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Lei Zhang,
Hua Xiao,
Hui Zhou,
Silverio Santiago,
Jay M Lee,
Edward B Garon,
Jieping Yang,
Ole Brinkmann,
Xinmin Yan, David Akin,
David Chia,
David Elashoff,
No-Hee Park,
David T W Wong
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ABSTRACT: Lung cancer is the leading cause of cancer death for both men and women worldwide. Since most of the symptoms found for lung cancer are nonspecific, diagnosis is mostly done at late and progressed stage with the consecutive poor therapy outcome. Effective early detection techniques are sorely needed. The emerging field of salivary diagnostics could provide scientifically credible, easy-to-use, non-invasive and cost-effective detection methods. Recent advances have allowed us to develop discriminatory salivary biomarkers for a variety of diseases from oral to systematic diseases. In this study, salivary transcriptomes of lung cancer patients were profiled and led to the discovery and pre-validation of seven highly discriminatory transcriptomic salivary biomarkers (BRAF, CCNI, EGRF, FGF19, FRS2, GREB1, and LZTS1). The logistic regression model combining five of the mRNA biomarkers (CCNI, EGFR, FGF19, FRS2, and GREB1) could differentiate lung cancer patients from normal control subjects, yielding AUC value of 0.925 with 93.75 % sensitivity and 82.81 % specificity in the pre-validation sample set. These salivary mRNA biomarkers possess the discriminatory power for the detection of lung cancer. This report provides the proof of concept of salivary biomarkers for the non-invasive detection of the systematic disease. These results poised the salivary biomarkers for the initiation of a multi-center validation in a definitive clinical context.
Cellular and Molecular Life Sciences CMLS 06/2012; 69(19):3341-50. · 6.57 Impact Factor
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ABSTRACT: The associations between oral diseases and increased risk of pancreatic cancer have been reported in several prospective cohort studies. In this study, we measured variations of salivary microbiota and evaluated their potential associations with pancreatic cancer and chronic pancreatitis.
This study was divided into three phases: (1) microbial profiling using the Human Oral Microbe Identification Microarray to investigate salivary microbiota variation between 10 resectable patients with pancreatic cancer and 10 matched healthy controls, (2) identification and verification of bacterial candidates by real-time quantitative PCR (qPCR) and (3) validation of bacterial candidates by qPCR on an independent cohort of 28 resectable pancreatic cancer, 28 matched healthy control and 27 chronic pancreatitis samples.
Comprehensive comparison of the salivary microbiota between patients with pancreatic cancer and healthy control subjects revealed a significant variation of salivary microflora. Thirty-one bacterial species/clusters were increased in the saliva of patients with pancreatic cancer (n=10) in comparison to those of the healthy controls (n=10), whereas 25 bacterial species/clusters were decreased. Two out of six bacterial candidates (Neisseria elongata and Streptococcus mitis) were validated using the independent samples, showing significant variation (p<0.05, qPCR) between patients with pancreatic cancer and controls (n=56). Additionally, two bacteria (Granulicatella adiacens and S mitis) showed significant variation (p<0.05, qPCR) between chronic pancreatitis samples and controls (n=55). The combination of two bacterial biomarkers (N elongata and S mitis) yielded a receiver operating characteristic plot area under the curve value of 0.90 (95% CI 0.78 to 0.96, p<0.0001) with a 96.4% sensitivity and 82.1% specificity in distinguishing patients with pancreatic cancer from healthy subjects.
The authors observed associations between variations of patients' salivary microbiota with pancreatic cancer and chronic pancreatitis. This report also provides proof of salivary microbiota as an informative source for discovering non-invasive biomarkers of systemic diseases.
Gut 04/2012; 61(4):582-8. · 10.11 Impact Factor
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David Elashoff,
Hui Zhou,
Jean Reiss,
Jianghua Wang,
Hua Xiao,
Bradley Henson,
Shen Hu,
Martha Arellano,
Uttam Sinha,
Anh Le, [......],
Vishad Nabili,
Mark Lingen,
Darly Morris,
Timothy Randolph,
Ziding Feng, David Akin,
Dragana A Kastratovic,
David Chia,
Elliot Abemayor,
David T W Wong
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ABSTRACT: Oral cancer is the sixth most common cancer with a 5-year survival rate of approximately 60%. Presently, there are no scientifically credible early detection techniques beyond conventional clinical oral examination. The goal of this study is to validate whether the seven mRNAs and three proteins previously reported as biomarkers are capable of discriminating patients with oral squamous cell carcinomas (OSCC) from healthy subjects in independent cohorts and by a National Cancer Institute (NCI)-Early Detection Research Network (EDRN)-Biomarker Reference Laboratory (BRL).
Three hundred and ninety-five subjects from five independent cohorts based on case controlled design were investigated by two independent laboratories, University of California, Los Angeles (Los Angeles, CA) discovery laboratory and NCI-EDRN-BRL.
Expression of all seven mRNA and three protein markers was increased in OSCC versus controls in all five cohorts. With respect to individual marker performance across the five cohorts, the increase in interleukin (IL)-8 and subcutaneous adipose tissue (SAT) was statistically significant and they remained top performers across different cohorts in terms of sensitivity and specificity. A previously identified multiple marker model showed an area under the receiver operating characteristic (ROC) curve for prediction of OSCC status ranging from 0.74 to 0.86 across the cohorts.
The validation of these biomarkers showed their feasibility in the discrimination of OSCCs from healthy controls. Established assay technologies are robust enough to perform independently. Individual cutoff values for each of these markers and for the combined predictive model need to be further defined in large clinical studies.
