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Blood-based lung cancer biomarkers identified through proteomic discovery in cancer tissues, cell lines and conditioned medium.

Birse CE, Lagier RJ, FitzHugh W, Pass HI, Rom WN, Edell ES, Bungum AO, Maldonado F, Jett JR, Mesri M, Sult E, Joseloff E, Li A, Heidbrink J, Dhariwal G, Danis C, Tomic JL, Bruce RJ, Moore PA, He T, Lewis ME, Ruben SM - Clin Proteomics (2015)

Bottom Line: In making their recommendation, the USPSTF noted that the moderate net benefit of screening was dependent on the resolution of most false-positive results without invasive procedures.Several markers selected for further validation showed elevated levels in serum collected from subjects with stage I NSCLC (n = 94), relative to healthy smoker controls (n = 189).Integrating biomarker discovery from multiple sample types (fresh tissue, cell lines and conditioned medium) has resulted in a diverse repertoire of candidate biomarkers.

View Article: PubMed Central - PubMed

Affiliation: Celera employees during the course of these studies, Celera, 1311 Harbor Bay Parkway, Alameda, CA 94502 USA.

ABSTRACT

Background: Support for early detection of lung cancer has emerged from the National Lung Screening Trial (NLST), in which low-dose computed tomography (LDCT) screening reduced lung cancer mortality by 20 % relative to chest x-ray. The US Preventive Services Task Force (USPSTF) recently recommended annual screening for the high-risk population, concluding that the benefits (life years gained) outweighed harms (false positive findings, abortive biopsy/surgery, radiation exposure). In making their recommendation, the USPSTF noted that the moderate net benefit of screening was dependent on the resolution of most false-positive results without invasive procedures. Circulating biomarkers may serve as a valuable adjunctive tool to imaging.

Results: We developed a broad-based proteomics discovery program, integrating liquid chromatography/mass spectrometry (LC/MS) analyses of freshly resected lung tumor specimens (n = 13), lung cancer cell lines (n = 17), and conditioned media collected from tumor cell lines (n = 7). To enrich for biomarkers likely to be found at elevated levels in the peripheral circulation of lung cancer patients, proteins were prioritized based on predicted subcellular localization (secreted, cell-membrane associated) and differential expression in disease samples. 179 candidate biomarkers were identified. Several markers selected for further validation showed elevated levels in serum collected from subjects with stage I NSCLC (n = 94), relative to healthy smoker controls (n = 189). An 8-marker model was developed (TFPI, MDK, OPN, MMP2, TIMP1, CEA, CYFRA 21-1, SCC) which accurately distinguished subjects with lung cancer (n = 50) from high risk smokers (n = 50) in an independent validation study (AUC = 0.775).

Conclusions: Integrating biomarker discovery from multiple sample types (fresh tissue, cell lines and conditioned medium) has resulted in a diverse repertoire of candidate biomarkers. This unique collection of biomarkers may have clinical utility in lung cancer detection and diagnoses.

No MeSH data available.


Related in: MedlinePlus

Multi-marker model resolves lung cancer cases from smoker controls. Receiver Operator Curves are plotted for all controls, nodule controls and no-nodule controls
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Fig2: Multi-marker model resolves lung cancer cases from smoker controls. Receiver Operator Curves are plotted for all controls, nodule controls and no-nodule controls

Mentions: The accuracy of the 8-marker model was tested in an independent study (Mayo Clinic). Controls (n = 50) were selected from the high risk control population evaluated in the Mayo CT-Screening Trial [34] and included subjects with pulmonary nodules (n = 22). Lung cancer cases were pre-operative surgical referrals (n = 50). Malignant lesions were significantly larger than screen detected benign nodules. Cases and controls were matched on age, gender and smoking history (Table 2). EDTA plasma samples were utilized in this study. Levels of all markers included in the model had been shown to be highly correlated in serum and EDTA plasma (Additional file 8: Table S4). The 8-marker model distinguished patients with malignant lesions from all smoker controls with an AUC = 0.775 (Fig. 2), accurately classifying control subjects with (AUC = 0.745) or without pulmonary nodules (AUC = 0.799).Fig. 2


Blood-based lung cancer biomarkers identified through proteomic discovery in cancer tissues, cell lines and conditioned medium.

