Molecular classification of gastric cancer

Single-cell RNA sequencing integrated with bulk RNA sequencing analysis reveals diagnostic and prognostic signatures and immunoinfiltration in gastric cancer

BACKGROUND

Early diagnosis and prognostic predication of gastric cancer (GC) pose significant challenges in current clinical practice of GC treatments. Therefore, our aim was to explore relevant gene signatures that can predict the prognosis of GC patients.

METHODS

Here, we established a single-cell transcriptional atlas of GC, focusing on the expression of T-cell-related genes for cell-cell communication analysis, trajectory analysis, and transcription factor regulatory network analysis. Additionally, we conducted validation and prediction of immune-related prognostic gene signatures in GC patients using TCGA and GEO data. Based on these prognostic gene signatures, we predicted the immune infiltration status of GC patients by grouping the patient samples into high or low-risk groups.

RESULTS

Based on 10 tumor samples and corresponding normal samples from GC patients, we selected 18,416 cells for subsequent analysis using single-cell sequencing. From these, we identified 3,284 T-cells and obtained 641 differentially expressed genes related to T-cells from 5 different T-cell subtypes. By integrating bulk RNA sequencing data, we identified prognostic signatures associated with T-cells. Stratifying patients based on these prognostic signatures into high-risk or low-risk groups allowed us to effectively predict their survival rates and the immunoinfiltration status of the tumor microenvironment.

CONCLUSION

This study explored prognostic gene signatures associated with T-cells in GC patients, providing insights into predicting patients' survival rates and immunoinfiltration levels.

KIFC3 Regulates the progression and metastasis of gastric cancer via Notch1 pathway

INTRODUCTION

KIFC3 is a member of the kinesin family which has shown great promise in cancer therapy recently. In this study, we sought to elucidate the role of KIFC3 in the development of GC and its possible mechanisms.

METHODS

Two databases and a tissue microarray were used to explore the expression of KIFC3 and its correlation with patients' clinicopathological characteristics. Cell proliferation was examined by cell counting kit-8 assay and colony formation assay. Wound healing assay and transwell assay were performed to examine cell metastasis ability. EMT and Notch signaling related proteins were detected by western blot. Additionally, a xenograft tumor model was established to investigate the function of KIFC3 in vivo.

RESULTS

The expression of KIFC3 was upregulated in GC, and was associated with higher T stage and poor prognosis in GC patients. The proliferation and metastasis ability of GC cells were promoted by KIFC3 overexpression while inhibited by KIFC3 knockdown in vitro and in vivo. Furthermore, KIFC3 might activate the Notch1 pathway to facilitate the progression of GC, and DAPT, an inhibitor of Notch signaling, could reverse this effect.

CONCLUSION

Together, our data revealed that KIFC3 could enhance the progression and metastasis of GC by activating the Notch1 pathway.

Cancer-associated fibroblast expression of glutamine fructose-6-phosphate aminotransferase 2 (GFPT2) is a prognostic marker in gastric cancer

Glutamine fructose-6-phosphate aminotransferase 2 (GFPT2) is a rate-limiting enzyme in hexosamine biosynthesis involved in the occurrence and progress of many cancers. What role it plays in gastric cancer (GC) is still unclear. In this study, transcriptome sequencing data from the Harbin Medical University (HMU)-GC cohort and The Cancer Genome Atlas (TCGA) dataset were combined with the HMU-TCGA training cohort to analyze the biological function and clinical significance of GFPT2. The correlation of GFPT2 with immune cells and stromal cells was analyzed in the GC immune microenvironment through transcriptome sequencing data and a public single-cell sequencing database. In cell lines, GC tissues, and the tissue microarray, GFPT2 protein expression was confirmed by western blotting and immunohistochemistry. The mRNA of GFPT2 was highly expressed in the tumor (p < 0.001), and GC cells and tumors expressed high levels of GFPT2 protein. Compared to low expression, high GFPT2 mRNA expression was associated with higher levels of tumor invasion, higher pathological stages, and poor prognosis (p = 0.02) in GC patients. In a drug susceptibility analysis, GFPT2 mRNA expression was associated with multiple chemotherapeutic drug sensitivity, including docetaxel, paclitaxel, and cisplatin. Gene enrichment analysis found that GFPT2 was mainly primarily involved in the extracellular matrix receptor interaction pathway. The ESTIMATE, CIBERSORT, and ssGSEA algorithms showed that GFPT2 was associated with immune cell infiltration. In addition, GFPT2 was more likely to be expressed within cancer-associated fibroblasts (CAFs), and high levels of GFPT2 expression were highly correlated with four CAFs scores (all p < 0.05). Finally, a prognostic model to assess the risk of death in GC patients was constructed based on GFPT2 protein expression and lymph node metastasis rate. In conclusion, GFPT2 plays an essential role in the function of CAFs in GC. It can be used as a biomarker to assess GC prognosis and immune infiltration.

Epigenetic Modification-Associated Molecular Classification of Gastric Cancer

Epigenetic modification is involved in tumorigenesis and cancer progression. We developed an epigenetic modification-associated molecular classification of gastric cancer (GC) to identify signature genes that accurately predict prognosis and the efficacy of immunotherapy. Least absolute shrinkage and selection operator and multivariate Cox regression analysis were conducted to develop an epigenetic modification-associated molecular classification. We investigated the significance of PIP4P2, an independent prognostic factor of the classification system, in predicting the prognosis and immunotherapy efficacy of patients with GC. The epigenetic modification-associated molecular classification was highly associated with the clinicopathological characteristics of patients and the existing classification of GC. PIP4P2 was highly expressed in GC tissue and tumor-associated macrophages. High PIP4P2 expression in GC tissue-induced tumor progression by activating PI3K/AKT signal transduction had a negative impact on immunotherapy efficacy. High expression of PIP4P2 in macrophages was correlated with poor prognosis in patients with GC. PIP4P2 is an independent unfavorable prognostic factor of epigenetic modification-associated molecular classification, is involved in tumorigenic progression, and is essential for assessing the prognosis and immunotherapy efficacy of GC.

LncRNAs and PTEN/PI3K signaling: A symphony of regulation in cancer biology

The Emergence of Long Non-coding RNAs (lncRNAs) as Key Regulators in Diverse Biological Processes: A Paradigm Shift in Understanding Gene Expression and its Impact on Cancer. The PTEN/PI3K pathway, a pivotal signaling cascade involved in cancer progression, orchestrates critical cellular functions such as survival, proliferation, and growth. In light of these advances, our investigation delves into the intricate and multifaceted interplay between lncRNAs and the PTEN/PI3K signaling pathway, unearthing previously undisclosed mechanisms that underpin cancer growth and advancement. These elusive lncRNAs exert their influence through direct targeting of the PTEN/PI3K pathway or by skillfully regulating the expression and activity of specific lncRNAs. This comprehensive review underscores the paramount significance of the interaction between lncRNAs and the PTEN/PI3K signaling pathway in cancer biology, unveiling an auspicious avenue for novel diagnostic tools and targeted therapeutic interventions. In this review, we navigate through the functional roles of specific lncRNAs in modulating PTEN/PI3K expression and activity. Additionally, we scrutinize their consequential effects on downstream components of the PTEN/PI3K pathway, unraveling the intricacies of their mutual regulation. By advancing our understanding of this complex regulatory network, this study holds the potential to revolutionize the landscape of cancer research, paving the way for tailored and efficacious treatments to combat this devastating disease.

Expression patterns and immunological characterization of PANoptosis -related genes in gastric cancer

Background

Accumulative studies have demonstrated the close relationship between tumor immunity and pyroptosis, apoptosis, and necroptosis. However, the role of PANoptosis in gastric cancer (GC) is yet to be fully understood.

Methods

This research attempted to identify the expression patterns of PANoptosis regulators and the immune landscape in GC by integrating the GSE54129 and GSE65801 datasets. We analyzed GC specimens and established molecular clusters associated with PANoptosis-related genes (PRGs) and corresponding immune characteristics. The differentially expressed genes were determined with the WGCNA method. Afterward, we employed four machine learning algorithms (Random Forest, Support Vector Machine, Generalized linear Model, and eXtreme Gradient Boosting) to select the optimal model, which was validated using nomogram, calibration curve, decision curve analysis (DCA), and two validation cohorts. Additionally, this study discussed the relationship between infiltrating immune cells and variables in the selected model.

Results

This study identified dysregulated PRGs and differential immune activities between GC and normal samples, and further identified two PANoptosis-related molecular clusters in GC. These clusters demonstrated remarkable immunological heterogeneity, with Cluster1 exhibiting abundant immune infiltration. The Support Vector Machine signature was found to have the best discriminative ability, and a 5-gene-based SVM signature was established. This model showed excellent performance in the external validation cohorts, and the nomogram, calibration curve, and DCA indicated its reliability in predicting GC patterns. Further analysis confirmed that the 5 selected variables were remarkably related to infiltrating immune cells and immune-related pathways.

Conclusion

Taken together, this work demonstrates that the PANoptosis pattern has the potential as a stratification tool for patient risk assessment and a reflection of the immune microenvironment in GC.

GADD45B regulates the carcinogenesis process of chronic atrophic gastritis and the metabolic pathways of gastric cancer

Background

Gastric cancer continues to be a significant global healthcare challenge, and its burden remains substantial. The development of gastric cancer (GC) is closely linked to chronic atrophic gastritis (CAG), yet there is a scarcity of research exploring the underlying mechanisms of CAG-induced carcinogenesis.

Methods

In this study, we conducted a comprehensive investigation into the oncogenes involved in CAG using both bulk transcriptome and single-cell transcriptome data. Our approach employed hdWGCNA to identify pathogenic genes specific to CAG, with non-atrophic gastritis (NAG) serving as the control group. Additionally, we compared CAG with GC, using normal gastric tissue as the control group in the single-cell transcriptome analysis. By intersecting the identified pathogenic genes, we pinpointed key network molecules through protein interaction network analysis. To further refine the gene selection, we applied LASSO, SVM-RFE, and RF techniques, which resulted in a set of cancer-related genes (CRGs) associated with CAG. To identify CRGs potentially linked to gastric cancer progression, we performed a univariate COX regression analysis on the gene set. Subsequently, we explored the relationship between CRGs and immune infiltration, drug sensitivity, and clinical characteristics in gastric cancer patients. We employed GSVA to investigate how CRGs regulated signaling pathways in gastric cancer cells, while an analysis of cell communication shed light on the impact of CRGs on signal transmission within the gastric cancer tumor microenvironment. Lastly, we analyzed changes in metabolic pathways throughout the progression of gastric cancer.

