We thank Dr. Roger Erickson for his support and assistance with preparation of the manuscript.
This work was supported by the National Cancer Institute at the National Institutes of Health
(Grant Number RO1CA177984; RO1CA138642), VA program project on prostate cancer (BX001604).

Formalin-fixed, paraffin-embedded (FFPE) or fresh frozen prostate cancer samples were obtained from the SFVAMC. Samples were from prostate cancer patients who underwent radical prostatectomy at SFVAMC. Written informed consent was obtained from all patients and the study was approved by the UCSF Committee on Human Research. Alternatively, prostate cancer tissues microarrays were procured from commercial sources and used for miRNA analyses by ISH. Clinicopathological and follow up information for analyzed prostate cancer patients was collected.
1. Tissue Samples
<ol>
	<li>Cut prostate cancer tissue samples into 10 &#181;m sections using a microtome and stain with H &#38; E following the manufacturer&#8217;s protocol.</li>
	<li>Review stained slides for the identification of prostate cancer foci as well as adjacent normal glandular epithelium. 
	Note: A board certified pathologist should review the H &#38; E stained slides and mark for tumor and normal areas. Use the marked slides as guides in the subsequent sections for miRNA analyses from tumor vs normal areas.</li>
</ol>
2. miRNA Expression Analyses by Quantitative Real-time PCR
Note: This workflow involves the following steps: Laser Capture microdissection, isolation of total RNA (including miRNA and mRNA), assaying of mature miRNAs using the TaqMan MicroRNA expression assays as detailed in the following sections.
<ol>
	<li>RNA Extraction
	<ol>
		<li>Isolation of miRNA from Prostate Cancer FFPE Tissues
		<ol>
			<li>Laser capture microdissection (LCM) 
			Note: Perform steps 2.1.1.1.1- 2.1.1.1.4 in a chemical fume hood.
			<ol>
				<li>Prepare tissue slides (10 &#181;m sections) for LCM. Deparrafinize tissue sections by soaking in Xylene (2x), for 10 min each, then rehydrate the tissues by incubating the slides for 5 min each in graded ethanol (100%, 95%, 90%, 80%, 70%) followed by distilled water (5 min).</li>
				<li>Following rehydration, stain sections with hematoxylin for 30 sec followed by water.</li>
				<li>Place tissues in graded ethanol (70%, 95% 90%, 80%, 70%) (5 min each) and xylene (5 min).</li>
				<li>Dry slides in a fume hood and then place in the LCM instrument for microdissection.</li>
				<li>Perform microdissections with the LCM System in accordance with the manufacturer&#8217;s instructions24. Use pathologist marked up slides as guides for the identification of prostate cancer foci as well as adjacent normal tissue. Use the laser beam at a 10-20 &#181;m diameter pulses with a power of 70-90 mW.</li>
				<li>Capture areas of interest with infrared laser pulses onto LCM caps. Combine cells from 2-5 caps for miRNA extraction per sample. To ensure integrity of extracted RNA, immediately process captured cells for miRNA extraction.</li>
				<li>Alternatively, lyse cells in the miRNA extraction buffer (according to manufacturer&#8217;s protocol) and store lysates at -80 &#186;C.</li>
			</ol>
			</li>
			<li>miRNA Extraction and Analyses from LCM Microdissected Tissues
			<ol>
				<li>Extract total RNA from microdissected FFPE tissues using a commercial kit following the manufacturer&#8217;s instructions. 
				Note: The yield of RNA from laser capture miscrodissection is typically low. Therefore, RNA is eluted into low volumes (20-30 &#181;l) and used for expression profiling using Taqman microRNA expression assays following manufacturer&#8217;s instructions (also described in section 2.2). Optimization of input RNA for real time PCR detection of mature miRNAs suggests that 5 &#181;l of the eluted RNA is optimal for each miRNA-specific reverse transcription reaction. As an endogenous control, RNU48/RNU24 is used. For control reactions, 2 &#181;l of the eluted RNA is used for the reverse transcription reaction.</li>
			</ol>
			</li>
		</ol>
		</li>
		<li>Isolation of miRNA from Prostate Cancer Frozen Tissues
		<ol>
			<li>Homogenize frozen resected prostate tissues by grinding the tissues in liquid nitrogen using a mortar and pestle. Transfer homogenized tissue to a microcentrifuge tube using a cooled spatula. Maintain the mortar/pestle and spatula at the same temperature by dipping in liquid nitrogen so homogenized tissue can be easily transferred.</li>
			<li>Add commercial guanidine isothiocyanate-phenol reagent (1 ml/0.1 g of tissue) to the homogenized tissue and incubate at room temperature for 5 min. 
			Note: Homogenized tissues in the commercial guanidine isothiocyanate-phenol reagent can be stored at -80 &#186;C for several months.</li>
			<li>Add chloroform to the homogenate (0.2 ml chloroform/ml) and shake vigorously for 30 sec. Incubate samples at RT for 3-5 min followed by centrifugation at 10,000 x g for 20 min at 4 &#186;C.</li>
