Name: sequencing small non-coding rna from formalin-fixed tissues and serum-derived exosomes from castration-resistant prostate cancer patients
Uploaded: 2019-11-19T02:00:00
Description: Watch this Scientific Journal Video about Sequencing Small Non-coding RNA from Formalin-fixed Tissues and Serum-derived Exosomes from Castration-resistant Prostate Cancer Patients at JoVE.com

This work is supported by the US Army Medical Research Acquisition Activity (USAMRAA) through the Idea Development Award underAward No. W81XWH-18-1-303 and W81XWH-18-2-0013 and additionally by Award no. W81XWH-18-2-0015, W81XWH-18-2-0016, W81XWH-18-2-0017, W81XWH-18-2-0018, and W81XWH-18-2-0019 Prostate Cancer Biorepository Network (PCBN). Funding support to authors' lab by the National Cancer Institute at the National Institutes of Health (Grant Number RO1CA177984) is also acknowledged. Rajvir Dahiya is a Senior Research Career Scientist at the Department of Veterans Affairs, BX004473 and funded by NIH-UO1CA199694 (RD). Opinions, interpretations, conclusions, and recommendations are those of the author and are not necessarily endorsed by the Department of Defense or U.S. Army. We are thankful to Judy Shigenaga, director of core facility at San Francisco VAMC, for her assistance with the NextSeq 500 sequencer.

This study was conducted in accordance with the ethical guidelines of US Common Rule and was approved by the Institutional Committee on Human Research.
1. Microdissection
NOTE: FFPE metastatic CRPC tissues with adenocarcinoma features (CRPC-Adeno) or NE differentiation (CRPC-NE) were obtained from the Prostate Cancer Biorepository Network (PCBN). Ten-micron PCa sections on glass slides were prepared for manual microdissection as discussed previously<s...

