Techniques, technology & analysis

This Perspective discusses single-cell and single-nuclei RNA sequencing in metabolic dysfunction-associated steatotic liver disease and explains how our understanding of the pathology of the disease will accelerate following the advances in spatial transcriptomics.

Artificial intelligence (AI) is advancing rapidly and is already starting to transform cancer research and care. Here, the authors outline how AI could be incorporated into liver cancer management, highlighting areas with academic, commercial and clinical potential, as well as ongoing progress and pitfalls.

Bile acids have important roles in human metabolism and immune regulation. In this Perspective, Dorrestein and colleagues discuss the technologies and data science-related approaches that are improving our understanding of the diversity of bile acids and their multifaceted roles.

Histological assessment of nonalcoholic fatty liver disease (NAFLD) is essential for clinical practice as it outlines diagnosis and lays the foundation of medical care. This Perspective summarizes the advancements in digital histology and discusses current and future applications in NAFLD.

In this Review, the authors discuss gene therapy involving the use of recombinant adeno-associated virus vectors for the treatment of inherited liver diseases, including ongoing clinical trials that are producing promising results.

Advances in artificial intelligence (AI) are changing endoscopy and gastrointestinal surgery, including computer-assisted detection and diagnosis, computer-aided navigation, robot-assisted intervention and automated reporting. This Perspective introduces the role of AI in computer-assisted interventions in gastroenterology with insights on regulatory aspects and the challenges ahead.

Ceresa et al. discuss machine perfusion technologies for liver preservation and transplantation, including the potential of hypothermic and normothermic machine perfusion to improve preservation time and organ quality, as well as the future applications of perfusion technologies.

In this Review, Chu and Traverso provide an overview of gastrointestinal-based drug delivery, discussing conventional delivery methods and challenges posed by the gastrointestinal tract as a drug delivery environment, as well as emerging technologies.

Metabolomics and lipidomics approaches are being used to identify biomarkers for nonalcoholic fatty liver disease (NAFLD). This Review discusses the application of metabolomics and lipidomics in clinical studies and in the identification of key metabolic pathway alterations in NAFLD.

Human microphysiology systems (MPS) have evolved as experimental model systems. This Review explores these so-called organ-on-a-chip systems and the role of biomimetic human liver MPS in drug development and precision medicine, providing insights into their design and use as models of liver physiology and disease.

Large-scale datasets of increasing size and complexity are being produced in the microbiome and oncology field. This Perspective discusses the potential to harness gut microbiome analysis, big data and machine learning in cancer, and the potential and limitations with this approach.

Single-cell transcriptomic technologies are transforming our understanding of cellular diversity and function in health and disease. This Review discusses how these technologies have been applied in hepatology, advancing our understanding of cellular heterogeneity and providing novel insights into liver biology such as metabolic zonation and the mechanisms underpinning liver regeneration.

The evidence base for robotic gastrointestinal surgery does not yet support its widespread adoption. Here, Kinross et al. discuss this evidence base and the principles on which future gastrointestinal surgical trials should be based, as well as emerging technologies.

Organoid technology has emerged as a powerful method for studying gastrointestinal cancers. This Review describes organoid models of gastrointestinal cancers, such as colorectal and liver cancer, and discusses how they can be used in basic and translational research in fields such as drug discovery and personalized medicine.

Several big data ‘omics’ studies have analysed hepatocellular carcinoma (HCC). This Review describes omics studies in HCC and their potential in drug discovery and as candidate biomarkers. The application of emerging new artificial intelligence methods in HCC drug discovery is also discussed.

The introduction of white light imaging capsule endoscopy has motivated research to improve its diagnostic capabilities through integration with other sensing modalities. In this Review, the authors summarize studies on non-white light imaging devices, such as those using optical coherence tomography, ultrasonography or biophysical measurements

In this Review, the authors explore potential applications of big data in IBD research, including predictive models of disease course and response to therapy, characterization of disease heterogeneity, drug safety and development, precision medicine and cost-effectiveness of care.

Electric stimulation of nerves might be useful for various gastrointestinal disorders. In this Review, the authors discuss neuromodulation therapies in relation to current knowledge of the nerve circuitry, provide insights into possible mechanisms and explore reasons for limited success and how effectiveness might be improved.

Optogenetic and chemogenetic approaches hold great promise in neurogastroenterological research. In this Review, the authors discuss the advantages and limitations of available tools and cover optimal approaches for targeting specific cell types in the gut.

Environmental enteric dysfunction (EED) is an important cause of impaired development and stunting in children in the developing world. In this Consensus Statement, the authors assess the potential of optical biopsy technologies to facilitate the study and diagnosis of this global burden.

Various technologies and systems have been developed to improve adenoma detection rate during colonoscopy and thereby reduce colorectal cancer incidence. Here, Matsuda and colleagues discuss how add-on devices, colonoscope advances and image-enhanced endoscopy might assist in the detection of polyps and adenomas.

Clinicians face a rapidly evolving set of challenges and opportunities for generating insights into the health of patients from microbiome analysis. Here, the authors summarize the major decision points confronting new entrants to the field or for those designing new projects in microbiome research.

Magnetic resonance imaging following injection of hepatobiliary contrast agents improves the detection of hepatocellular carcinomas when contrast agent accumulations in tumours and the surrounding pathological liver differ. However, tissue accumulation is poorly investigated, and this Clinical Outlook article highlights experimental data to understand better contrast agent accumulation in human pathological livers.

Live microorganisms can be manipulated and engineered for colorectal cancer detection and treatment through methods such as faecal microbiota transplantation, native bacteria engineering and synthetic circuit engineering. Although promising, substantial effort is required to translate these approaches for clinical use.

The application of single-cell RNA sequencing platforms has generated notable insights into the heterogeneity underlying pancreatic ductal adenocarcinoma (PDAC), encompassing both the neoplastic compartment and the tumour microenvironment. In this Comment, we discuss the most pertinent findings gleaned from both mouse models and human PDAC samples, as well as future opportunities.

Traditionally underutilized human excreta have emerged as a rich source of digital biomarkers for disease prevention and early detection. In this Comment, we highlight the breadth of digital biomarkers that can be extracted from human excreta and their potential uses in the context of ‘precision health’.

Intestinal ultrasonography (IUS) is an emerging, noninvasive, highly accessible and low-cost cross-sectional imaging modality for inflammatory bowel disease. This Comment summarizes how IUS in a point-of-care setting enables close patient monitoring.

In 2020, major advances to the understanding of gastrointestinal inflammatory and infectious disease have been made using ‘mini-gut’ organoids. Key findings include the discovery of somatic inflammatory gene mutations in ulcerative colitis epithelium, a unique mutational signature in colorectal cancer caused by genotoxic Escherichia coli, and infection of intestinal organoids by SARS-CoV-2.

Deep learning can mine clinically useful information from histology. In gastrointestinal and liver cancer, such algorithms can predict survival and molecular alterations. Once pathology workflows are widely digitized, these methods could be used as inexpensive biomarkers. However, clinical translation requires training interdisciplinary researchers in both programming and clinical applications.