Salivary Transcriptome Diagnostics for Oral Cancer Detection

It is a common experience to sacrifice sleep to meet the demands of our 24-h society. Current estimates reveal that as a society, we sleep on average 2 h less than we did 40 years ago. This level of sleep restriction results in negative health outcomes and is sufficient to produce cognitive deficits and reduced attention and is associated with increased risk for traffic and occupational accidents. Unfortunately, there is no simple quantifiable marker that can detect an individual who is excessively sleepy before adverse outcomes become evident. To address this issue, we have developed a simple and effective strategy for identifying biomarkers of sleepiness by using genetic and pharmacological tools that dissociate sleep drive from wake time in the model organism Drosophila melanogaster. These studies have identified a biomarker, Amylase, that is highly correlated with sleep drive. More importantly, both salivary Amylase activity and mRNA levels are also responsive to extended waking in humans. These data indicate that the fly is relevant for human sleep research and represents a first step in developing an effective method for detecting sleepiness in vulnerable populations.Drosophila ͉ saliva ͉ sleep deprivation I t has been suggested that forced and self-inflicted sleep loss have reached epidemic proportions in Western industrialized populations (1, 2), costing billions of dollars in lost productivity and creating hazardous conditions on our roadways (3), in our skies (4), and in our hospitals (5). The National Highway Traffic Safety Administration estimates that 20% of motor vehicle crashes are attributed to sleepiness and fully 37% of adult drivers report falling asleep at the wheel at some point in their lives. Moreover, both regional and long-haul pilots accumulate sleep debt during trips, fall asleep in the cockpit, and experience levels of sleepiness that are associated with performance decrements (6, 7). In the hospital setting, training demands frequently disrupt the sleep of medical residents, which is then associated with increased attentional failures and medical errors (8). Indeed, after a heavy call rotation, the driving performance of medical residents was similar to those with a blood alcohol level of 0.05 g % (9) and is associated with increased risk of falling asleep while driving (10).Given the magnitude of this problem, it is not surprising that the sleep community, public health officials, and others have devoted considerable attention toward minimizing the negative impact of sleep loss on public health and safety (11). In addition to more focused basic research and increased educational campaigns to create public awareness, both regulatory and legislative initiatives have been implemented to address this problem. A general theme that has emerged from all of these efforts has been the importance of identifying a simple and quantifiable biomarker of sleepiness (11)(12)(13). A biomarker of sleepiness should be responsive to increasing levels of sleep debt and should only be activated by period...

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“…In addition, saliva contains Ϸ3,000 mRNA species (19). We wondered whether any of these genes could be used as biomarkers of sleepiness.…”

Section: Resultsmentioning

confidence: 99%

“…Saliva samples were assayed for cortisol by using a commercially available immunoassay protocol (Salimetrics). RNA was isolated from cell-free supernatant as described (19). RNA was treated with RNase-free DNase I (TURBO DNA-free; Ambion, Austin, TX) according to the manufacturer's instructions.…”

Section: Discussionmentioning

confidence: 99%

Identification of a biomarker for sleep drive in flies and humans

Seugnet

Boero

Gottschalk

et al. 2006

Proc. Natl. Acad. Sci. U.S.A.

105

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“…Upon this finding we profiled salivary RNA of healthy subjects on gene expression arrays, establishing the "normal salivary core transcripts" (NSCT), a set of 185 mRNAs which were detected in each saliva supernatant of the studied 10 healthy subjects [10]. The translational utility of salivary transcriptome analysis was established by the array based discovery of several oral cancer mRNA biomarkers [11]: 9 candidate transcripts were chosen from a comparison of ten early stage oral cancer patients and ten healthy matched control subjects for validation by quantitative "real-time" RT-PCR. In a validation cohort of 32 patients and 32 controls (including the samples used in the discovery) 7 transcripts were confirmed to be elevated in OSCC with statistical significance (p<0.05 with Wilcoxon's signed rank test): DUSP1, H3F3A, IL1B, IL8, OAZ1, SAT and S100P.…”

