Dissecting expression profiles of gastric precancerous lesions and early gastric cancer to explore crucial molecules in intestinal-type gastric cancer tumorigenesis

Genomic events stratifying prognosis of early gastric cancer

BACKGROUND

The purpose of the study was to conduct a comprehensive genomic characterization of gene alterations, microsatellite instability (MSI), and tumor mutational burden (TMB) in submucosal-penetrating (Pen) early gastric cancers (EGCs) with varying prognoses.

METHODS

Samples from EGC patients undergoing surgery and with 10-year follow-up data available were collected. Tissue genomic alterations were characterized using Trusight Oncology panel (TSO500). Pathway instability (PI) scores for a selection of 218 GC-related pathways were calculated both for the present case series and EGCs from the TCGA cohort.

RESULTS

Higher age and tumor location in the upper-middle tract are significantly associated with an increased hazard of relapse or death from any cause (p = 0.006 and p = 0.032). Even if not reaching a statistical significance, Pen A tumors more frequently present higher TMB values, higher frequency of MSI-subtypes and an overall increase in PI scores, along with an enrichment in immune pathways. ARID1A gene was observed to be significantly more frequently mutated in Pen A tumors (p = 0.006), as well as in patients with high TMB (p = 0.027). Tumors harboring LRP1B alterations seem to have a higher hazard of relapse or death from any cause (p = 0.089), being mutated mainly in relapsed patients (p = 0.093).

CONCLUSIONS

We found that the most aggressive subtype Pen A is characterized by a higher frequency of ARID1A mutations and a higher genetic instability, while LRP1B alterations seem to be related to a lower disease-free survival. Further investigations are needed to provide a rationale for the use of these markers to stratify prognosis in EGC patients.

Exploring the HIF-1α signalling pathway and the mechanism of YiQiHuoXue decoction against Precancerous Lesions of Gastric Cancer based on Network Pharmacology and Molecular Docking

Precancerous Lesions of Gastric Cancer (PLGC) are an essential step in the advancement of Gastric cancer (GC). Early intervention represents the most effective strategy to impede the development of PLGC. However, additional research is necessary to comprehend the molecular mechanism of PLGC. YQHXD is originated from Si Wu Decoction, has been utilized as an empirical formula for the treatment of PLGC for several years. In this study, we employed network pharmacology, molecular docking, and experimental validation to examine the inhibitory and ameliorative properties of YQHXD on PLGC. Multiple databases were utilized to gather genetic information on drugs in PLGC and YQHXD, in order to obtain cross-targets. We discovered 142 common targets between YQHXD and PLGC. GO and KEGG enrichment analyses indicate that YQHXD treatment of PLGC might be linked with cellular response to oxygen levels and the HIF-1α signaling pathway. Finally, we performed in vitro experiments, of which the results reveal that YQHXD mitigates gastric mucosal atrophy, intestinalization, and heterogeneous hyperplasia, and reduces the expression of inflammatory factors in rats. Therefore, we considered that YQHXD has the potential to delay the PLGC process by inhibiting the HIF-1α signaling pathway.

DNA methylation profiling identifies epigenetic signatures of early gastric cancer

Research on the DNA methylation status of gastric cancer (GC) has primarily focused on identifying invasive GC to develop biomarkers for diagnostic. However, DNA methylation in noninvasive GC remains unclear. We conducted a comprehensive DNA methylation profiling study of differentiated-type intramucosal GCs (IMCs). Illumina 850K microarrays were utilized to assess the DNA methylation profiles of formalin-fixed paraffin-embedded tissues from eight patients who were Epstein-Barr virus-negative and DNA mismatch repair proficient, including IMCs and paired adjacent nontumor mucosa. Gene expression profiling microarray data from the GEO database were analyzed via bioinformatics to identify candidate methylation genes. The final validation was conducted using quantitative real-time PCR, the TCGA methylation database, and single-sample gene set enrichment analysis (GSEA). Genome-wide DNA methylation profiling revealed a global decrease in methylation in IMCs compared with nontumor tissues. Differential methylation analysis between IMCs and nontumor tissues identified 449 differentially methylated probes, with a majority of sites showing hypomethylation in IMCs compared with nontumor tissues (66.1% vs 33.9%). Integrating two RNA-seq microarray datasets, we found one hypomethylation-upregulated gene: eEF1A2, overlapped with our DNA methylation data. The mRNA expression of eEF1A2 was higher in twenty-four IMC tissues than in their paired adjacent nontumor tissues. GSEA indicated that the functions of eEF1A2 were associated with the development of IMCs. Furthermore, TCGA data indicated that eEF1A2 is hypomethylated in advanced GC. Our study illustrates the implications of DNA methylation alterations in IMCs and suggests that aberrant hypomethylation and high mRNA expression of eEF1A2 might play a role in IMCs development.

Serum proteomic profiling of precancerous gastric lesions and early gastric cancer reveals signatures associated with systemic inflammatory response and metaplastic differentiation

The noninvasive detection technique using serum for large-scale screening is useful for the early diagnosis of gastric cancer (GC). Herein, we employed liquid chromatography mass spectrometry to determine the serum proteome signatures and related pathways in individuals with gastric precancerous (pre-GC) lesions and GC and explore the effect of Helicobacter pylori (H. pylori) infection. Differentially expressed proteins in GC and pre-GC compared with non-atrophic gastritis (NAG) group were identified. APOA4, a protein associated with metaplastic differentiation, and COMP, an extracellular matrix protein, were increased in the serum of patients with pre-GC lesions and GC. In addition, several inflammation-associated proteins, such as component C3, were decreased in the GC and pre-GC groups, which highlight a tendency for the inflammatory response to converge at the gastric lesion site during the GC cascade. Moreover, the abundance of proteins associated with oxidant detoxification was higher in the GC group compared with that in the NAG group, and these proteins were also increased in the serum of the H. pylori-positive GC group compared with that in the H. pylori-negative GC patients, reflecting the importance of oxidative stress pathways in H. pylori infection. Collectively, the findings of this study highlight pathways that play important roles in GC progression, and may provide potential diagnostic biomarkers for the detection of pre-GC lesions.

