Volume 32, Issue 1 (3-2025)
RJMS 2025, 32(1): 1-9 |
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Research code: 1234
Ethics code: 1234
Clinical trials code: 1234
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Alami Daronkalai F Z, Hassanlou M, Javanmard A, Abiri M. Discovery of Novel microRNAs in the Musculoaponeurotic Fibrosarcoma Gene. RJMS 2025; 32 (1) :1-9
URL: http://rjms.iums.ac.ir/article-1-9157-en.html
URL: http://rjms.iums.ac.ir/article-1-9157-en.html
1- Farzanegan Campus, Semnan University, Semnan, Iran
2- Farzanegan Campus, Semnan University, Semnan, Iran ,m.hassanlou@semnan.ac.ir
3- Department of Molecular Genetics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran
4- Department of Medical Genetics, Faculty of Medicine, Iran University of Medical Sciences, Tehran, Iran
2- Farzanegan Campus, Semnan University, Semnan, Iran ,
3- Department of Molecular Genetics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran
4- Department of Medical Genetics, Faculty of Medicine, Iran University of Medical Sciences, Tehran, Iran
Abstract: (171 Views)
Background & Aims: MicroRNAs (miRNAs) are short, non-coding RNAs, 20–24 nucleotides long, that regulate gene expression post-transcriptionally. By binding to complementary sites in the 3′ UTRs of target mRNAs, they cause translational repression or mRNA degradation. Through this mechanism, miRNAs critically influence diverse cellular processes, including cell cycle control, differentiation, apoptosis, immune function, and adaptation to stress, highlighting their broad biological significance (1–3). Their ability to fine-tune gene expression makes them indispensable components of cellular homeostasis. Over the past twenty years, miRNAs have emerged as crucial regulators in human health and disease. Dysregulated expression contributes to diverse disorders, especially cancer. Aberrant miRNA profiles are found across nearly all malignancies, where they act either as oncogenes (oncomiRs) or tumor suppressors, influencing tumor development and progression (2, 4–6). This duality underscores their potential utility as diagnostic biomarkers, prognostic indicators, and therapeutic targets (3, 7). The musculoaponeurotic fibrosarcoma (MAF) gene encodes a transcription factor of the AP-1 superfamily. MAF proteins possess a basic leucine zipper (bZIP) domain that mediates DNA binding and dimerization, regulating gene expression programs controlling cell fate. MAF is crucial for differentiation of diverse cell types, including T cells, macrophages, and lens epithelial cells (8). Importantly, aberrant expression or mutation of MAF has been associated with several malignancies, such as multiple myeloma, angiosarcoma, and certain soft tissue sarcomas (9–11). In these cancers, MAF may contribute to oncogenesis by promoting proliferation, inhibiting apoptosis, and altering cellular metabolism (10). Although MAF plays a critical role in tumor biology, its regulatory mechanisms remain poorly defined. Transcriptional and post-translational regulation have been studied, but miRNA involvement is underexplored. Considering miRNAs’ central role in gene regulation, novel miRNAs may reside within the MAF locus or target its transcripts, potentially influencing MAF expression and function in cancer (12).
Recent progress in high-throughput sequencing and advanced computational tools enables systematic discovery of novel miRNAs. Researchers can scan genomic regions for hairpin-like precursors, predict secondary structures, and evaluate evolutionary conservation and expression profiles, providing comprehensive insights into miRNA biology and regulatory roles across the genome (13, 14). In this context, the present study aims to discover and characterize novel miRNAs associated with the MAF gene, with the goal of uncovering new regulatory elements that may contribute to its oncogenic potential. By integrating bioinformatic predictions with expression data from tumor tissues, this research seeks to provide a deeper understanding of the miRNA-mediated regulation of MAF and its implications for cancer biology.
Methods: To explore novel microRNAs within the MAF gene, a multi-step bioinformatic pipeline was applied, integrating structural prediction, thermodynamic evaluation, and expression profiling. The process began with scanning the gene sequence for stem-loop structures resembling canonical miRNA precursors using SSCprofiler, a tool specialized in detecting hairpin motifs based on sequence and structural features. Candidate precursors were then analyzed with RNAfold, which predicts RNA secondary structures through minimum free energy (MFE) calculations. This analysis provided insights into the thermodynamic stability of RNA molecules, a key determinant of miRNA precursor functionality. Stable hairpin structures with low MFE values were considered more likely to undergo proper processing by the cellular miRNA biogenesis machinery, including Drosha and Dicer enzymes (15-17).
