Stomach encyclopedia: Combined single-cell and spatial transcriptomics reveal cell diversity and homeostatic regulation of human stomach

Dissecting the Spatial and Single-Cell Transcriptomic Architecture of Cancer Stem Cell Niche Driving Tumor Progression in Gastric Cancer

Despite significant advancements in identifying novel therapeutic targets and compounds, cancer stem cells (CSCs) remain pivotal in driving therapeutic resistance and tumor progression in gastric cancer (GC). High-resolution knowledge of the transcriptional programs underlying the role of CSC niche in driving tumor stemness and progression is still lacking. Herein, spatial and single-cell RNA sequencing of 32 human gastric mucosa tissues at various stages of malignancy, illuminating the phenotypic plasticity of tumor epithelium and transcriptional trajectory from mature gastric chief cells to the CSC state, which is associated with activation of EGFR and WNT signaling pathways, is conducted. Moreover, the CSCs interact with not only the immunosuppressive CXCL13+ T cells and CCL18+ M2 macrophages to evade immune surveillance, but also the inflammatory cancer-associated fibroblasts (iCAFs) to promote tumorigenesis and maintain stemness, which construct the CSC niche leading to inferior prognosis. Notably, it is uncovered that amphiregulin (AREG) derived from iCAFs promotes tumor stemness by upregulating the expression of SOX9 in tumor cells, and contributes to drug resistance via the AREG-ERBB2 axis. This study provides valuable insight into the characteristics of CSC niche in driving tumor stemness and progression, offering novel perspective for designing effective strategies to overcome GC therapy resistance.

The role of the tumor microenvironment and inflammatory pathways in driving drug resistance in gastric cancer: A systematic review and meta-analysis

Tumor microenvironment (TME) plays a pivotal role in progression and low responsiveness to chemotherapy of gastric cancer (GC). The cascade of events that culminate with a sustained and chronic activation of inflammatory pathways underlies gastric tumorigenesis. Infiltrating immune cells enrolling in crosstalk with cancer cells that regulate inflammatory and immune status, generating an immunosuppressive TME that influences the response to therapy. Here we discuss the role of TME and the activation of inflammatory pathways to comprehend strategies to improve drug response. Furthermore, we provides systematic insight the role of TME cytotypes and related signatures reinforcing the critical roles of TAMs and Tregs, in promoting GC chemoresistance and tumor progression.

Effect of cooking treatment on protein digestibility, peptide profile and potential bioactive peptides of beef tripe during in vitro gastrointestinal digestion

The purpose of this study was to understand the effects of cooking treatment on the protein hydrolysis of beef tripe and the release of potentially bioactive peptides using an in vitro gastrointestinal model. The results showed that digestion promoted the hydrolysis of proteins and release of free amino acids in beef tripe, but cooking treatment significantly reduced them. The sample of the cooked beef tripe after gastrointestinal digestion had the highest antioxidant activity. Peptidomic and in silico analyses of gastrointestinal digesta were performed to identify bioactive antioxidant peptide sequences. A total of 14 peptides were identified, which were confirmed with structural characteristics to exhibit antioxidation effects as well as a range of other biological functions, such as angiotensin I-converting enzyme (ACE) and dipeptidyl peptidase IV (DPP-IV) inhibitory activities. These findings indicate that beef tripe and its digestive products have health-promoting potential, which can be utilized in functional food as ingredients.

Divergent lineage trajectories and genetic landscapes in human gastric intestinal metaplasia organoids associated with early neoplastic progression

BACKGROUND

Gastric intestinal metaplasia (IM) is a precancerous stage spanning a morphological spectrum that is poorly represented by human cell line models.

OBJECTIVE

We aim to establish and characterise human IM cell models to better understand IM progression along the cancer spectrum.

DESIGN

A large human gastric IM organoid (IMO) cohort (n=28), their clonal derivatives and normal gastric organoids (n=42) for comparison were established. Comprehensive multi-omics profiling and functional characterisation were performed.

