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>
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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 ...

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 ...