Following structural validation, the predicted precursors were analyzed using MatureBayes, a probabilistic model-based tool that predicts the location and sequence of mature miRNAs within precursor hairpins (18). MatureBayes utilizes sequence features and positional information to identify the most likely mature miRNA products, enabling researchers to pinpoint the functional regions of the precursor molecules. To assess the biological relevance of the predicted miRNAs, expression data from publicly available microRNA sequencing (miRNA-seq) datasets were examined. These datasets include profiles from various tissue types, including normal and tumor samples, allowing for comparative analysis of miRNA expression patterns. The presence of the predicted miRNAs in tumor tissues was considered a key indicator of their potential involvement in oncogenic processes (3, 6, 19).
Results: The computational analysis of the MAF gene sequence yielded three distinct microRNA candidates, each exhibiting hallmark features of canonical miRNA precursors. These candidates were characterized by well-defined stem-loop structures, as identified by SSCprofiler, and demonstrated favorable thermodynamic profiles with low MFE values, as confirmed by RNAfold modeling (15–17). The predicted secondary structures were consistent with those observed in known functional miRNAs, suggesting that these molecules may be processed by the endogenous miRNA biogenesis pathway.
MatureBayes analysis further refined the predictions by identifying the precise sequences of the mature miRNA products derived from each precursor (18). These sequences were mapped to the MAF gene locus and found to reside within intronic or untranslated regions, consistent with the genomic architecture of many miRNAs (13). Importantly, sequence alignment across multiple vertebrate species revealed high conservation of these miRNA candidates, indicating evolutionary preservation and potential functional importance (14). Expression profiling using miRNA-seq data provided compelling evidence for the transcriptional activity of the predicted miRNAs. All three candidates were found to be expressed in a variety of tissue types, with notable enrichment in tumor samples (3, 6, 19). This pattern suggests that the miRNAs may play a role in cancer-related gene regulation, possibly by modulating MAF expression or interacting with downstream targets involved in cell proliferation and survival. The consistent expression across diverse biological contexts supports the hypothesis that these miRNAs are not merely transcriptional noise but may have functional significance in oncogenesis.
Conclusion: The findings of this study offer strong evidence for the existence of previously uncharacterized microRNAs within the musculoaponeurotic fibrosarcoma (MAF) gene locus. Through a rigorous bioinformatic approach, three novel miRNA candidates were identified, structurally validated, and shown to be expressed in tumor tissues. These miRNAs exhibit features consistent with functional regulatory molecules, including stable secondary structures, conserved sequences, and tissue-specific expression patterns. The discovery of these miRNAs adds a new dimension to the regulatory landscape of the MAF proto-oncogene. Given MAF's role in cell differentiation, proliferation, and transformation, the presence of embedded miRNAs may contribute to its fine-tuned regulation under physiological and pathological conditions (8–11). These miRNAs could act as internal modulators of MAF activity or participate in broader gene networks that influence tumor behavior. From a clinical perspective, the identification of novel miRNAs associated with MAF opens up exciting possibilities for cancer diagnostics and therapeutics. These miRNAs may serve as biomarkers for MAF-driven malignancies or as targets for RNA-based interventions aimed at restoring normal gene regulation (1–3, 6). Further validation and functional studies are needed to clarify miRNAs’ roles in cancer progression. This research demonstrates the strength of integrative bioinformatics in revealing hidden regulatory layers and emphasizes miRNAs’ influence on oncogenes. Advancing miRNA biology promises innovative strategies for cancer therapy and personalized medicine in the future (2, 4, 6).
Recent progress in high-throughput sequencing and advanced computational tools enables systematic discovery of novel miRNAs. Researchers can scan genomic regions for hairpin-like precursors, predict secondary structures, and evaluate evolutionary conservation and expression profiles, providing comprehensive insights into miRNA biology and regulatory roles across the genome (13, 14). In this context, the present study aims to discover and characterize novel miRNAs associated with the MAF gene, with the goal of uncovering new regulatory elements that may contribute to its oncogenic potential. By integrating bioinformatic predictions with expression data from tumor tissues, this research seeks to provide a deeper understanding of the miRNA-mediated regulation of MAF and its implications for cancer biology.
