Response In Gastric Cancer Research Articles

Tumor budding as a predictor for prognosis and therapeutic response in gastric cancer: A mini review.

In recent years, the role of tumor budding in gastric cancer has received increased attention across a number of disciplines. Several studies have found associations between tumor budding and the prediction of lymph node metastasis in early gastric cancer, prognosis of advanced gastric cancer, predictors of therapeutic response to immune checkpoint inhibitors, such as microsatellite instability (MSI), and therapeutic targets of molecular targeted therapy, such as human epidermal growth factor receptor 2 (HER-2). Therefore, tumor budding is a major element in the formulation of risk stratification and precision medicine strategies for patients with gastric cancer.

HIPPO signaling-related signature for predicting prognosis and therapeutic response in gastric cancer.

Background: Gastric cancer (GC) is a multifactorial progressive disease with high mortality and heterogeneous prognosis. Effective prognostic biomarkers for GC were critically needed. Hippo signaling pathway is one of the critical mechanisms regulating the occurrence and development of GC, and has potential clinical application value for the prognosis and treatment of GC patients. However, there is no effective signature based on Hippo signaling pathway-related genes (HSPRGs) to predict the prognosis and treatment response of GC patients. Our study aimed to build a HSPRGs signature and explore its performance in improving prognostic assessment and drug therapeutic response in GC. Methods: Based on gene expression profiles obtained from The Cancer Genome Atlas (TCGA) database, we identified differentially expressed HSPRGs and conducted univariate and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis to construct a multigene risk signature. Subsequently, the Kaplan-Meier curve and receiver operating characteristic (ROC) were performed to evaluate the predictive value of the risk signature in both training and validation cohort. Furthermore, we carried out univariate and multivariate Cox regression analysis to investigate the independent prognostic factors and establish a predictive nomogram. The enriched signaling pathways in risk signature were analyzed by gene set enrichment analysis (GSEA). Tumor immune dysfunction and exclusion (TIDE) and drug sensitivity analysis were performed to depict therapeutic response in GC. Results: In total, 38 differentially expressed HSPRGs were identified, and final four genes (DLG3, TGFB3, TGFBR1, FZD6) were incorporated to build the signature. The ROC curve with average 1-, 3-, and 5-year areas under the curve (AUC) equal to .609, .634, and .639. Clinical ROC curve revealed that risk signature was superior to other clinicopathological factors in predicting prognosis. Calibration curves and C-index (.655) of nomogram showed excellent consistency. Besides, in the immunotherapy analysis, exclusion (p < 2.22 × 10-16) and microsatellite instability (p = .0058) performed significantly differences. Finally, our results suggested that patients in the high-risk group were more sensitive to specific chemotherapeutic agents. Conclusion: Results support the hypothesis that Hippo-related signature is a novel prognostic biomarker and predictor, which could help optimize GC prognostic stratification and inform clinical medication decisions.

Infiltration of Gastric Cancer Stroma by Tumor-Infiltrating Lymphocytes Correlates with mTOR Signaling.

We investigated whether the infiltration of tumor-infiltrating lymphocytes (TILs) in gastric cancer (GC), as evaluated by hematoxylin & eosin (H&E) staining, could be a prognostic marker. We also explored on the relationship between TILs and mechanistic target of rapamycin (mTOR) and how it regulates immune effector responses in GC. A total of 183 patients with available data on TIL were included. TIL infiltration was evaluated using H&E staining. We also conducted immunohistochemistry to determine mTOR expression. Positive TIL infiltration was defined as TILs ≥20%. There were 72 (39.3%) and 111 (60.7%) positive and negative cases, respectively. TILs positivity significantly correlated with both absence of lymph node metastasis (p = 0.037) and negative p-mTOR expression (p = 0.040). TIL infiltration correlated with a significantly better overall (p = 0.046) and disease-free (p = 0.020) survival. mTOR possibly suppresses TIL infiltration in GC. H&E staining is an effective tool for evaluating the immune status of GC patients. H&E staining may be used in clinical practice to monitor treatment response in GC.

CD36-BATF2\MYB Axis Predicts Anti-PD-1 Immunotherapy Response in Gastric Cancer.

