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Polyamines are essential for the growth and proliferation of mammalian cells and are intimately involved in biological mechanisms such as DNA replication, RNA transcription, protein synthesis, and post-translational modification. These mechanisms regulate cellular proliferation, differentiation, programmed cell death, and the formation of tumors. Several studies have confirmed the positive effect of polyamines on the maintenance of health, while others have demonstrated that their activity may promote the occurrence and progression of diseases. This review examines a variety of topics, such as polyamine source and metabolism, including metabolism, transport, and the potential impact of polyamines on health and disease. In addition, a brief summary of the effects of oncogenes and signaling pathways on tumor polyamine metabolism is provided. 5ikmGssBZD_e4xpSJscY2Y Video Abstract

Hepatocellular carcinoma with cirrhosis promotes the advancement of malignancy and the development of fibrosis in normal liver tissues. Understanding the pathological mechanisms underlying the development of HCC with cirrhosis is important for developing effective therapeutic strategies. Herein, the RNA-sequencing (RNA-seq) data and corresponding clinical features of patients with HCC were extracted from The Cancer Genome Atlas (TCGA) database using the University of California Santa Cruz (UCSC) Xena platform. The enrichment degree of hallmarkers for each TCGA-LIHC cohort was quantified by ssGSEA algorithm. Weighted gene co-expression network analysis (WGCNA) revealed two gene module eigengenes (MEs) associated with cirrhosis, namely, MEbrown and MEgreen. Analysis of these modules using AUCell showed that MEbrown had higher enrichment scores in all immune cells, whereas MEgreen had higher enrichment scores in malignant cells. The CellChat package revealed that both immune and malignant cells contributed to the fibrotic activity of myofibroblasts through diverse signaling pathways. Additionally, spatial transcriptomic data showed that hepatocytes, proliferating hepatocytes, macrophages, and myofibroblasts were located in closer proximity in HCC tissues. These cells may potentially participate in the process of stimulating myofibroblast fibrotic activity, which may be related to the development of liver fibrosis. In summary, we made full use of multi-omics data to explore gene networks and cell types that may be involved in the development and progression of cirrhosis in HCC.

The objective of this study was to identify the prognostic biomarkers for hepatocellular carcinoma (HCC) by analyzing the N6-methyladenosine (m6A) RNA modification. HCC is a complex malignant tumor induced by various pathogenic factors. m6A RNA modification and its regulators influence the tumorigenesis and advancement of HCC. RNA sequencing and clinical data were extracted from the TCGA-LIHC and ICGC-LIRI-JP database. Single-cell RNA sequencing data were processed using Seurat and Harmony packages. ConsensusClusterPlus identified molecular subtypes, and ssGSEA quantified m6A regulator-related gene sets. Differentially expressed genes were analyzed, followed by the establishment of a risk model. qRT-PCR validated mRNA expression in Huh7, Hep 3B, and Hep G2 cells and normal hepatocytes. Four molecular subtypes based on m6A regulator transcriptional profiles of m6A regulators were identified, each exhibiting unique clinical, prognostic, and pathway characteristics. A robust risk model distinguished the high- and low-risk groups, revealing obvious differences in immune cells infiltration and chemotherapeutic drug sensitivity. qRT-PCR confirmed significant differential expression of key genes (TRNP1, KIF20A, and CFRHR3) in HCC cell lines and normal hepatocytes. In conclusion, the established risk model may serve as a perspective tool for prognostic prediction, and provide insights into the functions of m6A involved in HCC.

Artificial intelligence (AI) enhances the precision, personalization, and efficiency of cancer treatment through deep learning and machine learning techniques. This review comprehensively examines the evolution of AI and its expanding applications in cancer radiotherapy, immunotherapy, and drug discovery and repurposing. In radiotherapy, AI enables automated medical image segmentation, thereby facilitating the accurate delineation of tumor targets. Furthermore, AI-driven feedback systems support clinicians in developing individualized treatment plans by offering real-time assessment of treatment safety and potential efficacy. In the context of cancer immunotherapy, AI integrates multi-omics data to advance the discovery of novel biomarkers, analyze the tumor immune microenvironment, and accurately predict responses to immune checkpoint inhibitors. Moreover, AI accelerates drug discovery and repurposing through virtual screening, protein structure prediction, and the identification of novel therapeutic targets. However, the true clinical value of these AI models depends heavily on their generalizability across diverse patient cohorts and their performance compared to standard clinical baselines. Despite these promising prospects, AI still faces challenges in clinical applications, such as insufficient data standardization, poor model interpretability, and a lack of ethical oversight, delaying its formal inclusion into standardized clinical guidelines. With the rapid growth of data volume and computational power, AI is expected to play an increasingly central role in cancer management, holding immense promise for improving patient outcomes and advancing precision oncology.

