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Differential Expression of Peroxisomal Proteins in Distinct Types of Parotid Gland Tumors.

ABSTRACT: Salivary gland cancers are rare but aggressive tumors that have poor prognosis and lack effective cure. Of those, parotid tumors constitute the majority. Functioning as metabolic machinery contributing to cellular redox balance, peroxisomes have emerged as crucial players in tumorigenesis. Studies on murine and human cells have examined the role of peroxisomes in carcinogenesis with conflicting results. These studies either examined the consequences of altered peroxisomal proliferators or compared their expression in healthy and neoplastic tissues. None, however, examined such differences exclusively in human parotid tissue or extended comparison to peroxisomal proteins and their associated gene expressions. Therefore, we examined differences in peroxisomal dynamics in parotid tumors of different morphologies. Using immunofluorescence and quantitative PCR, we compared the expression levels of key peroxisomal enzymes and proliferators in healthy and neoplastic parotid tissue samples. Three parotid tumor subtypes were examined: pleomorphic adenoma, mucoepidermoid carcinoma and acinic cell carcinoma. We observed higher expression of peroxisomal matrix proteins in neoplastic samples with exceptional down regulation of certain enzymes; however, the degree of expression varied between tumor subtypes. Our findings confirm previous experimental results on other organ tissues and suggest peroxisomes as possible therapeutic targets or markers in all or certain subtypes of parotid neoplasms.

SUBMITTER: Meyer MT

PROVIDER: S-EPMC8345988 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

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Differential Expression of Peroxisomal Proteins in Distinct Types of Parotid Gland Tumors.

Meyer Malin Tordis MT Watermann Christoph C Dreyer Thomas T Wagner Steffen S Wittekindt Claus C Klussmann Jens Peter JP Ergün Süleyman S Baumgart-Vogt Eveline E Karnati Srikanth S

International journal of molecular sciences 20210723 15

Salivary gland cancers are rare but aggressive tumors that have poor prognosis and lack effective cure. Of those, parotid tumors constitute the majority. Functioning as metabolic machinery contributing to cellular redox balance, peroxisomes have emerged as crucial players in tumorigenesis. Studies on murine and human cells have examined the role of peroxisomes in carcinogenesis with conflicting results. These studies either examined the consequences of altered peroxisomal proliferators or compar ...[more]

PMID: 34360635

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Project description:BackgroundParotid gland tumors (PGTs) are the most common benign tumors of salivary gland tumors. However, the diagnostic value of relative values of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion kurtosis imaging (DKI) parameters for PGTs has not been extensively studied. Therefore, this study aimed to evaluate the diagnostic performance of combined DKI and DCE-MRI for differentiating PGTs by introducing the concept of relative value.MethodsThe DCE-MRI and DKI imaging data of 142 patients with PGTs between June 2018 and August 2022 were collected. Patients were divided into four groups by histopathology: malignant tumors (MTs), pleomorphic adenomas (PAs), Warthin tumors (WTs), and basal cell adenomas (BCAs). All MRI examinations were conducted using a 3 T MRI scanner with a 20-channel head and neck coil. Quantitative parameters of DCE-MRI and DKI and their relative values were determined. Kruskal-Wallis H test, post-hoc test with Bonferroni correction, one-way analysis of variance (ANOVA) and post-hoc test with least significant difference (LSD) method, and the receiver operating characteristic (ROC) curve were used for statistical analysis. Statistical significance was set at P<0.05.ResultsOnly the combination of DKI and DCE-MRI parameters could reliably distinguish BCAs from other PGTs. PAs demonstrated the lowest transfer constant from plasma to extravascular extracellular space (Ktrans) value [0.09 (0.06, 0.20) min-1], relative Ktrans (rKtrans) [-0.24 (-0.64, 1.00)], rate constant from extravascular extracellular space to plasma (Kep) value [0.32 (0.22, 0.53) min-1], relative Kep (rKep) [0.32 (0.22, 0.53) min-1], and initial area under curve (iAUC) value [0.15 (0.09, 0.26) mmol·s/kg] compared with WTs, BCAs, and MTs (all P<0.05). The Ktrans values for MTs were substantially lower [0.17 (0.10, 0.31) min-1] than those for WTs (P=0.01). The Kep values for MTs [0.71 (0.52, 1.28) min-1] were substantially lower (all P<0.05) than those for WTs and BCAs. PAs and BCAs had higher diffusion coefficient (D) values and lower diffusion kurtosis (K) values and relative K (rK) values than MTs and WTs. However, the D and K values did not differ significantly even in their relative values of PAs and BCAs (all P>0.05). By using logistic regression, the combination of K value and rKep value further enhanced their discriminatory power between PAs and WTs [area under the ROC curve (AUC), 0.986], the combination of K and rKep value further enhanced their discriminatory power between PAs and MTs (AUC, 0.915), and the combination of D and Kep value further enhanced their discriminatory power between BCAs and MTs (AUC, 0.909).ConclusionsDKI and DCE-MRI can be used to differentiate PGTs quantitatively and can complement each other. The combined use of DKI and DCE-MRI parameters can improve the diagnostic accuracy of distinguishing PGTs.

