scholarly journals Profiles Combining Muscle Atrophy and Neutrophil-to-Lymphocyte Ratio Are Associated with Prognosis of Patients with Stage IV Gastric Cancer

Nutrients ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1884 ◽  
Author(s):  
Kota Shigeto ◽  
Takumi Kawaguchi ◽  
Shunji Koya ◽  
Keisuke Hirota ◽  
Toshimitsu Tanaka ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Regression Analysis ◽  
Muscle Atrophy ◽  
Cox Regression ◽  
Stage Iv ◽  
Decision Tree Analysis ◽  
Tree Analysis ◽  
Cox Regression Analysis ◽  
Stage Iv Gastric Cancer ◽  
Prognostic Profile

We aimed to investigate the impact of muscle atrophy and the neutrophil-to-lymphocyte ratio (NLR), a sub-clinical biomarker of inflammation and nutrition, on the prognosis of patients with unresectable advanced gastric cancer. We retrospectively enrolled 109 patients with stage IV gastric cancer (median age 69 years; female/male 22%/78%; median observational period 261 days). Independent factors and profiles for overall survival (OS) were determined by Cox regression analysis and decision-tree analysis, respectively. OS was calculated using the Kaplan–Meier method. The prevalence of muscle atrophy was 82.6% and the median NLR was 3.15. In Cox regression analysis, none of factors were identified as an independent factor for survival. The decision-tree analysis revealed that the most favorable prognostic profile was non-muscle atrophy (OS rate 36.8%). The most unfavorable prognostic profile was the combination of muscle atrophy and high NLR (OS rate 19.6%). The OS rate was significantly lower in patients with muscle atrophy and high NLR than in patients with non-muscle atrophy (1-year survival rate 28.5% vs. 54.7%; log-rank test p = 0.0014). In conclusion, “muscle atrophy and high NLR” was a prognostic profile for patients with stage IV gastric cancer. Thus, the assessment of muscle mass, subclinical inflammation, and malnutrition may be important for the management of patients with stage IV gastric cancer.

scholarly journals Expression of LOX Suggests Poor Prognosis in Gastric Cancer

2021 ◽  
Vol 8 ◽  
Author(s):  
Jinfeng Zhu ◽  
Chen Luo ◽  
Jiefeng Zhao ◽  
Xiaojian Zhu ◽  
Kang Lin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Poor Prognosis ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
High Expression ◽  
Expression Level ◽  
Cox Regression Analysis

Background: Lysyl oxidase (LOX) is a key enzyme for the cross-linking of collagen and elastin in the extracellular matrix. This study evaluated the prognostic role of LOX in gastric cancer (GC) by analyzing the data of The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) dataset.Methods: The Wilcoxon rank-sum test was used to calculate the expression difference of LOX gene in gastric cancer and normal tissues. Western blot and immunohistochemical staining were used to evaluate the expression level of LOX protein in gastric cancer. Kaplan-Meier analysis was used to calculate the survival difference between the high expression group and the low expression group in gastric cancer. The relationship between statistical clinicopathological characteristics and LOX gene expression was analyzed by Wilcoxon or Kruskal-Wallis test and logistic regression. Univariate and multivariate Cox regression analysis was used to find independent risk factors affecting the prognosis of GC patients. Gene set enrichment analysis (GSEA) was used to screen the possible mechanisms of LOX and GC. The CIBERSORT calculation method was used to evaluate the distribution of tumor-infiltrating immune cell (TIC) abundance.Results: LOX is highly expressed in gastric cancer tissues and is significantly related to poor overall survival. Wilcoxon or Kruskal-Wallis test and Logistic regression analysis showed, LOX overexpression is significantly correlated with T-stage progression in gastric cancer. Multivariate Cox regression analysis on TCGA and GEO data found that LOX (all p < 0.05) is an independent factor for poor GC prognosis. GSEA showed that high LOX expression is related to ECM receptor interaction, cancer, Hedgehog, TGF-beta, JAK-STAT, MAPK, Wnt, and mTOR signaling pathways. The expression level of LOX affects the immune activity of the tumor microenvironment in gastric cancer.Conclusion: High expression of LOX is a potential molecular indicator for poor prognosis of gastric cancer.

scholarly journals Application value of nomogram and prognostic factors of gastric cancer patients who underwent D2 radical lymphadenectomy