Recent studies have established the pivotal roles of patient‐derived tumour organoids (PDTOs), innovative three‐dimensional (3D) culture systems, in various biological and medical applications. PDTOs, as promising tools, have been established and extensively used for drug screening, prediction of immune response and assessment of immunotherapeutic effectiveness in various cancer types, including glioma, ovarian cancer and so on. The overarching goal is to facilitate the translation of new therapeutic modalities to guide personalised immunotherapy. Notably, there has been a recent surge of interest in the co‐culture of PDTOs with immune cells to investigate the dynamic interactions between tumour cells and immune microenvironment. A comprehensive and in‐depth investigation is necessary to enhance our understanding of PDTOs as promising testing platforms for cancer immunotherapy. This review mainly focuses on the latest updates on the applications and challenges of PDTO‐based methods in anti‐cancer immune responses. We strive to provide a comprehensive understanding of the potential and prospects of PDTO‐based technologies as next‐generation strategies for advancing immunotherapy approaches. Using 3D platforms to monitor the cancer immune response Organoids displayed preferable potential for cancer immunotherapy Novel technologies to generate immune‐tumour organoids

Tumors of the digestive system pose a significant threat to human health and longevity. These tumors are associated with high morbidity and mortality rates, leading to a heavy economic burden on healthcare systems. Several intratumoral microorganisms are present in digestive system tumors, and their sources and abundance display significant heterogeneity depending on the specific tumor subtype. These microbes have a complex and precise function in the neoplasm. They can facilitate tumor growth through various mechanisms, such as inducing DNA damage, influencing the antitumor immune response, and promoting the degradation of chemotherapy drugs. Therefore, these microorganisms can be targeted to inhibit tumor progression for improving overall patient prognosis. This review focuses on the current research progress on microorganisms present in the digestive system tumors and how they influence the initiation, progression, and prognosis of tumors. Furthermore, the primary sources and constituents of tumor microbiome are delineated. Finally, we summarize the application potential of intratumoral microbes in the diagnosis, treatment, and prognosis prediction of digestive system tumors. DEFNFSt1_c_iMar5wcyWRv Video Abstract

Asia bears a disproportionate burden of head and neck cancer (HNC). This study aimed to analyze its spatial distribution and temporal trends in Asia from 1990 to 2021, projecting trends to 2030. We performed a secondary analysis of data from the Global Burden of Disease Study (GBD) 2021, examining disability-adjusted life years (DALYs) for HNC and its five major subtypes: nasopharyngeal cancer (NPC), thyroid cancer (TC), laryngeal cancer (LC), lip and oral cavity cancer (LOC), and other pharyngeal cancer (OPC), across five Asian subregions and 34 countries/territories from 1990 to 2021. Temporal trends were evaluated using Joinpoint regression, and projections to 2030 were generated through Bayesian Age-Period-Cohort model. From 1990 to 2021, DALYs for HNC increased in five subregions. In contrast, age-standardized DALY rates (ASDR) declined across all subregions except South Asia, with East Asia experiencing the most rapid decrease. In 2021, South Asia recorded the highest DALYs (6,412,639) and ASDR (405.82 per 100,000) for HNC. LOC was the main HNC type in most regions (32.41% - 46.23%), except East Asia, where NPC was most common (38.96%). South Asia also exhibited the highest ASDRs for LC (67.29), LOC (182.29), and OPC (93.00) per 100,000, while Southeast Asia demonstrated the highest ASDRs for NPC (50.77) and TC (18.22) per 100,000. Significant disparities in ASDR trends for HNC subtypes were observed across Asia. By 2030, South Asia is projected to maintain the highest ASDRs for HNC (394.59), LC (62.98), LOC (185.31), and OPC (95.50). East and Southeast Asia are expected to show comparable ASDRs for NPC (approximately 50.00), with Southeast Asia leading in TC ASDR (23.90). HNC remains a significant public health challenge in Asia, with substantial heterogeneity in its subtypes across the five subregions. Implementing targeted, region-specific strategies is crucial to mitigating the disease burden.