Project description:ObjectiveThis study assessed whether radiomics features could stratify parotid gland tumours accurately based on only noncontrast CT images and validated the best classifier of different radiomics models.MethodsIn this single-centre study, we retrospectively recruited 249 patients with a diagnosis of pleomorphic adenoma (PA), Warthin tumour (WT), basal cell adenoma (BCA) or malignant parotid gland tumours (MPGTs) from June 2020 to August 2022. Each patient was randomly classified into training and testing cohorts at a ratio of 7:3, and then, pairwise comparisons in different parotid tumour groups were performed. CT images were transferred to 3D-Slicer software and the region of interest was manually drawn for feature extraction. Feature selection methods were performed using the intraclass correlation coefficient, t test and least absolute shrinkage and selection operator. Five common classifiers, namely, random forest (RF), support vector machine (SVM), logistic regression (LR), K-nearest neighbours (KNN) and general Bayesian network (Gnb), were selected to build different radiomics models. The receiver operating characteristic curve, area under the curve (AUC), accuracy, sensitivity, specificity and F-1 score were used to assess the prediction performances of these models. The calibration of the model was calculated by the Hosmer-Lemeshow test. DeLong's test was utilized for comparing the AUCs.ResultsThe radiomics model based on the RF, SVM, Gnb, LR, LR and RF classifiers obtained the highest AUC in differentiating PA from MPGTs, WT from MPGTs, BCA from MPGTs, PA from WT, PA from BCA, and WT from BCA, respectively. Accordingly, the AUC and the accuracy of the model for each classifier were 0.834 and 0.71, 0.893 and 0.79, 0.844 and 0.79, 0.902 and 0.88, 0.602 and 0.68, and 0.861 and 0.94, respectively.ConclusionOur study demonstrated that noncontrast CT-based radiomics could stratify refined pathological types of parotid tumours well but could not sufficiently differentiate PA from BCA. Different classifiers had the best diagnostic performance for different parotid tumours. Our study findings add to the current knowledge on the differential diagnosis of parotid tumours.

Project description:BackgroundEarly detection and diagnosis of parotid gland cancer (PGC) are essential to improve clinical outcomes, because Tumor-Node-Metastasis stage at diagnosis is a very strong indicator of prognosis in PGC. Nevertheless, some patients still present with large parotid mass, maybe due to the unawareness or ignorance of their disease. In this study, we aimed to present the clinical outcomes of bulky PGC (defined by a 4 cm cutoff point for T3-4 versus T1-2 tumors), to emphasize the necessity of a self-examination tool for parotid gland tumor.MethodsWe retrospectively reviewed 60 consecutive cases with bulky (equal to and greater than 4 cm in the longest diameter, determined radiologically) malignant tumors arising from the parotid gland from 1995 to 2016. The clinical and pathological factors were analyzed to identify risk factors for poor outcomes using Cox proportional hazard models. In addition, we designed a self-examination tool for parotid gland tumors, similar to breast self-examination for breast cancer detection.ResultsPatients with bulky parotid cancer showed 48.9% 5-year and 24.5% 10-year overall survival rates and a 47.9% risk of high-grade malignancy. The common pathological diagnoses were carcinoma ex pleomorphic adenoma (18.3%), adenocarcinoma (16.7%), mucoepidermoid carcinoma (16.7%), salivary duct carcinoma (16.7%), and adenoid cystic carcinoma (11.7%). Survival analyses revealed that tumor size (hazard ratio, HR = 1.262 upon increase of 1 cm, 95% confidence interval, 95%CI 1.059-1.502), lymph node metastasis (HR = 2.999, 95%CI 1.048-8.583), and high tumor grade (HR = 4.148, 95%CI 1.215-14.154) were independent prognostic factors in multivariable analysis. Functional preservation of the facial nerve was possible only in less than half of patients.ConclusionIn bulky PGC, lymph node metastasis at diagnosis and high tumor grade indicated poor survival outcomes, and functional outcomes of the facial nerve were suboptimal. Thus, a public effort seems to be necessary to decrease these patients with bulky PGC, and to increase patients' self-awareness of their disease. As a way of early detection, we proposed a parotid self-examination tool to detect parotid gland tumors at an early stage, which is similar to breast self-examination.

Dataset Information

Differential Expression of Peroxisomal Proteins in Distinct Types of Parotid Gland Tumors.

Publications

Differential Expression of Peroxisomal Proteins in Distinct Types of Parotid Gland Tumors.

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