The authors thank the Radiation Biology Core Laboratory of Institute for Radiological Research, Chang Gung Memorial Hospital, for technical support. This study was supported by grants from Chang Gung Memorial hospital (CMRPD1J0321),&#160;Cheng Hsin General Hospital (CHGH 106-06), and Mackay Memorial Hospital (MMH-CT-10605 and MMH-106-61). Funding bodies did not have any influence in the design of the study and data collection, analysis and interpretation of data or in writing the manuscript.

1. Cell culture and tumorsphere formation
<ol>
	<li>Culture HT29 cells in a 10 cm dish containing Dulbecco&#8217;s modified eagle medium (DMEM) with 10% fetal bovine serum (FBS) and 1% penicillin-streptomycin antibiotic (P/S).</li>
	<li>Grow the cells in an incubator at 37 &#176;C with 5% CO2 and 95% humidity under aseptic conditions, until they reach 80% confluency.</li>
	<li>Trypsinize HT29 cells with 1 mL of 0.25% trypsin for 5 min at 37 &#176;C and consequently neutralize the trypsin by adding 2 mL of DM...

<ol>
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S., Huang, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Prevalence+and+risk+factors+of+colorectal+cancer+in+Asia.">Prevalence and risk factors of colorectal cancer in Asia.</a> Intestinal Research. 17 (3), 317-329 (2019).</li><li>Liu, Q., 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=Positive+expression+of+basic+transcription+factor+3+predicts+poor+survival+of+colorectal+cancer+patients:+possible+mechanisms+involved.">Positive expression of basic transcription factor 3 predicts poor survival of colorectal cancer patients: possible mechanisms involved.</a> Cell Death &amp; Disease. 10 (7), 509 (2019).</li><li>Slattery, M. 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Y., 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=Two+novel+SHP-1+agonists,+SC-43+and+SC-78,+are+more+potent+than+regorafenib+in+suppressing+the+in+vitro+stemness+of+human+colorectal+cancer+cells.">Two novel SHP-1 agonists, SC-43 and SC-78, are more potent than regorafenib in suppressing the in vitro stemness of human colorectal cancer cells.</a> Cell Death Discovery. 4, 25 (2018).</li><li>Cheng, C. 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The authors have no relevant financial disclosures.

In this study, cultured cancer stem-like tumorspheres were used as a model in analyzing RNAseq data with available bioinformatics. For a disease model, HT29-derived tumorspheres were used. Because the tumorspheres have drug resistance against tumor therapies, the established model can be used to investigate the detailed mechanisms of resistance by investigating differences in gene expression. Moreover, genomic technology using RNAseq with available bioinformatics provides rapid understanding of the study model so the gen...

Colorectal cancer (CRC) is a leading cause of death with high prevalence and mortality worldwide1,2. Due to gene mutations and amplifications, cancer cells grow without proliferative control, which contributes to cell survival3, anti-apoptosis4, and cancer stemness5,6,7. Within a tumor tissue, tumor heterogeneity allows tumor cells to adapt and survive during therapeutic treatments8. Cancer stem cells (CSCs), with a higher rate of self-renewal and pluripotency than differential cancer types, are principally responsible for tumor recurrence9,10 and metastatic CRC11. CSCs present more drug resistance12,13,14 and anti-apoptosis properties15,16, thus surviving tumor chemotherapies.
Here, in order to investigate the potential mechanism for stemness in the selected CRC stem cells, RNAseq was performed to screen differentially expressed genes in tumor spheroids. The cancer cells can form spheroids (also called tumorspheres) when grown in low adherence conditions and stimulated by growth factors added to the cultured medium, including EGF, bFGF, HGF, and IL6. Therefore, we selected CRC HT29 tumor cells that resist chemotherapies with an increase in phosphorylated STAT3 when treated with oxaliplatin and irinotecon17. In addition, HT29 expressed higher stemness markers when cultured in the described culture conditions. The HT29-derived CSC model expressed higher amounts of leucine-rich repeat-containing G-protein-coupled receptor 5 (LGR5)18, a specific marker of CRC stem cells19,20. Moreover, CD133, considered a general biomarker for cancer stem cells, is also highly expressed in the HT29 cell line21. This protocol&#39;s purpose is to discover groups of driver genes in the established cancer stem-like tumorspheres based on bioinformatics datasets as opposed to investigating individual oncogenes22. It investigates potential molecular mechanisms through RNAseq analysis followed by available bioinformatics analyses.
Next generation sequencing is a high-throughput, easily available, and reliable DNA sequencing method based on computational help, used to comprehensively screen driver genes for guiding tumor therapies23. The technology is also used for detecting gene expression from reverse transcription of an isolated RNA sample24. However, when screening with RNAseq, the most important genes to target with therapy may not have the highest expression differential between experimental and control samples. Therefore, some bioinformatics were developed for classifying and identifying genes based on current datasets such as KEGG25, GO26,27, or PANTHER28, including Ingenuity Pathway Analysis (IPA)29 and NetworkAnalyst30. This protocol shows the integration of RNAseq and NetworkAnalyst to quickly discover a group of genes in the selected HT29-derived spheroids compared to parental HT29 cells. Application of this method to other disease models is also suggested for discovering differences in important genes.
Compared to investigation of individual gene expression, a high-throughput technique provides advantages to find potential driver genes easily for tumor precision medicine. With useful datasets such as KEGG, GO, or PANTHER, specific genes can be identified based on the disease models, signaling pathways, or specific functions, and this allows quickly focusing on specific, important genes, saving time and research costs. A similar application is used in previous studies14,18,31. Particularly, a tumor is more complicated because different types of tumors express distinguishing genes and pathways for survival and proliferation. Therefore, this protocol can pick up genes distinguishing different tumor types under different circumstances. There is the potential to find effective strategies against cancers by understanding the mechanism of specific gene expression.

