Chemotherapy-induced peripheral neurotoxicity (CIPN) is a severe dose-limiting adverse event of chemotherapy. Presently, the mechanism underlying the induction of CIPN remains unclear, and no effective treatment is available. In this study, through metabolomics analyses, we found that nab-paclitaxel therapy markedly increased serum serotonin [5-hydroxtryptamine (5-HT)] levels in both cancer patients and mice compared to the respective controls. Furthermore, nab-paclitaxel-treated enterochromaffin (EC) cells showed increased 5-HT synthesis, and serotonin-treated Schwann cells showed damage, as indicated by the activation of CREB3L3/MMP3/FAS signaling. Venlafaxine, an inhibitor of serotonin and norepinephrine reuptake, was found to protect against nerve injury by suppressing the activation of CREB3L3/MMP3/FAS signaling in Schwann cells. Remarkably, venlafaxine was found to significantly alleviate nab-paclitaxel-induced CIPN in patients without affecting the clinical efficacy of chemotherapy. In summary, our study reveals that EC cell-derived 5-HT plays a critical role in nab-paclitaxel-related neurotoxic lesions, and venlafaxine co-administration represents a novel approach to treating chronic cumulative neurotoxicity commonly reported in nab-paclitaxel-based chemotherapy.
Paclitaxel/toxicity* ; Animals ; Albumins/adverse effects* ; Serotonin/metabolism* ; Mice ; Humans ; Male ; Female ; Venlafaxine Hydrochloride/therapeutic use* ; Neurotoxicity Syndromes/metabolism* ; Middle Aged ; Schwann Cells/metabolism* ; Peripheral Nervous System Diseases/drug therapy* ; Antineoplastic Agents

The development of safe and effective carriers is crucial for improving the in vivo stability of siRNA drugs and facilitating their clinical translation. Chitosan (CS), a natural cationic polymer, shows great potential in nucleic acid drug delivery. To optimize the physicochemical properties of CS/siRNA nanoparticles (NPs) and increase their siRNA delivery efficacy, in this study, hyaluronic acid (HA) was added into CS to form stable complex NPs through electrostatic interactions. The HA component is able to target the CD44 receptors on the surface of tumor cells, facilitating efficient siRNA delivery. First, we systematically investigated the effects of the molecular weights and mass ratio of CS and HA on the physicochemical properties of CS/HA NPs. The results showed that at HA: CS mass ratios of approximately 5:5 and 6:4, the complex NPs exhibited small particle sizes, narrow size distribution, and high storage stability. Under similar conditions, the size of CS/HA NPs increased with the increase in the molecular weights of CS and HA. Based on these findings, suitable conditions were selected to prepare CS/HA NPs for siRNA delivery. Cell experiments demonstrated that the introduction of HA effectively reduced the cytotoxicity of the CS delivery system and enhanced the NP uptake. The CS/HA/siRNA NPs achieved 50% to 60% silencing of the luciferase gene in HeLa-Luc cells. CS/HA NPs formed smaller nanoparticles with siRNA than pure CS and mediated specific interactions with tumor cells via HA, leading to efficient siRNA delivery. These findings provide valuable insights into the construction of natural polymer composite nanoparticles for application in siRNA delivery.
Hyaluronic Acid/chemistry* ; Chitosan/chemistry* ; RNA, Small Interfering/administration & dosage* ; Nanoparticles/chemistry* ; Humans ; Particle Size ; HeLa Cells ; Hyaluronan Receptors

Colorectal cancer is one of the common malignant tumors of the digestive tract.With the popularization of screening methods and advancement of endoscopic technology,an increasing number of T1 stage colorectal cancers can be discovered.Accurately predicting lymph node metastasis risk is significantly important for guiding clinical treatment decisions,reducing complications and mortality.Current research on risk factors for lymph node metastasis in T1 stage colorectal cancer covers multiple aspects including clinical pathological features,molecular phenotypes and genetic characteristics.Some studies have built prediction models by integrating these factors,which show higher sensitivity,specificity and accuracy compared to current clinical guidelines.These models provide valuable experience for clinical practice.