RESULTS

Single-cell transcriptomes revealed IMO cells spanning a spectrum from hybrid gastric/intestinal to advanced intestinal differentiation. Their lineage trajectories connected different cycling and quiescent stem and progenitors, highlighting differences in gastric to IM transition and the potential origin of IM from STMN1 cycling isthmus stem cells. Hybrid IMOs showed impaired differentiation potential, high lineage plasticity beyond gastric or intestinal fates and reactivation of a fetal gene programme.Cell populations in gastric IM and cancer tissues were highly similar to those derived from IMOs and exhibited a fetal signature. Genomically, IMOs showed elevated mutation burden, frequent chromosome 20 gain and epigenetic deregulation of many intestinal and gastric genes. Functionally, IMOs were FGF10 independent and showed downregulated FGFR2. Several IMOs exhibited a cell-matrix adhesion independent subpopulation that displayed chromosome 20 gain but lacked key cancer driver mutations, potentially representing the earliest neoplastic precursor of IM-induced gastric cancer.

CONCLUSIONS

Overall, our IMO biobank captured the heterogeneous nature of IM, revealing mechanistic insights on IM pathogenesis and progression, offering an ideal platform for studying early gastric neoplastic transformation and chemoprevention.

Predicting chemotherapy responsiveness in gastric cancer through machine learning analysis of genome, immune, and neutrophil signatures

BACKGROUND

Gastric cancer is a major oncological challenge, ranking highly among causes of cancer-related mortality worldwide. This study was initiated to address the variability in patient responses to combination chemotherapy, highlighting the need for personalized treatment strategies based on genomic data.

METHODS

We analyzed whole-genome and RNA sequences from biopsy specimens of 65 advanced gastric cancer patients before their chemotherapy treatment. Using machine learning techniques, we developed a model with 123 omics features, such as immune signatures and copy number variations, to predict their chemotherapy outcomes.

RESULTS

The model demonstrated a prediction accuracy of 70-80% in forecasting chemotherapy responses in both test and validation cohorts. Notably, tumor-associated neutrophils emerged as significant predictors of treatment efficacy. Further single-cell analyses from cancer tissues revealed different neutrophil subgroups with potential antitumor activities suggesting their usefulness as biomarkers for treatment decisions.

CONCLUSIONS

This study confirms the utility of machine learning in advancing personalized medicine for gastric cancer by identifying tumor-associated neutrophils and their subgroups as key indicators of chemotherapy response. These findings could lead to more tailored and effective treatment plans for patients.

Comprehensive analysis and experimental validation of disulfidptosis-associated prognostic signature and immune microenvironment characterization of gastric cancer

BACKGROUND

Gastric cancer (GC) is one of the most common causes of cancer-related death worldwide. As a novel form of programmed cell death, disulfidptosis is characterized by excessive cysteine accumulation, disulfide stress and actin destruction. There is evidence that targeting disulfidptosis is a promising anticancer strategy. Further improvement of GC risk stratification based on disulfidptosis has positive clinical significance.

METHODS

We analyzed the expression levels of disulfidptosis-associated genes (DPAGs) in normal and GC tissues and characterized the molecular subtypes of GC patients. Based on the characteristics of DPAG subtypes, differentially expressed prognosis-related genes were selected by LASSO-univariate Cox analysis and multivariate Cox analysis analyzed to establish a prognostic model. Using single-cell sequencing analysis reveals the cell subpopulation for GC. The function of the selected target in GC was verified by in vitro experimental means, including siRNA, qRT-PCR, Western blot, CCK-8, and Transwell assay.

RESULTS

DPAG score was verified to be an independent prognostic factor of GC and was significantly associated with poor prognosis of gastric cancer. Subsequent studies on subgroup immunoinfiltration characteristics, drug sensitivity analysis, immunotherapy response and somatic mutation characteristics of DPAG score comprehensively confirmed the potential guiding significance of DPAG score for individualized treatment of gastric cancer patients. Single-cell sequencing analysis revealed the expression characteristics of DPAG-related prognostic signatures across cell subpopulations. In vitro experiments showed APC11, as one of the selected DPAGs, was highly expressed in gastric cancer, and knockdown of APC11 could significantly inhibit the proliferation and migration of GC cells, demonstrating the reliability of bioinformatics results.

CONCLUSION

The results of this study provide a new perspective for exploring the role of disulfidptosis in the occurrence and development of GC.

Mendelian randomization and multiomics comprehensively reveal the causal relationship and potential mechanism between atrial fibrillation and gastric cancer

Objective

Gastric cancer is a harmful disease, the comorbidity mechanism and causality relationship between this disease and other diseases are worth studying.