			<li>Transfer the upper aqueous phase to a fresh sterile RNase-free 1.5 ml tube.</li>
			<li>Add an equal volume of isopropyl alcohol. Mix and incubate for 10 min at RT followed by centrifugation at 12,000 x g for 20 min at 4 &#186;C to pellet the RNA.</li>
			<li>Aspirate the supernatant and wash the RNA pellet with 1 mL of 70% ethanol. Centrifuge at 12,000 x g for 10 min at 4 &#186;C.</li>
			<li>Carefully aspirate the supernatant. Dry RNA pellets at RT for 5-10 min. Dissolve RNA in 50-100 &#181;l nuclease-free water.</li>
			<li>Perform quantification of RNA using a nanodrop spectrophotometer and determine RNA integrity with a bioanalyzer. Adjust RNA concentrations to 10 ng/&#181;l. Use 10-50 ng RNA for miRNA- specific cDNA reaction followed by real-time PCR analyses (Section 2.2).</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Quantitative Real-time PCR for miRNA Expression Analyses 
	Note: Assay mature miRNAs using a two-step RT-PCR protocol as described below.
	<ol>
		<li>Reverse Transcription (RT)
		<ol>
			<li>Reverse transcribe cDNA from RNA using a miRNA reverse transcription kit in accordance with the manufacturer&#39;s instructions. Use 10-50 ng of total RNA with miRNA specific primer from the MicroRNA Assays and RT kit. Use RNU48/RNU24/RNU6B as controls. Dilute cDNA 1:5 to 1:10 (depending on the abundance of the analyzed miRNA) and use in Real-time PCR detection as described in the following step.</li>
		</ol>
		</li>
		<li>Real-time PCR for Detection of Mature miRNA
		<ol>
			<li>Amplify PCR products from cDNA samples using the MicroRNA assays with a Fast Universal master mix in accordance with manufacturer&#8217;s instructions. Normalize samples to RNU48/RNU24/RNU6B control. Use the comparative Ct (threshold cycle) method to calculate the relative changes in gene expression on the Fast Real Time PCR System. Analyze each sample in triplicate.</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>
3. miRNA Expression Analyses by In Situ Hybridization (ISH)
<ol>
	<li>Pre-Treatment of Tissues
	<ol>
		<li>Cut 5 &#181;m sections from FFPE prostate cancer tissue blocks using a microtome.</li>
		<li>Fix tissue sections by incubating the slides at 56 &#176;C for 1 hr. 
		Note: Slides can be stored at RT for several weeks for miRNA analyses.</li>
		<li>Deparrafinize the tissues by soaking the slides with xylene (2x), for 15 min each.</li>
		<li>Rehydrate the tissues by incubating the slides for 5 min each in graded ethanol (100% (2x), 95%, 90%, 80%, 70%) followed by distilled water (5 min).</li>
		<li>Fix the slides with 4% paraformaldehyde in PBS at room temperature for 20 min.</li>
		<li>Wash the slides with PBS (2x) at room temperature for 5 min each.</li>
		<li>Treat the slides with 10 &#181;g/ml Proteinase K at 37 &#186;C for 10 min in pre-warmed proteinase K buffer (5 mM Tris-HCL pH 7.4, 1 mM EDTA, 1 mM NaCl).</li>
		<li>Following Proteinase-K treatment, rinse the slides with 0.2% glycine in PBS for 30 sec.</li>
		<li>Wash slides in PBS (1x) at room temperature for 5 min.</li>
		<li>Fix the slides with 4% Paraformaldehyde in PBS for 15 min.</li>
		<li>Rinse slides with PBS for 5 min.</li>
	</ol>
	</li>
	<li>Hybridization
	<ol>
		<li>Pre-hybridize the slides with pre-hybridization solution for 3-4 hr at 55 &#186;C in a humidified chamber. Use tissue lab wipes soaked in 50% formamide/50% 5x SSC to keep the chamber humidified.</li>
		<li>Use 5&#8217; digoxigenin labeled probes at a concentration of 20-50 nM in hybridization buffer. Dilute miRNA-specific probe (20-50 nM) and small nuclear RNA U6 control probe (20 nM), heat at 90 &#186;C for 4 min, place it on ice, and add to ice cold hybridization buffer (2-4 ng/&#181;l).</li>
		<li>Remove pre-hybridization solution, add hybridization solution (probe + hybridization buffer, 100 &#181;l per slide), incubate for 12-16 hr at probe-specific hybridization temperature (Hybridization temperature =Tm probe-21 &#186;C). Perform hybridizations in a humidified chamber (50% formamide/50% 5x SSC).</li>
	</ol>
	</li>
	<li>Washing Steps
	<ol>
		<li>Wash the slides with 2x SSC for 10 min at 45 &#186;C.</li>
		<li>Wash the slides with 1.5x SSC for 10 min at 45 &#186;C.</li>
		<li>Wash the slides with 0.2x SSC (2x) at 37 &#186;C for 20 min each.</li>
		<li>Incubate slides with 1x blocking solution for 1-2 hr at room temperature</li>
	</ol>
	</li>
	<li>Detection
	<ol>
		<li>Incubate the slides with 1:100 PBS diluted AP-conjugated anti-digoxigenin antibody for 1-4 hr or overnight at 4 &#186;C.</li>
		<li>Wash the slides with PBS (3x) at room temp for 10 min each.</li>
		<li>Wash the slides (2x) with Alkaline Phosphatase buffer (100 mM Tris pH 9.5, 50 mM MgCl2, 100 mM NaCl, 0.1% Tween-20) at RT for 5 min each.</li>
		<li>Incubate the slides in BM Purple AP substrate in the dark at RT for 1-20 hr.</li>
		<li>Rinse the slides with PBS containing 0.1% Tween-20 and wash (2x) in water.</li>
		<li>Mount the slides using an aqueous mounting media and examine under a microscope.</li>
	</ol>
	</li>
</ol>

