Overcoming challenges in human saliva gene expression measurements.

Saliva, as a non-invasive and easily accessible biofluid, has been shown to contain RNA biomarkers for prediction and diagnosis of several diseases. However, systematic analysis done by our group identified two problematic issues not coherently described before: (1) most of the isolated RNA originates from the oral microbiome and (2) the amount of isolated human RNA is comparatively low. The degree of bacterial contamination showed ratios up to 1:900,000, so that only about one out of 900,000 RNA copies was of human origin, but the RNA quality (average RIN 6.7 + /- 0.8) allowed for qRT-PCR. Using 12 saliva samples from healthy donors, we modified the methodology to (1) select only human RNA during cDNA synthesis by aiming at the poly(A)+-tail and (2) introduced a pre-amplification of human RNA before qRT-PCR. Further, the manufacturer's criteria for successful pre-amplification (Ct values ≤ 35 for unamplified cDNA) had to be replaced by (3) proofing linear pre-amplification for each gene, thus, increasing the number of evaluable samples up to 70.6%. When considering theses three modifications unbiased gene expression analysis on human salivary RNA can be performed.

Biological dosimetry and modern (-omic) methods.

The increased risk of acute large-scale radiation exposure of the population underlies the necessity to develop new methods that could provide a rapid assessment of the doses received while using modern high-throughput technologies. At the same time, there is a growing interest in discovering new biomarkers enabling the categorization of irradiated individuals that could be used in epidemiological studies to correlate the estimated absorbed doses with the consequent impact on patients health. The aim of this study was to summarize the current literature on biological dosimetry, specifically ionizing radiation-responsive biomarkers. We briefly describe current knowledge in the field of radiation genomics, metabolomics, and proteomics. Although the majority of studies that provided a plethora of useful information were conducted in animal models, oncological patients remain the crucial experimental model. The authors describe various biological materials that could be potentially used to predict the effect of ionizing radiation. Plasma proteins appear to be ideal for this purpose. Out of many candidate markers, the ferredoxin reductase (FDXR) seems to be promising, as it has been confirmed in several biodosimetric studies at the level of both human gene and protein.

The hunt for radiation biomarkers: current situation.

Purpose: The possibility of a large-scale acute radiation exposure necessitates the development of new methods that could provide a rapid assessment of the doses received by individuals using high-throughput technologies. There is also a great interest in developing new biomarkers of dose exposure, which could be used in large molecular epidemiological studies in order to correlate estimated doses received and health effects. The goal of this review was to summarize current literature focused on biological dosimetry, namely radiation-responsive biomarkers.Methods: The studies involved in this review were thoroughly selected according to the determined criteria and PRISMA guidelines.Results: We described briefly recent advances in radiation genomics and metabolomics, giving particular emphasis to proteomic analysis. The majority of studies were performed on animal models (rats, mice, and non-human primates). They have provided much beneficial information, but the most relevant tests have been done on human (oncological) patients. By inspecting the radiaiton biodosimetry literate of the last 10 years, we identified a panel of candidate markers for each -omic approach involved.Conslusions: We reviewed different methodological approaches and various biological materials, which can be exploited for dose-effect prediction. The protein biomarkers from human plasma are ideal for this specific purpose. From a plethora of candidate markers, FDXR is a very promising transcriptomic candidate, and importantly this biomarker was also confirmed by some studies at protein level in humans.