Dissecting the genetic and microenvironmental factors of gastric tumorigenesis in mice

Decoding the role of intratumoral microbiota in gastric cancer

Intratumoral microbiota are increasingly recognized for their impact on gastric cancer, with growing evidence highlighting their complexity and significance. This review synthesizes current knowledge on the origins, heterogeneity, detection, and mechanistic roles of intratumoral microbiota in gastric carcinogenesis. In gastric cancer, intratumoral microbiota can originate from mucosal disruption and may migrate from normal adjacent tissues or be influenced by the TME. It exhibits spatial and functional heterogeneity within gastric cancer. Despite challenges in the detection of intratumoral microbiota, advances in deep sequencing and spatial omics have enhanced our understanding of microbial diversity and functionality. Mechanistically, intratumoral microbiota influence gastric cancer development through genetic and epigenetic alterations, signaling pathway modulation, metabolic reprogramming, and regulation of chronic inflammation and immune responses. These insights underscore the microbiota's dual function in both promoting and hindering tumor advancement. Therapeutically, the microbiota's impact on chemotherapy resistance and immune modulation presents opportunities for novel interventions. Integrating microbiome analysis into cancer research and leveraging microbial therapies may enable more effective, personalized treatment strategies. Future research should further elucidate the intricate microbe-tumor interactions to advance clinical applications and improve outcomes for gastric cancer patients.

MARMOT: A multifaceted R pipeline for analysing spectral flow cytometry data from subcutaneously growing murine gastric organoids

The analysis of murine immune cell types is a critical component of immunological research, necessitating precise and reproducible methodologies. Here, we present a comprehensive protocol and pipeline designed to streamline the process from murine gastric organoid transplant sample preparation to figure generation. This pipeline includes a detailed staining panel tailored for murine immune cells, ensuring accurate and comprehensive identification of various cell types. Additionally, it integrates an R-based analysis script (MARMOT Pipeline), encompassing data processing and visualisation. A key feature of this pipeline is its ability to produce publication-quality figures with minimal direct R coding, thus making advanced data analysis accessible to researchers with limited programming experience. Additionally, figures can be customised using a provided Shiny application. This approach both enhances the efficiency of data analysis and enables the reproducibility required for high-quality scientific research.

Single-cell and spatial RNA sequencing identify divergent microenvironments and progression signatures in early- versus late-onset prostate cancer

The clinical and pathological outcomes differ between early-onset (diagnosed in men ≤55 years of age) and late-onset prostate cancer, potentially attributed to the changes in hormone levels and immune activities associated with aging. Exploring the heterogeneity therein holds potential for developing age-specific precision interventions. Here, through single-cell and spatial transcriptomic analyses of prostate cancer tissues, we identified that an androgen response-related transcriptional meta-program (AR-MP) might underlie the age-related heterogeneity of tumor cells and microenvironment. APOE+ tumor-associated macrophages infiltrated AR-MP-activated tumor cells in early-onset prostate cancer, potentially facilitating tumor progression and immunosuppression. By contrast, inflammatory cancer-associated fibroblasts in late-onset prostate cancer correlated with downregulation of AR-MP of tumor cells and increased epithelial-to-mesenchymal transition and pre-existing castration resistance, which may also be linked to smoking. This study provides potential insights for tailoring precision treatments by age groups, emphasizing interventions that include targeting AR and tumor-associated macrophages in young patients but anchoring epithelial-to-mesenchymal transition and inflammatory cancer-associated fibroblasts in old counterparts.

Loss of Kmt2c / d promotes gastric cancer initiation and confers vulnerability to mTORC1 inhibition and anti-PD1 immunotherapy

KMT2C and KMT2D ( KMT2C/D ) are frequently mutated in gastric adenocarcinoma, yet their function in cancer initiation remains poorly understood. In this study, based on the observation that loss-of-function mutations of KMT2C and KMT2D are enriched and co-occur in gastric adenocarcinoma, we developed genetically engineered mouse models to selectively knock out Kmt2c and Kmt2d in gastric epithelial cells with Tmprss2-CreER T2 . Through histological staining and single-cell RNA sequencing, we observed that Kmt2c/d loss led to nuclear dysplasia and expansion of cells with mixed gastric lineage markers. When combined with Pten deletion, Kmt2c/d loss drove rapid development of muscle-invasive gastric adenocarcinoma as early as 3 weeks post Cre-mediated gene deletion. The adenocarcinoma exhibited decreased expression of gastric lineage markers and increased expression of intestinal differentiation markers, phenocopying human gastric adenocarcinoma. Kmt2c/d knockout reduced protein synthesis but upregulated transcription of ribosomal proteins, rendering sensitivity to mTORC1 inhibitors. Additionally, Kmt2c/d knockout increased MHC-I molecule expression and enhanced antigen presentation. Combination of mTROC1 inhibition and anti-PD1 immunotherapy significantly suppressed tumor growth in immune-competent mice. Together, these findings reveal the role of Kmt2c / d loss in gastric cancer initiation and suggest the potential therapeutic strategies for KMT2C/D -deficient gastric cancer.