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The authors have no financial disclosures.

In this article, we describe a simplified workflow for miRNA expression profiling in archived FFPE or fresh frozen prostate cancer clinical tissues. In prostate cancer, several studies suggest an important role of microRNAs in prostate cancer initiation, progression and metastasis. However, conflicting results are often obtained on a specific miRNA22 since the miRNA extraction and analyses methods differ widely. In view of the emerging evidence supporting the potential application of miRNAs as alternative prostate cancer biomarkers for prostate cancer prognosis, diagnosis and therapy, there is a need to accurately quantitate miRNA expression profiles in clinical tissues.
We employ a combination of quantitative real-time PCR and in situ hybridization for miRNA analyses of prostate cancer clinical specimens. Within this workflow, we optimized the existing methodologies for miRNA extraction, expression analyses by Taqman primer based RT-PCR and ISH analyses by LNA probes. During the entire workflow, it is of utmost importance to maintain an RNase free environment. All the reagents/solutions used should be RNase free and extra caution should be used in handling RNA and other reagents. All real time reactions should be set up on ice to minimize RNA degradation.
Accurate expression profiling in prostate cancer tissues is often hindered by heterogeneity and the multifocal nature of prostate cancer lesions25. This can be overcome by using a laser-capture microdisssection technique that allows the separation of benign and malignant epithelial cells and also reduces stromal contamination, allowing accurate downstream molecular analyses of prostate tissues22,25. We employ LCM of archived FFPE tissues followed by miRNA expression profiling using Taqman MicroRNA expression assays that has been reported to be reliable. miRNA profiling of LCM tissues has significant potential to enhance miRNA biomarker discovery. In fact, there is considerable interest in analyzing FFPE tissues considering that these tissues are widely used by pathologists for clinical analyses, preservation, and archiving and are readily available3. Also, owing to their small size and resistance to endogenous RNase activity, miRNAs are relatively less affected by FFPE dependent degradation and are attractive potential biomarkers3. The miRNA expression profiles of formalin fixed tissues have been reported to be strongly correlated to those of frozen tissues21.
We employed and compared two different commercial kits for miRNA extraction from FFPE tissues. While both kits yielded high quality RNA for RT-PCR analyses, we used the one that uses a simple, streamlined protocol for consistent purification of miRNAs and total RNA from FFPE tissues.
Integrity, purity and concentration of RNA should be tested before RT-PCR analyses. Samples showing low A260/A230 ratio (&#60;1.8) should be re-precipitated and re-analyzed for purity before using in an RT reaction. Also, real-time PCR analyses of clinical tissues may need to be further optimized. Threshold cycle (Ct values) &#62;33 indicate low amplification reflecting low starting cDNA template. In this case, cDNA template inputs can be increased. Also, it is of utmost importance that adequate control is used for normalizing and determining relative miRNA quantifications between normal and tumor tissues. Endogenous control (RNU48/RNU24/RNU6B) is chosen based on the uniformity of amplification signals in normal vs. tumor samples.
Also, we describe an optimized protocol for miRNA ISH analyses of prostate cancer tissues based on LNA- based probes. Our optimized miRNA ISH protocol can be applied to prostate cancer tissue slides or prostate cancer tissue microarrays (TMA), with the latter offering the potential to accelerate miRNA biomarker discovery. This protocol can also be applied to other tissue types. However, the duration of proteinaseKdigestionandparaformaldehydetreatment may need to be optimized. Proteinase K digestion allows the miRNA probe to get into the cells while paraformaldehyde fixation is needed to prevent miRNA loss following permeabilization. This protocol, originally developed for use with LNA probes26 is optimized to get a specific signal with minimal background in prostate tissues. Probe concentrations and incubation conditions are optimized for prostate cancer tissues. We employ 5&#8217;digoxigeninlabeledprobes at a concentration of 20-50 nM depending upon the abundance of miRNA. However, 3&#8217;digoxigeninlabeledprobes and dual labeled (5&#8217; and 3&#8217;) labeled probes can be substituted. In fact, dual labeled probes offer the potential for better colorimetric development for microRNA detection and are recommended for low abundance miRNA detection. Also, duration of blocking and antibody incubations may be optimized. Longer blocking is recommended for lower background, particularly with low abundance miRNAs. Thedurationofcolor reaction with BM purple substrate should be closely monitored. Longer incubations can generate background staining. Usually, abundant miRNAs require shorter incubations (1-2 hr) while less abundant miRNA are detected with longer incubations. During ISH, it is important to ensure that the tissue sections do not dry out during any of the steps as this may lead to staining artifacts.
In conclusion, though several studies suggest miRNAs as important prostate cancer biomarkers, the significance of several of these studies is often debated due to conflicting results. Here we have defined an optimized workflow for accurate miRNA expression analyses in prostate cancer clinical specimens that have a potential to accelerate the discovery of miRNA as biomarkers for prostate cancer. While this workflow has significant potential to accurately profile miRNA expression in prostate cancer clinical tissues, there are inherent limitations of the techniques employed. Low abundant miRNAs may be difficult to profile with the optimized miRNA RT-PCR and ISH analyses described here. Though RT-PCR based profiling has a wider dynamic range than ISH27,28, low RNA amounts obtained from LCM may limit detection of low abundant miRNAs. ISH-based detection of miRNAs yields powerful spatial information, however its limitations are that it is a semi-quantitative technique with a lesser dynamic range28. This technique relies on sensitivity and specificity of probes employed and also on the optimization of conditions for hybridization and detection of miRNAs.

