Screening for High-risk Group of Gastric Cancer by Using Barium Radiography is Useful in Okayama Prefecture Population-based Gastric Cancer Mass Screening

Background: Additional surgery after non-curative endoscopic submucosal dissection (ESD) may be excessive as few patients have lymph node metastasis (LNM). It is necessary to develop a risk stratification system for LNM after non-curative ESD, such as the eCura system, which was introduced in the Japanese gastric cancer treatment guidelines. However, the eCura system requires venous and lymphatic invasion to be separately assessed, which is difficult to distinguish without special immunostaining. In this study, we practically modified the eCura system by classifying lymphatic and venous invasion as lymphovascular invasion (LVI). Method: We retrospectively reviewed 543 gastric cancer patients who underwent radical gastrectomy after non-curative ESD between 2006 and 2019. LNM was evaluated according to LVI as well as size >30 mm, submucosal invasion ≥500 µm, and vertical margin involvement, which were used in the eCura system. Results: LNM was present in 8.1% of patients; 3.6%, 2.3%, 7.4%, 18.3%, and 61.5% of patients with no, one, two, three, and four risk factors had LNM, respectively. The LNM rate in the patients with no risk factors (3.6%) was not significantly different from that in patients with one risk factor (2.3%, p = 0.523). Among patients with two risk factors, the LNM rate without LVI was significantly lower than with LVI (2.4% vs. 10.7%, p = 0.027). Among patients with three risk factors, the LNM rate without LVI was lower than with LVI (0% vs. 20.8%, p = 0.195), although not statistically significantly. Based on LNM rates according to risk factors, patients with LVI and other factors were assigned to the high-risk group (LNM, 17.4%) while other patients as a low-risk group (LNM, 2.4%). Conclusions: Modifying the eCura system by classifying lymphatic and venous invasion as LVI successfully stratified LNM risk after non-curative ESD. Moreover, the high-risk group can be simply identified based on LVI and the presence of other risk factors.

Download Full-text

Prognostic Autophagy-Related Model Revealed by Integrating Single-Cell RNA Sequencing Data and Bulk Gene Profiles in Gastric Cancer

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.729485 ◽

2022 ◽

Vol 9 ◽

Author(s):

Tianying Tong ◽

Jie Zhang ◽

Xiaoqiang Zhu ◽

Pingping Hui ◽

Zhimin Wang ◽

...

Keyword(s):

Gastric Cancer ◽

High Risk ◽

Single Cell ◽

Rna Sequencing ◽

Immune Checkpoint ◽

Risk Model ◽

Risk Group ◽

High Risk Group ◽

Related Model ◽

Single Cell Rna Sequencing

Autophagy has been associated with tumor progression, prognosis, and treatment response. However, an autophagy-related model and their clinical significance have not yet been fully elucidated. In the present study, through the integrative analysis of bulk RNA sequencing and single-cell RNA sequencing, an autophagy-related risk model was identified. The model was capable of distinguishing the worse prognosis of patients with gastric cancer (GC), which was validated in TCGA and two independent Gene Expression Omnibus cohorts utilizing the survival analysis, and was also independent of other clinical covariates evaluated by multivariable Cox regression. The clinical value of this model was further assessed using a receiver operating characteristic (ROC) and nomogram analysis. Investigation of single-cell RNA sequencing uncovered that this model might act as an indicator of the dysfunctional characteristics of T cells in the high-risk group. Moreover, the high-risk group exhibited the lower expression of immune checkpoint markers (PDCD1 and CTLA4) than the low-risk group, which indicated the potential predictive power to the current immunotherapy response in patients with GC. In conclusion, this autophagy-associated risk model may be a useful tool for prognostic evaluation and will facilitate the potential application of this model as an indicator of the predictive immune checkpoint biomarkers.

Download Full-text

Eradication of H. pylori Did Not Improve Abnormal Sonic Hedgehog Expression in the High Risk Group for Gastric Cancer

Digestive Diseases and Sciences ◽

10.1007/s10620-011-1916-3 ◽

2011 ◽

Vol 57 (3) ◽

pp. 643-649 ◽

Cited By ~ 9

Author(s):

Akiko Shiotani ◽

Takahisa Murao ◽

Noriya Uedo ◽

Hiroyasu Iishi ◽

Yoshiyuki Yamanaka ◽

...

Keyword(s):

Gastric Cancer ◽

High Risk ◽

Sonic Hedgehog ◽

Risk Group ◽

High Risk Group ◽

H Pylori

Download Full-text

Prevalence of diabetes mellitus in patients with acromegaly

Endocrine Connections ◽

10.1530/ec-14-0021 ◽

2014 ◽

Vol 3 (2) ◽

pp. 93-98 ◽

Cited By ~ 39

Author(s):

A V Dreval ◽

I V Trigolosova ◽

I V Misnikova ◽

Y A Kovalyova ◽

R S Tishenina ◽

...

