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ORIGINAL RESEARCH article
Front. Mol. Biosci.
Sec. Molecular Diagnostics and Therapeutics
Volume 12 - 2025 |
doi: 10.3389/fmolb.2025.1522246
Application of Bioinformatics-Based CDK1 and STAT1 in the Diagnosis of Acute Kidney Injury in Patients with Gastrointestinal Cancers
Provisionally accepted- Civil Aviation Shanghai Hospital, Shanghai, Shanghai Municipality, China
Introduction: Patients with gastrointestinal cancers are prone to acute kidney injury (AKI) due to treatment or disease progression, and current diagnostic methods exhibit insufficient sensitivity and specificity. This study aims to evaluate the potential value of CDK1 and STAT1 in the diagnosis of AKI in this patient population. Methods: A retrospective analysis was conducted on adjacent tissue, cancerous and the clinical data tissue from 150 gastrointestinal cancer patients treated at our hospital from May 2022 to May 2023. Differentially expressed genes (DEGs) associated with gastrointestinal cancer and kidney injury were identified through bioinformatics analysis. The expression of DEGs proteins in cancerous and adjacent tissues was assessed using immunohistochemical scoring (H scores). Patients were classified into AKI (n=42) and non-AKI groups (n=108) according to KDIGO AKI criteria. Univariate and multivariate logistic regression analyses were performed to investigate the influencing factors of AKI occurrence. Spearman correlation analysis was used to explore the relationship between DEGs and AKI biomarkers (Scr, BUN, MAU, and UA). The application value of DEGs in early diagnosis of AKI was evaluated using ROC curves. Results: Bioinformatics analysis identified CDK1, STAT1, COL1A2, and COL1A1 as DEGs related to AKI in gastrointestinal cancer. Immunohistochemical analysis revealed elevated H scores for CDK1, STAT1, COL1A2, and COL1A1 in tumor tissues. Univariate analysis showed no significant differences in age, sex, marital status, education level, monthly income, disease type, cancer stage, or tumor markers (CEA, CA242, CA50) between AKI and non-AKI groups (P>0.05). However, the AKI group exhibited significantly higher levels of MAU, UA, and H scores for CDK1, STAT1, COL1A2, and COL1A1 compared to the non-AKI group (P<0.05). Multivariate logistic regression confirmed that MAU, UA, CDK1, and STAT1 are independent risk factors for AKI in gastrointestinal cancer patients. Correlation analysis indicated a significant positive association between CDK1, STAT1, and AKI biomarker levels (P<0.05). ROC curve analysis demonstrated that CDK1 and STAT1 possess high diagnostic value for early detection of AKI in patients with gastrointestinal cancer, with enhanced efficacy when used in combination. Conclusion: CDK1 and STAT1 serve as early diagnostic indicators for the occurrence of AKI in gastrointestinal cancer patients.
Keywords: bioinformatics, Cdk1, STAT1, Digestive tract cancer, AKI In summary, CDK1, STAT1, COL1A2, and COL1A1 identified through
Received: 11 Nov 2024; Accepted: 03 Jan 2025.
Copyright: © 2025 Wei, Shen, Tian and Ling. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Yunzhi Ling, Civil Aviation Shanghai Hospital, Shanghai, 200051, Shanghai Municipality, China
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