<ol>
	<li>Heinlein, C. A., Chang, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Androgen+receptor+in+prostate+cancer.">Androgen receptor in prostate cancer.</a> Endocrine Reviews. 25 (2), 276-308 (2004).</li><li>Tilki, D., Schaeffer, E. M., Evans, C. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Understanding+Mechanisms+of+Resistance+in+Metastatic+Castration-resistant+Prostate+Cancer:+The+Role+of+the+Androgen+Receptor.">Understanding Mechanisms of Resistance in Metastatic Castration-resistant Prostate Cancer: The Role of the Androgen Receptor.</a> European Urology Focus. 2 (5), 499-505 (2016).</li><li>Vlachostergios, P. J., Puca, L., Beltran, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Emerging+Variants+of+Castration-Resistant+Prostate+Cancer.">Emerging Variants of Castration-Resistant Prostate Cancer.</a> Current Oncology Reports. 19 (5), 32 (2017).</li><li>Aggarwal, R., Zhang, T., Small, E. J., Armstrong, A. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neuroendocrine+prostate+cancer:+subtypes,+biology,+and+clinical+outcomes.">Neuroendocrine prostate cancer: subtypes, biology, and clinical outcomes.</a> Journal of the National Comprehensive Cancer Network. 12 (5), 719-726 (2014).</li><li>Beltran, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Divergent+clonal+evolution+of+castration-resistant+neuroendocrine+prostate+cancer.">Divergent clonal evolution of castration-resistant neuroendocrine prostate cancer.</a> Nature Medicine. 22 (3), 298-305 (2016).</li><li>Calin, G. A., Croce, C. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MicroRNA+signatures+in+human+cancers.">MicroRNA signatures in human cancers.</a> Nature Reviews Cancer. 6 (11), 857-866 (2006).</li><li>Coppola, V., De Maria, R., Bonci, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MicroRNAs+and+prostate+cancer.">MicroRNAs and prostate cancer.</a> Endocrine-Related Cancer. 17 (1), 1-17 (2010).</li><li>Ambs, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genomic+profiling+of+microRNA+and+messenger+RNA+reveals+deregulated+microRNA+expression+in+prostate+cancer.">Genomic profiling of microRNA and messenger RNA reveals deregulated microRNA expression in prostate cancer.</a> Cancer Research. 68 (15), 6162-6170 (2008).</li><li>Lu, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MicroRNA+expression+profiles+classify+human+cancers.">MicroRNA expression profiles classify human cancers.</a> Nature. 435 (7043), 834-838 (2005).</li><li>Bhagirath, D., Yang, T. L., Dahiya, R., Saini, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MicroRNAs+as+Regulators+of+Prostate+Cancer+Metastasis.">MicroRNAs as Regulators of Prostate Cancer Metastasis.</a> Advances in Experimental Medicine and Biology. 1095, 83-100 (2018).</li><li>Hoshino, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tumour+exosome+integrins+determine+organotropic+metastasis.">Tumour exosome integrins determine organotropic metastasis.</a> Nature. 527 (7578), 329-335 (2015).</li><li>Colombo, M., Raposo, G., Thery, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biogenesis,+secretion,+and+intercellular+interactions+of+exosomes+and+other+extracellular+vesicles.">Biogenesis, secretion, and intercellular interactions of exosomes and other extracellular vesicles.</a> Annual Review of Cell and Developmental Biology. 30, 255-289 (2014).</li><li>Bhagirath, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=microRNA-1246+Is+an+Exosomal+Biomarker+for+Aggressive+Prostate+Cancer.">microRNA-1246 Is an Exosomal Biomarker for Aggressive Prostate Cancer.</a> Cancer Research. 78 (7), 1833-1844 (2018).</li><li>Witte, J. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Prostate+cancer+genomics:+towards+a+new+understanding.">Prostate cancer genomics: towards a new understanding.</a> Nature Reviews Genetics. 10 (2), 77-82 (2009).</li><li>Kim, J. H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Deep+sequencing+reveals+distinct+patterns+of+DNA+methylation+in+prostate+cancer.">Deep sequencing reveals distinct patterns of DNA methylation in prostate cancer.</a> Genome Research. 21 (7), 1028-1041 (2011).</li><li>Robinson, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Integrative+clinical+genomics+of+advanced+prostate+cancer.">Integrative clinical genomics of advanced prostate cancer.</a> Cell. 161 (5), 1215-1228 (2015).</li><li>Kim, J., Yu, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Interrogating+genomic+and+epigenomic+data+to+understand+prostate+cancer.">Interrogating genomic and epigenomic data to understand prostate cancer.</a> Biochimica Et Biophysica Acta. 1825 (2), 186-196 (2012).</li><li>Bucay, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=miRNA+Expression+Analyses+in+Prostate+Cancer+Clinical+Tissues.">miRNA Expression Analyses in Prostate Cancer Clinical Tissues.</a> Journal of Visualized Experiments. (103), e53123 (2015).</li><li>Geiss, G. K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Direct+multiplexed+measurement+of+gene+expression+with+color-coded+probe+pairs.">Direct multiplexed measurement of gene expression with color-coded probe pairs.</a> Nature Biotechnology. 26 (3), 317-325 (2008).</li><li>Tam, S., de Borja, R., Tsao, M. S., McPherson, J. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Robust+global+microRNA+expression+profiling+using+next-generation+sequencing+technologies.">Robust global microRNA expression profiling using next-generation sequencing technologies.</a> Laboratory Investigation. 94 (3), 350-358 (2014).</li><li>Rodriguez, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identification+of+noninvasive+miRNAs+biomarkers+for+prostate+cancer+by+deep+sequencing+analysis+of+urinary+exosomes.">Identification of noninvasive miRNAs biomarkers for prostate cancer by deep sequencing analysis of urinary exosomes.</a> Molecular Cancer. 16 (1), 156 (2017).</li><li>Guelfi, G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Next+Generation+Sequencing+of+urine+exfoliated+cells:+an+approach+of+prostate+cancer+microRNAs+research.">Next Generation Sequencing of urine exfoliated cells: an approach of prostate cancer microRNAs research.</a> Scientific Reports. 8 (1), 7111 (2018).</li><li>Daniel, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Panel+of+MicroRNAs+as+Diagnostic+Biomarkers+for+the+Identification+of+Prostate+Cancer.">A Panel of MicroRNAs as Diagnostic Biomarkers for the Identification of Prostate Cancer.</a> International Journal of Molecular Sciences. 18 (6), 1281 (2017).</li><li>Xuan, J., Yu, Y., Qing, T., Guo, L., Shi, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Next-generation+sequencing+in+the+clinic:+promises+and+challenges.">Next-generation sequencing in the clinic: promises and challenges.</a> Cancer Letters. 340 (2), 284-295 (2013).</li></ol>

In this article, we describe a protocol to isolate RNA from FFPE tissues and serum-derived EVs using kits that were optimized to increase the yield and quality of isolated RNAs. Further, the purified RNAs were used to generate cDNA libraries for small RNA sequencing. Both of the listed steps are essential in determining the quality and depth of the sequencing reads that are the final result from the run24. Therefore, optimizing these crucial steps is critical to a successful sequencing run.
<p...

