Literature DB >> 27531880

'Cytology-on-a-chip' based sensors for monitoring of potentially malignant oral lesions.

Timothy J Abram1, Pierre N Floriano2, Nicolaos Christodoulides1, Robert James3, A Ross Kerr4, Martin H Thornhill5, Spencer W Redding6, Nadarajah Vigneswaran7, Paul M Speight8, Julie Vick3, Craig Murdoch5, Christine Freeman5, Anne M Hegarty9, Katy D'Apice9, Joan A Phelan4, Patricia M Corby10, Ismael Khouly11, Jerry Bouquot7, Nagi M Demian12, Y Etan Weinstock13, Stephanie Rowan6, Chih-Ko Yeh14, H Stan McGuff15, Frank R Miller16, Surabhi Gaur1, Kailash Karthikeyan1, Leander Taylor1, Cathy Le1, Michael Nguyen1, Humberto Talavera1, Rameez Raja1, Jorge Wong1, John T McDevitt17.   

Abstract

UNLABELLED: Despite significant advances in surgical procedures and treatment, long-term prognosis for patients with oral cancer remains poor, with survival rates among the lowest of major cancers. Better methods are desperately needed to identify potential malignancies early when treatments are more effective.
OBJECTIVE: To develop robust classification models from cytology-on-a-chip measurements that mirror diagnostic performance of gold standard approach involving tissue biopsy.
MATERIALS AND METHODS: Measurements were recorded from 714 prospectively recruited patients with suspicious lesions across 6 diagnostic categories (each confirmed by tissue biopsy -histopathology) using a powerful new 'cytology-on-a-chip' approach capable of executing high content analysis at a single cell level. Over 200 cellular features related to biomarker expression, nuclear parameters and cellular morphology were recorded per cell. By cataloging an average of 2000 cells per patient, these efforts resulted in nearly 13 million indexed objects.
RESULTS: Binary "low-risk"/"high-risk" models yielded AUC values of 0.88 and 0.84 for training and validation models, respectively, with an accompanying difference in sensitivity+specificity of 6.2%. In terms of accuracy, this model accurately predicted the correct diagnosis approximately 70% of the time, compared to the 69% initial agreement rate of the pool of expert pathologists. Key parameters identified in these models included cell circularity, Ki67 and EGFR expression, nuclear-cytoplasmic ratio, nuclear area, and cell area.
CONCLUSIONS: This chip-based approach yields objective data that can be leveraged for diagnosis and management of patients with PMOL as well as uncovering new molecular-level insights behind cytological differences across the OED spectrum.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Cytology; High content analysis; LASSO; Machine learning; Microfluidic; Oral cancer; Oral epithelial dysplasia; Random forest

Mesh:

Year:  2016        PMID: 27531880      PMCID: PMC5056560          DOI: 10.1016/j.oraloncology.2016.07.002

Source DB:  PubMed          Journal:  Oral Oncol        ISSN: 1368-8375            Impact factor:   5.337


  34 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

2.  Continuous-flow cytomorphological staining and analysis.

Authors:  Andrew P Tan; Jaideep S Dudani; Armin Arshi; Robert J Lee; Henry T K Tse; Daniel R Gossett; Dino Di Carlo
Journal:  Lab Chip       Date:  2014-02-07       Impact factor: 6.799

3.  An empirical assessment of validation practices for molecular classifiers.

Authors:  Peter J Castaldi; Issa J Dahabreh; John P A Ioannidis
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4.  Dysplasia classification: pathology in disgrace?

Authors:  F T Bosman
Journal:  J Pathol       Date:  2001-06       Impact factor: 7.996

5.  Nano-bio-chip sensor platform for examination of oral exfoliative cytology.

Authors:  Shannon E Weigum; Pierre N Floriano; Spencer W Redding; Chih-Ko Yeh; Stephen D Westbrook; H Stan McGuff; Alan Lin; Frank R Miller; Fred Villarreal; Stephanie D Rowan; Nadarajah Vigneswaran; Michelle D Williams; John T McDevitt
Journal:  Cancer Prev Res (Phila)       Date:  2010-03-23

Review 6.  Diagnostic tests for oral cancer and potentially malignant disorders in patients presenting with clinically evident lesions.

Authors:  Richard Macey; Tanya Walsh; Paul Brocklehurst; Alexander R Kerr; Joseph L Y Liu; Mark W Lingen; Graham R Ogden; Saman Warnakulasuriya; Crispian Scully
Journal:  Cochrane Database Syst Rev       Date:  2015-05-29

7.  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

Review 8.  Natural history of potentially malignant oral lesions and conditions: an overview of the literature.