Identification of Immune Infiltrating Cell-Related Biomarkers in Early Gastric Cancer Progression

OBJECTIVES

Gastric cancer (GC) is one of the most prevalent malignancies worldwide, and early detection is crucial for improving patient survival rates. We aimed to identify immune infiltrating cell-related biomarkers in early gastric cancer (EGC) progression.

METHODS

The GSE55696 and GSE130823 datasets with low-grade intraepithelial neoplasia (LGIN), high-grade intraepithelial neoplasia (HGIN), and EGC samples were downloaded from the Gene Expression Omnibus database to perform an observational study. Immune infiltration analysis was performed by single sample gene set enrichment analysis and Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data. Weighted gene co-expression network analysis was used to explore the co-expression modules and genes, and further enrichment analysis was performed on these genes. A protein-protein interaction (PPI) network of these genes was constructed to identify biomarkers associated with EGC progression. Screened hub genes were validated by the rank sum test and reverse transcription quantitative polymerase chain reaction.

RESULTS

Immune scores were significantly elevated in EGC samples compared to LGIN and HGIN samples. The green-yellow module exhibited the strongest correlation with both immune score and disease progression. The 87 genes within this module were associated with the chemokine signaling pathways, the PI3K-Akt signaling pathways, leukocyte transendothelial migration, and Ras signaling pathways. Through PPI network analysis, the hub genes identified were protein tyrosine phosphatase receptor-type C (PTPRC), pleckstrin, CD53, CD48, lymphocyte cytosolic protein 1 (LCP1), hematopoietic cell-specific Lyn substrate 1, IKAROS Family Zinc Finger 1, Bruton tyrosine kinase, and Vav guanine nucleotide exchange factor 1. Notably, CD48, LCP1, and PTPRC showed high expression levels in EGC samples, with the remaining hub genes demonstrating a similar expression trend.

CONCLUSION

This study identified 9 immune cell-related biomarkers that may be actively involved in the progression of EGC and serve as potential targets for GC diagnosis and treatment.

Quantitative Analysis on Molecular Characteristics Evolution of Gastric Cancer Progression and Prognosis

The dynamic changes of key biological characteristics from gastric low-grade intraepithelial neoplasia (LGIN) to high-grade intraepithelial neoplasia (HGIN) to early gastric cancer (EGC) are still unclear, which greatly affect the accurate diagnosis and treatment of EGC and prognosis evaluation of gastric cancer (GC). In this study, bioinformatics methods/tools are applied to quantitatively analyze molecular characteristics evolution of GC progression, and a prognosis model is constructed. This study finds that some dysregulated differentially expressed mRNAs (DEmRNAs) in the LGIN stage may continue to promote the occurrence and development of EGC. Among the LGIN, HGIN, and EGC stages, there are differences and relevance in the transcription expression patterns of DEmRNAs, and the activation related to immune cells is very different. The biological functions continuously changed during the progression from LGIN to HGIN to EGC. The COX model constructed based on the three EGC-related DEmRNAs has GC prognostic risk prediction ability. The evolution of biological characteristics during the development of EGC mined by the authors provides new insight into understanding the molecular mechanism of EGC occurrence and development. The three-gene prognostic risk model provides a new method for assisting GC clinical treatment decisions.

Identification and validation of ferroptosis-related biomarkers and the related pathogenesis in precancerous lesions of gastric cancer

Using advanced bioinformatics techniques, we conducted an analysis of ferroptosis-related genes (FRGs) in precancerous lesions of gastric cancer (PLGC). We also investigated their connection to immune cell infiltration and diagnostic value, ultimately identifying new molecular targets that could be used for PLGC patient treatment. The Gene Expression Omnibus (GEO) and FerrDb V2 databases were used to identify FRGs. These genes were analysed via ClueGO pathways and Gene Ontology (GO) enrichment analysis, as well as single-cell dataset GSE134520 analysis. A machine learning model was applied to identify hub genes associated with ferroptosis in PLGC patients. Receiver Operating Characteristics (ROC) curve analysis was conducted to verify the diagnostic efficacy of these genes, and a PLGC diagnosis model nomogram was established based on hub genes. R software was utilized to conduct functional, pathway, gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) on the identified diagnostic genes. Hub gene expression levels and survival times in gastric cancer were analysed using online databases to determine the prognostic value of these genes. MCPcounter and single-sample gene set enrichment analysis (ssGSEA) algorithms were used to investigate the correlation between hub genes and immune cells. Finally, noncoding RNA regulatory mechanisms and transcription factor regulatory networks for hub genes were mapped using multiple databases. Eventually, we identified 23 ferroptosis-related genes in PLGC. Enrichment analyses showed that ferroptosis-related genes were closely associated with iron uptake and transport and ferroptosis in the development of PLGC. After differential analysis using machine learning algorithms, we identified four hub genes in PLGC patients, including MYB, CYB5R1, LIFR and DPP4. Consequently, we established a ferroptosis diagnosis model nomogram. GSVA and GSEA mutual verification analysis helped uncover potential regulatory mechanisms of hub genes. MCPcounter and ssGSEA analysed immune infiltration in the disease and indicated that B cells and parainflammation played an important role in disease progression. Finally, we constructed noncoding RNA regulatory networks and transcription factor regulatory networks. Our study identified ferroptosis-related diagnostic genes and therapeutic targets for PLGC, providing novel insights and a theoretical foundation for research into the molecular mechanisms, clinical diagnosis, and treatment of this disease.