Despite the utilization of anti-PD-1 therapy in gastric cancer (GC), the absence of a reliable predictive biomarker continues to pose a challenge. In this study, we utilized bioinformatic analysis and immunohistochemistry to develop a prediction model for activated CD4+ memory T cells, considering both mRNA and protein levels. An elevation of activated CD4+ memory T cells in GC was noted, which exhibited a strong association with the patients' overall survival. By utilizing WGCNA and DEG analysis, we discovered that BATF2, MYB, and CD36 are genes that exhibit differential expression and are linked to activated CD4+ memory T cells. Afterwards, a forecast model was built utilizing Stepwise regression and immunohistochemistry relying on the three genes. The model's high-risk score showed significant associations with a suppressive immune microenvironment. Moreover, our model exhibited encouraging prognostic value and superior performance in predicting response to immune checkpoint blockade therapy compared with the conventional CD8+PD-L1 model. In terms of mechanism, CD36 could function as a receptor upstream that identifies Helicobacter pylori and fatty acids. This recognition then results in the reduction of the BATF2-MYB protein complex and subsequent alterations in the transcription of genes associated with classical T cell activation. As a result, the activation state of CD4+ memory T cells is ultimately suppressed. The CD36-BATF2/MYB signature serves as a robust predictor of anti-PD-1 immunotherapy response in GC.

A comprehensive review of the role of lncRNAs in gastric cancer (GC) pathogenesis, immune regulation, and their clinical applications.

Gastric cancer (GC) is the fifth most common malignant tumor and the third leading cause of cancer-related deaths worldwide. Although numerous studies have been conducted on advanced GC, the molecular mechanisms behind it remain obscure. Long non-coding RNAs (lncRNAs) are a family of RNA transcripts capable of regulating target genes at transcriptional, post-transcriptional, and translational stages. They do this by modifying mRNAs, miRNAs, and proteins. These RNAs are critical regulators of many biological processes, including gene epigenetics, transcription, and post-transcriptional levels. This article highlights recent results on lncRNAs involved in drug resistance, proliferation, migration, angiogenesis, apoptosis, autophagy, and immune response in GC. The potential clinical implications of lncRNAs as biomarkers and therapeutic targets in GC are also discussed.

Development and Evaluation of a Novel Cuproptosis-Related lncRNA Signature for Gastric Cancer Prognosis.

According to a growing body of research, long noncoding RNAs (lncRNAs) participate in the progress of gastric cancer (GC). Cuproptosis is a distinct kind of programmed cell death, separating it from several other forms of programmed cell death that may be caused by genetic programming. Consequently, it is crucial to examine cuproptosis-related lncRNAs (CRLs) prognostic importance for the prognosis and treatment response in GC. The Cancer Genome Atlas (TCGA) database was used to retrieve RNA-seq data, pertinent clinical information, and somatic mutation data. A list of cuproptosis-related genes (CRGs) was obtained from prior work. We can distinguish prognostic CRLs using coexpression and univariate Cox analysis. Then, using CRLs, we developed a risk prediction model using multivariate Cox regression analysis and the least absolute shrinkage selection operator (LASSO) technique. To evaluate the diagnostic accuracy of this model, a Kaplan-Meier (K-M) survival analysis and a receiver operating characteristic (ROC) analysis were used. Moreover, the relationships between the risk model and immunological function, somatic mutation, and drug sensitivity were also investigated. Using the multivariate Cox analysis technique, we developed a signature based on cuproptosis-related four lncRNAs. We then classified patients into high-risk and low-risk groups based on the likelihood of unfavorable outcomes. The model was subjected to further testing, including K-M survival analysis, ROC analysis, and multivariate Cox regression analysis, all of which proved the model's exceptional robustness and predictive capacity. In addition, a nomogram that has a strong capacity for prediction ability was built. This nomogram included age, gender, clinical grade, pathologic stage, T stage, and risk score. Furthermore, we discovered substantial disparities in immune function and the number of mutations carried by tumors between the high-risk and low-risk groups. Moreover, this research also found that the IC50 values for 27 chemotherapeutic drugs varied widely across patients within high- and low-risk groups. The proposed 4-CRLs signature is a promising biomarker to predict clinical outcomes in GC.

COLEC12 Promotes Tumor Progression and Is Correlated With Poor Prognosis in Gastric Cancer.

