scholarly journals ICAM1 Regulates the Development of Gastric Cancer and May Be a Potential Biomarker for the Early Diagnosis and Prognosis of Gastric Cancer

2020 ◽  
Vol Volume 12 ◽  
pp. 1523-1534
Author(s):  
Songda Chen ◽  
Shan Pan ◽  
Huijie Wu ◽  
Jingyuan Zhou ◽  
Yueli Huang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Early Diagnosis ◽  
Diagnosis And Prognosis ◽  
Potential Biomarker ◽  
Development Of Gastric Cancer

scholarly journals Inverse correlation between Interleukin-34 and gastric cancer, a potential biomarker for prognosis

2020 ◽  
Author(s):  
Qinghua Liu ◽  
Ying Zhang ◽  
Jiwei Zhang ◽  
Kun Tao ◽  
Brett D Hambly ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Prognostic Factor ◽  
Early Diagnosis ◽  
Precision Medicine ◽  
Cellular Therapy ◽  
Inverse Correlation ◽  
Independent Prognostic Factor ◽  
Cancer Tissue ◽  
High Morbidity ◽  
Potential Biomarker

Abstract Background Gastric cancer (GC) is a malignancy with high morbidity/mortality, partly due to a lack of reliable biomarkers for early diagnosis. It is important to develop reliable biomarker(s) with specificity, sensitivity and convenience for early diagnosis. The role of tumour-associated macrophages (TAMs) and survival of GC patients are controversial. Macrophage colony stimulating factor (MCSF) regulates monocytes/macrophages. Elevated MCSF is correlated with invasion, metastasis and poor survival of tumour patients. IL-34, a ligand of the MCSF receptor, acts as a “twin” to MCSF, demonstrating overlapping and complimentary actions. IL-34 involvement in tumours is controversial, possibly due to the levels of MCSF receptors. While the IL34/MCSF/MCSFR axis is very important for regulating macrophage differentiation, the specific interplay between these cytokines, macrophages and tumour development is unclear.Methods A multi-factorial evaluation could provide more objective utility, particularly for either prediction and/or prognosis of gastric cancer. Precision medicine requires molecular diagnosis to determine the specifically mutant function of tumours, and is becoming popular in the treatment of malignancy. Therefore, elucidating specific molecular signalling pathways in specific cancers facilitates the success of a precision medicine approach. Gastric cancer tissue arrays were generated from stomach samples with TNM stage, invasion depth and the demography of these patients (n = 185). Using immunohistochemistry/histopathology, MCSF, IL-34 and macrophages were determined.Results We found that IL-34 may serve as a predictive biomarker, but not as an independent, prognostic factor in GC; MCSF inversely correlated with survival of GC in TNM III‑IV subtypes. Increased CD68+TAMs were a good prognostic factor in some cases and could be used as an independent prognostic factor in male T3 stage GC.Conclusion Our data support the potency of IL-34, MCSF, TAMs and the combination of IL34/TAMs as novel biological markers for GC, and may provide new insight for both diagnosis and cellular therapy of GC.

Exosomal miR-1246 in serum as a potential biomarker for early diagnosis of gastric cancer

2019 ◽  
Vol 25 (1) ◽  
pp. 89-99 ◽  
Author(s):  
Yuntao Shi ◽  
Zhonghong Wang ◽  
Xiaojuan Zhu ◽  
Ling Chen ◽  
Yilan Ma ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Early Diagnosis ◽  
Potential Biomarker

scholarly journals NDRG4 hypermethylation is a potential biomarker for diagnosis and prognosis of gastric cancer in Chinese population

Oncotarget ◽  
2016 ◽  
Vol 8 (5) ◽  
pp. 8105-8119 ◽  
Author(s):  
Xiaoying Chen ◽  
Yong Yang ◽  
Jing Liu ◽  
Bin Li ◽  
Yan Xu ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Chinese Population ◽  
Diagnosis And Prognosis ◽  
Potential Biomarker

scholarly journals Inverse correlation between Interleukin-34 and gastric cancer, a potential biomarker for prognosis

2020 ◽  
Author(s):  
Qinghua Liu ◽  
Ying Zhang ◽  
Jiwei Zhang ◽  
Kun Tao ◽  
Brett D Hambly ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Prognostic Factor ◽  
Early Diagnosis ◽  
Precision Medicine ◽  
Cellular Therapy ◽  
Inverse Correlation ◽  
Independent Prognostic Factor ◽  
Cancer Tissue ◽  
High Morbidity ◽  
Potential Biomarker