Prostate cancer is driven by androgens acting via AR signaling. Therefore, targeting the AR pathway is the mainstay treatment for the disease1. However, resistance often ensues as a result of targeted therapies and the disease progresses to an advanced metastatic CRPC2. CRPC is treated by second generation of AR therapy that includes enzalutamide and abiraterone2,3 which improves survival initially. However, lethal variants such as NEPC often emerge in 25&#8722;30% of treated CRPC cases that have limited treatment options, leading to increased mortality3. NEPC arises via a reversible transdifferentiation process known as NED, wherein PCa cells undergo a lineage switch from adenocarcinomas and show decreased expression of AR and increased expression of NE lineage markers including enolase 2 (ENO2), chromogranin A (CHGA), and synaptophysin (SYP)4. Given that these resistance variants arise as a result of therapeutic interventions, it is essential to decipher pathways that lead to generation of this deadly, hard to treat form of PCa.
The genomics of NEPC was recently deciphered in an exhaustive study done by Beltran et al. whereby copy number alterations, mutations, single nucleotide polymorphisms (SNPs), and DNA methylation from patient-derived metastatic tissues were analyzed5. Despite significant advancement in the understanding of the genomics of this aggressive form of PCa, little is known about the epigenetic factors, including the small non-coding RNAs (microRNAs) that are involved in the transition of CRPC-adenocarcinoma to NEPC. MicroRNAs (miRNAs) are 22 bp long, double-stranded RNAs that act primarily by suppressing gene expression post-transcriptionally by sequence-specific interactions with the 3'-untranslated regions (UTRs) of cognate mRNA targets6. Several oncomiRs and tumor suppressors have now been identified, and their role in regulating disease onset and metastasis has been well studied in different cancers6,7. These small non-coding RNAs often serve as very important targets in controlling disease mortality6,8,9. More recent research has been focused on understanding the paracrine effects of miRNAs in cancer metastasis via their transport in EVs, such as exosomes, that flow in the bloodstream and allow tumor cells to send these secondary messengers to metastatic locations in a nuclease-free environment10,11,12. EVs carry miRNAs from the tumor cells to transfer the transforming effects from the host cells12. Identification of EVs as secondary messengers of tumor cells can therefore be useful in noninvasive detection of disease severity.
The miR-1246 is highly upregulated in EVs from aggressive PCa, and it indicates the disease severity13. These EV-associated miRNAs not only serve as noninvasive biomarkers of the disease, but also play functionally important roles in driving tumorigenesis. Thus, it essential to understand the significance of the miRNA repertoire that is associated with resistant forms of PCa to allow better identification of noninvasive biomarkers as well as their functional significance.
The advent of next generation sequencing has offered the most comprehensive platform to study the details of tumor landscape involving alterations in the genome such as mutations, chromosomal relocations, chromothripsis, and methylation, all of which contribute significantly to the form and nature of cancer14,15,16. Likewise, it is also an essential tool to understand the vast epigenomic changes that occur in a tumor cell and that are often important players in disease severity17. With the aim of understanding the miRNA repertoire associated with the generation of NEPC, small RNA sequencing was performed on FFPE metastatic CRPC tissues and their corresponding serum-derived EVs. RNA derived from either of these two sample sources is (1) low in yield and (2) of bad quality due to the degradation that often happens due to formalin fixation and EV isolation. Furthermore, generating cDNA libraries is a critical, but cumbersome, step of a sequencing run. Thus, methods for isolating these RNAs and using them to generate libraries for small RNA sequencing require optimization to generate accurate and reliable data.
There are several methods to profile miRNA expression in different samples, including RT-PCR, microarrays, and in-situ hybridization (ISH). A protocol using FFPE tissue-derived RNA to evaluate miRNA expression by RT-PCR and ISH was recently published18. More recent technologies offer more exhaustive and comprehensive platforms for profiling miRNA expression in a sample. NanoString nCounter offers a sensitive miRNA detection platform19, but the detection is often limited by the number of miRNAs that are available in the array (~2,000). In such a scenario, a more sensitive and exhaustive platform such as next generation sequencing offers much wider depth of miRNA identification and simultaneous profiling in different samples20. The method has been used to determine the miRNA signatures in urine or plasma from PCa patients21,22,23. In the current article, a protocol is presented to use a next generation sequencing platform to study miRNA profiles associated with aggressive CRPC using FFPE tissues and serum-derived EV RNAs.