Results

Using hdWGCNA, we have identified a total of 143 pathogenic genes that were shared by CAG and GC. To further investigate the underlying mechanisms, we conducted protein interaction network analysis and employed machine learning screening techniques. As a result, we have identified 15 oncogenes that are specifically associated with chronic atrophic gastritis. By performing ROC reanalysis and prognostic analysis, we have determined that GADD45B is the most significant gene involved in the carcinogenesis of CAG. Immunohistochemical staining and differential analysis have revealed that GADD45B expression was low in GC tissues while high in normal gastric tissues. Moreover, based on prognostic analysis, high expression of GADD45B has been correlated with poor prognosis in GC patients. Additionally, an analysis of immune infiltration has shown a relationship between GADD45B and the infiltration of various immune cells. By correlating GADD45B with clinical characteristics, we have found that it primarily affects the depth of invasion in GC. Through cell communication analysis, we have discovered that the CD99 signaling pathway network and the CDH signaling pathway network are the main communication pathways that significantly alter the microenvironment of gastric tissue during the development of chronic atrophic gastritis. Specifically, GADD45B-low GC cells were predominantly involved in the network communication of the CDH signaling pathway, while GADD45B-high GC cells played a crucial role in both signaling pathways. Furthermore, we have identified several metabolic pathways, including D-Glutamine and D-glutamate metabolism and N-Glycan biosynthesis, among others, that played important roles in the occurrence and progression of GC, in addition to the six other metabolic pathways. In summary, our study highlighted the discovery of 143 pathogenic genes shared by CAG and GC, with a specific focus on 15 oncogenes associated with CAG. We have identified GADD45B as the most important gene in the carcinogenesis of CAG, which exhibited differential expression in GC tissues compared to normal gastric tissues. Moreover, GADD45B expression was correlated with patient prognosis and is associated with immune cell infiltration. Our findings also emphasized the impact of the CD99 and CDH signaling pathway networks on the microenvironment of gastric tissue during the development of CAG. Additionally, we have identified key metabolic pathways involved in GC progression.

Conclusion

GADD45B, an oncogene implicated in chronic atrophic gastritis, played a critical role in GC development. Decreased expression of GADD45B was associated with the onset of GC. Moreover, GADD45B expression levels were closely tied to poor prognosis in GC patients, influencing the infiltration patterns of various cells within the tumor microenvironment, as well as impacting the metabolic pathways involved in GC progression.

B-cell-specific Moloney murine leukemia virus integration site 1 knockdown impairs adriamycin resistance of gastric cancer cells

BACKGROUND AND STUDY AIMS

The B-cell-specific Moloney murine leukemia virus integration site 1 (BMI-1) is associated with the progression of gastric cancer (GC). However, its role in drug resistance of gastric cancer stem cell (GCSC) remains unclear. This study aimed to explore the biological function of BMI-1 in GC cells and its role in drug resistance of GCSCs.

PATIENTS AND METHODS

We assessed BMI-1 expression in the GEPIA database and in our collected samples from patients with GC. We silenced BMI-1 using siRNA to study the cell proliferation and migration of GC cells. We also used Hoechst 33342 staining to verify the effect of adriamycin (ADR) on side population (SP) cells, and measured the effects of BMI-1 on the expression of N-cadherin, E-cadherin, and drug-resistance-related proteins (multidrug resistance mutation 1 and lung resistance-related protein). Finally, we analyzed BMI-1-related proteins uing the STRING and GEPIA databases.

RESULTS

BMI-1 mRNA was upregulated in GC tissues and cell lines, especially in MKN-45 and HGC-27 cells. Silencing BMI-1 reduced the proliferation and migration of GC cells. Knocking down BMI-1 significantly decreased epithelial-mesenchymal transition progression, expression levels of drug-resistant proteins, and the number of SP cells in ADR-treated GC cells. Bioinformatics analysis showed that EZH2, CBX8, CBX4, and SUZ12 were positively correlated with BMI-1 in GC tissues.

CONCLUSION

Our study demonstrates that BMI-1 affects the cellular activity, proliferation, migration, and invasion of GC cells. Silencing the BMI-1 gene significantly reduces the number of SP cells and the expression of drug-resistant proteins in ADR-treated GC cells. We speculate that inhibition of BMI-1 increases the drug resistance of GC cells by affecting GCSCs, and that EZH2, CBX8, CBX4, and SUZ12 may participate in BMI-1-induced enhancement of GCSC-like phenotype and viability.

KCND2: A prognostic biomarker and regulator of immune function in gastric cancer

BACKGROUND

Gastric cancer is a highly heterogeneous disease, which makes it challenging to develop effective targeted therapies. Although the potassium voltage-gated channel subfamily D (KCND) channels, particularly KCND2 (also known as Kv4.2), have found evidence of involvement in the occurrence and development of various cancers, there are still some limitations in our understanding of KCND2's roles in gastric cancer.

METHODS

We analyzed the correlation between KCND2 expression and clinical features as well as immune infiltration using the Cancer Genome Atlas (TCGA) database. Functional assays of KCND2 were conducted using Cell counting Kit-8 (CCK8), clone formation assay and cell cycle analysis. Additionally, immunofluorescence, flow cytometry and quantitative real-time polymerase chain reaction (qRT-PCR) techniques were used to investigate tumor proliferation and immune cell infiltration at different levels of KCND2 expression in vivo.

RESULTS

KCND2 was markedly elevated in gastric cancer and its expression appeared to link to different grades, T stages, and N stages. In addition, KCND2 was an independent predictor of prognosis, and its elevated levels in TCGA database revealed a more unfavorable prognosis for patients with gastric cancer. KCND2 strengthened the viability at the cellular level by boosting the proliferation of gastric cancer cells and reducing their death rate. Additionally, it also highlights that KCND2 the abilities of proliferating of gastric cancer cells by stimulating NF-κB both in cell and animal levels. In addition, the findings provided proof that in animal levels, KCND2 might regulate the immune system by associating with promoting M2 macrophages, which are known to play critical roles in cancer progression. Mechanistically, KCND2 was found to lead to the infiltration of M2 macrophages through activation of NF-κB, ultimately promoting the advancement of gastric cancer.

CONCLUSION

Overall, these findings suggest that KCND2 is likely to be available as an underlying therapeutic target for gastric cancer.

ACTL6A protects gastric cancer cells against ferroptosis through induction of glutathione synthesis

Gastric cancer (GC), one of the most common malignant tumors in the world, exhibits a rapid metastasis rate and causes high mortality. Diagnostic markers and potential therapeutic targets for GCs are urgently needed. Here we show that Actin-like protein 6 A (ACTL6A), encoding an SWI/SNF subunit, is highly expressed in GCs. ACTL6A is found to be critical for regulating the glutathione (GSH) metabolism pathway because it upregulates γ-glutamyl-cysteine ligase catalytic subunit (GCLC) expression, thereby reducing reactive oxygen species (ROS) levels and inhibiting ferroptosis, a regulated form of cell death driven by the accumulation of lipid-based ROS. Mechanistic studies show that ACTL6A upregulates GCLC as a cotranscription factor with Nuclear factor (erythroid-derived 2)-like 2 (NRF2) and that the hydrophobic region of ACTL6A plays an important role. Our data highlight the oncogenic role of ACTL6A in GCs and indicate that inhibition of ACTL6A or GCLC could be a potential treatment strategy for GCs.

The Optimal Tumor Mutational Burden Cutoff Value as a Novel Marker for Predicting the Efficacy of Programmed Cell Death-1 Checkpoint Inhibitors in Advanced Gastric Cancer

PURPOSE

The optimal tumor mutational burden (TMB) value for predicting treatment response to programmed cell death-1 (PD-1) checkpoint inhibitors in advanced gastric cancer (AGC) remains unclear. We aimed to investigate the optimal TMB cutoff value that could predict the efficacy of PD-1 checkpoint inhibitors in AGC.

MATERIALS AND METHODS

Patients with AGC who received pembrolizumab or nivolumab between October 1, 2020, and July 27, 2021, at Samsung Medical Center in Korea were retrospectively analyzed. The TMB levels were measured using a next-generation sequencing assay. Based on receiver operating characteristic curve analysis, the TMB cutoff value was determined.

RESULTS

A total 53 patients were analyzed. The TMB cutoff value for predicting the overall response rate (ORR) to PD-1 checkpoint inhibitors was defined as 13.31 mutations per megabase (mt/Mb) with 56% sensitivity and 95% specificity. Based on this definition, 7 (13.2%) patients were TMB-high (TMB-H). The ORR differed between the TMB-low (TMB-L) and TMB-H (8.7% vs. 71.4%, P=0.001). The progression-free survival and overall survival (OS) for 53 patients were 1.93 (95% confidence interval [CI], 1.600-2.268) and 4.26 months (95% CI, 2.992-5.532). The median OS was longer in the TMB-H (20.8 months; 95% CI, 2.292-39.281) than in the TMB-L (3.31 months; 95% CI, 1.604-5.019; P=0.049).

CONCLUSIONS

The TMB cutoff value for predicting treatment response in AGC patients who received PD-1 checkpoint inhibitor monotherapy as salvage treatment was 13.31 mt/Mb. When applying the programmed death ligand-1 status to TMB-H, patients who would benefit from PD-1 checkpoint inhibitors can be selected.

Single-Cell Profiling of Tumor Immune Microenvironment Reveals Immune Irresponsiveness in Gastric Signet-Ring Cell Carcinoma

BACKGROUND & AIMS

Gastric cancer (GC) is a major cancer type characterized by high heterogeneity in both tumor cells and the tumor immune microenvironment (TIME). One intractable GC subtype is gastric signet-ring cell carcinoma (GSRCC), which is associated with poor prognosis. However, it remains unclear what the GSRCC TIME characteristics are and how these characteristics may contribute to clinical outcomes.

METHODS

We enrolled 32 patients with advanced GC of diverse subtypes and profiled their TIME using an immune-targeted single-cell profiling strategy, including (1) immune-targeted single-cell RNA sequencing (n = 20 patients) and (2) protein expression profiling by a targeted antibody panel for mass cytometry (n = 12 patients). We also generated matched V(D)J (variable, diversity, and joining gene segments) sequencing of T and B cells along CD45+ immunocytes.

