Effective combinations of anti-cancer and targeted drugs for pancreatic cancer treatment

Exploring the therapeutic potential of rabdoternin E in lung cancer treatment: Targeting the ROS/p38 MAPK/JNK signaling pathway

Lung cancer has the highest incidence and mortality rates of all cancer types in China and therefore represents a serious threat to human health. In the present study, the mechanism of rabdoternin E against the proliferation of the lung cancer cell line A549 was explored. It was found that rabdoternin E caused the accumulation of large amounts of reactive oxygen species (ROS), promoted cell S phase arrest by reducing the expression of CDK2 and cyclin A2, induced apoptosis by increasing the Bax/Bcl‑2 ratio and promoted the phosphorylation of proteins in the ROS/p38 MAPK/JNK signaling pathway, which is associated with apoptosis and ferroptosis. In addition, it was also found that Z‑VAD‑FMK (an apoptosis inhibitor), ferrostatin‑1 (ferroptosis inhibitor) and N‑acetylcysteine (a ROS inhibitor) could partially or greatly reverse the cytotoxicity of rabdoternin E to A549 cells. Similarly, NAC (N‑acetylcysteine) treatment notably inhibited the rabdoternin E‑stimulated p38 MAPK and JNK activation. Furthermore, in vivo experiments in mice revealed that Rabdoternin E markedly reduced tumor volume and weight and regulated the expression levels of apoptosis and ferroptosis‑related proteins (including Ki67, Bcl‑2, Bax, glutathione peroxidase 4, solute carrier family 7 member 11 and transferrin) in the tumor tissues of mice. Histopathological observation confirmed that the number of tumor cells decreased markedly after administration of rabdoternin E. Taken together, rabdoternin E induced apoptosis and ferroptosis of A549 cells by activating the ROS/p38 MAPK/JNK signaling pathway. Therefore, the results of the present study showed that rabdoternin E is not toxic to MCF‑7 cells (normal lung cells), had no significant effect on body weight and was effective and therefore may be a novel therapeutic treatment for lung cancer.

An Efficient Fabrication Approach for Multi-Cancer Responsive Chemoimmuno Co-Delivery Nanoparticles

Background/Objectives: Cancer remains one of the leading causes of death, with breast, liver, and pancreatic cancers significantly contributing to this burden. Traditional treatments face issues including dose-limiting toxicity, drug resistance, and limited efficacy. Combining therapeutic agents can enhance effectiveness and reduce toxicity, but separate administration often leads to inefficiencies due to differing pharmacokinetics and biodistribution. Co-formulating hydrophobic chemotherapeutics such as paclitaxel (PTX) and hydrophilic immunologic agents such as polyinosinic-polycytidylic acid (Poly IC) is particularly challenging due to their distinct physicochemical properties. This study presents a novel and efficient approach for the co-delivery of PTX and Poly IC using chitosan-based nanoparticles. Method: Chitosan-PEG (CP) nanoparticles were developed to encapsulate both PTX and Poly IC, overcoming their differing physicochemical properties and enhancing therapeutic efficacy. Results: With an average size of ~100 nm, these nanoparticles facilitate efficient cellular uptake and stability. In vitro results showed that CP-PTX-Poly IC nanoparticles significantly reduced cancer cell viability in breast (4T1), liver (HepG2), and pancreatic (Pan02) cancer types, while also enhancing dendritic cell (DC) maturation. Conclusions: This dual-modal delivery system effectively combines chemotherapy and immunotherapy, offering a promising solution for more effective cancer treatment and improved outcomes.

Prediction of synergistic gemcitabine-based combination treatment through a novel tumor stemness biomarker NANOG in pancreatic cancer