<table>
	<tbody>
		<tr>
			<td>3M NaOAc pH 5.5</td>
			<td>USB Corp.</td>
			<td>75897 100 mL</td>
			<td></td>
		</tr>
		<tr>
			<td>5 &#181;m filter tubes</td>
			<td>IST Engineering Inc.</td>
			<td>5388-50</td>
			<td></td>
		</tr>
		<tr>
			<td>6% TBE polyacrylamide gels</td>
			<td>Novex</td>
			<td>EC6265BOX</td>
			<td></td>
		</tr>
		<tr>
			<td>BaseSpace</td>
			<td>Illumina</td>
			<td></td>
			<td>Analysis software</td>
		</tr>
		<tr>
			<td>Bio-analyzer</td>
			<td>Agilent</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>DNA loading dye</td>
			<td>Novex</td>
			<td>LC6678</td>
			<td></td>
		</tr>
		<tr>
			<td>Eppendorf Thermostat plus</td>
			<td>Eppendorf 1.5 mL</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>EtBr</td>
			<td>Pierce</td>
			<td>17898</td>
			<td></td>
		</tr>
		<tr>
			<td>Ethyl alcohol 200 proof</td>
			<td>Pharmco</td>
			<td>111000200</td>
			<td></td>
		</tr>
		<tr>
			<td>Exosomal RNA isolation kit</td>
			<td>Norgen</td>
			<td>58000</td>
			<td></td>
		</tr>
		<tr>
			<td>Gel breaking tubes</td>
			<td>IST Engineering Inc.</td>
			<td>3388-100</td>
			<td></td>
		</tr>
		<tr>
			<td>Glycogen molecular biology grade</td>
			<td>Thermo Scientifc</td>
			<td>R0561</td>
			<td></td>
		</tr>
		<tr>
			<td>Hematoxylin Select</td>
			<td>Stat lab</td>
			<td>SL401</td>
			<td></td>
		</tr>
		<tr>
			<td>Microcentrifuge</td>
			<td>Fisher Scientific</td>
			<td>13-100-676</td>
			<td>accuSpin Micro 17R</td>
		</tr>
		<tr>
			<td>miRNeasy FFPE kit</td>
			<td>Qiagen</td>
			<td>217504</td>
			<td></td>
		</tr>
		<tr>
			<td>Nanodrop</td>
			<td>Thermo Scientifc</td>
			<td>Nano Drop 1000</td>
			<td></td>
		</tr>
		<tr>
			<td>Nanosight NTA</td>
			<td>Malvern</td>
			<td>LM14</td>
			<td></td>
		</tr>
		<tr>
			<td>NextSeq 500 Sequencer</td>
			<td>Illumina</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>NextSeq 500/550 Mid Output Kit v2 (150 cycles)</td>
			<td>Illumina</td>
			<td>FC-404-2001</td>
			<td></td>
		</tr>
		<tr>
			<td>Pellet paint</td>
			<td>Millipore</td>
			<td>70748-3</td>
			<td></td>
		</tr>
		<tr>
			<td>Superscript II Reverse Transcriptase</td>
			<td>Invitogen</td>
			<td>18064014</td>
			<td></td>
		</tr>
		<tr>
			<td>T4 RNA Ligase 2 Deletion Mutant</td>
			<td>Lucigen</td>
			<td>LR2D11310K</td>
			<td></td>
		</tr>
		<tr>
			<td>TBE Running buffer (5X)</td>
			<td>Novex</td>
			<td>LC6675</td>
			<td></td>
		</tr>
		<tr>
			<td>Thermal cycler</td>
			<td>MJ Research</td>
			<td>PTC100</td>
			<td></td>
		</tr>
		<tr>
			<td>Total exosome isolation reagent (from serum)</td>
			<td>Invitrogen</td>
			<td>4478360</td>
			<td></td>
		</tr>
		<tr>
			<td>TrueSeq small RNA library Prep kit-Set A (Indexes 1-12)</td>
			<td>Illumina</td>
			<td>RS-200-0012</td>
			<td></td>
		</tr>
		<tr>
			<td>Xylene</td>
			<td>Fisher Scientific</td>
			<td>X3P- 1GAL</td>
			<td></td>
		</tr>
		<tr>
			<td>RNA 3&#39; Primer</td>
			<td></td>
			<td></td>
			<td>GUUCAGAGUUCUACAGUCCGACGAUC</td>
		</tr>
		<tr>
			<td>RNA 5&#39; Primer</td>
			<td></td>
			<td></td>
			<td>TGGAATTCTCGGGTGCCAAGG</td>
		</tr>
		<tr>
			<td>Stop Oligo</td>
			<td></td>
			<td></td>
			<td>GAAUUCCACCACGUUCCCGUGG</td>
		</tr>
		<tr>
			<td>RNA RT Primer</td>
			<td></td>
			<td></td>
			<td>GCCTTGGCACCCGAGAATTCCA</td>
		</tr>
		<tr>
			<td>RNA PCR Primer</td>
			<td></td>
			<td></td>
			<td>AATGATACGGCGACCACCGAGATCTACACGTTCAGAGTTCTACAGTCCGA</td>
		</tr>
		<tr>
			<td>RNA PCR Index Primer</td>
			<td></td>
			<td></td>
			<td>CAAGCAGAAGACGGCATACGAGAT[6 bases]GTGACTGGAGTTCCTTGGCACCCGAGAATTCCA</td>
		</tr>
		<tr>
			<td>-</td>
			<td>-</td>
			<td>-</td>
			<td>6 bases in adapter</td>
		</tr>
		<tr>
			<td>RNA PCR Index Primer 1</td>
			<td></td>
			<td></td>
			<td>CGTGAT</td>
		</tr>
		<tr>
			<td>RNA PCR Index Primer 2</td>
			<td></td>
			<td></td>
			<td>ACATCG</td>
		</tr>
		<tr>
			<td>RNA PCR Index Primer 3</td>
			<td></td>
			<td></td>
			<td>GCCTAA</td>
		</tr>
		<tr>
			<td>RNA PCR Index Primer 4</td>
			<td></td>
			<td></td>
			<td>TGGTCA</td>
		</tr>
		<tr>
			<td>RNA PCR Index Primer 5</td>
			<td></td>
			<td></td>
			<td>CACTGT</td>
		</tr>
		<tr>
			<td>RNA PCR Index Primer 6</td>
			<td></td>
			<td></td>
			<td>ATTGGC</td>
		</tr>
		<tr>
			<td>RNA PCR Index Primer 7</td>
			<td></td>
			<td></td>
			<td>GATCTG</td>
		</tr>
		<tr>
			<td>RNA PCR Index Primer 8</td>
			<td></td>
			<td></td>
			<td>TCAAGT</td>
		</tr>
		<tr>
			<td>RNA PCR Index Primer 9</td>
			<td></td>
			<td></td>
			<td>CTGATC</td>
		</tr>
		<tr>
			<td>RNA PCR Index Primer 10</td>
			<td></td>
			<td></td>
			<td>AAGCTA</td>
		</tr>
		<tr>
			<td>RNA PCR Index Primer 11</td>
			<td></td>
			<td></td>
			<td>GTAGCC</td>
		</tr>
		<tr>
			<td>RNA PCR Index Primer 12</td>
			<td></td>
			<td></td>
			<td>TACAAG</td>
		</tr>
	</tbody>
</table>

