The Immune Microenvironment in Gastric Cancer: Prognostic Prediction

Significance of dysregulated M2 macrophage and ESR2 in the ovarian metastasis of gastric cancer

Background

Prognosis of gastric cancer (GC) patients with ovarian metastasis (OM) remains poor. We hereby characterized the role of tumor immune microenvironment (TIME) and identified potential key regulators in the OM with the aim of understanding its molecular basis to develop novel therapeutic targets.

Methods

Transcriptomic analyses of paired primary and ovarian metastatic lesions of seven GC patients from Fudan University Shanghai Cancer Center uncovered and functionally annotated their differentially expressed genes (DEGs). CIBERSORT analysis revealed differential TIME between primary GCs and OMs, which was further validated by multiplex immunofluorescence (mIF). Unique overexpression of candidate regulator in OMs was validated by an immunohistochemical (IHC) staining-based cohort study and in vitro cell growth, migration and invasion assays were conducted to characterize its function in GC progression.

Results

Functional enrichment analyses of DEGs between GCs and matched OMs revealed multiple significantly dysregulated immune-related and cancer-related pathways. Distinctive subsets of immune cells, especially M2 macrophage, were selectively enriched in metastatic lesions. mIF-based quantification further validated the overexpression of CD68+CD206+ M2 macrophage in the OMs. Estrogen receptor 2 (ESR2), which encodes estrogen receptor β (ERβ), was not only potentially correlated with M2 macrophage but also overexpressed in the OM of GC. ESR2 was up-regulated in cancerous tissue and its high expression correlated with younger age, more advanced lymph node metastasis and pathological stage, as well as a worse patient survival. IHC staining of ERβ in the cohort of paired primary and metastatic GCs validated its selective overexpression in OMs. Small-interfering RNAs (siRNAs)-induced knockdown of ESR2 significantly inhibited the invasion and migration of both AGS and HGC-27 GC cell lines.

Conclusions

Comparative RNA-sequencing analysis revealed the dysregulated TIME, M2 macrophage in particular, between primary GC and OM. ESR2 potentially correlated with M2 macrophage and played pro-oncogenic roles in GC progression and metastasis.

Identification and validation of Cystatin A as a novel promising therapeutic target for gastric cancer

Background

The effect of pharmacological treatment of gastric cancer (GC) is limited, thus, it holds significant scientific importance to thoroughly investigate the molecular mechanisms underlying GC development and identify novel molecules capable of substantially extending patients' survival. This study utilized bioinformatics techniques to identify 11 genes associated with recurrence-free survival (RFS) in GC patients and investigated the potential biological functions of these genes through single-cell transcriptomic analysis. Subsequently, a single gene Cystatin A (CSTA) was selected for further analysis to explore its impact on signaling pathways and treatment.

Methods

Differentially expressed genes (DEGs) were identified and overlapped in the analysis of RFS to identify potential prognostic genes for GC patients, based on data from the Cancer Genome Atlas-stomach adenocarcinoma (TCGA-STAD) and GSE54129. Subsequently, a prognostic model based on RFS in GC patients was established. Single-cell sequencing data were employed to explore the potential functions of these model genes. CSTA, one of the RFS-related genes, was further investigated using immunohistochemistry (IHC), Cell Counting Kit 8 (CCK-8), transwell, scratch, colony formation assays, flow cytometry, and Western blotting methods.

Results

Through bioinformatics analysis, we identified 23 RFS-related genes in GC. Using the least absolute shrinkage and selection operator (LASSO)-Cox method, an RFS prognostic model was developed which pinpointed 11 GC prognosis-related (GPR) genes as significant factors influencing RFS in GC patients. The single-cell analysis revealed their potential role in affecting differentiation and maturation of pre-fibroblasts thereby impacting RFS in GC patients. CSTA exhibited low expression levels in GC tissues. Overexpression of CSTA promoted apoptosis in GC cells through the caspase-dependent apoptotic pathway and enhanced their response to cisplatin via this same pathway.