Gemcitabine remains a first-class chemotherapeutic drug for pancreatic cancer. However, due to the rapid development of gemcitabine resistance in pancreatic cancer, gemcitabine alone or in combination with other anti-cancer drugs only showed limited effect in the clinic. It is extremely challenging to effectively and efficiently determine the optimal drug regimens. Thus, identification of appropriate prediction biomarkers is critical for the rational design of gemcitabine-based therapeutic options. Herein, a pancreatic cancer stem cell (PCSC) model exhibiting chemoresistance to gemcitabine was used to test the activity of clinical cancer drugs in the presence or absence of gemcitabine. As determined by combinatorial treatment, several types of drugs resensitized gemcitabine-resistant PCSCs to gemcitabine, with sorafenib (EGFR inhibitor)/gemcitabine and sunitinib (TBK1 inhibitors)/gemcitabine drug combinations being the most preferred treatments for PCSCs. Following the validation of the PCSC model by an antibody array test of 15-gene expression of stemness biomarkers, NANOG showed markedly different expression in PCSCs compared to the parental cells. From comprehensive analysis of stem cell index versus combination index, a stemness-related correlation model was successfully constructed to demonstrate the correlation between NANOG expression and synergism. Cancer cell stemness was ascertained to be highly relevant to NANOG overexpression that can be abrogated by synergized gemcitabine-drug combinations. Therefore, NANOG works as a therapeutic biomarker for predicating efficient combinatorial treatment of gemcitabine in pancreatic cancer.

Establishment of a prognostic model for pancreatic cancer based on vesicle-mediated transport protein-related genes

This study attempted to build a prognostic riskscore model for pancreatic cancer (PC) patients based on vesicle-mediated transport protein-related genes (VMTGs). We initially conducted differential expression analysis and Cox regression analysis, followed by the construction of a riskscore model to classify PC patients into high-risk (HR) and low-risk (LR) groups. The GEO GSE62452 dataset further validated the model. Kaplan-Meier survival analysis was employed to analyze the survival rate of the HR group and LR group. Cox analysis confirmed the independent prognostic ability of the riskscore model. Additionally, we evaluated immune status in both HR and LR groups, utilizing data from the GDSC database to predict drug response among PC patients. We identified six PC-specific genes from 724 VMTGs. Survival analysis revealed that the survival rate of the HR group was lower than that of the LR group (P<0.05). Cox analysis confirmed that the prognostic riskscore model could independently predict the survival status of PC patients (P<0.001). Immunological analysis revealed that the ESTIMATE score, immune score, and stroma score of the HR group were considerably lower than those of the LR group, and the tumor purity score of the HR group was higher. The IC50 values of Gemcitabine, Irinotecan, Oxaliplatin, and Paclitaxel in the LR group were considerably lower than those in the HR group (P<0.001). In summary, the VMTG-based prognostic riskscore model could stratify PC risk and effectively predict the survival of PC patients.

Hawthorn with "homology of medicine and food": a review of anticancer effects and mechanisms

Over the past few years, there has been a gradual increase in the incidence of cancer, affecting individuals at younger ages. With its refractory nature and substantial fatality rate, cancer presents a notable peril to human existence and wellbeing. Hawthorn, a medicinal food homology plant belonging to the Crataegus genus in the Rosaceae family, holds great value in various applications. Due to its long history of medicinal use, notable effects, and high safety profile, hawthorn has garnered considerable attention and plays a crucial role in cancer treatment. Through the integration of modern network pharmacology technology and traditional Chinese medicine (TCM), a range of anticancer active ingredients in hawthorn have been predicted, identified, and analyzed. Studies have shown that ingredients such as vitexin, isoorientin, ursolic acid, and maslinic acid, along with hawthorn extracts, can effectively modulate cancer-related signaling pathways and manifest anticancer properties via diverse mechanisms. This review employs network pharmacology to excavate the potential anticancer properties of hawthorn. By systematically integrating literature across databases such as PubMed and CNKI, the review explores the bioactive ingredients with anticancer effects, underlying mechanisms and pathways, the synergistic effects of drug combinations, advancements in novel drug delivery systems, and ongoing clinical trials concerning hawthorn's anticancer properties. Furthermore, the review highlights the preventive health benefits of hawthorn in cancer prevention, offering valuable insights for clinical cancer treatment and the development of TCM with anticancer properties that can be used for both medicinal and edible purposes.

