Single-Cell Atlas of Lineage States, Tumor Microenvironment, and Subtype-Specific Expression Programs in Gastric Cancer

TMExplorer: A tumour microenvironment single-cell RNAseq database and search tool

MOTIVATION

The tumour microenvironment (TME) contains various cells including stromal fibroblasts, immune and malignant cells, and its composition can be elucidated using single-cell RNA sequencing (scRNA-seq). scRNA-seq datasets from several cancer types are available, yet we lack a comprehensive database to collect and present related TME data in an easily accessible format.

RESULTS

We therefore built a TME scRNA-seq database, and created the R package TMExplorer to facilitate investigation of the TME. TMExplorer provides an interface to easily access all available datasets and their metadata. The users can search for datasets using a thorough range of characteristics. The TMExplorer allows for examination of the TME using scRNA-seq in a way that is streamlined and allows for easy integration into already existing scRNA-seq analysis pipelines.

A novel immune-related radioresistant lncRNAs signature based model for risk stratification and prognosis prediction in esophageal squamous cell carcinoma

Background and purpose: Radioresistance remains a major reason of radiotherapeutic failure in esophageal squamous cell carcinoma (ESCC). Our study is to screen the immune-related long non-coding RNA (ir-lncRNAs) of radiation-resistant ESCC (rr-ESCC) via Gene Expression Omnibus (GEO) database and to construct a prognostic risk model.

Methods: Microarray data (GSE45670) related to radioresistance of ESCC was downloaded from GEO. Based on pathologic responses after chemoradiotherapy, patients were divided into a non-responder (17 samples) and responder group (11 samples), and the difference in expression profiles of ir-lncRNAs were compared therein. Ir-lncRNA pairs were constructed for the differentially expressed lncRNAs as prognostic variables, and the microarray dataset (GSE53625) was downloaded from GEO to verify the effect of ir-lncRNA pairs on the long-term survival of ESCC. After modelling, patients are divided into high- and low-risk groups according to prognostic risk scores, and the outcomes were compared within groups based on the COX proportional hazards model. The different expression of ir-lncRNAs were validated using ECA 109 and ECA 109R cell lines via RT-qPCR.

Results: 26 ir-lncRNA genes were screened in the GSE45670 dataset with differential expression, and 180 ir-lncRNA pairs were constructed. After matching with ir-lncRNA pairs constructed by GSE53625, six ir-lncRNA pairs had a significant impact on the prognosis of ESCC from univariate analysis model, of which three ir-lncRNA pairs were significantly associated with prognosis in multivariate COX analysis. These three lncRNA pairs were used as prognostic indicators to construct a prognostic risk model, and the predicted risk scores were calculated. With a median value of 2.371, the patients were divided into two groups. The overall survival (OS) in the high-risk group was significantly worse than that in the low-risk group (p < 0.001). The 1-, 2-, and 3-year prediction performance of this risk-model was 0.666, 0.702, and 0.686, respectively. In the validation setting, three ir-lncRNAs were significantly up-regulated, while two ir-lncRNAs were obviouly down-regulated in the responder group.

Conclusion: Ir-lncRNAs may be involved in the biological regulation of radioresistance in patients with ESCC; and the prognostic risk-model, established by three ir-lncRNAs pairs has important clinical value in predicting the prognosis of patients with rr-ESCC.

scRNA-seq of gastric tumor shows complex intercellular interaction with an alternative T cell exhaustion trajectory

The tumor microenvironment (TME) in gastric cancer (GC) has been shown to be important for tumor control but the specific characteristics for GC are not fully appreciated. We generated an atlas of 166,533 cells from 10 GC patients with matched paratumor tissues and blood. Our results show tumor-associated stromal cells (TASCs) have upregulated activity of Wnt signaling and angiogenesis, and are negatively correlated with survival. Tumor-associated macrophages and LAMP3⁺ DCs are involved in mediating T cell activity and form intercellular interaction hubs with TASCs. Clonotype and trajectory analysis demonstrates that Tc17 (IL-17⁺CD8⁺ T cells) originate from tissue-resident memory T cells and can subsequently differentiate into exhausted T cells, suggesting an alternative pathway for T cell exhaustion. Our results indicate that IL17⁺ cells may promote tumor progression through IL17, IL22, and IL26 signaling, highlighting the possibility of targeting IL17⁺ cells and associated signaling pathways as a therapeutic strategy to treat GC.

