Molecular pathogenesis, targeted therapies, and future perspectives for gastric cancer

TNS4 promotes lymph node metastasis of gastric cancer by interacting with integrin Β1 and inducing the activation of fibroblastic reticular cell

Lymph node (LN) metastasis of gastric cancer (GC) is one of the important pathways of GC metastasis, indicating the clinical staging and prognosis of patients. To investigate the underlying mechanism during the process of GC-induced LN metastasis, 7 pairs of GC tissues, paracancerous (PC) tissues, GC-positive LN (LN.P) and GC-negative LN (LN.N) tissues from GC patients with homogeneity were selected for RNA sequencing (RNA-seq) analysis. Tensin 4 (TNS4) was screened out and found to be significantly upregulated in LN.P tissues and closely related with the characteristics of GC. In vitro and in vivo experiments demonstrated that knockdown of TNS4 could significantly inhibit LN metastasis of GC cells and activation of fibroblastic reticular cells (FRCs) in LNs, thus inhibiting LN expansion induced by tumor cell invasion. Moreover, TNS4 was found to be interacted with integrin beta 1 (ITGB1) on FRCs, thereby affecting the binding of transforming growth factor β1 (TGF-β1) to ITGB1 and subsequently regulating downstream signaling molecules, and supporting the GC cell-induced LN metastasis.

Harnessing technologies to unravel gastric cancer heterogeneity

Gastric cancer arises from complex carcinogenic factor interactions, with limited treatment options due to the lack of targetable driver gene mutations and significant tumor heterogeneity. Recent studies have provided promising novel approaches to improve our understanding of gastric cancer heterogeneity through integrated characterization, combining genomics with emerging technologies. Delineating the molecular changes and targeting specific molecular subtypes will enhance the efficacy of gastric cancer treatment and improve clinical outcomes. This review provides a comprehensive overview of current technologies used in gastric cancer research, highlighting key discoveries and treatment strategies driven by these innovations. Finally, we discuss the emerging technology-guided directions and potential breakthroughs that could enhance the understanding of gastric cancer tumor heterogeneity, ultimately improving clinical outcomes.

Molecular feature-based classification of retroperitoneal liposarcoma: a prospective cohort study

Background

Retroperitoneal liposarcoma (RPLS) is a critical malignant disease with various clinical outcomes. However, the molecular heterogeneity of RPLS was poorly elucidated, and few biomarkers were proposed to monitor its progression.

Methods

RNA sequencing was performed on a training cohort of 88 RPLS patients to identify dysregulated genes and pathways using clusterProfiler. The GSVA algorithm was utilized to assess signaling pathway levels in each sample, and unsupervised clustering was employed to distinguish RPLS subtypes. Differentially expressed genes (DEGs) between RPLS subtypes were identified to construct a simplified dichotomous clustering via nonnegative matrix factorization. The feasibility of this classification was validated in a separate validation cohort (n=241) using immunohistochemistry (IHC) from the REtroperitoneal SArcoma Registry (RESAR). The study is registered with https://clinicaltrials.gov/ under number NCT03838718.

Results

Cell cycle, DNA damage and repair, and metabolism were identified as the most aberrant biological processes in RPLS, enabling the division of RPLS patients into two distinct subtypes with unique molecular signatures, tumor microenvironment, clinical features, and outcomes (overall survival [OS] and disease-free survival [DFS]). A simplified RPLS classification based on representative biomarkers (LEP and PTTG1) demonstrated high accuracy (area under the curve [AUC]>0.99), with patients classified as LEP+ and PTTG1-, showing lower aggressive pathological composition ratio and fewer surgery times, along with better OS (HR = 0.41, p<0.001) and DFS (HR = 0.60, p=0.005).

Conclusions

Our study provided an ever-largest gene expression landscape of RPLS and established an IHC-based molecular classification that was clinically relevant and cost-effective for guiding treatment decisions.

Funding

This work was supported by grants from the Beijing Municipal Science and Technology Project (Z191100006619081), National Natural Science Foundation of China (82073390), and Young Elite Scientists Sponsorship Program (2023QNRC001). The study sponsors had no role in the design and preparation of this manuscript.

Clinical trial number

NCT03838718.

A superior method for antitumor therapy and application: dual-ligand nanomedicines

Currently, nanomedicines have been widely applied in the treatment of various types of tumors. However, due to the complexity of the tumor microenvironment, conventional nanomedicines often exhibit poor efficacy, insufficient site specificity, and susceptibility to off-target effects. In contrast, dual-ligand nanomedicines demonstrate superior targeting ability and drug penetration in tumor therapy. These nanomedicines are equipped with two ligands on their surface, enabling targeting of specific receptors on the same or different cells. The specific binding between ligands and receptors significantly enhances the selectivity and targeting of dual-ligand nanomedicines towards tumors. This review systematically describes the preparation of dual-ligand nanomedicines, the influencing factors, and the types of delivered drugs, focusing on the application of dual-ligand nanomedicines in targeting the treatment of various tumors. We highlight the comprehensiveness of dual-ligand nanomedicines for the treatment of tumors, including glioblastoma, lung cancer, breast cancer, gastric cancer, and many other types of tumors. Finally, the possible challenges for the future development of dual-ligand nanomedicines in terms of preparation, clinic, and safety are further analyzed. We look forward to exploring dual-ligand nanomedicines in greater depth to provide references for their future development and clinical applications.

Roles of plasma proteins in mediating the causal effect of the lipid species on gastric cancer: Insights from proteomic and two-step Mendelian randomization

The change of plasma lipid species has close contacts with gastric cancer (GC). However, the specific mechanism still needs to be explored further. We aim to utilize plasma proteins to decipher the association between lipid species and GC, and seek possible drug targets for GC. We performed a two-step Mendelian randomization (MR) analysis to investigate causal relationships among 179 lipid species, 4907 plasma proteins, and GC. Using summary-data-based MR and colocalization, we first examined protein-GC associations in discovery (N = 35,559) and validation (N = 54,219) cohorts. Subsequent MR analyses assessed lipid-GC and lipid-protein relationships, followed by mediation analysis using error propagation methods. Finally, macromolecular docking of prioritized proteins identified potential therapeutic ligands. Our MR analysis revealed causal relationships between 12 lipid species and GC, as well as 3 plasma proteins and GC. Importantly, mediation analysis demonstrated that CCDC80 protein mediates 2.90% (95% CI: 0.30-5.5%) of the protective effect of diacylglycerol (16:1_18:1) against GC. Based on these findings, we identified valproic acid as a promising therapeutic candidate targeting CCDC80 for GC treatment. Our study demonstrates that reduced CCDC80 expression mediates the tumor-promoting effects of diacylglycerol (16:1_18:1) in GC pathogenesis. Molecular docking confirms valproic acid binds stably to CCDC80, suggesting its therapeutic potential. These findings advance GC etiology understanding and provide a new drug development direction.

PTPRG-AS1 regulates the KITLG/KIT pathway through the ceRNA axis to promote the malignant progression of gastric cancer and the intervention effect of Compound Kushen injection on it

Gastric cancer (GC) is a common malignant tumor with high mortality, recurrence, and metastasis rates. Compound Kushen injection (CKI) combination chemotherapy has been clinically used for the treatment of GC in China for many years, but its underlying mechanisms of action remain unclear. Recent reports have highlighted the important role of the competing endogenous RNA (ceRNA) mechanism of noncoding RNA (ncRNA) and messenger RNA (mRNA) formation in GC and other tumors. This study aimed to investigate the effects of CKI on GC from the ceRNA perspective. We confirmed the inhibitory effect of CKI on GC in mouse models and cell lines. By examining the GC cell lines sensitive to CKI treatment, we developed the CNScore method to analyze the ceRNA network, revealing that the CKI-GC ceRNA network promotes GC proliferation and metastasis through the PTPRG-AS1/hsa-miR-421/KITLG axis. Finally, we constructed GC cell models with PTPRG-AS1 overexpression or knockdown and GC liver metastasis models and found that PTPRG-AS1 can sponge hsa-miR-421, releasing KITLG and promoting GC proliferation and metastasis through the KITLG/KIT pathway. Taken together, CKI can suppress these malignant phenotypes by regulating the PTPRG-AS1/hsa-miR-421/KITLG axis.

9-Hexadecenoic acid inhibits the aggressiveness of gastric cancer via targeting PTPN1/FTH1 signaling

9-Hexadecenoic acid (9-HA) possesses anti-tumor properties. However, the effects of 9-HA on gastric cancer are scarcely reported. The present study aimed to investigate the effects of 9-HA on gastric cancer. mRNA levels were detected by reverse transcription quantitative PCR. Protein expression was detected by western blot. Cell behaviors were analyzed using Cell Counting Kit-8, colony formation, transwell, and propidium iodide staining assays. Co-localization of PTPN1 and FTH1 was determined using fluorescence in situ hybridization assay. In vivo assay was conducted to further verify the effects of 9-HA on gastric cancer. 9-HA suppressed the malignant behavior of gastric cancer. Moreover, 9-HA promoted iron-overload-dependent ferroptosis of gastric cancer in vivo and in vitro. Traditional Chinese medicine systems pharmacology predicted that 9-HA could target PTPN1, which was upregulated in gastric cancer cells. PTPN1-mediated phosphorylation of FTH1 contributed to the latter degradation. Overexpressed PTPN1 alleviated the effects of 9-HA, promoting the aggressiveness of gastric cancer and suppressing tumor cell ferroptosis. Interestingly, overexpressed PTPN1 antagonized the effects of 9-HA, promoted tumor growth, and inhibited the ferroptosis of gastric cancer. In summary, 9-HA-mediated downregulation of PTPN1 drives ferroptosis and inhibit the aggressiveness of gastric cancer. Thence, 9-HA may be an alternative strategy for gastric cancer.