Gastric precancerous lesions:occurrence, development factors, and treatment

Patients with gastric precancerous lesions (GPL) have a higher risk of gastric cancer (GC). However, the transformation of GPL into GC is an ongoing process that takes several years. At present, several factors including H.Pylori (Hp), flora imbalance, inflammatory factors, genetic variations, Claudin-4, gastric stem cells, solute carrier family member 26 (SLC26A9), bile reflux, exosomes, and miR-30a plays a considerable role in the transformation of GPL into GC. Moreover, timely intervention in the event of GPL can reduce the risk of GC. In clinical practice, GPL is mainly treated with endoscopy, acid suppression therapy, Hp eradication, a cyclooxygenase-2 inhibitor, aspirin, and diet. Currently, the use of traditional Chinese medicine (TCM) or combination with western medication to remove Hp and the use of TCM to treat GPL are common in Asia, particularly China, and have also demonstrated excellent clinical efficacy. This review thoroughly discussed the combining of TCM and Western therapy for the treatment of precancerous lesions as conditions allow. Consequently, this review also focuses on the causes of the development and progression of GPL, as well as its current treatment. This may help us understand GPL and related treatment.

PLEKHS1 drives PI3Ks and remodels pathway homeostasis in PTEN-null prostate

The PIP3/PI3K network is a central regulator of metabolism and is frequently activated in cancer, commonly by loss of the PIP3/PI(3,4)P2 phosphatase, PTEN. Despite huge research investment, the drivers of the PI3K network in normal tissues and how they adapt to overactivation are unclear. We find that in healthy mouse prostate PI3K activity is driven by RTK/IRS signaling and constrained by pathway feedback. In the absence of PTEN, the network is dramatically remodeled. A poorly understood YXXM- and PIP3/PI(3,4)P2-binding PH domain-containing adaptor, PLEKHS1, became the dominant activator and was required to sustain PIP3, AKT phosphorylation, and growth in PTEN-null prostate. This was because PLEKHS1 evaded pathway-feedback and experienced enhanced PI3K- and Src-family kinase-dependent phosphorylation of Y258XXM, eliciting PI3K activation. hPLEKHS1 mRNA and activating Y419 phosphorylation of hSrc correlated with PI3K pathway activity in human prostate cancers. We propose that in PTEN-null cells receptor-independent, Src-dependent tyrosine phosphorylation of PLEKHS1 creates positive feedback that escapes homeostasis, drives PIP3 signaling, and supports tumor progression.

A transcriptomic intratumour heterogeneity-free signature overcomes sampling bias in prognostic risk classification for hepatocellular carcinoma

Background & Aims

Intratumour heterogeneity (ITH) fosters the vulnerability of RNA expression-based biomarkers derived from a single biopsy to tumour sampling bias, and is regarded as an unaddressed confounding factor for patient precision stratification using molecular biomarkers. This study aimed to identify an ITH-free predictive biomarker in hepatocellular carcinoma (HCC).

Methods

We interrogated the confounding effect of ITH on performance of molecular biomarkers and quantified transcriptomic heterogeneity utilising three multiregional HCC transcriptome datasets involving 142 tumoural regions from 30 patients. A de novo strategy based on the heterogeneity metrics was devised to develop a surveillant biomarker (a utility gadget using RNA; AUGUR) using three datasets involving 715 liver samples from 509 patients with HCC. The performance of AUGUR was assessed in seven cross-platform HCC cohorts that encompassed 1,206 patients.

Results

An average discordance rate of 39.9% at the level of individual patients was observed applying 13 published prognostic signatures to classify tumour regions. We partitioned genes into four heterogeneity quadrants, from which we developed and validated a reproducible robust ITH-free expression signature AUGUR that showed significant positive associations with adverse features of HCC. High AUGUR risk increased the risk of disease progression and mortality independent of established clinicopathological indices, which maintained concordance across seven cohorts. Moreover, AUGUR compared favourably to the discriminative ability, prognostic accuracy, and patient risk concordant rates of 13 published signatures. Finally, a well-calibrated predictive nomogram integrating AUGUR and tumour-node-metastasis (TNM) stage was established, which generated a numerical probability of mortality.

Conclusions

We constructed and validated an ITH-free AUGUR and nomogram that overcame sampling bias and provided reliable prognostic information for patients with HCC.

Impact and Implications

Intratumour heterogeneity (ITH) is prevalent in hepatocellular carcinoma (HCC), and is regarded as an unaddressed confounding factor for biomarker design and application. We examined the confounding effect of transcriptomic ITH in patient risk classification, and found existing molecular biomarkers of HCC were vulnerable to tumour sampling bias. We then developed an ITH-free expression biomarker (a utility gadget using RNA; AUGUR) that overcame clinical sampling bias and maintained prognostic reproducibility and generalisability across multiple HCC patient cohorts from different commercial platforms. Furthermore, we established and validated a well-calibrated nomogram based on AUGUR and tumour-node-metastasis (TNM) stage that provided an individualised prognostic information for patients with HCC.

