Potential Biomarker For Gastric Cancer Research Articles

Gut metagenomic analysis of gastric cancer patients reveals Akkermansia, Gammaproteobacteria, and Veillonella microbiota as potential non-invasive biomarkers

The goal of the study was to investigate the changes in the gut microbiota during the advancement of gastric cancer (GC) and identify pertinent taxa associated with the disease. We used a public fecal amplicon gastric cancer dataset from the Sequence Retrieval Archive (SRA), of patients with GC, gastritis, and healthy individuals. We did sequence pre-processing, including quality filtering of the sequences. Then, we performed a diversity analysis, evaluating α- and β-diversity. Next, taxonomic composition analysis was performed and the relative abundances of different taxa at the phylum and genus levels were compared between GC, gastritis, and healthy controls. The obtained results were subsequently subjected to statistical validation. To conclude, metagenomic function prediction was carried out, followed by correlation analysis between the microbiota and KEGG pathways. α analysis revealed a significant difference between male and female categories, while β analysis demonstrated significant distinctions between GC, gastritis, and healthy controls, as well as between sexes within the GC and gastritis groups. The statistically confirmed taxonomic composition analysis highlighted the presence of the microbes Bacteroides and Veillonella. Furthermore, through metagenomic prediction analysis and correlation analysis with pathways, three taxa, namely Akkermansia, Gammaproteobacteria, and Veillonella, were identified as potential biomarkers for GC. Additionally, this study reports, for the first time, the presence of two bacteria, Desulfobacteriota and Synergistota, in GC, necessitating further investigation. Overall, this research sheds light on the potential involvement of gut microbiota in GC pathophysiology; however, additional studies are warranted to explore its functional significance.

Volatilomic profiles of gastric juice in gastric cancer patients

Volatilomics is a powerful tool capable of providing novel biomarkers for the diagnosis of gastric cancer. The main objective of this study was to characterize the volatilomic signatures of gastric juice in order to identify potential alterations induced by gastric cancer. Gas chromatography with mass spectrometric detection, coupled with headspace solid phase microextraction as the pre-concentration technique, was used to identify volatile organic compounds (VOCs) released by gastric juice samples collected from 78 gastric cancer patients and two cohorts of controls (80 and 96 subjects) from four different locations (Latvia, Ukraine, Brazil, and Colombia). 1440 distinct compounds were identified in samples obtained from patients and 1422 in samples provided by controls. However, only 6% of the VOCs exhibited an incidence higher than 20%. Amongst the volatiles emitted, 18 showed differences in their headspace concentrations above gastric juice of cancer patients and controls. Ten of these (1-propanol, 2,3-butanedione, 2-pentanone, benzeneacetaldehyde, 3-methylbutanal, butylated hydroxytoluene, 2-pentyl-furan, 2-ethylhexanal, 2-methylpropanal and phenol) appeared at significantly higher levels in the headspace of the gastric juice samples obtained from patients; whereas, eight species showed lower abundance in patients than found in controls. Given that the difference in the volatilomic signatures can be explained by cancer-related changes in the activity of certain enzymes or pathways, the former set can be considered potential biomarkers for gastric cancer, which may assist in developing non-invasive breath tests for the diagnosis of this disease. Further studies are required to elucidate further the mechanisms that underlie the changes in the volatilomic profile as a result of gastric cancer.

Integrated analysis of transcriptome and epigenome reveals ENSR00000272060 as a potential biomarker in gastric cancer.

Background: Enhancer RNAs (eRNAs) are involved in gene expression regulation. Although functional roles of eRNAs in the pathophysiology of neoplasms have been reported, their involvement in gastric cancer (GC) is less known. Materials & methods: A network-based integrative approach was utilized for analyzing transcriptome and epigenome alterations in GC, and an eRNA was selected for experimental validation. Survival analysis and clinicopathological associations were also performed. Results: A hub eRNA, ENSR00000272060, showed significantly increased expression in tumor versus nontumor tissues, as well as an association with clinicopathological features. A seven-gene prognostic model was also constructed. Conclusion: The constructed network provides a comprehensive understanding of the underlying processes implicated in the progression of GC, along with a starting point from which to derive potential diagnostic/prognostic biomarkers.