Gastric cancer can vary in tumour stage and immune cell involvement. Here the authors compare gene expression in immune cell types from the blood and the tumour site from GC patients using single cell and TCR sequencing and show that IL17⁺CD8⁺ T cells have a phenotype related to that seen with exhausted cells.

Integration of Genomic Biology Into Therapeutic Strategies of Gastric Cancer Peritoneal Metastasis

The peritoneum is a common site of metastasis in advanced gastric cancer (GC). Diagnostic laparoscopy is now routinely performed as part of disease staging, leading to an earlier diagnosis of synchronous peritoneal metastasis (PM). The biology of GCPM is unique and aggressive, leading to a dismal prognosis. These tumors tend to be resistant to traditional systemic therapy, and yet, this remains the current standard-of-care recommended by most international clinical guidelines. As this is an area of unmet clinical need, several translational studies and clinical trials have focused on addressing this specific disease state. Advances in genomic sequencing and molecular profiling have revealed several promising therapeutic targets and elucidated novel biology, particularly on the role of the surrounding tumor microenvironment in GCPM. Peritoneal-specific clinical trials are being designed with a combination of locoregional therapeutic strategies with systemic therapy. In this review, we summarize the new knowledge of cancer biology, advances in surgical techniques, and emergence of novel therapies as an integrated strategy emerges to address GCPM as a distinct clinical entity.

Single-Cell and Bulk RNA Sequencing Reveal Malignant Epithelial Cell Heterogeneity and Prognosis Signatures in Gastric Carcinoma

Gastric carcinoma (GC) heterogeneity represents a major barrier to accurate diagnosis and treatment. Here, we established a comprehensive single-cell transcriptional atlas to identify the cellular heterogeneity in malignant epithelial cells of GC using single-cell RNA sequencing (scRNA-seq). A total of 49,994 cells from nine patients with paired primary tumor and normal tissues were analyzed by multiple strategies. This study focused on the malignant epithelial cells, which were divided into three subtypes, including pit mucous cells, chief cells, and gastric and intestinal cells. The trajectory analysis results suggest that the differentiation of the three subtypes could be from the pit mucous cells to the chief cells and then to the gastric and intestinal cells. Lauren’s histopathology of GC might originate from various subtypes of malignant epithelial cells. The functional enrichment analysis results show that the three subtypes focused on different biological processes (BP) and pathways related to tumor development. In addition, we generated and validated the prognostic signatures for predicting the OS in GC patients by combining the scRNA-seq and bulk RNA sequencing (bulk RNA-seq) datasets. Overall, our study provides a resource for understanding the heterogeneity of GC that will contribute to accurate diagnosis and prognosis.

Identification of novel tumor microenvironment-associated genes in gastric cancer based on single-cell RNA-sequencing datasets

Tumor microenvironment and heterogeneity play vital roles in the development and progression of gastric cancer (GC). In the past decade, a considerable amount of single-cell RNA-sequencing (scRNA-seq) studies have been published in the fields of oncology and immunology, which improve our knowledge of the GC immune microenvironment. However, much uncertainty still exists about the relationship between the macroscopic and microscopic data in transcriptomics. In the current study, we made full use of scRNA-seq data from the Gene Expression Omnibus database (GSE134520) to identify 25 cell subsets, including 11 microenvironment-related cell types. The MIF signaling pathway network was obtained upon analysis of receptor–ligand pairs and cell–cell interactions. By comparing the gene expression in a wide variety of cells between intestinal metaplasia and early gastric cancer, we identified 64 differentially expressed genes annotated as immune response and cellular communication. Subsequently, we screened these genes for prognostic clinical value based on the patients’ follow-up data from The Cancer Genome Atlas. TMPRSS15, VIM, APOA1, and RNASE1 were then selected for the construction of LASSO risk scores, and a nomogram model incorporating another five clinical risk factors was successfully created. The effectiveness of least absolute shrinkage and selection operator risk scores was validated using gene set enrichment analysis and levels of immune cell infiltration. These findings will drive the development of prognostic evaluations affected by the immune tumor microenvironment in GC.

