Abstract

Cancer-specific drug delivery represents an attractive approach to preventing undesirable side effects and increasing the accumulation of the drug in tumors. The surface modification of selenium nanoparticles (SeNPs) with targeting moieties thus represents an effective strategy for cancer therapy. In this study, SeNPs were modified with folic acid (FA), whose receptors were overexpressed on the surface of cancer cells, including human cervical carcinoma HeLa cells, to fabricate tumor-targeting delivery carrier FA-SeNPs nanoparticles. Then, the anticancer drug doxorubicin (DOX) was loaded onto the surface of the FA-SeNPs for improving the antitumor efficacy of DOX in human cervical carcinoma therapy. The chemical structure characterization of FA-Se@DOX showed that DOX was successfully loaded to the surface of FA-SeNPs to prepare FA-Se@DOX nanoparticles. FA-Se@DOX exhibited significant cellular uptake in human cervical carcinoma HeLa cells (folate receptor overexpressing cells) in comparison with lung cancer A549 cells (folate receptor deficiency cells), and entered HeLa cells mainly by the clathrin-mediated endocytosis pathway. Compared to free DOX or Se@DOX at the equivalent dose of DOX, FA-Se@DOX showed obvious activity to inhibit HeLa cells’ proliferation and induce the apoptosis of HeLa cells. More importantly, FA-Se@DOX could specifically accumulate in the tumor site, which contributed to the significant antitumor efficacy of FA-Se@DOX in vivo. Taken together, FA-Se@DOX may be one novel promising drug candidate for human cervical carcinoma therapy.

Highlights

  • Human cervical cancer mainly resulted from human papillomavirus (HPV) is one of the most popular cancers in women’s health worldwide, and it is the fifth leading cause of cancer deaths among females [1]

  • A number of strategies using nanoparticles have been developed for cancer therapy, and most of these therapies are based on the enhanced permeation and retention (EPR) effect [8]

  • The expression of Ki67 protein related with tumor cell growth and apoptosis-related proteins pp53 and caspase-3 was tested via immunohistochemistry

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Summary

Introduction

Human cervical cancer mainly resulted from human papillomavirus (HPV) is one of the most popular cancers in women’s health worldwide, and it is the fifth leading cause of cancer deaths among females [1]. Doxorubicin (DOX) is one very common and effective chemotherapeutic drug for cancer therapy [4]. Clinical application of DOX is limited by its poor water solubility and off-target side effects [5]. ((AA)) PPaarrttiiccllee ssiizzee ddiissttrriibbuuttiioonn ooff FFAA--SSee@@DDOOXX nnaannooppaarrttiicclleess.. (((BBB))) RRReeeppprrreeessseeennntttaaatttiiivvveee tttrrraaannnsssmmmiiissssssiiiooonnn eeellleeeccctttrrrooonnn mmiiccrroossccooopppyyy ((TTEEMM)) iimmaaggee ooff FFFAAA---SSSeee@@@DDOOXX nnaannooppaaarrrtttiiicccllleeesss... TThheerreelleeaasseepprrooffiilleess ooff DDOOXX ffrroommFFAA--SSee@@DDOOXX nnaannooppaarrttiicclleess wweerree sshhoowwnn iinn FFiigguurree 44AA;; tthheerree wwaassaannootteewwoorrtthhyybbuurrssttddrruuggrreelleeaassee dduurriinngg tthhee iinniittiiaall 44 hh iinn bbootthh ppHH vvaalluueess. FCAe-Slle@wDouOnXdS-huepaplriensgs tahsesaMyiwgraatsiountialinzdedIntvoasaisosnesosf HwehLeathCeerllsFA-Se@DOX could effectively inhibit the migration of cancer cells. Cell wound-healing assay was utilized to assess whether FA-Se@DOX could effectively inhibit the migration of cancer cells. The wound-healing assay results showed that FA-Se@DOX decreased the migration of HeLa cells over a 12-h interval. FA-Se@DOX decreased the migration of HeLa cells over a 12-h interval. FFigiguurree1100..HH&&EEaannaalylysesessoof fhheeaartr,t,lilviveer,r,ssppleleeenn, ,lulunngg, ,aannddkkididnneeyyaaftfeterrtrtereaatmtmeennt twwitihthsasalilnine,e,DDOOXX, , SSee@@DDOOXX, ,aannddFFAA-S-See@@DDOOXX, ,rreessppeecctitviveelyly..SSccaalleebbaarriiss5500μμmm

Materials
Cellular Uptake Study
In Vitro Release of DOX
MTT Assay
Wound Healing Assay
Transwell Assay
Flow Cytometry Assay
3.11. Xenograft Mouse Model
3.13. Statistical Analysis
Findings
Conclusions
Full Text
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