SLC25A42 promotes gastric cancer growth by conferring ferroptosis resistance through enhancing CPT2-mediated fatty acid oxidation

Accumulating evidence has shown that the dysfunction of mitochondria, the multifunctional organelles in various cellular processes, is a pivotal event in the development of various diseases, including human cancers. Solute Carrier Family 25 Member 42 (SLC25A42) is a mitochondrial protein governing the transport of coenzyme A (CoA). However, the biological roles of SLC25A42 in human cancers are still unexplored. Here we uncovered that SLC25A42 is upregulated and correlated with a worse prognosis in GC patients. SLC25A42 promotes the proliferation of gastric cancer (GC) cells while suppresses apoptosis in vitro and in vivo. Mechanistically, SLC25A42 promotes the growth and inhibits apoptosis of GC cells by reprograming lipid metabolism. On the one hand, SLC25A42 enhances fatty acid oxidation-mediated mitochondrial respiration to provide energy for cell survival. On the other hand, SLC25A42 decreases the levels of free fatty acids and ROS to inhibit ferroptosis. Moreover, we found that SLC25A42 reprograms lipid metabolism in GC cells by upregulating the acetylation and thus the expression of CPT2. Collectively, our data reveal a critical oncogenic role of SLC25A42 in GCs and suggest that SLC25A42 represent a promising therapeutic target for GC.

Combining immune checkpoint inhibitors with standard treatment regimens in advanced human epidermal growth factor receptor-2 positive gastric cancer patients

BACKGROUND

Gastric cancer is one of the most common malignant tumors worldwide, with its incidence and mortality rates ranking among the highest in gastrointestinal cancers. The overexpression or gene amplification of human epidermal growth factor receptor 2 (HER-2) occurs in approximately 15%-20% of gastric cancers and serves as a critical molecular target influencing prognosis and treatment outcomes. For patients with HER-2-positive gastric cancer, trastuzumab combined with platinum-based chemotherapy has been established as the standard first-line treatment. However, despite the demonstrated clinical benefits in prolonging survival, the overall efficacy remains limited. In recent years, with the successful application of immune checkpoint inhibitors (ICIs) in various malignant tumors, combining ICIs with existing standard treatment regimens has emerged as a promising approach to enhance the therapeutic efficacy of HER-2-positive gastric cancer. Nevertheless, the efficacy and prognostic factors of ICIs combined with trastuzumab and chemotherapy in HER-2-positive gastric cancer remain unclear.

AIM

To analyze the efficacy of ICIs combined with standard treatment regimens and the prognostic factors in patients with advanced HER-2-positive gastric cancer.

METHODS

Clinical data from 104 patients with advanced HER-2-positive gastric cancer who were treated at our hospital between March 2021 and May 2023 were retrospectively analyzed. Patients were divided into a control group (n = 54, treated with trastuzumab combined with platinum-based chemotherapy as the standard regimen) and an observation group (n = 50, treated with ICIs in addition to the standard regimen). The therapeutic efficacy, survival outcomes, and adverse reactions were compared between the two groups. Univariate and Cox multivariate analyses were performed to identify factors influencing patient prognosis.

RESULTS

With a median follow-up time of 14.6 months, there were no significant differences between the two groups in terms of objective response rate or disease control rate (P > 0.05). The median progression-free survival (mPFS) and mPFS for patients with immunohistochemistry 3 + in the observation group were significantly higher than those in the control group (P < 0.05). Among patients in the observation group, those with positive programmed death-ligand 1 (PD-L1) expression had a significantly higher mPFS than those with negative PD-L1 expression (P < 0.05). Regarding adverse events, significant differences were observed between the two groups in hypothyroidism and neutropenia (P < 0.05). Cox multivariate analysis showed that Eastern Cooperative Oncology Group (ECOG) performance status, peritoneal metastasis, positive programmed death-1 expression, and treatment regimen were independent factors influencing PFS (hazard ratio > 1, P < 0.05).

CONCLUSION

ICIs combined with standard treatment regimens for patients with advanced HER-2-positive gastric cancer demonstrate favorable clinical efficacy, significantly prolonging PFS with manageable safety. ECOG performance status, peritoneal metastasis, positive PD-L1 expression, and treatment regimen are independent factors influencing PFS, warranting increased clinical attention to patients exhibiting these factors.

The evolving landscape of biomarkers for systemic therapy in advanced hepatocellular carcinoma

Hepatocellular carcinoma (HCC) remains one of the most prevalent and deadliest cancers. With the approval of multiple first- and second-line agents, especially the combination therapies based on immune checkpoint inhibitor (ICI) regimens, the landscape of systemic therapy for advanced HCC (aHCC) is more diverse than ever before. The efficacy of current systemic therapies shows great heterogeneity in patients with aHCC, thereby identifying biomarkers for response prediction and patient stratification has become an urgent need. The main biomarkers for systemic therapy in hepatocellular carcinoma are derived from peripheral blood, tissues, and imaging. Currently, the understanding of the clinical response to systemic therapy indicates unequivocally that a single biomarker cannot be used to identify patients who are likely to benefit from these treatments. In this review, we provide an integrated landscape of the recent development in molecular targeted therapies and ICIs-based therapies, especially focusing on the role of clinically applicable predictive biomarkers. Additionally, we further highlight the latest advancements in biomarker-driven therapies, including targeted treatments, adoptive cell therapies, and bispecific antibodies.

The role of UPK1B in gastric cancer: multi-omics analysis and experimental validation

BACKGROUND

UPK1B has been implicated in various cancers; however, its mechanism of action in gastric cancer remains elusive.

METHODS

We utilized transcriptional data and clinical information, and mutation profiles from The Cancer Genome Atlas (TCGA) database to analyze UPK1B's expression and clinical relevance. Biological enrichment, immune microenvironment characterization, and drug sensitivity analyses were conducted. Functional assays, including proliferation, migration, invasion, and in vivo metastasis models, were used to validate UPK1B's role in gastric cancer.

RESULTS

UPK1B was significantly upregulated in gastric cancer and correlated with worse clinical outcomes, including advanced stages and reduced survival rates. Biological enrichment analysis revealed its involvement in cancer-related pathways such as DNA replication and immune regulation. UPK1B was negatively correlated with NK cells and M1 macrophages, indicating its role in immune evasion. Functional experiments demonstrated that knockdown of UPK1B significantly suppressed gastric cancer cell proliferation, invasion, and migration in vitro and reduced pulmonary metastases in vivo. Drug sensitivity analysis suggested that high UPK1B expression was associated with increased sensitivity to lapatinib and resistance to cisplatin.

CONCLUSIONS

UPK1B promotes tumor progression and modulates the immune microenvironment in gastric cancer, making it a potential therapeutic target for future research and clinical applications.

Miltirone enhances the chemosensitivity of gastric cancer cells to cisplatin by suppressing the PI3K/AKT signaling pathway

Background

Gastric cancer (GC) is one of the most common malignant tumors with poor survival. Although cisplatin is a first-line chemotherapy drug for GC, it still has the potential to develop drug resistance and side effects. Miltirone, extracted from Chinese herb Salvia miltiorrhiza Bunge, has been reported to significantly inhibit some types of cancer. However, its effects on GC have not been studied, the possible anti-tumor effects of miltirone in combination with cisplatin in GC patients have not been explored.

Materials and methods

Human GC cell lines AGS, HGC27, MKN45 and MGC803 cells were treated with miltirone and cisplatin individually or combinatorially. Cell proliferation assay, flow cytometric assay, colony formation assay and Western blot were employed to evaluate the cytotoxic effects under these treatments. Wound healing and transwell assays were used to examine the effects of miltirone and/or cisplatin on GC cell migration and invasion. RNA-seq analysis was used to determine miltirone's potential target genes in AGS cells. GO analysis and molecular docking assay were used to determine the pathways affected by miltirone. Next, we examined changes in the selected pathway proteins. The in vivo animal model was verified the results of the in vitro experiments.

Results

Miltirone inhibited cell growth, migration, and invasion, as well as induced apoptosis in GC cells. In combinatorial treatments, miltirone synergistically enhanced cytotoxicity of cisplatin in GC cells. Moreover, the expression levels of 606 genes appeared to be significantly modulated by miltirone via RNA-seq analyses, and PI3K/AKT signaling pathway was found to refer to miltirone activity. Furthermore, miltirone together with cisplatin treatment significantly reduced the expression levels of p-PI3K, p-Akt, p-mTOR, while the total levels of PI3K and Akt remained unchanged. In addition, compared with the control group, the tumors growth was significantly suppressed in groups treated with the two agents alone or in combination, and even more so in the combination group in vivo.