Section: Salivary Transcriptomementioning

confidence: 99%

“…• Microarray technology was applied to identify RNA profiles in cell free saliva [10] and to define a normalSalivary core transcriptome (NSCT) • Salivary mRNA biomarkers for oral cancer were identified through microarray technology as DUSP1, H3F3A, OAZ1, S100P, SAT, IL8 and IL1B [9][10][11].…”

Section: Salivary Transcriptomementioning

confidence: 99%

Salivary mRNA targets for cancer diagnostics

Zimmermann

Wong

2008

Oral Oncology

Self Cite

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Head and neck squamous cell carcinoma (HNSCC) affects almost 1 million people worldwide per year. Despite therapeutic advances the overall survival rate remains low because diagnosis often occurs only at advanced stages with poor prognosis. Like in most cancers, the implementation of an early detection scheme would have a positive impact on this disease. Similarly, as oral cancer has a very high recurrence rate, the early identification of recurrence or second primary tumors is an important challenge.HNSCC detection is currently based on expert clinical examination of the upper aerodigestive tract and histologic analysis of suspicious areas, but it may be undetectable in hidden sites, and unfortunately visual screening for oral lesions is an often neglected part of dental healthcare. Our group is actively pursuing the assembly of a toolbox for the molecular analysis of oral fluid. Here we present our current status utilizing the salivary transcriptome for oral cancer diagnostics.

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“…In the United States, commercial products for saliva-based diagnosis of drug abuse and HIV infection and for assessing hormone levels and various toxicology issues have been approved by the FDA and are in widespread use (5). Studies have demonstrated that evaluation of salivary transcripts, proteins, metabolites, and other molecules can detect oral cancer (6)(7)(8), breast cancer (9, 10), lung cancer (11), ovarian cancer (12), Sj€ ogren syndrome (13), and other oral and systemic diseases (14,15).…”

Section: Introductionmentioning

confidence: 99%

Salivary microRNAs Show Potential as a Noninvasive Biomarker for Detecting Resectable Pancreatic Cancer

Xie

Yin

Gong

et al. 2015

Cancer Prevention Research

106

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Early surgery is vital in the treatment of pancreatic cancer, which is often fatal. However, there is currently no useful noninvasive biomarker to screen for pancreatic cancer. Studies have documented that many salivary molecules can be used to detect systemic diseases. We investigated whether salivary miRNAs are useful biomarkers for detecting resectable pancreatic cancer. Using an Agilent microarray, salivary miRNAs were profiled from saliva samples of 8 patients with resectable pancreatic cancer and 8 healthy controls. Candidate biomarkers identified in the profiles were subjected to validation using quantitative PCR and an independent sample set of 40 patients with pancreatic cancer, 20 with benign pancreatic tumors (BPT), and 40 healthy controls. The validated salivary miRNA biomarkers were evaluated within three discriminatory categories: pancreatic cancer versus healthy control, pancreatic cancer versus BPT, and pancreatic cancer versus noncancer (healthy control þ BPT). miR-3679-5p showed significant downregulation in the pancreatic cancer group within the three categories (P ¼ 0.008, 0.007, and 0.002, respectively), whereas miR-940 showed significant upregulation in pancreatic cancer (P ¼ 0.006, 0.004, and 0.0001, respectively). Logistic regression models combining the two salivary miRNAs were able to distinguish resectable pancreatic cancer within the three categories, showing sensitivities of 72.5%, 62.5%, and 70.0% and specificities of 70.0%, 80.0%, and 70.0%, respectively. Salivary miR-3679-5p and miR-940 possess good discriminatory power to detect resectable pancreatic cancer, with reasonable specificity and sensitivity. This report provides a new method for the early detection of pancreatic cancer and other systemic diseases by assessing salivary miRNAs. Cancer Prev Res; 8(2); 165-73. Ó2014AACR.

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Salivary Transcriptome Diagnostics for Oral Cancer Detection

Cited by 511 publications

References 42 publications

Identification of a biomarker for sleep drive in flies and humans

Identification of a biomarker for sleep drive in flies and humans

Salivary mRNA targets for cancer diagnostics

Salivary microRNAs Show Potential as a Noninvasive Biomarker for Detecting Resectable Pancreatic Cancer

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