Automated sputum cytometry for detection of intraepithelial neoplasias in the lung

Gerald Li, Martial Guillaud, Jean LeRiche, Annette McWilliams, Adi Gazdar, Stephen Lam, Calum MacAulay

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

BACKGROUND: Despite the benefits of early lung cancer detection, no effective strategy for early screening and treatment exists, partly due to a lack of effective surrogate biomarkers. Our novel sputum biomarker, the Combined Score (CS), uses automated image cytometric analysis of ploidy and nuclear morphology to detect subtle intraepithelial changes that often precede lung tumours.

METHODS: 2249 sputum samples from 1795 high-risk patients enrolled in ongoing chemoprevention trials were subjected to automated quantitative image cytometry after Feulgen-thionin staining. Samples from normal histopathology patients were compared against samples from carcinoma in situ (CIS) and cancer patients to train the CS.

RESULTS: CS correlates with several lung cancer risk factors, including histopathological grade, age, smoking status, and p53 and Ki67 immunostaining. At 50% specificity, CS detected 78% of all highest-risk subjects-those with CIS or worse plus those with moderate or severe dysplasia and abnormal nuclear morphology.

CONCLUSION: CS is a powerful yet minimally invasive tool for rapid and inexpensive risk assessment for the presence of precancerous lung lesions, enabling enrichment of chemoprevention trials with highest-risk dysplasias. CS correlates with other biomarkers, so CS may find use as a surrogate biomarker for patient assessment and as an endpoint in chemoprevention clinical trials.

Original languageEnglish
Pages (from-to)187-201
Number of pages15
JournalAnalytical Cellular Pathology
Volume35
Issue number3
DOIs
Publication statusPublished - 2012
Externally publishedYes

Fingerprint

Sputum
Chemoprevention
Biomarkers
Lung
Carcinoma in Situ
Lung Neoplasms
Neoplasms
Thionins
Image Cytometry
Ploidies
Early Detection of Cancer
Smoking
Clinical Trials
Staining and Labeling
Therapeutics

Keywords

  • Adult
  • Intraepithelial neoplasia (IEN)
  • lung cancer
  • Automation
  • Bronchi
  • Carcinoma
  • Early Detection of Cancer
  • ploidy analysis
  • intermediate or pre-neoplastic markers and risk factors
  • Image Cytometry
  • Lung Neoplasms
  • malignancy associated changes
  • Middle Aged
  • Respiratory Mucosa
  • Sputum
  • risk assessment
  • biomarkers and intervention studies
  • chemoprevention
  • cancer surveillance and screening
  • quantitative image cytometry
  • chemoprevention clinical trials

Cite this

Li, G., Guillaud, M., LeRiche, J., McWilliams, A., Gazdar, A., Lam, S., & MacAulay, C. (2012). Automated sputum cytometry for detection of intraepithelial neoplasias in the lung. Analytical Cellular Pathology, 35(3), 187-201. https://doi.org/10.3233/ACP-2012-0053
Li, Gerald ; Guillaud, Martial ; LeRiche, Jean ; McWilliams, Annette ; Gazdar, Adi ; Lam, Stephen ; MacAulay, Calum. / Automated sputum cytometry for detection of intraepithelial neoplasias in the lung. In: Analytical Cellular Pathology. 2012 ; Vol. 35, No. 3. pp. 187-201.
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Li, G, Guillaud, M, LeRiche, J, McWilliams, A, Gazdar, A, Lam, S & MacAulay, C 2012, 'Automated sputum cytometry for detection of intraepithelial neoplasias in the lung', Analytical Cellular Pathology, vol. 35, no. 3, pp. 187-201. https://doi.org/10.3233/ACP-2012-0053

Automated sputum cytometry for detection of intraepithelial neoplasias in the lung. / Li, Gerald; Guillaud, Martial; LeRiche, Jean; McWilliams, Annette; Gazdar, Adi; Lam, Stephen; MacAulay, Calum.

