The Matrisome Is Associated with Metabolic Reprograming in Stem-like Phenotypes of Gastric Cancer

Nanoparticles in tumor microenvironment remodeling and cancer immunotherapy

Cancer immunotherapy and vaccine development have significantly improved the fight against cancers. Despite these advancements, challenges remain, particularly in the clinical delivery of immunomodulatory compounds. The tumor microenvironment (TME), comprising macrophages, fibroblasts, and immune cells, plays a crucial role in immune response modulation. Nanoparticles, engineered to reshape the TME, have shown promising results in enhancing immunotherapy by facilitating targeted delivery and immune modulation. These nanoparticles can suppress fibroblast activation, promote M1 macrophage polarization, aid dendritic cell maturation, and encourage T cell infiltration. Biomimetic nanoparticles further enhance immunotherapy by increasing the internalization of immunomodulatory agents in immune cells such as dendritic cells. Moreover, exosomes, whether naturally secreted by cells in the body or bioengineered, have been explored to regulate the TME and immune-related cells to affect cancer immunotherapy. Stimuli-responsive nanocarriers, activated by pH, redox, and light conditions, exhibit the potential to accelerate immunotherapy. The co-application of nanoparticles with immune checkpoint inhibitors is an emerging strategy to boost anti-tumor immunity. With their ability to induce long-term immunity, nanoarchitectures are promising structures in vaccine development. This review underscores the critical role of nanoparticles in overcoming current challenges and driving the advancement of cancer immunotherapy and TME modification.

Telomere maintenance mechanism subtype reveals different immune activity in vestibular schwannoma

BACKGROUND

The immortality of cancer cells relies on maintaining the length of telomeres, which prevents cellular senescence and enables unlimited replication. However, little is currently known about telomerase activity and the alternative lengthening of telomeres (ALT) in vestibular schwannomas. In this study we aimed to elucidate the role that telomerase and ALTs play in vestibular schwannomas.

METHODS

To address this gap, we conducted a study where we used the gene set variation analysis algorithm with bulk RNA-seq and single-cell RNA-seq to identify the characteristics of each group of patients with vestibular schwannomas, based on their telomere maintenance mechanism subtype.

RESULTS

Our findings suggest that patients with relatively high ALT-like groups have a better prognosis than those with relatively high telomerase groups. Specifically, we found that the high telomerase group had relatively higher antigen-presenting cell (APC) activity than the high ALT like group. At the single-cell level, microglia, neutrophils, and fibroblasts showed high telomerase activity and relatively high APC activity compared to other cell types. In addition, Schwann cells in the group with low ALT levels exhibited elevated immune activity at the single-cell level.

CONCLUSION

These results suggest that personalized drug therapy could be developed from the perspective of precision medicine for patients with relatively high telomerase activity and a high ALT-like group.

Comprehensive Profiling of Early Neoplastic Gastric Microenvironment Modifications and Biodynamics in Impaired BMP-Signaling FoxL1+-Telocytes

FoxL1⁺telocytes (TC^FoxL1+) are novel gastrointestinal subepithelial cells that form a communication axis between the mesenchyme and epithelium. TC^FoxL1+ are strategically positioned to be key contributors to the microenvironment through production and secretion of growth factors and extracellular matrix (ECM) proteins. In recent years, the alteration of the bone morphogenetic protein (BMP) signaling in TC^FoxL1+ was demonstrated to trigger a toxic microenvironment with ECM remodeling that leads to the development of pre-neoplastic gastric lesions. However, a comprehensive analysis of variations in the ECM composition and its associated proteins in gastric neoplasia linked to TC^FoxL1+ dysregulation has never been performed. This study provides a better understanding of how TC^FoxL1+ defective BMP signaling participates in the gastric pre-neoplastic microenvironment. Using a proteomic approach, we determined the changes in the complete matrisome of BmpR1a^△FoxL1+ and control mice, both in total antrum as well as in isolated mesenchyme-enriched antrum fractions. Comparative proteomic analysis revealed that the deconstruction of the gastric antrum led to a more comprehensive analysis of the ECM fraction of gastric tissues microenvironment. These results show that TC^FoxL1+ are key members of the mesenchymal cell population and actively participate in the establishment of the matrisomic fraction of the microenvironment, thus influencing epithelial cell behavior.

Tumor microenvironment-mediated immune tolerance in development and treatment of gastric cancer

Tumor microenvironment is the general term for all non-cancer components and their metabolites in tumor tissue. These components include the extracellular matrix, fibroblasts, immune cells, and endothelial cells. In the early stages of tumors, the tumor microenvironment has a tumor suppressor function. As the tumor progresses, tumor immune tolerance is induced under the action of various factors, such that the tumor suppressor microenvironment is continuously transformed into a tumor-promoting microenvironment, which promotes tumor immune escape. Eventually, tumor cells manifest the characteristics of malignant proliferation, invasion, metastasis, and drug resistance. In recent years, stress effects of the extracellular matrix, metabolic and phenotypic changes of innate immune cells (such as neutrophils, mast cells), and adaptive immune cells in the tumor microenvironment have been revealed to mediate the emerging mechanisms of immune tolerance, providing us with a large number of emerging therapeutic targets to relieve tumor immune tolerance. Gastric cancer is one of the most common digestive tract malignancies worldwide, whose mortality rate remains high. According to latest guidelines, the first-line chemotherapy of advanced gastric cancer is the traditional platinum and fluorouracil therapy, while immunotherapy for gastric cancer is extremely limited, including only Human epidermal growth factor receptor 2 (HER-2) and programmed death ligand 1 (PD-L1) targeted drugs, whose benefits are limited. Clinical experiments confirmed that cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), vascular endothelial growth factor receptor (VEGFR) and other targeted drugs alone or in combination with other drugs have limited efficacy in patients with advanced gastric cancer, far less than in lung cancer, colon cancer, and other tumors. The failure of immunotherapy is mainly related to the induction of immune tolerance in the tumor microenvironment of gastric cancer. Therefore, solving the immune tolerance of tumors is key to the success of gastric cancer immunotherapy. In this study, we summarize the latest mechanisms of various components of the tumor microenvironment in gastric cancer for inducing immune tolerance and promoting the formation of the malignant phenotype of gastric cancer, as well as the research progress of targeting the tumor microenvironment to overcome immune tolerance in the treatment of gastric cancer.

Machine Learning Predictor of Immune Checkpoint Blockade Response in Gastric Cancer

Predicting responses to immune checkpoint blockade (ICB) lacks official standards despite the discovery of several markers. Expensive drugs and different reactivities for each patient are the main disadvantages of immunotherapy. Gastric cancer is refractory and stem-like in nature and does not respond to immunotherapy. In this study, we aimed to identify a characteristic gene that predicts ICB response in gastric cancer and discover a drug target for non-responders. We built and evaluated a model using four machine learning algorithms for two cohorts of bulk and single-cell RNA seq to predict ICB response in gastric cancer patients. Through the LASSO feature selection, we discovered a marker gene signature that distinguishes responders from non-responders. VCAN, a candidate characteristic gene selected by all four machine learning algorithms, had a significantly high prevalence in non-responders (p = 0.0019) and showed a poor prognosis (p = 0.0014) at high expression values. This is the first study to discover a signature gene for predicting ICB response in gastric cancer by molecular subtype and provides broad insights into the treatment of stem-like immuno-oncology through precision medicine.