Discussion

Miltirone inhibited the proliferation of GC cells and significantly potentiates the anticancer activities of cisplatin by downregulating the PI3K/AKT signaling pathway. Combination therapy of miltirone and cisplatin represents a novel potential treatment of gastric cancer.

Microsatellite-Stable Gastric Cancer Can be Classified into 2 Molecular Subtypes with Different Immunotherapy Response and Prognosis Based on Gene Sequencing and Computational Pathology

Most patients with gastric cancer (GC) exhibit microsatellite stability, yet comprehensive subtyping for prognostic prediction and clinical treatment decisions for microsatellite-stable GC is lacking. In this work, RNA-sequencing gene expression data and clinical information of patients with microsatellite-stable GC were obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. We employed several machine learning methods to develop and validate a signature based on immune-related genes (IRGs) for subtyping patients with microsatellite-stable GC. Moreover, 2 deep learning models based on the Vision Transformer (ViT) architecture were developed to predict GC tumor tiles and identify microsatellite-stable GC subtypes from digital pathology slides. Microsatellite status was evaluated by immunohistochemistry, and prognostic data as well as hematoxylin and eosin whole-slide images were collected from 105 patients with microsatellite-stable GC to serve as an independent validation cohort. A signature comprising 5 IRGs was established and validated, stratifying patients with microsatellite-stable GC into high-risk (microsatellite-stable-HR) and low-risk (microsatellite-stable-LR) groups. This signature demonstrated consistent performance, with areas under the receiver operating characteristic curve (AUC) of 0.65, 0.70, and 0.70 at 1, 3, and 5 years in the TCGA cohort, and 0.70, 0.60, and 0.62 in the GEO cohort, respectively. The microsatellite-stable-HR subtype exhibited higher levels of tumor immune dysfunction and exclusion, suggesting a greater potential for immune escape compared with the microsatellite-stable-LR subtype. Moreover, the microsatellite-stable-HR/LR subtypes showed differential sensitivities to various therapeutic drugs. Leveraging morphologic differences, the tumor recognition segmentation model achieved an impressive AUC of 0.97, whereas the microsatellite-stable-HR/LR identification model effectively classified microsatellite-stable-HR/LR subtypes with an AUC of 0.94. Both models demonstrated promising results in classifying patients with microsatellite-stable GC in the external validation cohort, highlighting the strong ability to accurately differentiate between microsatellite-stable GC subtypes. The IRG-related microsatellite-stable-HR/LR subtypes had the potential to enhance outcome prediction accuracy and guide treatment strategies. This research may optimize precision treatment and improve the prognosis for patients with microsatellite-stable GC.

NAT10 promotes gastric cancer progression by enhancing the N4-acetylcytidine modification of TNC mRNA

BACKGROUND

Gastric cancer (GC) is a very aggressive malignant tumor of the digestive system. Previous studies have shown that N-acetyltransferase 10 (NAT10) can regulate the N4-acetylcytidine (ac4C) modification of downstream mRNAs through certain pathways to promote the progression of various tumors. However, reports on the regulatory effects of NAT10 on GC are rare. This study aimed to explore the potential mechanism by which NAT10 regulated GC progression.

METHODS

Clinical samples were used to study the correlation between NAT10 expression and poor prognosis in patients with GC by univariate analysis and multivariate analysis. In vitro and in vivo assays were performed to assess the effects of NAT10 and Tenascin C (TNC) on the malignant biological behaviors of GC cells. Acetylated RNA immunoprecipitation sequencing was conducted to explore the role of NAT10 in ac4C modification in GC. mRNA stability and translation efficiency assays were performed to investigate the effect of changes in NAT10 expression on its target TNC.

RESULTS

Analysis of clinical samples revealed that NAT10 expression was abnormally elevated and positively correlated with TNC expression in GC, and increased NAT10 expression led to poor overall survival. In vitro and in vivo experiments revealed that high NAT10 expression promoted the invasive and proliferative capacity of GC cells. Rescue experiments suggested that TNC played an important role in the above process. Mechanistically, the acetylation-based RNA immunoprecipitation sequencing and acetylated RNA immunoprecipitation qPCR results indicated that NAT10 regulated the level of ac4C modification by binding to specific regions in TNC mRNA, increasing mRNA stability and translation, upregulating TNC expression, further activating the TNC/Akt/TGF-β1 positive feedback loop.

CONCLUSIONS

In summary, our results reveal that NAT10 plays a critical role in GC development by affecting TNC mRNA stability and translation efficiency, which ultimately activates the TNC/Akt/TGF-β1 positive feedback loop. This study is expected to provide a novel target and theoretical basis for improving the diagnosis and treatment of GC.

Exploration of the clinicopathological and prognostic significance of BRCA1 in gastric cancer

Gastric cancer (GC) is one of the most common malignancies and is a highly heterogeneous disease; it is also a leading cause of cancer-related death. Owing to the complexity and late-stage diagnosis of GC, the prognosis remains poor. To explore potential biomarkers for GC, GC patient transcriptome data were subjected to a comprehensive approach involving machine learning, binary nomogram prediction model construction, the topological algorithm of CytoHubba, and Kaplan-Meier and Mendelian randomization (MR) analyses. First, gene expression data for normal and GC tissues were assessed via machine learning and the topological algorithm of CytoHubba, and a total of 792 differentially expressed genes (DEGs) and nine core genes were identified. Kaplan-Meier analysis and analysis of a nomogram binary prediction model for the core genes revealed that the expression level of BRCA1 was closely and significantly correlated with the survival time of GC patients, suggesting that BRCA1 may be considered a valuable biomarker for GC diagnosis. Furthermore, MR analysis revealed that BRCA1 promotes the transformation of normal cells into GC cells by regulating NADPH levels, leading to a continuous increase in oxidative stress. This is one of the initial comprehensive analysis involving MR and multidimensional approaches; it revealed the significant role of BRCA1 in GC, providing new ideas on drugs and targets for GC clinical treatment.

The artificial intelligence revolution in gastric cancer management: clinical applications

Nowadays, gastric cancer has become a significant issue in the global cancer burden, and its impact cannot be ignored. The rapid development of artificial intelligence technology is attempting to address this situation, aiming to change the clinical management landscape of gastric cancer fundamentally. In this transformative change, machine learning and deep learning, as two core technologies, play a pivotal role, bringing unprecedented innovations and breakthroughs in the diagnosis, treatment, and prognosis evaluation of gastric cancer. This article comprehensively reviews the latest research status and application of artificial intelligence algorithms in gastric cancer, covering multiple dimensions such as image recognition, pathological analysis, personalized treatment, and prognosis risk assessment. These applications not only significantly improve the sensitivity of gastric cancer risk monitoring, the accuracy of diagnosis, and the precision of survival prognosis but also provide robust data support and a scientific basis for clinical decision-making. The integration of artificial intelligence, from optimizing the diagnosis process and enhancing diagnostic efficiency to promoting the practice of precision medicine, demonstrates its promising prospects for reshaping the treatment model of gastric cancer. Although most of the current AI-based models have not been widely used in clinical practice, with the continuous deepening and expansion of precision medicine, we have reason to believe that a new era of AI-driven gastric cancer care is approaching.

Analysis of shared pathogenic mechanisms and drug targets in myocardial infarction and gastric cancer based on transcriptomics and machine learning

Background

Recent studies have suggested a potential association between gastric cancer (GC) and myocardial infarction (MI), with shared pathogenic factors. This study aimed to identify these common factors and potential pharmacologic targets.

Methods

Data from the IEU Open GWAS project were used. Two-sample Mendelian randomization (MR) analysis was used to explore the causal link between MI and GC. Transcriptome analysis identified common differentially expressed genes, followed by enrichment analysis. Drug target MR analysis and eQTLs validated these associations with GC, and the Steiger direction test confirmed their direction. The random forest and Lasso algorithms were used to identify genes with diagnostic value, leading to nomogram construction. The performance of the model was evaluated via ROC, calibration, and decision curves. Correlations between diagnostic genes and immune cell infiltration were analyzed.

Results

MI was linked to increased GC risk (OR=1.112, P=0.04). Seventy-four genes, which are related mainly to ubiquitin-dependent proteasome pathways, were commonly differentially expressed between MI and GC. Nine genes were consistently associated with GC, and eight had diagnostic value. The nomogram built on these eight genes had strong predictive performance (AUC=0.950, validation set AUC=0.957). Immune cell infiltration analysis revealed significant correlations between several genes and immune cells, such as T cells, macrophages, neutrophils, B cells, and dendritic cells.

Conclusion

MI is associated with an increased risk of developing GC, and both share common pathogenic factors. The nomogram constructed based on 8 genes with diagnostic value had good predictive performance.

Single-cell RNA sequencing and spatial transcriptomics reveal the heterogeneity and intercellular communication of cancer-associated fibroblasts in gastric cancer

BACKGROUND

Gastric cancer is a highly aggressive malignancy characterized by a complex tumor microenvironment (TME). Cancer-associated fibroblasts (CAFs), which are a key component of the TME, exhibit significant heterogeneity and play crucial roles in tumor progression. Therefore, a comprehensive understanding of CAFs is essential for developing novel therapeutic strategies for gastric cancer.