HANSynergy: Heterogeneous Graph Attention Network for Drug Synergy Prediction

Drug synergy therapy is a promising strategy for cancer treatment. However, the extensive variety of available drugs and the time-intensive process of determining effective drug combinations through clinical trials pose significant challenges. It requires a reliable method for the rapid and precise selection of drug synergies. In response, various computational strategies have been developed for predicting drug synergies, yet the exploitation of heterogeneous biological network features remains underexplored. In this study, we construct a heterogeneous graph that encompasses diverse biological entities and interactions, utilizing rich data sets from sources, such as DrugCombDB, PubChem, UniProt, and cancer cell line encyclopedia (CCLE). We initialize node feature representations and introduce a novel virtual node to enhance drug representation. Our proposed method, the heterogeneous graph attention network for drug-drug synergy prediction (HANSynergy), has been experimentally validated to demonstrate that the heterogeneous graph attention network can extract key node features, efficiently harness the diversity of information, and further enhance network functionality through the incorporation of a multihead attention mechanism. In the comparative experiment, the highest accuracy (Acc) and area under the curve (AUC) are 0.877 and 0.947, respectively, in DrugCombDB_early data set, demonstrating the superiority of HANSynergy over the competing methods. Moreover, protein-protein interactions are important in understanding the mechanism of action of drugs. The heterogeneous attention mechanism facilitates protein-protein interaction analysis. By analyzing the changes of attention weight before and after heterogeneous network training, we investigated proteins that may be associated with drug combinations. Additionally, case studies align our findings with existing research, underscoring the potential of HANSynergy in drug synergy prediction. This advancement not only contributes to the burgeoning field of drug synergy prediction but also holds the potential to provide valuable insights and uncover new drug synergies for combating cancer.

Gemcitabine effects on tumor microenvironment of pancreatic ductal adenocarcinoma: Special focus on resistance mechanisms and metronomic therapies

Pancreatic ductal adenocarcinoma (PDAC) is considered one of the deadliest malignancies, with dismal survival rates and extremely prevalent chemoresistance. Gemcitabine is one of the primary treatments used in treating PDACs, but its benefits are limited due to chemoresistance, which could be attributed to interactions between the tumor microenvironment (TME) and intracellular processes. In preclinical models, certain schedules of administration of gemcitabine modulate the TME in a manner that does not promote resistance. Metronomic therapy constitutes a promising strategy to overcome some barriers associated with current PDAC treatments. This review will focus on gemcitabine's mechanism in treating PDAC, combination therapies, gemcitabine's interactions with the TME, and gemcitabine in metronomic therapies.

Identification of a chemoresistance-related prognostic gene signature by comprehensive analysis and experimental validation in pancreatic cancer

Background

Chemoresistance is a major hurdle to improving the prognosis of pancreatic cancer (PC). This study aimed to identify key genes regulating chemoresistance and develop a chemoresistance-related gene signature for prognosis prediction.

Methods

A total of 30 PC cell lines were subtyped according to gemcitabine sensitivity data from the Cancer Therapeutics Response Portal (CTRP v2). Differentially expressed genes (DEGs) between gemcitabine-resistant and gemcitabine-sensitive cells were subsequently identified. These upregulated DEGs associated with prognostic values were incorporated to build a LASSO Cox risk model for The Cancer Genome Atlas (TCGA) cohort. Four datasets (GSE28735, GSE62452, GSE85916, and GSE102238) from the Gene Expression Omnibus (GEO) were used as an external validation cohort. Then, a nomogram was developed based on independent prognostic factors. The responses to multiple anti-PC chemotherapeutics were estimated by the "oncoPredict" method. Tumor mutation burden (TMB) was calculated using the "TCGAbiolinks" package. Analysis of the tumor microenvironment (TME) was performed using the "IOBR" package, while the TIDE and "easier" algorithms were employed to estimate immunotherapy efficacy. Finally, RT-qPCR, Western blot and CCK-8 assays were conducted to validate the expression and functions of ALDH3B1 and NCEH1.

Results

A five-gene signature and a predictive nomogram were developed from six prognostic DEGs, including EGFR, MSLN, ERAP2, ALDH3B1, and NCEH1. Bulk and single-cell RNA sequencing analyses indicated that all five genes were highly expressed in tumor samples. This gene signature was not only an independent prognostic factor but also a biomarker forecasting chemoresistance, TMB, and immune cells. In vitro experiments suggested that ALDH3B1 and NCEH1 were involved in PC progression and gemcitabine chemoresistance.

Conclusion

This chemoresistance-related gene signature links prognosis with chemoresistance, TMB, and immune features. ALDH3B1 and NCEH1 are two promising targets for treating PC.