Collectin subfamily member 12, a transmembrane scavenger receptor C-type lectin, is aberrantly expressed in various cancers. However, its physiological role in gastric cancer remains somewhat unclear. This study aimed to investigate the Collectin subfamily member 12 expression pattern in human gastric cancer and its role in gastric cancer progression. The Kaplan-Meier method was used for survival analysis. The univariate and multivariate Cox proportional hazards regression models were used to identify independent predictors for progression-free survival and overall survival. The effects of Collectin subfamily member 12 on gastric cancer cell proliferation, migration, invasion, and apoptosis were detected through the cell counting kit-8 assay, colony formation assay, wound healing assay, transwell assay, and flow cytometry analysis, respectively. Additionally, the correlation between Collectin subfamily member 12 expression and immune cell infiltration was analyzed through bioinformatics. Collectin subfamily member 12 was highly expressed in advanced gastric cancer (T3-T4, pathologic stage III-IV). High Collectin subfamily member 12 expression was correlated with a worse progression-free survival and overall survival in the gastric cancer patients. In vitro, cell line studies revealed that Collectin subfamily member 12 promoted gastric cancer cell proliferation, migration, and invasion and inhibited gastric cancer cell apoptosis. The bioinformatics analysis further demonstrated that the Collectin subfamily member 12 expression level positively correlated with infiltration of several immune cells, such as M2 macrophages, dendritic cells, neutrophils, and regulatory T cells, suggesting that Collectin subfamily member 12 may also play a role in suppressing tumor immune response in gastric cancer. Collectin subfamily member 12 was identified as a novel predictive marker and target for the clinical treatment of gastric cancer.

Posttranslational Modifications of Rev-Erbα Protein and Abnormal Inflammatory Response in Gastric Cancer.

We reported that Rev-erbα, a transcriptional repressor, is reduced in human gastric cancer and that it inhibits glycolysis in cultured gastric cancer cells. However, it is unclear whether Rev-erbα undergoes posttranslational modifications in gastric cancer. Here, we determined levels of Rev-erbα and its posttranslational modifications including phosphorylation, SUMOylation, and ubiquitination in N-methyl-N-nitrosourea (MNU)/Helicobacter pylori (H. pylori)-induced gastric cancer in mice and in cultured human gastric cancer cells. Administration of MNU plus H. pylori infection successfully induced gastric tumor in C57BL/6J mice. MNU/H. pylori decreased the levels of Rev-erbα in gastric tumor tissues of mice accompanied by an increase in the level of lactic acid. Rev-erbα protein SUMOylation and ubiquitination modifications were significantly increased, whereas phosphorylation was unchanged, in gastric cancer cells line BGC-823 and MNU/H. pylori-induced mouse gastric cancer tissues. Using human gastric cancer tissues, we found that Rev-erbα was specifically reduced in mucosal epithelial cells in gastric tissue. Cytokine levels were increased in MNU/H. pylori-exposed mice compared with control mice. Similarly, the levels of IL-6 IL-10, TNF-α, and VEGF were higher in the BGC-823 cell line compared with GES-1 cells. IL-6 and IL-1 incubation did not affect Rev-erbα levels in BGC-823 cells. Furthermore, Rev-erbα was recruited on the promoters of these cytokine genes, which suppressed their expression. Conclusively, Rev-erbα SUMOylation and subsequent ubiquitination may contribute to its protein reduction, which leads to increased glycolysis and abnormal inflammatory responses during the development of gastric cancer. Targeting Rev-erbα and its SUMOylation represents promising approaches for prevention and management of gastric cancer.

Comprehensive analysis of cuproptosis-related genes in prognosis, tumor microenvironment infiltration, and immunotherapy response in gastric cancer.

