scholarly journals Variation in Plasma Levels of TRAF2 Protein During Development of Squamous Cell Carcinoma of the Oral Tongue

2021 ◽  
Vol 11 ◽  
Author(s):  
Xiaolian Gu ◽  
Philip Coates ◽  
Lixiao Wang ◽  
Baris Erdogan ◽  
Amir Salehi ◽  
...  

As early detection is crucial for improvement of cancer prognosis, we searched for biomarkers in plasma from individuals who later developed squamous cell carcinoma of the oral tongue (SCCOT) as well as in patients with an already established SCCOT. Levels of 261 proteins related to inflammation and/or tumor processes were measured using the proximity extension assay (PEA) in 179 plasma samples (42 collected before diagnosis of SCCOT with 81 matched controls; 28 collected at diagnosis of SCCOT with 28 matched controls). Statistical modeling tools principal component analysis (PCA) and orthogonal partial least square - discriminant analysis (OPLS-DA) were applied to provide insights into separations between groups. PCA models failed to achieve group separation of SCCOT patients from controls based on protein levels in samples taken prior to diagnosis or at the time of diagnosis. For pre-diagnostic samples and their controls, no significant OPLS-DA model was identified. Potentials for separating pre-diagnostic samples collected up to five years before diagnosis (n = 15) from matched controls (n = 28) were seen in four proteins. For diagnostic samples and controls, the OPLS-DA model indicated that 21 proteins were important for group separation. TNF receptor associated factor 2 (TRAF2), decreased in pre-diagnostic plasma (< 5 years) but increased at diagnosis, was the only protein showing altered levels before and at diagnosis of SCCOT (p-value < 0.05). Taken together, changes in plasma protein profiles at diagnosis were evident, but not reliably detectable in pre-diagnostic samples taken before clinical signs of tumor development. Variation in protein levels during cancer development poses a challenge for the identification of biomarkers that could predict SCCOT development.

2021 ◽  
Author(s):  
Rabeia Almahmoudi ◽  
Abdelhakim Salem ◽  
Elin Hadler‐Olsen ◽  
Gunbjørg Svineng ◽  
Tuula Salo ◽  
...  

PLoS ONE ◽  
2017 ◽  
Vol 12 (7) ◽  
pp. e0180620 ◽  
Author(s):  
Pei-Feng Liu ◽  
Yu-Chang Hu ◽  
Bor-Hwang Kang ◽  
Yu-Kai Tseng ◽  
Pi-Chuang Wu ◽  
...  

Cancer ◽  
2020 ◽  
Author(s):  
Benjamin R. Campbell ◽  
Zhishan Chen ◽  
Daniel L. Faden ◽  
Nishant Agrawal ◽  
Ryan J. Li ◽  
...  

2020 ◽  
Author(s):  
Na Guo ◽  
Weike Zeng ◽  
Hong Deng ◽  
Huijun Hu ◽  
Ziliang Cheng ◽  
...  

Abstract Background: To investigate whether quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) pharmacokinetic parameters can be used to predict the pathologic stages of oral tongue squamous cell carcinoma (OTSCC). Methods: For this prospective study, DCE-MRI was performed in participants with OTSCC from May 2016 to June 2017. The pharmacokinetic parameters, including K trans , K ep , V e , and V p , were derived from DCE-MRI by utilizing a two-compartment extended Tofts model and a three-dimensional volume of interest. The postoperative pathologic stage was determined in each patient based on the 8th AJCC cancer staging manual. The quantitative DCE-MRI parameters were compared between stage I-II and stage III-IV lesions. Logistic regression analysis was used to determine independent predictors of tumor stages, followed by receiver operating characteristic (ROC) analysis to evaluate the predictive performance. Results: The mean K trans , K ep and V p values were significantly lower in stage III-IV lesions compared with stage I-II lesions ( p = 0.013, 0.005 and 0.011, respectively). K ep was an independent predictor for the advanced stages as determined by univariate and multivariate logistic analysis. ROC analysis showed that K ep had the highest predictive capability, with a sensitivity of 64.3%, a specificity of 82.6%, a positive predictive value of 81.8%, a negative predictive value of 65.5%, and an accuracy of 72.5%. Conclusion: The quantitative DCE-MRI parameter K ep can be used as a biomarker for predicting pathologic stages of OTSCC.


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