METHODS

This study investigates the characteristics and functional information of CAF subtypes and explores the intercellular communication between CAFs and malignant epithelial cells (ECs) in gastric cancer by analyzing single-cell sequencing data from 24 gastric cancer samples. CellChat was employed to map intercellular communication, and Seurat was used to integrate single-cell sequencing data with spatial transcriptome data to reconstruct a comprehensive single-cell spatial map. The spatial relationship between apCAFs and cancer cells was analyzed using multicolor immunohistochemistry.

RESULTS

Cells were categorized into nine distinct categories, revealing a positive correlation between the proportions of epithelial cells (ECs) and fibroblasts. Furthermore, six fibroblast subpopulations were identified: inflammatory (iCAFs), pericytes, matrix (mCAFs), antigen-presenting (apCAFs), smooth muscle cells (SMCs), and proliferative CAFs (pCAFs). Each of these subpopulations was linked to various biological processes and immune responses. Malignant ECs exhibited heightened intercellular communication, particularly with CAF subpopulations, through specific ligand-receptor interactions. High-density regions of CAF subpopulations displayed spatial exclusivity, with pericytes serving as a source for iCAFs, mCAFs, and apCAFs. Notably, malignant ECs and apCAFs showed increased interactions, with certain ligand-receptor pairs potentially impacting the prognosis of gastric cancer. Multiplex immunohistochemistry (mIHC) confirmed the close spatial proximity of apCAFs to cancer cells in gastric cancer.

CONCLUSION

Our study provided a comprehensive characterization of CAF heterogeneity in gastric cancer and revealed the intricate intercellular networks within the TME. The identified CAF subpopulations and their interactions with malignant cells could serve as potential therapeutic targets.

Cellular heterogeneity and communication networks in gastric cancer: Single-cell analysis reveals β-hydroxybutyrylation-associated genes and immune infiltration characteristics

Gastric cancer is characterized by high heterogeneity, with its complex microenvironment and intercellular communications playing critical roles in disease progression and treatment responses. In this study, we utilized single-cell sequencing to dissect the intricate landscape of gastric cancer, identifying diverse cell populations and their interactions. We focused on the role of β-hydroxybutyrylation (Kbhb)-associated genes and their impact on the tumor microenvironment. By analyzing 189,700 single-cell profiles, we identified four distinct malignant epithelial cell subpopulations characterized by unique gene expression patterns. Among these, 20 β-hydroxybutyrylation (Kbhb)-associated genes were identified, including key genes such as MRPL13, LDHB, COX6C, FABP5, and RPS13, which were significantly associated with immune infiltration and tumor microenvironment remodeling. Hierarchical clustering based on these genes classified gastric cancer patients into two subgroups with distinct prognostic outcomes. Patients in the high-risk subgroup exhibited increased expression of pro-tumor genes and reduced immune infiltration, correlating with poorer survival. We further constructed a robust risk scoring model incorporating these genes, achieving AUC values of 0.72, 0.69, and 0.66 for predicting 1-, 3-, and 5-year survival in the TCGA dataset. These findings underscore the prognostic value of Kbhb-associated genes and their potential as therapeutic targets. This study not only provides insights into the molecular underpinnings of gastric cancer but also offers potential biomarkers for patient stratification and targets for therapeutic intervention.

Bioinformatics Analysis of the Expression and Prognostic Significance of Transcription Factor YY1 in Gastric Cancer

BACKGROUND

Emerging evidence indicates that the transcription factor Yin Yang 1 (YY1) plays a critical role in the carcinogenesis and progression of various human malignancies. YY1 is highly expressed in gastric cancer (GC), raising interest in its role in GC.

AIMS

This study aims to analyze the role of YY1 in gastric cancer, investigate its effect on the tumor microenvironment, and assess its potential as a prognostic marker.

METHODS AND RESULTS

Transcriptomic data and clinical information from GC patients were obtained from the TCGA and UCSC databases. YY1 expression was analyzed using the R "limma" package. Gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed with the online tool clusterProfiler. The relationship between YY1 expression levels and the tumor microenvironment was examined in different risk groups of GC patients. Additionally, YY1-positive staining in 26 clinical GC samples was measured using ImageJ software. Co-expression analysis was used to identify prognostic genes associated with YY1, and a prognostic risk model was built and optimized. Results showed that YY1 was significantly overexpressed in 415 GC (p < 0.001) and was associated with poorer survival outcomes (p = 0.043). GO and KEGG showed that YY1 was involved in key biological processes of the disease. Higher YY1 expression was correlated with lower stromal and immune cell content in the tumor microenvironment. Immunohistochemical staining confirmed YY1 overexpression in GC tissues compared to normal tissues (p = 0.0293). Positive correlations were observed between YY1 and the genes MTA1, TTL15, HNRNPU, WDR20, and PPP4R3A. The prognostic model, which included genes significantly associated with YY1 (risk score AUC = 0.690), predicted patient survival better than other clinical variables.

CONCLUSION

These findings suggest that YY1 plays an important role in the development of GC. Targeting the YY1 pathway may be a potential treatment strategy for GC.

Mechanism research on inhibition of gastric cancer in vitro by the extract of Pinellia ternata based on network pharmacology and cellular metabolomics

Background and purpose

Gastric cancer is a kind of malignant tumor with high incidence and high mortality, which has strong tumor heterogeneity. A classic Chinese medicine, Pinellia ternata (PT), was shown to exert therapeutic effects on gastric cancer cells. However, its chemical and pharmacological profiles remain to be elucidated. In the current study, we aimed to reveal the mechanism of PT in treating gastric cancer cells through metabolomic analysis and network pharmacology.

Methods

Metabolomic analysis of two strains of gastric cancer cells treated with the Pinellia ternata extract (PTE) was used to identify differential metabolites, and the metabolic pathways were enriched by MetaboAnalyst. Then, network pharmacology was applied to dig out the potential targets against gastric cancer cells induced by PTE. The integrated network of metabolomics and network pharmacology was constructed based on Cytoscape.

Results

The PTE was confirmed to significantly inhibit cell proliferation, migration, and invasion of HGC-27 and BGC-823 cells. The results of cellular metabolomics showed that 61 metabolites were differently expressed in gastric cancer cells of the experimental and control groups. Through pathway enrichment analysis, 16 metabolites were found to be involved in the glycerophospholipid metabolism, purine metabolism, sphingolipid metabolism, and tryptophan metabolism. Combined with network pharmacology, seven bioactive compounds were found in PT, and the networks of bioactive compound-target gene-metabolic enzyme-metabolite interactions were constructed.

Conclusions

In conclusion, this study revealed the complicated mechanisms of PT against gastric cancer. Our work provides a novel paradigm to identify the potential mechanisms of pharmacological effects derived from a natural compound.

Preoperative sarcopenia and postoperative accelerated muscle loss negatively impact survival after resection of locally advanced gastric cancer

BACKGROUND

Gastric cancer remains a major health concern worldwide, with locally advanced gastric cancer (LAGC) posing significant challenges due to frequent lymph node metastasis and poor prognosis. While curative gastrectomy with D2 lymph node dissection is the standard treatment, sarcopenia and perioperative skeletal muscle loss (SML) have emerged as critical prognostic factors.

METHODS

We retrospectively analyzed 198 LAGC patients who underwent curative gastrectomy. Preoperative and postoperative sarcopenia were assessed via computed tomography (CT)-derived skeletal muscle index (SMI) at the L3 level. SML was defined based on sex-specific thresholds of SMI changes (%/30 days). Prognostic significance for overall survival (OS) and disease-free survival (DFS) was evaluated using Kaplan-Meier and Cox regression analyses.

RESULTS

The prevalence of sarcopenia increased from 23.7% preoperatively to 33.3% postoperatively. Patients with significant muscle loss (SML) showed worse OS and DFS compared to non-SML patients (P < 0.05). SML was also associated with a higher incidence of Clavien-Dindo grade ≥ 3a complications (P < 0.05). Multivariate analysis identified preoperative sarcopenia (HR = 2.332, P = 0.001), postoperative sarcopenia (HR = 3.189, P = 0.011), and SML (HR = 11.231, P = 0.002) as independent risk factors for OS. Adjuvant chemotherapy significantly improved both OS (HR = 0.532, P = 0.015) and DFS (HR = 0.587, P = 0.041).

CONCLUSIONS

Both preoperative sarcopenia and perioperative SML may negatively impact postoperative prognosis in LAGC patients, suggesting that perioperative evaluation of skeletal muscle mass may help identify high-risk surgical candidates for targeted interventions.

Deciphering the risk of developing liver cancer following gastric cancer diagnosis with genetic evidence: a Mendelian randomization analysis in an East Asian population

BACKGROUND

Liver cancer is a common second primary cancer in gastric cancer patients, but whether a gastric cancer diagnosis contributes to the development of second primary liver cancer remains contentious. This study aims to utilize Mendelian randomization (MR) analysis to investigate the potential causal relationship between gastric cancer and second primary liver cancer from a genetic perspective.

METHODS

We extracted single nucleotide polymorphism for gastric cancer and liver cancer in the East Asian population from the Genome-Wide Association Studies database as instrumental variables and employed univariate and multivariate MR analysis to evaluate the causal relationship between gastric cancer and liver cancer. The robustness of the findings was ensured through heterogeneity and sensitivity analyses.