<table>
	<tbody>
		<tr>
			<td>iRiS Digital Cell Imaging System</td>
			<td>Logos Biosystems, Inc</td>
			<td>I10999</td>
			<td>for observing the formation of tumorspheres</td>
		</tr>
		<tr>
			<td>Flow cytometry</td>
			<td>BD biosciences</td>
			<td>FACSCalibur</td>
			<td>for detecting the LGR5 and CD133 in the tumorspheres</td>
		</tr>
		<tr>
			<td>anti-LGR5-PE</td>
			<td>Biolegend</td>
			<td>373803</td>
			<td>LGR5 detection reagent</td>
		</tr>
		<tr>
			<td>anti-CD133-PE</td>
			<td>Biolegend</td>
			<td>372803</td>
			<td>CD133 detection reagent</td>
		</tr>
		<tr>
			<td>EGF</td>
			<td>GenScript</td>
			<td>Z00333</td>
			<td>for culture of tumorspheres</td>
		</tr>
		<tr>
			<td>bFGF</td>
			<td>GenScript</td>
			<td>Z03116</td>
			<td>for culture of tumorspheres</td>
		</tr>
		<tr>
			<td>HGF</td>
			<td>GenScript</td>
			<td>Z03229</td>
			<td>for culture of tumorspheres</td>
		</tr>
		<tr>
			<td>IL6</td>
			<td>GenScript</td>
			<td>Z03034</td>
			<td>for culture of tumorspheres</td>
		</tr>
		<tr>
			<td>PureLink RNA extraction kit</td>
			<td>Invitrogen</td>
			<td>12183025</td>
			<td>isolate total RNA for RNAseq analysis</td>
		</tr>
		<tr>
			<td>RNAseq performance</td>
			<td>Biotools, Taiwan</td>
			<td></td>
			<td>RNAseq analysis is done commerially by Biotools, Ttaiwan</td>
		</tr>
		<tr>
			<td>NetworkAnalyst</td>
			<td>Institute of Parasitology, McGill University, Montreal, Quebec, Canada</td>
			<td></td>
			<td>http://www.networkanalyst.ca/</td>
		</tr>
		<tr>
			<td>Prism</td>
			<td>GraphPad Software</td>
			<td></td>
			<td>a statistical analysis software</td>
		</tr>
	</tbody>
</table>

discovery of driver genes in colorectal ht29-derived cancer stem-like tumorspheres

Cancer stem cells play a vital role against clinical therapies, contributing to tumor relapse. There are many oncogenes involved in tumorigenesis and the initiation of cancer stemness properties. Since gene expression in the formation of colorectal cancer-derived tumorspheres is unclear, it takes time to discover the mechanisms working on one gene at a time. This study demonstrates a method to quickly discover the driver genes involved in the survival of the colorectal cancer stem-like cells in vitro. Colorectal HT29 cancer cells that express the LGR5 when cultured as spheroids and accompany an increase CD133 stemness markers were selected and used in this study. The protocol presented is used to perform RNAseq with available bioinformatics to quickly uncover the overexpressed driver genes in the formation of colorectal HT29-derived stem-like tumorspheres. The methodology can quickly screen and discover potential driver genes in other disease models.

To establish the model for investigating the mechanism in cancer stem cells, colorectal HT29 cells were used to culture the cancer stem-like tumorspheres in vitro in a low-attachment plate containing B27, EGF, bFGF, HGF, and IL6. The tumorspheres &#62;100 &#181;m in diameter were formed in 7 days (Figure 1A). The tumorspheres were trypsinized to single cells and analyzed using flow cytometry to detect LGR5 and CD133 expression. LGR5 increased in the HT29-drived tumorspheres from 1.1% to 11.4...

