Prognostic significance of tumor immune microenvironment and immunotherapy: Novel insights and future perspectives in gastric cancer

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

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

Comprehensive Analysis on Prognostic Signature Based on T Cell-Mediated Tumor Killing Related Genes in Gastric Cancer

Although immunotherapy is a valuable treatment for gastric cancer (GC), identifying the patients who would benefit most from this approach presents a challenge. In this study, GC patients were divided into two subtypes by consensus clustering according to T cell-mediated tumor killing related genes (TTKRGs), and there were significant differences in tumor-infiltrating immune cells, signaling pathways, and gene expression of immunomodulators and inhibitory immune checkpoints between the two subtypes. Then, we developed an individualized signature based on TTKRGs, and its clinical and predictive value in GC patients for chemotherapeutic and immunotherapeutic responses was assessed. We confirmed the expression levels of signature genes in GC tumor tissue using quantitative real-time polymerase chain reaction (qRT-PCR). Additionally, to improve the accuracy of GC prognosis predictions, we established a nomogram. We further identified some compounds as sensitive drugs targeting GC risk groups. The signature showed significant predictive ability across RNA-seq, microarray, and qRT-PCR cohorts, which could assist in predicting survival, immunotherapeutic and chemotherapeutic outcomes in GC patients.

Prognosis stratification and response to treatment in breast cancer based on one-carbon metabolism-related signature

Introduction

Breast cancer (BC) is the most common malignant tumor in the female population. Despite staging and treatment consensus guidelines, significant heterogeneity exists in BC patients' prognosis and treatment efficacy. Alterations in one-carbon (1C) metabolism are critical for tumor growth, but the value of the role of 1C metabolism in BC has not been fully investigated.

Methods

To investigate the prognostic value of 1C metabolism-related genes in BC, 72 1C metabolism-related genes from GSE20685 dataset were used to construct a risk-score model via univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) regression algorithm, which was validated on three external datasets. Based on the risk score, all BC patients were categorized into high-risk and low-risk groups. The predictive ability of the model in the four datasets was verified by plotting Kaplan-Meier curve and receiver operating characteristic (ROC) curve. The candidate genes were then analyzed in relation to gene mutations, gene enrichment pathways, immune infiltration, immunotherapy, and drug sensitivity.

Results

We identified a 7-gene 1C metabolism-related signature for prognosis and structured a prognostic model. ROC analysis demonstrated that the model accurately predicted the 2-, 3-, and 5-year overall survival rate of BC patients in the four cohorts. Kaplan-Meier analysis revealed that survival time of high-risk patients was markedly shorter than that of low-risk patients (p < 0.05). Meanwhile, high-risk patients had a higher tumor mutational burden (TMB), enrichment of tumor-associated pathways such as the IL-17 signaling pathway, lower levels of T follicular helper (Tfh) and B cells naive infiltration, and poorer response to immunotherapy. Furthermore, a strong correlation was found between MAT2B and CHKB and immune checkpoints.

Discussion

These findings offer new insights into the effect of 1C metabolism in the onset, progression, and therapy of BC and can be used to assess BC patients' prognosis, study immune infiltration, and develop potentially more effective clinical treatment options.

Role of immune related genes in predicting prognosis and immune response in patients with hepatocellular carcinoma

Immunotherapy has developed rapidly in recent years. This study aimed to establish a prognostic signature for immune-related genes (IRGs) and explore related potential immunotherapies. The RNA-seq transcriptome profiles and clinicopathological information of patients were obtained from The Cancer Genome Atlas. Differentially expressed IRGs in tumors and normal tissues were screened and a risk score signature was constructed to predict the prognosis in patients with hepatocellular carcinoma (HCC). Receiver operating characteristic curves, survival analyses, and correlation analyses were used to explore the clinical application of this model. We further analyzed the differences in clinical characteristics, immune infiltration, somatic mutations, and treatment sensitivity between the high- and low-risk populations characterized by the prognostic models. The immune cell infiltration score and immune-related pathway activity were calculated using the single sample gene set enrichment analysis (ssGSEA) set enrichment analysis. Gene ontology (GO), Kyoto encyclopedia of genes and genomes, and GSEA were used to explore the underlying mechanisms. We constructed a nine-IRG formula to predict the prognosis in HCC patients. The higher the risk score, the higher the malignancy of the tumor and the worse the prognosis. There were significant differences in immune related processes between the high- and low-risk groups. TP53 and CTNNB1 mutations were significantly different between different risk groups. The expression of model gene was closely related to the sensitivity of tumor cells to chemotherapeutic drugs. This risk score model, which is helpful for the individualized treatment of patients with different risk factors, could be a reliable prognostic tool for HCC patients.

The value of CDC42 effector protein 2 as a novel prognostic biomarker in liver hepatocellular carcinoma: a comprehensive data analysis

BACKGROUND

The prognostic significance of CDC42 effector protein 2 (CDC42EP2) and its association with tumor-infiltrating immune cells (TIICs) have not been explored in liver hepatocellular carcinoma (LIHC). This study aims to assess the potential prognostic value of CDC42EP2 by conducting a comprehensive analysis of online databases pertaining to LIHC.

METHODS

We evaluated the potential of CDC42EP2 as a prognostic biomarker by utilizing online databases such as TIMER, GEPIA2, KM, OSlihc, HPA, and LinkedOmics.

RESULTS

In LIHC, we observed that the mRNA and protein expression of CDC42EP2 were upregulated compared to normal tissues. Upregulated CDC42EP2 expression was associated with a worse prognosis based on the clinicopathological characteristics of patients with LIHC. Furthermore, CDC42EP2 was positively associated with TIICs. In the co-expression and functional enrichment analyses of CDC42EP2, 11,416 genes showed positive associations with CDC42EP2 while 8,008 genes showed negative associations. CDC42EP2-related co-expression genes were involved in protein localization to the endoplasmic reticulum, translational initiation, and RNA catabolic processes in gene set enrichment analysis-Gene Ontology (GSEAGO), and regulated the ribosome, spliceosome, and primary immune deficiency in the GSEAKyoto Encyclopedia of Genes and Genomes (KEGG) pathway. In a survival map, 23 and 17 genes that exhibited positive associations with CDC42EP2 showed a significant hazard ratio (HR) for overall survival and disease-free survival, respectively.

CONCLUSION

Our findings demonstrated that CDC42EP2 is a novel prognostic biomarker and a potential tumor immune therapeutic target in patients with LIHC.

Construction of a hypoxia-immune-related prognostic panel based on integrated single-cell and bulk RNA sequencing analyses in gastric cancer

Introduction

Gastric cancer (GC) is the fifth most common tumor, contributing to the third-highest number of cancer-related deaths. Hypoxia is a major feature of the tumor microenvironment. This study aimed to explore the influence of hypoxia in GC and establish a hypoxia-related prognostic panel.

Methods

The GC scRNA-seq data and bulk RNA-seq data were downloaded from the GEO and TCGA databases, respectively. AddModuleScore() and AUCell() were used to calculate module scores and fractions of enrichment for hypoxia-related gene expression in single cells. Least absolute shrinkage and selection operator cox (LASSO-COX) regression analysis was utilized to build a prognostic panel, and hub RNAs were validated by qPCR. The CIBERSORT algorithm was adopted to evaluate immune infiltration. The finding of immune infiltration was validated by a dual immunohistochemistry staining. The TIDE score, TIS score and ESTIMATE were used to evaluate the immunotherapy predictive efficacy.

Results

Hypoxia-related scores were the highest in fibroblasts, and 166 differentially expressed genes were identified. Five hypoxia-related genes were incorporated into the hypoxia-related prognostic panel. 4 hypoxia-related genes (including POSTN, BMP4, MXRA5 and LBH) were significantly upregulated in clinical GC samples compared with the normal group, while APOD expression decreased in GC samples. Similar results were found between cancer-associated fibroblasts (CAFs) and normal fibroblasts (NFs). A high hypoxia score was associated with advanced grade, TNM stage, N stage, and poorer prognosis. Decreased antitumor immune cells and increased cancer-promoting immune cells were found in patients with high hypoxia scores. Dual immunohistochemistry staining showed high expression of CD8 and ACTA2 in gastric cancer tissue. In addition, the high hypoxia score group possessed higher TIDE scores, indicating poor immunotherapy benefit. A high hypoxia score was also firmly related to sensitivity to chemotherapeutic drugs.

Discussion

This hypoxia-related prognostic panel may be effective in predicting the clinical prognosis, immune infiltrations, immunotherapy, and chemotherapy in GC.

