Putative Biomarkers of malignant transformation of sinonasal inverted papilloma into squamous cell carcinoma
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PROVIDER: PRJNA516218 | ENA |
REPOSITORIES: ENA
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Project description:OBJECTIVE: Although the malignant transformation of sinonasal inverted papilloma (SNIP) into squamous cell carcinomas (SCC) has been reported in the literature, the molecular mechanisms driving this transformation have not been elucidated. This study compares genome-wide DNA methylation between SNIP and SCC arising in SNIP and further validates the expression of aberrantly methylated genes. Methots:We used a comprehensive methylation profiling technique to investigate DNA methylation in CpG islands and promoters in six SNIP samples and seven SCC arising in SNIP samples. A total of 11,201 nominally differentially methylated sites were observed, between SNIP and SCC arising in SNIP. This study is the first to compare the differences in global DNA methylation between SNIP and SCC arising in SNIP.
2019-01-22 | GSE125399 | GEO
Project description:To explore the expression profile, potential functions, and diagnostic and clinicopathological significance of lncRNAs in sinonasal inverted papilloma (SNIP).The expression profiles of lncRNAs and mRNAs were analyzed using a microarray. The potential functions and clinical implications of specific lncRNAs were further analyzed by bioinformatics and statistical methods.
2022-01-05 | GSE193016 | GEO
Project description:Microarray analysis of lncRNA and mRNA expression profiles in sinonasal inverted papilloma
| PRJNA794137 | ENA
Project description:PurposeAccurate preoperative prediction of the malignant transformation of sinonasal inverted papilloma (IP) is essential for guiding biopsy, planning appropriate surgery and prognosis of patients. We aimed to investigate the value of MRI-based radiomics in discriminating IP from IP-transformed squamous cell carcinomas (IP-SCC).MethodsA total of 236 patients with IP-SCC (n=92) or IP (n=144) were enrolled and divided into a training cohort and a testing cohort. Preoperative MR images including T1-weighted, T2-weighted, and contrast enhanced T1-weighted images were collected. Radiomic features were extracted from MR images and key features were merged into a radiomic model. A morphological features model was developed based on MR morphological features assessed by radiologists. A combined model combining radiomic features and morphological features was generated using multivariable logistic regression. For comparison, two head and neck radiologists were independently invited to distinguish IP-SCC from IP. The area under the receiver operating characteristics curve (AUC) was used to assess the performance of all models.ResultsA total of 3948 radiomic features were extracted from three MR sequences. After feature selection, we saved 15 key features for modeling. The AUC, sensitivity, specificity, and accuracy on the testing cohort of the combined model based on radiomic and morphological features were respectively 0.962, 0.828, 0.94, and 0.899. The diagnostic ability of the combined model outperformed the morphological features model and also outperformed the two head and neck radiologists.ConclusionsA combined model based on MR radiomic and morphological features could serve as a potential tool to accurately predict IP-SCC, which might improve patient counseling and make more precise treatment planning.
| S-EPMC8983836 | biostudies-literature
Project description:ObjectiveTo investigate the diagnostic performance of quantitative and semi-quantitative parameters derived from dynamic contrast-enhanced MRI (DCE-MRI) in differentiating sinonasal inverted papilloma (SIP) from SIP with coexisting malignant transformation into squamous cell carcinoma (MT-SIP).MethodsThis retrospective study included 122 patients with 88 SIP and 34 MT-SIP. Quantitative and semi-quantitative parameters derived from DCE-MRI were compared between SIP and MT-SIP. The multivariate logistic regression analysis was performed to identify independent indicators and construct regression model for distinguishing MT-SIP and SIP. Diagnostic performance of independent indicators and regression model were evaluated using receiver operating coefficient (ROC) analysis and compared using DeLong test.ResultsThere were significant differences in maximum slope of increase, contrast-enhancement ratio, bolus arrival time, volume of extravascular extracellular space (Ve), and rate constant (Kep) between SIP and MT-SIP (p < 0.05). There were no significant differences in initial area under the gadolinium curve (p = 0.174) and volume transfer constant (p = 0.105) between two groups. Multivariate analysis results showed that Ve and Kep were identified as the independent indicators for differentiating MT-SIP from SIP (p < 0.001). Areas under the ROC curves (AUCs) for predicting MT-SIP were 0.779 for Ve and 0.766 for Kep. The AUC of the combination of Ve and Kep was 0.831, yielding 83% specificity and 76.5% sensitivity.ConclusionDCE-MRI can quantitatively differentiate between MT-SIP and SIP. The combination of Ve and Kep yielded an optimal performance for discriminating SIP from its malignant mimics.Advances in knowledgeDCE-MRI with quantitative and semi-quantitative parameters can provide valuable evidences for quantitatively identifying MT-SIP.