Cancer of the prostate gland is a commonly diagnosed male malignancy that is one of the leading causes of cancer related mortality among men. In US, an estimated 220,800 new cases and 27,540 deaths will be reported in 20151.
Prostate cancer is a heterogeneous disease with highly variable disease course- tumors can be indolent or very aggressive. A critical challenge in prostate cancer clinical management is posed by the inadequacy of currently used methods/biomarkers for disease screening, diagnosis, prognosis and treatment2. Current screening methods include prostate specific antigen (PSA) testing and a digital rectal examination (DRE) followed by prostate biopsies3. Prostate specific antigen (PSA) is the most widely used prostate cancer biomarker that has significantly revolutionized clinical management and improved survival rates4. However, due to inherent limitations of PSA including lack of specificity, PSA-based screening has led to over diagnosis and over treatment of the disease. In view of this, intensive efforts are being directed towards a search for alternate prostate cancer biomarkers, particularly those which can predict the aggressiveness of the disease and drive better treatment decisions4,5. Over the last few years, microRNAs (miRNAs) have emerged as promising alternate prostate cancer biomarkers.
MicroRNAs (miRNAs) constitute an evolutionarily conserved class of small non-coding RNAs that suppress gene expression post-transcriptionally via sequence-specific interactions with the 3&#8217;- untranslated regions (UTRs) of cognate mRNA targets. It is estimated that &#62;60% of mRNAs are conserved targets of miRNAs6. miRNA genes are located in intergenic regions or within introns or exons of protein/non-protein coding genes7. These genes are preferentially transcribed by RNA Polymerase II into primary miRNAs (pri-miRNAs, several kilobases long) that form hairpin shaped stem loop secondary structures. These pri-miRNAs are processed into precursor miRNAs (pre-miRNAs, 60-75 nucleotide long) that are exported to the cytoplasm and further processed into mature miRNAs (18-25 nucleotide long)8-10. miRNAs regulate key cellular processes including proliferation, development, differentiation and apoptosis11. Studies suggest a widespread dysregulation of miRNA expression profiles in various human malignancies including prostate cancer12-15. miRNA expression profiles have been reported to be widely dysregulated in primary and metastatic prostate cancer. Altered miRNA expression have been linked with prostate cancer progression, aggressiveness and recurrence highlighting the prognostic potential of miRNAs12,14,16-19. A growing body of evidence indicates that miRNAs play important mechanistic roles in prostate cancer initiation, development, progression and metastasis. Overall, miRNAs are emerging as promising alternate biomarkers for prostate cancer diagnosis and prognosis that can distinguish between normal and cancer tissues and aid in stratification of prostate tumors12. Also, miRNAs are important targets for development of effective therapeutics against prostate cancer20.
Owing to their small size and resistance to endogenous RNase activity, miRNAs are stable biomarkers that can be readily detected in formalin-fixed tissues21 and in prostate biopsies22. Moreover, the expression profiles of miRNAs have been compared in frozen and formalin fixed tissues and have been found to be strongly correlated21. However, miRNA expression profiling in prostate cancer clinical tissues is often challenging owing to tumor heterogeneity, sampling errors, stromal contamination etc. The development of miRNAs as effective biomarkers for prostate cancer heavily relies on their accurate detection in clinical tissues. Here we describe a simplified workflow used in our lab for miRNA expression profiling in archived FFPE or fresh frozen prostate cancer clinical specimens. We employ a combination of quantitative real-time PCR and in situ hybridization for miRNA analyses of clinical specimens, with the former yielding more quantitative information and the latter for visualizing the differential expression of potential miRNA biomarkers in an array of tissues. Within this workflow, we optimize the existing methodologies for miRNA extraction from FFPE and frozen prostate tissues, expression analyses by Taqman-probe based miRNA RT-PCR and miRNA in situ hybridization technique using locked nucleic acid (LNA)-based probes23. LNA-based probes offer increased sensitivity and specificity compared to DNA- or RNA- based probes and enables robust detection of all miRNA sequences, regardless of their GC content and also allow discrimination of miRNA families. Our optimized miRNA ISH protocol can be applied to prostate cancer tissue slides or prostate cancer tissue microarrays (TMA), with the latter offering the potential to accelerate miRNA biomarker discovery.

<table border="0" cellpadding="0" cellspacing="0">
	<tbody>
		<tr>
			<td>Microtome</td>
			<td>Leica Biosystems&#160;</td>
			<td>RM2255</td>
			<td></td>
		</tr>
		<tr>
			<td>Arcturus Autopix for LCM</td>
			<td>Arcturus/ Life Technologies</td>
			<td>LCM1621/LCM1110</td>
			<td>Alternatively, Arcutus Xt system from Life Technolgies can be used.&#160;</td>
		</tr>
		<tr>
			<td>CapSure Macro LCM Caps</td>
			<td>Life Technologies</td>
			<td>LCM0211</td>
			<td></td>
		</tr>
		<tr>
			<td>miRNeasy FFPE Kit&#160;</td>
			<td>Qiagen</td>
			<td align="right">217504</td>
			<td></td>
		</tr>
		<tr>
			<td>7500 Fast Real Time PCR System&#160;</td>
			<td>Applied Biosystems/ Life Technologies</td>
			<td align="right">4351106</td>
			<td></td>
		</tr>
		<tr>
			<td>Taqman MicroRNA Reverse Transcription kit&#160;</td>
			<td>Applied Biosystems/ Life Technologies</td>
			<td align="right">4366596</td>
			<td></td>
		</tr>
		<tr>
			<td>Taqman Fast Universal PCR master mix&#160;</td>
			<td>Applied Biosystems/ Life Technologies</td>
			<td align="right">4352042</td>
			<td></td>
		</tr>
		<tr>
			<td>DIG labeled LNA probe for U6</td>
			<td>Exiqon</td>
			<td>99002-01</td>
			<td></td>
		</tr>
		<tr>
			<td>BM Purple AP substrate</td>
			<td>Roche</td>
			<td align="right">11442074001</td>
			<td></td>
		</tr>
		<tr>
			<td>Pre-hybridization solution&#160;</td>
			<td>Biochain</td>
			<td><a href="http://www.biochain.com/coa/K21910XXCA.pdf">K2191050-1</a></td>
			<td></td>
		</tr>
		<tr>
			<td>Hybridization solution&#160;</td>
			<td>Biochain</td>
			<td><a href="http://www.biochain.com/coa/K21910XXCA.pdf">K2191050-2</a></td>
			<td></td>
		</tr>
		<tr>
			<td>Blocking solution&#160;</td>
			<td>Biochain</td>
			<td><a href="http://www.biochain.com/coa/K21910XXCA.pdf">K2191050-8</a></td>
			<td></td>
		</tr>
		<tr>
			<td>AP-conjugated anti-digoxigenin antibody</td>
			<td>Biochain</td>
			<td><a href="http://www.biochain.com/coa/K21910XXCA.pdf">K2191050-7</a></td>
			<td></td>
		</tr>
		<tr>
			<td>Aqueous mounting media&#160;</td>
			<td>Vector Laboratories&#160;</td>
			<td>H-5501&#160;&#160;</td>
			<td></td>
		</tr>
		<tr>
			<td>Trizol (guanidine isothiocyanate-phenol reagent)&#160;</td>
			<td>Life Technologies</td>
			<td><a href="https://www.lifetechnologies.com/order/catalog/product/15596018">15596-018</a></td>
			<td></td>
		</tr>
		<tr>
			<td>Harris hematoxylin</td>
			<td>Statlab</td>
			<td>SL200</td>
			<td></td>
		</tr>
		<tr>
			<td>Eosin&#160;</td>
			<td>Statlab</td>
			<td>SL201&#160;</td>
			<td></td>
		</tr>
	</tbody>
</table>