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Guang-Chuan Mu ◽  
Yuan Huang ◽  
Zhi-Ming Liu ◽  
Xiang-Hua Wu ◽  
Xin-Gan Qin ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Regression Analysis ◽  
Prognostic Factors ◽  
Cancer Patients ◽  
Cox Regression ◽  
Term Survival ◽  
Long Term Survival ◽  
Cox Regression Analysis ◽  
Gastric Cancer Patients

Abstract Background The aim of this study was to explore the prognostic factors and establish a nomogram to predict the long-term survival of gastric cancer patients. Methods The clinicopathological data of 421 gastric cancer patients, who were treated with radical D2 lymphadenectomy by the same surgical team between January 2009 and March 2017, were collected. The analysis of long-term survival was performed using Cox regression analysis. Based on the multivariate analysis results, a prognostic nomogram was formulated to predict the 5-year survival rate probability. Results In the present study, the total overall 3-year and 5-year survival rates were 58.7 and 45.8%, respectively. The results of the univariate Cox regression analysis revealed that tumor staging, tumor location, Borrmann type, the number of lymph nodes dissected, the number of lymph node metastases, positive lymph nodes ratio, lymphocyte count, serum albumin, CEA, CA153, CA199, BMI, tumor size, nerve invasion, and vascular invasion were prognostic factors for gastric cancer (all, P < 0.05). However, merely tumor staging, tumor location, positive lymph node ratio, CA199, BMI, tumor size, nerve invasion, and vascular invasion were independent risk factors, based on the results of the multivariate Cox regression analysis (all, P < 0.05). The nomogram based on eight independent prognostic factors revealed a well-degree of differentiation with a concordance index of 0.76 (95% CI: 0.72–0.79, P < 0.001), which was better than the AJCC-7 staging system (concordance index = 0.68). Conclusion The present study established a nomogram based on eight independent prognostic factors to predict long-term survival in gastric cancer patients. The nomogram would be beneficial for more accurately predicting the prognosis of gastric cancer, and provide important basis for making individualized treatment plans following surgery.

Clinical features and the role of surgery in stage IV gastric cancer: A single center experience.

2015 ◽  
Vol 33 (3_suppl) ◽  
pp. 212-212
Author(s):  
Narjust Perez-Florez ◽  
Larysa Jessica Gromko ◽  
Eric Yoon ◽  
Andrew Jennis ◽  
Zubin M. Bamboat ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Multivariate Analysis ◽  
Survival Benefit ◽  
Cox Regression ◽  
Stage Iv ◽  
Treatment Modalities ◽  
Stage Iv Gastric Cancer ◽  
Significant Difference ◽  
To Receive

212 Background: Gastric cancer is a prevalent global disease with significant mortality. Nearly 22,220 patients are diagnosed annually in the US, with approximately 50% of them presenting with disease that extends beyond loco-regional confines, and only a small percentage undergoing curative resection. We aim to study the clinical characteristics and survival benefit of surgery in stage IV gastric cancer. Methods: We reviewed the records of all patients diagnosed with gastric cancer in our cancer center from 1999 to 2013. A total of 272 stage IV cases were identified. Demographics, tumor characteristics, treatment modalities (surgical vs. non-surgical) and survival rate were analyzed. Kaplan-Meier was used for survival analysis and Cox regression for univariate and multivariate analysis. Results: Within the cohort 70 (26%) patients received surgery and 202 (74%) were treated with chemotherapy ± radiation. Mean age at diagnosis was 64 years in the surgical (S) patients and 66 years in the non-surgical (NS). Non-Hispanics whites were more likely to receive surgery vs. all other ethnic groups combined, representing 77% vs. 23% of the S subgroup (p<0.0001). Patients with proximal tumors were more likely to receive surgery when compared with distal tumors (37 (53%) vs. 14 (20%), p<0.0001). Total gastrectomy was the most common surgical procedure 33 (47%). There was a significant difference in disease specific survival between the two groups, being 17.3 months for S (95%CI: 11.1-23.4) and 5.3 months for NS (95%CI: 3.8-6.7) (p<0.0001). Age > 70 years (OR: 1.74, p<0.02), proximal tumor location (OR: 0.75, p<0.04), surgery (OR: 0.37, p<0.0001) and extended lymphadenectomy (D2) (OR: 0.26, p<0.02) were independent and significant predictors of survival by multivariate analysis. Conclusions: In our cohort, non-Hispanic whites and patients with proximal tumors were more likely to undergo surgery. A major survival benefit was observed for the surgical subgroup when compared to non-surgical treatment for stage IV gastric cancer. Future research should aim to further elucidate the specific role of surgery, as this could potentially impact management and transform the standard of care in stage IV gastric cancer.