RESULTS

We found that compared to non-GSRCC, the GSRCC TIME appears to be quiescent, where both CD4+ and CD8+ T cells are difficult to be mobilized, which further impairs the proper functions of B cells. CXCL13, mainly produced by follicular helper T cells, T helper type 17, and exhausted CD8+ T cells, is a central coordinator of this transformation. We show that CXCL13 expression can predict the response to immune checkpoint blockade in GC patients, which may be related to its effects on tertiary lymphoid structures.

CONCLUSIONS

Our study provides a comprehensive molecular portrait of immune cell compositions and cell states in advanced GC patients, highlighting adaptive immune irresponsiveness in GSRCC and a mediator role of CXCL13 in TIME. Our targeted single-cell transcriptomic and proteomic profiling represents a powerful approach for TIME-oriented translational research.

Efficacy of PD-1 Inhibitors in First-Line Treatment for Advanced Gastroesophageal Junction and Gastric Cancer by Subgroups: A Systematic Review and Meta-Analysis

BACKGROUND

PD-1 inhibitors have been approved for the first-line treatment of patients with advanced gastric cancer, gastroesophageal junction cancer, or esophageal adenocarcinoma. However, the results of several clinical trials are not entirely consistent, and the dominant population of first-line immunotherapy for advanced gastric/gastroesophageal junction cancer still needs to be precisely determined.

OBJECTIVE

This objective of this study is to evaluate the efficacy of anti-PD-1/PD-L1 therapy in advanced gastric/gastroesophageal junction adenocarcinoma patients through a systematic review and meta-analysis of relevant clinical trials.

METHOD

The PubMed, Embase, and Cochrane Library electronic databases were searched up to August 1, 2022, for clinical trials of anti-PD-1/PD-L1 immunotherapy for the first-line treatment of advanced gastroesophageal cancer. Hazard ratios and 95% confidence intervals for overall survival, progression-free survival, and objective response rates were extracted and pooled for meta-analysis. Prespecified subgroups included the following: agent type, PD-L1 expression, and high microsatellite instability.

RESULTS

This study analyzed 5 RCTs involving 3,355 patients. Compared with the chemotherapy group, the combined immunotherapy group had a significantly higher objective response rate (OR = 0.63, 95% CI: 0.55-0.72, p < 0.00001) and prolonged overall survival (HR = 0.82, 95% CI: 0.76-0.88, p < 0.00001) and progression-free survival (HR = 0.75, 95% CI: 0.69-0.82, p < 0.00001). The combination of immunotherapy and chemotherapy prolonged OS in both MSI-H (HR = 0.38, p = 0.002) and MSS (HR = 0.78, p < 0.00001) populations, but there was a significant difference between groups (p = 0.02). However, in improving ORR, the benefit of ICI combined with chemotherapy in the MSS group and MSI-H group was not significantly different between groups (p = 0.52). Combination therapy with ICIs was more effective than chemotherapy alone in prolonging OS in the subgroup with a high CPS, regardless of the CPS cutoff for PD-L1. However, when the cutoff of CPS was 1, the difference between subgroups did not reach statistical significance (p = 0.12), while the benefit ratio of the MSI-H group was higher when the cutoff was 10 (p = 0.004) than when the cutoff value was 5 (p = 0.002).

CONCLUSIONS

For first-line treatment of advanced gastroesophageal cancer, an ICI combination strategy is more effective than chemotherapy. The subgroup of patients with a CPS ≥10 has a more significant benefit, and CPS ≥10 has the potential to be used as an accurate marker of the dominant population of immuno-combined therapy.

Cross-talk of RNA modification "writers" describes tumor stemness and microenvironment and guides personalized immunotherapy for gastric cancer

BACKGROUND

RNA modifications, TME, and cancer stemness play significant roles in tumor development and immunotherapy. The study investigated cross-talk and RNA modification roles in the TME, cancer stemness, and immunotherapy of gastric cancer (GC).

METHODS

We applied an unsupervised clustering method to distinguish RNA modification patterns in GC. GSVA and ssGSEA algorithms were applied. The WM_Score model was constructed for evaluating the RNA modification-related subtypes. Also, we conducted an association analysis between the WM_Score and biological and clinical features in GC and explored the WM_Score model's predictive value in immunotherapy.

RESULTS

We identified four RNA modification patterns with diverse survival and TME features. One pattern consistent with the immune-inflamed tumor phenotype showed a better prognosis. Patients in WM_Score high group were related to adverse clinical outcomes, immune suppression, stromal activation, and enhanced cancer stemness, while WM_Score low group showed opposite results. The WM_Score was correlated with genetic, epigenetic alterations, and post-transcriptional modifications in GC. Low WM_Score was related to enhanced efficacy of anti-PD-1/L1 immunotherapy.

CONCLUSIONS

We revealed the cross-talk of four RNA modification types and their functions in GC, providing a scoring system for GC prognosis and personalized immunotherapy predictions.

Gastric Cancer Biomarker Candidates Identified by Machine Learning and Integrative Bioinformatics: Toward Personalized Medicine

Gastric cancer (GC) is among the leading causes of cancer-related deaths worldwide. The discovery of robust diagnostic biomarkers for GC remains a challenge. This study sought to identify biomarker candidates for GC by integrating machine learning (ML) and bioinformatics approaches. Transcriptome profiles of patients with GC were analyzed to identify differentially expressed genes between the tumor and adjacent normal tissues. Subsequently, we constructed protein-protein interaction networks so as to find the significant hub genes. Along with the bioinformatics integration of ML methods such as support vector machine, the recursive feature elimination was used to select the most informative genes. The analysis unraveled 160 significant genes, with 88 upregulated and 72 downregulated, 10 hub genes, and 12 features from the variable selection method. The integrated analyses found that EXO1, DTL, KIF14, and TRIP13 genes are significant and poised as potential diagnostic biomarkers in relation to GC. The receiver operating characteristic curve analysis found KIF14 and TRIP13 are strongly associated with diagnosis of GC. We suggest KIF14 and TRIP13 are considered as biomarker candidates that might potentially inform future research on diagnosis, prognosis, or therapeutic targets for GC. These findings collectively offer new future possibilities for precision/personalized medicine research and development for patients with GC.

The Human Gastric Juice: A Promising Source for Gastric Cancer Biomarkers

Gastric cancer (GC) is a major public health problem worldwide, with high mortality rates due to late diagnosis and limited treatment options. Biomarker research is essential to improve the early detection of GC. Technological advances and research methodologies have improved diagnostic tools, identifying several potential biomarkers for GC, including microRNA, DNA methylation markers, and protein-based biomarkers. Although most studies have focused on identifying biomarkers in biofluids, the low specificity of these markers has limited their use in clinical practice. This is because many cancers share similar alterations and biomarkers, so obtaining them from the site of disease origin could yield more specific results. As a result, recent research efforts have shifted towards exploring gastric juice (GJ) as an alternative source for biomarker identification. Since GJ is a waste product during a gastroscopic examination, it could provide a "liquid biopsy" enriched with disease-specific biomarkers generated directly at the damaged site. Furthermore, as it contains secretions from the stomach lining, it could reflect changes associated with the developmental stage of GC. This narrative review describes some potential biomarkers for gastric cancer screening identified in gastric juice.

PD-1 inhibitors-based second-line therapy for metastatic gastric cancer

Background

Metastatic gastric cancer (MGC) patients with progression on first-line treatment still have poor outcomes on chemotherapy. The KEYNOTE-061 study demonstrated that pembrolizumab, a PD-1inhibitor, was not better than paclitaxel as second-line therapy for MGC. Herein, we explored the efficacy and safety of PD-1inhibitor based treatment for MGC patients in the second line.

Methods

In this observational, retrospective study, we enrolled MGC patients treated with anti-PD-1 based therapy as second-line in our hospital. We primarily assessed the treatment's efficacy and safety. We also evaluated the relationship between clinical features and outcomes using univariate and multivariate analyses.

Results

We enrolled 129 patients with an objective response rate (ORR) of 16.3% and a disease control rate (DCR) of 79.1%. Patients treated with PD-1inhibitor combined with chemotherapy and anti-angiogenic agents had ORR of 19.6% and higher DCR of 94.1%. The median progression-free survival (PFS) was 4.10 months, and the median overall survival (OS) was 7.60 months. In univariate analysis, patients treated with PD-1inhibitor combined with chemotherapy and anti-angiogenic agents and with prior anti-PD-1 history were significantly associated with favorable PFS and OS. In the multivariate analysis, different combination therapy and prior anti-PD-1 history were independent prognosis biomarkers for PFS and OS. Grade 3 or 4 treatment-related adverse events (TRAEs) occurred in 28 (21.7%) patients. Common adverse events (AEs) included fatigue, hyper/hypothyroidism, neutrophil decrease, anemia, skin reactions, proteinuria, and hypertension. We did not observe treatment-related deaths.

Conclusion

Our current results indicated that PD-1-inhibitor and chemo-anti-angiogenic agents combination therapy and prior PD-1 treatment history might improve clinical activity for GC immunotherapy as second-line treatment with acceptable safety profiles. Further studies are needed to verify those outcomes for MGC in other centers.

Mucin-Phenotype and Expression of the Protein V-Set and Immunoglobulin Domain Containing 1 (VSIG1): New Insights into Gastric Carcinogenesis

In gastric cancer (GC), intestinal metaplasia (IM) is a common precursor lesion, but its relationship to the MUC2/MUC5AC/CDX2 axis is not completely understood. Although V-set and immunoglobulin domain containing 1 (VSIG1) is supposed to be a specific marker for gastric mucosa and GC, respectively, no data about its relationship with IM or mucin phenotype have been published. The aim of our study was to explore the possible linkage between IM and these four molecules. The clinicopathological features of 60 randomly selected GCs were examined in association with VSIG1, MUC2, MUC5AC and CDX2. Two online database platforms were also used to establish the transcription factors (TFs) network involved in MUC2/MUC5AC/CDX2 cascade. IM was more frequently encountered in females (11/16 cases) and in patients below 60 years old (10/16 cases). Poorly differentiated (G3) carcinomas tended to show a loss of CDX2 (27/33 cases) but not of MUC2 and MUC5AC. MUC5AC and CDX2 were lost in parallel with the depth of invasion of the pT4 stage (28/35 and 29/35 cases), while an advanced Dukes-MAC-like stage was only correlated with CDX2 and VSIG1 loss (20/37 and 30/37 cases). VSIG1 was directly correlated with MUC5AC (p = 0.04) as an indicator of gastric phenotype. MUC2-negative cases showed a propensity towards lymphatic invasion (37/40 cases) and distant metastases, while CDX2-negative cases tended to associate with hematogenous dissemination (30/40 cases). Regarding the molecular network, only 3 of the 19 TFs involved in this carcinogenic cascade (SP1, RELA, NFKB1) interacted with all targeted genes. In GC, VSIG1 can be considered an indicator of gastric phenotype carcinomas, where carcinogenesis is mainly driven by MUC5AC. Although infrequently encountered in GC, CDX2 positivity might indicate a locally advanced stage and risk for vascular invasion, especially in tumors developed against the background of IM. The loss of VSIG1 indicates a risk for lymph node metastases.