Prediction of immune subtypes and overall survival in lung squamous cell carcinoma

OBJECTIVE

Lung squamous cell carcinoma (LUSC), one of the most common subtypes of lung cancer, is a leading cause of cancer-caused deaths in the world. It has been well demonstrated that a deep understanding of the tumor environment in cancer would be helpful to predict the prognosis of patients. This study aimed to evaluate the tumor environment in LUSC, and to construct an efficient prognosis model involved in specific subtypes.

METHODS

Four expression files were downloaded from the Gene Expression Omnibus (GEO) database. Three datasets (GSE19188, GSE2088, GSE6044) were considered as the testing group and the other dataset (GSE11969) was used as the validation group. By performing LUSC immune subtype consensus clustering (CC), LUSC patients were separated into two immune subtypes comprising subtype 1 (S1) and subtype 2 (S2). Weighted gene co-expression network (WGCNA) and least absolute shrinkage and selection operator (LASSO) were performed to identify and narrow down the key genes among subtype 1 related genes that were closely related to the overall survival (OS) of LUSC patients. Using immune subtype related genes, a prognostic model was also constructed to predict the OS of LUSC patients.

RESULTS

It showed that LUSC patients in the S1 immune subtype exhibited a better OS than in the S2 immune subtype. WGCNA and LASSO analyses screened out important immune subtype related genes in specific modules that were closely associated with LUSC prognosis, followed by construction of the prognostic model. Both the testing datasets and validation dataset confirmed that the prognostic model could be efficiently used to predict the OS of LUSC patients in subtype 1.

CONCLUSION

We explored the tumor environment in LUSC and established a risk prognostic model that might have the potential to be applied in clinical practice.

Glutamate-cysteine ligase catalytic and its modifier function as novel immunotargets in gastric adenocarcinoma

OBJECTIVES

To determine the expression and function of glutamate-cysteine ligase catalytic (GCLC) and glutamate-cysteine ligase catalytic modifier (GCLM) in gastric adenocarcinoma.

METHODS

Bioinformatics was used to analyze the expression of GCLC and GCLM. We download and analyzed the expression of gastric adenocarcinoma patients from TCGA database. Moreover, the method of immunochemistry was used to verify the expression of GCLC and GCLM in gastric adenocarcinoma.

RESULTS

At first, the expression of GCLC and GCLM in gastric adenocarcinoma tissues were both significantly higher compared with normal tissues analyzed via TCGA database. Then, gastric adenocarcinoma tissues were collected and performed with immunochemistry. The gastric adenocarcinoma with positive staining for GCLC and GCLM was 77% and 80%, respectively, which was significantly higher compared with adjacent normal tissues (9% and 11%, respectively).

CONCLUSIONS

The disordered expression of GCLC and GCLM in gastric adenocarcinoma suggested that these factors may induce tumorigenesis and may be a novel target for diagnosis and treatment of gastric adenocarcinoma.

CDK5RAP3 acts as a tumour suppressor in gastric cancer through the infiltration and polarization of tumour-associated macrophages

We have demonstrated that CDK5RAP3 exerts a tumour suppressor effect in gastric cancer, but its role in regulating tumour-associated macrophages (TAMs) has not yet been reported. Here, we show that CDK5RAP3 is related to the infiltration and polarization of macrophages. It inhibits the polarization of TAMs to M2 macrophages and promotes the polarization of the M1 phenotype. CDK5RAP3 reduces the recruitment of circulating monocytes to infiltrate tumour tissue by inhibiting the CCL2/CCR2 axis in gastric cancer. Blocking CCR2 reduces the growth of xenograft tumours and the infiltration of monocytes. CDK5RAP3 inhibits the nuclear transcription of NF-κB, thereby reducing the secretion of the cytokines IL4 and IL10 and blocking the polarization of M2 macrophages. In addition, the absence of CDK5RAP3 in gastric cancer cells allows macrophages to secrete more MMP2 to promote the epithelial-mesenchymal transition (EMT) process of gastric cancer cells, thereby enhancing the invasion and migration ability. Our results imply that CDK5RAP3 may be involved in the regulation of immune activity in the tumour microenvironment and is expected to become a potential immunotherapy target for gastric cancer.

[Prognostic Value of the Expression of Myeloid Leukemia Factor 1-Interacting Protein in Gastric Cancer and Its Regulatory Role in Tumor Progression]

Objective

To investigate the prognostic value of the expression of myeloid leukemia factor 1-interacting protein (MLF1IP) in gastric cancer tissue and its regulatory role in tumor progression.

Methods

Gene Expression Omnibus (GEO) database was used to analyze the expression level of MLF1IP in tumor tissues of gastric cancer patients. Kaplan-Meier Plotter database was used to analyze the relationship between MLF1IP expression level and patient prognosis. We conducted a retrospective analysis of 108 gastric cancer patients who had undergone radical surgery at our hospital between January 2015 and December 2015. The expression of MLF1IP in gastric cancer tissue and adjacent tissues was examined. We analyzed the relationship between MLF1IP and the clinicopathological parameters of gastric cancer patients and its impact on the long-term prognosis of gastric cancer patients. Univariate and multivariate regression analyses were done to identify the risk factors affecting the long-term prognosis of gastric cancer patients. The assessment value of MLF1IP for long-term prognosis of gastric cancer was analyzed with ROC curve. The effects of MLF1IP on the proliferation, migration, and invasion of gastric cancer cells were analyzed in vitro with gastric cancer cell line (MGC803). A xenograft tumor model was established with nude mice to analyze in vivo the effect of MLF1IP on tumor growth.

Results

The results of the gastric cancer cohort GSE29272 of GEO database showed that the expression level of MLF1IP in gastric cancer tissues was significantly higher than that in normal tissues ( P<0.05). Analysis with Kaplan-Meier Plotter database indicated that high MLF1IP expression was correlated with poor prognosis in gastric cancer patients. Immunohistochemical analysis showed that the expression level of MLF1IP in gastric cancer tissues was higher than that in adjacent tissues ( P<0.05). Correlation analysis showed that the MLF1IP level in gastric cancer tissue was positively correlated with Ki67 ( r=0.609, P<0.01), peripheral blood carcinoembryonic antigen (CEA) ( r=0.572, P<0.01) and carbohydrate antigen 19-9 (CA19-9) ( r=0.623, P<0.01). Kaplan-Meier (K-M) survival analysis showed that the 5-year survival rate of patients in the MLF1IP high expression group was significantly lower than that in the MLF1IP low expression group ( P<0.01). Cox regression analysis showed that independent risk factors for 5-year survival after radical gastrectomy for gastric cancer included the expression of MLF1IP ( HR=2.508, 95% CI: 1.259-4.999), CEA≥5 μg/L ( HR=2.171, 95% CI: 1.152-4.092), CA19-9≥37 kU/L ( HR=2.401, 95% CI: 1.094-5.269), and T3-T4 stages ( HR=2.779, 95% CI: 1.049-7.358) and N2-N3 stages ( HR=2.072, 95% CI: 1.100-3.904). ROC analysis showed that the sensitivity, specificity, and accuracy of MLF1IP (the cut-off value was 3.00 relative protein expression level) in assessing the 5-year survival rate after radical gastrectomy for gastric cancer was 75.00%, 76.92%, and 76.2%, respectively ( P<0.05). CCK-8, Transwell assay, and scratch assays showed that in vitro knocking down of MLF1 IP gene expression significantly inhibited the proliferation, migration and invasion of gastric cancer cells. Subcutaneous tumor xenograft experiment in nude mice showed that knocking down MLF1 IP gene significantly inhibited tumor growth.

Conclusion

Increased expression of MLF1IP in gastric cancer tissue, which may be involved in the malignant activities of proliferation, migration, and invasion of gastric cancer cells, has a certain predictive value for poor prognosis.

