scholarly journals Diagnostic and prognostic utilities of humoral fibulin-3 in malignant pleural mesothelioma: Evidence from a meta-analysis

Oncotarget ◽  
2017 ◽  
Vol 8 (8) ◽  
pp. 13030-13038 ◽  
Author(s):  
Dongxu Pei ◽  
Yongwei Li ◽  
Xinwei Liu ◽  
Sha Yan ◽  
Xiaolan Guo ◽  
...  
2019 ◽  
Vol 40 (11) ◽  
pp. 1320-1331 ◽  
Author(s):  
Christina N Gillezeau ◽  
Maaike van Gerwen ◽  
Julio Ramos ◽  
Bian Liu ◽  
Raja Flores ◽  
...  

Abstract Malignant pleural mesothelioma (MPM) is a rare but aggressive cancer, and early detection is associated with better survival. Mesothelin, fibulin-3 and osteopontin have been suggested as screening biomarkers. The study conducted a meta-analysis of the mean differences of mesothelin, osteopontin and fibulin-3 in blood and pleural samples. PubMed searches were conducted for studies that measured levels of mesothelin, osteopontin and fibulin-3 in participants with MPM compared with malignancy, benign lung disease or healthy participants. Thirty-two studies with mesothelin levels, 12 studies with osteopontin levels and 9 studies with fibulin-3 levels were included in the meta-analysis. Statistically significant mean differences were seen between MPM patients and all other comparison groups for mesothelin blood and pleural levels. Statistically significant differences in blood osteopontin levels were seen between participants with benign lung disease and healthy participants compared with participants with MPM, but not when comparing participants with cancer with MPM participants. There were not enough studies that reported osteopontin levels in pleural fluid to complete a meta-analysis. Statistically significant differences were seen in both blood and pleural levels of fibulin-3 in MPM patients compared with all other groups. On the basis of these results, mesothelin and fibulin-3 levels appear to be significantly lower in all control groups compared with those with MPM, making them good candidates for screening biomarkers. Osteopontin may be a useful biomarker for screening healthy individuals or those with benign lung disease but would not be useful for screening patients with malignancies.


Oncotarget ◽  
2017 ◽  
Vol 8 (28) ◽  
pp. 46425-46435 ◽  
Author(s):  
Long Tian ◽  
Rujun Zeng ◽  
Xin Wang ◽  
Cheng Shen ◽  
Yutian Lai ◽  
...  

2020 ◽  
Vol 12 ◽  
pp. 175883592096236
Author(s):  
Liu Jin ◽  
Weiling Gu ◽  
Xueqin Li ◽  
Liang Xie ◽  
Linhong Wang ◽  
...  

Background: The prognostic value of programmed death-ligand 1 (PD-L1) expression in patients with malignant pleural mesothelioma (MPM) has been controversial according to previous investigations. Therefore, we conducted a meta-analysis to assess the potential prognostic significance of PD-L1 expression in MPM. Methods: PubMed, Embase, Web of Science, Scopus, and the Cochrane Library were thoroughly searched for relevant original articles published before 9 April 2020. The pooled hazard ratios (HRs) and 95% confidence intervals (CIs) of overall survival (OS) and progression-free survival (PFS) were calculated. The results of the meta-analysis were verified using The Cancer Genome Atlas (TCGA) dataset. Results: In total 16 studies were included in our meta-analysis. A high PD-L1 expression was associated with a poor OS (HR = 1.53, 95% CI = 1.28–1.83, p < 0.001), but not a grave PFS (HR = 1.07, 95% CI = 0.82–1.39, p = 0.643) in MPM. Furthermore, the PD-L1 expression correlated with the sarcomatoid + biphasic type of MPM (odds ratio = 4.32, 95% CI = 2.16–8.64, p < 0.001). TCGA data indicated that PD-L1 was a significant prognostic factor for OS (HR = 2.069, 95% CI = 1.136–3.769, p = 0.0175), but not for PFS (HR = 1.205, 95% CI = 0.572–2.539, p = 0.624), which was in accordance with the results of the meta-analysis. Conclusion: A high PD-L1 expression is a significant prognostic factor for poor OS of patients with MPM. We therefore suggest that PD-L1 expression levels can be used to predict the clinical outcomes of patients with MPM in the future.


Oncotarget ◽  
2016 ◽  
Vol 7 (51) ◽  
pp. 84851-84859 ◽  
Author(s):  
Ran Ren ◽  
Pengpeng Yin ◽  
Yan Zhang ◽  
Jianyun Zhou ◽  
Yixing Zhou ◽  
...  

2015 ◽  
Vol 309 (7) ◽  
pp. L677-L686 ◽  
Author(s):  
Georgios D. Vavougios ◽  
Evgeniy I. Solenov ◽  
Chrissi Hatzoglou ◽  
Galina S. Baturina ◽  
Liubov E. Katkova ◽  
...  

The aim of our study was to assess the differential gene expression of Parkinson protein 7 (PARK7) interactome in malignant pleural mesothelioma (MPM) using data mining techniques to identify novel candidate genes that may play a role in the pathogenicity of MPM. We constructed the PARK7 interactome using the ConsensusPathDB database. We then interrogated the Oncomine Cancer Microarray database using the Gordon Mesothelioma Study, for differential gene expression of the PARK7 interactome. In ConsensusPathDB, 38 protein interactors of PARK7 were identified. In the Gordon Mesothelioma Study, 34 of them were assessed out of which SUMO1, UBC3, KIAA0101, HDAC2, DAXX, RBBP4, BBS1, NONO, RBBP7, HTRA2, and STUB1 were significantly overexpressed whereas TRAF6 and MTA2 were significantly underexpressed in MPM patients ( network 2). Furthermore, Kaplan-Meier analysis revealed that MPM patients with high BBS1 expression had a median overall survival of 16.5 vs. 8.7 mo of those that had low expression. For validation purposes, we performed a meta-analysis in Oncomine database in five sarcoma datasets. Eight network 2 genes (KIAA0101, HDAC2, SUMO1, RBBP4, NONO, RBBP7, HTRA2, and MTA2) were significantly differentially expressed in an array of 18 different sarcoma types. Finally, Gene Ontology annotation enrichment analysis revealed significant roles of the PARK7 interactome in NuRD, CHD, and SWI/SNF protein complexes. In conclusion, we identified 13 novel genes differentially expressed in MPM, never reported before. Among them, BBS1 emerged as a novel predictor of overall survival in MPM. Finally, we identified that PARK7 interactome is involved in novel pathways pertinent in MPM disease.


Oncotarget ◽  
2018 ◽  
Vol 9 (30) ◽  
pp. 21628-21628
Author(s):  
Dongxu Pei ◽  
Yongwei Li ◽  
Xinwei Liu ◽  
Sha Yan ◽  
Xiaolan Guo ◽  
...  

BMJ Open ◽  
2014 ◽  
Vol 4 (2) ◽  
pp. e004145 ◽  
Author(s):  
Ai Cui ◽  
Xiao-Guang Jin ◽  
Kan Zhai ◽  
Zhao-Hui Tong ◽  
Huan-Zhong Shi

Sign in / Sign up

Export Citation Format

Share Document