Free Radic Biol Med. 2026 Sep 9;256:441-460. doi: 10.1016/j.freeradbiomed.2026.09.006. Online ahead of print.

ABSTRACT

Gestational diabetes mellitus (GDM) is a common pregnancy complication with a rising global prevalence, posing serious short-term and long-term health threats to both mothers and offspring. This review repositions GDM as a systemic disorder in which oxidative stress acts as a proposed mechanistic hub, linking upstream risk factors to downstream pathophysiology. We first examine how "upstream" factors-including genetic susceptibility, pre-conception status, and environmental exposures-converge to promote a state of pathological redox imbalance. We then examine key mechanistic pathways through which oxidative stress is thought to contribute to systemic insulin resistance and pancreatic β-cell failure, highlighting novel pathways involving intercellular communication via tunneling nanotubes and exosomes. Furthermore, we explore the downstream cascade, where oxidative stress may program maternal accelerated biological aging and multi-organ offspring disease trajectories through nuclear epigenetic programming and mitochondrial dysfunction programming, leaving what has been termed a persistent "metabolic memory". Consequently, this review evaluates emerging strategies that target oxidative stress for early prediction and precision intervention. Early prediction models based on direct redox biomarkers and multi-omics signatures hold potential to shift diagnosis from late-gestation oral glucose tolerance test (OGTT) to first-trimester risk stratification. Current supporting evidence draws from human epidemiological associations, ex vivo placental analyses, and experimental models. However, direct causal and interventional validation in pregnant women remains limited. Integrating targeted redox risk stratification and precision interventions into a life-course clinical framework may help interrupt the intergenerational transmission of metabolic disease initiated by GDM.

PMID:42716407 | DOI:10.1016/j.freeradbiomed.2026.09.006

Front Immunol. 2026 Apr 14;17:1767512. doi: 10.3389/fimmu.2026.1767512. eCollection 2026.

ABSTRACT

Gastric cancer (GC) is plagued by profound intratumoral heterogeneity and a complex tumor microenvironment (TME), which are the core obstacles to precise diagnosis and treatment. Conventional bulk multi-omics technologies average molecular signals across tissues, thus masking cellular heterogeneity; single-cell multi-omics resolves cellular diversity but dissociates cells from their native spatial context, leading to the loss of critical information on intercellular crosstalk and molecular spatial distribution. These limitations result in an incomplete understanding of GC pathogenesis and TME regulatory networks. Spatial multi-omics technologies, integrating genomics, transcriptomics, proteomics, and metabolomics with high-resolution spatial localization, address these key scientific problems by preserving the native tissue architecture and elucidating the spatiotemporal dynamics of molecular and cellular events in GC. This review systematically synthesizes the latest advances in the application of four major spatial multi-omics modalities in GC research over the past 15 years, with a critical evaluation of the technical performance, methodological shortcomings, and clinical translation potential of existing studies. Unlike previous reviews that only summarize research findings, this work uniquely integrates technical principles, mechanistic discoveries, and clinical translation of spatial multi-omics in GC, deeply analyzes the practical barriers to clinical application, and systematically elaborates the integration of spatial multi-omics with artificial intelligence (AI). We also identify unresolved challenges in the field and propose future development directions, providing a comprehensive and in-depth reference for the advancement of GC precision medicine based on spatial multi-omics.

PMID:42058209 | PMC:PMC13120937 | DOI:10.3389/fimmu.2026.1767512

J Cancer. 2026 Jan 30;17(3):515-523. doi: 10.7150/jca.127381. eCollection 2026.

ABSTRACT

Gastrointestinal (GI) cancers remain a leading cause of cancer-related morbidity and mortality worldwide, largely due to their molecular heterogeneity, complex tumor microenvironment (TME), and variable treatment responses. In recent years, the emergence of spatially resolved omics technologies-encompassing spatial transcriptomics, proteomics, metabolomics, and epigenomics-has revolutionized the ability to interrogate tumor architecture with unprecedented resolution. These methods enable precise mapping of cellular and molecular interactions within intact tissue contexts, thereby uncovering spatially defined niches that influence tumor progression, immune evasion, and therapeutic resistance. In GI malignancies such as colorectal, gastric, and esophageal cancers, spatial omics have provided critical insights into cancer-stromal-immune crosstalk, identified predictive biomarkers for immunotherapy and targeted agents, and guided the development of novel therapeutic strategies. This review synthesizes the latest advances in spatial omics applied to GI oncology over the past five years, with an emphasis on their integration into early diagnosis, treatment stratification, and real-time monitoring of therapeutic efficacy. We also discuss current challenges, including standardization, data integration, and clinical validation, as well as future directions for incorporating spatial profiling into routine oncology practice. By bridging the gap between bench discoveries and bedside applications, spatial omics hold transformative potential for achieving truly personalized treatment in gastrointestinal cancers.

PMID:41869445 | PMC:PMC13003551 | DOI:10.7150/jca.127381