Natural products targeting signaling pathways associated with regulated cell death in gastric cancer: Recent advances and perspectives

Gastric cancer (GC) is one of the most serious gastrointestinal malignancies with high morbidity and mortality. The complexity of GC process lies in the multi-phenotypic linkage regulation, in which regulatory cell death (RCD) is the core link, which largely dominates the fate of GC cells and becomes a key determinant of GC development and prognosis. In recent years, increasing evidence has been reported that natural products can prevent and inhibit the development of GC by regulating RCDs, showing great therapeutic potential. In order to further clarify its key regulatory characteristics, this review focused on specific expressions of RCDs, combined with a variety of signaling pathways and their crosstalk characteristics, sorted out the key targets and action rules of natural products targeting RCD. It is highlighted that a variety of core biological pathways and core targets are involved in the decision of GC cell fate, including the PI3K/Akt signaling pathway, MAPK-related signaling pathways, p53 signaling pathway, ER stress, Caspase-8, gasdermin D (GSDMD), and so on. Moreover, natural products target the crosstalk of different RCDs by modulating above signaling pathways. Taken together, these findings suggest that targeting various RCDs in GC with natural products is a promising strategy, providing a reference for further clarifying the molecular mechanism of natural products treating GC, which warrants further investigations in this area.

Epigenetically regulated gene expression profiles decipher four molecular subtypes with prognostic and therapeutic implications in gastric cancer

BACKGROUND

Gastric cancer (GC) is one of the most common malignant tumors of the digestive tract which seriously endangers the health of human beings worldwide. Transcriptomic deregulation by epigenetic mechanisms plays a crucial role in the heterogeneous progression of GC. This study aimed to investigate the impact of epigenetically regulated genes on the prognosis, immune microenvironment, and potential treatment of GC.

RESULTS

Under the premise of verifying significant co-regulation of the aberrant frequencies of microRNA (miRNA) correlated (MIRcor) genes and DNA methylation-correlated (METcor) genes. Four GC molecular subtypes were identified and validated by comprehensive clustering of MIRcor and METcor GEPs in 1521 samples from five independent multicenter GC cohorts: cluster 1 was characterized by up-regulated cell proliferation and transformation pathways, with good prognosis outcomes, driven by mutations, and was sensitive to 5-fluorouracil and paclitaxel; cluster 2 performed moderate prognosis and benefited more from apatinib and cisplatin; cluster 3 was featured by an up-regulated ligand-receptor formation-related pathways, poor prognosis, an immunosuppression phenotype with low tumor purity, resistant to chemotherapy (e.g., 5-fluorouracil, paclitaxel, and cisplatin), and targeted therapy drug (apatinib) and sensitive to dasatinib; cluster 4 was characterized as an immune-activating phenotype, with advanced tumor stages, benefit more from immunotherapy and displayed worst prognosis.

CONCLUSIONS

According to the epigenetically regulated GEPs, we developed four robust GC molecular subtypes, which facilitated the understanding of the epigenetic mechanisms underlying GC heterogeneity, offering an optimized decision-making and surveillance platform for GC patients.

Proteomic analysis of DZIP3 interactome and its role in proliferation and metastasis in gastric cancer cells

Gastric cancer is a serious malignant tumor in the world, accounting for the third cause of cancer death worldwide. The pathogenesis of gastric cancer is very complex, in which epigenetic inheritance plays an important role. In our study, we found that DZIP3 was significantly up-regulated in gastric cancer tissues as compared to adjacent normal tissue, which suggested it may be play a crucial part in gastric cancer. To clarify the mechanism of it, we further analyzed the interacting proteome and transcriptome of DZIP3. An association between DZIP3 and some epigenetic regulators, such as CUL4B complex, was verified. We also present the first proteomic characterization of the protein-protein interaction (PPI) network of DZIP3. Then, the transcriptome analysis of DZIP3 demonstrated that knockdown DZIP3 increased a cohort of genes, including SETD7 and ZBTB4, which have essential role in tumors. We also revealed that DZIP3 promotes proliferation and metastasis of gastric cancer cells. And the higher expression of DZIP3 is positively associated with the poor prognosis of several cancers. In summary, our study revealed a mechanistic role of DZIP3 in promoting proliferation and metastasis in gastric cancer, supporting the pursuit of DZIP3 as a potential target for gastric cancer therapy.

System Analysis Based on Lipid-Metabolism-Related Genes Identifies AGT as a Novel Therapy Target for Gastric Cancer with Neoadjuvant Chemotherapy

Gastric cancer (GC) is one of the most common causes of cancer-related deaths worldwide, and chemotherapy is still a standard strategy for treating patients with advanced GC. Lipid metabolism has been reported to play an important role in the carcinogenesis and development of GC. However, the potential values of lipid-metabolism-related genes (LMRGs) concerning prognostic value and the prediction of chemotherapy responsiveness in GC remains unclear. A total of 714 stomach adenocarcinoma patients were enrolled from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Using univariate Cox and LASSO regression analyses, we developed a risk signature based on LMRGs that can distinguish high-GC-risk patients from low-risk patients with significant differences in overall survival. We further validated this signature prognostic value using the GEO database. The R package "pRRophetic" was applied to calculate the sensitivity of each sample from high- and low-risk groups to chemotherapy drugs. The expression of two LMRGs, AGT and ENPP7, can predict the prognosis and response to chemotherapy in GC. Furthermore, AGT significantly promoted GC growth and migration, and the downregulation of AGT enhanced the chemotherapy response of GC both in vitro and in vivo. Mechanistically, AGT induced significant levels of epithelial-mesenchymal transition (EMT) through the PI3K/AKT pathway. The PI3K/AKT pathway agonist 740 Y-P can restore the EMT of GC cells impaired by AGT knockdown and treatment with 5-fluorouracil. Our findings suggest that AGT plays a key role in the development of GC, and targeting AGT may help to improve the chemotherapy response of GC patients.

Multiplex immune profiling reveals the role of serum immune proteomics in predicting response to preoperative chemotherapy of gastric cancer

Responses toward preoperative chemotherapy are heterogeneous in patients with gastric adenocarcinoma. Existing studies in the field focus heavily on the tumor microenvironment (TME), whereas little is known about the relationship between systemic immunity and chemotherapy response. In this study, we collect serum samples from patients with gastric adenocarcinoma before, on, and after preoperative chemotherapy and study their immune proteomics using an antibody-based proteomics panel. We also collect surgically resected tumor samples and incorporate multiple methods to assess their TME. We find that both local and systemic immune features are associated with treatment response. Preoperative chemotherapy induces a sophisticated systemic immune response indicated by dynamic serum immune proteomics. A pretreatment serum protein scoring system is established for response prediction. Together, these findings highlight the fundamental but largely underestimated role of systemic immunity in the treatment of gastric cancer, suggesting a patient stratification strategy based on pretreatment serum immune proteomics.

Identification of three metabolic subtypes in gastric cancer and the construction of a metabolic pathway-based risk model that predicts the overall survival of GC patients

Gastric cancer (GC) is highly heterogeneous and GC patients have low overall survival rates. It is also challenging to predict the prognosis of GC patients. This is partly because little is known about the prognosis-related metabolic pathways in this disease. Hence, our objective was to identify GC subtypes and genes related to prognosis, based on changes in the activity of core metabolic pathways in GC tumor samples. Differences in the activity of metabolic pathways in GC patients were analyzed using Gene Set Variation Analysis (GSVA), leading to the identification of three clinical subtypes by non-negative matrix factorization (NMF). Based on our analysis, subtype 1 showed the best prognosis while subtype 3 exhibited the worst prognosis. Interestingly, we observed marked differences in gene expression between the three subtypes, through which we identified a new evolutionary driver gene, CNBD1. Furthermore, we used 11 metabolism-associated genes identified by LASSO and random forest algorithms to construct a prognostic model and verified our results using qRT-PCR (five matched clinical tissues of GC patients). This model was found to be both effective and robust in the GSE84437 and GSE26253 cohorts, and the results from multivariate Cox regression analyses confirmed that the 11-gene signature was an independent prognostic predictor (p < 0.0001, HR = 2.8, 95% CI 2.1-3.7). The signature was found to be relevant to the infiltration of tumor-associated immune cells. In conclusion, our work identified significant GC prognosis-related metabolic pathways in different GC subtypes and provided new insights into GC-subtype prognostic assessment.

A novel metabolism-related prognostic gene development and validation in gastric cancer

BACKGROUND

The importance of metabolism-related alterations in the development of gastric cancer (GC) is increasingly recognized. The present study aimed to identify metabolism-related genes to facilitate prognosis of GC patients.

METHODS

Gene expression datasets and clinical information of GC patients were downloaded from TCGA and GEO databases. We scored the enrichment of human metabolism-related pathways (n = 86) in GC samples by GSV, constructed prognostic risk models using LASSO algorithm and multivariate Cox regression analysis, combined with clinical information to construct a nomogram, and finally cis score algorithm to analyze the abundance of immune-related cells in different subtypes. We used Weka software to screen for prognosis-related marker genes and finally validated the expression of the selected genes in clinical cancer patient tissues.

RESULTS

We identified that two GC metabolism-related signatures were strongly associated with OS and the levels of immune cell infiltration. Moreover, a survival prediction model for GC was established based on six GC metabolism-related genes. Time-dependent ROC analysis showed good stability of the risk prediction scoring model. The model was successfully validated in an independent ACRG cohort, and the expression trends of key genes were also verified in the GC tissues of patients. DLX1, LTBP2, FGFR1 and MMP2 were highly expressed in the cluster with poorer prognosis while SLC13A2 and SLCO1B3 were highly expressed in the cluster with better prognosis.