RESULTS

Univariate MR analysis revealed that genetic susceptibility to gastric cancer in the East Asian population was significantly associated with an increased risk of liver cancer [Inverse-variance weighted (IVW): OR = 1.252, 95% CI 1.076-1.457, P = 0.004]. Multivariate MR analysis indicated that after adjusting for confounding factors, the significant positive causal relationship between gastric cancer and liver cancer remained robust (all P < 0.05). Furthermore, no causal relationship was observed between liver cancer diagnosis and the development of gastric cancer in the East Asian population (IVW: OR = 1.111, 95% CI 0.936-1.318, P = 0.228).

CONCLUSION

Genetic prediction results suggest that gastric cancer survivors might face an increased risk of developing second primary liver cancer, implying the potential value of routine liver cancer screening for gastric cancer survivors.

Overcoming immunotherapy resistance in gastric cancer: insights into mechanisms and emerging strategies

Gastric cancer (GC) remains a leading cause of cancer-related mortality worldwide, with limited treatment options in advanced stages. Immunotherapy, particularly immune checkpoint inhibitors (ICIs) targeting PD1/PD-L1, has emerged as a promising therapeutic approach. However, a significant proportion of patients exhibit primary or acquired resistance, limiting the overall efficacy of immunotherapy. This review provides a comprehensive analysis of the mechanisms underlying immunotherapy resistance in GC, including the role of the tumor immune microenvironment, dynamic PD-L1 expression, compensatory activation of other immune checkpoints, and tumor genomic instability. Furthermore, the review explores GC-specific factors such as molecular subtypes, unique immune evasion mechanisms, and the impact of Helicobacter pylori infection. We also discuss emerging strategies to overcome resistance, including combination therapies, novel immunotherapeutic approaches, and personalized treatment strategies based on tumor genomics and the immune microenvironment. By highlighting these key areas, this review aims to inform future research directions and clinical practice, ultimately improving outcomes for GC patients undergoing immunotherapy.

Integrative analysis of anoikis-related prognostic signature to evaluate the immune landscape and predict therapeutic response in stomach adenocarcinoma

Stomach adenocarcinoma (STAD) is the most prevalent gastrointestinal malignancy and seriously threatens the life of the global population. Anoikis, a process of programmed cell death that occurs when cells detach from the extracellular matrix, is closely associated with tumor invasion and metastasis. In this study, we used the TCGA-STAD database to identify the expression patterns and prognostic relevance of anoikis-related genes (ARGs) in STAD. Functional enrichment analysis was used to explore the potential pathway. LASSO and Cox regression were used to construct anoikis-related prognostic signature. The anoikis risk score (ARS) incorporated 7 genes and stratified patients into highand low-risk subgroups by median value splitting. In addition, external validation was performed based on GSE66229, GSE15459, and GSE84437 cohorts. Nomograms were created based on risk characteristics in combination with clinical variants and the performance of the model was validated with time-dependent AUC, calibration curves, and decision curve analysis (DCA). The prognostic signature indicated that the low-risk subgroup had better outcomes and significant correlations with tumor microenvironment, immune landscape, immunotherapy response, and drug sensitivity. In addition, single-cell analysis displayed the cell types, the subcellular localization of prognostic genes, and the cellular interaction to reveal the potential molecular communication mechanism of anoikis resistance. Finally, in vitro experiments confirmed the critical role of CRABP2 in STAD. The results indicated that CRABP2 knockdown inhibited gastric cancer cell proliferation, migration and invasion, and promoted apoptosis. In summary, ARS can serve as a biomarker for predicting survival outcomes in STAD patients, providing new tools for personalized treatment decisions for STAD patients.

EBV-miR-BART14-3p Targets LACTB to Enhance Gastric Cancer Cell Proliferation and Migration

Epstein-Barr virus (EBV), the first human virus identified with oncogenic properties, encodes a class of microRNAs known as miR-BART (BamHI-A rightward transcript microRNAs). This study investigates the pivotal role of EBV-miR-BART14-3p in the progression of gastric cancer, particularly focusing on its effects on epithelial-mesenchymal transition (EMT), cell proliferation, and migration. EBV-associated gastric cancer (EBVaGC) is distinguished by unique genomic and epigenomic characteristics, with EBV miRNAs significantly influencing tumor biology by regulating gene expression. Our research demonstrates that EBV-miR-BART14-3p facilitates gastric cancer cell migration and invasion by targeting the tumor suppressor gene LACTB, which in turn activates the Phosphoinositide 3-kinase (PI3K)/AKT signaling pathway, a critical driver of EMT. The suppression of LACTB in EBVaGC highlights its crucial role in inhibiting tumor progression. These findings position EBV-miR-BART14-3p as a key player in gastric cancer development and underscore its potential as both a prognostic biomarker and a therapeutic target for EBVaGC.

Gastric Cancer Models Developed via GelMA 3D Bioprinting Accurately Mimic Cancer Hallmarks, Tumor Microenvironment Features, and Drug Responses

Current in vitro models for gastric cancer research, such as 2D cell cultures and organoid systems, often fail to replicate the complex extracellular matrix (ECM) found in vivo. For the first time, this study utilizes a gelatin methacryloyl (GelMA) hydrogel, a biomimetic ECM-like material, in 3D bioprinting to construct a physiologically relevant gastric cancer model. GelMA's tunable mechanical properties allow for the precise manipulation of cellular behavior within physiological ranges. Genetic and phenotypic analyses indicate that the 3D bioprinted GelMA (3Db) model accurately mimics the clinical tumor characteristics and reproduces key cancer hallmarks, such as cell proliferation, invasion, migration, angiogenesis, and the Warburg effect. Comparisons of gene expression and drug responses between the 3Db model and patient-derived xenograft models, both constructed from primary gastric cancer cells, validate the model's clinical relevance. The ability of the 3Db model to closely simulate in vivo conditions highlights its crucial role in identifying treatment targets and predicting patient-specific responses, showcasing its potential in high-throughput drug screening and clinical applications. This study is the first to report the pivotal role of GelMA-based 3D bioprinting in advancing gastric cancer research and regenerative medicine.

Predicting early recurrence in locally advanced gastric cancer after gastrectomy using CT-based deep learning model: a multicenter study

BACKGROUND

Early recurrence in patients with locally advanced gastric cancer (LAGC) portends aggressive biological characteristics and a dismal prognosis. Predicting early recurrence may help determine treatment strategies for LAGC. The goal is to develop a deep learning model for early recurrence prediction (DLER) based on preoperative multiphase computed tomography (CT) images and to further explore the underlying biological basis of the proposed model.

MATERIALS AND METHODS

In this retrospective study, 620 LAGC patients from January 2015 to March 2023 were included in three medical centers and The Cancer Image Archive (TCIA). The DLER model was developed using DenseNet169 and multiphase 2.5D CT images, and then crucial clinical factors of early recurrence were integrated into the multilayer perceptron (MLP) classifier model (DLER MLP ). The area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity were applied to measure the performance of different models. The log-rank test was used to analyze survival outcomes. The genetic analysis was performed using RNA-sequencing data from TCIA.

RESULTS

Using the MLP classifier combined with clinical factors, DLER MLP showed higher performance than DLER and clinical models in predicting early recurrence in the internal validation set (AUC: 0.891 vs. 0.797, 0.752) and two external test sets: test set 1 (0.814 vs. 0.666, 0.808) and test set 2 (0.834 vs. 0.756, 0.766). Early recurrence-free survival, disease-free survival, and overall survival can be stratified using the DLER MLP (all P < 0.001). High DLER MLP score is associated with upregulated tumor proliferation pathways (WNT, MYC, and KRAS signaling) and immune cell infiltration in the tumor microenvironment.

CONCLUSION

The DLER MLP based on CT images was able to predict early recurrence of patients with LAGC and served as a useful tool for optimizing treatment strategies and monitoring.

To describe the subsets of malignant epithelial cells in gastric cancer, their developmental trajectories and drug resistance characteristics

Gastric cancer is an aggressive malignancy characterized by significant clinical heterogeneity arising from complex genetic and environmental interactions. This study employed single-cell RNA sequencing, using the 10 × Genomics platform, to analyze 262,532 cells from gastric cancer samples, identifying 32 distinct clusters and 10 major cell types, including immune cells (e.g., T cells, monocytes) and epithelial subpopulations. Among 27 epithelial subgroups, five malignant subpopulations were identified, each defined by unique marker gene expressions and playing diverse roles in tumor progression. Developmental trajectory analysis revealed potential stem-like characteristics in certain clusters, suggesting their involvement in therapeutic resistance and disease recurrence. Cell-cell communication analysis uncovered a dynamic network of interactions within the tumor microenvironment, potentially influencing tumor growth and metastasis. Differential gene expression analysis identified key genes (LDHA, GPC3, MIF, CD44, and TFF3) that were used to construct a prognostic risk score model. This model demonstrated robust predictive power, achieving AUC values of 0.77, 0.77, and 0.76 for 1-, 3-, and 5-year overall survival in the TCGA training dataset, with validation across independent cohorts. These findings deepen our understanding of gastric cancer's cellular and molecular heterogeneity, offering insights into potential therapeutic targets and biomarkers. By facilitating the development of targeted therapies and personalized treatment strategies, these results hold promise for improving clinical outcomes in gastric cancer patients.

