Xiaolin Zhong

Cancer metabolic reprogramming has typically been regarded as a cell-autonomous process; however, this perspective fails to fully capture the intricacies of immunosuppression and treatment resistance within the heterogeneous and spatially organized tumor microenvironment (TME). While the metabolism of all major nutrients is subject to spatial constraints, lipid metabolism exhibits a unique and pronounced sensitivity due to the hydrophobic nature of lipids, which necessitates a specialized network of carrier proteins and organelles for their transport, storage, and signaling. We propose a model of spatio-specific lipid-immune regulatory programs that connects the intrinsic metabolic drivers of cancer cells with the spatial architecture of the TME, While grounded in existing literature, several of the mechanistic connections we describe represent a conceptual framework and working hypotheses that require direct experimental testing in the tumor microenvironment. Our investigation focuses on how three distinct spatial niches, the hypoxic core, invasive margin, and perivascular area, shape diverse lipid metabolic profiles through their unique physicochemical conditions and cellular compositions. Metabolic states specific to location determine the destiny and role of infiltrating immune cells, shaping an immune network significantly impacted by spatial positioning. Additionally, we investigate the potential of this spatial framework in identifying niche-specific biomarkers and developing novel combination therapies.

The reduced phagocytic activity of macrophages in the tumor microenvironment (TME) and the presence of anti-phagocytic factors in cancer cells hinder the effectiveness of immune checkpoint inhibitors (ICIs) in clinical settings. Consequently, our objective was to create a risk assessment model using antibody-dependent cellular phagocytosis (ADCP) regulators to serve as prognostic indicators and immunotherapy markers for individuals with hepatocellular carcinoma (HCC). This research incorporated The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) group, the GSE14520 group, the International Cancer Genome Consortium (ICGC) group, and the single-cell dataset GSE166635. Machine learning was used to discover ADCP genes closely linked to prognosis, helping to determine the molecular subtypes of ADCP in HCC samples. The least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression algorithms were used to develop the ADCP-related signature (ADCPRS). This signature was evaluated using both training and external validation datasets. Furthermore, a nomogram that integrates ADCPRS was created to function as a quantitative instrument for predicting outcomes in clinical settings. A comprehensive multi-omics investigation was performed, integrating genomic, single-cell transcriptomic, and bulk transcriptomic analyses, with the aim of gaining a more profound understanding of the prognostic signature. We assessed how different risk categories respond to immunotherapy and identified drugs tailored to target these specific groups for customized treatment. We identified two ADCP subgroups by analyzing 91 genes linked to HCC prognosis. The two ADCP subgroups showed distinct outcomes, pathway activation, immune checkpoint gene expression levels, and immune cell infiltration within the TME. We developed a unified ADCPRS that excels in forecasting clinicopathological characteristics, patient outcomes, and TME stromal activity in HCC. The nomogram incorporating ADCPRS offered a numerical tool for use in medical practice. Notably, the high-risk group presented inflamed TME with an improved response to ICI. In addition, the high-ADCPRS group presented a high sensitivity to the derivative compounds provided by Cancer Therapeutics Response Portal (CTRP) and Profiling Relative Inhibition Simultaneously in Mixtures (PRISM). Our research developed a signature linked to ADCP, which shows promise as a key tool for predicting outcomes, implementing prevention, and enabling personalized treatment in HCC.

