Dataset Information

Vocal fold leukoplakia recurrence risk model.

ABSTRACT: The paper aims to define the variables that elevate the risk of VFL recurrence after adequate primary treatment, and to present the Recurrence Risk Model with practical conclusions to handle pVFL and rVFL. Out of 207 patients with primary vocal fold leukoplakia (pVFL), in 41 (19.8%) recurrent VFL (rVFL) was diagnosed. All patients were assessed by using a trans-nasal flexible video-endoscope using white light, and NBI. The primary measure of our study was to investigate whether morphological features of pVFL in WL, vascular pattern in NBI, and primary histological findings could predict VFL recurrence. To create a model of risk factors, two methods were used: logistic regression and a conditional inference decision tree. The study showed smoking was the factor that significantly and most strongly increased the likelihood of rVFL, as well as the older age groups have a greater odds of rVFL. Types IV, V and VI, according to Ni 2019 classification, were associated with a significantly higher risk of rVFL. The algorithm combining patients' dependent variables and the combination of two classifications improves the predictive value of the presented VFL Recurrence Risk Model.

SUBMITTER: Klimza H

PROVIDER: S-EPMC10761819 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature

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Vocal fold leukoplakia recurrence risk model.

Klimza Hanna H Jackowska Joanna J Pietruszewska Wioletta W Porębski Andrzej A Nogal Piotr P Leduchowska Agata A Wierzbicka Małgorzata M

Scientific reports 20240102 1

The paper aims to define the variables that elevate the risk of VFL recurrence after adequate primary treatment, and to present the Recurrence Risk Model with practical conclusions to handle pVFL and rVFL. Out of 207 patients with primary vocal fold leukoplakia (pVFL), in 41 (19.8%) recurrent VFL (rVFL) was diagnosed. All patients were assessed by using a trans-nasal flexible video-endoscope using white light, and NBI. The primary measure of our study was to investigate whether morphological fea ...[more]

PMID: 38168150

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Project description:There is a critical need for the establishment of an engineered model of the vocal fold epithelium that can be used to gain understanding of its role in vocal fold health, disease, and facilitate the development of new treatment options. Toward this goal, we isolated primary vocal fold epithelial cells (VFECs) from healthy porcine larynxes and used them within passage 3. Culture-expanded VFECs expressed the suprabasal epithelial marker cytokeratin 13 and intercellular junctional proteins occludin, E-cadherin, and zonula occludens-1. To establish the engineered model, we cultured VFECs on a hyaluronic acid-derived synthetic basement membrane displaying fibronectin-derived integrin-binding peptide (RGDSP) and/or laminin 111-derived syndecan-binding peptide AG73 (RKRLQVQLSIRT). Our results show that matrix stiffness and composition cooperatively regulate the adhesion, proliferation, and stratification of VFECs. Cells cultured on hydrogels with physiological stiffness (elastic shear modulus, G' = 1828 Pa) adopted a cobblestone morphology with close cell-cell contacts, whereas those on softer matrices (G' = 41 Pa) were spindle shaped with extensive intracellular stress fibers. The development of stratified epithelium with proliferating basal cells and additional (1-2) suprabasal layers requires the presence of both RGDSP and AG73 peptide signals. Supplementation of cytokines produced by vimentin positive primary porcine vocal fold fibroblasts in the VFEC culture led to the establishment of 4-5 distinct cell layers. The engineered vocal fold epithelium resembled native tissue morphologically; expressed cytokeratin 13, mucin 1, and tight/adherens junction markers; and secreted basement membrane proteins collagen IV and laminin 5. Collectively, our results demonstrate that stiffness matching, cell-matrix engagement, and paracrine signaling cooperatively contribute to the stratification of VFECs. The engineered epithelium can be used as a versatile tool for investigations of genetic and molecular mechanisms in vocal fold health and disease.

Dataset Information

Vocal fold leukoplakia recurrence risk model.

Publications

Vocal fold leukoplakia recurrence risk model.

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