Diagnosis and prognosis prediction model for digestive system tumors based on immunologic gene sets

According to 2020 global cancer statistics, digestive system tumors (DST) are ranked first in both incidence and mortality. This study systematically investigated the immunologic gene set (IGS) to discover effective diagnostic and prognostic biomarkers. Gene set variation (GSVA) analysis was used to calculate enrichment scores for 4,872 IGSs in patients with digestive system tumors. Using the machine learning algorithm XGBoost to build a classifier that distinguishes between normal samples and cancer samples, it shows high specificity and sensitivity on both the validation set and the overall dataset (area under the receptor operating characteristic curve [AUC]: validation set = 0.993, overall dataset = 0.999). IGS-based digestive system tumor subtypes (IGTS) were constructed using a consistent clustering approach. A risk prediction model was developed using the Least Absolute Shrinkage and Selection Operator (LASSO) method. DST is divided into three subtypes: subtype 1 has the best prognosis, subtype 3 is the second, and subtype 2 is the worst. The prognosis model constructed using nine gene sets can effectively predict prognosis. Prognostic models were significantly associated with tumor mutational burden (TMB), tumor immune microenvironment (TIME), immune checkpoints, and somatic mutations. A composite nomogram was constructed based on the risk score and the patient's clinical information, with a well-fitted calibration curve (AUC = 0.762). We further confirmed the reliability and validity of the diagnostic and prognostic models using other cohorts from the Gene Expression Omnibus database. We identified diagnostic and prognostic models based on IGS that provide a strong basis for early diagnosis and effective treatment of digestive system tumors.

Synergistic Effects of the Combinational Use of Escitalopram Oxalate and 5-Fluorouracil on the Inhibition of Gastric Cancer SNU-1 Cells

Owing to its high recurrence rate, gastric cancer (GC) is the leading cause of tumor-related deaths worldwide. Besides surgical treatment, chemotherapy is the most commonly used treatment against GC. However, the adverse events associated with chemotherapy use limit its effectiveness in GC treatment. In this study, we investigated the effects of using combinations of low-dose 5-fluorouracil (5-FU; 0.001 and 0.01 mM) with different concentrations of escitalopram oxalate (0.01, 0.02, 0.06, and 0.2 mM) to evaluate whether the assessed combination would have synergistic effects on SNU-1 cell survival. 5-FU (0.01 mM) + escitalopram oxalate (0.02 mM) and 5-FU (0.01 mM) + escitalopram oxalate (0.06 mM) administered over 24 h showed synergistic effects on the inhibition of SNU-1 cell proliferation. Moreover, 5-FU (0.001 mM) + escitalopram oxalate (0.02 or 0.06 mM) and 5-FU (0.01 mM) + escitalopram oxalate (0.02, 0.06, or 0.2 mM) administered over 48 h showed synergistic effects on the inhibition of SNU-1 cell proliferation. Compared with controls, SNU-1 cells treated with 5-FU (0.01 mM) + escitalopram oxalate (0.02 mM) exhibited significantly increased levels of annexin V staining, reactive oxygen species, cleaved poly (ADP-ribose) polymerase, and caspase-3 proteins. Furthermore, 5-FU (12 mg/kg) + escitalopram oxalate (12.5 mg/kg) significantly attenuated xenograft SNU-1 cell proliferation in nude mice. Our study is the first to report the synergistic effects of the combinational use of low-dose 5-FU and escitalopram oxalate on inhibiting SNU-1 cell proliferation. These findings may be indicative of an alternative option for GC treatment.

A novel association between Bmi-1 protein expression and the SUVmax obtained by 18F-FDG PET/CT in patients with gastric adenocarcinoma

This study aimed to examine B-cell-specific Moloney murine leukemia virus integration site 1 (Bmi-1) in gastric adenocarcinoma (GAC) and its association with the maximal standard uptake value (SUVmax) of preoperative fluorine-18-fludeoosyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT). Clinicopathological data were retrospectively collected from 60 primary GAC patients. The Bmi-1 protein expression in GAC and adjacent noncancerous tissues was examined by immunohistochemistry and western blot analysis. Pearson's correlation analysis was conducted to assess the correlation between Bmi-1 expression and the SUVmax. The Bmi-1 protein levels were significantly greater in GAC versus noncancerous tissues, and higher Bmi-1 was significantly correlated with a lower degree of tumor differentiation, higher tumor stages, more lymph node metastasis, and depth of invasion. The SUVmax value was significantly correlated with the T stage, N stage, and clinical stage, but not with age, gender, tumor size, histological differentiation degree, or Lauren classification. Moreover, a significant positive correlation between Bmi-1 and SUVmax was observed in GAC tissues. In conclusion, our findings demonstrate a novel correlation between Bmi-1 and preoperative SUVmax in GAC patients who did not receive radiotherapy, chemotherapy, or targeted treatment before surgery, and both are positively correlated with unfavorable prognostic factors and a higher grade of malignancy.

The Senescence-Related Signature Predicts Prognosis and Characterization of Tumor Microenvironment Infiltration in Pancreatic Cancer

Background. Senescence is thought to be an imperative effect on the development of cancer. However, few studies pay an attention to the senescence-associated genes in pancreatic cancer (PC). The prognostic value of senescence-related genes (SRGs) and their involvement in tumor microenvironment (TME) in the PC remain obscure. The aim of this research was to investigate the prognostic role of senescence-associated genes and their affection in TME in PC. Methods. The transcriptome and clinical information of PC patients were obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Two SRG-mediated molecular clusters were comprehensively identified. In total, data from the 285 PC patients were randomly used to develop a senescence-associated gene signature in the training set and verified in the validation set. Immune microenvironment analysis pertained to senescence-related genes was performed. Results. A SRG_score including five senescence-associated genes was established to separate PC patients into two risk groups. High-risk patients had worse overall survival than low-risk patients. The result of the multivariate Cox regression analysis identified the risk score and stage as independent prognostic factors for PC patients. Receiver operating characteristic curve (ROC) analysis confirmed the credible predictive ability of the nomogram. The area under time-dependent ROC curve (AUC) reached 0.746 at 1 year, 0.781 at 3 years, and 0.868 at 5 years in the training set and 0.653 at 1 year, 0.755 at 3 years, and 0.785 at 5 years in the validation set. Moreover, the SRG_score was associated with TME, tumor mutation burden (TMB), and chemotherapeutic drug sensitivity. Conclusions. This study found that the novel SRG_score could be an independent prognostic target for PC patients. Senescence-associated genes had a vital impact on the immune microenvironment and the treatment of PC patients.

Prognostic value of the metabolic score obtained via [(18)F]FDG PET/CT and a new prognostic staging system for gastric cancer

We developed and validated a new staging system that includes metabolic information from pretreatment [¹⁸F]Fluorodeoxyglucose ([¹⁸F]FDG) positron emission tomography/computed tomography (PET/CT) for predicting disease-specific survival (DSS) in gastric cancer (GC) patients. Overall, 731 GC patients undergoing preoperative [¹⁸F]FDG PET/CT were enrolled and divided into the training (n = 543) and validation (n = 188) cohorts. A metabolic score (MS) was developed by combining the maximum standardized uptake value (SUVmax) of the primary tumor (T_SUVmax) and metastatic lymph node (N_SUVmax). A new staging system incorporating the MS and tumor-node-metastasis (TNM) stage was developed using conditional inference tree analysis. The MS was stratified as follows: score 1 (T_SUVmax ≤ 4.5 and N_SUVmax ≤ 1.9), score 2 (T_SUVmax > 4.5 and N_SUVmax ≤ 1.9), score 3 (T_SUVmax ≤ 4.5 and N_SUVmax > 1.9), and score 4 (T_SUVmax > 4.5 and N_SUVmax > 1.9) in the training cohort. The new staging system yielded five risk categories: category I (TNM I, II and MS 1), category II (TNM I, II and MS 2), category III (TNM I, II and MS ≥ 3), category IV (TNM III, IV and MS ≤ 3), and category V (TNM III, IV and MS 4) in the training cohort. DSS differed significantly between both staging systems; the new staging system showed better prognostic performance in both training and validation cohorts. The MS was an independent prognostic factor for DSS, and discriminatory power of the new staging system for DSS was better than that of the conventional TNM staging system alone.

