Hussain Mohammad Shabir, Vij Puneet, Kotnala Sudhir, Ahmad Shadab, Chauhan Subhash C, Tripathi Manish K
Medicine and Oncology ISU, School of Medicine, The University of Texas Rio Grande Valley, McAllen, TX 78504, USA.
South Texas Center of Excellence in Cancer Research, School of Medicine, The University of Texas Rio Grande Valley, McAllen, TX 78504, USA.
Targets (Basel). 2025 Sep;3(3). doi: 10.3390/targets3030027. Epub 2025 Aug 11.
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.
长链非编码RNA(lncRNAs)越来越被认为是癌症中基因表达和细胞信号传导的关键调节因子。它们的功能主要通过与特定蛋白质伙伴的相互作用来介导,这些蛋白质伙伴可调节染色质结构、表观遗传重塑、转录和信号转导。在本综述中,我们探讨了lncRNA相关蛋白质的蛋白质组学表征的报告和策略,特别强调基于高通量液相色谱-质谱联用(LC-MS)的技术。基于亲和力的方法,如RNA下拉、ChIRP MS、RAP-MS、BioID-MS和SILAC-MS,能够灵敏且特异地绘制lncRNA与蛋白质复合物的图谱。这些方法揭示了癌症特异性蛋白质组学特征、翻译后修饰以及对肿瘤生物学的机制性见解。使用无标记定量、生物素化和交联策略进一步提高了动态RNA-蛋白质网络的分辨率。生物信息学分析后的验证工具,如蛋白质印迹法、免疫组织化学、免疫荧光和酶联免疫吸附测定,用于对研究结果进行优先级排序和确认。从肝细胞癌到结直肠癌和前列腺癌的lncRNA相关蛋白质谱分析的候选生物标志物,有望识别出具有临床可操作性的生物标志物和治疗靶点。本综述强调了lncRNA蛋白质研究的转化相关性,并倡导在肿瘤学研究中更广泛地采用这些研究。在LC-MS工作流程中,与lncRNAs结合的蛋白质被酶解成肽段,通过纳升液相色谱进行分离,并使用高分辨率串联质谱进行分析。无标记或同位素标记方法对差异富集进行定量,随后进行生物信息学驱动的通路注释。