A growing body of evidence indicates a strong relationship between inflammatory bowel disease (IBD) and a range of renal conditions, including chronic kidney disease, glomerulonephritis, tubulointerstitial disorders, nephrolithiasis, and secondary (AA) amyloidosis, which are rare yet severe systemic complications. In this review, we integrated clinical and epidemiological data to clarify the pathophysiological mechanisms underlying the gut–kidney axis. Existing evidence was critically appraised with the observation that, although associative data are plentiful, causal pathways in humans remain incompletely understood. We describe how dysbiosis of the gut microbiota, breakdown of the intestinal barrier, and altered microbial metabolites (e.g., trimethylamine N-oxide [TMAO] and short-chain fatty acids [SCFAs]) drive systemic inflammation and contribute to renal injury. Newer findings point to intestinal lymphatic dysfunction as a crucial intermediary. Injury to the proteinuric kidney triggers lymphangiogenesis within the gut and reshapes the composition of the lymph, thereby facilitating the systemic delivery of pro-inflammatory mediators, including IsoLG-modified apolipoprotein AI and Th17 cells, that worsen renal damage, thus establishing a self-reinforcing pathological loop. Nonetheless, evidence supporting the lymphatic pathway currently relies mainly on animal studies, with limited human validation. We also examined the contribution of conserved pathways such as IL-11-driven fibrosis, GSDMD-mediated pyroptosis, and free light chain toxicity. From a translational standpoint, these overlapping pathways represent promising therapeutic targets, although further testing is required to establish their clinical applicability. Such mechanistic insights underscore the importance of vigilant renal monitoring in individuals with IBD and careful management of drug-induced nephrotoxicity. Strategies that target these shared mechanisms, whether through restoration of the microbiota, modulation of lymphatic function, or precision immunomodulation, herald a new frontier for therapies aimed at dual-organ protection.

Hepatocellular carcinoma (HCC) is characterized by substantial heterogeneity and immune tolerance, and its therapeutic efficacy is profoundly influenced by the immune microenvironment. Ferroptosis, an iron-dependent form of regulated cell death, is closely linked to tumor immune regulation. We conducted an integrative multi-omics analysis to systematically delineate the composition and function of the ferroptosis–immunity network in HCC. Using TCGA data, we identified ferroptosis-related prognostic genes. By integrating these with immune features via weighted gene co-expression network analysis (WGCNA), we defined 55 ferroptosis–immune microenvironment–related genes (FIMRGs). Single-cell transcriptomic analysis showed that, among immune cell types, macrophages exhibited the highest ferroptosis–immunity activity. Spatial transcriptomics revealed that macrophages with high ferroptosis signaling (FehighMac) preferentially infiltrated tumor nests. These macrophages engaged in robust interactions with T cells via ligand–receptor axes such as ICAM1–ITGAX/ITGB2, TNF–TNFR, and LGALS9–CD45, potentially promoting T-cell exhaustion and shaping an immunosuppressive microenvironment. We identified CAPG-positive macrophages (CAPG + Mac) as the key driver of this process. Characterized by suppressed ferroptosis, enhanced glutathione metabolism, and upregulated immune checkpoints, CAPG + Mac appear to foster an immune-tolerant microenvironment. A prognostic model constructed from CAPG + Mac signature genes effectively stratified HCC patients into high- and low-risk groups and demonstrated stable predictive performance in external validation. This study reveals that CAPG + Mac putatively modulate ferroptosis signaling to influence immune homeostasis, highlighting them as a key target for HCC progression and immunotherapy responsiveness.

Background: Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy characterized by a complex tumor microenvironment. Ubiquitination regulates key oncogenic processes and microenvironmental remodeling; however, its cell type–specific activity and spatial organization within the PDAC microenvironment remain poorly understood. Materials and Methods: Single‐cell RNA sequencing, spatial transcriptomics, and bulk RNA‐seq datasets of PDAC were integrated for multiomics analysis. Ubiquitination activity was quantified using gene‐set scoring algorithms, followed by cell‐communication and spatial interaction analyses. Prognostic models were constructed using bulk cohorts, and key findings were validated through gene‐silencing functional assays. Results: Ubiquitination activity was significantly increased in PDAC tissues compared with adjacent normal tissues, with ductal epithelial cells and fibroblasts showing the most prominent elevation. High ubiquitination states were associated with enhanced ductal–fibroblast interactions and distinct spatial patterns linked to invasion‐associated tumor regions. Integration of ubiquitination‐associated gene signatures identified a robust prognostic model, highlighting an extracellular matrix–related factor consistently overexpressed in tumors and associated with poor survival. Functional assays demonstrated that suppression of this factor inhibited proliferation, migration, invasion, and survival of pancreatic cancer cells. Conclusion: Ubiquitination organizes ductal–fibroblast crosstalk within the PDAC microenvironment and links spatial tumor ecology with disease aggressiveness and patient prognosis. Targeting ubiquitination‐associated microenvironmental programs may offer new strategies for prognostic stratification and therapeutic intervention.