Nucleosome assembly protein 1-like 1 (NAP1L1) in gastric cancer patients: a potential biomarker with diagnostic and prognostic utility

Background The nucleosome assembly protein 1-like 1 (NAP1L1) is suggested to have an oncogenic role in several tumors based on its overexpression. However, its diagnostic and prognostic role in gastric cancer remains unclarified. This study aimed to evaluate the diagnostic and prognostic utility of NAP1L1 in gastric cancer patients. Methods A total of 85 patients [mean (SD) age: 60.9 (1.6) years, 49.4% were males] with newly-diagnosed gastric cancer and 40 healthy individuals [mean (SD) age: 60.7 (1.7) years, 52.5% were males] were included. Data on patient demographics (age, gender), TNM stages and tumor size, and the serum NAP1L1 levels were recorded. Results Serum NAP1L1 levels were significantly higher in gastric cancer patients than in control subjects [12 (9.5–13.8) vs. 1.8 (1.5–2.4) ng/mL, p < 0.001]. Also, certain tumor characteristics such as tumor size of >4 vs. <4 cm (p < 0.001), M1 vs. M0 stage (p < 0.001), N2 vs. N0 and N1 stage (p < 0.001), and T4 vs. lower T stage (p < 0.001) were associated with significantly higher serum NAP1L1 levels in gastric cancer patients. Conclusions Our findings revealed for the first time that serum levels for NAP1L1 were overexpressed in the gastric cancer, as also correlated with the disease progression. NAP1L1 seems to be a potential biomarker for gastric cancer, providing clinically important information on early diagnosis and risk stratification.

Identification of novel biomarkers with potential for diagnosis and prognosis of gastric cancer: a Bioinformatics Approach

Introduction: Gastric cancer (GC) is the fifth most diagnosed neoplasia and the third leading cause of cancer-related deaths. A substantial number of patients exhibit an advanced GC stage once diagnosed. Therefore, the search for biomarkers contributes to the improvement and development of therapies. Objective: This study aimed to identify potential GC biomarkers making use of in silico tools. Methods: Gastric tissue microarray data available in Gene Expression Omnibus and The Cancer Genome Atlas Program was extracted. We applied statistical tests in the search for differentially expressed genes between tumoral and non-tumoral adjacent tissue samples. The selected genes were submitted to an in-house tool for analyses of functional enrichment, survival rate, histological and molecular classifications, and clinical follow-up data. A decision tree analysis was performed to evaluate the predictive power of the potential biomarkers. Results: In total, 39 differentially expressed genes were found, mostly involved in extracellular structure organization, extracellular matrix organization, and angiogenesis. The genes SLC7A8, LY6E, and SIDT2 showed potential as diagnostic biomarkers considering the differential expression results coupled with the high predictive power of the decision tree models. Moreover, GC samples showed lower SLC7A8 and SIDT2 expression, whereas LY6E was higher. SIDT2 demonstrated a potential prognostic role for the diffuse type of GC, given the higher patient survival rate for lower gene expression. Conclusion: Our study outlines novel biomarkers for GC that may have a key role in tumor progression. Nevertheless, complementary in vitro analyses are still needed to further support their potential.

Exosomal hsa_circ_000200 as a potential biomarker and metastasis enhancer of gastric cancer via miR-4659a/b-3p/HBEGF axis

BackgroundExosome, a component of liquid biopsy, loaded protein, DNA, RNA and lipid gradually emerges as biomarker in tumors. However, exosomal circRNAs as biomarker and function mechanism in gastric cancer (GC) are not well understood.MethodsDifferentially expressed circRNAs in GC and healthy people were screened by database. The identification of hsa_circ_000200 was verified by RNase R and sequencing, and the expression of hsa_circ_000200 was evaluated using qRT-PCR. The biological function of hsa_circ_000200 in GC was verified in vitro. Western blot, RIP, RNA fluorescence in situ hybridization, and double luciferase assay were utilized to explore the potential mechanism of hsa_circ_000200.ResultsHsa_circ_000200 up-regulated in GC tissue, serum and serum exosomes. Hsa_circ_000200 in serum exosomes showed better diagnostic ability than that of tissues and serum. Combined with clinicopathological parameters, its level was related to invasion depth, TNM staging, and distal metastasis. Functionally, knockdown of hsa_circ_000200 inhibited GC cells proliferation, migration and invasion in vitro, while its overexpression played the opposite role. Importantly, exosomes with up-regulated hsa_circ_000200 promoted the proliferation and migration of co-cultured GC cells. Mechanistically, hsa_circ_000200 acted as a “ceRNA” for miR-4659a/b-3p to increase HBEGF and TGF-β/Smad expression, then promoted the development of GC.ConclusionsOur findings suggest that hsa_circ_000200 promotes the progression of GC through hsa_circ_000200/miR-4659a/b-3p/HBEGF axis and affecting the expression of TGF-β/Smad. Serum exosomal hsa_circ_000200 may serve as a potential biomarker for GC.

