Microarray-gebaseerde identificatie van individuele herv Loci Expression: Toepassing op Biomarker Discovery bij prostaatkanker

This Transcriptomic analysis of human prostate cancer tissues identifies individual human endogenous retrovirus expression loci to evaluate a custom high density microarray as a screening tool for biomarker discovery. After the surgeon has removed the prostate organ from the patient, the pathologist prepares tumoral and adjacent normal tissues separately in the lab extract, purify and qualify MR.NA from the normal and tumoral tissues amplify mRNAs using whole transcriptome ovation kit and then cleave and label the resulting amplified products. Then sequentially process the H-E-R-V-V two microarray by filling hybridizing, washing and scanning.

Ultimately using biocomputing methods probe sets, exhibiting significant signal and differential expression can be tracked leading to the identification of transcriptionally active individual loci. Many years ago we explored the behavior of the IRV W family in various contexts, including multiple sclerosis samples. Placenta testis.

I first had the idea of its method when we began to understand that overlapping or non-overlapping subgroups of IRV elements within a family were expressed. Depending on the context. Using ship technology allows for coordinated exploration of several her families and the simultaneous analysis of different region for each locus.

For example, US three and UF domain for LTR, which may support a direct role in the pathology. This method can help answer key questions in the cancer field, such as for diagnosis of prostate cancer, where the existing protein biomarkers like PSA, lacks specificity and sensitivity. Meanwhile, non-coding RNA like PCA three appear more promising, Demonstrating the prostate handling procedure will be selling michel a technician from the pathology department.

Philippe per will demonstrate the RNA extraction target preparation and analysis while al a technician from the John Unit laboratory will demonstrate the ship procedure. Mount the frozen tissue course vertically upon a small mound of OCT at the cryostat. Take a single five micron section, stain it with Blu udine, then perform a quick histological examination to examine the nature of the tissue for tumoral tissue.

Estimate the quantity of tural cells and select only cores with more than 80%tumoral cells. Cut another five micron section and stain with hematin, eoin and saffron. Now cut 15 sections of 30 micron thickness and transfer them to an RNAs free eend orph tube.

Then take a last five micron section for staining with hematin, eoin and saffron to control for the quantity of tumoral cells. At the end of the procedure, trans transfer the samples on dry ice to the molecular biology laboratory. Homogenize the tissue in Triol solution on ice, using a handheld grinder until the tissue is completely dissolved.

Incubate the samples at room temperature for five minutes. Then add 300 microliters of chloroform and vortex for 15 seconds. After two minutes at room temperature centrifuge at 12, 000 G for 15 minutes at two to eight degrees Celsius.

For the RNA, carefully transfer the top aqueous phase to a new tube. Add 750 microliters of isopropanol, mix by inversion and incubate at room temperature for 10 minutes. Centrifuge the samples to pellet the precipitated RNA, wash the RNA pellet with one milliliter of 80%ethanol.

Then centrifuge the samples at 7, 500 G for 10 minutes at four degrees Celsius. Remove the supernatant using P 1000 and P 10 tips. Allow the remaining ethanol to air dry.

Next, add 100 microliters of RNAs free water. Transfer the samples to a 70 degree Celsius heat block. To dissolve the pellet, check the quality of RNA and the RNA integrity using a bioanalyzer and a NanoDrop according to the manufacturer's instructions.

In an ideal RNA extraction, the RNA integrity number is typically seven or greater. Continue with the whole transcriptome ovation, RNA amplification kit following instructions from the supplier. Then purify the resulting single stranded CD NA product.

Check the yield and size distribution of the single stranded CDNA using a bioanalyzer and a NanoDrop according to the manufacturer's instructions. The size distribution of amplified CD NA should typically be between 101, 500 bases long with a peak around 600 bases and have an overall bell-shaped distribution. Next to fragment the CDNA, add 6.6 microliters of fragmentation mix to two micrograms of CD NA in 30 microliters spin and incubate at 37 degrees Celsius for 10 minutes.

Then inactivate the DNA's one at 95 degrees Celsius for 10 minutes and keep on ice. Aliquot one microliter of the fragmented CDNA for Agilent based size distribution verification. DNA's one treatment homogenizes the CD NA size distribution to around 100 nucleotides before hybridization.

Check for the single stranded CD NA size distribution using a bioanalyzer Pfizer pre-wet. The HERV gene chip with 200 microliters of pre hybridization. Mix and incubate at 50 degrees Celsius, 60 RPM for 10 minutes.

Add 131 microliters of hybridization mix to the 69 microliters of fragmented and labeled CD NA at room temperature mix and in nature for two minutes at 95 degrees Celsius. Then incubate at 50 degrees Celsius for five minutes and centrifuge at maximum speed for five minutes. Now empty the pre wetted HERV gene chip and load the 200 microliter target preparation.

Apply tough spots on the two SEPTA hybridize at 50 degrees Celsius, 60 RPM for 18 hours. Empty the HERV gene chip and fill the probe. Be array with 250 microliters of wash buffer, a place 600 microliters of SAPE solution mix and 600 microliters of antibody solution mix at positions number one and number two, place 800 microliters of array holding buffer at position.

Number three, push down the needles. Assign the right chip to each module. Select the FS 4 5 0 0 0 4 protocol and run each module as instructed by the software.

Apply tough spots onto the SEPTA to prevent leaking. Then load the chip into the auto loader or alternatively directly into the scanner. Start scanning.

After scanning the chip dot CEL files are generated, check the image and align the grid to the spot to identify the probe cells. Also subject the chips to several quality control measurements. Now normalize the chips and apply a hierarchical clustering approach to explore the dataset after normalization, significant analysis was performed to search for differentially expressed genes from the microarray procedure and was followed by a false discovery rate correction on five match pair tumor and normal prostate RNA samples.

This led to the identification of 207 HERV probe sets with differential expression values. Further analysis of 35 additional match pair samples from other cancer tissues identified 44 prostate specific HERV probe sets. These are the 10 most relevant HERV structures.

Finally, functional analysis can be performed in a dedicated interface consisting of annotated sequences of interest illustrated by one H-E-R-V-W element chosen in the top 10 identified proviral structures labeled on top with its dedicated specific probes present on the H-E-R-V-V two array and labeled with the functional retroviral regions LTR gag POLE N, and with a focus on the five prime LTRU three and U five subdomains, and the subsequent design of PCR primers for RT PCR validation. After watching this video, you should have a good understanding of how to master the critical steps involved in sample and target preparation, which are quality prerequisites to succeed in the use of microray for earth, as well as conventional bio marker discovery. We have designed a high density microarray in ametri format, aiming to optimally characterize individual of loci expression in order to better understand whether they can be active if the dry non-con area NA transcription or modulate coding gene expression.

This technique paves the way for researchers in the field of chronic and infectious diseases because the systematic identification of active voci may unify genetic, viral and environmental hypothesis as triggering factors in various pathologies. Working with a limited number of samples in a technical proof of concept experiment can be tricky to successfully discover biomarkers take precautions, such as respecting a statistically validated workflow, including robustness of the method, and a representative sampling of the targeted patient population.