We are grateful for the guidance of Pavel Lobachevsky, PhD in establishing this protocol. We&#39;d also like to acknowledge Washington University&#39;s School of Medicine in St. Louis&#39;s Department of Obstetrics and Gynecology and Division of Gynecologic Oncology, Washington University&#39;s Dean&#39;s Scholar Program, Gynecologic Oncology Group Foundation, and the Reproductive Scientist Development Program for their support of this project.

Tumor tissue and ascites were obtained after obtaining patient consent as part of a gynecologic oncology biorepository that was approved by the Washington University in St. Louis Institutional Review Board (IRB). Patients were included if they had advanced stage high-grade serous ovarian cancer (HGSOC). All procedures were performed at room temperature on the bench unless otherwise specified. All reagents were prepared at room temperature (unless otherwise indicated) and stored at 4 &#176;C.
1. Organoid generation
<ol>
	<li>Generate the organoids following the previously published report20.</li>
</ol>
2. Plating and irradiation of organoids
<ol>
	<li>Using organoids in culture, dislodge the tabs of the organoids from the culture dish through manual manipulation of a pipette tip. Collect the organoids in a 15 mL conical tube.</li>
	<li>Centrifuge the conical tube at 1,650 x g for 5 min at 4 &#176;C. Using a pipette, aspirate off the supernatant carefully.</li>
	<li>Add 1,000 &#181;L of an animal origin-free, recombinant enzyme to the pellet (see Table of Materials). Mix the solution and incubate for 15 min at 37 &#176;C.</li>
	<li>Centrifuge the solution at 1,650 x g for 5 min at 4 &#176;C. Using a pipette, carefully aspirate off the supernatant.</li>
	<li>After centrifugation and aspiration, resuspend the pellet in 1,000 &#181;L of phosphate-buffered saline.</li>
	<li>Transfer 10 &#181;L of the solution to a 1.5 mL microcentrifuge tube and mix with 10 &#181;L of trypan blue.</li>
	<li>Take 10 &#181;L of the trypan blue cell solution into a cell counting chamber slide and insert it into the cell counting machine (see Table of Materials).</li>
	<li>Plate 40,000 cells per 20 &#181;L of basement membrane extract (BME) into an 8-well glass chamber slide (see Table of Materials). This maintains the organoids for 3-5 days to allow the cells to form organoids and grow to a suitable size.</li>
	<li>To induce double-strand DNA breaks, radiate the plated organoids with 10 Gray (Gy) of &#611;-irradiation (see Table of Materials for irradiator details). 
	NOTE: This could take up to 5-10 min.</li>
	<li>Incubate the organoids in their culture media in a humidified incubator at 37 &#176;C and 5% CO2 for 4 h.</li>
</ol>
3. Immunofluorescence staining
NOTE: Volumes refer to the amount per well of the 8-well chamber slide (~300 &#181;L).
<ol>
	<li>After irradiation and incubation of the organoids, aspirate the media with a pipette, carefully so as not to disrupt the 3D matrix. Wash with 300 &#181;L of PBS.</li>
	<li>Fix the organoids in 300 &#181;L of 2% paraformaldehyde (PFA) for 10 min. 
	NOTES: Do not leave for too long, as the BME will depolymerize and could be aspirated off.</li>
	<li>Wash the organoids with 300 &#181;L of staining buffer (see Table of Materials). Place on a shaker for 5 min.</li>
	<li>For permeabilization, gently add 300 &#181;L of permeabilization buffer (see Table of Materials) and incubate for 20 min. Wash with 300 &#181;L of staining buffer. Place on a shaker for 5 min.</li>
	<li>Add 300 &#181;L of staining buffer to block the permeabilization step. Place on a shaker for 30 min. Aspirate off the staining buffer using a pipette.</li>
	<li>Add 300 &#181;L of primary antibodies (rabbit anti-RAD51, mouse anti-Geminin, rabbit anti-RPA, mouse anti-&#611;H2AX, rabbit anti-Geminin, mouse anti-53BP1; see Table of Materials) diluted in staining buffer. Incubate at 4 &#176;C for 16 h. 
	NOTE: Avoid co-staining with the same host animal. Leave the lid off to avoid the antibodies mixing into neighboring wells.</li>
	<li>Remove the primary antibody solution. Perform three washes with 300 &#181;L of staining buffer for 5 min each on the shaker.</li>
	<li>Add 300 &#181;L of secondary antibody (goat anti-mouse Alexa fluor 488 and goat anti-rabbit Alexa fluor 647; see Table of Materials) solution diluted in staining buffer and incubate for 1 h in the dark. 
	NOTE: All subsequent steps must be performed in the dark.</li>
	<li>Aspirate the secondary antibody solution. Add 300 &#181;L of diluted DAPI. Place on a shaker for 5 min.</li>
	<li>Perform three washes with 300 &#181;L of staining buffer for 5 min each on the shaker. Remove the staining buffer and detach the chambers using the removal kit included with the chamber slides (see Table of Materials). 
	NOTE: Ensure not to push too far forward so as to disrupt the 3D matrix.</li>
	<li>Using a p200 pipette tip with the tip cut off, add mounting medium (see Table of Materials) to cover each well with an organoid tab (e.g., 20-30 &#181;L for each organoid tab).</li>
	<li>Place a coverslip over the specimen, avoiding bubbles.</li>
	<li>Take clear nail polish and paint it onto the sides of the cover glass to seal the slide. Let it harden for 1 h and place it at -20 &#176;C. 
	&#8203;NOTE: After imaging, the slide can be stored for at least 6 months with minimal loss of fluorescence.</li>
</ol>
4. Imaging
<ol>
	<li>Acquire images using a confocal microscope (see Table of Materials) at 63x objective with immersion oil. 
	NOTE: If imaging nuclear proteins, 63x is advantageous, but 40x is also acceptable.</li>
	<li>Use DAPI to locate the organoids through the eyepiece. Select the appropriate filters for microscopy based on the fluorophores used. Set the parameters for capturing the z-stack images. 
	NOTE: The fluorophores used in the study were DAPI, 488, and 647. The 405, 488, and 638 lasers were turned on to visualize the staining. 
	NOTE: The recommended z-stack depends on the resolving power of the objective.</li>
	<li>Adjust the live image: set focus, laser intensity, etc. 
	NOTE: The higher the laser intensity, the more likely the sample will photo-bleach. Therefore, select an optimum laser intensity.</li>
	<li>Acquire the z-stack. 
	NOTE: This could take up to 5-10 min.</li>
	<li>From the images collected in the z-stack, screenshot at least three images per stack. 
	NOTE: Ensure to obtain screenshots throughout the stack so as to not duplicate the nuclei when quantifying.</li>
	<li>Save each file as a TIFF and proceed to analysis (step 5).</li>
</ol>
5. Analysis
NOTE: Use JCountPro for all image analysis following the previously published report21. To obtain this software, reference the associated publication.
<ol>
	<li>Under the object analysis panel (top of the program) in the file selection tab (bottom of the program), select the TIFF files.</li>
	<li>Click Add to move the selected files to the selected files group. Select Display.</li>
	<li>Under the segmentation tab, select blue as the color of the nuclei. Select Auto segmentation to optimize the threshold of the nuclei. 
	NOTE: If the auto segmentation does not accurately identify the objects, then the user can adjust the fine tune and raw tune to the image or see the user manual to further optimize the segmentation.</li>
	<li>Under the objects panel, select Auto split large objects and optimize the size of the nuclei. 
	NOTE: The nuclei typically have an unconditional size of 5,000 pixels, while the conditional size is 1,500 pixels. See the user manual to further optimize the size of the objects.</li>
	<li>Select Identify objects to test the parameters. 
	NOTE: If these parameters are not accurate, the size and tuning can be adjusted along with other settings. See the user manual for instructions regarding further optimization.</li>
	<li>After adjusting the parameters to the image, select Identify Objects in All Images to identify the nuclei in all the images selected.</li>
	<li>Select the Foci Analysis&#160;panel (top of the program).</li>
	<li>Under the select files tab (bottom of the program), select the TIFF files that were used for object analysis and select the Arrow Buttons (&#62;&#62;) to move the images to the image files group.</li>
	<li>In the directory group underneath the image files that were moved, double click the Manual Edit folder and select to move the ioc files into the object collection files group. 
	NOTE: All TIFFs selected must have matched ioc files.</li>
	<li>Press Select to move the files into the selected files group. Select the Foci counting tab at the bottom of the program.</li>
	<li>Optimize the parameters following the steps below.
	<ol>
		<li>Top hat settings index: 12.</li>
		<li>Focus channel: Select the color of the foci (green: &#611;-H2AX; red: RAD51).</li>
		<li>H dome settings: dome height %: 30; threshold %: 28 and 28.</li>
		<li>Shape/size setting: Min focus size, pixels: 5. Select Apply Shape/Size. Max focus size (conditional): 32. Min roundness, x100: 96. Max focus, pixels: 60.</li>
		<li>Noise filter: size 1. 
		NOTE: If determining if a nucleus is positive for geminin staining, under the second channel select green, and under analysis select intensity.</li>
	</ol>
	</li>
	<li>To test the parameters set, select the below buttons in order: Top Hat &#62; H-Dome &#62; Foci Count. 
	NOTE: If these parameters do not work, the size and tuning can be adjusted along with other settings. See user manual to learn more about how the image can be further optimized.</li>
	<li>Once the parameters are optimized for the selected images, select Auto count to count the foci in each image per nuclei. If the second channel is desired, the program will determine the intensity which can be used.</li>
</ol>