Study on the role and pharmacology of cuproptosis in gastric cancer

Objective

Gastric cancer has a poor prognosis and high mortality. Cuproptosis, a novel programmed cell death, is rarely studied in gastric cancer. Studying the mechanism of cuproptosis in gastric cancer is conducive to the development of new drugs, improving the prognosis of patients and reducing the burden of disease.

Methods

The TCGA database was used to obtain transcriptome data from gastric cancer tissues and adjacent tissues. GSE66229 was used for external verification. Overlapping genes were obtained by crossing the genes obtained by differential analysis with those related to copper death. Eight characteristic genes were obtained by three dimensionality reduction methods: lasso, SVM, and random forest. ROC and nomogram were used to estimate the diagnostic efficacy of characteristic genes. The CIBERSORT method was used to assess immune infiltration. ConsensusClusterPlus was used for subtype classification. Discovery Studio software conducts molecular docking between drugs and target proteins.

Results

We have established the early diagnosis model of eight characteristic genes (ENTPD3, PDZD4, CNN1, GTPBP4, FPGS, UTP25, CENPW, and FAM111A) for gastric cancer. The results are validated by internal and external data, and the predictive power is good. The subtype classification and immune type analysis of gastric cancer samples were performed based on the consensus clustering method. We identified C2 as an immune subtype and C1 as a non-immune subtype. Small molecule drug targeting based on genes associated with cuproptosis predicts potential therapeutics for gastric cancer. Molecular docking revealed multiple forces between Dasatinib and CNN1.

Conclusion

The candidate drug Dasatinib may be effective in treating gastric cancer by affecting the expression of the cuproptosis signature gene.

Establishment and Validation of a Pathologic Upgrade Prediction Nomogram Model for Gastric Low-Grade Intraepithelial Neoplasia Patients After the Eradication of Helicobacter pylori

BACKGROUND

As yet, there is no unified method of treatment for the evaluation and management of gastric low-grade intraepithelial neoplasia (LGIN) worldwide.

METHODS

Patients with gastric LGIN who had been treated with Helicobacter pylori eradication were gathered retrospectively. Based on several relevant characteristics described and analyzed by LASSO regression analysis and multivariable logistic regression, a prediction nomogram model was established. C-index, the area under the receiver operating characteristic curve (AUC), calibration plot, and decision curve analysis (DCA) were adopted to evaluate the accuracy and reliability of the model.

RESULTS

A total of 309 patients with LGIN were randomly divided into the training groups and the validation groups. LASSO regression analysis and multivariable logistic regression identified that 6 variables including gender, size, location, borderline, number, and erosion were independent risk factors. The nomogram model displayed good discrimination with a C-index of .765 (95% confidence interval: .702-.828). The accuracy and reliability of the model were also verified by an AUC of .764 in the training group and .757 in the validation group. Meanwhile, the calibration curve and the DCA suggested that the predictive nomogram had promising accuracy and clinical utility.

CONCLUSIONS

A predictive nomogram model was constructed and proved to be clinically applicable to identify high-risk groups with possible pathologic upgrade in patients with gastric LGIN. Since it is regarded that strengthening follow-up or endoscopic treatment of high-risk patients may contribute to improving the detection rate or reducing the incidence of gastric cancer, the predictive nomogram model provides a reliable basis for the treatment of LGIN.

Alterations of Microorganisms in Tongue Coating of Gastric Precancerous Lesion Patients with a Damp Phlegm Pattern

Objective. In the research, the microbial changes in the tongue coating of patients with a damp phlegm pattern of gastric precancerous lesion (GPL) were investigated. Methods. This was a case-control study, in which 80 tongue coating samples were collected including 40 patients with a damp phlegm pattern of GPL, 20 patients with a nondamp phlegm pattern of GPL, and 20 healthy control people. The 16S rRNA microbiome technology was used to analyze the alterations of microorganisms in tongue coating of GPL patients with a damp phlegm pattern. Results. Microorganisms in the genus level were analyzed. Compared with the healthy control group, the relative abundance of 4 microorganisms (Solobacterium, Rothia, Oribacterium, and Alloprevotella) in the GPL group was significantly higher ( $P<0.05$ ). The relative abundance of 10 microorganisms (Terrisporobacter, Solobacterium, Porphyromonas, Parvimonas, Lactobacillus, Johnsonella, Gemella, Fusibacter, Azoarcus, and Acidothermus) in the GPL damp phlegm pattern group was significantly lower than that in the GPL nondamp phlegm pattern group ( $P<0.05$ ). In the comparison of phenotype “forms biofilms,” the relative abundance of microorganisms in the GPL group was significantly higher than that in the healthy control group ( $P<0.05$ ). In the comparison of phenotype “contains mobile elements,” the relative abundance of microorganisms in the GPL damp phlegm pattern group was significantly lower than that in the GPL nondamp phlegm pattern group ( $P<0.05$ ). In the comparison of microbial metabolic functions, the abundance ratio of “infectious diseases: bacterial” in the GPL group was significantly lower than that in the healthy control group ( $P<0.05$ ). The abundance ratio of the “excretory system” and “folding, sorting, and degradation” in the GPL group was significantly higher than that in the healthy control group ( $P<0.05$ ). Conclusions. Solobacterium may be a marker microorganism of the GPL damp phlegm pattern. The differential phenotype of microorganisms in tongue coating of the GPL damp tongue pattern is mainly reflected in “forms biofilms” and “contains mobile elements.”

The Roles of Immune Cells in Gastric Cancer: Anti-Cancer or Pro-Cancer?

