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SDIRSACR Oncology Insights

cancer care will have equitable access, regardless of their geographic location.
A core component of the initiative is the integration of research into clinical care. Through capacity-building programs,
healthcare professionals are gaining enhanced skills to improve infrastructure for clinical research, data-driven decision-
making, and evidence-based practice. Participating centers are encouraged to collaborate with academic institutions,
increase patient participation in clinical trials, and include translational research outcomes into everyday oncology
workflows.
To further enhance system-wide quality, CORN-CCI4EU supports the standardization and optimization of patient
pathways through utilization of real-world data and outcome indicators. Activities include comprehensive site
assessments, regional educational events, and implementation of secure data-sharing platforms for benchmarking
and knowledge exchange.
The CORN-CCI4EU Deep Dive exemplifies the transformative potential of EU-supported collaboration: aligning clinical
practice with research, reducing regional inequalities, and investing in expertise and infrastructure. Early insights and
best practices from the project underline its role in shaping a sustainable, innovation-driven cancer care model.

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CircRNA-miRNA interactions and bioinformatics analysis in cancer

Sema Misir 1

1Department of Biochemistry, Faculty of Pharmacy, Sivas Cumhuriyet University, Sivas, Turkey

Keywords:cancer, CircRNA, miRNA

Although only a small part of the human genome-approximately 2%-consists of protein-coding genes, the remaining
98% comprises non-coding sequences. As research into these non-coding regions expands, the critical roles of non-
coding RNAs (ncRNAs) in gene transcription and expression regulation have become increasingly apparent [1]. Once
dismissed as “junk DNA,” ncRNAs have become a central focus in cancer biology and molecular research. Their newly
discovered roles offer promising avenues for cancer diagnosis and prognosis, underscoring their potential as valuable
biomarkers and therapeutic targets [2]. Advances in next-generation RNA sequencing and sophisticated analytical
techniques have revealed that circular RNAs (circRNAs) and microRNAs (miRNAs) are integral components of the
ncRNA family [3].
CircRNAs are a class of endogenous ncRNAs characterized by their covalently closed-loop structure, which lacks
both 5' caps and 3' poly-A tails. This unique circular conformation makes them resistant to exonuclease degradation,
conferring exceptional stability. Among the well-documented functional mechanisms of circRNAs are their ability to
act as molecular sponges for miRNAs, their interactions with RNA-binding proteins (RBPs), their potential to encode
proteins, and their regulatory influence on gene expression at both the transcriptional and post-transcriptional levels
[4]. Recent scientific advances have highlighted one of the most prominent roles of circRNAs: their miRNA-sponging
activity, which inhibits the functional impact of miRNAs [5]. miRNAs, typically 19–23 nucleotides in length, are small,
single-stranded, ncRNA molecules that play crucial roles in the post-transcriptional regulation of gene expression [1].
Highly conserved across species and exhibiting tissue-specific expression patterns in humans, miRNAs are essential
for regulating key biological processes such as apoptosis, cellular proliferation, stress responses, and differentiation.
CircRNAs selectively contain varying types and quantities of miRNA response elements (MREs), enabling them to inhibit
miRNA activity and consequently upregulate the expression of miRNA-associated target genes. Additionally, circRNAs
can transiently store or transport miRNAs, thereby influencing the expression patterns of genes regulated by these
miRNAs. Acting as endogenous miRNA sponges, circRNAs can function as oncogenes or tumor suppressors, depending
on the context of their molecular interactions [5].
Tumor bioinformatics plays an important role in cancer research and its support in this field has become indispensable.
Large-scale cancer datasets have rapidly accumulated with the advancement of high-throughput technologies in
recent years [6]. Bioinformatics approaches are increasingly utilized to elucidate the pathophysiological mechanisms
underlying diseases and to identify pharmacological targets at both the genetic and proteomic levels [7]. The integration
and analysis of these data resources provide valuable insights into the molecular pathways driving tumorigenesis.
Moreover, such analyses facilitate the identification of early diagnostic and prognostic biomarkers and support the
development of personalized therapeutic strategies [6].
Several online databases support predictive analysis of circRNA–miRNA interactions, including CircRNAprofiler, Circ2GO,
CircNet 2.0, CircAtlas 3.0, and updated versions of CircInteractome [8].

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