<ol>
	<li>Lheureux, S., Gourley, C., Vergote, I., Oza, A. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Epithelial+ovarian+cancer.">Epithelial ovarian cancer.</a> Lancet Oncology. 393 (10177), 1240-1253 (2019).</li><li>Tew, W. P., 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=PARP+inhibitors+in+the+management+of+ovarian+cancer:+ASCO+guideline.">PARP inhibitors in the management of ovarian cancer: ASCO guideline.</a> Journal of Clinical Oncology. 38 (30), 3468-3493 (2020).</li><li>Tomasova, 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=DNA+repair+and+ovarian+carcinogenesis:+impact+on+risk,+prognosis+and+therapy+outcome.">DNA repair and ovarian carcinogenesis: impact on risk, prognosis and therapy outcome.</a> Cancers. 12 (7), 1713 (2020).</li><li>Mukhopadhyay, 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=Development+of+a+functional+assay+for+homologous+recombination+status+in+primary+cultures+of+epithelial+ovarian+tumor+and+correlation+with+sensitivity+to+poly(ADP-Ribose)+polymerase+inhibitors.">Development of a functional assay for homologous recombination status in primary cultures of epithelial ovarian tumor and correlation with sensitivity to poly(ADP-Ribose) polymerase inhibitors.</a> Clinical Cancer Research. 16 (8), 2344-2351 (2010).</li><li>Graeser, 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=A+marker+of+homologous+recombination+predicts+pathologic+complete+response+to+neoadjuvant+chemotherapy+in+primary+breast+cancer.">A marker of homologous recombination predicts pathologic complete response to neoadjuvant chemotherapy in primary breast cancer.</a> Clinical Cancer Research. 16 (24), 6159-6168 (2010).</li><li>Hill, S. 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=Prediction+of+DNA+repair+inhibitor+response+in+short-term+patient-derived+ovarian+cancer+organoids.">Prediction of DNA repair inhibitor response in short-term patient-derived ovarian cancer organoids.</a> Cancer Discovery. 8 (11), 1404-1421 (2018).</li><li>Naipal, K. A. T., 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=Functional+ex+vivo+assay+to+select+homologous+recombination-deficient+breast+tumors+for+PARP+inhibitor+treatment.">Functional ex vivo assay to select homologous recombination-deficient breast tumors for PARP inhibitor treatment.</a> Clinical Cancer Research. 20 (18), 4816-4826 (2014).</li><li>Tumiati, 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=A+functional+homologous+recombination+assay+predicts+primary+chemotherapy+response+and+long-term+survival+in+ovarian+cancer+patients.">A functional homologous recombination assay predicts primary chemotherapy response and long-term survival in ovarian cancer patients.</a> Clinical Cancer Research. 24 (18), 4482-4493 (2018).</li><li>Mukhopadhyay, 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=Clinicopathological+features+of+homologous+recombination-deficient+epithelial+ovarian+cancers:+sensitivity+to+PARP+inhibitors,+platinum,+and+survival.">Clinicopathological features of homologous recombination-deficient epithelial ovarian cancers: sensitivity to PARP inhibitors, platinum, and survival.</a> Cancer Research. 72 (22), 5675-5682 (2012).</li><li>Johnson, S. W., Laub, P. B., Beesley, J. S., Ozols, R. F., Hamilton, T. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Increased+platinum-DNA+damage+tolerance+is+associated+with+cisplatin+resistance+and+cross-resistance+to+various+chemotherapeutic+agents+in+unrelated+human+ovarian+cancer+cell+lines.">Increased platinum-DNA damage tolerance is associated with cisplatin resistance and cross-resistance to various chemotherapeutic agents in unrelated human ovarian cancer cell lines.</a> Cancer Research. 57 (5), 850-856 (1997).</li><li>Stefanou, D. T., 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=Aberrant+DNA+damage+response+pathways+may+predict+the+outcome+of+platinum+chemotherapy+in+ovarian+cancer.">Aberrant DNA damage response pathways may predict the outcome of platinum chemotherapy in ovarian cancer.</a> PLoS One. 10 (2), 0117654 (2015).</li><li>Helleday, T., Petermann, E., Lundin, C., Hodgson, B., Sharma, R. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=DNA+repair+pathways+as+targets+for+cancer+therapy.">DNA repair pathways as targets for cancer therapy.</a> Nature Reviews Cancer. 8 (3), 193-204 (2008).</li><li>Ivashkevich, A., Redon, C. E., Nakamura, A. J., Martin, R. F., Martin, O. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Use+of+the+&#947;-H2AX+assay+to+monitor+DNA+damage+and+repair+in+translational+cancer+research.">Use of the &#947;-H2AX assay to monitor DNA damage and repair in translational cancer research.</a> Cancer Letters. 327 (1-2), 123-133 (2012).</li><li>Fuh, 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=Homologous+recombination+deficiency+real-time+clinical+assays,+ready+or+not.">Homologous recombination deficiency real-time clinical assays, ready or not.</a> Gynecologic Oncology. 159 (3), 877-886 (2020).</li><li>Cong, 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=Replication+gaps+are+a+key+determinant+of+PARP+inhibitor+synthetic+lethality+with+BRCA+deficiency.">Replication gaps are a key determinant of PARP inhibitor synthetic lethality with BRCA deficiency.