Identification of prognostic gene expression signatures based on the tumor microenvironment characterization of gastric cancer

Increasing evidence has elucidated that the tumor microenvironment (TME) shows a strong association with tumor progression and therapeutic outcome. We comprehensively estimated the TME infiltration patterns of 111 gastric cancer (GC) and 21 normal stomach mucosa samples based on bulk transcriptomic profiles based on which GC could be clustered as three subtypes, TME-Stromal, TME-Mix, and TME-Immune. The expression data of TME-relevant genes were utilized to build a GC prognostic model—GC_Score. Among the three GC TME subtypes, TME-Stomal displayed the worst prognosis and the highest GC_Score, while TME-Immune had the best prognosis and the lowest GC_Score. Connective tissue growth factor (CTGF), the highest weighted gene in the GC_Score, was found to be overexpressed in GC. In addition, CTGF exhibited a significant correlation with the abundance of fibroblasts. CTGF has the potential to induce transdifferentiation of peritumoral fibroblasts (PTFs) to cancer-associated fibroblasts (CAFs). Beyond characterizing TME subtypes associated with clinical outcomes, we correlated TME infiltration to molecular features and explored their functional relevance, which helps to get a better understanding of carcinogenesis and therapeutic response and provide novel strategies for tumor treatments.

Delineating Molecular Subtypes through Gene Set Variation Analysis Confers Therapeutic and Prognostic Capability in Gastric Cancer

To claim the features of nontumor tissue in gastric cancer patients, especially in those who have undergone gastrectomy, and to identify the molecular subtypes, we collected the immunogenic and hallmark gene sets from gene set enrichment analysis. The activity changes of these gene sets between tumor (375) and nontumor (32) tissues acquired from the Cancer Genome Atlas (TCGA-STAD) were calculated, and the novel molecular subtypes were delineated. Subsequently, prognostic gene sets were determined using least absolute shrinkage and selection operator (lasso) regression prognostic method. In addition, functional analysis was conducted. Totally, three subtypes were constructed in the present study, and there were differences in survival among three groups. Functional analysis showed genes from normal gene set were related to cell adhesion, and genes from tumor gene set were associated with focal adhesion, PI3K-Akt signaling pathway, regulation of actin cytoskeleton, and VEGF signaling pathway. Our study created lasting value beyond molecular subtypes and underscored the significance of normal tissues in gastric cancer development, which drawn a novel prognostic model for gastric treatment.

Augmentation of the RNA m6A reader signature is associated with poor survival by enhancing cell proliferation and EMT across cancer types

N⁶-Methyladenosine (m6A) RNA modification plays a critical role in the posttranscriptional regulation of gene expression. Alterations in cellular m6A levels and m6A-related genes have been reported in many cancers, but whether they play oncogenic or tumor-suppressive roles is inconsistent across cancer types. We investigated common features of alterations in m6A modification and m6A-related genes during carcinogenesis by analyzing transcriptome data of 11 solid tumors from The Cancer Genome Atlas database and our in-house gastric cancer cohort. We calculated m6A writer (W), eraser (E), and reader (R) signatures based on corresponding gene expression. Alterations in the W and E signatures varied according to the cancer type, with a strong positive correlation between the W and E signatures in all types. When the patients were divided according to m6A levels estimated by the ratio of the W and E signatures, the prognostic effect of m6A was inconsistent according to the cancer type. The R and especially the R2 signatures (based on the expression of IGF2BPs) were upregulated in all cancers. Patients with a high R2 signature exhibited poor prognosis across types, which was attributed to enrichment of cell cycle- and epithelial–mesenchymal transition-related pathways. Our study demonstrates common features of m6A alterations across cancer types and suggests that targeting m6A R proteins is a promising strategy for cancer treatment.

Studying the effects of a chemical modification of messenger RNA molecules (mRNA), which carry genetic information from DNA to the cell’s protein-making machinery, reveals new insights into the role of these modifications in cancer, suggesting potential therapeutic approaches. Researchers in Seoul, South Korea, led by Joon-Yong An at Korea University and Sung-Yup Cho at Seoul National University investigated the most common modifications of mRNA involving methyl groups (CH₃): addition (‘writing’), having a regulatory effect on the cell (‘reading’) or removal (‘erasing’). The molecular activities involved in reading the modifications were increased in all 11 types of cancer in cancer-sampling databases and their own patient cohort. Changes in writing and erasing of the modifications varied with cancer type. The proteins that mediate the reading responses to RNA methylation are possible targets for new anti-cancer drugs.