Cuproptosis is the most recently identified copper-dependent cell death form that influences tricarboxylic acid (TCA) cycle. However, the relationship between cuproptosis and clinical prognosis, tumor microenvironment infiltration (TME), and response to immunotherapy remains unclear. Single-sample gene-set enrichment analysis (ssGSEA) was employed to construct cuproptosisScore (cpS) and 1378 gastric cancer (GC) patients from five independent public datasets were classified into high- or low-cpS groups according to the median of cpS. Then the impacts of cuproptosis on tumor microenvironment infiltration (TME), biological function, response to immunotherapy, and clinical prognosis of GC were evaluated. RiskScore and nomogram were constructed using Lasso Cox regression algorithm to validate its predictive capability in GC patients. Compared to patients with high cpS, patients with low cpS exhibited poorer prognosis, higher TNM stage, and stronger stromal activation. Meanwhile, the analysis of response to immunotherapy confirmed patients with high cpS could better benefit from immunotherapy and had a better susceptibility to chemotherapeutic drugs. Then, 9 prognosis-related signatures were collected based on differentially expressed genes (DEGs) of cpS groups. Finally, a riskScore model was constructed using the multivariate Cox (multi-Cox) regression coefficients of prognosis-related signatures and had an excellent capability of predicting 1-, 3-, and 5-year survival in GC patients. This study revealed the role of curproptosis in TME, response to immunotherapy, and clinical prognosis in GC, which highlighted the significant clinical implications of curproptosis and provided novel ideas for the therapeutic application of cuproptosis in GC.

Gastric Cancer Risk and Pathogenesis in BRCA1 and BRCA2 Carriers.

Carriers of a pathogenic germline variant (PV) in BRCA1 or BRCA2 are at increased risk for a number of malignancies, including breast, ovarian, pancreatic, and prostate cancer. In this review, we discuss emerging evidence that BRCA2 PV carriers, and likely also BRCA1 PV carriers, are also at increased risk for gastric cancer (GC), highlighting that GC may be part of the BRCA1/2 cancer risk spectrum. While the pathogenesis of GC among BRCA1/2 PV carriers remains unclear, increasing evidence reveals that GCs are often enriched with mutations in homologous recombination-associated genes such as BRCA1/2, and that GC prognosis and response to certain therapies can depend on BRCA1/2 expression. Given the strength of data published to date, a risk management strategy for GC among BRCA1/2 PV carriers is needed, and herein we also propose a potential strategy for GC risk management in this population. Moving forward, further study is clearly warranted to define the mechanistic relationship between BRCA1/2 PVs and development of GC as well as to determine how GC risk management should be factored into the clinical care of BRCA1/2 carriers.

Calponin 1 increases cancer-associated fibroblasts-mediated matrix stiffness to promote chemoresistance in gastric cancer

The mechanical microenvironment regulated by cancer-associated fibroblasts (CAFs) influence tumor progression. Chemotherapeutic interventions including 5-Fluorouracil (5-Fu) are commonly used for primary treatment of patients with advanced gastric cancer (GC), and the development of acquired resistance to 5-Fu limits the clinical efficacy of these chemotherapies. However, if and how the interplay between CAFs and the mechanical microenvironment regulates GC response to 5-Fu is poorly understood. In this study, we demonstrate that high-level expression of calponin 1(CNN1) in gastric CAFs predicts poor clinical outcomes of GC patients, especially for those treated with 5-Fu. CNN1 knockdown in CAFs improves the effectiveness of 5-Fu in reducing tumor growth in a mouse GC model and confers increased sensitivity to 5-Fu in a 3D culture system. Furthermore, CNN1 knockdown impairs CAF contraction and reduces matrix stiffness without affecting the expression of matrix proteins. Mechanistically, CNN1 interacts with PDZ and LIM Domain 7 (PDLIM7) and prevents its degradation by the E3 ubiquitin ligase NEDD4-1, which leads to activation of the ROCK1/MLC pathway. The increased matrix stiffness, in turn, contributes to 5-Fu resistance in GC cells by activating YAP. Taken together, our data reveal a critical role of the mechanical microenvironment in 5-Fu resistance, which is modulated by CNN1hi CAFs-mediated matrix stiffening, indicating that targeting CAFs may provide a novel option for overcoming drug resistance in GC.

Identification of TGF-β signaling-related molecular patterns, construction of a prognostic model, and prediction of immunotherapy response in gastric cancer.

