Literature DB >> 15614828

Nuclear morphometry as a biomarker for bronchial intraepithelial neoplasia: correlation with genetic damage and cancer development.

Martial Guillaud1, Jean C le Riche, Chris Dawe, Jagoda Korbelik, Andy Coldman, Ignacio I Wistuba, In-Won Park, Adi Gazdar, Stephen Lam, Calum E MacAulay.   

Abstract

BACKGROUND: Bronchial carcinomas are preceded by epithelial morphologic changes. The variation in interpretation of these grades of intraepithelial neoplasia makes it difficult to determine its natural history and utility of histopathology as a surrogate endpoint biomarker. The objective of this study was to quantitate morphologic changes of intraepitherlial neoplasia and validate its utility through correlation with histopathology, allelic loss, and cancer development.
METHODS: Quantitative nuclear morphometry was performed on 47 normal bronchial biopsies and 28 invasive cancer to generate a morphometry index (MI) that was applied to 1,096 bronchial biopsies from 230 volunteers who were current smokers (> or =25 pack-years) and 30 patients who had cancer. In a subset of 631 biopsies, MI was correlated with frequency of loss of heterozygosity at nine chromosomal regions (14 polymorphic markers).
RESULTS: A significant correlation was found between MI and allelic loss in six of nine chromosomal regions. As part of patient long-term follow-up, 12 sites that progressed to cancer were identified and had significantly increased MIs relative to nonprogressing sites. Significant overlap in the MIs was found between most grades of intraepithelial neoplasia.
CONCLUSIONS: In chemoprevention trials, nuclear morphometry can supplement histopathology as a Surrogate Endpont Biomarker (SEB) because it is quantitative, collelates well with genetic damage, and may predict cancer development.

Entities:  

Mesh:

Year:  2005        PMID: 15614828     DOI: 10.1002/cyto.a.20101

Source DB:  PubMed          Journal:  Cytometry A        ISSN: 1552-4922            Impact factor:   4.355


  8 in total

1.  Automated classification of oral premalignant lesions using image cytometry and Random Forests-based algorithms.

Authors:  Jonathan Baik; Qian Ye; Lewei Zhang; Catherine Poh; Miriam Rosin; Calum MacAulay; Martial Guillaud
Journal:  Cell Oncol (Dordr)       Date:  2014-05-10       Impact factor: 6.730

Review 2.  Natural history of bronchial preinvasive lesions.

Authors:  Taichiro Ishizumi; Annette McWilliams; Calum MacAulay; Adi Gazdar; Stephen Lam
Journal:  Cancer Metastasis Rev       Date:  2010-03       Impact factor: 9.264

3.  Large-scale DNA organization is a prognostic marker of breast cancer survival.

Authors:  Martial Guillaud; Qian Ye; Sam Leung; Anita Carraro; Alan Harrison; Malcolm Hayes; Alan Nichol; Mira Keyes
Journal:  Med Oncol       Date:  2017-12-06       Impact factor: 3.064

4.  Potential use of quantitative tissue phenotype to predict malignant risk for oral premalignant lesions.

Authors:  Martial Guillaud; Lewei Zhang; Catherine Poh; Miriam P Rosin; Calum MacAulay
Journal:  Cancer Res       Date:  2008-05-01       Impact factor: 12.701

5.  In vivo optical coherence tomography imaging of preinvasive bronchial lesions.

Authors:  Stephen Lam; Beau Standish; Corisande Baldwin; Annette McWilliams; Jean leRiche; Adi Gazdar; Alex I Vitkin; Victor Yang; Norihiko Ikeda; Calum MacAulay
Journal:  Clin Cancer Res       Date:  2008-04-01       Impact factor: 12.531

6.  Epigenetically induced changes in nuclear textural patterns and gelatinase expression in human fibrosarcoma cells.

Authors:  M Poplineau; C Doliwa; M Schnekenburger; F Antonicelli; M Diederich; A Trussardi-Régnier; J Dufer
Journal:  Cell Prolif       Date:  2013-04       Impact factor: 6.831

7.  Diagnosis of lung cancer in individuals with solitary pulmonary nodules by plasma microRNA biomarkers.

Authors:  Jun Shen; Ziling Liu; Nevins W Todd; Howard Zhang; Jipei Liao; Lei Yu; Maria A Guarnera; Ruiyun Li; Ling Cai; Min Zhan; Feng Jiang
Journal:  BMC Cancer       Date:  2011-08-24       Impact factor: 4.430

8.  Quantitative nuclear phenotype signatures predict nodal disease in oral squamous cell carcinoma.

Authors:  Kelly Yi Ping Liu; Sarah Yuqi Zhu; Alan Harrison; Zhao Yang Chen; Martial Guillaud; Catherine F Poh
Journal:  PLoS One       Date:  2021-11-04       Impact factor: 3.240

  8 in total

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