mirna expression analyses in prostate cancer clinical tissues

A critical challenge in prostate cancer (PCa) clinical management is posed by the inadequacy of currently used biomarkers for disease screening, diagnosis, prognosis and treatment. In recent years, microRNAs (miRNAs) have emerged as promising alternate biomarkers for prostate cancer diagnosis and prognosis. However, the development of miRNAs as effective biomarkers for prostate cancer heavily relies on their accurate detection in clinical tissues. miRNA analyses in prostate cancer clinical specimens is often challenging owing to tumor heterogeneity, sampling errors, stromal contamination etc. The goal of this article is to describe a simplified workflow for miRNA analyses in archived FFPE or fresh frozen prostate cancer clinical specimens using a combination of quantitative real-time PCR (RT-PCR) and in situ hybridization (ISH). Within this workflow, we optimize the existing methodologies for miRNA extraction from FFPE and frozen prostate tissues and expression analyses by Taqman-probe based miRNA RT-PCR. In addition, we describe an optimized method for ISH analyses formiRNA detection in prostate tissues using locked nucleic acid (LNA)- based probes. Our optimized miRNA ISH protocol can be applied to prostate cancer tissue slides or prostate cancer tissue microarrays (TMA).

Expression profiling of miR-203 in LCM primary prostate cancer clinical specimens by RT-PCR analyses (Figure 1)
RT-PCR analyses of relative miR-203 expression in LCM primary prostate cancer tissues and the matched adjacent normal regions was carried out as described in Saini et al.15 RNU48 was used as a control. The Table below summarizes the relative miR-203 expression in prostate cancer tumor tissues relative to adjacent normal tissues.
Comparison of miR-383 expression by RT-PCR analyses in microdissected vs laser capture microdissected PCa tissues (Figure 2)
Prostate cancer tissues were either microdissected under the microscope or were subjected to LCM followed by RT-PCR analyses of miR-383 expression in tumor tissues relative to matched adjacent normal tissues.Relative miR-383 expression in tumor samples are shown.RNU48 was used as a control. As shown in Figure 2, differences were observed when miRNA expression was analyzed in these tissues. LCM has an advantage over microdissection under microscope as it allows isolation of a relatively pure population of prostate tissues and is more reliable.
ISH analyses of miR-203 expression in prostate cancer clinical tissues (Figure 3)
In situ hybridization analyses of miR-203 expression in normal and bone metastatic prostate cancer tissues was performed as described in Saini et al.15 Prostate cancer tissue microarray was used for ISH analyses using 5&#8217;- DIG labelled LNA probes specific for miR-203 and U6. Representative example of ISH analyses is shown in Figure 3, a figure partly reproduced from Saini et al. (2011)15 Figure 3A and 3B showsmiR-203 expression (left) and U6 control expression (right) in the indicated tissues. ISH signals were semi-quantitatively graded based on the intensity of staining and percent of stained cells and assigned a score of 1 to 4. Intensity scores of miR-203 expression were divided by those of U6 expression to obtain normalized miR-203 expression levels that were plotted in Figure 3C.
<img alt="Figure 1" src="/files/ftp_upload/53123/53123fig1.jpg" /> 
Figure 1: Expression profiling of miR-203 in LCM primary prostate cancer clinical specimens by RT-PCR analyses. RT-PCR analysis of relative miR-203 expression in LCM-prostate cancer tissues and the matched adjacent normal regions. RNU48 was used as a control. The Table below summarizes the relative miR-203 expression in prostate cancer tumor tissues relative to adjacent normal tissues. <a href="https://www.jove.com/files/ftp_upload/53123/53123fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/53123/53123fig2.jpg" /> 
Figure 2: Comparison of miR-383 expression by RT-PCR analyses in microdissected vs. laser capture microdissected PCa tissues. Prostate cancer tissues were either microdissected under the microscope or were subjected to LCM followed by RT-PCR analyses of miR-383 expression in tumor tissues relative to matched adjacent normal tissues. Relative miR-383 expressions in tumor samples are shown.RNU48 was used as a control. <a href="https://www.jove.com/files/ftp_upload/53123/53123fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" src="/files/ftp_upload/53123/53123fig3.jpg" /> 
Figure 3: ISH analyses of miR-203 expression in prostate cancer clinical tissues. This figure has been modified from15. Tissues were hybridized with DIG-labelled locked nucleic acid (LNA) based probes for mir-203 and U6 (control) as described in15. Representative example of ISH analysis of miR-203 expression (left panels) and control U6 expression (right panels) in human prostate cancer normal and bone metastatic tissues showing attenuated miR-203 expression in bone metastatic tissues. Representative ISH examples shown in A at a higher magnification (40X). Relative miR-203 expression levels in normal prostate tissues and bone metastatic prostate cancer tissues as assessed by ISH analysis. miR-203 expression was scored , normalized to U6 scores and plotted. Horizontal line represents the average value. <a href="https://www.jove.com/files/ftp_upload/53123/53123fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about miRNA Expression Analyses in Prostate Cancer Clinical Tissues at JoVE.com

miRNA Expression Analyses in Prostate Cancer Clinical Tissues

Here we describe a simplified protocol for microRNA (miRNA) expression analyses in archived Formalin-Fixed, Paraffin-Embedded (FFPE) or fresh frozen prostate cancer (PCa) clinical tissues employing quantitative real-time PCR (RT-PCR) and in situ hybridization (ISH).