A novel prognostic signature based on N7-methylguanosine-related long non-coding RNAs in breast cancer

Long non-coding RNA (lncRNA) are closely associated with the occurrence and progression of tumors. However, research on N7-methylguanosine (m7G)-related lncRNA in breast cancer is lacking. Therefore, the present study explored the prognostic value, gene expression characteristics, and effects of m7G-related lncRNA on tumor immune cell infiltration and tumor mutational burden (TMB) in breast cancer. lncRNA expression matrices and clinical follow-up data of patients with breast cancer were obtained from The Cancer Genome Atlas, revealing eight significantly differentially expressed and prognostically relevant m7G-related lncRNAs in breast cancer tissues: BAIAP2-DT, COL4A2-AS1, FARP1-AS1, RERE-AS1, NDUFA6-DT, TFAP2A-AS1, LINC00115, and MIR302CHG. A breast cancer prognostic signature was created based on these m7G-related lncRNAs according to least absolute shrinkage and selection operator Cox regression. The prognostic signature combined with potential prognostic factors showed independent prognostic value, reliability, and specificity. Meanwhile, we constructed a risk score-based nomogram to assist clinical decision-making. Gene set enrichment analysis revealed that low- and high-risk group were associated with metabolism-related pathways. Our study demonstrated the association between tumor immune cell infiltration based on analyses with the CIBERSORT algorithm and prognostic signature. We also assessed the correlation between prognostic signature and TMB. Lastly, quantitative real-time polymerase chain reaction analysis was performed to validate differentially expressed lncRNAs. The effective prognostic signature based on m7G-related lncRNAs has the potential to predict the survival prognosis of patients with breast cancer. The eight m7G-related lncRNAs identified in this study might represent potential biomarkers and therapeutic targets of breast cancer.

Nucleobindin-2/nesfatin-1 enhances the cell proliferation, migration, invasion and epithelial-mesenchymal transition in gastric carcinoma

Nesfatin-1, a newly discovered adipokine derived from nucleobindin-2 (NUCB2), has been described as a new prognostic marker in cancers. This study aimed to explore the functional role of NUCB2/nesfatin-1 in the cell proliferation, migration and invasion in gastric carcinoma (GC). The expressions of NUCB2/nesfatin-1 in GC tissues and normal adjacent tissues (NATs) were compared, and the effect of inhibition of NUCB2/nesfatin-1 on the cell proliferation, migration, invasion and epithelial-mesenchymal transition (EMT) in GC cell line SGC-7901 was investigated. Cell transfection was conducted to inhibit NUCB2/nesfatin-1 by short hairpin RNA. Cell proliferation, migration and invasion abilities were determined using cell counting kit-8 (CCK-8), 5-ethynyl-2'-deoxyuridine (EdU), wound healing and transwell assays, respectively. The expressions of EMT markers E-Cadherin and N-Cadherin were determined using western blotting. The expression of NUCB2/nesfatin-1 protein in GC tissues was significantly increased compared with that in NATs. Consistently, the serum concentrations of NUCB2/nesfatin-1 were significantly higher in patients with GC as compared with those in the control group. Moreover, the results of CCK-8 assay and EdU assay indicated that knockdown of NUCB2/nesfatin-1 could markedly decrease SGC-7901 proliferation. Furthermore, the results of wound healing assay and transwell assay demonstrated that knockdown of NUCB2/nesfatin-1 significantly suppressed SGC-7901 migration and invasion abilities. Additionally, knockdown of NUCB2/nesfatin-1 decreased the expressions of N-Cadherin and increased the expressions of E-Cadherin in SGC-7901 cells. These findings suggest that knockdown of NUCB2/nesfatin-1 suppressed the proliferation, migration, invasion and EMT of SGC-7901 cells, suggesting a potentially promising therapeutic target for GC.

Relationships among microbiota, gastric cancer, and immunotherapy

Currently, conventional neoadjuvant therapy or postoperative adjuvant therapy, such as chemotherapy and radiation therapy, can only bring limited survival benefits to gastric cancer (GC). Median survival after palliative chemotherapy is also low, at about 8–10 months. Immunotargeting is a new option for the treatment of GC, but has not been widely replicated. The highly immunosuppressed tumor microenvironment (TME) discounts the efficacy of immunotherapy for GC. Therefore, new strategies are needed to enhance the immune response of the TME. This paper reviewed the relationship between microorganisms and GC, potential links between microorganisms and immunotherapy and research of microorganisms combined immunotherapy.

Cell death affecting the progression of gastric cancer

Gastric cancer is a gastrointestinal tumor with high morbidity and mortality rates. Several factors influence its progression, cell death being an important element. In this review, we summarized the effects of necrosis, apoptosis, necroptosis, pyroptosis, ferroptosis, and eight less common cell death modalities on gastric cancer cells and the tumor microenvironment, detailed the molecular mechanisms of various cell death and their major regulatory pathways in gastric cancer, explored the prevalence and complexity of cell death in gastric cancer progression and highlighted the potentials of cell death-related therapies in gastric cancer.

Tumor vessel normalization and immunotherapy in gastric cancer

Gastric cancer (GC) is a common malignant tumor, and patients with GC have a low survival rate due to limited effective treatment methods. Angiogenesis and immune evasion are two key processes in GC progression, and they act synergistically to promote tumor progression. Tumor vascular normalization has been shown to improve the efficacy of cancer immunotherapy, which in turn may be improved through enhanced immune stimulation. Therefore, it may be interesting to identify synergies between immunomodulatory agents and anti-angiogenic therapies in GC. This strategy aims to normalize the tumor microenvironment through the action of the anti-vascular endothelial growth factor while stimulating the immune response through immunotherapy and prolonging the survival of GC patients.

Ferroptosis and its Role in Gastric Cancer

Gastric cancer (GC) is the fifth most common cancer and the third leading cause of cancer-related deaths worldwide. Currently, surgery is the treatment of choice for GC. However, the associated expenses and post-surgical pain impose a huge burden on these patients. Furthermore, disease recurrence is also very common in GC patients, thus necessitating the discovery and development of other potential treatment options. A growing body of knowledge about ferroptosis in different cancer types provides a new perspective in cancer therapeutics. Ferroptosis is an iron-dependent form of cell death. It is characterized by intracellular lipid peroxide accumulation and redox imbalance. In this review, we summarized the current findings of ferroptosis regulation in GC. We also tackled on the action of different potential drugs and genes in inducing ferroptosis for treating GC and solving drug resistance. Furthermore, we also explored the relationship between ferroptosis and the tumor microenvironment in GC. Finally, we discussed areas for future studies on the role of ferroptosis in GC to accelerate the clinical utility of ferroptosis induction as a treatment strategy for GC.

Relationship Between CNVs and Immune Cells Infiltration in Gastric Tumor Microenvironment

Gastric cancer (GC) is a highly fatal and common malignancy of the digestive system. Recent therapeutic advancements have significantly improved the clinical outcomes in GC, but due to the unavailability of suitable molecular targets, a large number of patients do not respond to the immune checkpoint inhibitors (ICI) therapy. To identify and validate potential therapeutic and prognostic targets of gastric cancer, we used the “inferCNV” R package for analyzing single-cell sequencing data (GSE112302) of GC and normal epithelial cells. First, by using LASSO, we screened genes that were highly correlated with copy number variations (CNVs). Therefrom, five gene signature (CPVL, DDC, GRTP1, ONECUT2, and PRSS21) was selected by cross-validating the prognosis and risk management with the GC RNA-seq data obtained from GEO and TCGA. Moreover, the correlation analyses between CNVs of these genes and immune cell infiltration in gastric cancer identified CPVL as a potential prognostic marker. Finally, CPVL showed high expression in gastric cancer samples and cell lines, then siRNA-mediated silencing of CPVL expression in gastric cancer cells showed significant proliferation arrest in MGC803 cells. Here, we conclude that CNVs are key regulators of the immune cells infiltration in gastric TME as well as cancer development, and CPVL could potentially be used as a prognostic and therapeutic marker in gastric cancer.

A Novel DNA Repair Gene Signature for Immune Checkpoint Inhibitor-Based Therapy in Gastric Cancer

Gastric cancer is a heterogeneous group of diseases with only a fraction of patients responding to immunotherapy. The relationships between tumor DNA damage response, patient immune system and immunotherapy have recently attracted attention. Accumulating evidence suggests that DNA repair landscape is a significant factor in driving response to immune checkpoint blockade (ICB) therapy. In this study, to explore new prognostic and predictive biomarkers for gastric cancer patients who are sensitive and responsive to immunotherapies, we developed a novel 15-DNA repair gene signature (DRGS) and its related scoring system and evaluated the efficiency of the DRGS in discriminating different molecular and immune characteristics and therapeutic outcomes of patients with gastric adenocarcinoma, using publicly available datasets. The results demonstrated that DRGS high score patients showed significantly better therapeutic outcomes for ICB compared to DRGS low score patients (p < 0.001). Integrated analysis of multi-omics data demonstrated that the patients with high DRGS score were characteristic of high levels of anti-tumor lymphocyte infiltration, tumor mutation burden (TMB) and PD-L1 expression, and these patients exhibited a longer overall survival, as compared to the low-score patients. Results obtained from HPA and IHC supported significant dysregulation of the genes in DRGS in gastric cancer tissues, and a positive correlation in protein expression between DRGS and PD-L1. Therefore, the DRGS scoring system may have implications in tailoring immunotherapy in gastric cancers. A preprint has previously been published (Yuan et al., 2021).

