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Objective: The peptide PNC-27 has been found to kill many different endodermal solid tissue and hematopoietic cancer cells but has no effect on normal cells. The mechanism involves binding to the HDM-2 protein, which is expressed in the membranes of cancer cells but not in normal (untransformed) cells. Our objectives in the current study are to determine 1) if PNC-27 is lethal to squamous cervical epithelial cancer cells but not to untransformed squamous cervical cells; 2) if membrane-bound HDM-2 is expressed uniquely in cervical cancer cells; and 3) whether HDM-2 is stable for detection in different types of preservative solutions.
Methods: We determined dose response curves for incubation of PNC-27 with the human squamous cervical cancer cell line HTB-35 (also called SiHa cells) and with the untransformed human squamous cervical cell line, PCS-480. Cell viability was determined using the MTT and LDH release assays. Finally, slot blots and flow cytometry were used to determine membrane expression of HDM-2 using a polyclonal anti-HDM-2 antibody.
Results: We found that PNC-27 is cytotoxic even at low doses (IC=12.4 μM) to the human HTB-35 cervical cancer squamous epithelial cell line but not to a counterpart normal human PCS-480 cell line. We found that HTB-35 cells express high levels of HDM-2 proteins in their membranes both in cell culture and in alcoholic preservative solutions but that the normal PCS-480 cells do not. Consistent with previous results, the data suggest that cervical cancer cells express HDM-2 in their membranes and that this is the target for PNC-27.
Conclusions: PNC-27 kills cervical squamous cancer but not normal cervical cells due to the unique expression of HDM-2 in the cervical squamous cell membranes. Thus, PNC-27 may be an effective drug against this cancer. Our results further suggest that the expression of membrane-bound HDM-2 on cervical cancer cells is stable both in cell culture media and in alcoholic preservative fluid.
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Biomaterials
September 2025
Key Laboratory of Biopharmaceutical Preparation and Delivery, Institute of Process Engineering, Chinese Academy of Sciences, Beijing, 100190, PR China; University of Chinese Academy of Sciences, Beijing, 100049, PR China. Electronic address:
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BC Cancer, Vancouver, British Columbia, Canada.
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Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland.
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Institute of Computational Science and Technology, Guangzhou University, Guangzhou, China.
MicroRNAs (miRNAs) are critical regulators of gene expression in cancer biology, yet their spatial dynamics within tumor microenvironments (TMEs) remain underexplored due to technical limitations in current spatial transcriptomics (ST) technologies. To address this gap, we present STmiR, a novel XGBoost-based framework for spatially resolved miRNA activity prediction. STmiR integrates bulk RNA-seq data (TCGA and CCLE) with spatial transcriptomics profiles to model nonlinear miRNA-mRNA interactions, achieving high predictive accuracy (Spearman's ρ > 0.
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