Authors:  Séamus S Napier; Paul M Speight
Journal:  J Oral Pathol Med       Date:  2008-01       Impact factor: 4.253

Review 9.  Increasing the Content of High-Content Screening: An Overview.

Authors:  Shantanu Singh; Anne E Carpenter; Auguste Genovesio
Journal:  J Biomol Screen       Date:  2014-04-07

10.  CellProfiler: image analysis software for identifying and quantifying cell phenotypes.

Authors:  Anne E Carpenter; Thouis R Jones; Michael R Lamprecht; Colin Clarke; In Han Kang; Ola Friman; David A Guertin; Joo Han Chang; Robert A Lindquist; Jason Moffat; Polina Golland; David M Sabatini
Journal:  Genome Biol       Date:  2006-10-31       Impact factor: 13.583

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Authors:  Michael P McRae; Glennon W Simmons; Nicolaos J Christodoulides; Zhibing Lu; Stella K Kang; David Fenyo; Timothy Alcorn; Isaac P Dapkins; Iman Sharif; Deniz Vurmaz; Sayli S Modak; Kritika Srinivasan; Shruti Warhadpande; Ravi Shrivastav; John T McDevitt
Journal:  Lab Chip       Date:  2020-06-03       Impact factor: 6.799

2.  Biomarkers of chronic inflammation in disease development and prevention: challenges and opportunities.

Authors:  Christina H Liu; Natalie D Abrams; Danielle M Carrick; Preethi Chander; Johanna Dwyer; Michelle R J Hamlet; Francesca Macchiarini; Mercy PrabhuDas; Grace L Shen; Pushpa Tandon; Merriline M Vedamony
Journal:  Nat Immunol       Date:  2017-10-18       Impact factor: 25.606

3.  Podoplanin Expression Independently and Jointly with Oral Epithelial Dysplasia Grade Acts as a Potential Biomarker of Malignant Transformation in Oral Leukoplakia.

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Journal:  Biomolecules       Date:  2022-04-19

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

Authors:  M P McRae; A R Kerr; M N Janal; M H Thornhill; S W Redding; N Vigneswaran; S K Kang; R Niederman; N J Christodoulides; D A Trochesset; C Murdoch; I Dapkins; J Bouquot; S S Modak; G W Simmons; J T McDevitt
Journal:  J Dent Res       Date:  2020-11-12       Impact factor: 6.116

Review 5.  Innovative Programmable Bio-Nano-Chip Digitizes Biology Using Sensors That Learn Bridging Biomarker Discovery and Clinical Implementation.

Authors:  Nicolaos J Christodoulides; Michael P McRae; Timothy J Abram; Glennon W Simmons; John T McDevitt
Journal:  Front Public Health       Date:  2017-05-22

6.  Point-of-care oral cytology tool for the screening and assessment of potentially malignant oral lesions.

Authors:  Michael P McRae; Sayli S Modak; Glennon W Simmons; Denise A Trochesset; A Ross Kerr; Martin H Thornhill; Spencer W Redding; Nadarajah Vigneswaran; Stella K Kang; Nicolaos J Christodoulides; Craig Murdoch; Steven J Dietl; Roger Markham; John T McDevitt
Journal:  Cancer Cytopathol       Date:  2020-02-07       Impact factor: 5.284

7.  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

8.  Diagnostic tests for oral cancer and potentially malignant disorders in patients presenting with clinically evident lesions.

Authors:  Tanya Walsh; Richard Macey; Alexander R Kerr; Mark W Lingen; Graham R Ogden; Saman Warnakulasuriya
Journal:  Cochrane Database Syst Rev       Date:  2021-07-20

9.  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

10.  Clinical Decision Support Tool and Rapid Point-of-Care Platform for Determining Disease Severity in Patients with COVID-19.

Authors:  Michael P McRae; Glennon W Simmons; Nicolaos J Christodoulides; Zhibing Lu; Stella K Kang; David Fenyo; Timothy Alcorn; Isaac P Dapkins; Iman Sharif; Deniz Vurmaz; Sayli S Modak; Kritika Srinivasan; Shruti Warhadpande; Ravi Shrivastav; John T McDevitt
Journal:  medRxiv       Date:  2020-04-22
  10 in total

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