Effect of combined consideration of distinct signatures of VEGF and soluble VEGFR2 on prognostic implication in gastric cancer.

2016 ◽  
Vol 34 (4_suppl) ◽  
pp. 56-56
Author(s):  
Chan-Young Ock ◽  
Ah-Rong Nam ◽  
Ju-Hee Bang ◽  
Tae-Yong Kim ◽  
Kyung-Hun Lee ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Regression Analysis ◽  
Growth Factor ◽  
Cox Regression ◽  
Linear Regression Analysis ◽  
Vegf Receptor ◽  
Prognostic Impact ◽  
Prognostic Implication ◽  
Cox Regression Analysis ◽  
Fibroblast Growth Factor Basic

56 Background: Anti-angiogenic strategy in gastric cancer (GC) has been highlighted again due to the recent success of ramucirumab and apatinib. Therefore, the comprehensive network of VEGF, soluble VEGF receptor-2 (sVEGFR2) and cytokines and other angiogenic factors (CAF) in GC and their prognostic impact would be of importance, although they have been poorly understood. We aimed to find out the CAF signature associated with VEGF and sVEGFR2, and to explore their prognostic implication in GC. Methods: We measured pretreatment serum levels of 52 CAFs, including VEGF and sVEGFR2, using multiplex bead immunoassays and ELISA, in 70 patients who were diagnosed with GC in Seoul National University Hospital, and treated with palliative chemotherapy. Linear regression analysis for correlating CAFs with VEGF and sVEGFR2, and survival analysis by log rank test and Cox regression analysis were performed. Results: The VEGF signature was shown to be associated with seven CAFs (interluekin [IL]-7, IL-12p70, IL-2Ra, IL-10, stem cell factor, Fibroblast growth factor-basic, IL-3). The sVEGFR2 signature was associated with IL-4 and platelet-derived growth factor beta, but VEGF and sVEGFR2 showed no association with each other. Patients with high VEGF had a tendency to have worse overall survival (OS) than those with low VEGF (11.2 months versus 16.7 months; P = 0.061). However, among patients with high-sVEGFR2, OS was not different according to VEGF (12.1 months, high-VEGF versus 15.1 months, low-VEGF; P = 0.546). Interestingly, the poor prognostic impact of high-VEGF was far significant in patients with low-sVEGFR2 (10.9 months versus 16.8 months; P = 0.036). With this perspective, VEGF/sVEGFR2 ratio was significantly correlated with worse OS in univariate as well as multivariate analysis (HR 1.78 [95% CI 1.08-2.94], P= 0.024). Conclusions: Based on the comprehensive network analysis of CAF, VEGF and sVEGFR2 had distinct CAF signatures in GC. Consideration of both VEGF and sVEGFR2 confers more accurate prognostic implication compared with VEGF alone in GC. Regarding the angiogenic aspect, VEGF/sVEGFR2 ratio is significantly correlated with survival outcome in GC.

scholarly journals High Expression of PABPC1 Predicts Worse Survival of Gastric Cancer Patients

2020 ◽  
Author(s):  
Tailai An ◽  
Lingna Deng ◽  
Zheng Yang ◽  
Cuicui Chai ◽  
Yan Wang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Regression Analysis ◽  
Molecular Mechanisms ◽  
Bioinformatics Analysis ◽  
Cox Regression ◽  
Disease Free Survival ◽  
Mrna Translation ◽  
High Expression ◽  
Depth Of Invasion ◽  
Cox Regression Analysis

Abstract Background: Gastric cancer (GC) is one of the most common cancers with one of the highest mortality rates. Unfortunately, underlying molecular mechanisms contributing to GC have not been fully illuminated. PABPC1 is involved in a series of processes, such as mRNA translation, and mRNA deadenylation and decay. We performed this study to clarify the role of PABPC1 in GC. Methods: To evaluate PABPC1 expressions in GC and normal tissues, we performed bioinformatics analysis of data from TCGA. PABPC1 expressions were evaluated by immunohistochemical (IHC) staining of 170 GC specimens. Associations between PABPC1 expression and clinicopathological variables were analyzed. Independent predictive factors for survival of GC patients were determined by Cox regression analysis. Results: It was revealed by bioinformatics analysis that compared with normal gastric tissues, PABPC1 expressions in GC tissues were significantly higher (P=0.002, paired) (P=3.605e^-9, unpaired). It was revealed that PABPC1 expression was significantly associated with tumor size (P=0.008), Borrmann classification (P=0.003), vessel invasion (P=0.017), depth of invasion (P=0.032), lymph node metastasis (P=0.001), and TNM stage (P=0.019). It was demonstrated through Cox regression analysis that PABPC1 expression was a predictive factor for both overall survival (OS) (P<0.001) and disease-free survival (DFS) (P<0.001) of GC patients. Conclusions: Compared with that of normal gastric tissue, expression level of PABPC1 in GC tissue was significantly higher and PABPC1,s high expression was significantly associated with poorer survival, suggesting its potential as a therapeutic biomarker for GC.