</a> Molecular Cell. 81 (15), 3128-3144 (2021).</li><li>Lee, E. K., Matulonis, U. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=PARP+inhibitor+resistance+mechanisms+and+implications+for+post-progression+combination+therapies.">PARP inhibitor resistance mechanisms and implications for post-progression combination therapies.</a> Cancers. 12 (8), 2054 (2020).</li><li>Panzarino, N. 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=Replication+gaps+underlie+BRCA+deficiency+and+therapy+response.">Replication gaps underlie BRCA deficiency and therapy response.</a> Cancer Research. 81 (5), 1388-1397 (2021).</li><li>Yee, C., Dickson, K. A., Muntasir, M. N., Ma, Y., Marsh, D. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Three-dimensional+modelling+of+ovarian+cancer:+from+cell+lines+to+organoids+for+discovery+and+personalized+medicine.">Three-dimensional modelling of ovarian cancer: from cell lines to organoids for discovery and personalized medicine.</a> Frontiers in Bioengineering and Biotechnology. 10, 836984 (2022).</li><li>Regan, J. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Immunofluorescence+staining+of+colorectal+cancer+patient-derived+organoids.">Immunofluorescence staining of colorectal cancer patient-derived organoids.</a> Methods Cell Biology. 171, 163-171 (2022).</li><li>Graham, O., 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=Generation+and+culturing+of+high-grade+serous+ovarian+cancer+patient+derived+organoids.">Generation and culturing of high-grade serous ovarian cancer patient derived organoids.</a> Journal of Visualized Experiments. (191), (2023).</li><li>Jakl, L., 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=Validation+of+JCountPro+software+for+efficient+assessment+of+ionizing+radiation-induced+foci+in+human+lymphocytes.">Validation of JCountPro software for efficient assessment of ionizing radiation-induced foci in human lymphocytes.</a> International Journal of Radiation Biology. 92 (12), 766-773 (2016).</li><li>Mullen, M. 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=GAS6/AXL+inhibition+enhances+ovarian+cancer+sensitivity+to+chemotherapy+and+PARP+inhibition+through+increased+DNA+damage+and+enhanced+replication+stress.">GAS6/AXL inhibition enhances ovarian cancer sensitivity to chemotherapy and PARP inhibition through increased DNA damage and enhanced replication stress.</a> Molecular Cancer Research. 20 (2), 265-279 (2022).</li><li>van Ineveld, R. L., Ariese, H. C. R., Wehrens, E. J., Dekkers, J. F., Rios, A. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Single-cell+resolution+three-dimensional+imaging+of+intact+organoids.">Single-cell resolution three-dimensional imaging of intact organoids.</a> Journal of Visualized Experiments. (160), e60709 (2020).</li><li>Dekkers, J. F., 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=High-resolution+3D+imaging+of+fixed+and+cleared+organoids.">High-resolution 3D imaging of fixed and cleared organoids.</a> Nature Protocols. 14 (6), 1756-1771 (2019).</li><li>O'Rourke, K. P., Dow, L. E., Lowe, S. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Immunofluorescent+staining+of+mouse+intestinal+stem+cells.">Immunofluorescent staining of mouse intestinal stem cells.</a> Bio Protocols. 6 (4), 1732 (2016).</li><li>Nwani, N. G., Sima, L. E., Nieves-Neira, W., Matei, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Targeting+the+microenvironment+in+high+grade+serous+ovarian+cancer.">Targeting the microenvironment in high grade serous ovarian cancer.</a> Cancers. 10 (8), 266 (2018).</li><li>Ghoneum, 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=Exploring+the+clinical+value+of+tumor+microenvironment+in+platinum-resistant+ovarian+cancer.">Exploring the clinical value of tumor microenvironment in platinum-resistant ovarian cancer.</a> Seminars in Cancer Biology. 77, 83-98 (2021).</li><li>Yang, Y., Yang, Y., Yang, J., Zhao, X., Wei, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tumor+microenvironment+in+ovarian+cancer:+function+and+therapeutic+strategy.">Tumor microenvironment in ovarian cancer: function and therapeutic strategy.</a> Frontiers in Cell and Developmental Biology. 8, 758 (2020).</li><li>van de Wetering, 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=Prospective+derivation+of+a+living+organoid+biobank+of+colorectal+cancer+patients.">Prospective derivation of a living organoid biobank of colorectal cancer patients.</a> Cell. 161 (4), 933-945 (2015).</li><li>Broutier, L., 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=Human+primary+liver+cancer-derived+organoid+cultures+for+disease+modeling+and+drug+screening.">Human primary liver cancer-derived organoid cultures for disease modeling and drug screening.</a> Nature Medicine. 23 (12), 1424-1435 (2017).</li><li>Drost, J., Clevers, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Organoids+in+cancer+research.">Organoids in cancer research.</a> Nature Reviews Cancer. 18 (7), 407-418 (2018).</li><li>Cybulla, E., Vindigni, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Leveraging+the+replication+stress+response+to+optimize+cancer+therapy.">Leveraging the replication stress response to optimize cancer therapy.</a> Nature Reviews. , (2022).</li></ol>