Methods

Using a two-sample Mendelian Randomization method, this study revealed the potential causal effect of atrial fibrillation (AF) on gastric cancer (GC) risk by constructing a genetic instrument containing 136 AF associated SNPs. Subsequently, analysis identifies 62 AF-GC co-associated genes and constructs a protein-protein interaction network of key genes. High-throughput sequencing data were further used to analyze the association between the two and their impact on the survival outcome of gastric cancer.

Results

The results showed that AF was negatively associated with gastric cancer, and further analysis revealed that this relationship was independent of GC risk factors such as chronic gastritis, Helicobacter pylori infection, and alcohol consumption. Enrichment analysis reveals associations of key genes with pathways related to cardiovascular disease, inflammatory gastrointestinal diseases, and tumorigenesis. Through single-cell sequencing data analysis, fibroblast subpopulations associated with the key gene set are identified in GC, showing significant correlations with cancer progression and inflammation regulation pathways. Transcription factor analysis and developmental trajectory analysis reveal the potential role of fibroblasts in GC development. Finally, prognosis analysis and gene mutation analysis using TCGA-STAD data indicate an adverse prognosis associated with the key gene set in GC.

Conclusion

This study provides new insights into the association between AF and GC and offers novel clues for understanding its impact on the pathogenesis and therapeutic strategies of GC.

Sleeve gastrectomy reveals the plasticity of the human gastric epithelium

Gastrin is secreted following a rise in gastric pH, leading to gastric acid secretion. Sleeve gastrectomy (SG), a bariatric surgery where 80% of the gastric corpus is excised, presents a challenge for gastric pH homeostasis. Using histology, and single-cell RNA sequencing of the gastric epithelium in 12 women, we observed that SG is associated with an increase in a sub-population of acid-secreting parietal cells that overexpress respiratory enzymes and an increase in histamine-secreting enterochromaffin-like cells (ECLs). ECLs of SG-operated patients overexpressed genes coding for biosynthesis of neuropeptides and serotonin. Mathematical modeling showed that pH homeostasis by gastrin is analogous to non-linear proportional and integral control, that drives adaptation of the epithelium to acid-secretion demand. Quantitative model predictions were validated in patients. The results demonstrate human gastric epithelium remodeling following SG at the molecular and cellular levels, and more generally how trophic hormones enable robust adaptation of tissue function to meet physiological demand.

Spatial-Omics Methods and Applications

Traditional tissue profiling approaches have evolved from bulk studies to single-cell analysis over the last decade; however, the spatial context in tissues and microenvironments has always been lost. Over the last 5 years, spatial technologies have emerged that enabled researchers to investigate tissues in situ for proteins and transcripts without losing anatomy and histology. The field of spatial-omics enables highly multiplexed analysis of biomolecules like RNAs and proteins in their native spatial context-and has matured from initial proof-of-concept studies to a thriving field with widespread applications from basic research to translational and clinical studies. While there has been wide adoption of spatial technologies, there remain challenges with the standardization of methodologies, sample compatibility, throughput, resolution, and ease of use. In this chapter, we discuss the current state of the field and highlight technological advances and limitations.

Challenges and Opportunities in the Clinical Translation of High-Resolution Spatial Transcriptomics

Pathology has always been fueled by technological advances. Histology powered the study of tissue architecture at single-cell resolution and remains a cornerstone of clinical pathology today. In the last decade, next-generation sequencing has become informative for the targeted treatment of many diseases, demonstrating the importance of genome-scale molecular information for personalized medicine. Today, revolutionary developments in spatial transcriptomics technologies digitalize gene expression at subcellular resolution in intact tissue sections, enabling the computational analysis of cell types, cellular phenotypes, and cell-cell communication in routinely collected and archival clinical samples. Here we review how such molecular microscopes work, highlight their potential to identify disease mechanisms and guide personalized therapies, and provide guidance for clinical study design. Finally, we discuss remaining challenges to the swift translation of high-resolution spatial transcriptomics technologies and how integration of multimodal readouts and deep learning approaches is bringing us closer to a holistic understanding of tissue biology and pathology.

