Organoids in gastrointestinal diseases: from bench to clinic.

The etiology of gastrointestinal (GI) diseases is intricate and multifactorial, encompassing complex interactions between genetic predisposition and gut microbiota. The cell fate change, immune function regulation, and microenvironment composition in diseased tissues are governed by microorganisms and mutated genes either independently or through synergistic interactions. A comprehensive understanding of GI disease etiology is imperative for developing precise prevention and treatment strategies. However, the existing models used for studying the microenvironment in GI diseases-whether cancer cell lines or mouse models-exhibit significant limitations, which leads to the prosperity of organoids models. This review first describes the development history of organoids models, followed by a detailed demonstration of organoids application from bench to clinic. As for bench utilization, we present a layer-by-layer elucidation of organoid simulation on host-microbial interactions, as well as the application in molecular mechanism analysis. As for clinical adhibition, we provide a generalized interpretation of organoid application in GI disease simulation from inflammatory disorders to malignancy diseases, as well as in GI disease treatment including drug screening, immunotherapy, and microbial-targeting and screening treatment. This review draws a comprehensive and systematical depiction of organoids models, providing a novel insight into the utilization of organoids models from bench to clinic.

Microbial and metabolic profiles unveil mutualistic microbe-microbe interaction in obesity-related colorectal cancer.

Obesity is a risk factor for colorectal cancer (CRC), and the involvement of gut microbiota in the pathogenesis of obesity and CRC is widely recognized. However, the landscape of fecal microbiome and metabolome distinguishing patients with obesity-related CRC from obesity remains unknown. Here, we utilize metagenomic sequencing and metabolomics from 522 patients with CRC and healthy controls to identify the characteristics of obese CRC. Our integrated analysis reveals that obesity-related CRC is characterized by elevated Peptostreptococcus stomatis, dysregulated fatty acids and phospholipids, and altered Kyoto Encyclopedia of Genes and Genomes pathways involving glycerophospholipid metabolism and lipopolysaccharide synthesis. Correlation analysis unveils microbial interactions in obesity, where the probiotic Faecalibacterium prausnitzii and the tumor-promoting species P. stomatis may engage in cross-feeding, thereby promoting tumorigenesis. In vitro experiments affirm enhanced growth under cross-feeding conditions. The mutualistic microbe-microbe interaction may contribute to the association between obesity and elevated CRC risk. Additionally, diagnostic models incorporating BMI-specific microbial biomarkers display promise for precise CRC screening.

Depicting the landscape of gut microbial-metabolic interaction and microbial-host immune heterogeneity in deficient and proficient DNA mismatch repair colorectal cancers.

BACKGROUND: Accumulating evidence has indicated the role of gut microbiota in remodeling host immune signatures, but various interplays underlying colorectal cancers (CRC) with deficient DNA mismatch repair (dMMR) and proficient DNA mismatch repair (pMMR) remain poorly understood. This study aims to decipher the gut microbiome-host immune interactions between dMMR and pMMR CRC. METHOD: We performed metagenomic sequencing and metabolomic analysis of fecal samples from a cohort encompassing 455 participants, including 21 dMMR CRC, 207 pMMR CRC, and 227 healthy controls. Among them, 50 tumor samples collected from 5 dMMR CRC and 45 pMMR CRC were conducted bulk RNA sequencing. RESULTS: Pronounced microbiota and metabolic heterogeneity were identified with 211 dMMR-enriched species, such as Fusobacterium nucleatum and Akkermansia muciniphila, 2 dMMR-depleted species, such as Flavonifractor plautii, 13 dMMR-enriched metabolites, such as retinoic acid, and 77 dMMR-depleted metabolites, such as lactic acid, succinic acid, and 2,3-dihydroxyvaleric acid. F. plautii was enriched in pMMR CRC and it was positively associated with fatty acid degradation, which might account for the accumulation of dMMR-depleted metabolites classified as short chain organic acid (lactic acid, succinic acid, and 2,3-dihydroxyvaleric acid) in pMMR CRC. The microbial-metabolic association analysis revealed the characterization of pMMR CRC as the accumulation of lactate induced by the depletion of specific gut microbiota which was negatively associated with antitumor immune, whereas the nucleotide metabolism and peptide degradation mediated by dMMR-enriched species characterized dMMR CRC. MMR-specific metabolic landscapes were related to distinctive immune features, such as CD8+ T cells, dendritic cells and M2-like macrophages. CONCLUSIONS: Our mutiomics results delineate a heterogeneous landscape of microbiome-host immune interactions within dMMR and pMMR CRC from aspects of bacterial communities, metabolic features, and correlation with immunocyte compartment, which infers the underlying mechanism of heterogeneous immune responses.

Applications of human organoids in the personalized treatment for digestive diseases.

Digestive system diseases arise primarily through the interplay of genetic and environmental influences; there is an urgent need in elucidating the pathogenic mechanisms of these diseases and deploy personalized treatments. Traditional and long-established model systems rarely reproduce either tissue complexity or human physiology faithfully; these shortcomings underscore the need for better models. Organoids represent a promising research model, helping us gain a more profound understanding of the digestive organs; this model can also be used to provide patients with precise and individualized treatment and to build rapid in vitro test models for drug screening or gene/cell therapy, linking basic research with clinical treatment. Over the past few decades, the use of organoids has led to an advanced understanding of the composition of each digestive organ and has facilitated disease modeling, chemotherapy dose prediction, CRISPR-Cas9 genetic intervention, high-throughput drug screening, and identification of SARS-CoV-2 targets, pathogenic infection. However, the existing organoids of the digestive system mainly include the epithelial system. In order to reveal the pathogenic mechanism of digestive diseases, it is necessary to establish a completer and more physiological organoid model. Combining organoids and advanced techniques to test individualized treatments of different formulations is a promising approach that requires further exploration. This review highlights the advancements in the field of organoid technology from the perspectives of disease modeling and personalized therapy.