Keyword(s):

Diabetes Mellitus ◽

High Risk ◽

General Population ◽

Glucose Tolerance ◽

Risk Group ◽

Adult Population ◽

Tolerance Test ◽

Population Based ◽

High Risk Group ◽

Oral Glucose

Early carbohydrate metabolism disorders (ECMDs) and diabetes mellitus (DM) are frequently associated with acromegaly. We aimed to assess the prevalence of ECMDs in patients with acromegaly and to compare the results with those in adults without acromegaly using two population-based epidemiologic surveys. We evaluated 97 patients with acromegaly in several phases of their disease (mean age, 56 years and estimated duration of acromegaly, 12.5 years). An oral glucose tolerance test was done in those not yet diagnosed with DM to reveal asymptomatic DM or ECMDs (impaired glucose tolerance+impaired fasting glucose). Comparisons were made between patients with acromegaly and participants from the general adult population (n=435) and an adult population with multiple type 2 diabetes risk factors (n=314), matched for gender, age and BMI. DM was diagnosed in 51 patients with acromegaly (52.5%) and 14.3% of the general population (P<0.001). The prevalence of ECMDs was also higher in patients with acromegaly than in the general population and in the high-risk group; only 22% of patients with acromegaly were normoglycaemic. The prevalence of newly diagnosed ECMDs or DM was 1.3–1.5 times higher in patients with acromegaly compared with the high-risk group. Patients with acromegaly having ECMDs or DM were older, more obese and had longer disease duration and higher IGF1 levels (Z-score). Logistic regression showed that the severity of glucose derangement was predicted by age, BMI and IGF1 levels. In patients with acromegaly, the prevalence of DM and ECMDs considerably exceeds that of the general population and of a high-risk group, and development of DM depends on age, BMI and IGF1 levels.

Download Full-text

A high-risk group for prostatism: a population-based epidemiological study in Korea

BJU International ◽

10.1046/j.1464-410x.1997.00149.x ◽

1997 ◽

Vol 79 (5) ◽

pp. 736-741 ◽

Cited By ~ 42

Author(s):

E. LEE ◽

M-S. PARK ◽

C. SHIN ◽

H. LEE ◽

K. YOO ◽

...

Keyword(s):

High Risk ◽

Epidemiological Study ◽

Risk Group ◽

Population Based ◽

High Risk Group

Download Full-text

A Ferroptosis-Related lncRNAs Signature Predicts Prognosis and Therapeutic Response of Gastric Cancer

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.736682 ◽

2021 ◽

Vol 9 ◽

Author(s):

Shilang Xiao ◽

Xiaoming Liu ◽

Lingzhi Yuan ◽

Fen Wang

Keyword(s):

Gastric Cancer ◽

High Risk ◽

Correlation Analysis ◽

Risk Score ◽

Therapeutic Response ◽

Risk Group ◽

High Risk Group ◽

Low Risk ◽

Biological Processes ◽

Spearman Correlation

Background: Accumulating literature demonstrates that long noncoding RNAs (lncRNAs) are involved in ferroptosis and gastric cancer progression. However, the predictive value of ferroptosis-related lncRNAs for prognosis and therapeutic response is yet to be elucidated in gastric cancer (GC).Method: The transcriptomic data and corresponding clinical information of GC patients were obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) database. The association between ferroptosis-related lncRNAs and ferroptosis regulators was analyzed by Spearman correlation analysis. Then, we established a risk predictive model based on the ferroptosis-related lncRNAs using multivariate Cox regression analysis. Furthermore, we performed correlation analysis for the risk score and characteristics of biological processes, immune landscape, stromal activity, genomic integrity, drug response, and immunotherapy efficacy.Results: We constructed a 17-ferroptosis-related-lncRNA signature via multivariate Cox analysis to divide patients into two groups: low- and high-risk groups. The low-risk group was linked to prolonged overall survival and relapse-free survival. The risk score had good predictive ability to predict the prognosis of GC patients compared with other clinical biomarkers. We found that the high-risk group was associated with activation of carcinogenetic signaling pathways, including stromal activation, epithelial-mesenchymal-transition (EMT) activation, and immune escape through integrated bioinformatics analysis. In contrast, the low-risk group was associated with DNA replication, immune-flamed state, and genomic instability. Additionally, through Spearman correlation analysis, we found that patients in the high-risk group may respond well to drugs targeting cytoskeleton, WNT signaling, and PI3K/mTOR signaling, and drugs targeting chromatin histone acetylation, cell cycle, and apoptosis regulation could bring more benefits for the low-risk group. The high-risk group was associated with poor immunotherapy efficacy.Conclusion: Our study systematically evaluated the role of ferroptosis-related lncRNAs in t tumor microenvironment, therapeutic response, and prognosis of GC. Risk score–based stratification could reflect the characteristic of biological processes, immune landscape, stromal activity, genomic stability, and pharmaceutical profile in GC patients. The ferroptosis-related lncRNA signature could serve as a reliable biomarker to predict prognosis and therapeutic response of patients with GC.