Simple Summary

Gastric cancer is still one of the leading causes of death caused by cancer in developing countries. The emerging role of immunotherapy in cancer treatment has led to more research to elucidate the roles of essential immune cells in gastric cancer prognosis. We reviewed the roles of immune cells including T cells, B cells, dendritic cells, macrophages and natural killer cells in gastric cancer. Although the studies conducted on the roles of immune cells in gastric cancer pathogenesis produced conflicting results, understanding the roles of immune cells in gastric cancer will help us to harness them for application in immunotherapy for better prognosis and management of gastric cancer patients.

Abstract

Despite the fact that the incidence of gastric cancer has declined over the last decade, it is still the world’s leading cause of cancer-related death. The diagnosis of early gastric cancer is difficult, as symptoms of this cancer only manifest at a late stage of cancer progression. Thus, the prognosis of gastric cancer is poor, and the current treatment for improving patients’ outcomes involves the application of surgery and chemotherapy. Immunotherapy is one of the most recent therapies for gastric cancer, whereby the immune system of the host is programmed to combat cancer cells, and the therapy differs based upon the patient’s immune system. However, an understanding of the role of immune cells, namely the cell-mediated immune response and the humoral immune response, is pertinent for applications of immunotherapy. The roles of immune cells in the prognosis of gastric cancer have yielded conflicting results. This review discusses the roles of immune cells in gastric cancer pathogenesis, specifically, T cells, B cells, macrophages, natural killer cells, and dendritic cells, as well as the evidence presented thus far. Understanding how cancer cells interact with immune cells is of paramount importance in designing treatment options for gastric cancer immunotherapy.

Manpixiao Decoction Halted the Malignant Transformation of Precancerous Lesions of Gastric Cancer: From Network Prediction to In-Vivo Verification

Manpixiao decoction (MPX), a traditional Chinese medicine formula, is mainly used to improve the gastric mucosal pathology and stomach discomfort in patients with gastric precancerous lesions. Precancerous lesion of gastric cancer (PLGC) refers to intestinal metaplasia and/or dysplasia based on gastric mucosal atrophy. Effective prevention and treatment of PLGC is of great significance to reduce the incidence of gastric cancer. Because of the complexity of the etiology and pathogenesis of PLGC, there is no unified and effective treatment plan in western medicine. In recent years, traditional Chinese medicine has shown obvious advantages in the treatment of PLGC and the prevention of its further progression to gastric cancer, relying on its multi-approach and multi-target comprehensive intervention characteristics. This study is designed to examine the protective effect of MPX against PLGC and further to reveal the engaged mechanism via integrating network pharmacology and in vivo experimental evidence. Network pharmacology results demonstrated that inflammation, immune responses, and angiogenesis might be associated with the efficacy of MPX in the treatment of PLGC, in which the PI3K-Akt, cellular senescence, P53 and protein processing in endoplasmic reticulum were involved. Then, we established a rat model of PLGC using a combination of N-methyl-N′-nitro-N-nitrosoguanidine (MNNG), sodium salicylate, irregular fasting, and ranitidine, and observed the effects after MPX treatment. Our result showed that MPX improved the pathological condition of gastric mucosa in PLGC rats and reduced the incidence of gastric cancer. Next, the analysis of serum inflammatory cytokines showed that MPX reduced the inflammation-related cytokines (such as IL-1α, IL-7, CSF-1, and CSF-3) in the serum. Additionally, MPX also had a regulation effect on the “protein/protein phosphorylation-signaling pathway” network in the core region of the PLGC rats. It is showed that MPX can inhibit the phosphorylation of PI3K-AKT, and downregulates the EGFR, β-catenin, and N-cadherin protein levels. These results indicate that MPX halted the PLGC progression through inhibiting EGFR-PI3K-AKT related epithelial-mesenchymal transition process.

Proteomic Analysis Reveals Molecular Differences in the Development of Gastric Cancer

Gastric cancer (GC) is the 3rd leading cause of death from cancer and the 5th most common cancer worldwide. The detection rate of GC among Tibetans is significantly higher than that in Han Chinese, probably due to differences in their living habits, dietary structure, and environment. Despite such a high disease burden, the epidemiology of gastric cancer has not been studied in this population. Molecular markers are required to aid the diagnosis and treatment of GC. In this study, we collected gastric tissue samples from patients in Tibet with chronic nonatrophic gastritis (CNAG) (n = 6), chronic atrophic gastritis (CAG) (n = 7), gastric intraepithelial neoplasia (GIN) (n = 4), and GC (n = 5). The proteins in each group were analyzed using coupled label-free mass spectrometry. In addition, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, and protein interaction networks were used to analyze the differentially expressed proteins (DEPs) among groups. DEPs were quantified in comparisons of GC versus CNAG (223), GC versus GIN (100), and GIN versus CNAG (341). GO and KEGG analyses showed that the DEPs were mainly associated with immunity (GC versus CNAG) and cancer proliferation and metastasis (GC versus GIN, and GIN versus CNAG). Furthermore, the expression levels of cell proliferation and cytoskeleton-related proteins increased consistently during cancer development, such as ITGA4, DDC, and CPT1A; thus, they are potential diagnostic markers. These results obtained by proteomics analysis could improve our understanding of cancer biology in GC and provide a rich resource for data mining and discovering potential immunotherapy targets.

