| Code | CSB-RA010611A0HU |
| Size | US$210 |
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| Application | Recommended Dilution |
|---|---|
| WB | 1:500-1:5000 |
| IHC | 1:50-1:200 |
| IF | 1:20-1:200 |
| IP | 1:200-1:1000 |
Heterogeneous nuclear ribonucleoprotein K (HNRNPK) serves as a critical regulator of gene expression, functioning at multiple levels from transcription to translation. This multifunctional RNA-binding protein participates in chromatin remodeling, mRNA processing, and signal transduction pathways, making it a key player in cellular responses to stress and proliferation signals. Also known as transformation up-regulated nuclear protein (TUNP), HNRNPK has garnered significant attention in cancer research due to its altered expression patterns in various malignancies.
This recombinant monoclonal antibody, clone 3G7, offers the consistency and reproducibility that demanding research protocols require. Generated against a synthetic peptide derived from human HNRNPK and produced using recombinant technology in rabbit host, this antibody provides sequence-defined specificity with minimal lot-to-lot variation, ensuring your experimental results remain comparable across studies.
Validation data demonstrates robust performance across multiple applications. Western blot analysis confirms reliable detection in diverse human cell lines including HeLa, MCF-7, HepG2, 293T, 293, U87, and SH-SY5Y lysates. The observed band at approximately 60 kDa runs slightly higher than the predicted molecular weight of 49-52 kDa, a shift commonly attributed to post-translational modifications such as phosphorylation or methylation that HNRNPK is known to undergo. Immunohistochemistry validation in human pancreatic and cervical cancer tissues demonstrates clear nuclear staining patterns, while immunofluorescence studies in A549 cells reveal expected nuclear localization. Immunoprecipitation from HepG2 lysates further confirms the antibody's utility for protein interaction studies.
For researchers investigating epigenetics, nuclear signaling, or RNA biology, this antibody provides a versatile tool adaptable to multiple experimental workflows.
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