Immune cell infiltration and immunotherapy in hepatocellular carcinoma

Hepatocellular carcinoma is a highly malignant tumor and patients yield limited benefits from the existing treatments. The application of immune checkpoint inhibitors is promising but the results described in the literature are not favorable. It is therefore urgent to systematically analyze the immune microenvironment of HCC and screen the population best suited for the application of immune checkpoint inhibitors to provide a basis for clinical treatment. In this study, we collected The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC)-related data sets to evaluate the immune microenvironment and immune cell infiltration (ICI) in HCC. Three independent ICI subtypes showing significant differences in survival were identified. Further, TCGA-LIHC immunophenoscore (IPS) was used to identify the differentially expressed genes between high- and low-IPS in HCC, so as to identify the immune gene subtypes in HCC tumors. The ICI score model for HCC was constructed, whereby we divided HCC samples into high- and low-score groups based on the median ICI score. The differences between these groups in genomic mutation load and immunotherapy benefit in HCC were examined in detail to provide theoretical support for accurate immunotherapy strategy in HCC. Finally, four genes were screened, which could accurately predict the subtype based on the tumor immune infiltration score. The findings may provide a basis and simplify the process for screening clinical drugs suitable for relevant subgroups.

Evaluation of Immune Infiltration Based on Image Plus Helps Predict the Prognosis of Stage III Gastric Cancer Patients with Significantly Different Outcomes in Northeastern China

Gastric cancer (GC) might have significantly different outcomes within the same AJCC/UICC-TNM stage. The purpose of this study is to help predict the different prognosis through the pattern of immune cell infiltration. We retrospectively analyzed 2605 patients who underwent radical gastrectomy in the Harbin Medical University Cancer Hospital between 2002 and 2013. For stage III with significantly different survival probability, we analyzed the relationship between immune cell surface antigen and survival in TCGA dataset. Furthermore, 200 cases in stage III GC with different survival outcomes were randomly selected for immunohistochemical verification. Image Plus software was used to evaluate the area of immune cell infiltration. We found that patients in stage III had significantly different outcomes. Bioinformatics analysis showed that there was a significant negative correlation between the expression of immune cell surface antigen and prognosis. In order to investigate whether immune infiltration can distinguish GC patients in stage III with differences in prognosis, we verified by immunohistochemistry that CD4+ T cells, CD20+ B cells, and CD177+ neutrophils infiltrated more in group B with better prognosis; CD8+ T cells, CD68+ macrophages, and CD117+ mast cells infiltrated more in group A with poor prognosis. CD117+ mast cells have the same trend of predicting significance for prognosis in the RNA and protein levels. In conclusion, patients with GC in northeastern China have significant prognostic differences only in stage III. CD117+ mast cells may be important evaluation factors in further studies of Immunoscore.

Bmi-1 directly upregulates glucose transporter 1 in human gastric adenocarcinoma

This study aimed to investigate whether and how Moloney murine leukemia virus integration site 1 (Bmi-1) plays a role in the regulation of glucose transporter 1 (GLUT1) in gastric adenocarcinoma (GAC). GAC and matched noncancerous tissues were obtained from GAC patients who underwent surgical treatment at the China-Japan Union Hospital, Jilin University (Changchun, Jilin, China). The human GAC cell line AGS and the gastric epithelial cell line GES-1 were used for in vitro studies. BALB/c nude mice were used for in vivo studies. The Bmi-1 and GLUT1 protein levels were significantly greater in human tissues from GAC patients and AGS cells in comparison with controls. Silencing of Bmi-1 resulted in significant decrease in glucose uptake, lactate levels, and GLUT1 expression. In vivo¹⁸F-deoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) imaging studies indicated that the nude mice bearing xenografts of AGS cells treated with Bmi-1-specific small interfering RNA (siRNA) had a significantly lower maximum standardized uptake value (SUV_max) in comparison with the control mice. Thus, Bmi-1 directly upregulates GLUT1 gene expression, through which it is involved in enhancing glucose uptake in GAC. The results also provide scientific evidence for ¹⁸F-FDG PET/CT imaging to evaluate Bmi-1 and glucose uptake in GAC.

Comprehensive analysis of tumor immune microenvironment and prognosis of m6A-related lncRNAs in gastric cancer

Background

N6-methyladenosine (m6A) modification and long non-coding RNAs (lncRNAs) play pivotal roles in gastric cancer (GC) progression. The emergence of immunotherapy in GC has created a paradigm shift in the approaches of treatment, whereas there is significant heterogeneity with regard to degree of treatment responses, which results from the variability of tumor immune microenvironment (TIME). How the interplay between m6A and lncRNAs enrolling in the shaping of TIME remains unclear.

Methods

The RNA sequencing and clinical data of GC patients were collected from TCGA database. Pearson correlation test and univariate Cox analysis were used to screen out m6A-related lncRNAs. Consensus clustering method was implemented to classify GC patients into two clusters. Survival analysis, the infiltration level of immune cells, Gene set enrichment analysis (GSEA) and the mutation profiles were analyzed and compared between two clusters. A competing endogenous RNA (ceRNA) network and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were applied for the identification of pathways in which m6A-related lncRNAs enriched. Then least absolute shrinkage and selection operator (LASSO) COX regression was implemented to select pivotal lncRNAs, and risk model was constructed accordingly. The prognosis value of the risk model was explored. In addition, the response to immune checkpoint inhibitors (ICIs) therapy were compared between different risk groups. Finally, we performed qRT-PCR to detect expression patterns of the selected lncRNAs in the 35 tumor tissues and their paired adjacent normal tissues, and validated the prognostic value of risk model in our cohort (N = 35).

Results

The expression profiles of 15 lncRNAs were included to cluster patients into 2 subtypes. Cluster1 with worse prognosis harbored higher immune score, stromal score, ESTIMATE score and lower mutation rates of the genes. Different immune cell infiltration patterns were also displayed between the two clusters. GSEA showed that cluster1 preferentially enriched in tumor hallmarks and tumor-related biological pathways. KEGG pathway analysis found that the target mRNAs which m6A-related lncRNAs regulated by sponging miRNAs mainly enriched in vascular smooth muscle contraction, cAMP signaling pathway and cGMP-PKG signaling pathway. Next, eight lncRNAs were selected by LASSO regression algorithm to construct risk model. Patients in the high-risk group had poor prognoses, which were consistent in our cohort. As for predicting responses to ICIs therapy, patients from high-risk group were found to have lower tumor mutation burden (TMB) scores and account for large proportion in the Microsatellite Instability-Low (MSI-L) subtype. Moreover, patients had distinct immunophenoscores in different risk groups.

Conclusion

Our study revealed that the interplay between m6A modification and lncRNAs might have critical role in predicting GC prognosis, sculpting TIME landscape and predicting the responses to ICIs therapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09377-8.

Development of Tumor Mutation Burden-Related Prognostic Model and Novel Biomarker Identification in Stomach Adenocarcinoma

Background: Stomach adenocarcinoma (STAD) is one of the most common tumors. Tumor mutation burden (TMB) has been linked to immunotherapy response. We wanted to see if there was any link between TMB and cancer prognosis.

Methods: The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases were used to obtain mutation data, gene expression profiles, and clinical data. We looked at the differences in gene expression and immune markers between low and high TMB groups, built an immune prognostic model, and created a dynamic nomograph App that may be used in the clinic. Simultaneously, We ran the immunotherapy prediction and model comparison at the same time. Finally, model gene mutation and copy number variation (CNV) were displayed. The cellular functional experiments were used to investigate the potential role of GLP2R in gastric cancer.

Results: Firstly, basic mutation information and differences in immune infiltration in STAD are revealed. Secondly, the prognostic model developed by us has good accuracy, and the corresponding dynamic nomograph Apps online and immunotherapy prediction facilitate clinical transformation. Furthermore, GLP2R knockdown significantly inhibited the proliferation, migration of gastric cancer cells in vitro.

Conclusion: Our findings imply that TMB plays a significant role in the prognosis of STAD patients from a biological perspective. GLP2R may serve as a potential target for gastric cancer.

