Phenotypically Screened Carbon Nanoparticles for Enhanced Combinatorial Therapy in Triple Negative Breast Cancer

Taylor Kampert, Santosh K. Misra, Indrajit Srivastava, Indu Tripathi, Dipanjan Pan

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Introduction: Triple negative breast cancer (TNBC) is a highly aggressive type of breast cancer with high resistance to current standard therapies. We demonstrate that phenotypically stratified carbon nanoparticle is highly effective in delivering a novel combinatorial triple drug formulation for synergistic regression of TNBC in vitro and in vivo. Method: The combinatorial formulation is comprised of repurposed inhibitors of STAT3 (nifuroxazide), topoisomerase-II-activation-pathway (amonafide) and NFκb (pentoxifylline). Synergistic effect of drug combination was established in a panel of TNBC-lines comprising mesenchymal-stem-like, mesenchymal and basal-like cells along with non-TNBC-cells. The delivery of combinatorial drug formulation was achieved using a phenotypically screened carbon nanoparticles for TNBC cell lines. Results: Results indicated a remarkable five-fold improvement (IC50-6.75 µM) from the parent drugs with a combinatorial index <1 in majority of the TNBC cells. Multi-compartmental carbon nanoparticles were then parametrically assessed based on size, charge (positive/negative/neutral) and chemistry (functionalities) to study their likelihood of crossing endocytic barriers from phenotypical standpoint in TNBC lines. Interestingly, a combination of clathrin mediated, energy and dynamin dependent pathways were predominant for sulfonated nanoparticles, whereas pristine and phospholipid particles followed all the investigated endocytic pathways. Conclusions: An exactitude ‘omics’ approach helps to predict that phospholipid encapsulated-particles will predominantly accumulate in TNBC comprising the drug-‘cocktail’. We investigated the protein expression effects inducing synergistic effect and simultaneously suppressing drug resistance through distinct mechanisms of action.

Original languageEnglish (US)
Pages (from-to)371-386
Number of pages16
JournalCellular and Molecular Bioengineering
Volume10
Issue number5
DOIs
StatePublished - Oct 1 2017

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • General Biochemistry, Genetics and Molecular Biology

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