Nanocarrier mediated entinostat and oxaliplatin combination therapy displayed enhanced efficacy against pancreatic cancer.

Pancreatic cancer is the third leading cause of cancer-related death in the United States, with a 5-year survival rate of only 12%. The poor prognosis of pancreatic cancer is primarily attributed to the lack of early detection, the aggressiveness of the disease, and its resistance to conventional chemotherapeutics. The use of combination chemotherapy targeting different key pathways has emerged as a potential strategy to minimize drug resistance while improving therapeutic outcomes. Here, we evaluated a novel approach to treating pancreatic cancer using entinostat (ENT), a selective class I and IV HDAC inhibitor, and oxaliplatin (OXP) administered at considerably lower dosages. Combination therapy exhibited strong synergistic interaction against human (PANC-1) and murine (KPC) pancreatic cancer cells. As expected, ENT treatment enhanced acetylated histone H3 and H4 expression in treated cells, which was even augmented in the presence of OXP. Similarly, cells treated with a combination therapy showed higher expression of cleaved caspase 3 and increased apoptosis compared to monotherapy. To further improve the efficacy of the combination treatment, we encapsulated OXP and ENT into bovine serum albumin and poly(lactic-co-glycolic) acid nanoparticles. Both nanocarriers showed suitable physicochemical properties with respect to size, charge, polydispersity index, and loading. Besides, the combination of OXP and ENT nanoparticles showed similar or even better synergistic effects compared to free drugs during in vitro cytotoxicity and colony formation assays towards pancreatic cancer cells.

Advancements in Circulating Tumor Cell Research: Bridging Biology and Clinical Applications.

Circulating tumor cells (CTCs) are cells released from the primary and metastatic tumor and intravasate into the blood or lymphatic vessels, where they are transported to distant sites and act as seeds that initiate cancer metastases or the development of further lesions. Recent advances in CTC research have shown their relevance as prognostic markers for early and metastatic disease detection, predictive biomarkers for relapse, and response to medical intervention or therapy. The rapidly evolving landscape of CTC biology has opened new avenues for understanding cancer progression, metastasis, and treatment response. Additionally, translating these findings into clinical applications holds promise for improving cancer diagnostics, prognosis, and personalized therapeutic strategies. This review discusses the significance of CTCs in cancer research and their associated challenges. We explore recent developments in the detection and characterization of CTCs and their implications in cancer research and clinical practice.

Advancements in Preclinical Models of Pancreatic Cancer.

ABSTRACT: Pancreatic cancer remains one of the deadliest of all cancer types with a 5-year overall survival rate of just 12%. Preclinical models available for understanding the disease pathophysiology have evolved significantly in recent years. Traditionally, commercially available 2-dimensional cell lines were developed to investigate mechanisms underlying tumorigenesis, metastasis, and drug resistance. However, these cells grow as monolayer cultures that lack heterogeneity and do not effectively represent tumor biology. Developing patient-derived xenografts and genetically engineered mouse models led to increased cellular heterogeneity, molecular diversity, and tissues that histologically represent the original patient tumors. However, these models are relatively expensive and very timing consuming. More recently, the advancement of fast and inexpensive in vitro models that better mimic disease conditions in vivo are on the rise. Three-dimensional cultures like organoids and spheroids have gained popularity and are considered to recapitulate complex disease characteristics. In addition, computational genomics, transcriptomics, and metabolomic models are being developed to simulate pancreatic cancer progression and predict better treatment strategies. Herein, we review the challenges associated with pancreatic cancer research and available analytical models. We suggest that an integrated approach toward using these models may allow for developing new strategies for pancreatic cancer precision medicine.