STAR Protocols

Protocol for assessing mobilization of peritoneal B cells to the pre-metastatic omentum in an orthotopic mouse model of ovarian cancer

The omentum is a visceral adipose tissue that undergoes dynamic immunological changes prior to and following metastasis. Here, we present a protocol for assessing the mobilization of peritoneal B cells to the pre-metastatic omentum in a mouse ovarian cancer model. We describe steps for isolation and adoptive transfer of peritoneal donor B cells and their detection in the omentum of recipient mice. This protocol could be utilized to study the mobilization of peritoneal B cells to the omentum in other pathological contexts. For complete details on the use and execution of this protocol, please refer to Lee et al.

Protocol for detecting homologous recombination activity in cancer cells by adenovirus-based functional assay

Cancer cells with homologous recombination deficiency (HRD) exhibit a distinctive vulnerability to poly(ADP-ribose) polymerase inhibitors (PARPis). To address the limitations of existing methodologies incapable of providing real-time insights into homologous recombination (HR) status, we present an adenovirus-based functional assay designed to quantify cellular HR activity. Here, we delineate the step-by-step procedure for producing the adenovirus harboring an HR reporter, processing primary cells, and assessing HR activity in primary ovarian cancer cells. For complete details on the use and execution of this protocol, please refer to Lee et al.

A protocol for selection in mice of highly metastatic ovarian cancer cell with omental tropism

Preclinical models mimicking spontaneous omental metastasis from ovarian cancer (OC) can benefit the study of anti-metastatic therapies for OC patients. Here, we present a protocol to establish a highly metastatic (HM) mouse model with omental tropism by in vivo selection. We describe the processes of implanting OC cells in the ovaries of mice and obtaining HM sublines from their omental metastases. HM cells can metastasize from the ovary to the omentum within 2 weeks. For complete details on the use and execution of this protocol, please refer to Ying et al.

Protocol for culturing patient-derived organoids of cervical cancer

Herein, we present a protocol for culturing patient-derived organoids (PDOs) of cervical cancer that includes workflows for tumor biopsy/resection tissue and cytobrush-sampled cells. We describe steps for PDO culture initiation, including rinsing, gentle dissociation, Lymphoprep separation, and cell assessment, as well as seeding cells from surgical and cytobrush tissue digestion. We then provide guidance on PDO maintenance and passage and techniques for producing conditioned medium. Overall, this protocol serves as a valuable guide for establishing and maintaining cervical cancer PDOs. For complete details on the use and execution of this protocol, please refer to Colbert et al.

In vivo CRISPR screening protocol to identify metastasis mediators using iteratively selected mouse models

In vivo CRISPR screens uncover metastasis genes in native contexts, surpassing in vitro model limitations. Here, we present a protocol to identify metastasis-driving genes in ovarian cancer using an in vivo CRISPR screening technique. Key steps include single-guide RNA (sgRNA) library design and validation, lentiviral transduction, establishment of metastatic mouse models, tissue collection, sgRNA amplification for sequencing, bioinformatics-based candidate gene identification, and functional validation. For complete details on the use and execution of this protocol, please refer to Wang et al.

Building in vitro 3D human multicellular models of high-grade serous ovarian cancer

Three-dimensional (3D), multicellular

Protocol for real-time monitoring of CD8+ T and myeloid cell behavior in human high-grade serous ovarian cancer slices

Studying cell behavior in live human tumors is crucial to understand and improve response to immunotherapies. Here, we present a protocol to slice human ovarian tumors ex vivo, maintain their viability for 24 h, and monitor the behavior of CD8

Protocol for identifying metabolite biomarkers in patient uterine fluid for early ovarian cancer detection

High mortality of ovarian cancer (OC) is primarily attributed to the lack of effective early detection methods. Uterine fluid, pooling molecules from neighboring ovaries, presents an organ-specific advantage over conventional blood samples. Here, we present a protocol for identifying metabolite biomarkers in uterine fluid for early OC detection. We describe steps for uterine fluid collection from patients, metabolite extraction, metabolomics experiments, and candidate metabolite biomarker screening. This standardized workflow holds the potential to achieve early OC diagnosis in clinical practice. For complete details on the use and execution of this protocol, please refer to Wang et al.

Protocol for investigating mitochondrial structure, function, and metabolism in human cervical cancer cells

Mitochondria regulate a variety of biological activities, including metabolism, oxidative stress, and cell death. Here, we present a protocol for the investigation of mitochondrial structure, function, and metabolism in human cervical cancer cells. We describe steps for staining and visualizing mitochondria using confocal microscopy to assess morphology, mass, membrane potential, calcium, reactive oxygen species (ROS), and lipid droplet accumulation. We then detail procedures for isolating mitochondria and performing metabolomic analysis of mitochondrial metabolites via mass spectrometry. For complete details on the use and execution of this protocol, please refer to Adiga et al.

Distinguishing parallel from series circuits with a double knockdown procedure in human cell lines

Signaling cascades can act in series or in parallel. Here, we describe a convenient and robust protocol for dual, sequential knockdown of two proteins using RNA interference. We detail the steps for a quantitative mapping of signaling circuitry. We used this approach to study kinases in human ovarian cancer cells, but the protocol can be applied to many other posttranslational modifications. For complete details on the use and execution of this protocol, please refer to Gocher et al. (2017).