CONCLUSIONS

We identified a risk predictive score model based on six metabolism-related genes related to survival, which may serve as prognostic indicators and potential therapeutic targets for GC.

Comprehensive transcriptomic profiling and mutational landscape of primary gastric linitis plastica

BACKGROUND

Primary gastric linitis plastica (GLP) is a distinct phenotype of gastric cancer with poor survival. Comprehensive molecular profiles and putative therapeutic targets of GLP remain undetermined.

METHODS

We subjected 10 tumor-normal tissue pairs to whole exome sequencing (WES) and whole transcriptome sequencing (WTS). 10 tumor samples were all GLP which involves 100% of the gastric wall macroscopically. TCGA data were compared to generate the top mutated genes and the overexpressed genes in GLP.

RESULTS

Our results reveal that GLP has distinctive genomic and transcriptomic features, dysfunction in the Hippo pathway is likely to be a key step during GLP development. 6 genes were identified as significantly highly mutated genes in GLP, including AOX1, ANKRD36C, CPXM1, PTPN14, RPAP1, and DCDC1). MUC6, as a previously identified gastric cancer driver gene, has a high mutation rate (20%) in GLP. 20% of patients in our GLP cohort had CDH1 mutations, while none had RHOA mutations. GLP exhibits high immunodeficiency and low AMPK pathway activity. Our WTS results showed that 3 PI3K-AKT pathway-related genes (PIK3R2, AKT3, and IGF1) were significantly up-regulated in GLP. Two genes were identified using immunohistochemistry (IHC), IGF2BP3 and MUC16, which specifically expressed in diffuse-type-related gastric cancer cell lines, and its knockdown inhibits PI3K-AKT pathway activity.

CONCLUSIONS

We provide the first integrative genomic and transcriptomic profiles of GLP, which may facilitate its diagnosis, prognosis, and treatment.

Differential Expression in the Tumor Microenvironment of mRNAs Closely Associated with Colorectal Cancer Metastasis

BACKGROUND

Metastasis of colorectal cancer (CRC) is a major cause of CRC-related mortality. However, the detailed molecular mechanism of CRC metastasis remains unknown. A recent study showed that the tumor microenvironment, which includes cancer cells and the surrounding stromal cells, plays a major role in tumor invasion and metastasis. Identification of altered messenger RNA (mRNA) expression in the tumor microenvironment is essential to elucidation of the mechanisms responsible for tumor progression. This study investigated the mRNA expression of genes closely associated with metastatic CRC compared with non-metastatic CRC.

METHODS

The samples examined were divided into cancer tissue and isolated cancer stromal tissue. The study examined altered mRNA expression in the cancer tissues using The Cancer Genome Atlas (TCGA) (377cases) and in 17 stromal tissues obtained from our laboratory via stromal isolation using an array-based analysis. In addition, 259 patients with CRC were enrolled to identify the association of the candidate markers identified with the prognosis of patients with stage 2 or 3 CRC. The study examined the enriched pathways identified by gene set enrichment analysis (GSEA) based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) module in both the TCGA dataset and isolated stromal tissue.

RESULTS

As a result, whereas tenascin-C, secreted phosphoprotein 1 and laminin were expressed in metastatic CRC cells, olfactory receptors (ORs) 11H1 and OR11H4 were expressed in stromal tissue cells isolated from metastatic CRC cases. Finally, upregulated expression of tenascin-C and OR11H4 was correlated with the outcome for CRC patients.

CONCLUSION

The authors suggest that upregulated expression levels of tenascin-C and OR11H1 play an important role in CRC progression.

Comprehensive analysis of autophagy-related clusters and individual risk model for immunotherapy response prediction in gastric cancer

Introduction

Autophagy can be triggered by oxidative stress and is a double-edged sword involved in the progression of multiple malignancies. However, the precise roles of autophagy on immune response in gastric cancer (GC) remain clarified.

Methods

We endeavor to explore the novel autophagy-related clusters and develop a multi-gene signature for predicting the prognosis and the response to immunotherapy in GC. A total of 1505 patients from eight GC cohorts were categorized into two subtypes using consensus clustering. We compare the differences between clusters by the multi-omics approach. Cox and LASSO regression models were used to construct the prognostic signature.

Results

Two distinct clusters were identified. Compared with cluster 2, the patients in cluster 1 have favorable survival outcomes and lower scores for epithelial-mesenchymal transition (EMT). The two subtypes are further characterized by high heterogeneity concerning immune cell infiltration, somatic mutation pattern, and pathway activity by gene set enrichment analysis (GSEA). We obtained 21 autophagy-related differential expression genes (DEGs), in which PTK6 amplification and BCL2/CDKN2A deletion were highly prevalent. The four-gene (PEA15, HSPB8, BNIP3, and GABARAPL1) risk signature was further constructed with good predictive performance and validated in 3 independent datasets including our local Tianjin cohort. The risk score was proved to be independent prognostic factor. A prognostic nomogram showed robust validity of GC survival. The risk score was significantly associated with immune cell infiltration status, tumor mutation burden (TMB), microsatellite instability (MSI), and immune checkpoint molecules. Furthermore, the model was efficient for predicting the response to tumor-targeted agent and immunotherapy and verified by the IMvigor210 cohort. This model is also capable of discriminating between low and high-risk patients receiving chemotherapy.

Conclusion

Altogether, our exploratory research on the landscape of autophagy-related patterns may shed light on individualized therapies and prognosis in GC.

Development and validation of survival prediction model for gastric adenocarcinoma patients using deep learning: A SEER-based study

Background

The currently available prediction models, such as the Cox model, were too simplistic to correctly predict the outcome of gastric adenocarcinoma patients. This study aimed to develop and validate survival prediction models for gastric adenocarcinoma patients using the deep learning survival neural network.

Methods

A total of 14,177 patients with gastric adenocarcinoma from the Surveillance, Epidemiology, and End Results (SEER) database were included in the study and randomly divided into the training and testing group with a 7:3 ratio. Two algorithms were chosen to build the prediction models, and both algorithms include random survival forest (RSF) and a deep learning based-survival prediction algorithm (DeepSurv). Also, a traditional Cox proportional hazard (CoxPH) model was constructed for comparison. The consistency index (C-index), Brier score, and integrated Brier score (IBS) were used to evaluate the model's predictive performance. The accuracy of predicting survival at 1, 3, 5, and 10 years was also assessed using receiver operating characteristic curves (ROC), calibration curves, and area under the ROC curve (AUC).

Results

Gastric adenocarcinoma patients were randomized into a training group (n = 9923) and a testing group (n = 4254). DeepSurv showed the best performance among the three models (c-index: 0.772, IBS: 0.1421), which was superior to that of the traditional CoxPH model (c-index: 0.755, IBS: 0.1506) and the RSF with 3-year survival prediction model (c-index: 0.766, IBS: 0.1502). The DeepSurv model produced superior accuracy and calibrated survival estimates predicting 1-, 3- 5- and 10-year survival (AUC: 0.825-0.871).

Conclusions

A deep learning algorithm was developed to predict more accurate prognostic information for gastric cancer patients. The DeepSurv model has advantages over the CoxPH and RSF models and performs well in discriminative performance and calibration.

A molecular classification of gastric cancer associated with distinct clinical outcomes and validated by an XGBoost-based prediction model

Gastric cancer (GC) is a heterogeneous disease and a leading cause of cancer-related deaths. Discovering robust, clinically relevant molecular classifications is critical for guiding personalized therapies for GC. Here, we propose a refined molecular classification scheme for GC using integrated optimal algorithms and multi-omics data. Based on the important features of mRNA, microRNA, and DNA methylation data selected by the multivariate Cox regression model, three subtypes linked to distinct clinical outcomes were identified by combining similarity network fusion and consensus clustering methods. Three subtypes were validated by an extreme gradient boosting machine learning prediction model with 125 differentially expressed genes in multiple independent cohorts. The molecular characteristics of mutation signatures, characteristic gene sets, driver genes, and chemotherapy sensitivity for each subtype were also identified: subtype 1 was associated with favorable prognosis and characterized by high ARID1A and PIK3CA mutations, subtype 2 was associated with a poor prognosis and harbored high recurrent TP53 mutations, and subtype 3 was associated with high CHD1, APOA1 mutations, and a poor prognosis. The proposed three-subtype scheme achieved a better clinical prediction performance (area under the curve value = 0.71) than The Cancer Genome Atlas classification, which may provide a practical subtyping framework to improve the treatment of GC.

EBV and MSI Status in Gastric Cancer: Does It Matter?

We investigated the impactof microsatellite instability (MSI) and Epstein-Barr virus (EBV) status in gastric cancer (GC), regarding response to perioperative chemotherapy (POPChT), overall survival (OS), and progression-free survival (PFS). We included 137 cases of operated GC, 51 of which were submitted to POPChT. MSI status was determined by multiplex PCR and EBV status by EBV-encoded RNA in situ hybridization. Thirty-seven (27%) cases presented as MSI-high, and seven (5.1%) were EBV+. Concerning tumor regression after POPChT, no differences were observed between the molecular subtypes, but females were more likely to respond (p = 0.062). No significant differences were found in OS or PFS between different subtypes. In multivariate analysis, age (HR 1.02, IC 95% 1.002-1.056, p = 0.033) and positive lymph nodes (HR 1.82, IC 95% 1.034-3.211, p = 0.038) were the only prognostic factors for OS. However, females with MSI-high tumors treated with POPChT demonstrated a significantly increased OS compared to females with MSS tumors (p = 0.031). In conclusion, we found a high proportion of MSI-high cases. MSI and EBV status did not influence OS or PFS either in patients submitted to POPChT or surgery alone. However, superior survival of females with MSI-high tumors suggests that sex disparities and molecular classification may influence treatment options in GC.