Abstract Background : Gastric cancer (GC) is a malignancy with high morbidity/mortality, partly due to a lack of reliable biomarkers for early diagnosis. It is important to develop reliable biomarker(s) with specificity, sensitivity and convenience for early diagnosis. The role of tumour-associated macrophages (TAMs) and survival of GC patients are controversial. Macrophage colony stimulating factor (MCSF) regulates monocytes/macrophages. Elevated MCSF is correlated with invasion, metastasis and poor survival of tumour patients. IL-34, a ligand of the MCSF receptor, acts as a “twin” to MCSF, demonstrating overlapping and complimentary actions. IL-34 involvement in tumours is controversial, possibly due to the levels of MCSF receptors. While the IL‑34/MCSF/MCSFR axis is very important for regulating macrophage differentiation, the specific interplay between these cytokines, macrophages and tumour development is unclear. Methods : A multi-factorial evaluation could provide more objective utility, particularly for either prediction and/or prognosis of gastric cancer. Precision medicine requires molecular diagnosis to determine the specifically mutant function of tumours, and is becoming popular in the treatment of malignancy. Therefore, elucidating specific molecular signalling pathways in specific cancers facilitates the success of a precision medicine approach. Gastric cancer tissue arrays were generated from stomach samples with TNM stage, invasion depth and the demography of these patients (n=185). Using immunohistochemistry/histopathology, MCSF, IL-34 and macrophages were determined. Results : We found that IL-34 may serve as a predictive biomarker, but not as an independent, prognostic factor in GC; MCSF inversely correlated with survival of GC in TNM III‑IV subtypes. Increased CD68 + TAMs were a good prognostic factor in some cases and could be used as an independent prognostic factor in male T3 stage GC. Conclusion : Our data support the potency of IL-34, MCSF, TAMs and the combination of IL‑34/TAMs as novel biological markers for GC, and may provide new insight for both diagnosis and cellular therapy of GC.

Evaluation of REG4 for early diagnosis and prognosis of gastric cancer

2011 ◽  
Vol 42 (10) ◽  
pp. 1401-1409 ◽  
Author(s):  
Hou-Quan Tao ◽  
Xu-Jun He ◽  
Ying-Yu Ma ◽  
Hui-Ju Wang ◽  
Ying-Jie Xia ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Early Diagnosis ◽  
Diagnosis And Prognosis

scholarly journals DEK Is a Potential Biomarker Associated with Malignant Phenotype in Gastric Cancer Tissues and Plasma

2019 ◽  
Vol 20 (22) ◽  
pp. 5689 ◽  
Author(s):  
Kam-Fai Lee ◽  
Ming-Ming Tsai ◽  
Chung-Ying Tsai ◽  
Chung-Guei Huang ◽  
Yu-Hsiang Ou ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Carbohydrate Antigen ◽  
Enzyme Linked Immunosorbent Assay ◽  
Absolute Quantitation ◽  
Roc Curve Analysis ◽  
Diagnosis And Prognosis ◽  
Potential Biomarker ◽  
Ca 19.9 ◽  
Novel Biomarkers ◽  
Isobaric Tags

Gastric cancer (GC) is the second most widespread cause of cancer-related mortality worldwide. The discovery of novel biomarkers of oncoproteins can facilitate the development of therapeutic strategies for GC treatment. In this study, we identified novel biomarkers by integrating isobaric tags for relative and absolute quantitation (iTRAQ), a human plasma proteome database, and public Oncomine datasets to search for aberrantly expressed oncogene-associated proteins in GC tissues and plasma. One of the most significantly upregulated biomarkers, DEK, was selected and its expression validated. Our immunohistochemistry (IHC) (n = 92) and quantitative real-time polymerase chain reaction (qRT-PCR) (n = 72) analyses disclosed a marked increase in DEK expression in tumor tissue, compared with paired nontumor mucosa. Importantly, significantly higher preoperative plasma DEK levels were detected in GC patients than in healthy controls via enzyme-linked immunosorbent assay (ELISA). In clinicopathological analysis, higher expression of DEK in both tissue and plasma was significantly associated with advanced stage and poorer survival outcomes of GC patients. Data from receiver operating characteristic (ROC) curve analysis disclosed a better diagnostic accuracy of plasma DEK than carcinoembryonic antigen (CEA), carbohydrate antigen 19.9 (CA 19.9), and C-reactive protein (CRP), highlighting its potential as an effective plasma biomarker for GC. Plasma DEK is also more sensitive in tumor detection than the other three biomarkers. Knockdown of DEK resulted in inhibition of GC cell migration via a mechanism involving modulation of matrix metalloproteinase MMP-2/MMP-9 level and vice versa. Our results collectively support plasma DEK as a useful biomarker for making diagnosis and prognosis of GC patients.

scholarly journals The miR-17-92 cluster as a potential biomarker for the early diagnosis of gastric cancer: evidence and literature review