A critical challenge in prostate cancer (PCa) clinical management is posed by the inadequacy of currently used biomarkers for disease screening, ...

mirna-expression-analyses-in-prostate-cancer-clinical-tissues

Nanyang Technological University

Research

JoVE Journal

Medicine

10.8K Views.  University of California San Francisco. Here we describe a simplified protocol for microRNA (miRNA) expression analyses in archived Formalin-Fixed, Paraffin-Embedded (FFPE) or fresh frozen prostate cancer (PCa) clinical tissues employing quantitative real-time PCR (RT-PCR) and in situ hybridization (ISH).

Video: miRNA Expression Analyses in Prostate Cancer Clinical Tissues

Evaluation of Nanoparticle Uptake in Tumors in Real Time Using Intravital Imaging

Current technologies for tumor imaging, such as ultrasound, MRI, PET and CT, are unable to yield high-resolution images for the assessment of nanoparticle uptake in tumors at the microscopic level1,2,3, highlighting the utility of a suitable xenograft model in which to perform detailed uptake analyses. Here, we use high-resolution intravital imaging to evaluate nanoparticle uptake in human tumor xenografts in a modified, shell-less chicken embryo model. The chicken embryo model is particularly well-suited for these in vivo analyses because it supports the growth of human tumors, is relatively inexpensive and does not require anesthetization or surgery 4,5. Tumor cells form fully vascularized xenografts within 7 days when implanted into the chorioallantoic membrane (CAM) 6. The resulting tumors are visualized by non-invasive real-time, high-resolution imaging that can be maintained for up to 72 hours with little impact on either the host or tumor systems. Nanoparticles with a wide range of sizes and formulations administered distal to the tumor can be visualized and quantified as they flow through the bloodstream, extravasate from leaky tumor vasculature, and accumulate at the tumor site. We describe here the analysis of nanoparticles derived from Cowpea mosaic virus (CPMV) decorated with near-infrared fluorescent dyes and/or polyethylene glycol polymers (PEG) 7, 8, 9,10,11. Upon intravenous administration, these viral nanoparticles are rapidly internalized by endothelial cells, resulting in global labeling of the vasculature both outside and within the tumor7,12. PEGylation of the viral nanoparticles increases their plasma half-life, extends their time in the circulation, and ultimately enhances their accumulation in tumors via the enhanced permeability and retention (EPR) effect 7, 10,11. The rate and extent of accumulation of nanoparticles in a tumor is measured over time using image analysis software. This technique provides a method to both visualize and quantify nanoparticle dynamics in human tumors.

We present a novel approach to quantify nanoparticle localization in the vasculature of human xenografted tumors using dynamic, real-time intravital imaging in an avian embryo model.

Current technologies for tumor imaging, such as ultrasound, MRI, PET and CT, are unable to yield high-resolution images for the assessment of nanoparticle ...

Cell Population Analyses During Skin Carcinogenesis

Cancer development is a multiple-step process involving many cell types including cancer precursor cells, immune cells, fibroblasts and endothelial cells. Each type of cells undergoes signaling and functional changes during carcinogenesis. The current challenge for many cancer researchers is to dissect these changes in each cell type during the multiple-step process in vivo. In the last few years, the authors have developed a set of procedures to isolate different cell populations during skin cancer development using K14creER/R26-SmoM2YFP mice. The procedure is divided into 6 parts: 1) generating appropriate mice for the study (K14creER+ and R26-SmoM2YFP+ mice in this protocol); 2) inducing SmoM2YFP expression in mouse skin; 3) preparing mouse skin biopsies; 4) isolating epidermis from skin; 5) preparing single cells from epidermis; 6) labeling single cell populations for flow cytometry analysis. Generation of sufficient number of mice with the right genotype is the limiting step in this protocol, which may take up to two months. The rest of steps take a few hours to a few days. Within this protocol, we also include a section for troubleshooting. Although we focus on skin cancer, this protocol may be modified to apply for other animal models of human diseases.

Carcinogenesis is a process involving interactions between cancer cells and the cancer microenvironment. To dissect the molecular events, one needs to isolate different cell populations at different stages during cancer development. Using a mouse model for basal cell carcinoma, we describe a protocol for cell analyses during carcinogenesis.

Cancer development is  a multiple-step process involving many cell types including cancer precursor  cells, immune cells, fibroblasts and endothelial ...

Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer

The prostate-specific antigen (PSA) is the main diagnostic biomarker for prostate cancer in clinical use, but it lacks specificity and sensitivity, particularly in low dosage values1&#8203;&#8203;. &#8216;How to use PSA&#39; remains a current issue, either for diagnosis as a gray zone corresponding to a concentration in serum of 2.5-10 ng/ml which does not allow a clear differentiation to be made between cancer and noncancer2 or for patient follow-up as analysis of post-operative PSA kinetic parameters can pose considerable challenges for their practical application3,4. Alternatively, noncoding RNAs (ncRNAs) are emerging as key molecules in human cancer, with the potential to serve as novel markers of disease, e.g. PCA3 in prostate cancer5,6 and to reveal uncharacterized aspects of tumor biology. Moreover, data from the ENCODE project published in 2012 showed that different RNA types cover about 62% of the genome. It also appears that the amount of transcriptional regulatory motifs is at least 4.5x higher than the one corresponding to protein-coding exons. Thus, long terminal repeats (LTRs) of human endogenous retroviruses (HERVs) constitute a wide range of putative/candidate transcriptional regulatory sequences, as it is their primary function in infectious retroviruses. HERVs, which are spread throughout the human genome, originate from ancestral and independent infections within the germ line, followed by copy-paste propagation processes and leading to multicopy families occupying 8% of the human genome (note that exons span 2% of our genome). Some HERV loci still express proteins that have been associated with several pathologies including cancer7-10. We have designed a high-density microarray, in Affymetrix format, aiming to optimally characterize individual HERV loci expression, in order to better understand whether they can be active, if they drive ncRNA transcription or modulate coding gene expression. This tool has been applied in the prostate cancer field (Figure 1).