Comprehensive Analysis of an Individualized Immune-Related lncRNA Pair Signature in Gastric Cancer

Long noncoding RNAs (lncRNAs) have diverse functions, including immune regulation. Increasing studies have reported immune-related lncRNAs in the prognosis of multiple cancers. In this study, we developed an individualized signature containing 13 immune-related lncRNA pairs (IRLPs) which could predict the overall survival, disease-free survival, progression-free survival, and disease-specific survival of gastric cancer (GC) patients in The Cancer Genome Atlas (TCGA) cohort, and internal and external validations, signature comparisons, and subgroup analyses further confirmed its superiority, stability, and generalizability. Notably, this signature also showed good applicability in discriminating the prognosis of pan-cancer patients. Then, we constructed and validated a nomogram for overall survival based on the signature and clinical factors, which allowed more accurate predictions of GC prognosis. In addition, we revealed that the low survival rate of patients with high-risk scores may be due to their aggressive clinical features, enriched cancer-related signaling pathways, the infiltration of specific immunosuppressive cells, and low tumor mutation burden. We further predicted obviously worse immunotherapeutic responses in the high-risk groups and identified some candidate compounds targeting GC risk group differentiation. This signature based on the IRLPs may be promising for predicting the survival outcomes and immunotherapeutic responses of GC patients in clinical practice.

Cellular immunotherapy in gastric cancer: adoptive cell therapy and dendritic cell-based vaccination

Gastric cancer (GC) is one of the most frequently diagnosed malignancies. Recent studies have highlighted cellular immunotherapy (CI) as a promising approach for treating this disease. Among the CI-based approaches, adoptive cell therapy and dendritic cell-based vaccination are commonly studied in preclinical and clinical trials. Here we review the current evidence on the potentiality of CI in treating GC, the targets for adoptive cell therapy, ongoing clinical trials, constraints and the future outlook. The results suggest that there is a need to identify novel biomarkers that predict which GC patients will most likely respond to these approaches. Also, CI plus chemotherapy or immune checkpoint inhibitors can improve the survival of patients with late-stage GC. Therefore, this approach can be promising for treating these patients.

An artificial intelligence method to assess the tumor microenvironment with treatment outcomes for gastric cancer patients after gastrectomy

Background

The tumor microenvironment (TME) plays an important role in the occurrence and development of gastric cancer (GC) and is widely used to assess the treatment outcomes of GC patients. Immunohistochemistry (IHC) and gene sequencing are the main analysis methods for the TME but are limited due to the subjectivity of observers, the high cost of equipment and the need for professional analysts.

Methods

The ImmunoScore (IS) was developed in the TCGA cohort and validated in GEO cohorts. The Radiomic ImmunoScore (RIS) was developed in the TCGA cohort and validated in the Nanfang cohort. A nomogram was developed and validated in the Nanfang cohort based on RIS and clinical features.

Results

For IS, the area under the curves (AUCs) were 0.798 for 2-year overall survival (OS) and 0.873 for 4-year overall survival. For RIS, in the TCGA cohort, the AUCs distinguishing High-IS or Low-IS and predicting prognosis were 0.85 and 0.81, respectively; in the Nanfang cohort, the AUC predicting prognosis was 0.72. The nomogram performed better than the TNM staging system according to the ROC curve (all P < 0.01). Patients with TNM stage II and III in the High-nomogram group were more likely to benefit from adjuvant chemotherapy than Low-nomogram group patients.

Conclusions

The RIS and the nomogram can be used to assess the TME, prognosis and adjuvant chemotherapy benefit of GC patients after radical gastrectomy and are valuable additions to the current TNM staging system. High-nomogram GC patients may benefit more from adjuvant chemotherapy than Low-nomogram GC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03298-7.

miR-139-3p/Kinesin family member 18B axis suppresses malignant progression of gastric cancer

miR-139-3p exerts tumor-suppressing functions in various cancers. We analyzed and identified that miR-139-3p expression was notably low in gastric cancer (GC) via edgeR differential analysis based on The Cancer Genome Atlas database and quantitative real-time polymerase chain reaction (qRT-PCR) assay. The binding relationship between Kinesin Family Member 18B (KIF18B) and miR-139-3p was predicted by bioinformatics databases, and verified through dual-luciferase assay. Western blot and qRT-PCR results also indicated that miR-139-3p restrained KIF18 expression at mRNA and protein levels. 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide, wound healing, transwell, flow cytometry assays were introduced to evaluate cell proliferation, migration, invasion, and cell cycle, respectively, where the results indicated that upregulating miR-139-3p inhibited proliferative, migratory, and invasive abilities of GC cells, while caused cell-cycle arrest. Moreover, the results of rescue experiments illustrated that miR-139-3p hampered the progression of GC cells by targeting and suppressing KIF18B. To sum up, we concluded that miR-139-3p suppressed GC progression by targeting KIF18B.

Gastric cancer cell death analyzed by live cell imaging of spheroids

Gastric cancer (GC) is the third cause of cancer-related mortality worldwide and is often diagnosed at advanced stages of the disease. This makes the development of more comprehensive models and efficient treatments crucial. One option is based on repurposing already marketed drugs as adjuvants to chemotherapy. Accordingly, we have previously developed the combination of docetaxel and the cholesterol-lowering drug, lovastatin, as a powerful trigger of HGT-1 human GC cells' apoptosis using 2D cultures. Because 3D models, known as spheroids, are getting recognized as possibly better suited than 2Ds in toxicological research, we aimed to investigate the efficacy of this drug combination with such a model. We established monocellular spheroids from two human (GC) cell lines, HGT-1 and AGS, and bicellular spheroids from these cells mixed with cancer-associated fibroblasts. With these, we surveyed drug-induced cytotoxicity with MTT assays. In addition, we used the Incucyte live imaging and analysis system to follow spheroid growth and apoptosis. Taken together, our results showed that the lovastatin + docetaxel combination was an efficient strategy to eliminate GC cells grown in 2D or 3D cultures, lending further support in favor of repurposing lovastatin as an adjuvant to taxane-based anticancer treatment.

Long noncoding RNA FAM225A promotes the malignant progression of gastric cancer through the miR-326/PADI2 axis

Gastric cancer (GC) is a global health problem and further studies of its molecular mechanisms are needed to identify effective therapeutic targets. Although some long noncoding RNAs (lncRNAs) have been found to be involved in the progression of GC, the molecular mechanisms of many GC-related lncRNAs remain unclear. In this study, a series of in vivo and in vitro assays were performed to study the relationship between FAM225A and GC, which showed that FAM225A levels were correlated with poor prognosis in GC. Higher FAM225A expression tended to be correlated with a more profound lymphatic metastasis rate, larger tumor size, and more advanced tumor stage. FAM225A also promoted gastric cell proliferation, invasion, and migration. Further mechanistic investigation showed that FAM225A acted as a miR-326 sponge to upregulate its direct target PADI2 in GC. Overall, our findings indicated that FAM225A promoted GC development and progression via a competitive endogenous RNA network of FAM225A/miR-326/PADI2 in GC, providing insight into possible therapeutic targets and prognosis of GC.

Differentially Expressed Genes in Clear Cell Renal Cell Carcinoma as a Potential Marker for Prognostic and Immune Signatures

Clear cell renal cell carcinoma (ccRCC) is characterized by the inactivation of the von Hippel–Lindau (VHL) gene. Of note, no other gene is mutated as frequently as VHL in ccRCC, turning out that patients with inactivated VHL constitute the majority of ccRCC-related character. Thus, differentially expressed genes (DEGs) and their molecular networks caused by VHL mutation were considered as important factors for influencing the prognosis of ccRCC. Here, we first screened out six DEGs (GSTA1, GSTA2, NAT8, FABP7, SLC17A3, and SLC17A4) which downregulated in ccRCC patients with VHL non-mutation than with the mutation. Generally, most DEGs with high expression were associated with a favorable prognosis and low-risk score. Meanwhile, we spotted transcription factors and their kinases as hubs of DEGs. Finally, we clustered ccRCC patients into three subgroups according to the expression of hub proteins, and analyzed these subgroups with clinical profile, outcome, immune infiltration, and potential Immune checkpoint blockade (ICB) response. Herein, DEGs might be a promising biomarker panel for immunotherapy and prognosis in ccRCC. Moreover, the ccRCC subtype associated with high expression of hubs fit better for ICB therapy.