Identification of INHBA as a potential biomarker for gastric cancer through a comprehensive analysis

Inhibin subunit beta A (INHBA) is a member of the transforming growth factor-beta (TGF-β) superfamily that plays a fundamental role in various cancers. However, a systematic analysis of the exact role of INHBA in patients with gastric cancer (GC) has not yet been conducted. We evaluated the expression levels of INHBA and the correlation between INHBA and GC prognosis in GC. The relationship between INHBA expression, immune infiltration levels, and type markers of immune cells in GC was also explored. In addition, we studied INHBA mutations, promoter methylation, and functional enrichment analysis. Besides, high expression levels of INHBA in GC were significantly related to unfavorable prognosis. INHBA was negatively correlated with B cell infiltration, but positively correlated with macrophage and most anticancer immunity steps. INHBA expression was positively correlated with the type markers of CD8+ T cells, neutrophils, macrophages, and dendritic cells. INHBA has a weak significant methylation level change between tumor and normal tissues and mainly enriched in cancer-related signaling pathways. The present study implies that INHBA may serve as a potential biomarker for predicting the prognosis of patients with GC. INHBA is a promising predictor of immunotherapy response, with higher levels of INHBA indicating greater sensitivity.

EBV antibody and gastric cancer risk: a population-based nested case-control study in southern China

BackgroundWe aim to clarify the controversial associations between EBV-related antibodies and gastric cancer risk.MethodsWe analysed the associations between serological Epstein-Barr nuclear antigen 1 immunoglobulin A (EBNA1-IgA) and viral capsid antigen immunoglobulin A (VCA-IgA) by enzyme-linked immunosorbent assay and the risk of gastric cancer in a nested case-control study originated from a population-based nasopharyngeal carcinoma (NPC) screening cohort in Zhongshan, a city of southern China, including 18 gastric cancer cases and 444 controls. Conditional logistic regression was used to calculate the odds ratios (ORs) and corresponding 95% confidence intervals (CIs).ResultsAll the sera of cases were sampled before diagnosis and the median time interval was 3.04 (range: 0.04, 7.59) years. Both increased relative optical density (rOD) values of EBNA1-IgA and VCA-IgA were associated with higher risks of gastric cancer with age adjusted ORs of 1.99 (95%CI: 1.07, 3.70) and 2.64 (95%CI: 1.33, 5.23), respectively. Each participant was further classified as high or medium/low risk based on a combination of two anti-EBV antibody levels. Participants in the high-risk group had substantially higher odds of developing gastric cancer than that in the medium/low risk group with an age adjusted OR of 6.53 (95%CI: 1.69, 25.26).ConclusionsOur research reveals positive associations between EBNA1-IgA and VCA-IgA and gastric cancer risk in southern China. We thus postulate that EBNA1-IgA and VCA-IgA might appear to be potential biomarkers for gastric cancer. More research to further validate the results among diverse populations and investigate its underlying biological mechanism is needed.

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

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

The Comprehensive Analysis of Specific Proteins as Novel Biomarkers Involved in the Diagnosis and Progression of Gastric Cancer.

Gastric cancer (GC) cases are predicted to rise by 2040 to approximately 1.8 million cases, while GC-caused deaths to 1.3 million yearly worldwide. To change this prognosis, there is a need to improve the diagnosis of GC patients because this deadly malignancy is usually detected at an advanced stage. Therefore, new biomarkers of early GC are sorely needed. In the present paper, we summarized and referred to a number of original pieces of research concerning the clinical significance of specific proteins as potential biomarkers for GC in comparison to well-established tumor markers for this malignancy. It has been proved that selected chemokines and their specific receptors, vascular endothelial growth factor (VEGF) and epidermal growth factor receptor (EGFR), specific proteins such as interleukin 6 (IL-6) and C-reactive protein (CRP), matrix metalloproteinases (MMPs) and their tissue inhibitors (TIMPs), a disintegrin and metalloproteinase with thrombospondin motifs (ADAMTS), as well as DNA- and RNA-based biomarkers, and c-MET (tyrosine-protein kinase Met) play a role in the pathogenesis of GC. Based on the recent scientific literature, our review indicates that presented specific proteins are potential biomarkers in the diagnosis and progression of GC as well as might be used as prognostic factors of GC patients' survival.

Gastric juice non-coding RNAs as potential biomarkers for gastric cancer.