Ginsenoside Rh1 regulates gastric cancer cell biological behaviours and transplanted tumour growth in nude mice via the TGF-β/Smad pathway

Gastric cancer (GC) is one of the most prevalent malignancies of the digestive tract. Ginsenoside Rh1 was reported to exert effects on GC. The current study set out to explore the mechanism underlying Ginsenoside Rh1 effects on GC. With oxaliplatin (OXA) serving as the positive control, human GC cells AGS were treated with 0, 10, 25, 50, 74, or 100 μM of ginsenoside Rh1 for 48 h. Proliferation, migration, invasion, and apoptosis were subsequently assessed by means of MTT, scratch test, Transwell, and TUNEL, respectively. AGS cells were further jointly treated with Rh1 and the TGF-β/Smad pathway activator Kartogenin, followed by detection of TGF-β/Smad pathway effects on AGS biological behaviours. Moreover, TGF-β/Smad pathway activation was detected with a Western blot assay. Furthermore, xenograft tumour models were established and tumour growth was recorded. Ki-67 expression patterns and apoptosis were detected with immunohistochemistry and TUNEL, respectively. In vitro, Ginsenoside Rh1 repressed AGS cell proliferation, migration, and invasion, and further promoted apoptosis, with a concentration of 50 μM Rh1 exerting the equivalent effects as OXA. In vivo, Ginsenoside Rh1 inhibited GC proliferation and induced tumour cell apoptosis. Mechanistically, Ginsenoside Rh1 reduced TGF-β1 and TGF-β2 levels and Smad2 and Smad3 phosphorylation levels. Collectively, our findings highlighted that ginsenoside Rh1 inhibited GC cell growth and tumour growth in xenograft tumour models via inhibition of the TGF-β/Smad pathway.

Potential value of the homologous recombination deficiency signature we developed in the prognosis and drug sensitivity of gastric cancer

Background: Homologous recombination is an important DNA repair mechanism, which deficiency is a common feature of many cancers. Defining homologous recombination deficiency (HRD) status can provide information for treatment decisions of cancer patients. HRD score is a widely accepted method to evaluate HRD status. This study aimed to explored HRD in gastric cancer (GC) patients' clinical outcomes with genes related to HRD score and HRD components score [HRD-loss of heterozygosity (LOH), large-scale state transitions (LST), and telomeric allelic imbalance (NtAI)]. Methods: Based on LOH, NtAI scores, LST, and integrated HRD scores-related genes, a risk model for stratifying 346 TCGA GC cases were developed by Cox regression analysis and LASSO Cox regression. The risk scores of 33 cancers in TCGA were calculated to analyze the relationship between risk scores of each cancer and HRD scores and 3 HRD component scores. Relationship between the risk model and patient survival, BRCA1, BRCA2 mutation, response to Cisplatin and Talazoparib treatment was analyzed by generating Kaplan-Meier curve, mutations waterfall map and conducting Pearson correlation analysis. Results: An gene signature was constructed based on 11 HRD scores-related gene (BEX2, C1QL2, DKK1, DRC1, GLUD2, HCAR1, IGFBP1, NXPH1, PROC, SERPINA5, and SLCA1A2). Risk groups were stratified by risk score. Prognosis of the high-risk score group was worse than the low-risk ones. Risk score was associated with BRCA2 mutation, and patients grouped according to BRCA2 mutation status had distinguishable risk score, NtAI score, HRD-LOH, LST, and HRD scores. The low-score group showed higher sensitivity to Cisplatin and Talazoparib. The risk score of adrenocortical carcinoma (ACC), stomach adenocarcinoma (STAD), uterine corpus endometrial carcinoma (UCEC), kidney renal clear cell carcinoma (KIRC), sarcoma (SARC), prostate adenocarcinoma (PRAD), breast invasive carcinoma (BRCA) was significantly positively correlated with HRD score. Conclusion: We developed an 11 HRD scores-related genes risk model and revealed the potential association between HRD status and GC prognosis, gene mutations, patients' sensitivity to therapeutic drugs.

Prognostic and predictive value of a pathomics signature in gastric cancer

The current tumour-node-metastasis (TNM) staging system alone cannot provide adequate information for prognosis and adjuvant chemotherapy benefits in patients with gastric cancer (GC). Pathomics, which is based on the development of digital pathology, is an emerging field that might improve clinical management. Herein, we propose a pathomics signature (PSGC) that is derived from multiple pathomics features of haematoxylin and eosin-stained slides. We find that the PSGC is an independent predictor of prognosis. A nomogram incorporating the PSGC and TNM staging system shows significantly improved accuracy in predicting the prognosis compared to the TNM staging system alone. Moreover, in stage II and III GC patients with a low PSGC (but not in those with a high PSGC), satisfactory chemotherapy benefits are observed. Therefore, the PSGC could serve as a prognostic predictor in patients with GC and might be a potential predictive indicator for decision-making regarding adjuvant chemotherapy.

Adénocarcinome œsogastrique – nouvelles cibles thérapeutiques

The median overall survival of metastatic esophagogastric adenocarcinoma is approximately twelve months. In fifteen years, major breakthrough have been the targeting of HER2 overexpression and more recently immunotherapy in patients with CPS≥5. Recent advances in molecular biology have identified some molecular alterations in esophageal adenocarcinoma, interesting to target. FGFR2 is overexpressed in one third of patients, and its targeting with a specific monoclonal antibody bemarituzumab showed a significant improvement in survival. Claudin 18.2 (CLDN 18.2) is overexpressed in at least a third of esophagogastric adenocarcinomas. The combination of zolbetuximab and chemotherapy provides a survival benefit, correlated with the intensity of CLDN 18.2 expression. The potential interest of targeting other pathways is under investigation in several trials with some encouraging preliminary data, and early trials in these indications, justifying considering large molecular screening in patients who might be candidate for early phase trial. Finally, with the recent advent of immunotherapy, one of the future challenges will be to optimize it through combination strategies with targeted therapies. The combination of anti-angiogenic and immunotherapy seems promising in gastric cancer.

Successes and failures of immunotherapy for gastric cancer

Many exploratory clinical studies have been conducted on immune checkpoint inhibitors (ICIs) as new therapeutic approaches for the first-line treatment of patients with advanced gastric cancer. Despite varying interpretations of the successes and failures of this clinical research, most analyses have focused on the results from the perspective of exploring the superiority of immunotherapy. Consequently, the role of chemotherapy as an important partner of immunotherapy in first-line combination therapy regimens for gastric cancer has attracted less attention. Here, we explore and analyze first-line immunotherapies for gastric cancer from the perspective of chemotherapy, to understand reasons for the failure of studies and to indicate directions for future clinical research.

Molecular bases of morphologically diffused tumors across multiple cancer types

Gastric cancer has two distinct subtypes: the diffuse (DGC) and the intestinal (IGC) subtypes. Morphologically, the former each consists of numerous scattered tiny tumors while the latter each has one or a few solid biomasses. The former tends to be more aggressive and takes place in younger patients than the latter. While these have long been documented, little is known about the underlying causes. Our hypothesis is that the level of sialic acid (SA) accumulation on the cancer cell surfaces is a key reason for the observed differences. Our transcriptomic data-based analyses provide evidence that (i) DGCs tend to deploy more SAs on cancer cell surfaces than IGCs; (ii) this gives rise to considerably stronger cell-cell electrostatic repulsion in DGCs due to the negative charge that each SA carries; and (iii) such repulsion drives stronger cell protrusion and metastasis. Similar observations as well as our transcriptomic data-based predictions hold for multiple other cancer types, namely breast, lung, prostate plus liver and thyroid cancers, each known to have diffuse-like vs. non-diffused subtypes as well as more aggressive behaviors like DGCs vs. IGCs. Hence, we speculate that the discovery presented here applies not only to gastric cancer but multiple and even potentially all cancer types having diffuse-like and non-diffused subtypes.

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

Gastric cancer is a major source of global cancer mortality with limited treatment options and poor patient survival. As our molecular understanding of gastric cancer improves, we are now beginning to recognize that these cancers are a heterogeneous group of diseases with incredibly unique pathogeneses and active oncogenic pathways. It is this molecular diversity and oftentimes lack of common oncogenic driver mutations that bestow the poor treatment responses that oncologists often face when treating gastric cancer. In this review, we will examine the treatments for gastric cancer including up-to-date molecularly targeted therapies and immunotherapies. We will then review the molecular subtypes of gastric cancer to highlight the diversity seen in this disease. We will then shift our discussion to basic science and gastric cancer mouse models as tools to study gastric cancer molecular heterogeneity. Furthermore, we will elaborate on a molecular process termed paligenosis and the cyclical hit model as key events during gastric cancer initiation that impart nondividing mature differentiated cells the ability to re-enter the cell cycle and accumulate disparate genomic mutations during years of chronic inflammation and injury. As our basic science understanding of gastric cancer advances, so too must our translational and clinical efforts. We will end with a discussion regarding single-cell molecular analyses and cancer organoid technologies as future translational avenues to advance our understanding of gastric cancer heterogeneity and to design precision-based gastric cancer treatments. Elucidation of interpatient and intratumor heterogeneity is the only way to advance future cancer prevention, diagnoses and treatment.

Low FNDC5/Irisin expression is associated with aggressive phenotypes in gastric cancer

Background: FNDC5 belongs to the family of proteins called fibronectin type III domain-containing which carry out a variety of functions. The expression of FNDC5 is associated with the occurrence and development of tumors. However, the role of FNDC5 in gastric cancer remains relatively unknown. Methods: In the research, the expression of FNDC5 and its value for the prognosis of gastric cancer patients were observed with the TCGA database and GEO datasets of gastric cancer patients. The role of FNDC5 in the regulation of gastric cancer cells proliferation, invasion, and migration was determined. WGCNA and Enrichment analysis was performed on genes co-expressed with FNDC5 to identify potential FNDC5-related signaling pathways. Meanwhile, the LASSO Cox regression analysis based on FNDC5-related genes develops a risk score to predict the survival of gastric cancer patients. Results: The expression of FNDC5 was decreased in gastric cancer tissues compared to normal gastric tissues. However, survival analysis indicated that lower FNDC5 mRNA levels were associated with better overall survival and disease-free survival in gastric cancer patients. Meanwhile, a significant negative correlation was found between FNDC5 and the abundance of CD4+ memory T cells in gastric cancer. In vitro overexpression of FNDC5 inhibits the migration and invasion of gastric cancer cells, without affecting proliferation. Finally, A two-gene risk score module based on FNDC5 co-expressed gene was built to predict the overall clinical ending of patients. Conclusion: FNDC5 is low expressed in gastric cancer and low FNDC5 predicts a better prognosis. The better prognosis of low FNDC5 expression may be attributed to the increased number of CD4+ memory activated T-cell infiltration in tumors, but the exact mechanism of the effect needs to be further explored. Overexpressing FNDC5 inhibits the invasion and migration of gastric cancer but does not affect proliferation. At last, we constructed a clinical risk score model composed of two FNDC5-related genes, and this model may help lay the foundation for further in-depth research on the individualized treatment of gastric cancer patients.