Single-cell integration reveals metaplasia in inflammatory gut diseases

The gastrointestinal tract is a multi-organ system crucial for efficient nutrient uptake and barrier immunity. Advances in genomics and a surge in gastrointestinal diseases1,2 has fuelled efforts to catalogue cells constituting gastrointestinal tissues in health and disease3. Here we present systematic integration of 25 single-cell RNA sequencing datasets spanning the entire healthy gastrointestinal tract in development and in adulthood. We uniformly processed 385 samples from 189 healthy controls using a newly developed automated quality control approach (scAutoQC), leading to a healthy reference atlas with approximately 1.1 million cells and 136 fine-grained cell states. We anchor 12 gastrointestinal disease datasets spanning gastrointestinal cancers, coeliac disease, ulcerative colitis and Crohn's disease to this reference. Utilizing this 1.6 million cell resource (gutcellatlas.org), we discover epithelial cell metaplasia originating from stem cells in intestinal inflammatory diseases with transcriptional similarity to cells found in pyloric and Brunner's glands. Although previously linked to mucosal healing4, we now implicate pyloric gland metaplastic cells in inflammation through recruitment of immune cells including T cells and neutrophils. Overall, we describe inflammation-induced changes in stem cells that alter mucosal tissue architecture and promote further inflammation, a concept applicable to other tissues and diseases.

Spatial omics technologies for understanding molecular status associated with cancer progression

Cancer cells are generally exposed to numerous extrinsic stimulations in the tumor microenvironment. In this environment, cancer cells change their expression profiles to fight against circumstantial stresses, allowing their progression in the challenging tissue space. Technological advancements of spatial omics have had substantial influence on cancer genomics. This technical progress, especially that occurring in the spatial transcriptome, has been drastic and rapid. Here, we describe the latest spatial analytical technologies that have allowed omics feature characterization to retain their spatial and histopathological information in cancer tissues. Several spatial omics platforms have been launched, and the latest platforms finally attained single-cell level or even higher subcellular level resolution. We discuss several key papers elucidating the initial utility of the spatial analysis. In fact, spatial transcriptome analyses reveal comprehensive omics characteristics not only in cancer cells but also their surrounding cells, such as tumor infiltrating immune cells and cancer-associated fibroblasts. We also introduce several spatial omics platforms. We describe our own attempts to investigate molecular events associated with cancer progression. Furthermore, we discuss the next challenges in analyzing the multiomics status of cells, including their morphology and location. These novel technologies, in conjunction with spatial transcriptome analysis and, more importantly, with histopathology, will elucidate even novel key aspects of the intratumor heterogeneity of cancers. Such enhanced knowledge is expected to open a new path for overcoming therapeutic resistance and eventually to precisely stratify patients.

Single-cell RNA sequencing to map tumor heterogeneity in gastric carcinogenesis paving roads to individualized therapy

Gastric cancer (GC) is a highly heterogeneous disease with a complex tumor microenvironment (TME) that encompasses multiple cell types including cancer cells, immune cells, stromal cells, and so on. Cancer-associated cells could remodel the TME and influence the progression of GC and therapeutic response. Single-cell RNA sequencing (scRNA-seq), as an emerging technology, has provided unprecedented insights into the complicated biological composition and characteristics of TME at the molecular, cellular, and immunological resolutions, offering a new idea for GC studies. In this review, we discuss the novel findings from scRNA-seq datasets revealing the origin and evolution of GC, and scRNA-seq is a powerful tool for investigating transcriptional dynamics and intratumor heterogeneity (ITH) in GC. Meanwhile, we demonstrate that the vital immune cells within TME, including T cells, B cells, macrophages, and stromal cells, play an important role in the disease progression. Additionally, we also overview that how scRNA-seq facilitates our understanding about the effects on individualized therapy of GC patients. Spatial transcriptomes (ST) have been designed to determine spatial distribution and capture local intercellular communication networks, enabling a further understanding of the relationship between the spatial background of a particular cell and its functions. In summary, scRNA-seq and other single-cell technologies provide a valuable perspective for molecular and pathological disease characteristics and hold promise for advancing basic research and clinical practice in GC.

Discovering cancer stem-like molecule, nuclear factor I X, using spatial transcriptome in gastric cancer

Gastric cancer (GC) is characterized by significant intratumoral heterogeneity, and stem cells are promising therapeutic targets. Despite advancements in spatial transcriptome analyses, unexplored targets for addressing cancer stemness remain unknown. This study aimed to identify Nuclear Factor IX (NFIX) as a critical regulator of cancer stemness in GC and evaluate its clinicopathological significance and function. Spatial transcriptome analysis of GC was conducted. The correlation between NFIX expression, clinicopathological factors, and prognosis was assessed using immunostaining in 127 GC cases. Functional analyses of cancer cell lines validated these findings. Spatial transcriptome analysis stratified GC tissues based on genetic profiles, identified CSC-like cells, and further refined the classification to identify and highlight the significance of NFIX, as validated by Monocle 3 and CytoTRACE analyses. Knockdown experiments in cancer cell lines have demonstrated the involvement of NFIX in cancer cell proliferation and kinase activity. This study underscores the role of spatial transcriptome analysis in refining GC tissue classification and identifying therapeutic targets, highlighting NFIX as a pivotal factor. NFIX expression is correlated with poor prognosis and drives GC progression, suggesting its potential as a novel therapeutic target for personalized GC therapies.