sequencing small non-coding rna from formalin-fixed tissues and serum-derived exosomes from castration-resistant prostate cancer patients

Ablation of androgen receptor (AR) signaling by androgen deprivation is the goal of the first line of therapy for prostate cancer that initially results in cancer regression. However, in a significant number of cases, the disease progresses to advanced, castration-resistant prostate cancer (CRPC), which has limited therapeutic options and is often aggressive. Distant metastasis is mostly observed at this stage of the aggressive disease. CRPC is treated by a second generation of AR pathway inhibitors that improve survival initially, followed by the emergence of therapy resistance. Neuroendocrine prostate cancer (NEPC) is a rare variant of prostate cancer (PCa) that often develops as a result of therapy resistance via a transdifferentiation process known as neuroendocrine differentiation (NED), wherein PCa cells undergo a lineage switch from adenocarcinomas and show increased expression of neuroendocrine (NE) lineage markers. In addition to the genomic alterations that drive the progression and transdifferentiation to NEPC, epigenetic factors and microenvironmental cues are considered essential players in driving disease progression. This manuscript provides a detailed protocol to identify the epigenetic drivers (i.e., small non-coding RNAs) that are associated with advanced PCa. Using purified microRNAs from formalin-fixed paraffin-embedded (FFPE) metastatic tissues and corresponding serum-derived extracellular vesicles (EVs), the protocol describes how to prepare libraries with appropriate quality control for sequencing microRNAs from these sample sources. Isolating RNA from both FFPE and EVs is often challenging because most of it is either degraded or is limited in quantity. This protocol will elaborate on different methods to optimize the RNA inputs and cDNA libraries to yield most specific reads and high-quality data upon sequencing.

The library was prepared after RNA isolation and a quality check was performed. Gel purification for the amplified cDNA library prepared from RNA isolated from microdissected tissues and serum-derived EVs is shown in Figure 1 and Figure 2. The product size for adaptor-ligated miRNAs corresponded to about 136&#8722;160 bp for each sample. Figure 1A-B are marked to show the range of the gel that should be precisely ex...

Watch this Scientific Journal Video about Sequencing Small Non-coding RNA from Formalin-fixed Tissues and Serum-derived Exosomes from Castration-resistant Prostate Cancer Patients at JoVE.com

Sequencing Small Non-coding RNA from Formalin-fixed Tissues and Serum-derived Exosomes from Castration-resistant Prostate Cancer Patients

Therapy resistance often develops in patients with advanced prostate cancer, and in some cases, cancer progresses to a lethal subtype called neuroendocrine prostate cancer. Assessing the small non-coding RNA-mediated molecular changes that facilitate this transition would allow better disease stratification and identification of causal mechanisms that lead to development of neuroendocrine prostate cancer.

Ablation of androgen receptor (AR) signaling by androgen deprivation is the goal of the first line of therapy for prostate cancer that initially results ...