scholarly journals Integrated analysis of 1804 samples of six centers to construct and validate a robust immune-related prognostic signature associated with stromal cell abundance in tumor microenvironment for gastric cancer

2022 ◽  
Vol 20 (1) ◽  
Author(s):  
Junyu Huo ◽  
Ge Guan ◽  
Jinzhen Cai ◽  
Liqun Wu
Keyword(s):  
Gastric Cancer ◽  
Regression Analysis ◽  
Risk Score ◽  
Stromal Cell ◽  
Immune Cell ◽  
Cox Regression ◽  
Risk Group ◽  
Integrated Analysis ◽  
Prognostic Signature ◽  
Cox Regression Analysis

Abstract Background Stromal cells in tumor microenvironment could promote immune escape through a variety of mechanisms, but there are lacking research in the field of gastric cancer (GC). Methods We identified differential expressed immune-related genes (DEIRGs) between the high- and low-stromal cell abundance GC samples in The Cancer Genome Atlas and GSE84437 datasets. A risk score was constructed basing on univariate cox regression analysis, LASSO regression analysis, and multivariate cox regression analysis in the training cohort (n=772). The median value of the risk score was used to classify patients into groups with high and low risk. We conducted external validation of the prognostic signature in four independent cohorts (GSE26253, n=432; GSE62254, n=300; GSE15459, n=191; GSE26901, n=109) from the Gene Expression Omnibus (GEO) database. The immune cell infiltration was quantified by the CIBERSORT method. Results The risk score contained 6 genes (AKT3, APOD, FAM19A5, LTBP3, NOV, and NOX4) showed good performance in predicting 5-year overall survival (OS) rate and 5-year recurrence-free survival (RFS) rate of GC patients. The risk death and recurrence of GC patients growing with the increasing risk score. The patients were clustered into three subtypes according to the infiltration of 22 kinds of immune cells quantified by the CIBERSORT method. The proportion of cluster A with the worst prognosis in the high-risk group was significantly higher than that in the low-risk group; the risk score of cluster C subtype with the best prognosis was significantly lower than that of the other two subtypes. Conclusion This study established and validated a robust prognostic model for gastric cancer by integrated analysis 1804 samples of six centers, and its mechanism was explored in combination with immune cell infiltration characterization.

Outcomes of patients with nonmetastatic gastric adenocarcinoma according to perioperative treatment strategy: a real-world, population-based study

2021 ◽  
Vol 10 (15) ◽  
pp. 1143-1151
Author(s):  
Omar Abdel-Rahman
Keyword(s):  
Gastric Cancer ◽  
Regression Analysis ◽  
Adjuvant Chemotherapy ◽  
Treatment Strategy ◽  
Cox Regression ◽  
Population Based ◽  
Survival Outcomes ◽  
Perioperative Chemotherapy ◽  
Cox Regression Analysis ◽  
Perioperative Treatment

Aim: To assess the survival outcomes of patients with nonmetastatic gastric cancer according to the type of perioperative treatment strategy used (surgery-only, adjuvant chemo-radiotherapy, adjuvant chemotherapy, perioperative chemotherapy) in a population-based setting. Materials & methods: Surveillance, Epidemiology and End Results research-plus database was explored, and patients with nonmetastatic gastric cancer who were treated with an oncologic surgery were reviewed. Multivariable Cox regression analysis was used to examine the impact of treatment strategy on overall and cancer-specific survival. Results: A total of 11,526 patients were found to be eligible and they were included in the current analysis. Looking at the percentages of different treatment strategies throughout the study years (2006–2017), the use of the following strategies increased: adjuvant chemotherapy (20.1 vs 10.6%), and perioperative chemotherapy (21.3 vs 0.5%); while the use of the following strategies decreased: surgery only (36.2 vs 58.2%), and adjuvant chemo-radiotherapy (22.4 vs 30.6%). Using multivariable Cox regression analysis, the following factors were associated with worse overall survival: older age (hazard [HR]: 1.021; 95% CI: 1.018–1.023), males (HR: 1.09; 95% CI: 1.04–1.14), Black race (HR: 1.11; 95% CI: 1.04–1.19), cardia subsite (HR: 1.09; 95% CI: 1.02–1.17), grade 3–4 (HR:1.32; 95% CI: 1.25–1.40), diffuse histology (HR: 1.46; 95% CI: 1.35–1.58), clinically node positive (HR:1.43; 95% CI: 1.34–1.53), total gastrectomy (HR: 1.20; 95% CI: 1.13–1.28), and surgery-only approach (HR: 1.65; 95% CI: 1.55–1.75). Conclusion: Among patients with localized gastric cancer, patients who were treated with surgery-only, and to a less extent, patients who were treated with surgery followed by adjuvant chemotherapy have worse survival outcomes; while those treated with perioperative chemotherapy have the best survival outcomes.