High Expression of COL10A1 Is an Independent Predictive Poor Prognostic Biomarker and Associated with Immune Infiltration in Advanced Gastric Cancer Microenvironment

Medical technology has become more and more sophisticated recently, which, however, fails to contribute to a better prognosis for patients suffering advanced gastric cancer (GC). Hence, new biomarkers specific to GC diagnosis and prognosis shall be identified urgently. This study screened differentially expressed genes (DEGs) between 375 GC samples and 32 paracancer tissue samples from TCGA datasets. The expression of Collagen type X alpha 1 (COL10A1) in GC was analyzed. The chi-square test assisted in analyzing the relevance of COL10A1 to the clinicopathologic characteristics. The Kaplan-Meier method helped to assess the survival curves and log-rank tests assisted in the examination of the differences. The Cox proportional hazard regression model served for analyzing the risk factors for GC. Then, we developed a nomogram that contained the COL10A1 expression and clinical information. Finally, how COL10A1 expression was associated with the immune infiltration was also evaluated. In this study, 7179 upregulated and 3771 downregulated genes were identified. Among them, COL10A1 expression was distinctly increased in GC specimens compared with nontumor specimens. High COL10A1 expression exhibited an obvious relation to tumor T and pathologic stage. ROC assays confirmed the diagnostic value of COL10A1 expression in screening GC samples from normal samples. Survival data displayed that patients with high COL10A1 expression exhibited a shorter OS and DSS than those with low COL10A1 expression. We obtained a predictive nomogram, which could better predict the COL10A1 expression by virtue of discrimination and calibration. The prognostic value of COL10A1 expression was further confirmed in GSE84426 datasets. Immune assays revealed that COL10A1 expression was associated with tumor-filtrating immune cells, like CD8 T cells, cytotoxic cells, DC, eosinophils, iDC, macrophages, mast cells, NK CD56dim cells, NK cells, pDC, T helper cells, Tem, Th1 cells, Th17 cells, and Treg. Overall, we firstly proved that COL10A1 may be a novel and valuable prognostic and diagnostic factor for GC patients. In addition, COL10A1 has potential to be an immune indicator in GC.

Signaling pathways and therapeutic interventions in gastric cancer

Gastric cancer (GC) ranks fifth in global cancer diagnosis and fourth in cancer-related death. Despite tremendous progress in diagnosis and therapeutic strategies and significant improvements in patient survival, the low malignancy stage is relatively asymptomatic and many GC cases are diagnosed at advanced stages, which leads to unsatisfactory prognosis and high recurrence rates. With the recent advances in genome analysis, biomarkers have been identified that have clinical importance for GC diagnosis, treatment, and prognosis. Modern molecular classifications have uncovered the vital roles that signaling pathways, including EGFR/HER2, p53, PI3K, immune checkpoint pathways, and cell adhesion signaling molecules, play in GC tumorigenesis, progression, metastasis, and therapeutic responsiveness. These biomarkers and molecular classifications open the way for more precise diagnoses and treatments for GC patients. Nevertheless, the relative significance, temporal activation, interaction with GC risk factors, and crosstalk between these signaling pathways in GC are not well understood. Here, we review the regulatory roles of signaling pathways in GC potential biomarkers, and therapeutic targets with an emphasis on recent discoveries. Current therapies, including signaling-based and immunotherapies exploited in the past decade, and the development of treatment for GC, particularly the challenges in developing precision medications, are discussed. These advances provide a direction for the integration of clinical, molecular, and genomic profiles to improve GC diagnosis and treatments.

Molecular Pathology of Gastric Cancer

Gastric cancer (GC) is one of the most common lethal malignant neoplasms worldwide, with limited treatment options for both locally advanced and/or metastatic conditions, resulting in a dismal prognosis. Although the widely used morphological classifications may be helpful for endoscopic or surgical treatment choices, they are still insufficient to guide precise and/or personalized therapy for individual patients. Recent advances in genomic technology and high-throughput analysis may improve the understanding of molecular pathways associated with GC pathogenesis and aid in the classification of GC at the molecular level. Advances in next-generation sequencing have enabled the identification of several genetic alterations through single experiments. Thus, understanding the driver alterations involved in gastric carcinogenesis has become increasingly important because it can aid in the discovery of potential biomarkers and therapeutic targets. In this article, we review the molecular classifications of GC, focusing on The Cancer Genome Atlas (TCGA) classification. We further describe the currently available biomarker-targeted therapies and potential biomarker-guided therapies. This review will help clinicians by providing an inclusive understanding of the molecular pathology of GC and may assist in selecting the best treatment approaches for patients with GC.

Integration of transcriptomics, proteomics, and metabolomics data to reveal HER2-associated metabolic heterogeneity in gastric cancer with response to immunotherapy and neoadjuvant chemotherapy

Background

Currently available prognostic tools and focused therapeutic methods result in unsatisfactory treatment of gastric cancer (GC). A deeper understanding of human epidermal growth factor receptor 2 (HER2)-coexpressed metabolic pathways may offer novel insights into tumour-intrinsic precision medicine.

Methods

The integrated multi-omics strategies (including transcriptomics, proteomics and metabolomics) were applied to develop a novel metabolic classifier for gastric cancer. We integrated TCGA-STAD cohort (375 GC samples and 56753 genes) and TCPA-STAD cohort (392 GC samples and 218 proteins), and rated them as transcriptomics and proteomics data, resepectively. 224 matched blood samples of GC patients and healthy individuals were collected to carry out untargeted metabolomics analysis.

Results

In this study, pan-cancer analysis highlighted the crucial role of ERBB2 in the immune microenvironment and metabolic remodelling. In addition, the metabolic landscape of GC indicated that alanine, aspartate and glutamate (AAG) metabolism was significantly associated with the prevalence and progression of GC. Weighted metabolite correlation network analysis revealed that glycolysis/gluconeogenesis (GG) and AAG metabolism served as HER2-coexpressed metabolic pathways. Consensus clustering was used to stratify patients with GC into four subtypes with different metabolic characteristics (i.e. quiescent, GG, AAG and mixed subtypes). The GG subtype was characterised by a lower level of ERBB2 expression, a higher proportion of the inflammatory phenotype and the worst prognosis. However, contradictory features were found in the mixed subtype with the best prognosis. The GG and mixed subtypes were found to be highly sensitive to chemotherapy, whereas the quiescent and AAG subtypes were more likely to benefit from immunotherapy.

Conclusions

Transcriptomic and proteomic analyses highlighted the close association of HER-2 level with the immune status and metabolic features of patients with GC. Metabolomics analysis highlighted the co-expressed relationship between alanine, aspartate and glutamate and glycolysis/gluconeogenesis metabolisms and HER2 level in GC. The novel integrated multi-omics strategy used in this study may facilitate the development of a more tailored approach to GC therapy.

Consensus Molecular Subtypes Efficiently Classify Gastric Adenocarcinomas and Predict the Response to Anti-PD-1 Immunotherapy

Background: Gastric adenocarcinoma (GAC) is highly heterogeneous and closely related to colorectal cancer (CRC) both molecularly and functionally. GAC is currently subtyped using a system developed by TCGA. However, with the emergence of immunotherapies, this system has failed to identify suitable treatment candidates. Methods: Consensus molecular subtypes (CMSs) developed for CRC were used for molecular subtyping in GAC based on public expression cohorts, including TCGA, ACRG, and a cohort of GAC patients treated with the programmed cell death 1 (PD-1) inhibitor pembrolizumab. All aspects of each subtype, including clinical outcome, molecular characteristics, oncogenic pathway activity, and the response to immunotherapy, were fully explored. Results: CMS classification was efficiently applied to GAC. CMS4, characterized by EMT activation, stromal invasion, angiogenesis, and the worst clinical outcomes (median OS 24.2 months), was the predominant subtype (38.8%~44.3%) and an independent prognostic indicator that outperformed classical TCGA subtyping. CMS1 (20.9%~21.5%) displayed hypermutation, low SCNV, immune activation, and best clinical outcomes (median OS > 120 months). CMS3 (17.95%~25.7%) was characterized by overactive metabolism, KRAS mutation, and intermediate outcomes (median OS 85.6 months). CMS2 (14.6%~16.3%) was enriched for WNT and MYC activation, differentiated epithelial characteristics, APC mutation, lack of ARID1A, and intermediate outcomes (median OS 48.7 months). Notably, CMS1 was strongly correlated with immunotherapy biomarkers and favorable for the anti-PD-1 drug pembrolizumab, whereas CMS4 was poorly responsive but became more sensitive after EMT-based stratification. Conclusions: Our study reveals the practical utility of CMS classification for GAC to improve clinical outcomes and identify candidates who will respond to immunotherapy.

Engineered exosome-mediated delivery of circDIDO1 inhibits gastric cancer progression via regulation of MiR-1307-3p/SOCS2 Axis

Background

Our previous study has identified a novel circRNA (circDIDO1) that is down-regulated in gastric cancer (GC) and significantly inhibits GC progression. The purpose of this study is to identify the molecular mechanism for circDIDO1 and to evaluate the therapeutic effect of circDIDO1 in GC.

Methods

By combining bioinformatic analysis with RNA sequencing data, we predicted the potential target of circDIDO1 and further validated the regulatory mechanisms for its tumor suppressor function in GC. RIP assay, luciferase reporter assay and in vitro cell function assays were performed to analyze circDIDO1-regulated downstream target genes. For the therapeutic study, circDIDO1-loaded, RGD-modified exosomes (RGD-Exo-circDIDO1) were constructed and its anti-tumor efficacy and biological safety were evaluated in vitro and in vivo.

Results

CircDIDO1 inhibited GC progression by regulating the expression of the signal transducer inhibitor SOSC2 through sponging miR-1307-3p. Overexpression of circDIDO1 or SOSC2 antagonized the oncogenic role of miR-1307-3p. RGD-Exo-circDIDO1 could efficiently deliver circDIDO1 to increase SOCS2 expression in GC cells. Compared with PBS and RGD-Exo-vector treatment, RGD-Exo-circDIDO1 treatment significantly inhibited the proliferation, migration and invasion of GC cells while promoted cell apoptosis. The therapeutic efficacy of RGD-Exo-circDIDO1 was further confirmed in a mouse xenograft tumor model. In addition, major tissues including the heart, liver, spleen, lungs and kidneys showed no obvious histopathological abnormalities or lesions in the RGD-Exo-circDIDO1 treated group.