Conclusions

The 11 GPR genes are primarily enriched within a specific type of stromal cell exhibiting heightened communication, metabolism, and differentiation levels. The gene signature of these stromal cells has implications for patient prognosis. Additionally, CSTA, a gene related to prognosis, has been shown to influence apoptosis levels in GC cells.

Proteome-based molecular subtyping and therapeutic target prediction in gastric cancer

Different molecular classifications for gastric cancer (GC) have been proposed based on multi-omics platforms with the long-term goal of improved precision treatment. However, the GC (phospho)proteome remains incompletely characterized, particularly at the level of tyrosine phosphorylation. In addition, previous multiomics-based stratification of patient cohorts has lacked identification of corresponding cell line models and comprehensive validation of broad or subgroup-selective therapeutic targets. To address these knowledge gaps, we applied a reverse approach, undertaking the most comprehensive (phospho)proteomic analysis of GC cell lines to date and cross-validating this using publicly available data. Mass spectrometry (MS)-based (phospho)proteomic and tyrosine phosphorylation datasets were subjected to individual or integrated clustering to identify subgroups that were subsequently characterized in terms of enriched molecular processes and pathways. Significant congruence was detected between cell line proteomic and specific patient-derived transcriptomic subclassifications. Many protein kinases exhibiting 'outlier' expression or phosphorylation in the cell line dataset exhibited genomic aberrations in patient samples and association with poor prognosis, with casein kinase I isoform delta/epsilon (CSNK1D/E) being experimentally validated as potential therapeutic targets. Src family kinases were predicted to be commonly hyperactivated in GC cell lines, consistent with broad sensitivity to the next-generation Src inhibitor eCF506. In addition, phosphoproteomic and integrative clustering segregated the cell lines into two subtypes, with epithelial-mesenchyme transition (EMT) and proliferation-associated processes enriched in one, designated the EMT subtype, and metabolic pathways, cell-cell junctions, and the immune response dominating the features of the other, designated the metabolism subtype. Application of kinase activity prediction algorithms and interrogation of gene dependency and drug sensitivity databases predicted that the mechanistic target of rapamycin kinase (mTOR) and dual specificity mitogen-activated protein kinase kinase 2 (MAP2K2) represented potential therapeutic targets for the EMT and metabolism subtypes, respectively, and this was confirmed using selective inhibitors. Overall, our study provides novel, in-depth insights into GC proteomics, kinomics, and molecular taxonomy and reveals potential therapeutic targets that could provide the basis for precision treatments.

Integrated Analysis Construct a Tumor-Associated Macrophage Novel Signature with Promising Implications in Predicting the Prognosis and Immunotherapeutic Response of Gastric Cancer Patients

BACKGROUND

Gastric cancer (GC) remains one of the most prevalent malignant tumors worldwide. At present, tumor-associated macrophages (TAMs) are essential in the progression, metastasis, and drug resistance of tumors. Therefore, TAMs can be a crucial target for tumor treatment.

AIMS

We intended to investigate the TAM characteristics in GC and develop a risk signature based on TAM to predict the prognosis of GC patients.

METHODS

The single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data were acquired from a publicly available database. We utilized the Seurat pipeline to process the scRNA-seq data and determine TAM cell types using marker genes. Univariate Cox regression analysis was utilized to examine TAM-related prognostic genes, and then we employed Lasso-Cox regression analysis, and Multivariate Cox regression analysis established a novel risk profile to forecast the clinical value of the model with a new nomogram combining risk profiles and clinicopathological characteristics.

RESULTS

The current study employed scRNA-seq data to identify five TAM clusters in GC, among which four were significantly associated with GC prognosis. Accordingly, we further developed a TAM-related risk signature utilizing nine genes. After evaluation, our model accurately predicted the prognosis of gastric cancer. Generally, GC patients with low TAMS scores exhibited a more favorable prognosis, greater benefits from immunotherapy, and higher levels of immune cell infiltration.