Application of next-generation sequencing in the diagnosis of gastric cancer

Objectives: Gastric cancer (GC) is a disease with high mortality, poor prognosis and numerous risk factors. GC has an asymptomatic nature in early stages of the diseases, making timely diagnosis complicated using common conventional approaches, namely pathological examinations and imaging tests. Recently, molecular profiling of GC using next generation sequencing (NGS) has opened new doors to efficient prognostic, diagnostic, and therapeutic strategies. The current review aims to thoroughly discuss and compare the current NGS techniques and commercial platforms utilized for GC diagnosis and treatment, highlighting the most recent NGS-based GC studies. Furthermore, this review addresses the challenges of clinical implementation of NGS in GC.Materials and methods: This review was conducted according to the eligible studies identified via search of Web of Science, PubMed, Scopus, Embase and the Cochrane Library. In the present study, data on gastric cancer patients and NGS methods used to diagnose the disease were reviewed.Conclusion: Given the ever-rising advancements in NGS technologies, bioinformatics, healthcare guidelines and refined classifications, it is hoped that these technologies can actualize their advantages and optimize GC patients' experience.

A Single-Center Follow-Up Study of Low-Grade Gastric Intraepithelial Neoplasia and the Screening of Key Genes of Precancerous Lesions

Objective

The study aimed to summarize the morphological characteristics of low-grade gastric intraepithelial neoplasia (LGIN) and explore its outcomes and risk factors. Additionally, it aimed to screen the core different expression genes (DEGs) of high-grade gastric intraepithelial neoplasia (HGIN) using bioinformatics methods to identify biomarkers for early gastric cancer outcomes.

Methods

The clinical and pathological data of 449 patients with LGIN in the endoscopy center of the Second Hospital of Hebei Medical University from June 2013 to September 2018 were collected for retrospective analysis. The GSE130823 and GSE55696 data sets were selected from the Gene Expression Omnibus database, and the GEO2R tool was used to screen DEGs in HGIN and chronic gastritis tissue types. A DEG functional enrichment analysis was conducted using the Database for Annotation, Visualization, and Integrated Discovery. The STRING database was utilized to create a protein–protein interaction network, and the CytoHubba plug-in was used to screen the key genes of HGIN.

Results

The incidence of LGIN increased with age, and most of the patients were aged between 45–59 years (P = 0.048). Lesions were found mainly in the cardia, mostly in people aged 60 (P < 0.05). Progression occurred in 42 of 449 patients, with a 9.4% rate of cancer development. Foci larger than 10 mm, ulcerative lesions, and an Helicobacter pylori-positive result were factors affecting the outcome of LGIN (P < 0.05). Seven core genes of HGIN were screened, including MYC, SOX2, CDX2, TBX3, KRT7, CDKN2A, and MUC5AC.

Conclusion

The patients with LGIN reflected the potential for developing cancer. A magnifying gastroscope can contribute to the detection of early gastric cancer. Additionally, the MYC, CDX2, and TBX3 genes may act as specific biomarkers of HGIN.

Telomere maintenance mechanism dysregulation serves as an early predictor of adjuvant therapy response and a potential therapeutic target in human cancers

Telomere maintenance mechanisms (TMMs) rescue cells from telomere crisis, endow cells immortal property, stabilize genomic integrity. However, TMM-associated molecular profiles and their clinical outcomes in cancer remain elusive. Here, we performed a pan-cancer and integrated analysis of TMM gene expression profiles from 10,107 unique samples with clinicopathological, molecular and outcome features across 7 malignancies from the same microarray platform (Affymetrix GPL570 platform). This resource was divided into Case-Control datasets for obtaining dysregulated TMM genes and Survival datasets for evaluating clinical outcomes. Multidimensional data from The Cancer Genome Atlas (TCGA) were used to elucidate associations between TMM dysregulation and survival, genomic instability. Our results demonstrated that TMMs had a consistent dysregulation spectrum across cancers, based on which we developed the TMM-dysregulation signature TMScore that was positively associated with various tumor adverse features. Two opposite prognostic patterns of TMScore independent of clinicopathological and molecular characteristics were identified, which might be explained by genomic instability: breast and lung cancer patients with elevated TMScore had inferior outcomes, suggesting TMScore-related genes as potential therapeutic targets, on the contrary, colon and stomach cancer patients had superior outcomes. Most important, the prognostic value of TMScore was still significant regardless of whether patients had received adjuvant therapy, which was valuable for discriminating non-responders from responders, and could predict the effectiveness of adjuvant therapy. In summary, our resources delineate TMMs dysregulated landscape across cancers, shed light on the impact of TMMs dysregulation on patient outcomes and adjuvant therapy, and provide novel therapeutic opportunities for cancer treatment.

Proposed Models for Prediction of Mortality in Stage-I and Stage-II Gastric Cancer and 5 Years after Radical Gastrectomy

The current American Joint Committee on Cancer (AJCC) staging system provides limited information for patients with early death from stage-I and stage-II gastric cancer (GC) and death at >5 years after radical gastrectomy. The aim of this study was to construct nomogram models to predict the mortality risk of these patients. In this study, clinical and pathological data on patients who underwent curative gastrectomy at Harbin Medical University Cancer Hospital between 2000 and 2014 were retrospectively collected. Receiver operating characteristic analysis was used to screen for sensitive serum immune biomarkers to predict the risk of mortality death >5 years after radical gastrectomy (Group A) and risk of early death in stage-I and stage-II GC (Group B). The prediction model was constructed by combining serum immune markers with clinicopathological features by R Studio. We found that serum fibrinogen (F), systemic immune inflammation (SII), and pTNM stage were independent risk factors for prognosis in Group A (P < 0.05). F, SII, age, Borrmann type, and scope of gastrectomy were independent risk factors for prognosis in Group B (P < 0.05). The area under the curve of the predictive model in Groups A and B was 0.726 and 0.848, respectively. In conclusion, the predictive models of F and SII combined with clinicopathological features can predict high mortality risk in patients with stage-I and stage-II GC and >5 years after radical gastrectomy, which will contribute to the supplement of the traditional AJCC system and to individual survival prediction.