The authors have nothing to disclose.

The DNA damage response plays an integral role in both the development of ovarian cancer and chemotherapy resistance. Therefore, a thorough understanding of DNA repair mechanisms is imperative. Here, a methodology is presented to study DNA damage repair proteins in 3D, intact organoids. A reproducible, reliable protocol is developed utilizing hallmark antibodies to evaluate DNA damage, homologous recombination, non-homologous end joining, and replication stress. Importantly, these methods are validated using genetically ...

Ovarian cancer is the leading cause of death due to gynecologic malignancy. The majority of patients are treated with DNA-damaging drugs such as carboplatin, and those with homologous recombination repair (HRR)-deficient tumors can be given poly (ADP-ribose) polymerase (PARP) inhibitors1,2. However, most patients develop resistance to these therapies and die within 5 years of diagnosis. Dysregulation of the DNA damage response (DDR) has been associated with the development of ovarian cancer and both chemotherapy and PARP inhibitor resistance3. Thus, study of the DDR is imperative in understanding the pathophysiology of ovarian cancer, potential biomarkers, and novel targeted therapies.
Current methods to evaluate the DDR utilize immunofluorescence (IF), as this allows for the accurate identification and localization of DNA damage proteins and nucleotide analogs. Once there is a double-stranded break (DSB) in the DNA, the histone protein H2AX is rapidly phosphorylated, forming a focus where DNA damage repair proteins congregate4. This phosphorylation can be easily identified utilizing IF; in fact, the &#611;-H2AX assay has commonly been employed to confirm the induction of a DSB5,6,7,8,9. Increased DNA damage has been associated with platinum sensitivity and efficacy of DNA damaging agents10,11,12, and &#611;-H2AX has been proposed as a biomarker associated with chemotherapy response in other cancer treatments13. Upon a DSB, a cell proficient in HRR performs a series of events that leads to BRCA1 and BRCA2 recruiting RAD51 to replace replication protein A (RPA) and bind to the DNA. HRR repair uses a DNA template to faithfully repair the DSB. However, when tumors are deficient in HRR, they rely on alternative repair pathways such as non-homologous end joining (NHEJ). NHEJ is known to be error-prone and creates a high mutational burden on the cell, which uses 53BP1 as a positive regulator14. These DNA damage proteins can all be accurately identified as foci using IF. In addition to staining for proteins, IF can be used to study fork protection and single-stranded DNA gap formation. The ability to have stable forks has been correlated with platinum response, and recently, gap assays have shown the potential to predict the response to PARP inhibitors6,15,16,17. Therefore, staining for the nucleotide analogs after introduction into the genome is another way to study the DDR.
To date, evaluation of the DDR in ovarian cancer has been largely limited to homogenous 2D cell lines that do not recapitulate the clonal heterogeneity, microenvironment, or architecture of in vivo tumors18,19. Recent research suggests organoids are superior to 2D cell lines in studying complex biologic processes such as DDR mechanisms6. The present methodology evaluates RAD51, &#611;-H2AX, 53BP1, RPA, and geminin in PDOs. These methods assess the intact organoid and allow for the study of DDR mechanisms in a setting more similar to the in vivo tumor microenvironment. Together with confocal microscopy and automated foci counting, this methodology can aid in understanding the DDR pathway in ovarian cancer and personalizing treatment plans for patients.