Watch this Scientific Journal Video about Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres at JoVE.com

Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres

Presented here is a protocol to discover the overexpressed driver genes maintaining the established cancer stem-like cells derived from colorectal HT29 cells. RNAseq with available bioinformatics was performed to investigate and screen gene expression networks for elucidating a potential mechanism involved in the survival of targeted tumor cells.

Cancer stem cells play a vital role against clinical therapies, contributing to tumor relapse. There are many oncogenes involved in tumorigenesis and the ...

Our protocol utilized RNA-Seq and bioinformatical tools to quickly uncover the overexpressed driver genes that contribute to the formation of stem-like colorectal tumorspheres. This protocol is used to screen a differentially expressed gene and signal pathways to investigate a molecular mechanism for cancer stemness in a selective colorectal cancers. On day seven of culture, use an inverted microscope with a digital cell imaging system to observe and measure the diameter of the tumorspheres.When the tumorspheres reach a greater than 100 micrometer diameter, treat the culture with 0.25%trypsin. After five minutes at 37 degrees Celsius, neutralize the trypsin with two times the volume of growth medium and count the cells using a hemocytometer. Collect the cells by centrifugation.And resuspend the pellet at a five times 10 to the four cells per 100 microliters of medium concentration. Add two microliters of the primary antibody of interest to each tube and incubate the cells for 30 minutes at room temperature and 200 revolutions per minute. At the end of the incubation, wash each tube with 900 microliters of PBS and analyze the cells for expression of the protein of interest by flow cytometry according to standard protocols.For RNA isolation after trypsin collection as just demonstrated, resuspend the cells at a two times 10 to the fifth cells per 50 microliters of PBS concentration and lyse each sample with 200 microliters of lysis buffer supplemented with two microliters of beta mercaptoethanol per tube. After brief vortexing and a five minute incubation at room temperature, collect the lysates by centrifugation and add 200 microliters of 70%ethanol to each tube. Transfer the samples into rapid columns and remove the solvent by centrifugation.Wash the samples with 400 microliters of wash solution one and 600 microliters of wash solution two to completely remove any non-RNA by centrifugation, followed by an additional two minutes centrifugation under the same centrifuge conditions to remove any residual ethanol. Then resuspend the pellets in 50 microliters of distilled water per tube and centrifuge the sample for one minute before collecting the RNA containing supernatants. To investigate the differential gene expression between tumorsphere cells compared to parental tumor cells after RNA sequencing analysis.Select genes with a greater than one to minus one log2 fold change with read counts greater than 100 in the tumorsphere and parental groups. And use the commands as indicated. To obtain a volcano plot of the data to determine the differential gene expression.For drive gene selection in network analyst, select single gene input and copy and paste the selected overexpressed genes with human specified as the organism and official gene symbol as the ID type. Click Upload and proceed. To insert and analyze the data using protein-protein interaction, following genetic protein-protein interaction, use the STRING interactome database with a confidence score cut off of 900 to show the seed genes.Cross-linking the uploaded genes. The seed genes associating with more individual genes can be selected as driver genes that may be involved in maintaining formation of the tumorsphere. Select Proceed in the mapping overview white in the Background and Force Atlas in the Layout knob.Then select PANTHER base pair to analyze the upregulation gene group. Tumorspheres of greater than 100 micrometers in diameter form within seven days of culture. Flow cytometric analysis reveals an increase in LGR5 and CD133 expression in HT29-derived tumorspheres compared to parental HT29 cells.After RNA sequencing, the genes with a greater than one log2 fold change in their up or downregulation with a P-value less than 0.05 as determined by heat map can be plotted to distinguish the significant genes between HT29-derived tumorspheres and parental HT29 cells. In this representative experiment, analysis of the upregulated genes with a greater than one log2 fold resulted in 10 seed genes, cross-linking the gene networks. PANTHER base pair analysis indicated that two genes were associated with negative regulation of apoptosis.Moreover, the selected genes were consequently validated by quantitative PCR confirming their increased expression in HT29-derived tumorspheres. The differential gene selection is the most important step of the procedures. Remember to use a log2 fold change greater than one with recounts greater than 100 as the criteria.Using this protocol, the genes selected from the colorectal-derived tumorspheres can be knocked down or overexpressed to uncover their potential roles in tumorsphere formation.

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JoVE Journal

Cancer Research

6.4K visualizações.  Chang Gung University, Chang Gung Memorial Hospital at Linkou. Nosso protocolo utilizou RNA-Seq e ferramentas bioinformaticas para descobrir rapidamente os genes de driver superexpressos que contribuem para a formação de tumores colorretais semelhantes a troncos. Este protocolo é usado para rastrear um gene expresso diferencialmente e caminhos de sinal para investigar um mecanismo molecular para a stemness do câncer em um câncer colorretal seletivo. No sétimo dia de cultura, use um microscópio invertido com um sistema de imagem celular digital par...