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Molecular Target Prediction and Transcriptomic Analysis of a Copper Complex as an anticancer candidate agent
1 , 2 , 2, 3 , 1 , 1 , 4 , * 4
1  Unidad de Biotecnología Médica y Farmacéutica. Centro de Investigación y Asistencia en Tecnología y Diseño del Estado de Jalisco A.C., Av. Normalistas 800, Col. Colinas de la Normal, Guadalajara, Jalisco,C.P. 44270, Mexico
2  División de Genética, Centro de Investigación Biomédica de Occidente (CIBO), Centro Médico Nacional de Occidente (CMNO), Instituto Mexicano del Seguro Social (IMSS), Guadalajara 44340, Jalisco, México.
3  Centro Universitario de Ciencias de la Salud (CUCS), Universidad de Guadalajara (UdeG), Guadalajara 44340, Jalisco, México.
4  Departamento de Farmacobiología, Centro Universitario de Ciencias Exactas e Ingenierías, Universidad de Guadalajara, Guadalajara 44430, Jalisco, Mexico
Academic Editor: Enrico Mini

Abstract:

Introduction
PC-Cu (1,10-phenanthroline)(cyclobutane-1,1-dicarboxylate) is a copper-based coordination complex proposed as a novel anticancer candidate. Identifying its potential molecular targets and evaluating their expression in cancer may offer valuable insights into its therapeutic potential within the context of precision oncology.

Methods
We used the SuperPred and TargetNet platforms to predict potential molecular targets of PC-Cu, applying a cutoff of probability and accuracy ≥ 0.8. Subsequently, we analyzed gene expression profiles using GEPIA3, which integrates TCGA and GTEx transcriptomic data. Genes were considered significantly deregulated if they exhibited a log2FC > 1 or < –1 and a p-value or q-value < 0.05.

Results
A total of 34 high-confidence targets were identified. Of these, 21 showed significant differential expression across various cancer types. Strong overexpression was observed for BCL2A1 in melanoma (log2FC = 6.37), CTSD in diffuse large B-cell lymphoma (log2FC = 5.25), PRKCG in cholangiocarcinoma (log2FC = 4.37), GLRA1 in paraganglioma (log2FC = 4.28), and CDC25B in sarcoma (log2FC = 2.31). Conversely, significant downregulation was found for NR3C1 in bladder cancer (log2FC = –0.86), CYP19A1 in bladder (–0.87), NR1H4 in prostate (–0.69), GLRA1 in lung (–0.73), and APEX1 in paraganglioma (–0.68). These findings suggest that PC-Cu may modulate key molecular processes including apoptosis regulation, hormonal signaling, and tumor metabolism.

Conclusion
PC-Cu interacts with several genes involved in cancer biology and demonstrates a tissue-specific expression in cancer. These results support its potential as a precision oncology agent and justify further experimental validation.

Keywords: Copper Complex, Genetics, Oncology, Cheminformatics, Bioinformatics
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