| Title |
Tissue metabolic profiling of human gastric cancer assessed by 1H NMR
|
|---|---|
| Published in |
BMC Cancer, June 2016
|
| DOI | 10.1186/s12885-016-2356-4 |
| Pubmed ID | |
| Authors |
Huijuan Wang, Hailong Zhang, Pengchi Deng, Chunqi Liu, Dandan Li, Hui Jie, Hu Zhang, Zongguang Zhou, Ying-Lan Zhao |
| Abstract |
Gastric cancer is the fourth most common cancer and the second most deadly cancer worldwide. Study on molecular mechanisms of carcinogenesis will play a significant role in diagnosing and treating gastric cancer. Metabolic profiling may offer the opportunity to understand the molecular mechanism of carcinogenesis and help to identify the potential biomarkers for the early diagnosis of gastric cancer. In this study, we reported the metabolic profiling of tissue samples on a large cohort of human gastric cancer subjects (n = 125) and normal controls (n = 54) based on (1)H nuclear magnetic resonance ((1)H NMR) together with multivariate statistical analyses (PCA, PLS-DA, OPLS-DA and ROC curve). The OPLS-DA model showed adequate discrimination between cancer tissues and normal controls, and meanwhile, the model excellently discriminated the stage-related of tissue samples (stage I, 30; stage II, 46; stage III, 37; stage IV, 12) and normal controls. A total of 48 endogenous distinguishing metabolites (VIP > 1 and p < 0.05) were identified, 13 of which were changed with the progression of gastric cancer. These modified metabolites revealed disturbance of glycolysis, glutaminolysis, TCA, amino acids and choline metabolism, which were correlated with the occurrence and development of human gastric cancer. The receiver operating characteristic diagnostic AUC of OPLS-DA model between cancer tissues and normal controls was 0.945. And the ROC curves among different stages cancer subjects and normal controls were gradually improved, the corresponding AUC values were 0.952, 0.994, 0.998 and 0.999, demonstrating the robust diagnostic power of this metabolic profiling approach. As far as we know, the present study firstly identified the differential metabolites in various stages of gastric cancer tissues. And the AUC values were relatively high. So these results suggest that the metabolic profiling of gastric cancer tissues has great potential in detecting this disease and helping to understand its underlying metabolic mechanisms. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Saudi Arabia | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 33% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 1 | 2% |
| Unknown | 42 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 19% |
| Student > Master | 6 | 14% |
| Student > Doctoral Student | 5 | 12% |
| Researcher | 5 | 12% |
| Student > Bachelor | 3 | 7% |
| Other | 7 | 16% |
| Unknown | 9 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 13 | 30% |
| Agricultural and Biological Sciences | 8 | 19% |
| Chemistry | 4 | 9% |
| Medicine and Dentistry | 2 | 5% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 2% |
| Other | 1 | 2% |
| Unknown | 14 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 June 2016.
All research outputs
#15,557,505
of 23,881,329 outputs
Outputs from BMC Cancer
#3,807
of 8,483 outputs
Outputs of similar age
#217,920
of 356,000 outputs
Outputs of similar age from BMC Cancer
#93
of 227 outputs
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