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Systemic disease-induced salivary biomarker profiles in mouse models of melanoma and non-small cell lung cancer.

Gao K, Zhou H, Zhang L, Lee JW, Zhou Q, Hu S, Wolinsky LE, Farrell J, Eibl G, Wong DT - PLoS ONE (2009)

Bottom Line: Saliva (oral fluids) is an emerging biofluid poised for detection of clinical diseases.Taken together, our data support the conclusion that upon systemic disease development, significant changes can occur in the salivary biomarker profile.Although the origins of the disease-induced salivary biomarkers may be both systemic and local, stimulation of salivary gland by mediators released from remote tumors plays an important role in regulating the salivary surrogate biomarker profiles.

View Article: PubMed Central - PubMed

Affiliation: School of Dentistry & Dental Research Institute, University of California Los Angeles, Los Angeles, CA, USA.

ABSTRACT

Background: Saliva (oral fluids) is an emerging biofluid poised for detection of clinical diseases. Although the rationale for oral diseases applications (e.g. oral cancer) is intuitive, the rationale and relationship between systemic diseases and saliva biomarkers are unclear.

Methodology/principal findings: In this study, we used mouse models of melanoma and non-small cell lung cancer and compared the transcriptome biomarker profiles of tumor-bearing mice to those of control mice. Microarray analysis showed that salivary transcriptomes were significantly altered in tumor-bearing mice vs. controls. Significant overlapping among transcriptomes of mouse tumors, serum, salivary glands and saliva suggests that salivary biomarkers have multiple origins. Furthermore, we identified that the expression of two groups of significantly altered transcription factors (TFs) Runx1, Mlxipl, Trim30 and Egr1, Tbx1, Nr1d1 in salivary gland tissue of melanoma-bearing mice can potentially be responsible for 82.6% of the up-regulated gene expression and 62.5% of the down-regulated gene expression, respectively, in the saliva of melanoma-bearing mice. We also showed that the ectopic production of nerve growth factor (NGF) in the melanoma tumor tissue as a tumor-released mediator can induce expression of the TF Egr-1 in the salivary gland.

Conclusions: Taken together, our data support the conclusion that upon systemic disease development, significant changes can occur in the salivary biomarker profile. Although the origins of the disease-induced salivary biomarkers may be both systemic and local, stimulation of salivary gland by mediators released from remote tumors plays an important role in regulating the salivary surrogate biomarker profiles.

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Expression profilings of saliva in the melanoma and lung cancer mouse models.A, Cluster analysis of 152 up-regulated known genes (representing 225 probsets, the left panel) and 359 down-regulated known genes (representing 403 probsets, the right panel) differentially expressed in saliva of melanoma mice vs. control mice (P-value<0.05; fold change ≥2). The expression profiles were standardized to have zero mean and unit standard deviation. Red and green represent high and low expression levels after standardization, respectively. B, Cluster analysis of 290 up-regulated and 784 down-regulated probesets differentially expressed in saliva of lung carcinoma mice vs. control mice (P-value<0.05; fold change ≥2). C and D, Overlapping of differentiated gene expression between the melanoma model and lung cancer model. C, overlapping of 225 up-regulated genes in the melanoma model and 290 up-regulated genes in the lung cancer model. D, overlapping of 403 down-regulated genes in the melanoma model and 784 down-regulated genes in the lung cancer model.
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pone-0005875-g002: Expression profilings of saliva in the melanoma and lung cancer mouse models.A, Cluster analysis of 152 up-regulated known genes (representing 225 probsets, the left panel) and 359 down-regulated known genes (representing 403 probsets, the right panel) differentially expressed in saliva of melanoma mice vs. control mice (P-value<0.05; fold change ≥2). The expression profiles were standardized to have zero mean and unit standard deviation. Red and green represent high and low expression levels after standardization, respectively. B, Cluster analysis of 290 up-regulated and 784 down-regulated probesets differentially expressed in saliva of lung carcinoma mice vs. control mice (P-value<0.05; fold change ≥2). C and D, Overlapping of differentiated gene expression between the melanoma model and lung cancer model. C, overlapping of 225 up-regulated genes in the melanoma model and 290 up-regulated genes in the lung cancer model. D, overlapping of 403 down-regulated genes in the melanoma model and 784 down-regulated genes in the lung cancer model.

Mentions: To assess whether the salivary transcriptome biomarker profile changes upon development of a remote tumor, we performed microarray analysis to compare the transcriptome biomarker profiles in saliva of control mice (three groups, 5 mice in each group) with tumor-bearing (melanoma or lung) mice (three groups, 5 mice in each group) (Fig. 1). It is necessary to have five mice in each tumor or control group in order to pool sufficient saliva for RNA isolation. Biomarker selection criteria were set as fold change>2 and P<0.05. We identified 152 significantly up-regulated known genes and 359 significantly down-regulated known genes (Fig. 2A, Table S3 and S4) in the saliva of melanoma-bearing mice compared to control mice. Similarly, we found 290 significantly up-regulated transcripts and 784 significantly down-regulated transcripts (Fig. 2B,.Table S5 and S6) in the saliva of lung cancer-bearing mice compared to control mice.