A Golgi apparatus‑related subtype and risk signature predicts prognosis and evaluates immunotherapy response in gastric cancer

BACKGROUND

Gastric cancer (GC) remains a significant health burden, calling for the discovery of novel biomarkers. Golgi apparatus, a crucial cellular organelle involved in tumorigenesis, remains underexplored in GC research. A comprehensive understanding of its role and associated mechanisms is urgently needed.

MATERIALS AND METHODS

Utilizing the TCGA-STAD dataset as the training cohort and GSE84433 as the validation cohort, we explored potential associations between Golgi apparatus-related genes (GARG) and GC clinical risk. We aimed to decipher the prognostic significance and underlying biological mechanisms of these genes via consistent clustering, differential expression analysis, enrichment analyses, and immune infiltration profiling. To assess the relationship between risk stratification and survival outcomes, drug sensitivity, and immune infiltration, we developed the Golgi Apparatus-Related Risk Signature (GARRS). The reliability of GARRS was further corroborated using immunohistochemical staining.

RESULTS

Consensus clustering based on 17 GARG identified two patient subgroups, C1 and C2, exhibiting differential survival, immune scores, and immune cell infiltration. We developed a GARRS using Cox-Lasso regression analysis, accurately stratifying patients into high- and low-risk groups. GARRS' validity was confirmed in the validation set and immunohistochemical staining. Our findings underline the Golgi apparatus' significance in the GC immune microenvironment and GARRS' utility in predicting GC survival outcomes.

CONCLUSION

This study underscores the association between Golgi apparatus subtypes and GC immunotumor microenvironment. GARRS, validated for its prognostic, immune infiltration, and drug sensitivity predictive abilities, offers new insights into gastric cancer treatment strategies.

LncRNA HOXA10-AS as a novel biomarker and therapeutic target in human cancers

Long non-coding RNAs (lncRNAs) are crucial regulatory molecules that participate in numerous cellular development processes, and they have gathered much interest recently. HOXA10 antisense RNA (HOXA10-AS, also known as HOXA-AS4) is a novel lncRNA that was identified to be dysregulated in some prevalent malignancies. In this review, the clinical significance of HOXA10-AS for the prognosis of various cancers is analyzed. In addition, the major advances in our understanding of the cellular biological functions and mechanisms of HOXA10-AS in different human cancers are summarized. These cancers include esophageal carcinoma (ESCA), gastric cancer (GC), glioma, laryngeal squamous cell carcinoma (LSCC), acute myeloid leukemia (AML), lung adenocarcinoma (LUAD), nasopharyngeal carcinoma (NPC), oral squamous cell carcinoma (OSCC), and pancreatic cancer. We also note that the aberrant expression of HOXA10-AS promotes malignant progression through various underlying mechanisms. In conclusion, HOXA10-AS is expected to serve as an ideal clinical biomarker and an effective cancer therapy target.

Methionine restriction promotes the polarization of macrophages towards M1 and the immunotherapy effect of PD-L1/PD-1 blockades by inhibiting the secretion of MIF by gastric carcinoma cells

BACKGROUND

The limited curative effect of PD-L1/PD-1 blockades presents challenges to immunotherapy for advanced gastric cancer. We have found that methionine restriction (MR) enhances the drug resistance of gastric carcinoma cells. We aimed to explore whether MR can enhance the efficacy of PD-L1/PD-1 blockades in gastric cancer.

METHODS

To conduct MR, gastric carcinoma cells were transfected with LV-METase in vitro, and 615 mice were injected with MFC cells with stable METase expression in vivo. Flow cytometry was conducted to measure the proportions of M1/M2 macrophages and CD8+ GZMB+/IFN-γ+ T cells. Additionally, the levels of M1/M2 macrophage markers and MIF were also detected.

RESULTS

MR increased M1 and down-regulated M2 macrophages. MR suppressed MIF levels in gastric carcinoma cells, while the addition of anti-MIF neutralizing antibody inhibited the effect of MR on macrophage M1/M2 polarization. MR enhanced the increase of the proportion of CD8+ GZMB+ T cells and CD8+ IFN-γ+ T cells induced by PD-L1/PD-1 blockades. In vivo detection verified the efficacy of the combination of MR and PD-L1/PD-1 blockades on gastric cancer.

CONCLUSIONS

MR inhibits the secretion of MIF by gastric carcinoma cells, promotes macrophage M1 polarization, and enhances the therapeutic effect of PD-L1/PD-1 blockades in gastric cancer.

Adverse skin reactions secondary to sintilimab for advanced gastric adenocarcinoma: A case report and literature review

Immune checkpoint inhibitors, a class of anticancer drugs, which act via enhancing T cell responses against tumor cells, are associated with immune-related adverse events. The skin is one of the most commonly affected organs. In the present study, a case of a 78-year-old man, who developed systemic eczema dermatitis due to neoadjuvant treatment of locally advanced gastric adenocarcinoma with sintilimab combined with Tigio plus oxaliplatin regimen, was reported. The eczema dermatitis completely subsided after treatment with methylprednisolone. The patient and his family strongly requested surgical intervention. Postoperative pathology revealed a pathological complete response.

METTL14 attenuates cancer stemness by suppressing ATF5/WDR74/β-catenin axis in gastric cancer

Stemness is a key factor contributing to treatment failure in gastric cancer (GC). Methyltransferase-like 14 (METTL14) has been linked to various cancers, though its specific role in regulating stemness in GC remains undefined. In this study, we assessed METTL14 expression levels in GC tissues using public datasets and clinical specimens and investigated its impact on cell proliferation, metastasis, and stemness both in vitro and in vivo. Through m6A RNA immunoprecipitation (MeRIP) and luciferase reporter assays, we identified downstream targets of METTL14. Rescue assays were performed to examine whether METTL14 overexpression could reverse stemness in GC. We also explored the underlying mechanisms using chromatin immunoprecipitation (ChIP) and western blot analysis, focusing on the role of ATF5 and the upstream regulation of METTL14. Our findings show that lower METTL14 expression is associated with poorer overall survival in GC patients. Functionally, METTL14 knockdown enhanced stemness traits in GC cells. Mechanistically, METTL14 facilitated m6A modification, promoting the degradation of ATF5 mRNA. Overexpression of ATF5 reversed the stemness inhibition caused by METTL14 overexpression by increasing WDR74 transcription and enhancing β-catenin nuclear translocation. Furthermore, histone H3 lactylation at Lys18 was found to upregulate METTL14 expression. In conclusion, METTL14 knockdown promotes stemness in GC by mediating m6A modification of ATF5 mRNA, which activates the WDR74/β-catenin axis, making METTL14 a potential therapeutic target for gastric cancer treatment.

Clinical Significance and Immune Infiltration Analyses of a Novel Nerve-Related lncRNA Signature in Gastric Cancer

Gastric cancer (GC) is a progressive disease with high morbidity and mortality. Accumulating evidence indicated that nervous system-cancer crosstalk can affect the occurrence and progression of GC. However, the role of nerve-related lncRNAs (NRLs) in GC remains largely unexplored. In this study, a total of 441 nerve-related genes were collected from the KEGG database, and two approaches, unsupervised clustering and WGCNA, were employed to identify NRLs. Lasso regression analysis was then used to construct the nerve-related lncRNA signature (NRLS). Based on the expression profiles of 5 lncRNAs, we developed a stable NRLS to predict survival in GC patients, and survival analyses showed significantly shorter overall survival (OS) in patients with high NRLS. In addition, the NRLS was found to be positively correlated with immune characteristics, including tumor-infiltrating immune cells, immune modulators, cytokines and chemokines. We then analyzed the role of NRLS in predicting chemotherapy and immunotherapy responses, and constructed the OS nomogram combining NRLS and other clinical features. In conclusion, we constructed a robust NRLS model to stratify GC patients and predict the outcomes of chemotherapy and immunotherapy. This study can provide a new perspective for future individualized treatment of GC.

TRPC6 is a Biomarker for Prognosis and Immunotherapy of Stomach Adenocarcinoma Based on Bioinformatic Analysis and Experimental Validation

BACKGROUND

Transient receptor potential canonical 6 (TRPC6), a key member of the TRPC family, is involved in diverse physiological and pathological processes. Although previous studies have implicated TRPC6 in the progression of stomach adenocarcinoma (STAD), its precise functions and mechanisms remain unclear. Understanding TRPC6's role in STAD may provide insights into its prognostic and therapeutic potential.

METHODS

Using transcriptional and clinical data from The Cancer Genome Atlas (TCGA) database, we assessed the expression and prognostic value of TRPC6 in STAD through Kaplan-Meier survival curve analysis and correlation studies. Immune-related parameters, including immune cell infiltration and immune checkpoint gene expression, were also evaluated. Additionally, drug response analyses explored TRPC6's association with therapeutic agents. In vitro experiments were conducted to investigate TRPC6's role in STAD cell proliferation, migration, and invasion, focusing on its regulation of the PI3K-Akt signaling pathway.

RESULTS

TRPC6 was significantly overexpressed in STAD tissues compared to normal tissues, with high TRPC6 expression associated with poor overall survival. TRPC6 expression correlated strongly with immune cell infiltration, immune checkpoint genes, and sensitivity to therapies such as Lapatinib, anti-CTLA4, and anti-PD1 treatments. Functional assays confirmed that TRPC6 promotes STAD cell proliferation, migration, and invasion by activating the PI3K-Akt signaling pathway.