Background: TGF-β signaling pathway plays an essential role in tumor progression and immune responses. However, the link between TGF-β signaling pathway-related genes (TSRGs) and clinical prognosis, tumor microenvironment (TME), and immunotherapy in gastric cancer is unclear. Methods: Transcriptome data and related clinical data of gastric cancer were downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and 54 TSRGs were obtained from the Molecular Signatures Database (MSigDB). We systematically analyzed the expression profile characteristics of 54 TSRGs in 804 gastric cancer samples and examined the differences in prognosis, clinicopathological features, and TME among different molecular subtypes. Subsequently, TGF-β-related prognostic models were constructed using univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analysis to quantify the degree of risk in each patient. Patients were divided into two high- and low-risk groups based on the median risk score. Finally, sensitivity to immune checkpoint inhibitors (ICIs) and anti-tumor agents was assessed in patients in high- and low-risk groups. Results: We identified two distinct TGF-β subgroups. Compared to TGF-β cluster B, TGF-β cluster A exhibits an immunosuppressive microenvironment with a shorter overall survival (OS). Then, a novel TGF-β-associated prognostic model, including SRPX2, SGCE, DES, MMP7, and KRT17, was constructed, and the risk score was demonstrated as an independent prognostic factor for gastric cancer patients. Further studies showed that gastric cancer patients in the low-risk group, characterized by higher tumor mutation burden (TMB), the proportion of high microsatellite instability (MSI-H), immunophenoscore (IPS), and lower tumor immune dysfunction and exclusion (TIDE) score, had a better prognosis, and linked to higher response rate to immunotherapy. In addition, the risk score and anti-tumor drug sensitivity were strongly correlated. Conclusion: These findings highlight the importance of TSRGs, deepen the understanding of tumor immune microenvironment, and guide individualized immunotherapy for gastric cancer patients.

A SERPINE1-Based Immune Gene Signature Predicts Prognosis and Immunotherapy Response in Gastric Cancer.

Immune checkpoint inhibitors (ICIs) therapy has been successfully utilized in the treatment of multiple tumors, but only a fraction of patients with gastric cancer (GC) could greatly benefit from it. A recent study has shown that the tumor microenvironment (TME) can greatly affect the effect of immunotherapy in GC. In this study, we established a novel immune risk signature (IRS) for prognosis and predicting response to ICIs in GC based on the TCGA-STAD dataset. Characterization of the TME was explored and further validated to reveal the underlying survival mechanisms and the potential therapeutic targets of GC. The GC patients were stratified into high- and low-risk groups based on the IRS. Patients in the high-risk group, associated with poorer outcomes, were characterized by significantly higher immune function. Further analysis showed higher T cell immune dysfunction and probability of potential immune escape. In vivo, we detected the expressions of SERPINE1 by the quantitative real-time polymerase chain reaction (qPCR)in tumor tissues and adjacent normal tissues. In vitro, knockdown of SERPINE1 significantly attenuated malignant biological behaviors of tumor cells in GC. Our signature can effectively predict the prognosis and response to immunotherapy in patients with GC.

The mechanisms on evasion of anti-tumor immune responses in gastric cancer.

The immune system and the tumor have been at each other's throats for so long that the neoplasm has learned to avoid detection and avoid being attacked, which is called immune evasion. Malignant tumors, such as gastric cancer (GC), share the ability to evade the body's immune system as a defining feature. Immune evasion includes alterations to tumor-associated antigens (TAAs), antigen presentation mechanisms (APMs), and the tumor microenvironment (TME). While TAA and APM are simpler in nature, they both involve mutations or epigenetic regulation of genes. The TME is comprised of numerous cell types, cytokines, chemokines and extracellular matrix, any one of which might be altered to have an effect on the surrounding ecosystem. The NF-kB, MAPK, PI3K/AKT, JAK/STAT, Wnt/β-catenin, Notch, Hippo and TGF-β/Smad signaling pathways are all associated with gastric cancer tumor immune evasion. In this review, we will delineate the functions of these pathways in immune evasion.

Genetic mutation and tumor microbiota determine heterogenicity of tumor immune signature: Evidence from gastric and colorectal synchronous cancers.