<table><tbody><tr><td>1x phosphate buffered saline with calcium and magnesium (PBS++)</td><td>Sigma</td><td>14-040-133</td><td></td></tr><tr><td>1x phosphate buffered saline without calcium and magnesium (PBS)</td><td>Fisher Scientific&amp;nbsp;</td><td>ICN1860454</td><td></td></tr><tr><td>Ant-53BP1 Antibody&amp;nbsp;</td><td>BD Biosciences</td><td>612522</td><td>diluted to 1:500 in staining buffer</td></tr><tr><td>Ant-Geminin Antibody&amp;nbsp;</td><td>Abcam</td><td>ab104306</td><td>diluted to 1:200 in staining buffer</td></tr><tr><td>Anti-Geminin Antibody&amp;nbsp;</td><td>ProteinTech</td><td>10802-1-AP</td><td>diluted to 1:400 in staining buffer</td></tr><tr><td>Anti-RAD51 Antibody&amp;nbsp;</td><td>Abcam</td><td>ab133534</td><td>diluted to 1:1000 in staining buffer</td></tr><tr><td>Anti-yH2AX Antibody&amp;nbsp;</td><td>Millipore-Sigma</td><td>05-636</td><td>diluted to 1:500 in staining buffer</td></tr><tr><td>Ant-phospho-RPA32 (S4/S8) Antibody</td><td>Bethyl Laboratories&amp;nbsp;</td><td>A300-245A-M</td><td>diluted to 1:200 in staining buffer</td></tr><tr><td>Bovine Serum Albumin (BSA)</td><td>Fisher Scientific&amp;nbsp;</td><td>BP1605 100</td><td></td></tr><tr><td>Centrifuge; Sorvall St 16R Centrifuge</td><td>Thermo Scientific&amp;nbsp;</td><td>75004240</td><td></td></tr><tr><td>Confocal Microscope, Leica SP5 confocal system DMI4000</td><td>Leica&amp;nbsp;</td><td>389584</td><td></td></tr><tr><td>Conical Tubes, 15 mL</td><td>Corning&amp;nbsp;</td><td>14-959-53A</td><td></td></tr><tr><td>Countess 3 FL Automated Cell Counter (Cell Counting Machine)&amp;nbsp;</td><td>Thermo Scientific&amp;nbsp;</td><td>AMQAF2000</td><td></td></tr><tr><td>Countess Cell Counting Chamber Slides</td><td>Thermo Scientific&amp;nbsp;</td><td>C10228</td><td></td></tr><tr><td>Cover Slip</td><td>LA Colors</td><td></td><td>Any clear nail polish will suffice</td></tr><tr><td>Cultrex&amp;nbsp;RGF Basement Membrane Extract, Type 2</td><td>&amp;nbsp;R&amp;amp;D Systems&amp;nbsp;</td><td>3533-010-02</td><td>Could probably use Matrigel or other BME Matrix&amp;nbsp;</td></tr><tr><td>DAPI&amp;nbsp;</td><td>Thermo Scientific&amp;nbsp;</td><td>&amp;nbsp;R37606</td><td>NucBlue Fixed Cell ReadyProbes Reagent, Diluted in 1x PBS&amp;nbsp;</td></tr><tr><td>Glycine&amp;nbsp;</td><td>Fisher Scientific&amp;nbsp;</td><td>NC0756056</td><td></td></tr><tr><td>JCountPro</td><td>JCountPro</td><td></td><td>For access to the software, Email: jcountpro@gmail.com&amp;nbsp;</td></tr><tr><td>Microcentrifuge Tubes&amp;nbsp;</td><td>Fisher Scientific&amp;nbsp;</td><td>07-000-243</td><td></td></tr><tr><td>Nail Polish&amp;nbsp;</td><td>StatLab</td><td>SL102450</td><td></td></tr><tr><td>Parafomraldehyde (PFA), 2%&amp;nbsp;</td><td>Electron Microscopy Sciences&amp;nbsp;</td><td>157-4</td><td>Dilute to 4% PFA in PBS++ to obtain 2% PFA</td></tr><tr><td>Permeabilization Buffer</td><td>Made in Lab</td><td></td><td>0.2% X-100 Triton in PBS++&amp;nbsp;</td></tr><tr><td>Pipette</td><td>Rainin</td><td>17014382</td><td></td></tr><tr><td>Pipette Tips&amp;nbsp;</td><td>Rainin&amp;nbsp;</td><td>17014967</td><td></td></tr><tr><td>ProLong Gold Antifade Mountant</td><td>Thermo Scientific&amp;nbsp;</td><td>&amp;nbsp;P36930</td><td></td></tr><tr><td>Staining Buffer&amp;nbsp;</td><td>Made in Lab</td><td></td><td>0.5% BSA, 0.15% Glycine, 0.1% X-100 Triton in PBS++&amp;nbsp;</td></tr><tr><td>Thermo Scientific Nunc Lab-Tek II Chamber Slide System&amp;nbsp;</td><td>Thermo Scientific&amp;nbsp;</td><td>12-565-8</td><td></td></tr><tr><td>Triton X-100</td><td>Sigma-Alderich&amp;nbsp;</td><td>11332481001</td><td></td></tr><tr><td>Trypan Blue Solution, 0.4%</td><td>Thermo Scientific&amp;nbsp;</td><td>15250061</td><td></td></tr><tr><td>TrypLE Express</td><td>Invitrogen</td><td>12604013</td><td>animal origin-free, recombinant enzyme</td></tr><tr><td>X-RAD 320 Biological Irradiator&amp;nbsp;</td><td>Precision X-Ray Irradiation&amp;nbsp;</td><td>X-RAD320</td><td></td></tr></tbody></table>

visualizing dna damage repair proteins in patient-derived ovarian cancer organoids via immunofluorescence assays

Immunofluorescence is one of the most widely used techniques to visualize target antigens with high sensitivity and specificity, allowing for the accurate identification and localization of proteins, glycans, and small molecules. While this technique is well-established in two-dimensional (2D) cell culture, less is known about its use in three-dimensional (3D) cell models. Ovarian cancer organoids are 3D tumor models that recapitulate tumor cell clonal heterogeneity, the tumor microenvironment, and cell-cell and cell-matrix interactions. Thus, they are superior to cell lines for the evaluation of drug sensitivity and functional biomarkers. Therefore, the ability to utilize immunofluorescence on primary ovarian cancer organoids is extremely beneficial in understanding the biology of this cancer. The current study describes the technique of immunofluorescence to detect DNA damage repair proteins in high-grade serous patient-derived ovarian cancer organoids (PDOs). After exposing the PDOs to ionizing radiation, immunofluorescence is performed on intact organoids to evaluate nuclear proteins as foci. Images are collected using z-stack imaging on confocal microscopy and analyzed using automated foci counting software. The described methods allow for the analysis of temporal and special recruitment of DNA damage repair proteins and colocalization of these proteins with cell-cycle markers.

The presented protocol can successfully stain, visualize, and quantify nuclear DNA damage repair proteins in organoids. This technique was used to stain and evaluate PDOs both before and after irradiation. PDOs were exposed to 10 Gy of radiation and evaluated for the following biomarkers: &#611;-H2AX (Figure 1), a marker of DNA damage; RAD51 (Figure 2), a marker for HRR; 53BP1, a marker of NHEJ; RPA, a marker of replication stress (Figure 3<...

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Visualizing DNA Damage Repair Proteins in Patient-Derived Ovarian Cancer Organoids via Immunofluorescence Assays

The present protocol describes methods for evaluating DNA damage repair proteins in patient-derived ovarian cancer organoids. Included here are comprehensive plating and staining methods, as well as detailed, objective quantification procedures.