With the use of this protocol researchers can identify novel exome or extracellular vesicle based and tissue based micro cellular for advanced prostate cancer. Isolating RNA from both F-F-B tissues and extracellular vesicles is often challenging as most of it is either de created or is in limited quantity This particle will elaborate on different methods to optimize the R-N-A inputs and C-D-N-A libraries to gene most specific free and high quality data for next generation sequencing. Next gen sequencing offers the most comprehensive platform for understanding molecule alteration in tumor that underlie tumor progression this particle is optimized with prostate cancer clinical sample, and can provide novel insights into the underlying biology of advanced aggressive prostate cancer.Optimizing the C-D-N-A libraries from low input material is a crucial step for a successful sequencing run it is therefore very important to generate high quality C-D-N-A libraries to get accurate results. After performing micro dissection of tissues as previously done proceed to isolating serum derived E-V's Thaw rows of patient serum samples at four degrees celsius. Transfer 110 micro liters of thawed serum sample to a tube and spin at two thousand times G for thirty minutes.Elect the super naden for subsequent E-V or exosome isolation and discard the debree pellet. At 30 microleters of serum exosome isolation reagent to the super natent. An incubate it four degree celsius for thirty minutes.Spin at ten thousand times G for ten minutes. Elect the E-V super nadent carefully without disturbing the pellet in a separate 1.5 milliliter tube and store minus 80 degree Celsius for future analysis. Then re suspend the E-V pellet in 70 micro liters of P-B-S prepared in nuclease free water.After isolating total R-N-A from micro dissected tissues, and purified E-V's using commercial kits perform Library Preparation into five micro liters of a normalized forty nanogram per micro liter R-N-A sample at one micro liter of three prime adapter. Pre-heat the thermal cycler to 70 degree celsius and incubate the sample for two minutes. Immediately transfer the samples on ice.In a separate tube mix two micro liters of ligation buffer, one micro liter of RNase inhibitor and one micro liter of T4 RNA ligase two, a deletion mutant. Mix bye pie bedding up and down. Then add four micro liters of the mix to the tube with the R-N-A 3 prime adapter on ice.Preheat the thermal cycler to 28 degree Celsius. And place the tube in the thermal cycler to incubate for one hour. After that, add one micro liter of stop solution into the tube while keeping the sample on the thermal cycler.Incubate at 28 degrees Celsius for another 15 minutes. Then immediately remove the tube and keep on ice. In a separate tube add one microliter of five prime adapter.Transfer to a thermal cycler that's been preheated to 70 degrees Celsius. And incubate for two minutes. Immediately place the tube on ice to prevent reannealing of the adapters.Add one micro liter of ten millimole A-T-P to the tube of D natured five prime adapter. Mix bye pie pedding and add one micro liter of T4 R-N-A ligase to the mix. Mix bye pie pedding.Transfer three microliters of this mix to the tube containing the three prime adapter ligated R-N-A. Place the tube on the thermal cycler that has been pre heated to 28 degrees celsius and incubate for one hour. After that immediately transfer the tube onto ice and either proceed further with the samples or store at minus 80 degrees Celsius for future use.To perform R-T-P-C-R, use six micro ligers of each adapter ligated R-N-A and add one micro liger of R-N-A R-T primer to it. Transfer the tube to the thermal cycler preheated to 70 degrees Celsius and incubate for two minutes. Transfer the tube to ice.In a separate tube mix two micro liters of 5X, strand buffer, 5 micro liters of 12.5 milimoler DNTP's, one micro liter of 100 milimolar DTT, one micro liter of R-N-A's inhibitor, and one micro liter of reverse transcriptase. Add five microliters of this mix to the adapter ligated RNA and transfer it to the thermal cycler that has been preheated to 50 degrees Celsius to incubate for one hour. After one hour transfer the adapter ligated complimentary DNA immediately to ice.In a separate tube, mix 25 microliters of PCR mix, two micro liters of RNA PCR primer, two micro liters of RNA PCR primer index, and 8.5 microliters of RNA's free water. Add 37.5 microliters of this mix to 12.5 microliters of the adapter ligated CDNA. Transfer the tube to the thermal cycler that has been preheated to 98 degrees celsius.Program the thermal cycler as suggested in the manufacturer's protocol with the cycle number