieve this objective in this work, but we propose that closer examination of SNPs alleles affected in both diseases in different populations might explain role of genetics in comorbidity of cancer and DM. We also executed drug repositioning and discovered new connections Drug-Gen-Disease for all analyzed diseases. This study will further the discovery of more reliable biomarkers for cancer and DM and enable search for biomarkers which will help us assess risk of comorbidity in DM patients.

• Keywords: genomics, diabetes mellitus, cancer, comorbidity, drug repositioning, data base