Visualizing DNA Damage Repair Proteins in Patient-Derived Ovarian Cancer Organoids via Immunofluorescence Assays

Immunofluorescence is one of the most widely used techniques to visualize target antigens with high sensitivity and specificity, allowing for the accurate ...

visualizing-dna-damage-repair-proteins-patient-derived-ovarian-cancer

Research

JoVE Journal

Cancer Research

1.6K Views.  Washington University in St. Louis. De studie van de DNA-schaderespons is noodzakelijk om de pathofysiologie van potentiële biomarkers van eierstokkanker in nieuwe gerichte therapie te begrijpen. Deze techniek zorgt ervoor dat het monster intact blijft en maakt het mogelijk om antigenen op hun werkingslocatie te onderzoeken. Dit protocol is snel en kan worden aangepast aan elk antigeen dat vatbaar is voor immunofluorescentie.Deze methode geeft inzicht in eierstokkanker en DNA-schadeherstelprocessen die betrokken zijn bi...

Video: Visualizing DNA Damage Repair Proteins in Patient-Derived Ovarian Cancer Organoids via Immunofluorescence Assays

Detection and Visualization of DNA Damage-induced Protein Complexes in Suspension Cell Cultures Using the Proximity Ligation Assay

The DNA damage response orchestrates the repair of DNA lesions that occur spontaneously, are caused by genotoxic stress, or appear in the context of programmed DNA breaks in lymphocytes. The Ataxia-Telangiectasia Mutated kinase (ATM), ATM- and Rad3-Related kinase (ATR) and the catalytic subunit of DNA-dependent Protein Kinase (DNA-PKcs) are among the first that are activated upon induction of DNA damage, and are central regulators of a network that controls DNA repair, apoptosis and cell survival. As part of a tumor-suppressive pathway, ATM and ATR activate p53 through phosphorylation, thereby regulating the transcriptional activity of p53. DNA damage also results in the formation of so-called ionizing radiation-induced foci (IRIF) that represent complexes of DNA damage sensor and repair proteins that accumulate at the sites of DNA damage, which are visualized by fluorescence microscopy. Co-localization of proteins in IRIFs, however, does not necessarily imply direct protein-protein interactions, as the resolution of fluorescence microscopy is limited. 
In situ Proximity Ligation Assay (PLA) is a novel technique that allows the direct visualization of protein-protein interactions in cells and tissues with unprecedented specificity and sensitivity. This technique is based on the spatial proximity of specific antibodies binding to the proteins of interest. When the interrogated proteins are within ~40 nm an amplification reaction is triggered by oligonucleotides that are conjugated to the antibodies, and the amplification product is visualized by fluorescent labeling, yielding a signal that corresponds to the subcellular location of the interacting proteins. Using the established functional interaction between ATM and p53 as an example, it is demonstrated here how PLA can be used in suspension cell cultures to study the direct interactions between proteins that are integral parts of the DNA damage response.

Here, it is demonstrated how the in situ Proximity Ligation Assay (PLA) can be used to detect and visualize the direct protein-protein interactions between ATM and p53 in suspension cell cultures exposed to genotoxic stress.

The DNA damage response orchestrates the repair of DNA lesions that occur spontaneously, are caused by genotoxic stress, or appear in the context of ...

Biochemistry

Immunofluorescence Imaging of DNA Damage and Repair Foci in Human Colon Cancer Cells

The purpose of the manuscript is to provide a step-by-step protocol for performing immunofluorescence microscopy to study the radiation-induced DNA damage response induced by neutron-gamma mixed-beam used in boron neutron capture therapy (BNCT). Specifically, the proposed methodology is applied for the detection of repair proteins activation which can be visualized as foci using antibodies specific to DNA double-strand breaks (DNA-DSBs). DNA repair foci were assessed by immunofluorescence in colon cancer cells (HCT-116) after irradiation with the neutron-mixed beam. DNA-DSBs are the most genotoxic lesions and are repaired in mammalian cells by two major pathways: non-homologous end-joining pathway (NHEJ) and homologous recombination repair (HRR). The frequencies of foci, immunochemically stained, for commonly used markers in radiobiology like &#947;-H2AX, 53BP1 are associated with DNA-DSB number and are considered as efficient and sensitive markers for monitoring the induction and repair of DNA-DSBs. It was established that &#947;-H2AX foci attract repair proteins, leading to a higher concentration of repair factors near a DSB. To monitor DNA damage at the cellular level, immunofluorescence analysis for the presence of DNA-PKcs representative repair protein foci from the NHEJ pathway and Rad52 from the HRR pathway was planned. We have developed and introduced a reliable immunofluorescence staining protocol for the detection of radiation-induced DNA damage response with antibodies specific for repair factors from NHEJ and HRR pathways and observed radiation-induced foci (RIF). The proposed methodology can be used for investigating repair protein that is highly activated in the case of neutron-mixed beam radiation, thereby indicating the dominance of the repair pathway.

Radiation-induced DNA damage response activated by neutron mixed-beam used in boron neutron capture therapy (BNCT) has not been fully established. This protocol provides a step-by-step procedure to detect radiation-induced foci (RIF) of repair proteins by immunofluorescence staining in human colon cancer cell lines after irradiation with the neutron-mixed beam.

The purpose of the manuscript is to provide a step-by-step protocol for performing immunofluorescence microscopy to study the radiation-induced DNA damage ...

Generation and Culturing of High-Grade Serous Ovarian Cancer Patient-Derived Organoids

Organoids are 3D dynamic tumor models that can be grown successfully from patient-derived ovarian tumor tissue, ascites, or pleural fluid and aid in the discovery of novel therapeutics and predictive biomarkers for ovarian cancer. These models recapitulate clonal heterogeneity, the tumor microenvironment, and cell-cell and cell-matrix interactions. Additionally, they have been shown to match the primary tumor morphologically, cytologically, immunohistochemically, and genetically. Thus, organoids facilitate research on tumor cells and the tumor microenvironment and are superior to cell lines. The present protocol describes distinct methods to generate patient-derived ovarian cancer organoids from patient tumors, ascites, and pleural fluid samples with a higher than 97% success rate. The patient samples are separated into cellular suspensions by both mechanical and enzymatic digestion. The cells are then plated utilizing a basement membrane extract (BME) and are supported with optimized growth media containing supplements specific to the culturing of high-grade serous ovarian cancer (HGSOC). After forming initial organoids, the PDOs can sustain long-term culture, including passaging for expansion for subsequent experiments.

