| Title |
Abnormal expression levels of sMICA and NKG2D are correlated with poor prognosis in pancreatic cancer
|
|---|---|
| Published in |
Therapeutics and Clinical Risk Management, December 2015
|
| DOI | 10.2147/tcrm.s96869 |
| Pubmed ID | |
| Authors |
Jiong Chen, Hong Xu, Xing-Xing Zhu |
| Abstract |
Soluble major histocompatibility complex class I-related chain A molecules (sMICA) and natural-killer group 2 member D (NKG2D) not only correlate with tumorigenesis and progression, but also with tumor invasion and metastasis. In this study, we used immunohistochemistry to investigate the correlation and prognostic significance of the differential expression of sMICA and NKG2D in pancreatic carcinoma and paracarcinoma tissues from 70 patients with pancreatic carcinomas. The results showed that sMICA expression was significantly (P<0.05) higher in tumor tissues (67.1%) than that in adjacent nontumor tissues (31.4%), whereas NKG2D expression was significantly (P<0.001) lower in tumor tissues (32.9%) than that in adjacent nontumor tissues (60.0%). Spearman's rank correlation test showed a negative correlation between the expression of sMICA and that of NKG2D (r=-0.676, P<0.001). Kaplan-Meier survival analysis showed that a high sMICA expression was significantly correlated with decreased disease-free survival (DFS) (P<0.001) and overall survival (OS) (P<0.001), while a high NKG2D expression was significantly associated with increased DFS (P=0.001) and OS (P=0.001) of the patients. Multivariate analysis showed that a high sMICA expression was an independent predictive factor for poor DFS (P<0.001) and OS (P=0.012); but low NKG2D expression was not an independent prognostic factor for poor DFS (P=0.238) and OS (P=0.574). In conclusion, our findings suggest that the expression levels of sMICA and NKG2D are abnormal and negatively correlated with one another in pancreatic carcinoma tissues; they may be considered as valuable biomarkers for the prognosis of pancreatic carcinoma. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 3 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 15 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 40% |
| Researcher | 2 | 13% |
| Student > Bachelor | 2 | 13% |
| Other | 1 | 7% |
| Student > Doctoral Student | 1 | 7% |
| Other | 1 | 7% |
| Unknown | 2 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 6 | 40% |
| Biochemistry, Genetics and Molecular Biology | 3 | 20% |
| Immunology and Microbiology | 2 | 13% |
| Environmental Science | 1 | 7% |
| Chemistry | 1 | 7% |
| Other | 0 | 0% |
| Unknown | 2 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 28 December 2015.
All research outputs
#14,913,296
of 25,371,288 outputs
Outputs from Therapeutics and Clinical Risk Management
#638
of 1,323 outputs
Outputs of similar age
#195,480
of 395,411 outputs
Outputs of similar age from Therapeutics and Clinical Risk Management
#14
of 43 outputs
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