CXCR4 is a Novel Biomarker Correlated With Malignant Transformation and Immune Infiltrates in Gastric Precancerous Lesions

Background: As early gastric cancer (EGC) has a far better prognosis than advanced gastric cancer (GC), early diagnosis and treatment are essential. However, understanding the mechanism of the process from gastric precancerous lesion (GPL) becoming EGC has made little advances. Besides, biomarkers that can monitor the progression of GPL-to-GC are still much insufficient. Methods: Key gene modules associated with GPL progression to EGC were identified by integrating two GPL-related data sets, GSE55696 and GSE130823, using the WGCNA method. Combining with the TCGA-STAD cohort, hub genes were identified. Immunofluorescence was conducted to validate the expression. To explore the implication of hub genes in GPL malignant transformation, a correlation test was conducted to identify their co-expression genes, co-expression cytokines, and co-expression immune cells. Least absolute shrinkage and selection operator (LASSO) Cox regression was applied to shrink CXCR4-related predictors and construct a prognostic model. Functional enrichment was applied for exploring the potential mechanism. Results: The green module in GSE55696 and the yellow module in GSE130823 were regarded as key gene modules associated with GPL progression to EGC, and 219 intersection genes from them were mainly enriched in critical immune biological processes. Combining with the TCGA-STAD cohort, CXCR4 was identified as a novel biomarker correlated with the malignant transformation of GPL, the positive rate of which was increased with GPL progression according to immunofluorescence. CXCR4 co-expression genes were found mainly involved in regulation of actin. CXCR4 co-expression cytokines were enriched in regulation of chemotaxis, cell chemotaxis, mononuclear cell migration, leukocyte chemotaxis, etc. As for co-expression immune cells, the expression level of CXCR4 was positively correlated with the abundance of macrophages but negatively correlated with that of effector memory T cells and NKT cells during GPL malignant transformation. In addition, the CXCR4-related prognostic model was able to predict the prognosis of GC and serve as an independent predictor for overall survival (OS). Conclusions: CXCR4 was a novel biomarker correlated with malignant transformation of GPL and played a vital role in the control of tumor immunity. CXCR4 is possible to serve as a therapeutic target for malignant transformation of GPL.

MustSeq, an alternative approach for multiplexible strand-specific 3' end sequencing of mRNA transcriptome confers high efficiency and practicality

RNA-seq has been widely used to reveal the molecular mechanism of variants of life process. We have developed an alternative method, MustSeq, which generates multiple second strands along a single 1^st strand cDNA by random-priming initiation, immediately after reverse transcription for each RNA extract using sample-barcoded poly-dT primers, then 3' ends-enriching PCR is applied to construct the library. Unlike the conventional RNA seq, MustSeq avoids procedures such as mRNA isolation, fragmentation and RNA 5'-end capture, enables early pooling of multiple samples, and requires only one twentieth of sequencing reads of full-length sequencing. We demonstrate the power and features of MustSeq comparing with TruSeq and NEBNext RNA-seq, two conventional full-length methods and QuantSeq, an industrial 3' end method. In cancer cell lines, the reads distribution of CDS-exon as well as genes, lncRNAs and GO terms detected by MustSeq are closer than QuantSeq to TruSeq. In mouse hepatocarcinoma and healthy livers, MustSeq enriches the same pathways as by NEBNext, and reveals the molecular profile of carcinogenesis. Overall MustSeq is a robust and accurate RNA-seq method allowing efficient library construction, sequencing and analysis, particularly valuable for analysis of differentially expressed genes with a large number of samples. MustSeq will greatly accelerate the application of bulk RNA-seq on different fields, and potentially applicable for single cell RNA-seq.

Molecular Landscapes of Gastric Pre-Neoplastic and Pre-Invasive Lesions

Gastric carcinoma (GC) represents one of the most common and most lethal malignancies worldwide. The histopathological characterization of GC precursor lesions has provided great knowledge about gastric carcinogenesis, with the consequent introduction of effective strategies of primary and secondary prevention. In recent years, a large amount of data about the molecular events in GC development is emerging, flanking the histomorphological descriptions. In this review, we describe the landscape of molecular alterations in gastric pre-invasive lesions with a glance at their potential use in the diagnostic and therapeutic decision-making process.

Construction and Validation of a Novel Prognostic Signature for Intestinal Type of Gastric Cancer

Background

Intestinal type of gastric cancer (IGC) is the largest subtype of gastric cancer (GC) by Lauren classification. The purpose of this present study was to construct a prognostic signature for IGC patients, based on the high-grade dysplasia (HGD) and IGC tissues, to improve and enhance the prognostic accuracy.

Methods

The microarray datasets and associated clinical characteristics of HGD and IGC were obtained from the Gene Expression Omnibus (GEO) database. Based on the differential expression analysis between HGD and IGC, the prognostic-related differential expression genes (DEGs) were identified in a training set by univariate COX regression analysis. The least absolute shrinkage and selection operator (LASSO) regression was used to construct an optimal prognostic signature. The enrichment analysis was performed by using Gene Set Enrichment Analysis (GSEA). The performance of the nomogram was assessed by the calibration curve and concordance index (C-index). The results were validated by using a testing set.