Patient-derived organoids (PDO) are a three-dimensional (3D) culture that can mimic the tumor environment in vitro. In high-grade serous ovarian cancer, PDOs represent a model to study novel biomarkers and therapeutics.

Organoids are 3D dynamic tumor models that can be grown successfully from patient-derived ovarian tumor tissue, ascites, or pleural fluid and aid in the ...

Quantifying Replication Stress in Ovarian Cancer Cells Using Single-Stranded DNA Immunofluorescence

Replication stress is a hallmark of several ovarian cancers. Replication stress can emerge from multiple sources, including double-strand breaks, transcription-replication conflicts, or amplified oncogenes, inevitably resulting in the generation of single-stranded DNA (ssDNA). Quantifying ssDNA, therefore, presents an opportunity to assess the level of replication stress in different cell types and under various DNA-damaging conditions or treatments. Emerging evidence also suggests that ssDNA can be a predictor of responses to chemotherapeutic drugs that target DNA repair. Here, we describe a detailed immunofluorescence-based methodology to quantify ssDNA. This methodology involves labeling the genome with a thymidine analog, followed by the antibody-based detection of the analog at the chromatin under non-denaturing conditions. Stretches of ssDNA can be visualized as foci under a fluorescence microscope. The number and intensity of the foci directly co-relate with the level of ssDNA present in the nucleus. We also describe an automated pipeline to quantify the ssDNA signal. The method is rapid and reproducible. Furthermore, the simplicity of this methodology makes it amenable to high-throughput applications such as drug and genetic screens.

Here, we describe an immunofluorescence-based method to quantify the levels of single-stranded DNA in cells. This efficient and reproducible method can be utilized to examine replication stress, a common feature in several ovarian cancers. Additionally, this assay is compatible with an automated analysis pipeline, which further increases its efficiency.

Replication stress is a hallmark of several ovarian cancers. Replication stress can emerge from multiple sources, including double-strand breaks, ...

Ovarian Cancer Patient-Derived Organoid Models for Pre-Clinical Drug Testing

Ovarian cancer is a fatal gynecologic cancer and the fifth leading cause of cancer death among women in the United States. Developing new drug treatments is crucial to advancing healthcare and improving patient outcomes. Organoids are in-vitro three-dimensional multicellular miniature organs. Patient-derived organoid (PDO) models of ovarian cancer may be optimal for drug screening because they more accurately recapitulate tissues of interest than two-dimensional cell culture models and are inexpensive compared to patient-derived xenografts. In addition, ovarian cancer PDOs mimic the variable tumor microenvironment and genetic background typically observed in ovarian cancer. Here, a method is described that can be used to test conventional and novel drugs on PDOs derived from ovarian cancer tissue and ascites. A luminescence-based adenosine triphosphate (ATP) assay is used to measure viability, growth rate, and drug sensitivity. Drug screens in PDOs can be completed in 7-10 days, depending on the rate of organoid formation and drug treatments.

We present a protocol that can be used to conduct therapeutic drug testing with patient-derived ovarian cancer organoids.

Ovarian cancer is a fatal gynecologic cancer and the fifth leading cause of cancer death among women in the United States. Developing new drug treatments ...

Automated Kinetic Imaging for Drug Assessment in Patient-Derived Tumor Organoids

Multiplexed Live-Cell Imaging for Drug Responses in Patient-Derived Organoid Models of Cancer

Patient-derived organoid (PDO) models of cancer are a multifunctional research system that better recapitulates human disease as compared to cancer cell lines. PDO models can be generated by culturing patient tumor cells in extracellular basement membrane extracts (BME) and plating them as three-dimensional domes. However, commercially available reagents that have been optimized for phenotypic assays in monolayer cultures often are not compatible with BME. Herein, we describe a method to plate PDO models and assess drug effects using an automated live-cell imaging system. In addition, we apply fluorescent dyes that are compatible with kinetic measurements to quantify cell health and apoptosis simultaneously. Image capture can be customized to occur at regular time intervals over several days. Users can analyze drug effects in individual Z-plane images or a Z Projection of serial images from multiple focal planes. Using masking, specific parameters of interest are calculated, such as PDO number, area, and fluorescence intensity. We provide proof-of-concept data demonstrating the effect of cytotoxic agents on cell health, apoptosis, and viability. This automated kinetic imaging platform can be expanded to other phenotypic readouts to understand diverse therapeutic effects in PDO models of cancer.

Author Spotlight: Developing Multiplexed Kinetic Assays for Organoid-Based Drug Response Analysis

Patient-derived tumor organoids are a sophisticated model system for basic and translational research. This methods article details the use of multiplexed fluorescent live-cell imaging for simultaneous kinetic assessment of different organoid phenotypes.

Patient-derived organoid (PDO) models of cancer are a multifunctional research system that better recapitulates human disease as compared to cancer cell ...

