Hepatocellular carcinoma (HCC) is the most common type of liver cancer and one of the leading causes of cancer-related death worldwide. Advanced HCC displays strong resistance to chemotherapy, and traditional chemotherapy drugs do not achieve satisfactory therapeutic efficacy. Sorafenib is an oral kinase inhibitor that inhibits tumor cell proliferation and angiogenesis and induces cancer cell apoptosis. It also improves the survival rates of patients with advanced liver cancer. However, due to its poor solubility, fast metabolism, and low bioavailability, clinical applications of sorafenib have been substantially restricted. In recent years, various studies have been conducted on the use of nanoparticles to improve drug targeting and therapeutic efficacy in HCC. Moreover, nanoparticles have been extensively explored to improve the therapeutic efficacy of sorafenib, and a variety of nanoparticles, such as polymer, lipid, silica, and metal nanoparticles, have been developed for treating liver cancer. All these new technologies have improved the targeted treatment of HCC by sorafenib and promoted nanomedicines as treatments for HCC. This review provides an overview of hot topics in tumor nanoscience and the latest status of treatments for HCC. It further introduces the current research status of nanoparticle drug delivery systems for treatment of HCC with sorafenib.

Ferroptosis is a programmed death mode that regulates redox homeostasis in cells, and recent studies suggest that it is a promising mode of tumor cell death. Ferroptosis is regulated by iron metabolism, lipid metabolism, and intracellular reducing substances, which is the mechanism basis of its combination with photodynamic therapy (PDT). PDT generates reactive oxygen species (ROS) and ¹O₂ through type I and type II photochemical reactions, and subsequently induces ferroptosis through the Fenton reaction and the peroxidation of cell membrane lipids. PDT kills tumor cells by generating excessive cytotoxic ROS. Due to the limited laser depth and photosensitizer enrichment, the systemic treatment effect of PDT is not good. Combining PDT with ferroptosis can compensate for these shortcomings. Nanoparticles constructed by photosensitizers and ferroptosis agonists are widely used in the field of combination therapy, and their targeting and biological safety can be improved through modification. These nanoparticles not only directly kill tumor cells but also further exert the synergistic effect of PDT and ferroptosis by activating antitumor immunity, improving the hypoxia microenvironment, and inhibiting the tumor angiogenesis. Ferroptosis-agonist-induced chemotherapy and PDT-induced ablation also have good clinical application prospects. In this review, we summarize the current research progress on PDT and ferroptosis and how PDT and ferroptosis promote each other.

Cholangiocarcinoma (CCA), which is highly malignant, shows a relatively poor prognosis, due to the insensitivity of the tumour to chemotherapy and radiotherapy. Photodynamic therapy (PDT) has become a promising palliative therapeutic option for patients with unresectable cholangiocarcinoma (CCA), while the functional amount of ROS is limited by intracellular redox systemen. Sulfasalazine (SASP), a well-known anti-inflammatory agent, which also acts as an inhibitor of the amino acid transport system xc (xCT), decreases the intracellular glutathione (GSH) level, thus weakening the antioxidant defence of the cell by inhibition of the antiporter. However, the combination of SASP and PDT remains unexplored. We have reported that polyhematoporphyrin (PHP)-mediated PDT inhibits the cell viability of CCA cells and organoids. Furthermore, in PHP-enriched HCCC-9810 and TFK-1CCA cells, SASP enhances the sensitivity to PHP-mediated PDT through a GSH-dependent mechanism. We found that PHP-PDT can up-regulate xCT expression to promote cells against overloaded ROS, while SASP reduces GSH levels. After the combination of SASP and PHP-PDT, cell viability and GSH levels were significantly inhibited. xCT was also observed to be inhibited by SASP in human organoid samples. Our findings suggest that, in combination with PDT, SASP has potential as a promising approach against CCA.

The early diagnosis of ovarian cancer (OC) is critical to improve the prognosis and prevent recurrence of patients. Nevertheless, there is still a lack of factors which can accurately predict it. In this study, we focused on the interaction of immune infiltration and ferroptosis and selected the ESTIMATE algorithm and 15 ferroptosis-related genes (FRGs) to construct a novel E-FRG scoring model for predicting overall survival of OC patients. The gene expression and corresponding clinical characteristics were obtained from the TCGA dataset (n = 375), GSE18520 (n = 53), and GSE32062 (n = 260). A total of 15 FRGs derived from FerrDb with the immune score and stromal score were identified in the prognostic model by using least absolute shrinkage and selection operator (LASSO)–penalized COX regression analysis. The Kaplan–Meier survival analysis and time-dependent ROC curves performed a powerful prognostic ability of the E-FRG model via multi-validation. Gene Set Enrichment Analysis and Gene Set Variation Analysis elucidate multiple potential pathways between the high and low E-FRG score group. Finally, the proteins of different genes in the model were verified in drug-resistant and non–drug-resistant tumor tissues. The results of this research provide new prospects in the role of immune infiltration and ferroptosis as a helpful tool to predict the outcome of OC patients.

Background: Pancreatic signet ring cell carcinoma (PSRCC) is a rare and aggressive cancer that has been reported primarily as case reports. Due to limited large-scale epidemiological and prognostic analyses, the outcomes of PSRCC patients varies greatly in the absence of recognized first-line treatment strategies. This study aimed to compare the clinical features, treatment, and prognosis of PSRCC and pancreatic ductal cell carcinoma (PDAC), the most common subtype of pancreatic cancer, and to establish predictive models for these subtypes.Methods: The data on PSRCC and PDAC patients from 1998 to 2018 was obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Thereafter, the clinical, demographic, and treatment characteristics of the two groups and the differences and influencing factors of the two groups were evaluated by propensity score matching (PSM), Kaplan–Meier survival curves, Cox risk regression analyses, and least absolute shrinkage and selection operator (LASSO) analysis. Next, prognosis models were constructed and validated by KM and ROC analysis. Finally, a nomogram was constructed, based on the results of these analyses, to predict survival outcomes of PSRCC and PDAC patients.Results: A total of 84,789 patients (432 PSRCC and 84357 PDAC patients) were included in this study. The results of the study revealed that, compared to the PDAC patients, PSRCC patients were more likely to be male, aged between 58–72 years, have larger tumor masses, and less likely to undergo chemotherapy. Before PSM, the overall survival and cancer-specific survival of the PSRCC group were significantly lower than those PDAC group, but there was no difference in the prognosis of the two groups after PSM. Additionally, lymph node ratio (LNR), log odds of positive lymph node (LODDS), tumor size, age, T-stage, marital status, and summary stage were found to be independent prognostic factors for PSRCC. Lastly, the prediction model and nomogram based on these prognostic factors could accurately predict the survival rate of the patients in SEER datasets and external validation datasets.Conclusion: The prognosis of PSRCC and PDAC patients is similar under the same conditions; however, PSRCC patients may have more difficulty in receiving better treatment, thus resulting in their poor prognosis.