CONCLUSIONS

The prognosis of GC can be effectively predicted by TAM-based risk signatures, and the signature may provide a new perspective for comprehensively guiding clinical diagnosis, prediction, and immunotherapy for gastric cancer.

Differential genetic mutations and immune cell infiltration in high- and low-risk STAD: Implications for prognosis and immunotherapy efficacy

This study investigates genetic mutations and immune cell dynamics in stomach adenocarcinoma (STAD), focusing on identifying prognostic markers and therapeutic targets. Analysis of TCGA-STAD samples revealed C > A as the most common single nucleotide variant (SNV) in both high and low-risk groups. Key mutated driver genes included TTN, TP53 and MUC16, with frame-shift mutations more prevalent in the low-risk group and missense mutations in the high-risk group. Interaction analysis of hub genes such as C1QA and CD68 showed significant correlations, impacting immune cell infiltration patterns. Using ssGSEA, we found higher immune cell infiltration (B cells, CD4+ T cells, CD8+ T cells, DC cells, NK cells) in the high-risk group, correlated with increased risk scores. xCell algorithm results indicated distinct immune infiltration levels between the groups. The study's risk scoring model proved effective in prognosis prediction and immunotherapy efficacy assessment. Key molecules like CD28, CD27 and SLAMF7 correlated significantly with risk scores, suggesting potential targets for high-risk STAD patients. Drug sensitivity analysis showed a negative correlation between risk scores and sensitivity to certain treatments, indicating potential therapeutic options for high-risk STAD patients. We also validated the carcinogenic role of RPL14 in gastric cancer through phenotypic experiments, demonstrating its influence on cancer cell proliferation, invasion and migration. Overall, this research provides crucial insights into the genetic and immune aspects of STAD, highlighting the importance of a risk scoring model for personalized treatment strategies and clinical decision-making in gastric cancer management.

Metabolic and immune-related gene signatures: Predictive stratification and prognostic implications in gastric cancer

BACKGROUND

Gastric cancer, marked by its heterogeneous nature, showcases various molecular subtypes and clinical trajectories. This research delves into the significance of metabolic and immune-driven pathways in gastric cancer, constructing a prognostic signature derived from differentially expressed metabolic and immune-correlated genes (DE-MIGs).

METHODS

Metabolic and immune-associated gene were sourced from the GeneCards database. Differential expression analysis on the TCGA-STAD dataset was executed using the limma package, unveiling 51 DE-MIGs that underwent functional enrichment scrutiny. The LASSO Cox regression methodology guided the creation of the prognostic signature, and individual patient risk scores were determined. Assessment tools like CIBERSORT, ESTIMATE and ssGSEA were deployed to study the immune microenvironment, while mutation profiles, genomic stability, resistance to chemotherapy and immunotherapy responsiveness were scrutinized across distinct signature categorizations.

RESULTS

Among the identified DE-MIGs, 26 were significantly tied to the overall survival of gastric cancer patients. The developed prognostic signature proficiently differentiated patients into high-risk and low-risk cohorts, with the latter showing markedly better outcomes. The study underscored the centrality of the immune microenvironment in influencing gastric cancer outcomes. Key pathways such as TGF-Beta, TP53 and NRF2 dominated the high-risk group, whereas the LRTK-RAS and WNT pathways characterized the low-risk group. Interestingly, the low-risk segment also manifested a heightened tumor mutation burden and enhanced susceptibility to immunotherapy.

CONCLUSIONS

Our findings introduce a pivotal prognostic signature, rooted in DE-MIGs, that effectively segregates gastric cancer patients into distinct risk-based segments. Insights into the influential role of the immune microenvironment in gastric cancer progression pave the way for more refined therapeutic interventions.