Gastric cancer (GC), being one of the most common malignant human tumors, occupies the second position in the structure of mortality in men and women. High rates of morbidity and mortality in this pathology determine its extremely high clinical and social significance. Diagnosis and timely treatment of precancerous pathology is the main way to reduce morbidity and mortality, and early detection of GC and its adequate treatment improve prognosis. The ability to accurately predict the development of GC and start treatment on time, as well as the ability to determine the stage of the disease if the diagnosis is confirmed - non-invasive biomarkers can become the key to solving these and many other problems of modern medicine. One of the promising biomarkers being studied are non-coding RNAs, namely, miсroRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs). They are involved in a wide range of processes, including apoptosis, proliferation, differentiation, angiogenesis, which play a critical role in the development of GC oncogenesis. In addition, they are quite specific and stable due to their carriers (extracellular vesicles or Argonaute 2 protein) and can be detected in various human biological fluids, in particular gastric juice. Thus, miRNAs, lncRNAs, and circRNAs isolated from the gastric juice of GC patients are promising preventive, diagnostic and prognostic non-invasive biomarkers. This review article presents the characteristics of circulating or extracellular miRNAs, lncRNAs, and circRNAs in gastric juice, allowing their use in the GC preventive, diagnosis, prognosis and monitoring therapy.

Uncovering the special microbiota associated with occurrence and progression of gastric cancer by using RNA-sequencing

Gastric cancer (GC) has been identified as the third deadly cancer in the world. Accumulating researches suggest a potential role of microorganisms in tumorigenesis. However, the composition of microbiota in GC tissues is not clear and it changes throughout the different stages of GC remain mostly elusive. Our study integrated RNA-Seq data of 727 samples derived from gastric tissues across four datasets and revealed its microbial composition. In order to remove the false positive results, core taxa were defined and characterized. Based on it, we analyzed the influence of biological factors on its composition. The pan-microbiome of gastric tissues was estimated to be over than 1400 genera. Seventeen core genera were identified. Among them, Helicobacter, Lysobacter were significantly enriched in normal tissues, while Pseudomonas was enriched in tumor tissues. Interestingly, Acinetobacter, Pasteurella, Streptomyces, Chlamydia, and Lysobacter, showed a significant increase trend during tumor development and formed strong intra/inter-correlations among them or with other genera. Furthermore, we found that tumor stage played an important role in altering the microbial composition of GC tissues. This study provides support for the in-depth study of tumor microbiome, and the specific microbiome excavated provides a possibility for the subsequent identification of potential biomarkers for GC.

Identification of LSM family members as potential chemoresistance predictive and therapeutic biomarkers for gastric cancer.

The Like-Smith (LSM) family plays a critical role in the progression of several cancers. However, the function of LSMs in chemoresistance of gastric cancer (GC) is still elusive. The Cancer Genome Atlas (TCGA) database, Gene Expression Omnibus (GEO) database and Tumor Immune Estimation Resource Analysis (TIMER) were utilized to analyze the expression, prognostic value and immune infiltration of LSMs in GC patients. Moreover, qPCR and immunohistochemistry (IHC) experiment were conducted with clinical samples. The expression of LSMs was upregulated in GC tissues and most of LSMs were negatively correlated with overall survival of GC patients with 5-fluorouracil (5-FU) treatment. We further revealed that LSM5, 7 and 8 were hub genes of GEO (GSE14210). Besides, the qPCR results demonstrated that a higher level of LSM5 and LSM8 was associated with 5-FU chemoresistance in GC. Moreover, both TIMER and IHC revealed that a lower expression of LSM5 and LSM8 was correlated with high infiltration of T cells, regulatory T cells, B cells, macrophages, and neutrophils. Our study systematically investigated the expression pattern and biological features of LSM family members in GC, and identified LSM5 and LSM8 as potential biomarkers in GC with 5-FU chemotherapy.

CD93 serves as a potential biomarker of gastric cancer and correlates with the tumor microenvironment.