Both colorectal and gastric cancer are lethal solid-tumor malignancies, leading to the majority of cancer-associated deaths worldwide. Although colorectal cancer (CRC) and gastric cancer (GC) share many similarities, the prognosis and drug response of CRC and GC are different. However, determinants for such differences have not been elucidated. To avoid genetic background variance, we performed multi-omics analysis, including single-cell RNA sequencing, whole-exome sequencing, and microbiome sequencing, to dissect the tumor immune signature of synchronous primary tumors of GC and CRC. We found that cellular components of juxta-tumoral sites were quite similar, while tumoral cellular components were specific to the tumoral sites. In addition, the mutational landscape and microbiome contributed to the distinct TME cellular components. Overall, we found that different prognoses and drug responses of GC and CRC were mainly due to the distinct TME determined by mutational landscape and microbiome components.

Lipid metabolism characterization in gastric cancer identifies signatures to predict prognostic and therapeutic responses.

Purpose: Increasing evidence has elucidated the significance of lipid metabolism in predicting therapeutic efficacy. Obviously, a systematic analysis of lipid metabolism characterizations of gastric cancer (GC) needs to be reported. Experimental design: Based on two proposed computational algorithms (TCGA-STAD and GSE84437), the lipid metabolism characterization of 367 GC patients and its systematic relationship with genomic characteristics, clinicopathologic features, and clinical outcomes of GC were analyzed in our study. Differentially expressed genes (DEGs) were identified based on the lipid metabolism cluster. At the same time, we applied single-factor Cox regression and random forest to screen signature genes to construct a prognostic model, namely, the lipid metabolism score (LMscore). Next, we deeply explored the predictive value of the LMscore for GC. To verify the specific changes in lipid metabolism, a total of 90 serum, 30 tumor, and non-tumor adjacent tissues from GC patients, were included for pseudotargeted metabolomics analysis via SCIEX triple quad 5500 LC-MS/MS system. Results: Five lipid metabolism signature genes were identified from a total of 3,104 DEGs. The LMscore could be a prognosticator for survival in different clinicopathological GC cohorts. As well, the LMscore was identified as a predictive biomarker for responses to immunotherapy and chemotherapeutic drugs. Additionally, significant changes in sphingolipid metabolism and sphingolipid molecules were discovered in cancer tissue from GC patients by pseudotargeted metabolomics. Conclusion: In conclusion, multivariate analysis revealed that the LMscore was an independent prognostic biomarker of patient survival and therapeutic responses in GC. Depicting a comprehensive landscape of the characteristics of lipid metabolism may help to provide insights into the pathogenesis of GC, interpret the responses of gastric tumors to therapies, and achieve a better outcome in the treatment of GC. In addition, significant alterations of sphingolipid metabolism and increased levels of sphingolipids, in particular, sphingosine (d16:1) and ceramide, were discovered in GC tissue by lipidome pseudotargeted metabolomics, and most of the sphingolipid molecules have the potential to be diagnostic biomarkers for GC.

Analysis of exosomal competing endogenous RNA network response to paclitaxel treatment reveals key genes in advanced gastric cancer

Exosome is an important component of the tumor immune microenvironment and plays critical role in cancer pathogenesis. The exosome transcriptome of gastric cancer (GC) response to paclitaxel chemotherapy has not been investigated in the past. ceRNA microarrays were performed in exosomes from six advanced GC patients before and after paclitaxel treatment. Bioinformatics tools were used to identify differential expressing genes and construct competing endogenous RNA (ceRNA) networks. The importance of hub genes in the ceRNA network was confirmed by survival analysis and functional analysis. A total of 213 differential mRNAs, 370 lncRNAs, and 376 circRNAs were identified, and hub genes in ceRNA networks were screened. The differential genes were associated with GO terms SNAP complex, gap junction, protein transporter activity, cytokine receptor, and KEGG pathways synaptic vesicle cycle, propanoate metabolism, Epstein-Barr virus infection, heparin, and steroid biosynthesis, and beta-alanine metabolism. ULK2, CYP2R1, BTLA, and miR-105-5p are prognostic genes for overall survival. Paclitaxel may target ULK2 which is involved in mitosis and cell cycle. miR-105-5p may target ULK2 3'UTR. The work for the first time identified exosomal RNA biomarkers and constructed a ceRNA network in GC response to paclitaxel, revealed novel molecular mechanisms of GC, and provided new candidates for GC diagnosis and treatment.

A combined analysis of bulk and single-cell sequencing data reveals that depleted extracellular matrix and enhanced immune processes co-contribute to fluorouracil beneficial responses in gastric cancer.