Refining the diagnostic utility of OLFM4 in gastric cancer precursors: a call for rigorous methodologies

This commentary offers a thoughtful discussion of the study by Wei et al. published in the journal on the role of Olfactomedin 4 (OLFM4) in incomplete intestinal metaplasia, a gastric precancerous condition. The original paper introduces OLFM4 as a novel biomarker with potential enhanced diagnostic efficacy compared to established markers. However, several methodological and interpretive considerations are noted. The histopathological findings could be refined by using higher magnification to better elucidate the cellular localization of OLFM4. Including high-resolution images for key stainings would enhance the study's robustness in expression profiling. The statistical approach could be strengthened by employing more rigorous, quantitative methodologies. Additionally, integrating immunofluorescence double-staining may improve the reliability of the results. Discrepancies in immunohistochemical signals across datasets suggest a need for further investigation into tissue section representativeness. Clarifying the term "precancerous lesions of gastric carcinoma cells" to align with widely accepted definitions would enhance clarity. The choice of the GES-1 cell model treated with MNNG could be reconsidered in favor of more established models such as organoids, air-liquid interface models, and gastric cancer-specific cell lines. The in vivo MNNG-alcohol combination model might require additional empirical support, given the limited and conflicting literature on this approach, to ensure an accurate portrayal of IM pathogenesis. The commentary concludes with a call for stringent and standardized methodologies in biomarker research to ensure the clinical applicability and reliability of biomarker studies, particularly in the context of gastric cancer detection and intervention.

Highlights of how single-cell analyses are illuminating differentiation and disease in the gastric corpus

Single-cell RNA-sequencing (scRNA-seq) has emerged as a powerful technique to identify novel cell markers, developmental trajectories, and transcriptional changes during cell differentiation and disease onset and progression. In this review, we highlight recent scRNA-seq studies of the gastric corpus in both human and murine systems that have provided insight into gastric organogenesis, identified novel markers for the various gastric lineages during development and in adults, and revealed transcriptional changes during regeneration and tumorigenesis. Overall, by elucidating transcriptional states and fluctuations at the cellular level in healthy and disease contexts, scRNA-seq may lead to better, more personalized clinical treatments for disease progression.

The Fibroblast Landscape in Stomach Carcinogenesis

Numerous recent studies using single cell RNA sequencing and spatial transcriptomics have shown the vast cell heterogeneity, including epithelial, immune, and stromal cells, present in the normal human stomach and at different stages of gastric carcinogenesis. Fibroblasts within the metaplastic and dysplastic mucosal stroma represent key contributors to the carcinogenic microenvironment in the stomach. The heterogeneity of fibroblast populations is present in the normal stomach, but plasticity within these populations underlies their alterations in association with both metaplasia and dysplasia. In this review, we summarize and discuss efforts over the past several years to study the fibroblast components in human stomach from normal to metaplasia, dysplasia, and cancer. In the stomach, myofibroblast populations increase during late phase carcinogenesis and are a source of matrix proteins. PDGFRA-expressing telocyte-like cells are present in normal stomach and expand during metaplasia and dysplasia in close proximity with epithelial lineages, likely providing support for both normal and metaplastic progenitor niches. The alterations in fibroblast transcriptional signatures across the stomach carcinogenesis process indicate that fibroblast populations are likely as plastic as epithelial populations during the evolution of carcinogenesis.

Mapping Cell Atlases at the Single-Cell Level

Recent advancements in single-cell technologies have led to rapid developments in the construction of cell atlases. These atlases have the potential to provide detailed information about every cell type in different organisms, enabling the characterization of cellular diversity at the single-cell level. Global efforts in developing comprehensive cell atlases have profound implications for both basic research and clinical applications. This review provides a broad overview of the cellular diversity and dynamics across various biological systems. In addition, the incorporation of machine learning techniques into cell atlas analyses opens up exciting prospects for the field of integrative biology.