Adoptive cell therapies have transformed the treatment landscape for hematologic malignancies. Yet, translation to solid tumors remains constrained by antigen heterogeneity, an immunosuppressive tumor microenvironment (TME), and poor persistence of conventional CAR-T cells. In response, innate immune cell platforms, particularly chimeric antigen receptor–engineered natural killer (CAR-NK) cells and chimeric antigen receptor–macrophages (CAR-MΦ), have emerged as promising alternatives. This review summarizes recent advances in the design and application of CAR-NK and CAR-MΦ therapies for solid tumors. We highlight key innovations, including the use of lineage-specific intracellular signaling domains (e.g., DAP12, 2B4, FcRγ), novel effector constructs (e.g., NKG7-overexpressing CARs, TME-responsive CARs), and scalable induced pluripotent stem cell (iPSC)-derived platforms. Preclinical data support enhanced antitumor activity through mechanisms such as major histocompatibility complex (MHC)-unrestricted cytotoxicity, phagocytosis, trogocytosis, cytokine secretion, and cross-talk with adaptive immunity. Early-phase clinical studies (e.g., CT-0508) demonstrate feasibility and TME remodeling with CAR-MΦ. However, persistent challenges remain, including transient in vivo survival, manufacturing complexity, and risks of off-target inflammation. Emerging combinatorial strategies, such as dual-effector regimens (CAR-NK⁺ CAR-MΦ), cytokine-modulated cross-support, and bispecific or logic-gated CARs, may overcome these barriers and provide more durable, tumor-selective responses. Taken together, CAR-NK and CAR-MΦ platforms are poised to expand the reach of engineered cell therapy into the solid tumor domain.

Hematologic malignancies, including acute myeloid leukemia, myelodysplastic syndromes, lymphoma, and multiple myeloma, are characterized by profound biological heterogeneity and highly dynamic treatment trajectories that conventional, static prognostic systems incompletely capture. Cellular therapies, such as chimeric antigen receptor T-cell therapy and hematopoietic stem cell transplantation, offer potentially curative options for relapsed or refractory disease, yet outcomes remain highly variable, and management decisions regarding conditioning intensity, lymphodepletion, immunosuppression, and toxicity surveillance continue to be largely protocol-driven rather than individually adapted. Artificial intelligence (AI) and machine learning (ML) have demonstrated substantial promise in diagnostic support, prognostic stratification, and multimodal data integration across hematologic malignancies, but existing models remain predominantly static and related to pre-treatment in orientation, limiting their utility for real-time clinical guidance. This review summarizes current AI applications in hematologic oncology; critically compares the strengths, limitations, and clinical applicability of major AI model classes, including traditional machine learning, deep learning, multimodal integrative frameworks, reinforcement learning, digital twins, and emerging foundation models and large language models; and proposes an adaptive, multimodal paradigm. We examine key enabling technologies and address the clinical, regulatory, ethical, and implementation challenges that must be resolved before these systems can be deployed at the bedside. We argue that the central challenge facing the field is no longer whether AI can predict outcomes, but whether it can actively guide real-time therapeutic decisions, and that achieving this transition will require interdisciplinary collaboration, prospective validation, and governance frameworks capable of ensuring interpretability, equity, and clinical trustworthiness.

Downregulation of tumor suppression genes by DNA hypermethylation has been proposed as a potential cause of neuroendocrine neoplasm (NEN) formation. In this report, we present a patient simultaneously diagnosed with acute myeloid leukemia (AML) and a metastatic nonfunctioning pancreatic NEN. Because of the two competing diagnoses, he was treated with lanreotide, venetoclax and a long course of the hypomethylating agent decitabine. The AML responded to venetoclax and decitabine treatment while the PanNEN stabilized on lanreotide. Over multiple months of treatment, the PanNEN showed gradual tumor response, consistent with decitabine treatment effect and the patient remained without disease progression for both malignancies. We believe that some PanNENs can benefit from treatment with hypomethylating agents such as decitabine. To support this, we review the relevant literature and are providing a mechanism for the efficacy of decitabine in our case.

Immunotherapy is a biological therapy that helps the body’s immune system to fight against cancer cells. The Food and Drug Administration (FDA) approved the first immune checkpoint inhibitor in 2011. Since 2011, many immune checkpoint inhibitors have been approved. Programmed cell death 1 (PD-1) inhibitors are now commonly used in multiple malignancies due to their remarkable response. Thus, immune-related adverse events are now coming into the limelight due to the increasing use of PD-1 inhibitors. Here, we present a case of a 54-year-old female with non-small cell lung cancers (NSCLC) treated with pembrolizumab and later presented with severe neurotoxicity.