| S-EPMC10996421 | biostudies-literature
Project description:Inverted papilloma (IP) is a benign tumor occurring in the nasal cavity and paranasal sinuses. It is reported that 5-15% of IPs undergo malignant transformation into squamous cell carcinoma (SCC), and the role of microRNAs (miRNA/miR) in this process remains to be elucidated. In the present study, whole miRNA profiles using samples of IP and SCC were investigated, in order to detect the function of miRNA in the carcinogenesis of IP. Samples from IPs (n=5) and SCC lesions (n=5), which arose from IPs, were used for miRNA analysis. A total of 200 miRNAs exhibited a >2-fold differential expression between IP and SCC. miR-296-3p was markedly upregulated in SCC with a 23-fold difference. Computational analysis indicated that miR-296-3p targeted PTEN, which regulates the phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt) signaling pathway and PTEN is involved in the carcinogenesis of SCC. miR-296-3p directly regulated PTEN expression in head and neck cancer cells, with PTEN protein levels decreased in 4/19 the SCCs (21.0%), as compared with those in the IPs (76.4%). Positive p21 staining was observed in 64.7% of IPs; this was a significantly increased rate compared with that for SCCs (26.3%, P=0.0086). The results of the present study indicated that there were marked changes in the miRNA expression signature during the malignant transition. miR-296-3p may serve an important role in the malignant transformation of IPs via the regulation of PTEN, combined with the subsequent inhibition of the PI3K/Akt signaling pathway, and may be a novel agent for cancer prevention.
| S-EPMC5494725 | biostudies-other
Project description:BackgroundDNA methylation may be involved in the regulation of malignant transformation from sinonasal inverted papilloma (SNIP) to squamous cell carcinoma (SCC). The study of gene methylation changes and screening of differentially methylated loci (DMLs) are helpful to predict the possible key genes in the malignant transformation of SNIP-SCC.Materials and methodsMicroarray dataset GSE125399 was downloaded from the Gene Expression Omnibus (GEO) database and differentially methylated loci (DMLs) were analyzed using R language (Limma package). ClusterProfiler R package was used to perform Gene Ontology (GO) analysis on up-methylated genes and draw bubble maps. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and its visualization analysis were analyzed to speculate the possible key Genes in SNIP-SCC malignant transformation. Subsequently, SNIP cases archived in our department were collected, tissue microarray was made, and immunohistochemical staining was performed to analyze the expression levels of UCKL1, GSTT1, HLA-G, MAML2 and NRGN in different grades of sinonasal papilloma tissues.ResultsAnalysis of dataset GSE125399 identified 56 DMLs, including 49 upregulated DMLs and 7 downregulated DMLs. Thirty-one genes containing upregulated DNA methylation loci and three genes containing downregulated DNA methylation loci were obtained by methylation microarray annotation analysis. In addition, KEGG pathway visualization analysis of 31 up-methylated genes showed that there were four significantly up-methylated genes including UCKL1, GSTT1, HLA-G and MAML2, and one significantly down-methylated gene NRGN. Subsequently, compared with non-neoplasia nasal epithelial tissues, the expression of HLA-G and NRGN was upregulated in grade I, II, III and IV tissues, while the expression of MAML2 was lost. The protein expression changes of MAML2 and NRGN were significantly negatively correlated with their gene methylation levels.ConclusionsBy analyzing the methylation dataset, we obtained four up-regulated methylation genes UCKL1, GSTT1, HLA-G and MAML2 and one down-regulated gene NRGN. MAML2, a tumor suppressor gene with high methylation modification but loss of protein expression, and NRGN, a tumor gene with low methylation modification but upregulated protein expression, can be used as biological indicators to judge the malignant transformation of SNIP-SCC.