Regulation of regulatory T cells and tumor-associated macrophages in gastric cancer tumor microenvironment

INTRODUCTION

Despite advancements in the methods for prevention and early diagnosis of gastric cancer (GC), GC continues to be the fifth in incidence among major cancers and the third most common cause of cancer-related death. The therapeutic effects of surgery and drug treatment are still unsatisfied and show notable differences according to the tumor microenvironment (TME) of GC.

METHODS

Through screening Pubmed, Embase, and Web of Science, we identified and summarized the content of recent studies that focus on the investigation of Helicobacter pylori (Hp) infection, regulatory T cells (Tregs), and tumor-associated macrophages (TAMs) in the TME of GC. Furthermore, we searched and outlined the clinical research progress of various targeted drugs in GC treatment including CTLA-4, PD-1\PD-L1, and VEGF/VEGFR.

RESULTS

In this review, the findings indicate that Hp infection causes local inflammation and leads to immunosuppressive environment. High Tregs infiltration in the TME of GC is associated with increased induction and recruitment; the exact function of infiltrated Tregs in GC was also affected by phenotypes and immunosuppressive molecules. TAMs promote the development and metastasis of tumors, the induction, recruitment, and function of TAMs in the TME of gastric cancer are also regulated by various factors.

CONCLUSION

Discussing the distinct tumor immune microenvironment (TIME) of GC can deepen our understanding on the mechanism of cancer immune evasion, invasion, and metastasis, help us to reduce the incidence of GC, and guide the innovation of new therapeutic targets for GC eventually.

Gastric Cancer Immune Subtypes and Prognostic Modeling: Insights from Aging-Related Gene Analysis

Gastric cancer (GC) is highly heterogeneous and influenced by aging-related factors. This study aimed to improve individualized prognostic assessment of GC by identifying aging-related genes and subtypes. Immune scores of GC samples from GEO and TCGA databases were calculated using ESTIMATE and scored as high immune (IS_high) and low immune (IS_low). ssGSEA was used to analyze immune cell infiltration. Univariate Cox regression was employed to identify prognosis-related genes. LASSO regression analysis was used to construct a prognostic model. GSVA enrichment analysis was applied to determine pathways. CCK-8, wound healing, and Transwell assays tested the proliferation, migration, and invasion of the GC cell line (AGS). Cell cycle and aging were examined using flow cytometry, β-galactosidase staining, and Western blotting. Two aging-related GC subtypes were identified. Subtype 2 was characterized as lower survival probability and higher risk, along with a more immune-responsive tumor microenvironment. Three genes (IGFBP5, BCL11B, and AKR1B1) screened from aging-related genes were used to establish a prognosis model. The AUC values of the model were greater than 0.669, exhibiting strong prognostic value. In vitro, IGFBP5 overexpression in AGS cells was found to decrease viability, migration, and invasion, alter the cell cycle, and increase aging biomarkers (SA-β-galactosidase, p53, and p21). This analysis uncovered the immune characteristics of two subtypes and aging-related prognosis genes in GC. The prognostic model established for three aging-related genes (IGFBP5, BCL11B, and AKR1B1) demonstrated good prognosis performance, providing a foundation for personalized treatment strategies aimed at GC.

CAP2 promotes gastric cancer metastasis by mediating the interaction between tumor cells and tumor-associated macrophages