Human endogenous retroviruses (HERV), which occupy 8% of the human genome, retain scarce coding capacities but a hundred thousand long terminal repeats (LTRs). A custom Affymetrix microarray was designed to identify individual HERV locus expression and was used on prostate cancer tissues as a proof of concept for future clinical studies.

The prostate-specific antigen (PSA) is the main diagnostic biomarker for prostate cancer in clinical use, but it lacks specificity and sensitivity, ...

An Orthotopic Murine Model of Human Prostate Cancer Metastasis

Our laboratory has developed a novel orthotopic implantation model of human prostate cancer (PCa). As PCa death is not due to the primary tumor, but rather the formation of distinct metastasis, the ability to effectively model this progression pre-clinically is of high value. In this model, cells are directly implanted into the ventral lobe of the prostate in Balb/c athymic mice, and allowed to progress for 4-6 weeks. At experiment termination, several distinct endpoints can be measured, such as size and molecular characterization of the primary tumor, the presence and quantification of circulating tumor cells in the blood and bone marrow, and formation of metastasis to the lung. In addition to a variety of endpoints, this model provides a picture of a cells ability to invade and escape the primary organ, enter and survive in the circulatory system, and implant and grow in a secondary site. This model has been used effectively to measure metastatic response to both changes in protein expression as well as to response to small molecule therapeutics, in a short turnaround time.

This orthotopic model of human prostate cancer allows for quantification of tumor size, circulating tumor cells, and formation of distinct metastasis to the lung. As cells must escape the primary organ, enter the blood stream, and implant into a secondary site, this model effectively recapitulates the scenario in humans.

Our laboratory has developed a novel orthotopic implantation model of  human prostate cancer (PCa). As PCa death is not due to the primary tumor, but  ...

Isolation of Cancer Stem Cells From Human Prostate Cancer Samples

The cancer stem cell (CSC) model has been considerably revisited over the last two decades. During this time CSCs have been identified and directly isolated from human tissues and serially propagated in immunodeficient mice, typically through antibody labeling of subpopulations of cells and fractionation by flow cytometry. However, the unique clinical features of prostate cancer have considerably limited the study of prostate CSCs from fresh human tumor samples. We recently reported the isolation of prostate CSCs directly from human tissues by virtue of their HLA class I (HLAI)-negative phenotype. Prostate cancer cells are harvested from surgical specimens and mechanically dissociated. A cell suspension is generated and labeled with fluorescently conjugated HLAI and stromal antibodies. Subpopulations of HLAI-negative cells are finally isolated using a flow cytometer. The principal limitation of this protocol is the frequently microscopic and multifocal nature of primary cancer in prostatectomy specimens. Nonetheless, isolated live prostate CSCs are suitable for molecular characterization and functional validation by transplantation in immunodeficient mice.

The isolation of cancer stem cells (CSCs) directly from human tissues is requisite for their biological characterization. This manuscript describes a methodology for the isolation of prostate CSCs from human tissues, while also providing tips on troubleshooting difficult steps.

The cancer stem cell (CSC) model has been considerably revisited over the last two decades. During this time CSCs have been identified and directly ...

Ex Vivo Treatment Response of Primary Tumors and/or Associated Metastases for Preclinical and Clinical Development of Therapeutics

The molecular analysis of established cancer cell lines has been the mainstay of cancer research for the past several decades. Cell culture provides both direct and rapid analysis of therapeutic sensitivity and resistance. However, recent evidence suggests that therapeutic response is not exclusive to the inherent molecular composition of cancer cells but rather is greatly influenced by the tumor cell microenvironment, a feature that cannot be recapitulated by traditional culturing methods. Even implementation of tumor xenografts, though providing a wealth of information on drug delivery/efficacy, cannot capture the tumor cell/microenvironment crosstalk (i.e., soluble factors) that occurs within human tumors and greatly impacts tumor response. To this extent, we have developed an ex vivo (fresh tissue sectioning) technique which allows for the direct assessment of treatment response for preclinical and clinical therapeutics development. This technique maintains tissue integrity and cellular architecture within the tumor cell/microenvironment context throughout treatment response providing a more precise means to assess drug efficacy.

Ex Vivo Treatment Response of Primary Tumors and/or Associated Metastases for Preclinical and Clinical Development of Therapeutics

Established cancer cell lines and xenografts have been the mainstay of cancer research for the past several decades. However, recent evidence suggests that therapeutic response is greatly influenced by the tumor cell microenvironment. Therefore, we have developed an ex vivo analysis of primary tumor specimens for drug development purposes.

The molecular analysis of established cancer cell lines has been the mainstay of cancer research for the past several decades. Cell culture provides both ...

Studying Pancreatic Cancer Stem Cell Characteristics for Developing New Treatment Strategies

Pancreatic ductal adenocarcinoma (PDAC) contains a subset of exclusively tumorigenic cancer stem cells (CSCs) which have been shown to drive tumor initiation, metastasis and resistance to radio- and chemotherapy. Here we describe a specific methodology for culturing primary human pancreatic CSCs as tumor spheres in anchorage-independent conditions. Cells are grown in serum-free, non-adherent conditions in order to enrich for CSCs while their more differentiated progenies do not survive and proliferate during the initial phase following seeding of single cells. This assay can be used to estimate the percentage of CSCs present in a population of tumor cells. Both size (which can range from 35 to 250 micrometers) and number of tumor spheres formed represents CSC activity harbored in either bulk populations of cultured cancer cells or freshly harvested and digested tumors 1,2. Using this assay, we recently found that metformin selectively ablates pancreatic CSCs; a finding that was subsequently further corroborated by demonstrating diminished expression of pluripotency-associated genes/surface markers and reduced in vivo tumorigenicity of metformin-treated cells. As the final step for preclinical development we treated mice bearing established tumors with metformin and found significantly prolonged survival. Clinical studies testing the use of metformin in patients with PDAC are currently underway (e.g., NCT01210911, NCT01167738, and NCT01488552). Mechanistically, we found that metformin induces a fatal energy crisis in CSCs by enhancing reactive oxygen species (ROS) production and reducing mitochondrial transmembrane potential. In contrast, non-CSCs were not eliminated by metformin treatment, but rather underwent reversible cell cycle arrest. Therefore, our study serves as a successful example for the potential of in vitro sphere formation as a screening tool to identify compounds that potentially target CSCs, but this technique will require further in vitro and in vivo validation to eliminate false discoveries.