Systemic disease-induced salivary biomarker profiles in mouse models of melanoma and non-small cell lung cancer.

Gao K, Zhou H, Zhang L, Lee JW, Zhou Q, Hu S, Wolinsky LE, Farrell J, Eibl G, Wong DT - PLoS ONE (2009)

Expression profilings of saliva in the melanoma and lung cancer mouse models.A, Cluster analysis of 152 up-regulated known genes (representing 225 probsets, the left panel) and 359 down-regulated known genes (representing 403 probsets, the right panel) differentially expressed in saliva of melanoma mice vs. control mice (P-value<0.05; fold change ≥2). The expression profiles were standardized to have zero mean and unit standard deviation. Red and green represent high and low expression levels after standardization, respectively. B, Cluster analysis of 290 up-regulated and 784 down-regulated probesets differentially expressed in saliva of lung carcinoma mice vs. control mice (P-value<0.05; fold change ≥2). C and D, Overlapping of differentiated gene expression between the melanoma model and lung cancer model. C, overlapping of 225 up-regulated genes in the melanoma model and 290 up-regulated genes in the lung cancer model. D, overlapping of 403 down-regulated genes in the melanoma model and 784 down-regulated genes in the lung cancer model.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2691577&req=5

pone-0005875-g002: Expression profilings of saliva in the melanoma and lung cancer mouse models.A, Cluster analysis of 152 up-regulated known genes (representing 225 probsets, the left panel) and 359 down-regulated known genes (representing 403 probsets, the right panel) differentially expressed in saliva of melanoma mice vs. control mice (P-value<0.05; fold change ≥2). The expression profiles were standardized to have zero mean and unit standard deviation. Red and green represent high and low expression levels after standardization, respectively. B, Cluster analysis of 290 up-regulated and 784 down-regulated probesets differentially expressed in saliva of lung carcinoma mice vs. control mice (P-value<0.05; fold change ≥2). C and D, Overlapping of differentiated gene expression between the melanoma model and lung cancer model. C, overlapping of 225 up-regulated genes in the melanoma model and 290 up-regulated genes in the lung cancer model. D, overlapping of 403 down-regulated genes in the melanoma model and 784 down-regulated genes in the lung cancer model.
Mentions: To assess whether the salivary transcriptome biomarker profile changes upon development of a remote tumor, we performed microarray analysis to compare the transcriptome biomarker profiles in saliva of control mice (three groups, 5 mice in each group) with tumor-bearing (melanoma or lung) mice (three groups, 5 mice in each group) (Fig. 1). It is necessary to have five mice in each tumor or control group in order to pool sufficient saliva for RNA isolation. Biomarker selection criteria were set as fold change>2 and P<0.05. We identified 152 significantly up-regulated known genes and 359 significantly down-regulated known genes (Fig. 2A, Table S3 and S4) in the saliva of melanoma-bearing mice compared to control mice. Similarly, we found 290 significantly up-regulated transcripts and 784 significantly down-regulated transcripts (Fig. 2B,.Table S5 and S6) in the saliva of lung cancer-bearing mice compared to control mice.

Bottom Line: Saliva (oral fluids) is an emerging biofluid poised for detection of clinical diseases.Taken together, our data support the conclusion that upon systemic disease development, significant changes can occur in the salivary biomarker profile.Although the origins of the disease-induced salivary biomarkers may be both systemic and local, stimulation of salivary gland by mediators released from remote tumors plays an important role in regulating the salivary surrogate biomarker profiles.

View Article: PubMed Central - PubMed

Affiliation: School of Dentistry & Dental Research Institute, University of California Los Angeles, Los Angeles, CA, USA.

ABSTRACT

Background: Saliva (oral fluids) is an emerging biofluid poised for detection of clinical diseases. Although the rationale for oral diseases applications (e.g. oral cancer) is intuitive, the rationale and relationship between systemic diseases and saliva biomarkers are unclear.

Methodology/principal findings: In this study, we used mouse models of melanoma and non-small cell lung cancer and compared the transcriptome biomarker profiles of tumor-bearing mice to those of control mice. Microarray analysis showed that salivary transcriptomes were significantly altered in tumor-bearing mice vs. controls. Significant overlapping among transcriptomes of mouse tumors, serum, salivary glands and saliva suggests that salivary biomarkers have multiple origins. Furthermore, we identified that the expression of two groups of significantly altered transcription factors (TFs) Runx1, Mlxipl, Trim30 and Egr1, Tbx1, Nr1d1 in salivary gland tissue of melanoma-bearing mice can potentially be responsible for 82.6% of the up-regulated gene expression and 62.5% of the down-regulated gene expression, respectively, in the saliva of melanoma-bearing mice. We also showed that the ectopic production of nerve growth factor (NGF) in the melanoma tumor tissue as a tumor-released mediator can induce expression of the TF Egr-1 in the salivary gland.

Conclusions: Taken together, our data support the conclusion that upon systemic disease development, significant changes can occur in the salivary biomarker profile. Although the origins of the disease-induced salivary biomarkers may be both systemic and local, stimulation of salivary gland by mediators released from remote tumors plays an important role in regulating the salivary surrogate biomarker profiles.

Show MeSH
Related in: MedlinePlus