The metastasis of cancer cells is the main cause of death in patients with gastric cancer (GC). Mounting evidence has demonstrated the vital importance of tumor-associated macrophages in promoting tumor invasion and metastasis; however, the interaction between tumor cells and macrophages in GC is largely unknown. In this study, we demonstrated that cyclase-associated protein 2 (CAP2) was upregulated in GC, especially in cases with lymph node metastasis, and was correlated with a poorer prognosis. The transcription factor JUN directly bound to the promoter region of CAP2 and activated CAP2 transcription. The N-terminal domain of CAP2 bound to the WD5 to WD7 domains of receptor for activated C kinase 1 (RACK1) and induced M2 macrophage polarization by activating the SRC/focal adhesion kinase (FAK)/ERK signaling pathway, which resulted in IL-4 and IL-10 secretion. Polarized M2 macrophages induced premetastatic niche formation and promoted GC metastasis by secreting TGFB1, which created a TGFB1/JUN/CAP2 positive-feedback loop to activate CAP2 expression continuously. Furthermore, we identified salvianolic acid B as an inhibitor of CAP2, which effectively inhibited GC cell invasion capabilities by suppressing the SRC/FAK/ERK signaling pathway. Our data suggest that CAP2, a key molecule mediating the interaction between GC cells and tumor-associated macrophages, may be a promising therapeutic target for suppressing tumor metastasis in GC.

Bioinformatics Analysis Reveals the Vital Role of AKR1B1 in Immune Infiltration and Clinical Outcomes of Gastric Cancer

Infiltrated immune cells are an important constitute of tumor microenvironment, which exert complex effects on gastric cancer (GC) pathogenesis and progression. By using weighted gene co-expression network analysis, integrating the data from The Cancer Genome Atlas-stomach adenocarcinoma and GSE62254, we identify Aldo-Keto Reductase Family 1 Member B (AKR1B1) as a hub gene for immune regulation in GC. Notably, AKR1B1 is associated with higher immune infiltration and worse histologic grade of GC. In addition, AKR1B1 is an independent factor for predicting the survival rate of GC patients. In vitro experiments further demonstrated that AKR1B1-overexpressed THP-1-derived macrophages promoted the proliferation and migration of GC cells. Taken together, AKR1B1 plays an important role in GC progression by regulating immune microenvironment, which could be a biomarker for predicting GC prognosis as well as a potential therapeutic target for GC treatment.

Comprehensive analysis of COMMD10 as a novel prognostic biomarker for gastric cancer

Background

COMMD10 has an important role in the development of certain tumors, but its relevance to gastric cancer (GC) is unclear. The purpose of this study is to investigate the difference of COMMD10 expression in gastric adenocarcinoma (STAD) and analyze the correlation between COMMD10 expression and prognosis of STAD patients.

Methods

The expression levels of COMMD10 between STAD and normal tissues were explored using the The Cancer Genome Atlas (TCGA) database. In addition, the expression of COMMD10 in GC was further validated by immunohistochemistry (IHC) staining, qRT-PCR and Western blot. Dot blot experiments were used for exploring m6A expression levels in tissues with high and low COMMD10 expression. Kaplan-Meier analysis and COX regression analysis were used to explore the relationship between COMMD10 and STAD prognosis. A nomogram was constructed to predict the survival probability of STAD patients. GO and KEGG functional enrichment of COMMD10-related genes were performed. The Corrlot software package was used to analyze the correlation between COMMD10 expression levels and m6A modifications in STAD. An analysis of immune infiltration based on the CIBERSOFT and the single-sample GSEA (ssGSEA) method was performed.

Results

COMMD10 expression was significantly associated with multiple cancers, including STAD in TCGA. COMMD10 expression was elevated in STAD cancer tissues compared to paracancerous tissues. COMMD10 upregulation was associated with poorer overall survival (OS), clinical stage, N stage, and primary treatment outcome in STAD. Functional enrichment of COMMD10-related genes was mainly involved in biological processes such as RNA localization, RNA splicing, RNA transport, mRNA surveillance pathways, and spliceosomes. The dot blot experiment showed that m6A levels were higher in cancer tissues with high COMMD10 expression compared with paracancerous tissues. COMMD10 was significantly correlated with most m6A-related genes. COMMD10 was involved in STAD immune cells infiltration, correlated with macrophage cells expression.

Conclusion

High COMMD10 expression was significantly associated with poor prognosis in STAD patients, and its functional realization was related to m6A modification. COMMD10 involved in STAD immune infiltration.