modified to 15. After completion, keep the sample at four degree celsius. Proceed or store at minus 80 degree celsius for future use.To purify the ligated complimentary DNA, add ten microliters of the DNA loading dye to each complimentary DNA sample. And to ten microliters of the high resolution latter and custom RNA latter. Run 30 microliters of each sample in two separate lanes adjacent to each other in the six percent TBE Polyacrylamide gel.With custom RNA latter and high resolution latter, the intermediate space between the two different samples. Run the gel in one X TBE buffer at 145 volts for approximately 30 to 40 minutes. Keep track of the lower blue front of the loading dye.Stop the electrophoresis when it approaches the bottom of the gel. Transfer the gel in one X TBE buffer with 5 microgram per millimeter ethidium bromide. Visualize the gel in a transilluminator and cut the gel precisely between the 145 base pair and 160 base pair markers and slightly above the 145 base pair marker to avoid contamination with adapter dimer.A critical step is purification ligated CDNA that is done by cutting the gel precisely as adapter dimers run very lose to the desired brand. Transfer the gel pieces to DNA breaking tubes kept in two millimeter collecting tubes. Spin at 20 thousand times G for two minutes.And add three hundred micro liters of RNase-free water and allow it to rotate gently on a rocker overnight at room temperature. To perform the DNA precipitation on the following day transfer the contents of the tube to 5 micron filter tubes. Spin 600 times G for strictly ten seconds.Then add two microliters of glycogen thirty microliters of three molar sodium acetate, 1X pellet paint, and 975 microliters of 100 percent ethanol to eluted DNA. Spin at 17, 000 times G at 4 degrees Celsius for 20 minutes. Discard the supernatant and add 75 percent ethanol to wash the pellet.After spinning at 17 thousand times G at four degrees celsius for five minutes discard the supernatant and incubate the tubes at 37 degrees celsius on a thermal block completely evaporate the ethanol. Re suspend the pellet with 12 microliters of 10 millimolar tricider chloride at PH 8.5. Next perform a library quality check by diluting the purified and complimentary DNA ten times and using one microliter of the diluted CDNA to run on a bioanalyzer.Make sure the complimentary DNA product size corresponds to the range of the small RNA in the electropherogram between 136 and 160 base pairs. Calculate the total molarity for each sample. Normalize each sample to 2 nanomolar using the tris hydrochloride at PH 8.5.Hold the libraries by mixing equal volumes of each two nanomolar sample in a single two hundred microliter PCR tube. Denature and sequence following the steps as described in the manuscript. In this study the library was prepared after RNA isolation and a quality check was performed.The product size for adapter ligated micro Rnase corresponded to about 136 to 160 base pairs for each sample. The highlighted sections shows the range of the gel that was precisely excised for small RNA library of preparation. This figure shows the gel electrophoresis and electropherograms for the purified complimentary DNA library.Micro dissected FFPE tissue and serum derived EV's. The representative metrics from a small RNA sequencing run demonstrate the expected cluster density, Q score, cluster passing filter percentage, and the estimated yield and error rates for micro dissected FFP tissue and serum derived EV's. The Q score in both samples showed a value above three indicating 99.9 percent of base call accuracy.And the error rates were all below one. Each step in library preparation should be carefully executed and tubes should be immediately transferred to ice after each incubation. A critical step in the protocol is cutting the gel precisely to ensure you have an adapter dimer free and pure CDNA library.Generating CDNA library requires optimization for a high quality sequencing run. Understanding this protocol will help the viewers in extrapolating these minute details to other sequencing library prepration from limited source samples suggest serum and extracellular vesicles. This technique has helped us in identifying new micronase that are associated tumorate aggressiveness and therapy resistance in metastatic prostate cancer patients.These techniques can extrapolated to other disease types that can aid in Novel biomarker discovery. As this technique uses biological materials such as striation derived serum and tissue samples, one should take appropriate precautions. Further, ethidium bromide is a known carcinogen and should be very carefully handled by using this protocol.

