Immune checkpoint inhibitors (ICIs) have revolutionized the therapeutic landscape of cancer and have been widely approved for use in the treatment of diverse solid tumors. Targeted therapy has been an essential part of cancer treatment for decades, and in most cases, a special drug target is required. Numerous studies have confirmed the synergistic effect of combining ICIs with targeted therapy. For example, triple therapy of PD-L1 inhibitor atezolizumab plus BRAF inhibitor vemurafenib and MEK inhibitor cobimetinib has been approved as the first-line treatment in advanced melanoma patients with BRAF^V600 mutations. However, not all combinations of ICIs and targeted therapy work. Combining ICIs with EGFR inhibitors in non-small-cell lung cancer (NSCLC) with EGFR mutations only triggered toxicities and did not improve efficacy. Therefore, the efficacies of combinations of ICIs and different targeted agents are distinct. This review firstly and comprehensively covered the current status of studies on the combination of ICIs mainly referring to PD-1 and PD-L1 inhibitors and targeted drugs, including angiogenesis inhibitors, EGFR/HER2 inhibitors, PARP inhibitors and MAPK/ERK signaling pathway inhibitors, in the treatment of solid tumors. We discussed the underlying mechanisms, clinical efficacies, side effects, and potential predictive biomarkers to give an integrated view of the combination strategy and provide perspectives for future directions in solid tumors.

Brain tumors refer to the abnormal growths that occur within the brain's tissue, comprising both primary neoplasms and metastatic lesions. Timely detection, precise staging, suitable treatment, and standardized management are of significant clinical importance for extending the survival rates of brain tumor patients. Artificial intelligence (AI), a discipline within computer science, is leveraging its robust capacity for information identification and combination to revolutionize traditional paradigms of oncology care, offering substantial potential for precision medicine. This article provides an overview of the current applications of AI in brain tumors, encompassing the primary AI technologies, their working mechanisms and working workflow, the contributions of AI to brain tumor diagnosis and treatment, as well as the role of AI in brain tumor scientific research, particularly in drug innovation and revealing tumor microenvironment. Finally, the paper addresses the existing challenges, potential solutions, and the future application prospects. This review aims to enhance our understanding of the application of AI in brain tumors and provide valuable insights for forthcoming clinical applications and scientific inquiries.

Cancer-associated fibroblasts (CAFs) are critical components of the tumor microenvironment (TME), playing a pivotal role in tumor initiation, progression, and therapeutic resistance. This review explores the dual roles of CAFs in regulating tumor cell senescence and cell death, elucidating their mechanisms in inducing cellular senescence, shaping an immunosuppressive milieu, and modulating cell death pathways. CAFs promote tumor progression by secreting pro-inflammatory factors and extracellular matrix (ECM) components, while also contributing to metabolic reprogramming, immune evasion, and therapy resistance, thereby influencing anti-cancer treatment efficacy. Studies indicate that the heterogeneity and plasticity of CAFs determine their distinct functions across various tumor types. Consequently, precision-targeted therapeutic strategies against CAFs, including the elimination of senescent CAFs, inhibition of the senescence-associated secretory phenotype (SASP), and disruption of CAF-mediated cell death evasion mechanisms, have emerged as promising directions in cancer research. This review provides a comprehensive analysis of CAFs functions and their potential as therapeutic targets, offering valuable insights into the development of novel anti-cancer strategies.

Acute ischemic stroke (AIS) is the most prevalent type of stroke, and due to its high incidence, disability rate, and mortality rate, it imposes a significant burden on the health care system. Amino acids constitute one of the most crucial metabolic products within the human body, and alterations in their metabolic pathways have been identified in the microenvironment of AIS, thereby influencing the pathogenesis, severity, and prognosis of AIS. The amino acid metabolism characteristics in AIS are complex. On one hand, the dynamic progression of AIS continuously reshapes the amino acid metabolism pattern. Conversely, changes in the amino acid metabolism pattern also exert a double-edged effect on AIS. This interaction is bidirectional, dynamic, heterogeneous, and dose-specific. Therefore, the distinctive metabolic reprogramming features surrounding amino acids during the AIS process are systematically summarized in this paper, aiming to provide potential investigative strategies for the early diagnosis, treatment approaches, and prognostic enhancement of AIS.

The development of brain metastasis is a major cause of significantly reduced survival in breast cancer patients. The initiation and progression of breast cancer brain metastasis (BCBM) involve multiple distinct molecular pathways and reprogramming of the tumor microenvironment (TME). This review systematically summarizes key mechanisms underlying BCBM, including epithelial-mesenchymal transition (EMT), extracellular matrix (ECM) remodeling, and the spatiotemporal dynamics of metabolic reprogramming regulated by critical signaling pathways during brain colonization. In particular, we highlight emerging mechanisms of breaching the specialized brain multifunctional barriers. Furthermore, this review provides an in-depth analysis of the cooperative immune-suppressive network within the BCBM TME, emphasizing the crosstalk among various immune cell components (such as T cells, B cells, macrophages, neutrophils, NK cells, MDSCs) and intracranial-specific cellular elements (including astrocytes, microglia, brain metastasis-associated fibroblasts). Through the complex interplay, these cells collectively facilitate immune evasion and metastatic outgrowth. Accordingly, we discuss the current clinical management of BCBM and potential future directions. Deeper mechanistic insights are expected to offer novel biomarkers and reveal new targets for developing precision therapeutic strategies against BCBM.

Molecular imaging technologies have significantly transformed cancer research and clinical practice, offering valuable tools for visualizing and understanding the complex tumor immune microenvironment. These technologies allow for the non-invasive examination of key components within the tumor immune microenvironment, including immune cells, cytokines, and stromal cells, providing crucial insights into tumor biology and treatment responses. This paper reviews the latest advancements in molecular imaging, with a focus on its applications in assessing interactions within the tumor immune microenvironment. Additionally, the challenges faced by molecular imaging technologies are discussed, such as the need for highly sensitive and specific imaging agents, issues with data integration, and difficulties in clinical translation. The future outlook emphasizes the potential of molecular imaging to enhance personalized cancer treatment through the integration of artificial intelligence and the development of novel imaging probes. Addressing these challenges is essential to fully realizing the potential of molecular imaging in improving cancer diagnosis, treatment, and patient outcomes.