The tumor microenvironment (TME) plays an important role in the growth and expansion of gastric cancer (GC). Studies have identified that CD93 is involved in abnormal tumor angiogenesis, which may be related to the regulation of the TME. To determine the role of CD93 in GC. Transcriptomic data of GC was investigated in a cohort from The Cancer Genome Atlas. Additionally, RNA-seq data sets from Gene Expression Omnibus (GSE118916, GSE52138, GSE79973, GSE19826, and GSE84433) were applied to validate the results. We performed the immune infiltration analyses using ESTIMATE, CIBERSORT, and ssGSEA. Furthermore, weighted gene co-expression network analysis (WGCNA) was conducted to identify the immune-related genes. Compared to normal tissues, CD93 significantly enriched in tumor tissues (t = 4.669, 95%CI: 0.342-0.863, P < 0.001). Higher expression of CD93 was significantly associated with shorter overall survival (hazard ratio = 1.62, 95%CI: 1.09-2.4, P = 0.017), less proportion of CD8 T and activated natural killer cells in the TME (P < 0.05), and lower tumor mutation burden (t = 4.131, 95%CI: 0.721-0.256, P < 0.001). Genes co-expressed with CD93 were mainly enriched in angiogenesis. Moreover, 11 genes were identified with a strong relationship between CD93 and the immune microenvironment using WGCNA. CD93 is a novel prognostic and diagnostic biomarker for GC, that is closely related to the immune infiltration in the TME. Although this retrospective study was a comprehensive analysis, the prospective cohort studies are preferred to further confirm these conclusions.

Bioinformatics Identification of Therapeutic Gene Targets for Gastric Cancer.

The global prevalence of gastric cancer (GC) is increasing, and novel chemotherapeutic targets are needed. We searched for potential biomarkers for GC in three microarray datasets within the Gene Expression Omnibus (GEO) database. FunRich (v3.1.3) was used to perform Gene Ontology (GO) analyses and STRUN and Cytoscape (v3.6.0) were employed to construct a protein-protein interaction (PPI) network. To explore hub gene expression and survival, we used Gene Expression Profiling Interactive Analysis (GEPIA) and Kaplan-Meier (KM) plotter. Drugs that were closely related to key genes were screened by the Gene Set Cancer Analysis (GSCA), and relevant correlations were verified experimentally. We validated that the sensitivity of a GC cell line to these drugs was correlated with fibrillin1 (FBN1) mRNA expression levels. We identified 83 upregulated and 133 downregulated differentially expressed genes (DEGs) and these were enriched with regards to their cellular component (extracellular and exosomes), molecular function (extracellular matrix structural constituent and catalytic activity), and biological process (cell growth and/or maintenance and metabolism). The biological pathways most prominently involved were epithelial-to-mesenchymal transition (EMT) and β3integrin cell surface interactions. For the PPI network, we selected 10 hub genes, and 70% of these were significantly connected to poor overall survival (OS) in patients with GC. We found a significant link between the expression of FBN1 and two small molecule drugs (PAC-1 and PHA-793887). Overall, we suggest that these hub genes can be used as biomarkers and novel targets for GC. FBN1 may be associated with drug resistance in gastric cancer.

Analysis of a four-component competing endogenous RNA network reveals potential biomarkers in gastric cancer: An integrated systems biology and experimental investigation

Analysis of a four-component competing endogenous RNA network reveals potential biomarkers in gastric cancer: An integrated systems biology and experimental investigation

Analysis of Staged Features of Gastritis-Cancer Transformation and Identification of Potential Biomarkers in Gastric Cancer.

This work aims to elucidate the staged characteristics during gastritis-cancer transformation based on the transcriptome and use bioinformatics to identify potential biomarkers. We collected blood samples from healthy controls, patients with non-atrophic gastritis, atrophic gastritis, and gastric cancer, and tissue samples from patients with gastric cancer, respectively. RNA-seq was then performed. Differentially expressed genes, weighted gene co-expression network analysis and functional enrichment analysis were used to illustrate the staged characteristics of gastritis-cancer transformation. Genes with diagnostic potential were further identified in combination with ROC analysis. Additionally, for the gastric cancer stage, the gene expression of the collected tissue transcriptome was validated using the Cancer Genome Atlas and combined with survival analysis to identify potential biomarkers. The 279 overlapping genes among the differentially expressed genes of NAG, AG and CA indicated that the expression characteristics of different stages were different. However, the 2243 overlapping genes of differential genes between adjacent stages indicated a certain consistency in the expression characteristics of stage development. The core functions of different stages have strong stage specificity and basically have no similarities. Twenty genes with diagnostic potential for AG or CA were obtained, respectively, and no gene could effectively differentiate NAG samples. Thirty-four potential biomarkers for gastric cancer were identified, of which 14 genes have not been reported, including ACTG2, C1QTNF2, NCAPH and SORCS1. There may be a stable development mechanism in the process of gastritis-carcinoma transformation, resulting in the differences in the performance of each stage. The newly discovered staging features and potential biomarkers in this work can provide references for related research.