Asia bears a disproportionate burden of head and neck cancer (HNC). This study aimed to analyze its spatial distribution and temporal trends in Asia from 1990 to 2021, projecting trends to 2030. We performed a secondary analysis of data from the Global Burden of Disease Study (GBD) 2021, examining disability-adjusted life years (DALYs) for HNC and its five major subtypes: nasopharyngeal cancer (NPC), thyroid cancer (TC), laryngeal cancer (LC), lip and oral cavity cancer (LOC), and other pharyngeal cancer (OPC), across five Asian subregions and 34 countries/territories from 1990 to 2021. Temporal trends were evaluated using Joinpoint regression, and projections to 2030 were generated through Bayesian Age-Period-Cohort model. From 1990 to 2021, DALYs for HNC increased in five subregions. In contrast, age-standardized DALY rates (ASDR) declined across all subregions except South Asia, with East Asia experiencing the most rapid decrease. In 2021, South Asia recorded the highest DALYs (6,412,639) and ASDR (405.82 per 100,000) for HNC. LOC was the main HNC type in most regions (32.41% - 46.23%), except East Asia, where NPC was most common (38.96%). South Asia also exhibited the highest ASDRs for LC (67.29), LOC (182.29), and OPC (93.00) per 100,000, while Southeast Asia demonstrated the highest ASDRs for NPC (50.77) and TC (18.22) per 100,000. Significant disparities in ASDR trends for HNC subtypes were observed across Asia. By 2030, South Asia is projected to maintain the highest ASDRs for HNC (394.59), LC (62.98), LOC (185.31), and OPC (95.50). East and Southeast Asia are expected to show comparable ASDRs for NPC (approximately 50.00), with Southeast Asia leading in TC ASDR (23.90). HNC remains a significant public health challenge in Asia, with substantial heterogeneity in its subtypes across the five subregions. Implementing targeted, region-specific strategies is crucial to mitigating the disease burden.

Chirality amplification and transfer strategies enable covalent organic polymers (COPs) to adopt supramolecular helicity with diverse structural and functional possibilities. Although helicity and chiroptical response typically correlate, we reveal a distinct chiroptical isomerization in helical COPs, where polymers with identical mesoscopic helicity exhibit opposite chiroptical activities. Using a supramolecular templating method, we prepared helical polyimines that maintain uniform helicity yet display reversed Cotton effects upon subtle variations in a single polymerization parameter, such as monomer structures, good-solvent identity, or good/poor solvent ratios. This inversion likely originates from opposite chiral packing of sub-nanometer building units while preserving overall helicity. Leveraging the high symmetry and dynamic covalency of these polyimines, we transformed them into thermodynamically stable helical covalent organic frameworks (COFs) via stepwise linker exchange. Remarkably, both the mesoscopic helicity and the chiroptical isomerization behavior were retained throughout the crystallization process, providing direct evidence for chiroptical isomerization in COFs and enabling advanced design principles for tunable chiral materials. Chirality amplification and transfer strategies are powerful routes to endow covalent organic polymers with supramolecular helicity, expanding their structural and functional versatility. Here, the authors studied helical polyimines with uniform helicity but that displayed reversed chiroptical signatures upon subtle adjustments to a single polymerization parameter.

Numerous herbal-derived natural products are excellent anti-inflammatory agents. Several studies have reported that aloin, the major anthraquinone glycoside obtained from the Aloe species, exhibits anti-inflammatory activity. However, the molecular mechanism of this activity is not well understood. In this report, we found that aloin suppresses lipopolysaccharide-induced pro-inflammatory cytokine secretion and nitric oxide production, and downregulates the expression of tumor necrosis factor alpha (TNF-α), interleukin 6 (IL-6), inducible nitric oxide synthase (iNOS), and cyclooxygenase-2 (COX-2). Aloin inhibits the phosphorylation and acetylation of the NF-κB p65 subunit by suppressing the upstream kinases p38 and Msk1, preventing LPS-induced p65 translocation to the nucleus. We have also shown that aloin inhibits LPS-induced caspase-3 activation and apoptotic cell death. Collectively, these findings suggest that aloin effectively suppresses the inflammatory response, primarily through the inhibition of NF-κB signaling.