Salivary proteomic and transcriptomic biomarkers can discriminate oral cancer from control subjects.
Cancer Epidemiology Biomarkers & Prevention 03/2012; 21(4):664-72. · 4.12 Impact Factor
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Ole Brinkmann,
Dragana A Kastratovic,
Milovan V Dimitrijevic,
Vitomir S Konstantinovic,
Drago B Jelovac,
Jadranka Antic,
Vladimir S Nesic,
Srdjan Z Markovic,
Zeljko R Martinovic, David Akin,
Nadine Spielmann,
Hui Zhou,
David T Wong
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ABSTRACT: Early detection of oral squamous cell cancer (OSCC) is the key to improve the low 5-year survival rate. Using proteomic and genomic technologies we have previously discovered and validated salivary OSCC markers in American patients. The question arises whether these biomarkers are discriminatory in cohorts of different ethnic background. Six transcriptome (DUSP1, IL8, IL1B, OAZ1, SAT1, and S100P) and three proteome (IL1B, IL8, and M2BP) biomarkers were tested on 18 early and 17 late stage OSCC patients and 51 healthy controls with quantitative PCR and ELISA. Four transcriptome (IL8, IL1B, SAT1, and S100P) and all proteome biomarkers were significantly elevated (p<0.05) in OSCC patients. The combination of markers yielded an AUC of 0.86, 0.85 and 0.88 for OSCC total, T1-T2, and T3-T4, respectively. The sensitivity/specificity for OSCC total was 0.89/0.78, for T1-T2 0.67/0.96, and for T3-T4 0.82/0.84. In conclusion, seven of the nine salivary biomarkers (three proteins and four mRNAs) were validated and performed strongest in late stage cancer. Patient-based salivary diagnostics is a highly promising approach for OSCC detection. This study shows that previously discovered and validated salivary OSCC biomarkers are discriminatory and reproducible in a different ethnic cohort. These findings support the feasibility to implement multi-center, multi-ethnicity clinical trials towards the pivotal validation of salivary biomarkers for OSCC detection.
Oral Oncology 01/2011; 47(1):51-5. · 2.86 Impact Factor
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Lei Zhang,
Hua Xiao,
Scott Karlan,
Hui Zhou,
Jenny Gross,
David Elashoff, David Akin,
Xinmin Yan,
David Chia,
Beth Karlan,
David T Wong
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ABSTRACT: A sensitive assay to identify biomarkers using non-invasively collected clinical specimens is ideal for breast cancer detection. While there are other studies showing disease biomarkers in saliva for breast cancer, our study tests the hypothesis that there are breast cancer discriminatory biomarkers in saliva using de novo discovery and validation approaches. This is the first study of this kind and no other study has engaged a de novo biomarker discovery approach in saliva for breast cancer detection. In this study, a case-control discovery and independent preclinical validations were conducted to evaluate the performance and translational utilities of salivary transcriptomic and proteomic biomarkers for breast cancer detection.
Salivary transcriptomes and proteomes of 10 breast cancer patients and 10 matched controls were profiled using Affymetrix HG-U133-Plus-2.0 Array and two-dimensional difference gel electrophoresis (2D-DIGE), respectively. Preclinical validations were performed to evaluate the discovered biomarkers in an independent sample cohort of 30 breast cancer patients and 63 controls using RT-qPCR (transcriptomic biomarkers) and quantitative protein immunoblot (proteomic biomarkers). Transcriptomic and proteomic profiling revealed significant variations in salivary molecular biomarkers between breast cancer patients and matched controls. Eight mRNA biomarkers and one protein biomarker, which were not affected by the confounding factors, were pre-validated, yielding an accuracy of 92% (83% sensitive, 97% specific) on the preclinical validation sample set.
Our findings support that transcriptomic and proteomic signatures in saliva can serve as biomarkers for the non-invasive detection of breast cancer. The salivary biomarkers possess discriminatory power for the detection of breast cancer, with high specificity and sensitivity, which paves the way for prediction model validation study followed by pivotal clinical validation.
PLoS ONE 01/2010; 5(12):e15573. · 4.09 Impact Factor
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ABSTRACT: Lack of detection technology for early pancreatic cancer invariably leads to a typical clinical presentation of incurable disease at initial diagnosis. New strategies and biomarkers for early detection are sorely needed. In this study, we have conducted a prospective sample collection and retrospective blinded validation to evaluate the performance and translational utilities of salivary transcriptomic biomarkers for the noninvasive detection of resectable pancreatic cancer.
The Affymetrix HG U133 Plus 2.0 Array (Affymetrix, Santa Clara, CA) was used to profile transcriptomes and discover altered gene expression in saliva supernatant. Biomarkers discovered from the microarray study were subjected to clinical validation using an independent sample set of 30 pancreatic cancer patients, 30 chronic pancreatitis patients, and 30 healthy controls.
Twelve messenger RNA biomarkers were discovered and validated. The logistic regression model with the combination of 4 messenger RNA biomarkers (KRAS, MBD3L2, ACRV1, and DPM1) could differentiate pancreatic cancer patients from noncancer subjects (chronic pancreatitis and healthy control), yielding a receiver operating characteristic plot, area under the curve value of 0.971 with 90.0% sensitivity and 95.0% specificity.
The salivary biomarkers possess discriminatory power for the detection of resectable pancreatic cancer, with high specificity and sensitivity. This report provides the proof of concept of salivary biomarkers for the noninvasive detection of a systemic cancer and paves the way for prediction model validation study followed by pivotal clinical validation.
Gastroenterology 11/2009; 138(3):949-57.e1-7. · 11.68 Impact Factor