Cancer-associated fibroblasts in the single-cell era

Cancer-associated fibroblasts (CAFs) are central players in the microenvironment of solid tumors, affecting cancer progression and metastasis. CAFs have diverse phenotypes, origins and functions and consist of distinct subpopulations. Recent progress in single-cell RNA-sequencing technologies has enabled detailed characterization of the complexity and heterogeneity of CAF subpopulations in multiple tumor types. In this Review, we discuss the current understanding of CAF subsets and functions as elucidated by single-cell technologies, their functional plasticity, and their emergent shared and organ-specific features that could potentially be harnessed to design better therapeutic strategies for cancer.

Discovering Immune-Mediated Mechanisms of Gastric Carcinogenesis Through Single-Cell RNA Sequencing

Single-cell RNA sequencing (scRNAseq) technology is still relatively new in the field of gastric cancer immunology but gaining significant traction. This technology now provides unprecedented insights into the intratumoral and intertumoral heterogeneities at the immunological, cellular, and molecular levels. Within the last few years, a volume of publications reported the usefulness of scRNAseq technology in identifying thus far elusive immunological mechanisms that may promote and impede gastric cancer development. These studies analyzed datasets generated from primary human gastric cancer tissues, metastatic ascites fluid from gastric cancer patients, and laboratory-generated data from in vitro and in vivo models of gastric diseases. In this review, we overview the exciting findings from scRNAseq datasets that uncovered the role of critical immune cells, including T cells, B cells, myeloid cells, mast cells, ILC2s, and other inflammatory stromal cells, like fibroblasts and endothelial cells. In addition, we also provide a synopsis of the initial scRNAseq findings on the interesting epithelial cell responses to inflammation. In summary, these new studies have implicated roles for T and B cells and subsets like NKT cells in tumor development and progression. The current studies identified diverse subsets of macrophages and mast cells in the tumor microenvironment, however, additional studies to determine their roles in promoting cancer growth are needed. Some groups specifically focus on the less prevalent ILC2 cell type that may contribute to early cancer development. ScRNAseq analysis also reveals that stromal cells, e.g., fibroblasts and endothelial cells, regulate inflammation and promote metastasis, making them key targets for future investigations. While evaluating the outcomes, we also highlight the gaps in the current findings and provide an assessment of what this technology holds for gastric cancer research in the coming years. With scRNAseq technology expanding rapidly, we stress the need for periodic review of the findings and assess the available scRNAseq analytical tools to guide future work on immunological mechanisms of gastric carcinogenesis.  

Single-cell RNA-seq dissecting heterogeneity of tumor cells and comprehensive dynamics in tumor microenvironment during lymph nodes metastasis in gastric cancer

Lymph node metastasis is the common metastasis route of gastric cancer. However, until now, heterogeneities of tumor cells and tumor microenvironment in primary tumors (PT) and metastatic lymph nodes (MLN) of gastric cancer (GC) remains uncharacterized. In this study, scRNA-seq was performed on tissues from PT and MLN of gastric cancer. Trajectory analysis and function enrichment analyses were conducted to decode the underlying mechanisms contributing to LN metastasis of gastric cancer. Heterogeneous composition of immune cells and distant intercellular interactions in PT and MLN were analyzed. Based on the generated single cell transcriptome profiles, dynamics of gene expressions in cancer cells between PT and MLN were characterized. Moreover, we reconstructed the developmental trajectory of GC cells' metastasis to LN and identified two sub-types of GC cells with distinct potentials of having malignant biological behaviors. We characterized the repression of neutrophil polarization associated genes, like LCN2, which would contribute to LN metastasis, and histochemistry experiments validated our findings. Additionally, heterogeneity in neutrophils, rather than macrophages, was characterized. Immune checkpoint associated interaction of SPP1 was found active in MLN. In conclusion, we decode the dynamics of tumor cells during LN metastasis in GC and to identify a sub-type of GC cells with potentials of LN metastasis. Our data indicated that the disordering the neutrophils polarization and maturation and the activation of immune checkpoint SPP1 might contribute to LN metastasis in GC, providing a novel insight on the mechanism and potential therapeutic targets of LN metastasis in GC. This article is protected by copyright. All rights reserved.