CONCLUSION

This study highlights the prognostic significance of TRPC6 in STAD and its potential as a therapeutic target. TRPC6's involvement in immune regulation and cancer cell progression underscores its dual role in STAD pathogenesis and treatment, offering new avenues for targeted therapy development.

Combined single cell and spatial transcriptome analysis reveals cellular heterogeneity of hedgehog pathway in gastric cancer

Gastric cancer (GC) is one of the most common and deadly malignancies in the world. Abnormal activation of hedgehog pathway is closely related to tumor development and progression. However, potential therapeutic targets for GC based on the hedgehog pathway have not been clearly identified. In the present study, we combined single-cell sequencing data and spatial transcriptomics to deeply investigate the role of hedgehog pathway in GC. Based on a comprehensive scoring algorithm, we found that fibroblasts from GC tumor tissues were characterized by a highly enriched hedgehog pathway. By analyzing the development process of fibroblasts, we found that CCND1 plays an important role at the end stage of fibroblast development, which may be related to the formation of tumor-associated fibroblasts. Based on spatial transcriptome data, we deeply mined the role of CCND1 in fibroblasts. We found that CCND1-negative and -positive fibroblasts have distinct characteristics. Based on bulk transcriptome data, we verified that highly infiltrating CCND1 + fibroblasts are a risk factor for GC patients and can influence the immune and chemotherapeutic efficacy of GC patients. Our study provides unique insights into GC and hedgehog pathways and also new directions for cancer treatment strategies.

OTUD7B promotes cell migration and invasion, predicting poor prognosis of gastric cancer

BACKGROUND

OTUD7B, a member of the ovarian tumor (OTU) protein superfamily, functions as a deubiquitinating enzyme and is associated with various biological processes and disease conditions, including tumors. In this study, we aimed to explore the expression patterns, prognostic significance, and the functional roles and underlying mechanisms of OTUD7B in gastric cancer (GC).

MATERIALS AND METHODS

Using a blend of bioinformatics, clinical case reviews, and molecular experiments, we evaluated the expression of OTUD7B in GC at both mRNA and protein levels. We examined the relationship between OTUD7B expression and clinicopathological characteristics of GC patients. Additionally, in vitro assays were utilized to assess the effects of OTUD7B on the migratory and invasive capabilities of GC cells. RNA sequencing analysis was conducted to identify critical genes and pathways linked to OTUD7B in GC.

RESULTS

OTUD7B was found to be significantly overexpressed in GC, both at mRNA and protein levels. Higher levels of OTUD7B were positively associated with advanced tumor TNM stage, higher histological grade, and presence of lymph/vein invasion. These correlations were indicative of poorer overall survival (OS) and disease-free survival (DFS) in GC patients. In vitro assays revealed that genetic knockout of OTUD7B markedly reduced the migration and invasion of GC cells, while overexpression of OTUD7B led to enhanced cellular migration and invasion. Furthermore, RNA sequencing and bioinformatic analyses indicated that the absence of OTUD7B suppressed signaling pathways related to cancer progression, metastasis, and metabolism. Mechanistically, OTUD7B likely promotes GC metastasis through the WNT signaling pathway, specifically targeting β-catenin.

CONCLUSIONS

OTUD7B serves as a novel marker for poor prognosis in GC and actively promotes tumor metastasis. Our results shed light on the signaling pathways regulated by OTUD7B and highlight potential targets for therapeutic intervention.

IL-17A in gastric carcinogenesis: good or bad?

Cytokines, which are important to the tumor microenvironment (TME), play critical roles in tumor development, metastasis, and immune responses. Interleukin-17(IL-17) has emerged as a key biomarker in many malignancies; however, its precise involvement in gastric cancer is less fully understood. Elevated levels of IL-17 have been observed in stomach diseases such as Helicobacter pylori infection and autoimmune gastritis, indicating that a sustained Th17 response may precede the development of gastric cancer. While IL-17 is related to inflammatory processes that may lead to cancer, its specific influence on gastric cancer development and therapy needs to be completely understood. Specifically, the release of IL-17A by diverse immune cells has been associated with both tumor development and inhibition in gastric cancer. It may impact tumor development through mechanisms such as boosting cell proliferation, inducing angiogenesis, and enabling immune cell recruitment or, conversely, suppressing tumor growth via the activation of anti-tumor immune responses. The dual role of IL-17 in cancer, along with its various effects depending on the TME and immune cell composition, highlights the complexity of its activity. Current research reveals that although IL-17 might serve as a target for immunotherapy, its therapeutic potential is hindered by its various activities. Some studies have shown that anti-IL-17 drugs may be helpful, especially when paired with immune checkpoint inhibitors, whereas others point to concerns about the validity of IL-17 in gastric cancer therapy. The lack of clinical trials and the heterogeneity of human tumors underscore the necessity for individualized treatment approaches. Further studies are needed to identify the specific mechanisms of IL-17 in gastric cancer and to design targeted therapeutics appropriately.

MT1G promotes iron autophagy and inhibits the function of gastric cancer cell lines by intervening in GPX4/SQSTM1

Gastric cancer (GC) is the fifth most common cancer and the third most common cause of cancer death globally, with high invasiveness, high recurrence rate, and poor prognosis. Multiple studies have shown that Metallothionein-1G (MT1G) is closely associated with oxidative stress, ferroptosis, and autophagy. However, the role and potential mechanisms of MT1G in GC have not been fully elucidated. This study aims to explore the biological functions and regulatory mechanisms of MT1G in GC. Perform bioinformatics analysis using the TCGA database to investigate the expression of MT1G in GC. RT-qPCR and Western blot were used to detect the expression of MT1G, ferroptosis related proteins, autophagy related proteins and ARNTL clock autophagy related proteins in Hgc27, MKN45 and AGS cell lines. Exploring the biological functions of MT1G overexpressing GC cell lines through wound healing and transwell experiments. Use specific fluorescence probes to examine mitochondrial membrane potential and Fe2+ fluorescence intensity. Using immunoprecipitation analysis (CO-IP) to elucidate the association between GC cell lines GPX4, SQSTM and ARNTL. Use flow cytometry to detect ROS expression. Observation of autophagy related morphological changes in cells using transmission electron microscopy. Compared with gastric mucosal cell lines, the expression of MT1G is decreased in three gastric cancer cell lines (Hgc27, MKN45 and AGS). Overexpression of MT1G inhibits the proliferation, migration, and invasion functions of GC cells, reduces SOD and GSH content, increases MDA content, cause the mitochondrial membrane potential to weaken and promote the transformation of JC-1 aggregates to JC-1 monomer, increases Fe2+, affects ROS, and reduces GPX4 and SLC7A11 protein expression, promoting ferroptosis. Overexpression of MT1G promotes the transformation of LC3B I to LC3B II, reduces SQSTM1 protein expression, and leads to the appearance of more autophagosomes and autolysosomes at low magnification. At high magnification, mitochondrial autophagy, endoplasmic reticulum autophagy, lipid droplet autophagy, and wrinkled mitochondrial cristae are observed, promoting autophagy. Overexpression of MT1G inhibits GPX4, thereby affecting SQSTM1 as a vector to promote ARNTL autophagy and EGLN2, promoting ARNTL clock autophagy through the GPX4/SQSTM1 axis. Our research findings elucidate that overexpression of MT1G promotes iron autophagy centered around ARNTL in GC cells via the GPX4/SQSTM1 axis, thereby inhibiting GC cell function and providing a new molecular mechanism and therapeutic target for the development of GC.

LINC02139 interacts with and stabilizes XIAP to regulate cell proliferation and apoptosis in gastric cancer

Previous reports showed that long non-coding RNA (lncRNA) participates in the development and progression of tumors. Nevertheless, the effect of LINC02139 and its mechanism on gastric cancer (GC) is still unknown. We revealed that LINC02139 is upregulated in GC cell lines and tissues and high LINC02139 expression was correlated with the advancement of GC in patients. Functionally, overexpression of LINC02139 promoted, while knockdown of LINC02139 impaired GC cell proliferation, migration, and invasion in vitro and impeded tumorigenesis in a tumor xenograft model in vivo. Mechanistically, LINC02139 directly bound to XIAP and increased the protein level by maintaining its protein stability through inhibition of the ubiquitination and proteasome-dependent degradation pathway. Importantly, the regulatory function of XIAP in LINC02139-mediated oncogenic effects was demonstrated. Both in vitro and in vivo experiments showed that LINC02139 and XIAP collaboratively modulate GC cell growth and apoptosis. Analysis of clinical GC tissues further confirmed the upregulation of XIAP and the positive association between LINC02139 and XIAP expression. These findings established LINC02139 as a driver of tumorigenesis and highlighted the crucial involvement of the LINC02139-XIAP axis in GC progression, suggesting its potential as a promising therapeutic target for combating GC advancement.

