Antidepressant Sertraline Synergistically Enhances Paclitaxel Efficacy by Inducing Autophagy in Colorectal Cancer Cells.
Leping HeYuxi TianQingqing LiuJiaolin BaoRen-Bo DingPublished in: Molecules (Basel, Switzerland) (2024)
Colorectal cancer (CRC) is the second leading cause of cancer-related death worldwide. It is important to discover new therapeutic regimens for treating CRC. Depression is known to be an important complication of cancer diseases. Repurposing antidepressants into anticancer drugs and exploring the combinational efficacy of antidepressants and chemotherapy are potentially good options for developing CRC treatment regimens. In this study, sertraline, an antidepressant drug, and paclitaxel, an anticancer drug, were chosen to study their antitumor effects in the treatment of colorectal cancer, alone or in combination, and to explore their underlying mechanisms. The data showed that sertraline exerted a dose-dependent cytotoxic effect on MC38 and CT26 colorectal cancer cell lines with IC 50 values of 10.53 μM and 7.47 μM, respectively. Furthermore, sertraline synergistically sensitized chemotherapeutic agent paclitaxel efficacy in CRC cells with combination index (CI) values at various concentrations consistently lower than 1. Sertraline remarkably augmented paclitaxel-induced autophagy by increasing autophagosome formation indicated by elevated LC3-II/I ratio and promoting autophagic flux by degrading autophagy cargo receptor SQSTM1/p62, which may explain the synergistically cytotoxic effect of sertraline and paclitaxel combination therapy on CRC cells. This study provides important evidence to support repurposing sertraline as an anticancer agent and suggests a novel combinational regimen for effectively treating CRC as well as in the simultaneous treatment of CRC and depression.
Keyphrases
- combination therapy
- cell death
- major depressive disorder
- induced apoptosis
- oxidative stress
- signaling pathway
- cell cycle arrest
- depressive symptoms
- computed tomography
- emergency department
- bipolar disorder
- machine learning
- drug induced
- magnetic resonance imaging
- cell proliferation
- magnetic resonance
- squamous cell carcinoma
- radiation therapy
- artificial intelligence
- mass spectrometry
- locally advanced
- papillary thyroid
- diabetic rats
- image quality
- contrast enhanced