Antibody-Pattern Recognition Receptor Agonist Conjugates: A Promising Therapeutic Strategy for Cancer

High-risk HPV oncoproteins E6 and E7 and their interplay with the innate immune response: Uncovering mechanisms of immune evasion and therapeutic prospects

Human papillomaviruses (HPVs) are double-stranded DNA (dsDNA) tumor viruses causally associated with 5% of human cancers, comprising both anogenital and upper aerodigestive tract carcinomas. Despite the availability of prophylactic vaccines, HPVs continue to pose a significant global health challenge, primarily due to inadequate vaccine access and coverage. These viruses can establish persistent infections by evading both the intrinsic defenses of infected tissues and the extrinsic defenses provided by professional innate immune cells. Crucial for their evasion strategies is their unique intraepithelial life cycle, which effectively shields them from host detection. Thus, strategies aimed at reactivating the innate immune response within infected or transformed epithelial cells, particularly through the production of type I interferons (IFNs) and lymphocyte-recruiting chemokines, are considered viable solutions to counteract the adverse effects of persistent infections by these oncogenic viruses. This review focuses on the complex interplay between the high-risk HPV oncoproteins E6 and E7 and the innate immune response in epithelial cells and HPV-associated cancers. In particular, it details the molecular mechanisms by which E6 and E7 modulate the innate immune response, highlighting significant progress in our comprehension of these processes. It also examines forward-looking strategies that exploit the innate immune system to ameliorate existing anticancer therapies, thereby providing crucial insights into future therapeutic developments.

Dynamic polarization of tumor-associated macrophages and their interaction with intratumoral T cells in an inflamed tumor microenvironment: from mechanistic insights to therapeutic opportunities

Immunotherapy has brought a paradigm shift in the treatment of tumors in recent decades. However, a significant proportion of patients remain unresponsive, largely due to the immunosuppressive tumor microenvironment (TME). Tumor-associated macrophages (TAMs) play crucial roles in shaping the TME by exhibiting dual identities as both mediators and responders of inflammation. TAMs closely interact with intratumoral T cells, regulating their infiltration, activation, expansion, effector function, and exhaustion through multiple secretory and surface factors. Nevertheless, the heterogeneous and plastic nature of TAMs renders the targeting of any of these factors alone inadequate and poses significant challenges for mechanistic studies and clinical translation of corresponding therapies. In this review, we present a comprehensive summary of the mechanisms by which TAMs dynamically polarize to influence intratumoral T cells, with a focus on their interaction with other TME cells and metabolic competition. For each mechanism, we also discuss relevant therapeutic opportunities, including non-specific and targeted approaches in combination with checkpoint inhibitors and cellular therapies. Our ultimate goal is to develop macrophage-centered therapies that can fine-tune tumor inflammation and empower immunotherapy.

Drug Delivery Strategies for the Treatment of Pancreatic Cancer

Pancreatic cancer is fast becoming a global menace and it is projected to be the second leading cause of cancer-related death by 2030. Pancreatic adenocarcinomas, which develop in the pancreas' exocrine region, are the predominant type of pancreatic cancer, representing about 95% of total pancreatic tumors. The malignancy progresses asymptomatically, making early diagnosis difficult. It is characterized by excessive production of fibrotic stroma known as desmoplasia, which aids tumor growth and metastatic spread by remodeling the extracellular matrix and releasing tumor growth factors. For decades, immense efforts have been harnessed toward developing more effective drug delivery systems for pancreatic cancer treatment leveraging nanotechnology, immunotherapy, drug conjugates, and combinations of these approaches. However, despite the reported preclinical success of these approaches, no substantial progress has been made clinically and the prognosis for pancreatic cancer is worsening. This review provides insights into challenges associated with the delivery of therapeutics for pancreatic cancer treatment and discusses drug delivery strategies to minimize adverse effects associated with current chemotherapy options and to improve the efficiency of drug treatment.

The Mechanisms of Ferroptosis and the Applications in Tumor Treatment: Enemies or Friends?

Ferroptosis, as a newly discovered non-apoptotic cell death mode, is beginning to be explored in different cancer. The particularity of ferroptosis lies in the accumulation of iron dependence and lipid peroxides, and it is different from the classical cell death modes such as apoptosis and necrosis in terms of action mode, biochemical characteristics, and genetics. The mechanism of ferroptosis can be divided into many different pathways, so it is particularly important to identify the key sites of ferroptosis in the disease. Herein, based on ferroptosis, we analyze the main pathways in detail. More importantly, ferroptosis is linked to the development of different systems of the tumor, providing personalized plans for the examination, treatment, and prognosis of cancer patients. Although some mechanisms and side effects of ferroptosis still need to be studied, it is still a promising method for cancer treatment.

Identified Gefitinib Metabolism-Related lncRNAs can be Applied to Predict Prognosis, Tumor Microenvironment, and Drug Sensitivity in Non-Small Cell Lung Cancer

Gefitinib has shown promising efficacy in the treatment of patients with locally advanced or metastatic EGFR-mutated non-small cell lung cancer (NSCLC). Molecular biomarkers for gefitinib metabolism-related lncRNAs have not yet been elucidated. Here, we downloaded relevant genes and matched them to relevant lncRNAs. We then used univariate, LASSO, and multivariate regression to screen for significant genes to construct prognostic models. We investigated TME and drug sensitivity by risk score data. All lncRNAs with differential expression were selected for GO/KEGG analysis. Imvigor210 cohort was used to validate the value of the prognostic model. Finally, we performed a stemness indices difference analysis. lncRNA-constructed prognostic models were significant in the high-risk and low-risk subgroups. Immune pathways were identified in both groups at low risk. The higher the risk score the greater the value of exclusion, MDSC, and CAF. PRRophetic algorithm screened a total of 58 compounds. In conclusion, the prognostic model we constructed can accurately predict OS in NSCLC patients. Two groups of low-risk immune pathways are beneficial to patients. Gefitinib metabolism was again validated to be related to cytochrome P450 and lipid metabolism. Finally, drugs that might be used to treat NSCLC patients were screened.