Comprehensive analysis of lactylation-related gene sets and mitochondrial functions in gastric adenocarcinoma: implications for prognosis and therapeutic strategies

Gastric adenocarcinoma (STAD) is characterized by high heterogeneity and aggressiveness, leading to poor prognostic outcomes worldwide. This study explored the prognostic significance of lactylation-related gene sets and mitochondrial functions in STAD by integrating large-scale genomic datasets, including TCGA and several GEO datasets. We utilized Spatial transcriptomics and single-cell RNA sequencing to delineate the tumor microenvironment and assess the heterogeneity of cellular responses within the tumor. Additionally, the study identified distinct molecular subtypes within STAD that correspond with unique survival outcomes and immune profiles, enhancing the molecular classification beyond current paradigms. Prognostic models incorporating these molecular markers demonstrated superior predictive capabilities over existing models across multiple validation datasets. Furthermore, our analysis of immune landscapes revealed that variations in lactylation could influence immune cell infiltration and responsiveness, pointing towards novel avenues for tailored immunotherapy approaches. These comprehensive insights provide a foundation for targeted therapeutic strategies and underscore the potential of metabolic and immune modulation in improving STAD treatment outcomes.

Lenvatinib acts on platelet‑derived growth factor receptor β to suppress the malignant behaviors of gastric cancer cells

Given the limited treatment options and high mortality rates associated with gastric cancer, there is a need to explore novel therapeutic options. The present study aimed to investigate the efficacy of lenvatinib, a multi-target tyrosine kinase inhibitor, in mitigating the progress of gastric cancer in vitro. Comprehensive analyses were conducted to assess the impact of lenvatinib on gastric cancer cells, focusing on the inhibition of viability, suppression of proliferation, induction of apoptosis and reduction of metastatic potential. The effects of lenvatinib on these activities were determined using 5-ethynyl-2'-deoxyuridine staining, colony formation assay, flow cytometry, western blotting, scratch assay and Transwell assay. In addition, bioinformatics analyses were employed to identify key regulatory targets of lenvatinib, with particular attention given to platelet-derived growth factor receptor β (PDGFRB). In addition, the effects of PDGFRB overexpression on the regulation of lenvatinib were explored. Lenvatinib demonstrated significant inhibitory effects on the viability, proliferation and metastatic capabilities of MKN45 and HGC27 gastric cancer cell lines. Bioinformatics analyses identified PDGFRB as a crucial target of lenvatinib, with its downregulation showing promise in enhancing overall survival rates of patients with gastric cancer. By contrast, PDGFRB overexpression reversed the effects of lenvatinib on cells. The present findings underscore the potential of lenvatinib as a promising therapeutic option in the treatment of gastric cancer. By elucidating its mechanism of action and identifying PDGFRB as a primary target, the present study may aid further clinical advancements.

Organoids: development and applications in disease models, drug discovery, precision medicine, and regenerative medicine

Organoids are miniature, highly accurate representations of organs that capture the structure and unique functions of specific organs. Although the field of organoids has experienced exponential growth, driven by advances in artificial intelligence, gene editing, and bioinstrumentation, a comprehensive and accurate overview of organoid applications remains necessary. This review offers a detailed exploration of the historical origins and characteristics of various organoid types, their applications-including disease modeling, drug toxicity and efficacy assessments, precision medicine, and regenerative medicine-as well as the current challenges and future directions of organoid research. Organoids have proven instrumental in elucidating genetic cell fate in hereditary diseases, infectious diseases, metabolic disorders, and malignancies, as well as in the study of processes such as embryonic development, molecular mechanisms, and host-microbe interactions. Furthermore, the integration of organoid technology with artificial intelligence and microfluidics has significantly advanced large-scale, rapid, and cost-effective drug toxicity and efficacy assessments, thereby propelling progress in precision medicine. Finally, with the advent of high-performance materials, three-dimensional printing technology, and gene editing, organoids are also gaining prominence in the field of regenerative medicine. Our insights and predictions aim to provide valuable guidance to current researchers and to support the continued advancement of this rapidly developing field.

Unveiling promising targets in gastric cancer therapy: A comprehensive review

Gastric cancer (GC) poses a significant global health challenge, ranking fifth in incidence and third in mortality among all malignancies worldwide. Its insidious onset, aggressive growth, proclivity for metastasis, and limited treatment options have contributed to its high fatality rate. Traditional approaches for GC treatment primarily involve surgery and chemotherapy. However, there is growing interest in targeted therapies and immunotherapies. This comprehensive review highlights recent advancements in GC targeted therapy and immunotherapy. It delves into the mechanisms of various strategies, underscoring their potential in GC treatment. Additionally, the review evaluates the efficacy and safety of relevant clinical trials. Despite the benefits observed in numerous advanced GC patients with targeted therapies and immunotherapies, challenges persist. We discuss pertinent strategies to overcome these challenges, thereby providing a solid foundation for enhancing the clinical effectiveness of targeted therapies and immunotherapies.

Enhancing antitumor efficacy of CLDN18.2-directed antibody-drug conjugates through autophagy inhibition in gastric cancer

Claudin18.2 (CLDN18.2) is overexpressed in cancers of the digestive system, rendering it an ideal drug target for antibody-drug conjugates (ADCs). Despite many CLDN18.2-directed ADCs undergoing clinical trials, the inconclusive underlying mechanisms pose a hurdle to extending the utility of these agents. In our study, αCLDN18.2-MMAE, an ADC composed of an anti-CLDN18.2 monoclonal antibody and the tubulin inhibitor MMAE, induced a dose-dependent apoptosis via the cleavage of caspase-9/PARP proteins in CLDN18.2-positive gastric cancer cells. It was worth noting that autophagy was remarkably activated during the αCLDN18.2-MMAE treatment, which was characterized by the accumulation of autophagosomes, the conversion of autophagy marker LC3 from its form I to II, and the complete autophagic flux. Inhibiting autophagy by autophagy inhibitor LY294002 remarkably enhanced αCLDN18.2-MMAE-induced cytotoxicity and caspase-mediated apoptosis, indicating the cytoprotective role of autophagy in CLDN18.2-directed ADC-treated gastric cancer cells. Combination with an autophagy inhibitor significantly potentiated the in vivo antitumoral efficacy of αCLDN18.2-MMAE. Besides, the Akt/mTOR pathway inactivation was demonstrated to be implicated in the autophagy initiation in αCLDN18.2-MMAE-treated gastric cancer cells. In conclusion, our study highlighted a groundbreaking investigation into the mechanism of the CLDN18.2-directed ADC, focusing on the crucial role of autophagy, providing a novel insight to treat gastric cancer by the combination of CLDN18.2-directed ADC and autophagy inhibitor.

Gastrokine 1 transferred by gastric cancer exosomes inhibits growth and invasion of gastric cancer cells in vitro and in vivo

In gastric cancer, gastrokine 1 (GKN1) is a potential theragnostic marker while the related mechanisms remain elusive. Exosomes mediate intercellular communications via transferring various molecules, yet there are limited research studies on the specific cargos of gastric cancer exosomes and the associated mechanisms in this disease. In the present study, AGS and N87-C cells were transfected with an overexpressed GKN1 plasmid, followed by extraction of exosomes. The study utilized gastric cancer cell lines and a xenograft mouse model to investigate the functional significance of exosomal GKN1. Cell proliferation, metastasis, and apoptosis were assessed through CCK-8, Transwell, and flow cytometry assays, respectively. The study further explored the mechanism of exosomal GKN1 and its interaction with the PI3K/AKT/mTOR signaling pathways, including immunofluorescence and western blot analyses. Exosomal GKN1 was observed to suppress cell proliferation and invasion while enhancing apoptosis. This effect was attributed to the modulation of key proteins involved in cellular processes, including Ki-67, MMP-9, Bcl-2, Bax, caspase-3, and caspase-9, ultimately impacting the PI3K/AKT/mTOR signaling pathway. The findings suggest that exosomal GKN1 exerts inhibitory effects on gastric cancer cell growth and invasion through the regulation of the PI3K/AKT/mTOR signaling cascade, both in experimental cell cultures and animal models.

The preclinical discovery and development of zolbetuximab for the treatment of gastric cancer

INTRODUCTION

Gastric cancer remains a formidable challenge in oncology with high mortality rates and few advancements in treatment. Claudin-18.2 (CLDN18.2) is a tight junction protein primarily expressed in the stomach and is frequently overexpressed in certain subsets of gastric cancers. Targeting CLDN18.2 with monoclonal antibodies, such as zolbetuximab (IMAB362), has shown promising efficacy results in combination with chemotherapy.

AREAS COVERED

The molecular cell biology of CLDN18.2 is discussed along with studies demonstrating the utility of CLDN18.2 expression as a biomarker and therapeutic target. Important clinical studies are reviewed, including Phase III trials, SPOTLIGHT and GLOW, which demonstrate the efficacy of zolbetuximab in combination with chemotherapy in patients with CLDN18.2-positive advanced gastric cancer.

EXPERT OPINION

CLDN18.2 is involved in gastric differentiation through maintenance of epithelial barrier function and coordination of signaling pathways, and its expression in gastric cancers reflects a 'gastric differentiation' program. Targeting Claudin-18.2 represents the first gastric cancer specific 'targeted' treatment. Further studies are needed to determine its role within current gastric cancer treatment sequencing, including HER2-targeted therapies and immunotherapies. Management strategies will also be needed to better mitigate zolbetuximab-related treatment side effects, including gastrointestinal (GI) toxicities.