Brief Report - (2025) Volume 14, Issue 1
Received: 02-Jan-2025, Manuscript No. Ijdrt-25-163397; Editor assigned: 04-Jan-2025, Pre QC No. P-163397; Reviewed: 17-Jan-2025, QC No. Q-163397; Revised: 23-Jan-2025, Manuscript No. R-163397; Published: 31-Jan-2025, DOI: 10.37421/2277-1506.2025.14.490
Non-coding RNAs, including Micrornas long non-coding RNAs and circular RNAs play fundamental roles in colorectal cancer. miRNAs are short RNA molecules that post-transcriptionally regulate gene expression by targeting messenger RNAs (mRNAs) for degradation or translational repression. Numerous studies have identified dysregulated miRNAs in CRC, with some acting as oncogenes and others as tumor suppressors. Single-cell transcriptomic analysis has allowed for the identification of miRNA expression patterns in distinct tumor cell subpopulations, shedding light on their specific functions in tumor growth and immune evasion. Long non-coding RNAs are another class of ncRNAs implicated in CRC. Unlike miRNAs, lncRNAs are over 200 nucleotides in length and can regulate gene expression through various mechanisms, including chromatin modification, transcriptional regulation, and post-transcriptional control. Some lncRNAs act as Competing Endogenous RNAs by sequestering miRNAs, thereby preventing them from targeting their mRNA counterparts. Single-cell studies have revealed the spatial and temporal expression patterns of lncRNAs within CRC tumors, providing insights into their role in tumor microenvironment interactions, Epithelial-To-Mesenchymal Transition (EMT), and metastatic potential [1].
Circular RNAs represent a unique category of ncRNAs with covalently closed-loop structures that confer stability and resistance to exonuclease degradation. CircRNAs have been shown to function as miRNA sponges, transcriptional regulators, and protein interaction partners. Recent single-cell transcriptomic analyses have identified specific circRNAs enriched in different CRC subtypes, highlighting their potential as biomarkers and therapeutic targets. The ability to resolve circRNA expression at the single-cell level has uncovered novel regulatory networks that contribute to CRC pathogenesis. In addition to characterizing individual ncRNA species, single-cell transcriptomics enables the investigation of their functional interactions within colorectal tumors. By integrating scRNA-seq data with computational modeling and network analysis, researchers can reconstruct ncRNA-mediated gene regulatory networks that drive CRC progression. These approaches have facilitated the identification of ncRNA signatures associated with tumor aggressiveness, drug resistance, and immune evasion, offering potential avenues for precision oncology [2].
The Tumor Microenvironment (TME) plays a critical role in CRC progression, and single-cell transcriptomics has provided new insights into ncRNA-mediated crosstalk between cancer cells and stromal components. Tumor-associated fibroblasts (TAFs), immune cells, and endothelial cells interact with cancer cells through complex signaling pathways regulated by ncRNAs. Single-cell analysis has revealed that specific ncRNAs modulate immune evasion mechanisms, such as PD-L1 expression and T-cell exhaustion, which contribute to immune checkpoint blockade resistance. Understanding these interactions at a single-cell resolution could aid in the development of novel immunotherapeutic strategies targeting ncRNA-mediated pathways. Another promising application of single-cell transcriptomics in CRC research is its role in identifying ncRNA biomarkers for early diagnosis and prognosis. Liquid biopsy approaches leveraging Circulating Tumor Cells (CTCs) and Extracellular Vesicles (EVs) have demonstrated the potential of ncRNAs as minimally invasive biomarkers. Single-cell RNA sequencing of CTCs has uncovered distinct ncRNA expression profiles associated with metastatic dissemination, providing valuable prognostic information. Moreover, the stability of circRNAs in bodily fluids makes them attractive candidates for liquid biopsy-based CRC screening [3].
Despite its numerous advantages, single-cell transcriptomic analysis of ncRNAs in CRC faces several challenges. The low abundance of certain ncRNAs, particularly lncRNAs and circRNAs, can complicate their detection and quantification. Advances in sequencing technologies and computational methods are addressing these limitations by improving sensitivity and accuracy in ncRNA identification. Additionally, integrating single-cell transcriptomic data with other omics approaches, such as single-cell epigenomics and proteomics, will provide a more comprehensive understanding of ncRNA function in CRC. Future research in this field is expected to leverage artificial intelligence and machine learning algorithms to analyze large-scale single-cell transcriptomic datasets. These approaches will enable the identification of novel ncRNA regulatory mechanisms and facilitate the development of targeted therapies. Furthermore, single-cell multi-omics integration will enhance our ability to decipher the interplay between ncRNAs, chromatin modifications, and cellular metabolism in CRC [4,5].
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