Multi-omics characteristics of tumor-associated macrophages in the tumor microenvironment of gastric cancer and their exploration of immunotherapy potential

The Bidirectional Interplay between T Cell-Based Immunotherapies and the Tumor Microenvironment

T cell-based therapies, including tumor-infiltrating lymphocyte therapy, T-cell receptor-engineered T cells, and chimeric antigen receptor T cells, are powerful therapeutic approaches for cancer treatment. Whereas these therapies are primarily known for their direct cytotoxic effects on cancer cells, accumulating evidence indicates that they also influence the tumor microenvironment (TME) by altering the cytokine milieu and recruiting additional effector populations to help orchestrate the antitumor immune response. Conversely, the TME itself can modulate the behavior of these therapies within the host by either supporting or inhibiting their activity. In this review, we provide an overview of clinical and preclinical data on the bidirectional influences between T-cell therapies and the TME. Unraveling the interactions between T cell-based therapies and the TME is critical for a better understanding of their mechanisms of action, resistance, and toxicity, with the goal of optimizing efficacy and safety.

Unveiling the contribution of tumor-associated macrophages in driving epithelial-mesenchymal transition: a review of mechanisms and therapeutic Strategies

Tumor-associated macrophages (TAMs), fundamental constituents of the tumor microenvironment (TME), significantly influence cancer development, primarily by promoting epithelial-mesenchymal transition (EMT). EMT endows cancer cells with increased motility, invasiveness, and resistance to therapies, marking a pivotal juncture in cancer progression. The review begins with a detailed exposition on the origins of TAMs and their functional heterogeneity, providing a foundational understanding of TAM characteristics. Next, it delves into the specific molecular mechanisms through which TAMs induce EMT, including cytokines, chemokines and stromal cross-talking. Following this, the review explores TAM-induced EMT features in select cancer types with notable EMT characteristics, highlighting recent insights and the impact of TAMs on cancer progression. Finally, the review concludes with a discussion of potential therapeutic targets and strategies aimed at mitigating TAM infiltration and disrupting the EMT signaling network, thereby underscoring the potential of emerging treatments to combat TAM-mediated EMT in cancer. This comprehensive analysis reaffirms the necessity for continued exploration into TAMs' regulatory roles within cancer biology to refine therapeutic approaches and improve patient outcomes.

Integrated Analysis Construct a Tumor-Associated Macrophage Novel Signature with Promising Implications in Predicting the Prognosis and Immunotherapeutic Response of Gastric Cancer Patients

BACKGROUND

Gastric cancer (GC) remains one of the most prevalent malignant tumors worldwide. At present, tumor-associated macrophages (TAMs) are essential in the progression, metastasis, and drug resistance of tumors. Therefore, TAMs can be a crucial target for tumor treatment.

AIMS

We intended to investigate the TAM characteristics in GC and develop a risk signature based on TAM to predict the prognosis of GC patients.

METHODS

The single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data were acquired from a publicly available database. We utilized the Seurat pipeline to process the scRNA-seq data and determine TAM cell types using marker genes. Univariate Cox regression analysis was utilized to examine TAM-related prognostic genes, and then we employed Lasso-Cox regression analysis, and Multivariate Cox regression analysis established a novel risk profile to forecast the clinical value of the model with a new nomogram combining risk profiles and clinicopathological characteristics.

RESULTS

The current study employed scRNA-seq data to identify five TAM clusters in GC, among which four were significantly associated with GC prognosis. Accordingly, we further developed a TAM-related risk signature utilizing nine genes. After evaluation, our model accurately predicted the prognosis of gastric cancer. Generally, GC patients with low TAMS scores exhibited a more favorable prognosis, greater benefits from immunotherapy, and higher levels of immune cell infiltration.

CONCLUSIONS

The prognosis of GC can be effectively predicted by TAM-based risk signatures, and the signature may provide a new perspective for comprehensively guiding clinical diagnosis, prediction, and immunotherapy for gastric cancer.