Standardizing Ovarian Cancer Organoid Biobanking

Strategy for Biobanking of Ovarian Cancer Organoids: Addressing the Interpatient Heterogeneity across Histological Subtypes and Disease Stages

While the establishment of an ovarian cancer biobank from patient-derived organoids along with their clinical background information promises advances in research and patient care, standardization remains a challenge due to the heterogeneity of this lethal malignancy, combined with the inherent complexity of organoid technology. This adaptable protocol provides a systematic framework to realize the full potential of ovarian cancer organoids considering a patient-specific variability of progenitors. By implementing a structured experimental workflow to select optimal culture conditions and seeding methods, with parallel testing of direct 3D seeding versus a 2D/3D route, we obtain, in most cases, robust long-term expanding lines suitable for a broad range of downstream applications. 
Notably, the protocol has been tested and proven efficient in a great number of cases (N = 120) of highly heterogeneous starting material, including high-grade and low-grade ovarian cancer and stages of the disease with primary debulking, recurrent disease, and post-neoadjuvant surgical specimens. Within a low Wnt, high BMP exogenous signaling environment, we observed progenitors being differently susceptible to the activation of the Heregulin 1 &#223; (HER&#223;-1)-pathway, with HER&#223;-1 promoting organoid formation in some while inhibiting it in others. For a subset of the patient's samples, optimal organoid formation and long-term growth necessitate the addition of fibroblast growth factor 10 and R-Spondin 1 to the medium. 
Further, we highlight the critical steps of tissue digestion and progenitor isolation and point to examples where brief cultivation in 2D on plastic is beneficial for subsequent organoid formation in the Basement Membrane Extract type 2 matrix. Overall, optimal biobanking requires systematic testing of all main conditions in parallel to identify an adequate growth environment for individual lines. The protocol also describes the handling procedure for efficient embedding, sectioning, and staining to obtain high-resolution images of organoids, which is required for comprehensive phenotyping.

Author Spotlight: Advancing Personalized Medicine in Ovarian Cancer 

This protocol offers a systematic framework for the establishment of ovarian cancer organoids from different disease stages and addresses the challenges of patient-specific variability to increase yield and enable robust long-term expansion for subsequent applications. It includes detailed steps for tissue processing, seeding, adjusting media requirements, and immunofluorescence staining.

While the establishment of an ovarian cancer biobank from patient-derived organoids along with their clinical background information promises advances in ...

Modeling the Early Steps of Ovarian Cancer Dissemination in an Organotypic Culture of the Human Peritoneal Cavity

The pattern of ovarian cancer metastasis is markedly different from that of most other epithelial tumors, because it rarely spreads hematogenously. Instead, ovarian cancer cells exfoliated from the primary tumor are carried by peritoneal fluid to metastatic sites within the peritoneal cavity. These sites, most notably the abdominal peritoneum and omentum, are organs covered by a mesothelium-lined surface. To investigate the processes of ovarian cancer dissemination, we assembled a complex three-dimensional culture system that reconstructs the lining of the peritoneal cavity in vitro. Primary human fibroblasts and mesothelial cells were isolated from human omentum. The fibroblasts were then mixed with extracellular matrix and covered with a layer of the primary human mesothelial cells to mimic the peritoneal and omental surfaces encountered by metastasizing ovarian cancer cells. The resulting organotypic model is, as shown, used to examine the early steps of ovarian cancer dissemination, including cancer cell adhesion, invasion, and proliferation. This model has been used in a number of studies to investigate the role of the microenvironment (cellular and acellular) in early ovarian cancer dissemination. It has also been successfully adapted to high throughput screening and used to identify and test inhibitors of ovarian cancer metastasis.

Here, we present a protocol to construct a three-dimensional in vitro model of the lining of the peritoneal cavity, composed of primary human mesothelial cells and fibroblasts layered with extracellular matrix, as a tool to investigate ovarian cancer cell adhesion, invasion, and proliferation.

The pattern of ovarian cancer metastasis is markedly different from that of most other epithelial tumors, because it rarely spreads hematogenously. ...

Medicine

Visualization of DNA Repair Proteins Interaction by Immunofluorescence

Mammalian cells are constantly exposed to chemicals, radiations, and naturally occurring metabolic by-products, which create specific types of DNA insults. Genotoxic agents can damage the DNA backbone, break it, or modify the chemical nature of individual bases. Following DNA insult, DNA damage response (DDR) pathways are activated and proteins involved in the repair are recruited. A plethora of factors are involved in sensing the type of damage and activating the appropriate repair response. Failure to correctly activate and recruit DDR factors can lead to genomic instability, which underlies many human pathologies including cancer. Studies of DDR proteins can provide insights into genotoxic drug response and cellular mechanisms of drug resistance.
There are two major ways of visualizing&#160;proteins in vivo: direct observation, by tagging the protein of interest with a fluorescent protein and following it by live imaging, or indirect immunofluorescence on fixed samples. While visualization of fluorescently tagged proteins allows precise monitoring over time, direct tagging in N- or C-terminus can interfere with the protein localization or function. Observation of proteins in their unmodified, endogenous version is preferred. When DNA repair proteins are recruited to the DNA insult, their concentration increases locally and they form groups, or &#8220;foci&#8221;, that can be visualized by indirect immunofluorescence using specific antibodies.
Although detection of protein foci does not provide a definitive proof of direct interaction, co-localization of proteins in cells indicates that they regroup to the site of damage and can inform of the sequence of events required for complex formation. Careful analysis of foci spatial overlap in cells expressing wild type or mutant versions of a protein can provide precious clues on functional domains important for DNA repair function. Last, co-localization of proteins indicates possible direct interactions that can be verified by co-immunoprecipitation in cells, or direct pulldown using purified proteins.

Following DNA damage, human cells activate essential repair pathways to restore the integrity of their genome. Here, we describe the method of indirect immunofluorescence as a means to detect DNA repair proteins, analyze their spatial and temporal recruitment, and help interrogate protein-protein interaction at the sites of DNA damage.

Mammalian cells are constantly exposed to chemicals, radiations, and naturally occurring metabolic by-products, which create specific types of DNA ...

Biology

Assessing DNA Damage Foci: To Identify Radiation-Induced DNA Damage Foci in Cancer Cell Line Using Immunofluorescence Staining

Source: Maliszewska-Olejniczak et al. <a href="https://www.jove.com/v/61399"> Immunofluorescence Imaging of DNA Damage and Repair Foci in Human Colon Cancer Cells.</a> J. Vis. Exp. (2020).
This video describes a protocol to detect radiation-induced DNA repair foci in the colon cancer cell lines using immunofluorescence staining. DNA repair proteins get activated at the DNA damage site; therefore, we can detect them using specific antibodies and visualize them under a fluorescence microscope.

Source: Maliszewska-Olejniczak et al.  Immunofluorescence Imaging of DNA Damage and Repair Foci in Human Colon Cancer Cells. J. Vis. Exp. (2020).
This ...

Visualizing DNA Damage Repair Proteins in Patient-Derived Ovarian Cancer Organoids via Immunofluorescence Assays

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