Feasibility of Co-Targeting HER3 and EpCAM Using Seribantumab and DARPin-Toxin Fusion in a Pancreatic Cancer Xenograft Model

Pancreatic cancer (PC) is one of the most aggressive malignancies. A combination of targeted therapies could increase the therapeutic efficacy in tumors with heterogeneous target expression. Overexpression of the human epidermal growth factor receptor type 3 (HER3) and the epithelial cell adhesion molecule (EpCAM) in up to 40% and 30% of PCs, respectively, is associated with poor prognosis and highlights the relevance of these targets. Designed ankyrin repeat protein (DARPin) Ec1 fused with the low immunogenic bacterial toxin LoPE provides specific and potent cytotoxicity against EpCAM-expressing cancer cells. Here, we investigated whether the co-targeting of HER3 using the monoclonal antibody seribantumab (MM-121) and of EpCAM using Ec1-LoPE would improve the therapeutic efficacy in comparison to the individual agents. Radiolabeled ^99mTc(CO)₃-Ec1-LoPE showed specific binding with rapid internalization in EpCAM-expressing PC cells. MM-121 did not interfere with the binding of Ec1-LoPE to EpCAM. Evaluation of cytotoxicity indicated synergism between Ec1-LoPE and MM-121 in vitro. An experimental therapy study using Ec1-LoPE and MM-121 in mice bearing EpCAM- and HER3-expressing BxPC3 xenografts demonstrated the feasibility of the therapy. Further development of the co-targeting approach using HER3 and EpCAM could therefore be justified.

Discussion on gemcitabine combined with targeted drugs in the treatment of pancreatic cancer

Pancreatic cancer is a malignant tumor with poor prognosis. The treatment of pancreatic cancer depends on the tumor stage and type, and includes local treatment (surgery, radiotherapy and ablation intervention) and systemic therapy (chemotherapy, targeted therapy and immunotherapy). We read with great interest the review “Effective combinations of anti-cancer and targeted drugs for pancreatic cancer treatment” published on World J Gastroenterol and intended to share some of our perspectives in pancreatic cancer treatment. This review presents the therapeutic effects of the combination of gemcitabine and targeted drugs, which gives us a deeper insight into the combination treatments for pancreatic cancer.

Comparison of three exercise interventions with and without gemcitabine treatment on pancreatic tumor growth in mice: No impact on tumor infiltrating lymphocytes

Exercise has been shown to slow pancreatic tumor growth, but whether exercise interventions of differing volume or intensity yield differential effects on tumor outcomes is unknown. In this study, we compared three exercise training interventions implemented with and without chemotherapy on pancreatic tumor growth in mice. Methods: Male C57BL/6 mice (6-8 weeks old) were subcutaneously inoculated with pancreatic ductal adenocarcinoma tumor cells (PDAC 4662). Upon tumor detection, mice received gemcitabine 15 mg/kg intraperitoneally 3 days/week and were assigned to exercise: high volume continuous exercise (HVCE), low volume continuous exercise (LVCE), high intensity interval training (HIIT), or sedentary (SED). HVCE ran at 12 m/min for 45 min and LVCE for 15 min, 5 days/week. HIIT ran 1-min at 20 m/min, followed by 1-min walking at 8 m/min for 20 total intervals, 3 days/week. SED did not run. Additional sets of inoculated mice were assigned to the exercise interventions but did not receive gemcitabine. Tumor volume was measured every other day for 2 weeks; tumor-infiltrating lymphocytes were assessed by flow cytometry 3-week post-inoculation. Results: Tumor growth did not differ between groups that received gemcitabine (F(3, 34) = 1.487; p = 0.235; η2 = 0.116). In contrast, tumor growth differed between groups not provided gemcitabine (F(3,14) = 3.364; p = 0.049, η2 = 0.419), with trends for slower growth in LVCE than SED (p = 0.088) and HIIT (p = 0.084). Groups did not differ in tumor infiltrating lymphocytes. Conclusion: Contrary to our hypotheses, the exercise interventions compared here did not further reduce pancreatic tumor growth beyond that provided by gemcitabine. However, in mice not receiving gemcitabine, there was a trend for reduced tumor growth in LVCE.