Discovery and Validation of Novel Methylation Markers in Helicobacter pylori-Associated Gastric Cancer

Previous studies have shown that abnormal methylation is an early key event in the pathogenesis of most human cancers, contributing to the development of tumors. However, little attention has been given to the potential of DNA methylation patterns as markers for Helicobacter pylori- (H. pylori-) associated gastric cancer (GC). In this study, an integrated analysis of DNA methylation and gene expression was conducted to identify some potential key epigenetic markers in H. pylori-associated GC. DNA methylation data of 28 H. pylori-positive and 168 H. pylori-negative GC samples were compared and analyzed. We also analyzed the gene expression data of 18 H. pylori-positive and 145 H. pylori-negative GC cases. Finally, the results were verified by in vitro and in vivo experiments. A total of 5609 differentially methylated regions associated with 2454 differentially methylated genes were identified. A total of 228 differentially expressed genes were identified from the gene expression data of H. pylori-positive and H. pylori-negative GC cases. The screened genes were analyzed for functional enrichment. Subsequently, we obtained 28 genes regulated by methylation through a Venn diagram, and we identified five genes (GSTO2, HUS1, INTS1, TMEM184A, and TMEM190) downregulated by hypermethylation. HUS1, GSTO2, and TMEM190 were expressed at lower levels in GC than in adjacent samples (P < 0.05). Moreover, H. pylori infection decreased HUS1, GSTO2, and TMEM190 expression in vitro and in vivo. Our study identified HUS1, GSTO2, and TMEM190 as novel methylation markers for H. pylori-associated GC.

Immune landscape of advanced gastric cancer tumor microenvironment identifies immunotherapeutic relevant gene signature

Background

Advanced gastric cancer (AGC) is a disease with poor prognosis due to the current lack of effective therapeutic strategies. Immune checkpoint blockade treatments have shown effective responses in patient subgroups but biomarkers remain challenging. Traditional classification of gastric cancer (GC) is based on genomic profiling and molecular features. Therefore, it is critical to identify the immune-related subtypes and predictive markers by immuno-genomic profiling.

Methods

Single-sample gene-set enrichment analysis (ssGSEA) and ESTIMATE algorithm were used to identify the immue-related subtypes of AGC in two independent GEO datasets. Weighted gene co-expression network analysis (WGCNA) and Molecular Complex Detection (MCODE) algorithm were applied to identify hub-network of immune-related subtypes. Hub genes were confirmed by prognostic data of KMplotter and GEO datasets. The value of hub-gene in predicting immunotherapeutic response was analyzed by IMvigor210 datasets. MTT assay, Transwell migration assay and Western blotting were performed to confirm the cellular function of hub gene in vitro.

Results

Three immune-related subtypes (Immunity_H, Immunity_M and Immunity_L) of AGC were identified in two independent GEO datasets. Compared to Immunity_L, the Immuntiy_H subtype showed higher immune cell infiltration and immune activities with favorable prognosis. A weighted gene co-expression network was constructed based on GSE62254 dataset and identified one gene module which was significantly correlated with the Immunity_H subtype. A Hub-network which represented high immune activities was extracted based on topological features and Molecular Complex Detection (MCODE) algorithm. Furthermore, ADAM like decysin 1 (ADAMDEC1) was identified as a seed gene among hub-network genes which is highly associated with favorable prognosis in both GSE62254 and external validation datasets. In addition, high expression of ADAMDEC1 correlated with immunotherapeutic response in IMvigor210 datasets. In vitro, ADAMDEC1 was confirmed as a potential protein in regulating proliferation and migration of gastric cancer cell. Deficiency of ADAMDEC1 of gastric cancer cell also associated with high expression of PD-L1 and Jurkat T cell apoptosis.

Conclusions

We identified immune-related subtypes and key tumor microenvironment marker in AGC which might facilitate the development of novel immune therapeutic targets.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-09065-z.

Targeted FGFR/VEGFR/PDGFR inhibition with dovitinib enhances the effects of nab-paclitaxel in preclinical gastric cancer models

Standard chemotherapy regimens for gastric adenocarcinoma (GAC) have limited efficacy and considerable toxicity profiles. Nab-paclitaxel has shown promising antitumor benefits in previous GAC preclinical studies. Dovitinib inhibits members of the receptor tyrosine kinase family including FGFR, VEGFR and PDGFR, and has exhibited antitumor effects in many solid tumors including GAC. Based on the antimitotic, antistromal and EPR effects of nab-paclitaxel, we investigated augmentation of nab-paclitaxel response by dovitinib in multiple GAC preclinical models. In MKN-45 subcutaneous xenografts, inhibition in tumor growth by nab-paclitaxel and dovitinib was 75% and 76%, respectively. Dovitinib plus nab-paclitaxel had an additive effect on tumor growth inhibition and resulted in tumor regression (85% of its original value). Dovitinib monotherapy resulted in minimal improvement in animal survival (25 days) compared to control (23 days), while nab-paclitaxel monotherapy or dovitinib plus nab-paclitaxel combination therapy led to a clinically significant lifespan extension of 83% (42 days) and 187% (66 days), respectively. IHC analysis of subcutaneous tumors exhibited reduced tumor cell proliferation and tumor vasculature by dovitinib. In vitro studies demonstrated that dovitinib and nab-paclitaxel individually reduced tumor cell proliferation, with an additive effect from combination therapy. Immunoblot analyses of MKN-45 and KATO-III cells revealed that dovitinib decreased phospho-FGFR, phospho-AKT, phospho-ERK, phospho-p70S6K, phospho-4EBP1, Bcl-2 and increased cleaved PARP-1, cleaved-caspase-3, p27, Bax, Bim, with an additive effect from combination therapy. These results demonstrate that the FGFR/VEGFR/PDGFR inhibitor, dovitinib, has the potential to augment the antitumor effects of nab-paclitaxel, with implications for use in the advancement of clinical GAC therapy.

Development and Verification of an Immune-Based Gene Signature for Risk Stratification and Immunotherapeutic Efficacy Assessment in Gastric Cancer

Objective

Due to the molecular heterogeneity of gastric cancer, only minor patients respond to immunotherapeutic schemes. This study is aimed at developing an immune-based gene signature for risk stratification and immunotherapeutic efficacy assessment in gastric cancer.

Methods

An immune-based gene signature was developed in gastric cancer by LASSO method in the training set. The predictive performance was validated in the external datasets. KEGG pathways related to risk scores were assessed by GSEA. Based on multivariate Cox regression analysis, a nomogram was established. Sensitivity to chemotherapy drugs was evaluated between high- and low-risk samples. The relationships of risk scores with infiltration levels of immune cells, stromal scores, immune scores, immune cell subgroups, and overall response to anti-PD-L1 therapy were determined.

Results

Our results showed that high risk scores were indicative of undesirable survival outcomes both in the training set (p < 0.0001) and the validation set (p = 0.002). Moreover, this signature could independently predict patients' survival (HR: 2.656 (1.919-3.676) and p < 0.001). Subgroup analysis confirmed the sensitivity of this signature in predicting prognosis (all p < 0.05). Cancer-related pathways were primarily enriched in high-risk samples, such as MAPK and TGF-β pathways (p < 0.05). By incorporating stage and the risk score, we established a nomogram for predicting one-, three-, and five-year survival probability. Patients with high-risk scores were more sensitive to chemotherapy drugs (p < 0.05). There was heterogeneity in immune cells between high- and low-risk samples (p < 0.05). Samples with progressive disease exhibited the highest risk score, and those with complete response had the lowest risk score (p < 0.05).

Conclusion

This immune-based gene signature might be representative of a promising prognostic classifier for predicting risk stratification and immunotherapeutic efficacy in gastric cancer, assisting personalized therapy and follow-up plan.

State-of-the-Art of Monoclonal Antibodies for the Treatment of Gastric Cancer

Gastric cancer (GC) is a complex and heterogeneous disease with poor prognosis and limited available treatment options. During recent years, several molecular stratifications have been proposed to optimize the overall treatment strategy for GC patients. Breakthroughs in cancer biology and in molecular profiling through DNA and RNA sequencing are now opening novel landscapes, leading to the personalization of molecular matched therapy. In particular, therapies against HER2, Claudine 18.2, Fibroblast Growth Factor Receptors (FGFR), and other molecular alterations could significantly improve survival outcomes in the advance phase of the disease. Furthermore, immunotherapy with checkpoint inhibitors also represents a promising option in a selected population. Hoping that precision oncology will enter soon in clinical practice, our review describes the state of the art of many novel pathways and the current evidence supporting the use of monoclonal antibodies implicated in GC treatment.

