Literature DB >> 33179547

Nuclear F-actin Cytology in Oral Epithelial Dysplasia and Oral Squamous Cell Carcinoma.

M P McRae1, A R Kerr2, M N Janal3, M H Thornhill4, S W Redding5, N Vigneswaran6, S K Kang7, R Niederman8, N J Christodoulides1, D A Trochesset2, C Murdoch4, I Dapkins9, J Bouquot10, S S Modak1, G W Simmons1, J T McDevitt1.   

Abstract

Oral cavity cancer has a low 5-y survival rate, but outcomes improve when the disease is detected early. Cytology is a less invasive method to assess oral potentially malignant disorders relative to the gold-standard scalpel biopsy and histopathology. In this report, we aimed to determine the utility of cytological signatures, including nuclear F-actin cell phenotypes, for classifying the entire spectrum of oral epithelial dysplasia and oral squamous cell carcinoma. We enrolled subjects with oral potentially malignant disorders, subjects with previously diagnosed malignant lesions, and healthy volunteers without lesions and obtained brush cytology specimens and matched scalpel biopsies from 486 subjects. Histopathological assessment of the scalpel biopsy specimens classified lesions into 6 categories. Brush cytology specimens were analyzed by machine learning classifiers trained to identify relevant cytological features. Multimodal diagnostic models were developed using cytology results, lesion characteristics, and risk factors. Squamous cells with nuclear F-actin staining were associated with early disease (i.e., lower proportions in benign lesions than in more severe lesions), whereas small round parabasal-like cells and leukocytes were associated with late disease (i.e., higher proportions in severe dysplasia and carcinoma than in less severe lesions). Lesions with the impression of oral lichen planus were unlikely to be either dysplastic or malignant. Cytological features substantially improved upon lesion appearance and risk factors in predicting squamous cell carcinoma. Diagnostic models accurately discriminated early and late disease with AUCs (95% CI) of 0.82 (0.77 to 0.87) and 0.93 (0.88 to 0.97), respectively. The cytological features identified here have the potential to improve screening and surveillance of the entire spectrum of oral potentially malignant disorders in multiple care settings.

Entities:  

Keywords:  actins; artificial intelligence; biomarkers; cell biology; point-of-care testing; single-cell analysis

Mesh:

Substances:

Year:  2020        PMID: 33179547      PMCID: PMC8060776          DOI: 10.1177/0022034520973162

Source DB:  PubMed          Journal:  J Dent Res        ISSN: 0022-0345            Impact factor:   6.116


  25 in total

1.  Interobserver agreement in dysplasia grading: toward an enhanced gold standard for clinical pathology trials.

Authors:  Paul M Speight; Timothy J Abram; Pierre N Floriano; Robert James; Julie Vick; Martin H Thornhill; Craig Murdoch; Christine Freeman; Anne M Hegarty; Katy D'Apice; A Ross Kerr; Joan Phelan; Patricia Corby; Ismael Khouly; Nadarajah Vigneswaran; Jerry Bouquot; Nagi M Demian; Y Etan Weinstock; Spencer W Redding; Stephanie Rowan; Chih-Ko Yeh; H Stan McGuff; Frank R Miller; John T McDevitt
Journal:  Oral Surg Oral Med Oral Pathol Oral Radiol       Date:  2015-06-17

Review 2.  Emerging roles of mechanical forces in chromatin regulation.

Authors:  Yekaterina A Miroshnikova; Michele M Nava; Sara A Wickström
Journal:  J Cell Sci       Date:  2017-06-23       Impact factor: 5.285

Review 3.  Adjunctive Diagnostic Techniques for Oral and Oropharyngeal Cancer Discovery.

Authors:  Michaell A Huber
Journal:  Dent Clin North Am       Date:  2017-10-16

4.  Improving detection of precancerous and cancerous oral lesions. Computer-assisted analysis of the oral brush biopsy. U.S. Collaborative OralCDx Study Group.

Authors:  J J Sciubba
Journal:  J Am Dent Assoc       Date:  1999-10       Impact factor: 3.634

Review 5.  The use of light-based (optical) detection systems as adjuncts in the detection of oral cancer and oral potentially malignant disorders: a systematic review.

Authors:  A Rashid; S Warnakulasuriya
Journal:  J Oral Pathol Med       Date:  2014-09-03       Impact factor: 4.253

6.  Efficacy of oral brush cytology in the evaluation of the oral premalignant and malignant lesions.

Authors:  M Babshet; K Nandimath; Sk Pervatikar; Vg Naikmasur
Journal:  J Cytol       Date:  2011-10       Impact factor: 1.000

7.  Comparison of computer-assisted brush biopsy results with follow up scalpel biopsy and histology.

Authors:  John A Svirsky; James C Burns; William M Carpenter; Donald M Cohen; Indraneel Bhattacharyya; John E Fantasia; David A Lederman; Denis P Lynch; James J Sciubba; Susan L Zunt
Journal:  Gen Dent       Date:  2002 Nov-Dec

8.  Oral epithelial dysplasia classification systems: predictive value, utility, weaknesses and scope for improvement.

Authors:  S Warnakulasuriya; J Reibel; J Bouquot; E Dabelsteen
Journal:  J Oral Pathol Med       Date:  2008-03       Impact factor: 4.253

Review 9.  Mediators of Inflammation - A Potential Source of Biomarkers in Oral Squamous Cell Carcinoma.

Authors:  Mircea Tampa; Madalina Irina Mitran; Cristina Iulia Mitran; Maria Isabela Sarbu; Clara Matei; Ilinca Nicolae; Ana Caruntu; Sandra Milena Tocut; Mircea Ioan Popa; Constantin Caruntu; Simona Roxana Georgescu
Journal:  J Immunol Res       Date:  2018-11-12       Impact factor: 4.818

10.  Risk Stratification of Oral Potentially Malignant Disorders in Fanconi Anemia Patients Using Autofluorescence Imaging and Cytology-On-A Chip Assay.

Authors:  Timothy J Abram; Curtis R Pickering; Alexander K Lang; Nancy E Bass; Rameez Raja; Cynthia Meena; Amin M Alousi; Jeffrey N Myers; John T McDevitt; Ann M Gillenwater; Nadarajah Vigneswaran
Journal:  Transl Oncol       Date:  2018-02-24       Impact factor: 4.243

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  1 in total

1.  Smart Diagnostics: Combining Artificial Intelligence and In Vitro Diagnostics.

Authors:  Michael P McRae; Kritika S Rajsri; Timothy M Alcorn; John T McDevitt
Journal:  Sensors (Basel)       Date:  2022-08-24       Impact factor: 3.847

  1 in total

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