Resistance to chemotherapy, targeted agents, and particularly immunotherapy remains the principal challenge in the management of gastrointestinal malignancies. This review aims to comprehensively delineate the molecular and microenvironmental drivers of resistance, with emphasis on mechanisms impacting immunotherapy response, and evaluate emerging, mechanism−guided interventions (including immunotherapeutic combinations) for precision therapy. We first examine intrinsic mechanisms—including drug−target alterations, dysregulated drug metabolism and efflux, hyperactivation of DNA damage repair pathways, and epigenetic remodeling—and extrinsic influences stemming from the tumor microenvironment and extracellular matrix remodeling. We then highlight epithelial–mesenchymal transition (EMT) as a critical nexus that integrates stromal cues with cell−intrinsic survival programs, thereby promoting drug efflux and immune evasion. Next, we discuss how single−cell and spatial omics, liquid biopsy, patient−derived organoids, and AI−enabled analytics facilitate subclone−level mapping of resistance networks and real−time tracking of clonal evolution. Finally, we review mechanism−based strategies—including KRAS G12C inhibitors, efflux−pump antagonists, apoptosis reactivators, and epigenetic/autophagy modulators—and propose an integrated, multimodal regimen leveraging immunotherapy where appropriate, informed by real-time drug sensitivity data (e.g., from liquid biopsy), dynamic biomarkers and AI−driven optimization to overcome resistance and improve patient outcomes.

T cells play a central role in the immune response to gastric cancer, and their dysfunction directly contributes to immune escape from the tumor and limits the efficacy of immunotherapy. The immune microenvironment of gastric cancer consists of a wide range of cells and molecules, and this complex and dynamic environment exerts profound inhibitory effects on T cell function. upregulation of PD-1, CTLA-4, and other inhibitory molecules is a key mechanism of T cell depletion, and metabolic reprogramming and chronic antigenic stimulation further weaken the anti-tumor activity of T cells. In recent years, PD-1/PD-L1 inhibitors have demonstrated some efficacy in gastric cancer, but the problem of drug resistance remains prominent. To address these challenges, combinatorial therapeutic strategies have gradually become the focus of research, especially combining immune checkpoint inhibitors with chemotherapy, radiotherapy, or targeted therapy to enhance the antitumor effect of immunotherapy. This review delves into the molecular mechanisms of T-cell depletion and its impact in gastric cancer immunotherapy, and analyzes the potential application of biomarkers in predicting treatment response. By comprehensively analyzing T-cell depletion and the immune microenvironment in gastric cancer, this paper provides a theoretical basis for the development of future personalized combinatorial therapeutic strategies, with the aim of improving patient prognosis and enhancing the overall therapeutic efficacy.

Ozanimod was approved in the United States in March 2020 for the treatment of relapsing multiple sclerosis and subsequently in 2021 for moderately to severely active ulcerative colitis. However, there is limited information available on the adverse drug events associated with its use. The main objective of this study was to explore the safety of Ozanimod after its market launch. Data was gathered from the United States Food and Drug Administration Adverse Event Reporting System database. To detect safety signals associated with Ozanimod adverse events, disproportionality analyses were performed using the reporting odds ratio, proportional reporting ratio, Bayesian confidence propagation neural network, and multi-item gamma Poisson shrinker algorithms. We extracted 7,118,789 reports from the FDA Adverse Event Reporting System database, of which 5429 reports identified Ozanimod as the primary suspect drug. Adverse reactions attributed to Ozanimod manifested across 26 organ systems, encompassing a total of 90 preferred terms meeting the criteria of all 4 algorithms simultaneously. In our study, back pain, hypertension, increased blood pressure, elevated hepatic enzymes, abnormal hepatic enzymes, pollakiuria, micturition urgency, and herpes zoster were consistent with the results of clinical trials. Notably, we observed some common adverse drug reaction signals, such as hypesthesia, muscle spasms, balance disorder, and gait disturbance, which were not documented in the official drug label. The majority of adverse events occurred within the initial 30 days following the initiation of Ozanimod treatment. Ozanimod presents the potential for diverse adverse reactions alongside its therapeutic benefits. Hence, in clinical practice, prompt detection of adverse drug reactions and the implementation of timely and effective preventive measures are essential.