| S-EPMC10907326 | biostudies-literature
Project description:Objective To explore the best MRI radiomics-based machine learning model for differentiation of sinonasal inverted papilloma (SNIP) and malignant sinonasal tumor (MST), and investigate whether the combination of radiomics features and clinic–radiological features can produce a superior diagnostic performance. Methods The database of 247 patients with SNIP (n=106) or MST (n=141) were analyzed. Dataset from scanner A were randomly divided into training set (n=135) and test set 1 (n=58) in a ratio of 7:3, and dataset from scanner B and C were used as an additional independent test set 2 (n=54). Fourteen clinic-radiological features were analyzed by using univariate analysis, and those with significant differences were applied to construct clinical model. Based on the radiomics features extracted from single sequence (T2WI or CE-T1WI) and combined sequence, four commonly used classifiers (logistic regression (LR), support vector machine (SVM), decision tree (DT) and k-nearest neighbor (KNN)) were employed to constitute twelve different machine learning models, and the best-performing one was confirmed as the optimal radiomics model. Furthermore, a combined model incorporated best radiomics feature subsets and clinic-radiological features was developed. The diagnostic performances of these models were assessed by the area under the receiver operating characteristic (ROC) curve (AUC) and the calibration curves. Results Five clinic-radiological features (age, convoluted cerebriform pattern sign, heterogeneity, adjacent bone involvement and infiltration of surrounding tissue) were considered to be significantly different between the tumor groups (P < 0.05). Among the twelve machine learning models, the T2WI-SVM model exhibited optimal predictive efficacy for classification tasks on the two test sets, with the AUC of 0.878 and 0.914, respectively. For three types of diagnostic models, the combined model achieved highest AUC of 0.912 (95%CI: 0.807-0.970) and 0.927 (95%CI: 0.823-0.980) for differentiation of SNIP and MST in test 1 and test 2 sets, which performed prominently better than clinical model (P=0.011, 0.005), but not significantly different from the optimal radiomics model (P=0.100, 0.452). Conclusion The machine learning model based on T2WI sequence and SVM classifier achieved best performance in differentiation of SNIP and MST, and the combination of radiomics features and clinic-radiological features significantly improved the diagnostic capability of the model.
| S-EPMC9538572 | biostudies-literature
Project description:Inverted sinonasal papilloma (ISP) is a locally aggressive neoplasm associated with sinonasal squamous cell carcinoma (SNSCC) in 10% to 25% of cases. To date, no recurrent mutations have been identified in ISP or SNSCC. Using targeted next-generation sequencing and Sanger sequencing, we identified activating EGFR mutations in 88% of ISP and 77% of ISP-associated SNSCC. Identical EGFR genotypes were found in matched pairs of ISP and associated SNSCC, providing the first genetic evidence of a biologic link between these tumors. EGFR mutations were not identified in exophytic or oncocytic papillomas or non-ISP-associated SNSCC, suggesting that the ISP/SNSCC spectrum is biologically distinct among sinonasal squamous tumors. Patients with ISP harboring EGFR mutations also exhibited an increased progression-free survival compared with those with wild-type EGFR. Finally, treatment of ISP-associated carcinoma cells with irreversible EGFR inhibitors resulted in inactivation of EGFR signaling and growth inhibition. These findings implicate a prominent role for activating EGFR mutations in the pathogenesis of ISP and associated SNSCC and rationalize consideration of irreversible EGFR inhibitors in the therapy of these tumors.
| S-EPMC4508878 | biostudies-literature
Project description:Objective We review our institution's experience with the treatment of inverted papilloma (IP) with emphasis on the implications of surgical margins for disease control. Design Retrospective chart review of patients with IP treated at the University of Michigan from 1996 to 2011. Setting Tertiary care center. Participants Patients undergoing surgical resection with curative intent for IP. Main Outcome Measures Overall survival, disease-specific survival, and locoregional control were used as main outcome measures. Results We studied 129 patients including 19 with carcinoma arising from IP. Disease-free rates at 2, 3, and 5 years were 79.7%, 77.9%, and 61%, respectively. Overall, 10 of 18 recurrences were detected > 2 years from follow-up, with recurrences detected up to 8 years from surgery. For benign disease, obtaining tissue margins outside of the primary specimen for margin control did not affect disease control rates. Conclusion IP is a disease that requires significant follow-up periods beyond 2 years. For IP without carcinogenesis, acquiring margins outside of the tumor specimen did not appear to affect disease control rates in this study. No clear predictors of malignancy were seen in this study, which highlights the need for further research to predict this phenomenon.
| S-EPMC3969439 | biostudies-other