COX-2 promotes metastasis and predicts prognosis on gastric cancer via regulating mTOR

2020 ◽  
Author(s):  
Liangliang Xiang ◽  
Weimin Wang ◽  
Zhen Zhou ◽  
Mengying Lv ◽  
Li Tao ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Regression Analysis ◽  
Cox Regression ◽  
Malignant Tumors ◽  
Tissue Microarrays ◽  
Prognostic Indicators ◽  
Independent Factor ◽  
Cox Regression Analysis ◽  
The World ◽  
Cox 2

Aim: Gastric cancer (GC) is one of the most common malignant tumors in the world. It is important to find accurate and reliable biomarkers in order to decrease whole morbidity and mortality. Results: We examined the expression of COX-2 and mTOR on GC tissue microarrays by immunohistochemistry. Multivariate COX regression analysis showed that the expression of COX-2 or mTOR was an independent factor in the prognosis of GC patients. In addition, COX-2 and mTOR had the potentially synergistic effect on predicting the prognosis of GC. Conclusion: The combined expression of COX-2 and mTOR could serve as efficient prognostic indicators and COX-2 could suppress GC metastasis via regulating mTOR.

scholarly journals Transcription Elongation Factor A-like 7 is a Stemness-Related Prognostic Factor in Gastric Cancer

2021 ◽  
Author(s):  
Haisheng Qian ◽  
Xin Gao ◽  
Rui Ma ◽  
Wenjie Li ◽  
Zhen Yang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Overall Survival ◽  
Regression Analysis ◽  
Cox Regression ◽  
Learning Algorithm ◽  
Cox Regression Analysis ◽  
Normal Tissues ◽  
Significant Difference ◽  
Selection Operator ◽  
Level Group

Abstract Background: Stemness is described as the potential for self-renewal and differentiation from the cell-of-origin. A previous study calculated the mRNA expression-based stemness index (mRNAsi) based on a one-class logistic regression machine learning algorithm for describing stemness features of cancer. We aim to identify stemness-related prognostic genes in gastric cancer (GC) based on mRNAsi using bioinformatics analysis.Methods: The WGCNA analysis was performed to find the relevant gene modules to mRNAsi. Gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways annotation analysis were performed on genes in blue module. The overall survival analysis, univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) regression model were used to identify prognostic genes highly associated with survival. The multivariate Cox regression analysis was performed to analysis prognostic factors. The nomogram was constructed according to the result of multivariate analysis. qPCR, Western Blot and IHC staining were appliedResults: The mRNAsi of tumors is higher than normal tissues, and there was a significant difference in overall survival (OS) between the high and low mRNAsi GC groups. TCEAL7 was selected to be the key gene associated with mRNAsi and prognosis according to the result of least absolute shrinkage and selection operator (LASSO) Cox regression. The expression level of TCEAL7 was lower in tumors than in normal tissues, but high TCEAL7 level group showed a worse OS than low TCEAL7 level group in GC. Based on the result of multivariable Cox regression analysis which including TCEAL7 and clinical characteristics, a nomogram for predicting GC 1-, 3-, and 5-year survival was established. The C-index and the AUC (Area Under Curve) of the model indicated that the model has a good discrimination ability. Additionally, the calibration curves of 3- and 5-year OS rates showed the model fits well. The experimental validation of the expression of TCEAL7 in GC and normal tissues were consistent with the above.Conclusions: In summary, we verified mRNAsi was associated with the prognosis of GC patients. And TCEAL7 was finally identified as the key gene correlated with stemness features and prognosis in GC.

Sign in / Sign up

Export Citation Format

Share Document