Integration of Tumor Microenvironment in Patient-Derived Organoid Models Help Define Precision Medicine of Renal Cell Carcinoma

Renal cell carcinoma (RCC) is a common urological tumor, with a poor prognosis, as the result of insensitivity to chemotherapy and radiotherapy. About 20%–30% of patients with RCC have metastasis at the first diagnosis, so only systemic treatment is possible. Due to the heterogeneity of renal tumors, responses to drugs differ from person to person. Consequently, patient-derived organoid, highly recapitulating tumor heterogeneity, becomes a promising model for high-throughput ex vivo drug screening and thus guides the drug choice of patients with RCC. Systemic treatment of RCC mainly targets the tumor microenvironment, including neovasculature and immune cells. We reviewed several methods with which patient-derived organoid models mimic the heterogeneity of not only tumor epithelium but also the tumor microenvironment. We further discuss some new aspects of the development of patient-derived organoids, preserving in vivo conditions in patients with RCC.

Focal Adhesion-Related Signatures Predict the Treatment Efficacy of Chemotherapy and Prognosis in Patients with Gastric Cancer

Background

The current tumor-node-metastasis (TNM) staging system is insufficient for predicting the efficacy of chemotherapy in patients with gastric cancer (GC). This study aimed to analyze the association between the focal adhesion pathway and therapeutic efficacy of chemotherapy in patients with GC.

Methods

RNA sequencing was performed on 33 clinical samples from patients who responded or did not respond to treatment prior to neoadjuvant chemotherapy. The validation sets containing 696 GC patients with RNA data from three cohorts (PKUCH, TCGA, and GSE14210) were analyzed. A series of machine learning and bioinformatics approaches was combined to build a focal adhesion-related signature model to predict the treatment efficacy and prognosis of patients with GC.

Results

Among the various signaling pathways associated with cancer, focal adhesion was identified as a risk factor related to the treatment efficacy of chemotherapy and prognosis in patients with GC. The focal adhesion-related gene model (FAscore) discriminated patients with a high FAscore who are insensitive to neoadjuvant chemotherapy in our training cohort, and the predicted value was further verified in the GSE14210 cohort. Survival analysis also demonstrated that patients with high FAscores had a relatively shorter survival compared to those with low FAscores. In addition, we found that the levels of tumor mutation burden (TMB) and microsatellite instability (MSI) increased with an increase in FAscore, and the tumor microenvironment (TME) also shifted to a pro-tumor immune microenvironment.

Conclusion

The FAscore model can be used to predict the treatment efficacy of chemotherapy and select appropriate treatment strategies for patients with GC.

Epigenetics of Dendritic Cells in Tumor Immunology

Dendritic cells (DCs) are professional antigen-presenting cells with the distinctive property of inducing the priming and differentiation of naïve CD4+ and CD8+ T cells into helper and cytotoxic effector T cells to develop efficient tumor-immune responses. DCs display pathogenic and tumorigenic antigens on their surface through major histocompatibility complexes to directly influence the differentiation of T cells. Cells in the tumor microenvironment (TME), including cancer cells and other immune-infiltrated cells, can lead DCs to acquire an immune-tolerogenic phenotype that facilitates tumor progression. Epigenetic alterations contribute to cancer development, not only by directly affecting cancer cells, but also by their fundamental role in the differentiation of DCs that acquire a tolerogenic phenotype that, in turn, suppresses T cell-mediated responses. In this review, we focus on the epigenetic regulation of DCs that have infiltrated the TME and discuss how knowledge of the epigenetic control of DCs can be used to improve DC-based vaccines for cancer immunotherapy.

DNA Hypomethylation Is Associated with the Overexpression of INHBA in Upper Tract Urothelial Carcinoma