Comparative effectiveness and tolerability of targeted agents combined with chemotherapy in patients with HER2-positive gastroesophageal cancer: A network meta-analysis

BACKGROUND

Gastric cancer (GC) or gastroesophageal junction (GEJ) cancer with HER2 overexpression is highly invasive, with a poor prognosis. With the development of new targeted agents, which agents have ideal therapeutic effects must be determined. This network meta-analysis analyzed the effectiveness and tolerability of targeted agents combined with chemotherapy in HER2-positive GC/GEJ cancer.

METHODS

Public databases were searched from the date of inception to October 22, 2020. Randomized controlled trials (RCTs) on targeted agent-related regimens for HER2-positive advanced GC or GEJ cancer were included. Subgroup analyses based on publication language, first-line treatment, second/third-line treatment, and HER2 staining intensity were performed.

RESULTS

In total, 13 articles were included. The trastuzumabderuxtecan (TraD) and pertuzumab plus trastuzumab and chemotherapy (PerTraChemo) regimens were considered to have high effectiveness but low tolerability. In the subgroup analysis, PerTraChemo still had high effectiveness with low tolerability as the first-line therapy. As the second- or third-line therapy, TraD and lapatinib plus chemotherapy (LapChemo) had high effectiveness and moderate tolerability. In terms of overall survival (OS) time, PerTraChemo had a relative advantage in the immunohistochemistry (IHC) 2+/in situ hybridization (ISH)+ population, whereas TraD, PerTraChemo, and trastuzumab plus chemotherapy (TraChemo) had a relative advantage in the IHC3+ population.

CONCLUSION

TraD had relative advantages as the second- or third-line therapy and in the IHC3 + population. PerTraChemo is a potential first-line therapy, but it requires further confirmation because the JACOB phase III clinical trial failed to confirm the superiority of PerTraChemo over TraChemo with regard to OS.

Comprehensive analysis of prognostic genes in gastric cancer

Background: Gastric cancer is associated with high mortality, and effective methods for predicting prognosis are lacking. We aimed to identify potential prognostic markers associated with the development of gastric cancer through bioinformatic analyses.

Methods: Gastric cancer-associated gene expression profiles were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. The key genes involved in the development of gastric cancer were obtained by differential expression analysis, coexpression analysis, and short time-series expression miner (STEM) analysis. The potential prognostic value of differentially expressed genes was further evaluated using a Cox regression model and risk scores. Hierarchical clustering was applied to validate the impact of key genes on the overall survival of gastric cancer patients.

Results: A total of 1381 genes were consistently dysregulated in the development of gastric cancer. Among them, 186 genes affected the overall survival of gastric cancer patients. The following genes had areas under the receiver operating characteristic curve greater than 0.9 in both datasets and were therefore considered key genes: ADAM12, CEP55, LRFN4, INHBA, ADH1B, DPT, FAM107A, and LOC100506388. LRFN4, DPT, and LOC100506388 were identified as potential prognostic genes for gastric cancer through a nomogram. Overexpression of LRFN4 and LOC100506388 was associated with a higher risk of gastric cancer. Finally, we found that tumors were infiltrated with high levels of Th2 cells and mast cells, and the infiltration levels were associated with overall survival in gastric cancer patients.

Conclusions: We found that key dysregulated genes may have a prognostic value for the development of gastric cancer.

Helicobacter pylori promotes gastric cancer progression by upregulating semaphorin 5A expression via ERK/MMP9 signaling

Helicobacter pylori (H. pylori) infection is the strongest risk factor for the occurrence and development of gastric carcinoma. However, the molecular mechanism underlying H. pylori-induced pathogenesis has not yet been fully characterized. Here, we explored whether H. pylori upregulates semaphorin 5A to promote gastric cancer progression via the extracellular regulated protein kinases/matrix metalloproteinase (ERK/MMP9) signaling pathway. In this study, H. pylori upregulated semaphorin 5A expression in vitro and in vivo. Using the human gastric carcinoma cell lines SGC7901, SGC7901-siScrambled, and SGC7901-siSema 5A, our studies showed that H. pylori increased the proliferation, growth, migration, and invasiveness of gastric cancer cells via its effects on semaphorin 5A and that H. pylori increased the expression of MMP9 in gastric cancer cells via the semaphorin 5A-mediated ERK signaling pathway. Further analysis revealed that the ERK inhibitor PD98059 and MMP9 antibody (Ab) attenuated H. pylori-induced gastric cancer cell invasion and metastasis in vitro through a semaphorin 5A-dependent mechanism. In conclusion, H. pylori could promote gastric cancer progression in a semaphorin 5A-dependent manner via the ERK/MMP9 signaling pathway. Semaphorin 5A and its related signaling molecules potentially represent latent targets for H. pylori-related gastric cancer therapy.

Comparing immunotherapies to other frequently used treatments of gastric cancer

Introduction: Although standard doublet chemotherapy represents the upfront gold standard to increase survival and improve quality of life of gastric cancer patients, overall improvements in long-term outcomes are modest and novel treatments are urgently needed. Among these, immunotherapy is an increasingly attractive option.Areas covered: A number of clinical trials have shown that checkpoint inhibitors may be of value, but many unclear issues remain controversial and should be promptly untangled. In our short review, we offer the current available data regarding immunotherapies in gastric cancers, discuss potential limits of the reported trials, compare outcomes of checkpoints inhibitor to those of standard chemotherapy or other novel treatments, and present basic principles of immune surveillance and immune escape that may be embraced in the near future with novel drug combinations.Expert opinion: Gastric cancer patients may benefit from immunotherapy, both given alone in advanced lines and upfront in combination with chemotherapy. We believe that appropriate patients' and tumor's selection are crucial issues to maximize its potential efficacy. In addition, we think that assay standardization, biomarker agreement, and translational studies will improve the benefit-to-risk ratio of these agents in the clinical practice.

Comprehensive analysis on the expression profile and prognostic values of Synaptotagmins (SYTs) family members and their methylation levels in gastric cancer

Synaptotagmins (SYTs), constitute a family of 17 membrane-trafficking protein, palying crucial roles in the development and progression of human cancers. However, only very few studies have investigated the expression profile and prognostic values of SYTs family members in gastric cancer (GC). Therefore, we comprehensively evaluated the expression, methylation, prognosis and immune significance of SYTs family members through bioinformatics analysis from the online databases in GC. The expressions of SYT4, SYT9, and SYT14 were up-regulated, and negatively associated with their methylation levels in GC. Both the over-expression of SYT4, SYT9 and SYT14 and their hypomethylation levels contributed to an unsatisfactory overall survival (OS) and progression-free survival (PFS) in GC. Moreover, the low expressions of several methylation cg sites (cg02795029, cg07581146, cg15149095, cg19922137, cg25371503, cg26158959, cg02269161, cg03226737, cg08185661, cg16437728, cg22723056 and cg24678137) were significantly correlated with an unfavorable OS and PFS in GC. Furthermore, the expression of SYT4, SYT9 and SYT14 played a pivotal role in immune cells infiltration in GC. Collectively, our current finding suggested that SYT4, SYT9 and SYT14 might be potent prognostic indictors and promising immunotherapeutic targets for GC patients.

Immune-Related Nine-MicroRNA Signature for Predicting the Prognosis of Gastric Cancer

Recent findings have demonstrated the superiority and utility of microRNAs (miRNAs) as new biomarkers for cancer diagnosis, therapy, and prognosis. In this study, to explore the prognostic value of immune-related miRNAs in gastric cancer (GC), we analyzed the miRNA-expression profiles of 389 patients with GC, using data deposited in The Cancer Genome Atlas database. Using a forward- and backward-variable selection and multivariate Cox regression analyses model, we identified a nine-miRNA signature (the “ImmiRSig,” consisting of miR-125b-5p, miR-99a-3p, miR-145-3p, miR-328-3p, miR-133a-5p, miR-1292-5p, miR-675-3p, miR-92b-5p, and miR-942-3p) in the training cohort that enabled the division of patients into high- and low-risk groups with significantly different survival rates. The ImmiRSig was successfully validated with an independent test cohort of 193 GC patients. Univariate and multivariate Cox regression analyses indicated that the ImmiRSig would serve as an independent prognostic factor after adjusting for other clinical covariates. Pending further prospective validation, the identified ImmiRSig appears to have significant clinical importance in terms of improving outcome predictions and guiding personalized treatment for patients with GC. Finally, significant associations between the ImmiRSig and the half-maximal inhibitory concentrations of chemotherapeutic agents were observed, suggesting that ImmiRSig may predict the clinical efficacy of chemotherapy.