Research

JoVE Journal

Cancer Research

Four-color Fluorescence Immunohistochemistry of T-cell Subpopulations in Archival Formalin-fixed, Paraffin-embedded Human Oropharyngeal Squamous Cell Carcinoma Samples

The four-color fluorescence immunohistochemistry (IHC) technique is a method to quantify cell populations of interest while taking into account their ...

A Bioluminescent and Fluorescent Orthotopic Syngeneic Murine Model of Androgen-dependent and Castration-resistant Prostate Cancer

Orthotopic tumor modeling is a valuable tool for pre-clinical prostate cancer research, as it has multiple advantages over both subcutaneous and ...

Using 22C3 Anti-PD-L1 Antibody Concentrate on Biopsy and Cytology Samples from Non-small Cell Lung Cancer Patients

Pembrolizumab monotherapy has been approved for the first- and second-line treatment of patients with PD-L1-expressing advanced non-small cell lung cancer ...

Automated Multiplex Immunofluorescence Panel for Immuno-oncology Studies on Formalin-fixed Carcinoma Tissue Specimens

Continued developments in immuno-oncology require an increased understanding of the mechanisms of cancer immunology. The immunoprofiling analysis of ...

Capturing Small Molecule Communication Between Tissues and Cells Using Imaging Mass Spectrometry

Imaging mass spectrometry (IMS) has routinely been applied to three types of samples: tissue sections, spheroids, and microbial colonies. These sample ...

Semi-automatic PD-L1 Characterization and Enumeration of Circulating Tumor Cells from Non-small Cell Lung Cancer Patients by Immunofluorescence

Circulating tumor cells (CTCs) derived from the primary tumor are shed into the bloodstream or lymphatic system. These rare cells (1&#8722;10 cells per mL ...

Establishment and Analysis of Three-Dimensional (3D) Organoids Derived from Patient Prostate Cancer Bone Metastasis Specimens and their Xenografts

Establishment and Analysis of Three-Dimensional 3D Organoids Derived from Patient Prostate Cancer Bone Metastasis Specimens and their Xenografts

Three-dimensional (3D) culture of organoids from tumor specimens of human patients and patient-derived xenograft (PDX) models of prostate cancer, referred ...

Preparation of Mitochondria from Ovarian Cancer Tissues and Control Ovarian Tissues for Quantitative Proteomics Analysis

Ovarian cancer is a common gynecologic cancer with high mortality but unclear molecular mechanism. Most ovarian cancers are diagnosed in the advanced ...

Automated Dissection Protocol for Tumor Enrichment in Low Tumor Content Tissues

Tumor enrichment in low tumor content tissues, those below 20% tumor content depending on the method, is required to generate quality data reproducibly ...

Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2

RNA sequencing (RNA-seq) is one of the most widely used technologies in transcriptomics as it can reveal the relationship between the genetic alteration ...