Approaches for Identifying LncRNA-Associated Proteins for Therapeutic Targets and Cancer Biomarker Discovery

Long non-coding RNAs (lncRNAs) are increasingly recognized as key regulators of gene expression and cellular signaling in cancer. Their functions are primarily mediated through interactions with specific protein partners that modulate chromatin structure, epigenetic remodeling, transcription, and signal transduction. In this review, we explore reports and strategies for the proteomic characterization of lncRNA-associated proteins, particularly emphasizing high-throughput liquid chromatography-mass spectrometry (LC-MS)-based techniques. Affinity-based methods such as RNA pull-down, ChIRP MS, RAP-MS, BioID-MS, and SILAC-MS enable sensitive and specific mapping of lncRNA and protein complexes. These approaches reveal cancer-specific proteomic signatures, post-translational modifications, and mechanistic insights into tumor biology. The use of label-free quantification, bituminization, and crosslinking strategies further enhances the resolution of dynamic RNA-protein networks. Validation tools following bioinformatic analyses, such as Western blotting, immunohistochemistry, immunofluorescence, and ELISA, are used to prioritize and confirm findings. Candidate biomarkers from hepatocellular carcinoma to colorectal and prostate cancers, profiling lncRNA-associated proteins, hold promise for identifying clinically actionable biomarkers and therapeutic targets. This review highlights the translational relevance of lncRNA protein studies and advocates for their broader adoption in oncological research. In LC-MS workflows, proteins bound to lncRNAs are enzymatically digested into peptides, separated via nano-LC, and analyzed using high-resolution tandem MS. Label-free or isotope-labeled methods quantify differential enrichment, followed by bioinformatics-driven pathway annotation.