Oncotarget ◽  
2017 ◽  
Vol 8 (28) ◽  
pp. 45060-45071 ◽  
Author(s):  
Hong Li ◽  
Qiong Wu ◽  
Ting Li ◽  
Changhao Liu ◽  
Lin Xue ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Early Diagnosis ◽  
Literature Review ◽  
Potential Biomarker

scholarly journals Prediction of Gastric Cancer-Related Proteins Based on Graph Fusion Method

2021 ◽  
Vol 9 ◽  
Author(s):  
Hao Zhang ◽  
Ruisi Xu ◽  
Meng Ding ◽  
Ying Zhang
Keyword(s):  
Gastric Cancer ◽  
Early Diagnosis ◽  
High Speed ◽  
Large Scale ◽  
Interaction Network ◽  
Proteomics Data ◽  
Speed Increase ◽  
Topological Features ◽  
Potential Biomarker ◽  
Related Proteins

Gastric cancer is a common malignant tumor of the digestive system with no specific symptoms. Due to the limited knowledge of pathogenesis, patients are usually diagnosed in advanced stage and do not have effective treatment methods. Proteome has unique tissue and time specificity and can reflect the influence of external factors that has become a potential biomarker for early diagnosis. Therefore, discovering gastric cancer-related proteins could greatly help researchers design drugs and develop an early diagnosis kit. However, identifying gastric cancer-related proteins by biological experiments is time- and money-consuming. With the high speed increase of data, it has become a hot issue to mine the knowledge of proteomics data on a large scale through computational methods. Based on the hypothesis that the stronger the association between the two proteins, the more likely they are to be associated with the same disease, in this paper, we constructed both disease similarity network and protein interaction network. Then, Graph Convolutional Networks (GCN) was applied to extract topological features of these networks. Finally, Xgboost was used to identify the relationship between proteins and gastric cancer. Results of 10-cross validation experiments show high area under the curve (AUC) (0.85) and area under the precision recall (AUPR) curve (0.76) of our method, which proves the effectiveness of our method.

scholarly journals Metabolomic profiling on plasma reveals potential biomarkers for screening and early diagnosis of gastric cancer and precancerous stages

2020 ◽  
Author(s):  
Lijing Du ◽  
Shasha Li ◽  
Xue Xiao ◽  
Jin Li ◽  
Huizi Jin ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Early Diagnosis ◽  
High Performance ◽  
Diagnostic Performance ◽  
Roc Analysis ◽  
Characteristic Curve ◽  
Disease Process ◽  
Potential Biomarker ◽  
Disease Stratification ◽  
Potential Biomarkers

Abstract Background: Gastric cancer (GC) remains one of the most common cancers all over the world. The greatest challenge for GC is that it is often detected at advanced stages, leading to the loss of optimum time for treatment and giving rise to poor prognosis. Thus, there is a critical need to develop effective and noninvasive strategies for early diagnosis of the disease process. Methods: In total, 82 participants were enrolled in the study, including 50 chronic superficial gastritis (CSG) patients, 7 early gastric cancer (EGC) and 25 advanced gastric cancer (AGC) ones. Metabolites profiling on patient plasma was performed using ultra-high performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry ( UPLC-Q-TOF/MS ). Principal components analysis as well as orthogonal partial least squares-discriminant analysis was utilized to evaluate the variation on endogenous metabolites for GC patients and to screen potential biomarkers. Furthermore, the biomarker panels detected above were used to create logistic regression models, which discrimination efficiency and accuracy was ascertained by receiver operating characteristic curve (ROC) analysis. Metabolic pathways were carried out on MetaboAnalyst. Results: Totally 50 metabolites were detected differentially expressed among CSG, EGC and AGC patients. L-carnitine, L-proline, pyruvaldehyde, phosphatidylcholines (PC) (14:0/18:0), lysophosphatidylcholine (14:0) (LysoPC 14:0), lysinoalanine were defined as the potential biomarker panel for the diagnosis among CSG and EGC patients. Compared with EGC patients, 6 significantly changed metabolites, PC(O-18:0/0:0) and LysoPC(20:4(5Z,8Z,11Z,14Z)) were found to be up-regulated, whereas L-proline, L-valine, adrenic acid and pyruvaldehyde to be down-regulated in AGC patients. ROC analysis demonstrated a high diagnostic performance for metabolite panels with area under the curve (AUC) of 0.931 to 1. Moreover, the metabolomic pathway analysis revealed several metabolism pathway disruptions, including amino acid and lipid metabolisms, in GC patients. Conclusions: In this study, a total of six differential metabolites that contributed to GC and precancerous stages were identified, respectively. The biomarker panels further improve diagnostic performance for detecting GC, with AUC values of more than 93.1%. It indicated that the biomarker panels may be sensitive to the early diagnosis of GC disease, which can be used as a promising diagnostic and prognostic tool for disease stratification studies.

Sign in / Sign up

Export Citation Format

Share Document