Results

We identified 35 prognostic-related DGEs in the training set. The nine-gene signature was established by LASSO analysis. The nine-gene signature was an independent risk factor in both the training and testing sets. The areas under the curve (AUC) values of receiver operating characteristic (ROC) analysis were 0.733 and 0.700 for the training and testing sets, respectively. In GSEA analysis, the gene expression in high-risk group was enriched in hedgehog signaling, epithelial mesenchymal transition, and angiogenesis. The nomogram for IGC showed good performance with C-index of 0.81 (95% CI: 0.76-0.86) and 0.70 (95% CI: 0.63-0.77) in the training and testing sets, respectively.

Conclusion

We identified and verified a nine-gene signature for the prognostic prediction of IGC patients, which might identify subgroups of IGC patients and select more suitable therapeutic options.

Differences in Somatic Mutation Profiles between Korean Gastric Cancer and Gastric Adenoma Patients

BACKGROUND

We aimed to investigate molecular factors potentially related to the progression of gastric adenoma (GA) to gastric cancer (GC) and compare the mutation characteristics between GC and GA.

METHODS

We conducted custom gene panel sequencing for 135 GC-related genes and estimated the difference in somatic mutation profiles between 20 GC and 20 GA cases.

RESULTS

A total of 31 somatic mutations, including 22 missense, 3 nonsense, and 6 frameshift mutations, were detected in 17 samples. We estimated an average of 1.8 mutations per sample (range, 1 to 3 mutations), with 12 in GC and 5 in GA. GC tended to have one or more mutated genes (p = 0.0217), as well as higher allele frequencies of mutated genes (p = 0.0003), compared to GA. Likewise, known driver mutations associated with GC tumorigenesis (TP53, ERBB2, PIK3CA, and RNF43) were identified in half of the GC cases (50%, 10/20; p = 0.0002). Only the mutant burden, regardless of gene type, was retained, with an odds ratio of 1.8392 (95% confidence interval (CI), 1.0071 to 3.3588; p = 0.0474).

CONCLUSION

Our study demonstrates that the accumulation of mutant burden contributes to tumorigenesis progression from GA to GC in Korean patients, regardless of the kind of genes. These findings may elucidate the molecular pathogenesis of gastric carcinogenesis and malignant progression.

Identification of key genes and biological processes contributing to colitis associated dysplasia in ulcerative colitis

Background

Ulcerative colitis-associated colorectal cancer (UC-CRC) is a life-threatening complication of ulcerative colitis (UC). The mechanisms underlying UC-CRC remain to be elucidated. The purpose of this study was to explore the key genes and biological processes contributing to colitis-associated dysplasia (CAD) or carcinogenesis in UC via database mining, thus offering opportunities for early prediction and intervention of UC-CRC.

Methods

Microarray datasets (GSE47908 and GSE87466) were downloaded from Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) between groups of GSE47908 were identified using the “limma” R package. Weighted gene co-expression network analysis (WGCNA) based on DEGs between the CAD and control groups was conducted subsequently. Functional enrichment analysis was performed, and hub genes of selected modules were identified using the “clusterProfiler” R package. Single-gene gene set enrichment analysis (GSEA) was conducted to predict significant biological processes and pathways associated with the specified gene.

Results

Six functional modules were identified based on 4929 DEGs. Green and blue modules were selected because of their consistent correlation with UC and CAD, and the highest correlation coefficient with the progress of UC-associated carcinogenesis. Functional enrichment analysis revealed that genes of these two modules were significantly enriched in biological processes, including mitochondrial dysfunction, cell-cell junction, and immune responses. However, GSEA based on differential expression analysis between sporadic colorectal cancer (CRC) and normal controls from The Cancer Genome Atlas (TCGA) indicated that mitochondrial dysfunction may not be the major carcinogenic mechanism underlying sporadic CRC. Thirteen hub genes (SLC25A3, ACO2, AIFM1, ATP5A1, DLD, TFE3, UQCRC1, ADIPOR2, SLC35D1, TOR1AIP1, PRR5L, ATOX1, and DTX3) were identified. Their expression trends were validated in UC patients of GSE87466, and their potential carcinogenic effects in UC were supported by their known functions and other relevant studies reported in the literature. Single-gene GSEA indicated that biological processes and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to angiogenesis and immune response were positively correlated with the upregulation of TFE3, whereas those related to mitochondrial function and energy metabolism were negatively correlated with the upregulation of TFE3.

Conclusions

Using WGCNA, this study found two gene modules that were significantly correlated with CAD, of which 13 hub genes were identified as the potential key genes. The critical biological processes in which the genes of these two modules were significantly enriched include mitochondrial dysfunction, cell-cell junction, and immune responses. TFE3, a transcription factor related to mitochondrial function and cancers, may play a central role in UC-associated carcinogenesis.

Review: Gastric cancer: Basic aspects

Gastric cancer is still one of the most prevalent and deadliest cancers in the world. Although our knowledge about the disease has progressed extraordinarily, this has not been accompanied by our capacity to effectively treat the disease. In the last years, immunotherapy made its way into the cancer field and was responsible for major changes in the treatment success rates for several cancer types. Although gastric cancer was not among the first successful targets of this type of therapy, the relationship between this type of cancer, immunosurveillance and immunotherapy is now being actively researched. In this article, we review the literature of the past year regarding the relationship between gastric cancer, its immune microenvironment and response to immunotherapy. Published data indicate that the immune microenvironment influences the clinical behaviour of gastric cancer, and is correlated with its histologic and molecular subtypes with an emphasis on the microsatellite- and EBV-positive tumour subgroups. Although the literature regarding response to immunotherapy is scarce, there is good evidence that patient stratification for immunotherapy is going to become a reality in gastric cancer.