Allelic loss in amalgam‐associated oral lichenoid lesions compared to oral lichen planus and mucosa

Rodrigues, Leonardo Brand; Sousa, S.M.M.; Silva, Rcc; Abreu, Mhg; Fr, Pires; Mesquita, Ricardo-Alves; Bastos‐Rodrigues, Luciana; Marco, Luiz; Gomes, Ciro Martins; Gomez, Ricardo Santiago; Bernardes, Vanessa Fátima

doi:10.1111/odi.12627

Cited by 4 publications

(4 citation statements)

References 30 publications

(52 reference statements)

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“…Several different methods have been proposed to distinguish OLL from OLP ( 1 - 4 , 22 - 27 ). Jahanshahi, Ghalayani and Maleki have suggested that the number of degranulated mast cells and greater epithelium thickness were more frequently seen in OLL than in OLP ( 23 ).…”

Section: Discussionmentioning

confidence: 99%

“…However, OLP and OLL patients revealed almost similar prolidase activity and oxidative stress levels. Rodrigues and collaborators (2017), proposed that the loss of heterozygosity in chromosomes 9p (D9S157, D9S162, D9S171), 11q (D11S1369), and 17p (TP53, AFM238WF2) occurred more frequently in OLL than in OLP ( 27 ). Our findings disclosure a weaker MT staining in OLL, when compared to OLP.…”

Section: Discussionmentioning

confidence: 99%

“…As cited above, many clinical, histopathological, immunological and genetic criteria for differentiating OLP and OLL has been proposed in literature; however, there is currently no established cutoff to facilitate their segregation ( 1 - 4 , 22 - 27 ). Furthermore, since most of the described information relies on observational studies, such data must be taken with care because of inherent biases.…”

Section: Discussionmentioning

confidence: 99%

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Differential metallothionein expression in oral lichen planus and amalgam-associated oral lichenoid lesions

Mendes

Servato²,

Borges³

et al. 2018

Med Oral

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BackgroundOral lichen planus (OLP) is a chronic inflammatory disease mediated by T cells, which manifests as reticular (white) or erosive (red) lesions, that are eventually painful. Oral lichenoid lesion (OLL) are distinguished from OLP by the presence of precipitating factors. The aim of this study was to evaluate whether the presence of metallothionein, which is involved in anti-apoptotic pathways and the anti-oxidative response, could serve as a differential diagnostic for OLP and OLL.Material and MethodsWe evaluated the expression of metallothionein in 40 cases of OLP and 20 cases of OLL using immunohistochemistry.Results and ConclusionsWhite OLP has higher concentrations of metallothionein than red OLP in basal and parabasal layers. Moreover, metallothionein was more frequently observed in the cytoplasm and nuclei of basal cells in OLP patients compared to the same regions of OLL cases. Metallothionein levels are related to OLP severity and may contribute to a differential diagnosis between OLP and OLL. Key words:Oral lichen planus, oral lichenoid lesions, autoimmune disorders, metallothionein, immunohistochemistry.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Differential metallothionein expression in oral lichen planus and amalgam-associated oral lichenoid lesions

Mendes

Servato²,

Borges³

et al. 2018

Med Oral

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show abstract

“…This mechanism is characterized by the development of a band‐like region of inflammatory mononuclear cells comprising predominantly T‐lymphocytes 2,10 . Considering that clinical and histopathological changes of OLP and OLL are reflected by distinct molecular profiles, 11,12 previous studies have attempted to discriminate between these conditions based on the nature of infiltrated inflammatory cells 13,14 . However, these variables have not been included in OLP diagnostic criteria to date, likely due to the difficulty of potential standardization and optimization issues.…”

Section: Introductionmentioning

confidence: 99%

A machine‐learning algorithm for the reliable identification of oral lichen planus

Idrees

Farah

Shearston

et al. 2021

J Oral Pathology Medicine

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Background Oral lichen planus (OLP) is a relatively common oral disorder which shares clinical and histopathological features with other lichenoid lesions, leading to considerable inter‐observer disagreement. This negatively impacts understanding of the pathogenesis and malignant transformation potential of this condition. Methods Artificial intelligence was employed to create a machine‐learning artificial neural network to identify and quantify mononuclear cells and granulocytes within the inflammatory infiltrates in digitized hematoxylin and eosin microscopic slides. Twenty‐four regions of interest were extracted from OLP cases for learning purposes and validated on a retrospective cohort of 130 cases. All cases were related to patients with confirmed diagnoses of OLP, oral lichenoid lesions (OLLs), or oral epithelial dysplasia (OED) with lichenoid host response. Results The number of inflammatory cells was statistically significantly higher in OLP compared to OLLs or OED with lichenoid host response (p < 0.0005). The proposed machine‐learning method was reliably capable of detecting OLP cases based on the number of inflammatory cells and the number of mononuclear cells with an area under the curve of 0.982 and 0.988, respectively. Identifying a cut‐off point between OLP and other lichenoid conditions based on the number of mononuclear cells showed a sensitivity of 100% and an accuracy of 94.62%. Conclusion Artificial intelligence has shown promising outcomes and provides a robust approach to enhance the accuracy of anatomical pathologists in accurately diagnosing OLP using features of disease pathogenesis.

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Oral Lichen Planus and the Lichenoid Group of Diseases

Fonseca

Brennan

Gomez

et al. 2019

Head and Neck Cancer Clinics

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Allelic loss in amalgam‐associated oral lichenoid lesions compared to oral lichen planus and mucosa

Abstract: Our study shows that the profile of molecular changes in AAOLL and OLP, evaluated by LOH and Ki-67 expression, is similar. Additional studies including larger samples should be performed to confirm or to refute our findings.

Cited by 4 publications

References 30 publications

Differential metallothionein expression in oral lichen planus and amalgam-associated oral lichenoid lesions

Differential metallothionein expression in oral lichen planus and amalgam-associated oral lichenoid lesions

A machine‐learning algorithm for the reliable identification of oral lichen planus

Oral Lichen Planus and the Lichenoid Group of Diseases

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