ENTEGRE BİYOİNFORMATİK ANALİZ İLE KRONİK LENFOSİTİK LÖSEMİDE HEDEF GENLERİN VE YOLAKLARIN BELİRLENMESİ

Öz

Amaç: En yaygın lösemi türü olan kronik lenfositik lösemi (KLL), kanda, kemik iliğinde ve lenfoid organda spesifik bir immünofenotipe sahip monoklonal B hücrelerinin ilerleyici birikimi ile karakterize edilir. Bu çalışmanın amacı, biyoinformatik analiz yaparak KLL’nin altında yatan moleküler mekanizmaları araştırmak, KLL tanı ve tedavisi için potansiyel hedefleri belirlemektir.

Gereç ve Yöntem: Biyoinformatik analiz için GEO veri tabanından KLL hasta verilerine ait GSE22529 ve GSE26725 erişim numaralarına sahip ekspresyon dataları indirildi. GSE22529 numaralı data 41 KLL hasta ve 11 sağlıklı gruptan, GSE26725 numaralı data ise 12 KLL ve 5 sağlıklı gruptan alınan kan örnekleri ile çalışılmıştır. KLL hasta örnekleri ile sağlıklı kontrol örnekler farklı şekilde ifade edilen genleri (DEGs) bulabilmek için GEO2R ile analiz edildi. DEG'ler için DAVID programı kullanılarak GO ve KEGG zenginleştirme analizleri gerçekleştirildi. Cytoscape yazılımı kullanılarak protein-protein etkileşim (PPI) ağı oluşturuldu ve KLL ile ilişkili önemli genler tesbit edildi.

Sonuç ve Tartışma: GEO2R ile analiz sonrası p<0.05 ve log2FC<0, log2FC>0 olan DEG’ler seçildi. GSE22529 veri setinde KLL hastalarında kontrol grubuna göre 942 genin ifadesi artmış, 1007 genin ifadesi azalmıştır. GSE26725 veri setinde ise KLL hastalarında kontrol grubuna göre 939 genin ifadesi artmış, 916 genin ifadesi azalmıştır. Her 2 veri seti için ortak olarak ifadesi artan 229, ifadesi azalan 308 DEG tanımlanmıştır. İfadesi değişen bu ortak genlerin ER’de protein işlenmesi, kemokin, B-hücre reseptör, T-hücre reseptör, protein taşıma gibi yolaklarda zenginleştiği görülmüştür. Buna ek olarak DDOST, RPL18, RPL18A, RPL19, RPL31, GNB3, GNB4, GNG11, GNGT1, NEDD8, UBE2M RBX1, FBXO21, SKP1, KLHL9 and CAND1 en önemli genler olarak belirlenmiştir. Çalışmamızın sonucu, ortaya çıkan genlerin ve yolakların KLL’nin tanısında ve ilaç tedavisinde kullanılabilecek birer biyobelirteç adayı olabileceğini göstermiştir.

INTEGRATED BIOINFORMATIC ANALYSIS TO EVALUATE TARGET GENES AND PATHWAYS IN CHRONIC LYMPHOCYTIC LEUKEMIA

Öz

Objective: The most common type of leukemia, chronic lymphocytic leukemia (CLL), is characterized by progressive accumulation of monoclonal B cells with a specific immunophenotype in the blood, bone marrow, and lymphoid organ. The goal of this research was to use bioinformatic analysis to comprehend the molecular mechanisms causing CLL and to investigate potential targets for the diagnosis and therapy of CLL.

Material and Method: Expression data from CLL patients with accession numbers GSE22529 and GSE26725 were downloaded from the GEO database for bioinformatic analysis. GSE22529 data was studied with samples from 41 CLL patients and 11 healthy groups, while GSE26725 data was studied with blood samples from 12 CLL patients and 5 healthy groups. GEO2R was used to find differentially expressed genes (DEGs) in CLL patient samples and healthy control samples. The DAVID program was used to perform GO and KEGG enrichment analyses on DEGs. Using the Cytoscape software, a protein-protein interaction (PPI) network was created, and hub genes associated with CLL were identified.

Result and Discussion: DEGs with p 0.05 and log2FC 0, log2FC>0 were chosen after analysis with GEO2R. In the GSE22529 dataset, 942 genes had higher expression levels in CLL patients compared with controls, while the expression of 1007 genes decreased. In the GSE26725 dataset, CLL patients had lower expression levels for 916 genes compared with controls, while 939 genes showed an increase in expression. 229 DEGs with higher expression levels and 308 DEGs with lower expression levels were found in both sets of data. It has been observed that these common genes, whose expression has changed, are enriched in protein processing in the ER, Chemokine, B-cell receptor, T-cell receptor, protein export pathways. Additionally, DDOST, RPL18, RPL18A, RPL19, RPL31, GNB3, GNB4, GNG11, GNGT1, NEDD8, UBE2M RBX1, FBXO21, SKP1, KLHL9 and CAND1 were identified as the most important genes. Our study's findings demonstrated that newly discovered genes and pathways may be candidates for CLL biomarkers that can be used for both the diagnosis and drug treatment of the disease.

Anahtar Kelimeler

• Bioinformatic analysis
• CLL
• GEO
• microarray
• network module

Kaynakça

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