Download Full-text

Characterization of the Prognostic m6A-Related lncRNA Signature in Gastric Cancer

Frontiers in Oncology ◽

10.3389/fonc.2021.630260 ◽

2021 ◽

Vol 11 ◽

Author(s):

Haixu Wang ◽

Qingkai Meng ◽

Bin Ma

Keyword(s):

Gastric Cancer ◽

High Risk ◽

Prognostic Factor ◽

Risk Group ◽

Pearson Correlation ◽

High Risk Group ◽

Independent Prognostic Factor ◽

Low Risk ◽

Gene Set Enrichment Analysis ◽

Receptor Interaction

N6-methyladenosine (m6A) is a common form of mRNA modification regulated by m6A RNA methylation regulators and play an important role in the progression of gastric cancer (GC). However, the prognostic role of m6A-related lncRNA in gastric cancer has not been fully explored. This study aims at exploring the biological function and prognostic roles of the m6A-related lncRNA signature in gastric cancer. A total of 800 m6A-related lncRNAs were identified through Pearson correlation analysis between m6A regulators and all lncRNAs. Eleven m6A-related lncRNA signatures were identified through a survival analysis and the Kaplan-Meier (KM) curve analysis results suggest that patients in the low-risk group have a better overall survival (OS) and disease-free survival (DFS) outcome than the high-risk group. Also, the lncRNA signature can serve as an independent prognostic factor for OS and DFS. The gene set enrichment analysis (GSEA) result suggests that patients in the high-risk group were mainly enriched in the ECM receptor interaction, focal adhesion, and cytokine-cytokine receptor interaction pathway, while the low-risk group was characterized by the base excision repair pathway. We further constructed an individualized prognostic prediction model via the nomogram based on the independent prognostic factor for the OS and DFS, respectively. In addition, some candidate drugs aimed at GC risk group differentiation were identified using the Connective Map (CMAP) database. Lastly, four subgroups (C1, C2, C3, and C4) were identified based on the m6A-related lncRNA expression, through a consensus clustering algorithm. Among them, C1 and C2 have a greater likelihood to respond to immune checkpoint inhibitor immunotherapy, suggesting that the C1 and C2 subgroup might benefit from immunotherapy. In conclusion, the m6A-related lncRNA signature can independently predict the OS and DFS of GC and may aid in development of personalized immunotherapy strategies.

Download Full-text

Construction of a Prognostic Model Related to Ferroptosis and Iron-Metabolism and the Relationship with the Immune Microenvironment of Gastric Cancer

10.21203/rs.3.rs-708494/v1 ◽

2021 ◽

Author(s):

Fang Wen ◽

Xiaoxue Chen ◽

Wenjie Huang ◽

Shuai Ruan ◽

Suping Gu ◽

...

Keyword(s):

Gastric Cancer ◽

High Risk ◽

Iron Metabolism ◽

Risk Model ◽

Cox Regression ◽

Risk Group ◽

Risk Groups ◽

High Risk Group ◽

Low Risk ◽

Immune Microenvironment

Abstract Background: The diagnosis rate and mortality of gastric cancer (GC) are among the highest in the global, so it is of great significance to predict the survival time of GC patients. Ferroptosis and iron-metabolism make a critical impact on tumor development and are closely linked to the treatment of cancer and the prognosis of patients. However, the predictive value of the genes involved in ferroptosis and iron-metabolism in GC and their effects on immune microenvironment remain to be further clarified.Methods: In this study, the RNA sequence information and general clinical indicators of GC patients were acquired from the public databases. We first systematically screen out 134 DEGs and 13 PRGs related to ferroptosis and iron-metabolism. Then, we identified six PRDEGs (GLS2, MTF1, SLC1A5, SP1, NOX4, and ZFP36) based on the LASSO-penalized Cox regression analysis. The 6-gene prognostic risk model was established in the TCGA cohort and the GC patients were separated into the high- and the low-risk groups through the risk score median value. GEO cohort was used for verification. The expression of PRDEGs was verified by quantitative QPCR.Results: Our study demonstrated that patients in the low-risk group had a higher survival probability compared with those in high-risk group. In addition, univariate and multivariate Cox regression analyses confirmed that the risk score was an independent prediction parameter. The ROC curve analysis and nomogram manifested that the risk model had the high predictive ability and was more sensitive than general clinical features. Furthermore, compared with the high-risk group, the low-risk group had higher TMB and a longer 5-year survival period. In the immune microenvironment of GC, there were also differences in immune function and highly infiltrated immune cells between the two risk groups.Conclusions: The prognostic risk model based on the six genes associated with ferroptosis and iron-metabolism has a good performance for predicting the prognosis of patients with GC. The treatment of cancer by inducing tumor ferroptosis or mediating tumor iron-metabolism, especially combined with immunotherapy, provides a new possibility for individualized treatment of GC patients.

Download Full-text