Fluorouracil, also known as 5-FU, is one of the most commonly used chemotherapy drugs in the treatment of advanced gastric cancer (GC). Whereas, the presence of innate or acquired resistance largely limits its survival benefit in GC patients. Although accumulated studies have demonstrated the involvement of tumor microenvironments (TMEs) in chemo-resistance induction, so far little is known about the relevance of GC TMEs in 5-FU resistance. To this end, in this study, we investigated the relationship between TME features and 5-FU responses in GC patients using a combined analysis involving both bulk sequencing data from the TCGA database and single-cell RNA sequencing data from the GEO database. We found that depleted extracellular matrix (ECM) components such as capillary/stroma cells and enhanced immune processes such as increased number of M1 polarized macrophages/Memory T cells/Natural Killer T cells/B cells and decreased number of regulatory T cells are two important features relating to 5-FU beneficial responses in GC patients, especially in diffuse-type patients. We further validated these two features in the tumor tissues of 5-FU-benefit GC patients using immunofluorescence staining experiments. Based on this finding, we also established a Pro (63 genes) and Con (199 genes) gene cohort that could predict 5-FU responses in GC with an AUC (area under curve) score of 0.90 in diffuse-type GC patients, and further proved the partial applicability of this gene panel pan-cancer-wide. Moreover, we identified possible communications mediated by heparanase and galectin-1 which could regulate ECM remodeling and tumor immune microenvironment (TIME) reshaping. Altogether, these findings deciphered the relationship between GC TMEs and 5-FU resistance for the first time, as well as provided potential therapeutic targets and predicting rationale to overcome this chemo-resistance, which could shed some light on developing novel precision treatment strategies in clinical practice.

Immunoregulation and clinical significance of neutrophils/NETs-ANGPT2 in tumor microenvironment of gastric cancer.

Although significant progress has been made in the study of gastric cancer (GC), clinicians lack reliable protein markers for accurate diagnosis and tumor stratification. Neutrophil extracellular traps (NETs) are networks of extracellular fibers composed of DNA from neutrophils. We have previously reported that abundant NETs are deposited in GC, damaging human umbilical vein endothelial cells (HUVECs) and triggering the release of tissue factors, leading to a hypercoagulable state in GC. However, the specific effects of NETs on HUVECs are unclear. We aimed to explore the functional changes caused by NETs on HUVECs, providing evidence that NETs may fuel GC progression. Through quantitative proteomics, we identified 6182 differentially expressed proteins in NET-stimulated HUVECs by TMT. The reliability of the TMT technique was confirmed by parallel reaction monitoring (PRM) analysis of 17 differentially expressed proteins. Through bioinformatics analysis, we found that NETs upregulate ANGPT2 in HUVECs. We comprehensively analyzed the prognosis, biological function, immune response, and therapeutic value of ANGPT2 in GC. We found that overexpression of ANGPT2 in GC is associated with poor prognosis and potentially regulates multiple biological functions. At the same time, ANGPT2 also predicted immunotherapeutic and chemotherapeutic responses in GC. In conclusion, NETs promoted ANGPT2 overexpression in the GC microenvironment. In the future, the neutrophil/NETs-ANGPT2 axis may provide a new target for the treatment of GC.

The downregulated drug-metabolism related ALDH6A1 serves as predictor for prognosis and therapeutic immune response in gastric cancer.

Drug metabolism-associated genes have been clarified to play a vital role in the process of cancer cell growth and migration. Nevertheless, the correlation between drug metabolism-associated genes and gastric cancer (GC) has not been fully explored and clarified. This paper has focused on the role of aldehyde dehydrogenase 6 family member A1 (ALDH6A1), a drug metabolism-associated gene, in the immune regulation and prognosis of GC patients. Using several bioinformatics platforms and immunohistochemistry (IHC) assay, we found that ALDH6A1 expression was significantly down-regulated in GC tissues. Moreover, higher expression of ALDH6A1 was related to the better prognosis of GC patients. ALDH6A1 was also found to be involved in the regulation of several immune-associated signatures, including immunoinhibitors. In conclusion, the above results have concluded that aberrant expression of ALDH6A1 might be served as the promising predictor for prognosis and clinical immunotherapy response in GC patients.