Pancreatic cancer stem cells (CSCs) can be expanded in vitro using the anchorage-independent sphere culture technique, which represents a powerful tool to study CSC biology and can serve as the first step to develop novel CSC-targeting therapies. Here the methodology for expanding, analyzing and targeting of pancreatic CSCs is provided.

Pancreatic ductal adenocarcinoma (PDAC) contains a subset of exclusively tumorigenic cancer stem cells (CSCs) which have been shown to drive tumor ...

Generation of Prostate Cancer Patient Derived Xenograft Models from Circulating Tumor Cells

Patient derived xenograft (PDX) models are gaining popularity in cancer research and are used for preclinical drug evaluation, biomarker identification, biologic studies, and personalized medicine strategies. Circulating tumor cells (CTC) play a critical role in tumor metastasis and have been isolated from patients with several tumor types. Recently, CTCs have been used to generate PDX experimental models of breast and prostate cancer. This manuscript details the method for the generation of prostate cancer PDX models from CTCs developed by our group. Advantages of this method over conventional PDX models include independence from surgical sample collection and generating experimental models at various disease stages. Density gradient centrifugation followed by red blood cell lysis and flow cytometry depletion of CD45 positive mononuclear cells is used to enrich CTCs from peripheral blood samples collected from patients with metastatic disease. The CTCs are then injected into immunocompromised mice; subsequently generated xenografts can be used for functional studies or harvested for molecular characterization. The primary limitation of this method is the negative selection method used for CTC enrichment. Despite this limitation, the generation of PDX models from CTCs provides a novel experimental model to be applied to prostate cancer research.

This manuscript details a method used to generate prostate cancer patient derived xenografts (PDXs) from circulating tumor cells (CTCs). The generation of PDX models from CTCs provides an alternative experimental model to study prostate cancer; the most commonly diagnosed tumor and a frequent cause of death from cancer in men.

Patient derived xenograft (PDX) models are gaining popularity in cancer research and are used for preclinical drug evaluation, biomarker identification, ...

Working with Human Tissues for Translational Cancer Research

Medical research for human benefit is greatly impeded by the necessity for human tissues and subjects. However, upon obtaining consent for human specimens, precious samples must be handled with the greatest care in order to ensure integrity of organs, tissues, and cells to the highest degree. Unfortunately, tissue processing by definition requires extraction of tissues from the host, a change which can cause great cellular stress and have major repercussions on subsequent analyses. These stresses could result in the specimen being no longer representative of the site from which it was retrieved. Therefore, a strict protocol must be adhered to while processing these specimens to ensure representativeness. The desired assay(s) must also be taken into consideration in order to ensure that an optimal technique is used for sample processing. Outlined here is a protocol for tissue retrieval, processing and various analyses which may be performed on processed tissue in order to maximize downstream production from limited tissue samples.

Translational cancer research is dependent on extraction of human tissues. Much work has gone into optimizing extraction methods for ex vivo analysis. Here, we describe tissue processing methods allowing for maximal data output from limited samples.

Medical research for human benefit is greatly impeded by the necessity for human tissues and subjects. However, upon obtaining consent for human ...

Exosomal miRNA Analysis in Non-small Cell Lung Cancer (NSCLC) Patients' Plasma Through qPCR: A Feasible Liquid Biopsy Tool

The discovery of alterations in the EGFR and ALK genes, amongst others, in NSCLC has driven the development of targeted-drug therapy using selective tyrosine kinase inhibitors (TKIs). To optimize the use of these TKIs, the discovery of new biomarkers for early detection and disease progression is mandatory. These plasma-isolated exosomes can be used as a non-invasive and repeatable way for the detection and follow-up of these biomarkers. One ml of plasma from 12 NSCLC patients, with different mutations and treatments (and 6 healthy donors as controls), were used as exosome sources. After RNAse treatment, in order to degrade circulating miRNAs, the exosomes were isolated with a commercial kit and resuspended in specific buffers for further analysis. The exosomes were characterized by western blotting for ALIX and TSG101 and by transmission electron microscopy (TEM) analysis, the standard techniques to obtain biochemical and dimensional data of these nanovesicles. Total RNA extraction was performed with a high yield commercial kit. Due to the limited miRNA-content in exosomes, we decided to perform retro-transcription PCR using an individual assay for each selected miRNA. A panel of miRNAs (30b, 30c, 103, 122, 195, 203, 221, 222), all correlated with NSCLC disease, were analyzed taking advantage of the remarkable sensitivity and specificity of Real-Time PCR analysis; mir-1228-3p was used as endogenous control and data were processed according to the formula 2-&#916;&#916;ct 13. Control values were used as baseline and results are shown in logarithmic scale.

Exosomal miRNA Analysis in Non-small Cell Lung Cancer NSCLC Patients' Plasma Through qPCR: A Feasible Liquid Biopsy Tool

This protocol describes the feasibility to perform miRNA profiling in exosomes, released in plasma of NSCLC patients, through a commercial exosome isolation kit with Proteinase K and RNAse treatments, in order to avoid circulating miRNAs contamination and evaluate their biomarker features in NSCLC.

The discovery of alterations in the EGFR and ALK genes, amongst others, in NSCLC has driven the development of targeted-drug therapy using selective ...