Next generation sequencing and functional pathway analysis to understand the mechanism of action of copper-tolfenamic acid against pancreatic cancer cells

Myrna Hurtado, Laszlo Prokai, Umesh T. Sankpal, Blair Levesque, Rajasekhar Maram, Jaya Chhabra, Deondra T. Brown, Raj K. Gurung, Alvin A. Holder, Jamboor K. Vishwanatha, Riyaz Basha

Research output: Contribution to journalArticle

Abstract

Anti-cancer activity of tolfenamic acid (TA) in preclinical models for pancreatic cancer (PaCa) is well established. Since the dosage for anti-cancer actions of TA is rather high, we recently demonstrated that IC50 values of Copper-TA are 30–80% less than TA in 12 cancer cell lines. This study elucidates the underlying mechanisms of Copper-TA in PaCa cells. Control and Copper-TA (IC50) treated PaCa cells were processed by next-generation sequencing (NGS) to determine differentially expressed genes using HTG EdgeSeq Oncology Biomarker panel. Ingenuity Pathway Analysis (IPA®) was used to identify functional significance of altered genes. The conformational studies for assessing the expression of key regulators and genes were conducted by Western blot and qPCR. IPA® identified several networks, regulators, as well as molecular and cellular functions associated with cancer. The top 5 molecular and cellular functions affected by Cu-TA treatment were cell death and survival, cellular development, cell growth and proliferation, cell cycle and cellular movement. The expression of top upstream regulators was confirmed by Western blot analysis while qPCR results of selected genes demonstrated that Copper-TA is efficacious at lower doses than TA. Results suggest that Copper-TA alters genes/key regulators associated with cancer and potentially serve as an effective anti-cancer agent.

Original languageEnglish
Pages (from-to)155-164
Number of pages10
JournalProcess Biochemistry
Volume89
DOIs
StatePublished - Feb 2020

Keywords

  • Apoptosis
  • Copper-tolfenamic acid
  • Gene expression
  • Next generation sequencing
  • Pancreatic cancer
  • Pathway analysis

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