Background Ulcerative colitis (UC), a chronic inflammatory bowel disease, carries an elevated risk of colitis-associated colorectal cancer (CAC). While PANoptosis—a coordinated cell death mechanism integrating pyroptosis, apoptosis, and necroptosis—has been linked to inflammatory disorders, its role in UC progression and CAC transformation remains undefined. Objective To delineate PANoptosis-related signatures and develop predictive models for the assessment of UC and CAC. Methods Transcriptomic data from UC patients, CAC cases, and controls (GEO database) were analyzed to identify PANoptosis-associated genes. Enrichment and immune infiltration analyses elucidated functional roles, while a dextran sulfate sodium (DSS)-induced murine colitis model validated candidate gene expression via Western blot. Single-cell sequencing dissected cellular heterogeneity, Mendelian randomization established causality, and molecular docking screened therapeutic agents. Results Four PANoptosis hub genes (CASP1, LCN2, STAT3, ZBP1) were identified as UC drivers. The PANoptosis-Associated Risk Score (PAR-Score) demonstrated robust diagnostic accuracy (AUC > 0.75) and stratified disease activity, anti-TNF-α responsiveness, and CAC risk. Molecular docking revealed strong binding affinity between epidermal growth factor receptor (EGFR) inhibitors and target proteins (binding energy: −6.0 to −8.4 kcal/mol), suggesting therapeutic potential. Conclusion The PAR-Score based on PANoptosis genes predicts the progression of UC and the response to anti-TNF-α treatment. EGFR inhibitors may serve as potential therapeutic agents for UC and CAC.

Background: Patients with inflammatory bowel disease may develop infective pneumonia after using tumor necrosis factor-α inhibitors(TNFis). Due to the limitations of clinical trials, the occurrence of infective pneumonia in patients with inflammatory bowel disease using tumor necrosis factor-α(TNF-α) inhibitors remains uncertain. This article primarily explores the relationship between TNF-α inhibitors and adverse events(AEs) related to infective pneumonia in the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database. Methods: We collected data from the FAERS database, extracting reports for each TNF-α inhibitor from their market launch until the first quarter of 2024 (infliximab, adalimumab, certolizumab pegol, and golimumab) and assessing infective pneumonia associated with TNF-α inhibitors using disproportionality analysis. Results: After removing duplicate reports, a total of 7176 reports were included. Infliximab and adalimumab exhibited the highest incidence of infective pneumonia-related adverse events, occurring in 3,858 and 2,819 cases, respectively, whereas certolizumab pegol and golimumab showed lower incidences with only 297 and 202 cases. Infliximab had the most positive signals, totaling 10, including tuberculosis, pulmonary tuberculosis, pneumocystis jirovecii pneumonia, histoplasmosis, pneumonia bacterial, pneumonia legionella, bronchopulmonary aspergillosis, tuberculous pleurisy, pneumonia cryptococcal, blastomycosis. Golimumab had seven positive signals, including pneumonia, tuberculosis, pulmonary tuberculosis, bronchopulmonary aspergillosis, pneumonia legionella, pneumonia bacterial, and COVID-19 pneumonia. Certolizumab pegol had only two positive signals: pneumonia and pneumonia klebsiella. However, adalimumab did not show signals of infective pneumonia. Conclusion: Except for adalimumab, the other three TNF-α inhibitors showed positive signals related to infective pneumonia, with tuberculosis-related diseases being the most common. Our study provides important insights for healthcare professionals, which can help reduce the occurrence of infective pneumonia associated with TNF-α inhibitors.