In: Analytical Cellular Pathology, Vol. 35, No. 3, 2012, p. 187-201.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Automated sputum cytometry for detection of intraepithelial neoplasias in the lung

AU - Li, Gerald

AU - Guillaud, Martial

AU - LeRiche, Jean

AU - McWilliams, Annette

AU - Gazdar, Adi

AU - Lam, Stephen

AU - MacAulay, Calum

PY - 2012

Y1 - 2012

N2 - BACKGROUND: Despite the benefits of early lung cancer detection, no effective strategy for early screening and treatment exists, partly due to a lack of effective surrogate biomarkers. Our novel sputum biomarker, the Combined Score (CS), uses automated image cytometric analysis of ploidy and nuclear morphology to detect subtle intraepithelial changes that often precede lung tumours.METHODS: 2249 sputum samples from 1795 high-risk patients enrolled in ongoing chemoprevention trials were subjected to automated quantitative image cytometry after Feulgen-thionin staining. Samples from normal histopathology patients were compared against samples from carcinoma in situ (CIS) and cancer patients to train the CS.RESULTS: CS correlates with several lung cancer risk factors, including histopathological grade, age, smoking status, and p53 and Ki67 immunostaining. At 50% specificity, CS detected 78% of all highest-risk subjects-those with CIS or worse plus those with moderate or severe dysplasia and abnormal nuclear morphology.CONCLUSION: CS is a powerful yet minimally invasive tool for rapid and inexpensive risk assessment for the presence of precancerous lung lesions, enabling enrichment of chemoprevention trials with highest-risk dysplasias. CS correlates with other biomarkers, so CS may find use as a surrogate biomarker for patient assessment and as an endpoint in chemoprevention clinical trials.

AB - BACKGROUND: Despite the benefits of early lung cancer detection, no effective strategy for early screening and treatment exists, partly due to a lack of effective surrogate biomarkers. Our novel sputum biomarker, the Combined Score (CS), uses automated image cytometric analysis of ploidy and nuclear morphology to detect subtle intraepithelial changes that often precede lung tumours.METHODS: 2249 sputum samples from 1795 high-risk patients enrolled in ongoing chemoprevention trials were subjected to automated quantitative image cytometry after Feulgen-thionin staining. Samples from normal histopathology patients were compared against samples from carcinoma in situ (CIS) and cancer patients to train the CS.RESULTS: CS correlates with several lung cancer risk factors, including histopathological grade, age, smoking status, and p53 and Ki67 immunostaining. At 50% specificity, CS detected 78% of all highest-risk subjects-those with CIS or worse plus those with moderate or severe dysplasia and abnormal nuclear morphology.CONCLUSION: CS is a powerful yet minimally invasive tool for rapid and inexpensive risk assessment for the presence of precancerous lung lesions, enabling enrichment of chemoprevention trials with highest-risk dysplasias. CS correlates with other biomarkers, so CS may find use as a surrogate biomarker for patient assessment and as an endpoint in chemoprevention clinical trials.

KW - Adult

KW - Intraepithelial neoplasia (IEN)

KW - lung cancer

KW - Automation

KW - Bronchi

KW - Carcinoma

KW - Early Detection of Cancer

KW - ploidy analysis

KW - intermediate or pre-neoplastic markers and risk factors

KW - Image Cytometry

KW - Lung Neoplasms

KW - malignancy associated changes

KW - Middle Aged

KW - Respiratory Mucosa

KW - Sputum

KW - risk assessment

KW - biomarkers and intervention studies

KW - chemoprevention

KW - cancer surveillance and screening

KW - quantitative image cytometry

KW - chemoprevention clinical trials

U2 - 10.3233/ACP-2012-0053

DO - 10.3233/ACP-2012-0053

M3 - Article

C2 - 22277916

VL - 35

SP - 187

EP - 201

JO - Analytical Cellular Pathology

JF - Analytical Cellular Pathology

SN - 2210-7185

IS - 3

ER -