Metabolomics study identified bile acids as potential biomarkers for gastric cancer: A case control study.

Gastric cancer (GC) is a common lethal malignancy worldwide. Gastroscopy is an effective screening technique for decreasing mortality. However, there are still limited useful non-invasive markers for early detection of GC. Bile acids are important molecules for the modulation of energy metabolism. With an in-depth targeted method for accurate quantitation of 80 bile acids (BAs), we aimed to find potential biomarkers for the early screening of GC. A cohort with 280 participants was enrolled, including 113 GC, 22 benign gastric lesions (BGL) and 145 healthy controls. Potential markers were identified using a random forest machine algorithm in the discovery cohort (n=180), then validated in an internal validation cohort (n=78) and a group with 22 BGL. The results represented significant alterations in the circulating BA pool between GC and the controls. BAs also exhibited significant correlations with various clinical traits. Then, we developed a diagnostic panel that comprised six BAs or ratios for GC detection. The panel showed high accuracy for the diagnosis of GC with AUC of 1 (95%CI: 1.00-1.00) and 0.98 (95%CI: 0.93-1.00) in the discovery and validation cohort, respectively. This 6-BAs panel was also able to identify early GC with AUC of 1 (95%CI: 0.999-1.00) and 0.94 (95%CI: 0.83-1.00) in the discovery and validation cohort, respectively. Meanwhile, this panel achieved a good differential diagnosis between GC and BGL and the AUC was 0.873 (95%CI: 0.812-0.934). The alternations of serum bile acids are characteristic metabolic features of GC. Bile acids could be promising biomarkers for the early diagnosis of GC.

Serum amyloid A (SAA) and Interleukin-6 (IL-6) as the potential biomarkers for gastric cancer.

To explore serum amyloid A (SAA) and interleukin-6 (IL-6) as potential diagnostic biomarkers for gastric cancer (GCa) and the application value of the combined diagnosis of SAA, IL6, and Cancer embryonic antigen. Serum samples were collected before the initial surgery from 159 patients comprising samples from 122 patients with GCa and 37 patients with benign gastric disease. All patients were hospitalized at Beijing Aerospace General Hospital in China between 2018 and 2020. The IL-6 and SAA levels were assessed using standard laboratory protocols. The levels of SAA and IL-6 were significantly higher in patients with GCa than in controls. Compared with the healthy group, the concentration of SAA and IL-6 in FIGO III-IV group were significantly higher and the difference were statistically significant. In addition, significant differences were observed between the FIGO III-IV group and FIGO I-II groups. The Receiver operating characteristic (ROC) curve for the combined detection of SAA, IL-6, and Cancer embryonic antigen showed an area under the curve (AUC) of 0.948, sensitivity of 91.0%, and specificity of 89.2%. Spearman's correlation analysis indicated obvious correlations among the levels of serum SAA, IL-6, advanced FIGO stage, lymphatic invasion, and distant metastasis. AA and IL-6 may serve as useful biomarkers for poor prognosis of GCa. Clinical diagnosis combined with SAA and IL-6 may help assess therapeutic outcomes.

H19 may regulate the immune cell infiltration in carcinogenesis of gastric cancer through miR-378a-5p/SERPINH1 signaling

BackgroundIncreasing studies have indicated that noncoding RNA (ncRNA)-mediated competing endogenous RNA (ceRNA) network serves as a significant role in cancer progression, but the underlying regulatory mechanisms of which in gastric cancer (GC) remain largely unclear.MethodsBased on Gene Expression Omnibus and The Cancer Genome Atlas datasets, potential biomarkers for GC were screened and validated by machine learning. Then, upstream regulatory ncRNA of potential biomarkers was identified to construct a novel ceRNA network in GC through means of stepwise reverse prediction and validation. Ultimately, tumor immune cell infiltration analysis was performed based on the EPIC algorithm.ResultsA total of 188 differentially expressed genes (DEGs) were screened, and three candidate diagnostic biomarkers (FAP, PSAPL1, and SERPINH1) for GC were identified and validated. Subsequently, H19 and miR-378a-5p were identified as upstream regulatory ncRNAs that could potentially bind SERPINH1 in GC. Moreover, Immune infiltration analysis revealed that each component in the ceRNA network (H19/miR-378a-5p/SERPINH1) was significantly correlated with the infiltration abundances of diverse tumor-infiltrating immune cells.ConclusionsH19 may regulate the immune cell infiltration in carcinogenesis of GC through miR-378a-5p/SERPINH1 signaling.