A systematic review on the culture methods and applications of 3D tumoroids for cancer research and personalized medicine

Cancer is a highly heterogeneous disease, and thus treatment responses vary greatly between patients. To improve therapy efficacy and outcome for cancer patients, more representative and patient-specific preclinical models are needed. Organoids and tumoroids are 3D cell culture models that typically retain the genetic and epigenetic characteristics, as well as the morphology, of their tissue of origin. Thus, they can be used to understand the underlying mechanisms of cancer initiation, progression, and metastasis in a more physiological setting. Additionally, co-culture methods of tumoroids and cancer-associated cells can help to understand the interplay between a tumor and its tumor microenvironment. In recent years, tumoroids have already helped to refine treatments and to identify new targets for cancer therapy. Advanced culturing systems such as chip-based fluidic devices and bioprinting methods in combination with tumoroids have been used for high-throughput applications for personalized medicine. Even though organoid and tumoroid models are complex in vitro systems, validation of results in vivo is still the common practice. Here, we describe how both animal- and human-derived tumoroids have helped to identify novel vulnerabilities for cancer treatment in recent years, and how they are currently used for precision medicine.

Pairpot: a database with real-time lasso-based analysis tailored for paired single-cell and spatial transcriptomics

Paired single-cell and spatially resolved transcriptomics (SRT) data supplement each other, providing in-depth insights into biological processes and disease mechanisms. Previous SRT databases have limitations in curating sufficient single-cell and SRT pairs (SC-SP pairs) and providing real-time heuristic analysis, which hinder the effort to uncover potential biological insights. Here, we developed Pairpot (http://pairpot.bioxai.cn), a database tailored for paired single-cell and SRT data with real-time heuristic analysis. Pairpot curates 99 high-quality pairs including 1,425,656 spots from 299 datasets, and creates the association networks. It constructs the curated pairs by integrating multiple slices and establishing potential associations between single-cell and SRT data. On this basis, Pairpot adopts semi-supervised learning that enables real-time heuristic analysis for SC-SP pairs where Lasso-View refines the user-selected SRT domains within milliseconds, Pair-View infers cell proportions of spots based on user-selected cell types in real-time and Layer-View displays SRT slices using a 3D hierarchical layout. Experiments demonstrated Pairpot's efficiency in identifying heterogeneous domains and cell proportions.

A platform of functional studies of ESCC-associated gene mutations identifies the roles of TGFBR2 in ESCC progression and metastasis

Genomics studies have detected numerous genetic alterations in esophageal squamous cell carcinoma (ESCC). However, the functions of these mutations largely remain elusive, partially due to a lack of feasible animal models. Here, we report a convenient platform with CRISPR-Cas9-mediated introduction of genetic alterations and orthotopic transplantation to generate a series of primary ESCC models in mice. With this platform, we validate multiple frequently mutated genes, including EP300, FAT1/2/4, KMT2D, NOTCH2, and TGFBR2, as tumor-suppressor genes in ESCC. Among them, TGFBR2 loss dramatically promotes tumorigenesis and multi-organ metastasis. Paradoxically, TGFBR2 deficiency leads to Smad3 activation, and disruption of Smad3 partially restrains the progression of Tgfbr2-mutated tumors. Drug screening with tumor organoids identifies that pinaverium bromide represses Smad3 activity and restrains Tgfbr2-deficient ESCC. Our studies provide a highly efficient platform to investigate the in vivo functions of ESCC-associated mutations and develop potential treatments for this miserable malignancy.

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.