Protocol for iterative in vivo selection of highly metastatic ovarian cancer cell populations and metastasis modeling in mice

The molecular basis underlying ovarian cancers' multi-route metastasis remains poorly defined. This protocol details iterative in vivo selection of highly metastatic cancer cell populations and metastasis modeling in ovarian cancer. We outline steps for inoculation of ES-2-GFP-Luc, monitoring tumor growth and visceral spread, isolation and culture of tumor-derived derivatives, reinoculation of ES-2-MC1-Hep to establish ES-2-MC2-Hep, and assessment of metastatic colonization efficiency. This protocol enables mechanistic studies of distant metastasis in gynecological cancers. For complete details on the use and execution of this protocol, please refer to Wang et al.

Protocol for high-content drug screening using tumor organoids on a 384-pillar plate platform

Tumor organoids provide physiologically relevant three-dimensional (3D) models that overcome the limitations of two-dimensional cultures in drug screening. Here, we present a protocol for generating compact and reproducible ovarian cancer organoids using SKOV-3 cells embedded in growth-factor-reduced Matrigel and dispensed onto a 384-pillar plate. We describe automated cell-matrix dispensing, calcein-AM viability staining, and high-content fluorescence imaging for IC

Protocol for generating an in vitro 3D multicellular culture model of ovarian high-grade serous carcinoma

The development of translational ovarian cancer models to investigate and overcome treatment resistance, while accounting for the impact of the tumor microenvironment, is critical. Here, we present a protocol to establish a multicellular culture model that retains both genetic complexity and the microenvironment of patient tumors and is amenable to molecular and phenotypic analyses and high-throughput drug testing. We describe steps for culturing and characterizing stromal cells derived from cryopreserved and fresh samples and detail procedures for combining them with organoids.

Protocol to optimize the biobanking of ovarian cancer organoids by accommodating patient-specific differences in stemness potential

We present a protocol for effective biobanking of epithelial ovarian cancer organoids, considering the heterogeneous clinical presentation and high recurrence rates. Our protocol involves parallel testing of three media to identify patient-specific optimal conditions. We describe steps for tissue dissociation, differential seeding, organoid cultivation, and biobanking. We outline procedures for fixation, embedding, and staining for confocal imaging. Furthermore, we demonstrate that brief cultivation of isolates in 2D on plastic enhances organoid-forming potential in selected lines, expanding their application scope. For complete details on the use and execution of this protocol, please refer to Hoffmann et al.

Protocol for quantifying drug sensitivity in 3D patient-derived ovarian cancer models

Three-dimensional (3D) ex vivo cultures allow the study of cancer progression and drug resistance mechanisms. Here, we present a protocol for measuring on-target drug sensitivity in a scaffold-free 3D culture system through quantification of apoptotic tumor cells. We provide detailed steps for sample processing, immunofluorescence staining, semi-high-throughput confocal imaging, and imaged-based quantification of 3D cultures. This protocol is versatile and can be applied in principle to any patient-derived material.

Protocol for the isolation of tumor cell-derived extracellular vesicles followed by in vivo metastasis assessment in a murine ovarian cancer model

Extracellular vesicles (EVs) play a crucial role in facilitating communication between cancer cells and their immediate or remote microenvironments, thereby promoting the extensive spread of cancer throughout the body. In this context, we present a protocol for the isolation of tumor cell-derived EVs followed by in vivo metastasis assessment in a murine ovarian cancer model. We describe steps for the isolation and characterization of EVs from ID8 cells, development of a metastatic mouse model, and sample preparation for flow cytometry. For complete details on the use and execution of this protocol, please refer to Gupta et al.

Quantification of cell death and proliferation of patient-derived ovarian cancer organoids through 3D imaging and image analysis

Patient-derived organoids (PDOs) are ideal ex vivo model systems to study cancer progression and drug resistance mechanisms. Here, we present a protocol for measuring drug efficacy in three-dimensional (3D) high-grade serous ovarian cancer PDO cultures through quantification of cytotoxicity using propidium iodide incorporation in dead cells. We also provide detailed steps to analyze proliferation of PDOs using the Ki67 biomarker. We describe steps for sample processing, immunofluorescent staining, high-throughput confocal imaging, and image-based quantification for 3D cultures. For complete details on the use and execution of this protocol, please refer to Lahtinen et al. (2023).

Protocol for establishing organoids from human ovarian cancer biopsies

Ovarian cancer (OC) is the most lethal gynecological cancer. Faithful research models are indispensable to the progression of understanding OC etiology and therapy. Here, we provide a detailed protocol for establishing organoid cultures from patient OC biopsies. The organoids reproduce primary tumor- and patient-specific characteristics including phenotypic properties and genomic aberrations and exhibit patient-dependent responsiveness to drugs. OC-derived organoids provide powerful tools to gain deep insight into the cancer's pathobiology and to screen patient-tumor drug sensitivity to progress toward personalized medicine. For complete details on the use and execution of this protocol, please refer to Maenhoudt et al. (2020).