Methods: To explore novel microRNAs within the MAF gene, a multi-step bioinformatic pipeline was applied, integrating structural prediction, thermodynamic evaluation, and expression profiling. The process began with scanning the gene sequence for stem-loop structures resembling canonical miRNA precursors using SSCprofiler, a tool specialized in detecting hairpin motifs based on sequence and structural features. Candidate precursors were then analyzed with RNAfold, which predicts RNA secondary structures through minimum free energy (MFE) calculations. This analysis provided insights into the thermodynamic stability of RNA molecules, a key determinant of miRNA precursor functionality. Stable hairpin structures with low MFE values were considered more likely to undergo proper processing by the cellular miRNA biogenesis machinery, including Drosha and Dicer enzymes (15-17).
Following structural validation, the predicted precursors were analyzed using MatureBayes, a probabilistic model-based tool that predicts the location and sequence of mature miRNAs within precursor hairpins (18). MatureBayes utilizes sequence features and positional information to identify the most likely mature miRNA products, enabling researchers to pinpoint the functional regions of the precursor molecules. To assess the biological relevance of the predicted miRNAs, expression data from publicly available microRNA sequencing (miRNA-seq) datasets were examined. These datasets include profiles from various tissue types, including normal and tumor samples, allowing for comparative analysis of miRNA expression patterns. The presence of the predicted miRNAs in tumor tissues was considered a key indicator of their potential involvement in oncogenic processes (3, 6, 19).
Results: The computational analysis of the MAF gene sequence yielded three distinct microRNA candidates, each exhibiting hallmark features of canonical miRNA precursors. These candidates were characterized by well-defined stem-loop structures, as identified by SSCprofiler, and demonstrated favorable thermodynamic profiles with low MFE values, as confirmed by RNAfold modeling (15–17). The predicted secondary structures were consistent with those observed in known functional miRNAs, suggesting that these molecules may be processed by the endogenous miRNA biogenesis pathway.
MatureBayes analysis further refined the predictions by identifying the precise sequences of the mature miRNA products derived from each precursor (18). These sequences were mapped to the MAF gene locus and found to reside within intronic or untranslated regions, consistent with the genomic architecture of many miRNAs (13). Importantly, sequence alignment across multiple vertebrate species revealed high conservation of these miRNA candidates, indicating evolutionary preservation and potential functional importance (14). Expression profiling using miRNA-seq data provided compelling evidence for the transcriptional activity of the predicted miRNAs. All three candidates were found to be expressed in a variety of tissue types, with notable enrichment in tumor samples (3, 6, 19). This pattern suggests that the miRNAs may play a role in cancer-related gene regulation, possibly by modulating MAF expression or interacting with downstream targets involved in cell proliferation and survival. The consistent expression across diverse biological contexts supports the hypothesis that these miRNAs are not merely transcriptional noise but may have functional significance in oncogenesis.
Conclusion: The findings of this study offer strong evidence for the existence of previously uncharacterized microRNAs within the musculoaponeurotic fibrosarcoma (MAF) gene locus. Through a rigorous bioinformatic approach, three novel miRNA candidates were identified, structurally validated, and shown to be expressed in tumor tissues. These miRNAs exhibit features consistent with functional regulatory molecules, including stable secondary structures, conserved sequences, and tissue-specific expression patterns. The discovery of these miRNAs adds a new dimension to the regulatory landscape of the MAF proto-oncogene. Given MAF's role in cell differentiation, proliferation, and transformation, the presence of embedded miRNAs may contribute to its fine-tuned regulation under physiological and pathological conditions (8–11). These miRNAs could act as internal modulators of MAF activity or participate in broader gene networks that influence tumor behavior. From a clinical perspective, the identification of novel miRNAs associated with MAF opens up exciting possibilities for cancer diagnostics and therapeutics. These miRNAs may serve as biomarkers for MAF-driven malignancies or as targets for RNA-based interventions aimed at restoring normal gene regulation (1–3, 6). Further validation and functional studies are needed to clarify miRNAs’ roles in cancer progression. This research demonstrates the strength of integrative bioinformatics in revealing hidden regulatory layers and emphasizes miRNAs’ influence on oncogenes. Advancing miRNA biology promises innovative strategies for cancer therapy and personalized medicine in the future (2, 4, 6).
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