Distinct tumor-TAM interactions in IDH-stratified glioma microenvironments unveiled by single-cell and spatial transcriptomics

Tumor-associated macrophages (TAMs) residing in the tumor microenvironment (TME) are characterized by their pivotal roles in tumor progression, antitumor immunity, and TME remodeling. However, a thorough comparative characterization of tumor-TAM crosstalk across IDH-defined categories of glioma remains elusive, likely contributing to mixed outcomes in clinical trials. We delineated the phenotypic heterogeneity of TAMs across IDH-stratified gliomas. Notably, two TAM subsets with a mesenchymal phenotype were enriched in IDH-WT glioblastoma (GBM) and correlated with poorer patient survival and reduced response to anti-PD-1 immune checkpoint inhibitor (ICI). We proposed SLAMF9 receptor as a potential therapeutic target. Inference of gene regulatory networks identified PPARG, ELK1, and MXI1 as master transcription factors of mesenchymal BMD-TAMs. Our analyses of reciprocal tumor-TAM interactions revealed distinct crosstalk in IDH-WT tumors, including ANXA1-FPR1/3, FN1-ITGAVB1, VEGFA-NRP1, and TNFSF12-TNFRSF12A with known contribution to immunosuppression, tumor proliferation, invasion and TAM recruitment. Spatially resolved transcriptomics further elucidated the architectural organization of highlighted communications. Furthermore, we demonstrated significant upregulation of ANXA1, FN1, NRP1, and TNFRSF12A genes in IDH-WT tumors using bulk RNA-seq and RT-qPCR. Longitudinal expression analysis of candidate genes revealed no difference between primary and recurrent tumors indicating that the interactive network of malignant states with TAMs does not drastically change upon recurrence. Collectively, our study offers insights into the unique cellular composition and communication of TAMs in glioma TME, revealing novel vulnerabilities for therapeutic interventions in IDH-WT GBM.

Targeting metabolic sensing switch GPR84 on macrophages for cancer immunotherapy

INTRODUCTION

As one of the major components of the tumor microenvironment, tumor-associated macrophages (TAMs) possess profound inhibitory activity against T cells and facilitate tumor escape from immune checkpoint blockade therapy. Converting this pro-tumorigenic toward the anti-tumorigenic phenotype thus is an important strategy for enhancing adaptive immunity against cancer. However, a plethora of mechanisms have been described for pro-tumorigenic differentiation in cancer, metabolic switches to program the anti-tumorigenic property of TAMs are elusive.

MATERIALS AND METHODS

From an unbiased analysis of single-cell transcriptome data from multiple tumor models, we discovered that anti-tumorigenic TAMs uniquely express elevated levels of a specific fatty acid receptor, G-protein-coupled receptor 84 (GPR84). Genetic ablation of GPR84 in mice leads to impaired pro-inflammatory polarization of macrophages, while enhancing their anti-inflammatory phenotype. By contrast, GPR84 activation by its agonist, 6-n-octylaminouracil (6-OAU), potentiates pro-inflammatory phenotype via the enhanced STAT1 pathway. Moreover, 6-OAU treatment significantly retards tumor growth and increases the anti-tumor efficacy of anti-PD-1 therapy.

CONCLUSION

Overall, we report a previously unappreciated fatty acid receptor, GPR84, that serves as an important metabolic sensing switch for orchestrating anti-tumorigenic macrophage polarization. Pharmacological agonists of GPR84 hold promise to reshape and reverse the immunosuppressive TME, and thereby restore responsiveness of cancer to overcome resistance to immune checkpoint blockade.

A New Type of Endometrial Cancer Models in Mice Revealing the Functional Roles of Genetic Drivers and Exploring their Susceptibilities

Endometrial cancer (EC) is the most common female reproductive tract cancer and its incidence has been continuously increasing in recent years. The underlying mechanisms of EC tumorigenesis remain unclear, and efficient target therapies are lacking, for both of which feasible endometrial cancer animal models are essential but currently limited. Here, an organoid and genome editing-based strategy to generate primary, orthotopic, and driver-defined ECs in mice is reported. These models faithfully recapitulate the molecular and pathohistological characteristics of human diseases. The authors names these models and similar models for other cancers as organoid-initiated precision cancer models (OPCMs). Importantly, this approach can conveniently introduce any driver mutation or a combination of driver mutations. Using these models,it is shown that the mutations in Pik3ca and Pik3r1 cooperate with Pten loss to promote endometrial adenocarcinoma in mice. In contrast, the Kras G12D mutati led to endometrial squamous cell carcinoma. Then, tumor organoids are derived from these mouse EC models and performed high-throughput drug screening and validation. The results reveal distinct vulnerabilities of ECs with different mutations. Taken together, this study develops a multiplexing approach to model EC in mice and demonstrates its value for understanding the pathology of and exploring the potential treatments for this malignancy.