Birse CE, Lagier RJ, FitzHugh W, Pass HI, Rom WN, Edell ES, Bungum AO, Maldonado F, Jett JR, Mesri M, Sult E, Joseloff E, Li A, Heidbrink J, Dhariwal G, Danis C, Tomic JL, Bruce RJ, Moore PA, He T, Lewis ME, Ruben SM - Clin Proteomics (2015)

Multi-marker model resolves lung cancer cases from smoker controls. Receiver Operator Curves are plotted for all controls, nodule controls and no-nodule controls
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4537594&req=5

Fig2: Multi-marker model resolves lung cancer cases from smoker controls. Receiver Operator Curves are plotted for all controls, nodule controls and no-nodule controls
Mentions: The accuracy of the 8-marker model was tested in an independent study (Mayo Clinic). Controls (n = 50) were selected from the high risk control population evaluated in the Mayo CT-Screening Trial [34] and included subjects with pulmonary nodules (n = 22). Lung cancer cases were pre-operative surgical referrals (n = 50). Malignant lesions were significantly larger than screen detected benign nodules. Cases and controls were matched on age, gender and smoking history (Table 2). EDTA plasma samples were utilized in this study. Levels of all markers included in the model had been shown to be highly correlated in serum and EDTA plasma (Additional file 8: Table S4). The 8-marker model distinguished patients with malignant lesions from all smoker controls with an AUC = 0.775 (Fig. 2), accurately classifying control subjects with (AUC = 0.745) or without pulmonary nodules (AUC = 0.799).Fig. 2

Bottom Line: In making their recommendation, the USPSTF noted that the moderate net benefit of screening was dependent on the resolution of most false-positive results without invasive procedures.Several markers selected for further validation showed elevated levels in serum collected from subjects with stage I NSCLC (n = 94), relative to healthy smoker controls (n = 189).Integrating biomarker discovery from multiple sample types (fresh tissue, cell lines and conditioned medium) has resulted in a diverse repertoire of candidate biomarkers.

View Article: PubMed Central - PubMed

Affiliation: Celera employees during the course of these studies, Celera, 1311 Harbor Bay Parkway, Alameda, CA 94502 USA.

ABSTRACT

Background: Support for early detection of lung cancer has emerged from the National Lung Screening Trial (NLST), in which low-dose computed tomography (LDCT) screening reduced lung cancer mortality by 20 % relative to chest x-ray. The US Preventive Services Task Force (USPSTF) recently recommended annual screening for the high-risk population, concluding that the benefits (life years gained) outweighed harms (false positive findings, abortive biopsy/surgery, radiation exposure). In making their recommendation, the USPSTF noted that the moderate net benefit of screening was dependent on the resolution of most false-positive results without invasive procedures. Circulating biomarkers may serve as a valuable adjunctive tool to imaging.

Results: We developed a broad-based proteomics discovery program, integrating liquid chromatography/mass spectrometry (LC/MS) analyses of freshly resected lung tumor specimens (n = 13), lung cancer cell lines (n = 17), and conditioned media collected from tumor cell lines (n = 7). To enrich for biomarkers likely to be found at elevated levels in the peripheral circulation of lung cancer patients, proteins were prioritized based on predicted subcellular localization (secreted, cell-membrane associated) and differential expression in disease samples. 179 candidate biomarkers were identified. Several markers selected for further validation showed elevated levels in serum collected from subjects with stage I NSCLC (n = 94), relative to healthy smoker controls (n = 189). An 8-marker model was developed (TFPI, MDK, OPN, MMP2, TIMP1, CEA, CYFRA 21-1, SCC) which accurately distinguished subjects with lung cancer (n = 50) from high risk smokers (n = 50) in an independent validation study (AUC = 0.775).

Conclusions: Integrating biomarker discovery from multiple sample types (fresh tissue, cell lines and conditioned medium) has resulted in a diverse repertoire of candidate biomarkers. This unique collection of biomarkers may have clinical utility in lung cancer detection and diagnoses.

No MeSH data available.


Related in: MedlinePlus