Conclusion

Our findings revealed that circDIDO1 suppressed the progression of GC via modulating the miR-1307-3p/SOSC2 axis. Systemic administration of RGD modified, circDIDO1 loaded exosomes repressed the tumorigenicity and aggressiveness of GC both in vitro and in vivo, suggesting that RGD-Exo-circDIDO1 could be used as a feasible nanomedicine for GC therapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03527-z.

Clinical Study on the Evaluation of the Condition of Patients with Gastric Tumors and the Choice of Surgical Treatment by Gastric Ultrasonic Filling Method

OBJECTIVE

To explore the clinical value of the gastric ultrasonic filling method in evaluating the condition of patients with gastric tumors and guiding the selection of treatment methods, provide data support for clinical gastric filling ultrasonography in the evaluation of gastric cancer patients, and provide the basis for the choice of surgical treatment. Methods. This study retrospectively analyzed 50 patients with gastric cancer treated in our hospital from April 2017 to January 2022. All 50 patients were examined by the gastric ultrasound filling method. The TNM staging results of gastric cancer were analyzed with the results of gastroscopic biopsy or postoperative pathological examination as the diagnostic gold standard. Results. The ultrasonic detection rate of 50 patients with gastric cancer was 94.00% (47/50). Among them, 3 cases missed diagnosis were of early intramucosal carcinoma, which were only diagnosed as erosive gastritis. 1 case was located in the gastric body, and the other 2 cases were located in the gastric antrum. Ultrasound assessment of gastric mucosal thickness in T1-T2 stage was 9.8 mm, which was significantly lower than that in T3-T4 stage, which was 17.0 mm (p < 0.05). The diagnostic accuracy of the gastric ultrasound filling method in the diagnosis of T1, T2, T3, and T4 was 41.67%, 57.14%, 96.00%, and 83.33%, respectively. The total diagnostic accuracy of T-stage was 76.00% (38/50). The total judgment rate of too shallow and too deep was 10.00% and 14.00%, respectively. The diagnostic accuracy of the gastric ultrasound filling method was 88.89%, 81.81%, 70.00%, and 82.00%, respectively. The diagnostic accuracy of the gastric ultrasound filling method in the diagnosis of M0 and M1 stages was 100.00%, and the total diagnostic accuracy of the M-stage was 100.00%. The ROC curve drawn by GFUS in the diagnosis of T-stage of gastric cancer had three components: the specificity was the horizontal axis, the sensitivity was the vertical axis, and the area under the curve was 0.978. The difference was statistically significant (p < 0.05). Conclusion. Before the operation of patients with gastric cancer, using the gastric ultrasonic filling method and ultrasonic examination method to diagnose them can timely clarify the clinical stage of patients, so that clinicians can choose the most appropriate operation method according to their clinical stage, which is worthy of popularization and application in clinic.

Characterization of Immune-Related Molecular Subtypes and a Prognostic Signature Correlating With the Response to Immunotherapy in Patients With Gastric Cancer

Gastric cancer (GC) is a disease characterized by high molecular and phenotypic heterogeneity and represents a leading cause of cancer-related death worldwide. The tumor immune microenvironment (TIME) affects the response to immunotherapy and the prognosis of patients with GC. Explorations of the TIME in GC and characterization of molecular subtypes might enhance personalized treatment and facilitate clinical decision-making. In this study, two molecular subtypes were defined through unsupervised consensus clustering based on immune-related dysregulated genes. Then, patients with different molecular subtypes of GC were shown to have distinct differences in sensitivity to immune checkpoint blockers (ICBs). The immune-related prognostic signature was established utilizing least absolute shrinkage and selection operator (LASSO)-Cox regression analysis. Three independent external cohorts and the IMvigor210 cohort were introduced to validate the robustness of IPRS. scRNA-seq data of GC samples were used to decipher the underlying mechanisms of how IPRS contributes to the TIME. GC biospecimens were collected for RT-qPCR to further validate our findings. In summary, we characterized the abnormal TIME of GC and constructed a reliable immune-related prognostic signature correlating with the response to immunotherapy. This study may provide new strategies for developing individualized treatments for patients with GC.

CD40×HER2 bispecific antibody overcomes the CCL2-induced trastuzumab resistance in HER2-positive gastric cancer

Background

There was much hard work to study the trastuzumab resistance in HER2-positive gastric cancer (GC), but the information which would reveal this abstruse mechanism is little. In this study, we aimed to investigate the roles of tumor cell-derived CCL2 on trastuzumab resistance and overcome the resistance by treatment with the anti-CD40-scFv-linked anti-HER2 (CD40 ×HER2) bispecific antibody (bsAb).

Methods

We measured the levels of CCL2 expression in HER2-positive GC tissues, and revealed biological functions of tumor cell-derived CCL2 on tumor-associated macrophages (TAMs) and the trastuzumab resistance. Then, we developed CD40 ×HER2 bsAb, and examined the targeting roles on HER2 and CD40, to overcome the trastuzumab resistance without systemic toxicity.

Results

We found the level of CCL2 expression in HER2-postive GC was correlated with infiltration of TAMs, polarization status of infiltrated TAMs, trastuzumab resistance and survival outcomes of GC patients. On exposure to CCL2, TAMs decreased the M1-like phenotype, thereby eliciting the trastuzumab resistance. CCL2 activated the transcription of ZC3H12A, which increased K63-linked deubiquitination and K48-linked auto-ubiquitination of TRAF6/3 to inactivate NF-κB signaling in TAMs. CD40 ×HER2 bsAb, which targeted the CD40 to restore the ubiquitination level of TRAF6/3, increased the M1-like phenotypic transformation of TAMs, and overcame trastuzumab resistance without immune-related adversary effects (irAEs).

Conclusions

We revealed a novel mechanism of trastuzumab resistance in HER2-positive GC via the CCL2-ZC3H12A-TRAF6/3 signaling axis, and presented a CD40 ×HER2 bsAb which showed great antitumor efficacy with few irAEs.

A Radiomics Nomogram Integrated With Clinic-Radiological Features for Preoperative Prediction of DNA Mismatch Repair Deficiency in Gastric Adenocarcinoma

Purpose

To develop and validate a radiomics nomogram integrated with clinic-radiological features for preoperative prediction of DNA mismatch repair deficiency (dMMR) in gastric adenocarcinoma.

Materials and Methods

From March 2014 to August 2020, 161 patients with pathologically confirmed gastric adenocarcinoma were included from two centers (center 1 as the training and internal testing sets, n = 101; center 2 as the external testing sets, n = 60). All patients underwent preoperative contrast-enhanced computerized tomography (CT) examination. Radiomics features were extracted from portal-venous phase CT images. Max-relevance and min-redundancy (mRMR) and least absolute shrinkage and selection operator (LASSO) methods were used to select features, and then radiomics signature was constructed using logistic regression analysis. A radiomics nomogram was built incorporating the radiomics signature and independent clinical predictors. The model performance was assessed using receiver operating characteristic (ROC) curve analysis, calibration curve, and decision curve analysis (DCA).

Results

The radiomics signature, which was constructed using two selected features, was significantly associated with dMMR gastric adenocarcinoma in the training and internal testing sets (P < 0.05). The radiomics signature model showed a moderate discrimination ability with an area under the ROC curve (AUC) of 0.81 in the training set, which was confirmed with an AUC of 0.78 in the internal testing set. The radiomics nomogram consisting of the radiomics signature and clinical factors (age, sex, and location) showed excellent discrimination in the training, internal testing, and external testing sets with AUCs of 0.93, 0.82, and 0.83, respectively. Further, calibration curves and DCA analysis demonstrated good fit and clinical utility of the radiomics nomogram.

Conclusions

The radiomics nomogram combining radiomics signature and clinical characteristics (age, sex, and location) may be used to individually predict dMMR of gastric adenocarcinoma.

Clinicopathological differences, risk factors and prognostic scores for western patients with intestinal and diffuse-type gastric cancer

BACKGROUND

In the molecular era, the Laurén system is still a cost-effective and widely implemented classification for gastric cancer (GC) and it has been recently associated with clinical, histological and molecular features of these tumors. Despite recent advances in the understanding of the molecular biology of GC, there is a need to develop new prognostic tools for patient stratification in clinical practice. Thus, the identification of easily available prognostic factors in patients with intestinal and diffuse-type tumors can significantly improve risk assessment and patient stratification in GC.

AIM

To identify clinicopathological differences, risk factors, and to develop cost-effective prognostic scores for patients with intestinal and diffuse-type GC.

METHODS

Retrospective study of all patients undergoing surgery for GC at a tertiary referral center from 2001 to 2019. 286 cases met inclusion criteria (intestinal: 190, diffuse: 96). Clinical data and gross findings were collected. All specimens were reviewed by two independent pathologists and a detailed protocol for histologic evaluation was followed. Five tissue microarrays (TMAs) were constructed and sections of the TMA block were immunostained for HERCEPTEST, MSH2, MSH6, MLH1 and PMS2. Statistical analyses were performed and prognostic scores were developed based on hazard ratios.

RESULTS

Intestinal and diffuse-type GC showed different epidemiological, clinicopathological and prognostic features. Diffuse tumors were significantly associated with younger age, less symptomatology, flat morphology, deeper invasion, perineural infiltration, advanced stage at diagnosis, administration of adjuvant therapy and poorer prognosis. Intestinal lesions were fungoid or polypoid, showed necrosis, desmoplasia, microsatellite instability and HERCEPTEST positivity and were diagnosed at earlier stages. Tumor depth, desmoplasia, macroscopic type and lymph node involvement were independently related to the Laurén subtype. Furthermore, intestinal and diffuse GC were associated with different risk factors for progression and death. Vascular invasion, perineural infiltration and growth pattern were important prognostic factors in intestinal-type GC. On the contrary, tumor size and necrosis were significant prognosticators in diffuse-type GC. Our recurrence and cancer-specific death scores for patients with intestinal and diffuse-type GC showed an excellent patient stratification into three (diffuse GC) or four (intestinal) prognostic groups.

CONCLUSION

Our findings support that Laurén subtypes represent different clinicopathological and biological entities. The development of specific prognostic scores is a useful and cost-effective strategy to improve risk assessment in GC.