Urothelial carcinoma includes upper urinary tract cancer (UTUC) and bladder cancer. Although nephroureterectomy is the standard treatment for UTUC, the recurrence rate is approximately half and the tumor is associated with poor prognoses. Metastases are the most devastating and lethal clinical situation in urothelial carcinoma. Despite its clinical importance, few potential diagnostic biomarkers are suitable for early UC detection. We compared high-stage/high-grade urothelial carcinoma tissues to adjacent normal urothelial tissues using methyl-CpG binding domain protein capture for genome-wide DNA methylation analysis. Based on our findings, inhibin βA (INHBA) might be associated with carcinogenesis and metastasis. Further, clinical UC specimens had significant INHBA hypomethylation based on pyrosequencing. INHBA was detected by real-time PCR and immunohistochemistry staining, and was found to be highly expressed in clinical tissues and cell lines of urothelial carcinoma. Further, INHBA depletion was found to significantly reduce BFTC-909 cell growth and migration by INHBA-specific small interfering RNA. Interestingly, a positive correlation was found between SMAD binding and extracellular structure organization with INHBA using gene set enrichment analysis and gene ontology analysis. Together, these results are the first evidence of INHBA promoter hypomethylation and INHBA overexpression in UTUC. INHBA may affect urothelial carcinoma migration by reorganizing the extracellular matrix through the SMAD pathway.

Mapping the genomic diaspora of gastric cancer

Gastric cancer (GC) is a leading contributor to global cancer incidence and mortality. Pioneering genomic studies, focusing largely on primary GCs, revealed driver alterations in genes such as ERBB2, FGFR2, TP53 and ARID1A as well as multiple molecular subtypes. However, clinical efforts targeting these alterations have produced variable results, hampered by complex co-alteration patterns in molecular profiles and intra-patient genomic heterogeneity. In this Review, we highlight foundational and translational advances in dissecting the genomic cartography of GC, including non-coding variants, epigenomic aberrations and transcriptomic alterations, and describe how these alterations interplay with environmental influences, germline factors and the tumour microenvironment. Mapping of these alterations over the GC life cycle in normal gastric tissues, metaplasia, primary carcinoma and distant metastasis will improve our understanding of biological mechanisms driving GC development and promoting cancer hallmarks. On the translational front, integrative genomic approaches are identifying diverse mechanisms of GC therapy resistance and emerging preclinical targets, enabled by technologies such as single-cell sequencing and liquid biopsies. Validating these insights will require specifically designed GC cohorts, converging multi-modal genomic data with longitudinal data on therapeutic challenges and patient outcomes. Genomic findings from these studies will facilitate 'next-generation' clinical initiatives in GC precision oncology and prevention.

Comprehensive Analysis of Somatic Mutations in Driver Genes of Resected Pancreatic Ductal Adenocarcinoma Reveals KRAS G12D and Mutant TP53 Combination as an Independent Predictor of Clinical Outcome

BACKGROUND

Prognosis in pancreatic ductal adenocarcinoma (PDAC) remains poor despite improved systemic therapies and surgical techniques. The identification of biomarkers to advance insight in tumor biology and achieve better individualized prognostication could help improve outcomes. Our aim was to elucidate the prognostic role of the four main driver mutations (KRAS, TP53, SMAD4, CDKN2A) and their combinations in resected PDAC.

PATIENTS AND METHODS

A retrospective analysis was conducted utilizing the cBioPortal database and National Cancer Institute's Cancer Genomic Atlas (TCGA) on patients in whom next-generation sequencing was performed on upfront resected PDAC from 2012 to 2020. Multivariable Cox regression was implemented to elucidate risk-adjusted predictors of overall (OS) and recurrence-free survival (RFS). Results were validated employing a Johns Hopkins Hospital (JHH) cohort.'

RESULTS

In the discovery cohort (n = 587), increased number of mutated driver genes was associated with worse OS (p = 0.047). Specifically, patients with mutations in ≥ 2 driver genes had worse OS than ≤ 1 mutated gene (18.2 versus 32.3 months, p = 0.033). Co-occurrence of mutant (mt)KRAS p.G12D with mtTP53 (median OS, 25.9 months) conferred better prognosis than co-occurrence of other mtKRAS variants (p.G12V/R/other) with mtTP53 (median OS, 16.9 months, p = 0.038). The findings were validated using a JHH cohort. Multivariable risk-adjustment found co-occurrence of mtKRAS p.G12D with mtTP53 to be an independent predictor of beneficial OS and RFS [HR (95% CI): 0.18 (0.03-0.81) and 0.31 (0.11-0.89) respectively].

CONCLUSION

In chemo-naïve resected PDAC, combinations of mutations in the four driver genes are associated with prognosis. In patients with combined mtKRAS and mtTP53, KRAS p.G12D variant confers a better OS and RFS.