Log In Sign up
The largest database of trusted experimental protocols
> Disorders > Neoplastic Process > Ovarian Cancer

Ovarian Cancer

Ovarian Cancer: A Comprehensive Overview

Overian cancer is a complex and challenging disease that affects the ovaries, the female reproductive organs responsible for producing eggs and hormones.
This malignant condition arises from the abnormal growth and proliferation of cells within the ovaries, often leading to the formation of tumors.
Research in ovarian cancer is rapidly evolving, with new advancements in diagnostic techniques, treatment strategies, and preventive measures.
PubCompare.ai, an AI-powered platform, can help optimize your ovarian cancer research by enabling you to effortlessly locate the best protocols from literature, pre-prints, and patents, while providing accurate comparisons to enhance reproducibility and accuracy.
Explore the latest developments in ovarian cancer research and gain a deeper understanding of this disease through the use of PubCompare.ai.
Our platform offers a concise, informative overview to help you stay up-to-date with the latest findings and improve the quality and impact of your ovarian cancer research.

Most cited protocols related to «Ovarian Cancer»

1
Validating Cell Mixture Deconvolution
Cited 350 times
We describe several examples using existing methylation data sets as benchmarks for validating the proposed method, in order to demonstrate its clinical or epidemiological utility. First we describe the validation data set S0 used in all examples. Next we describe a laboratory reconstruction experiment, which validates our fundamental proposition that DNA methylation retains substantial information about cell mixtures. Finally we describe the results of applying our methodology to several different target data sets S1. For the head and neck cancer and ovarian cancer data sets, from which bead chip data were available, a linear mixed effects model with a random intercept for bead chip was used to estimate the corresponding row of B1. For the remaining data sets, no bead chip data were available; consequently, ordinary least squares was used. 250 bootstrap iterations were used for each example and each of the two bootstrap methods of standard error estimation.
Houseman E.A., Accomando W.P., Koestler D.C., Christensen B.C., Marsit C.J., Nelson H.H., Wiencke J.K, & Kelsey K.T. (2012). DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics, 13, 86.
Full text: Click here
Publication 2012
Cancer of Head and Neck Cells DNA Chips DNA Methylation Methylation Ovarian Cancer Reconstructive Surgical Procedures
2
Comprehensive Cancer Gene Expression Database
Cited 184 times
Datasets were obtained mainly from GEO (http://www.ncbi.nlm.nih.gov/geo/) and TCGA (https://tcga-data.nci.nih.gov) after searching for keywords related to cancer, survival, and gene expression technologies. Additionally, a few were obtained from author’s websites and from ArrayExpress (http://www.ebi.ac.uk/arrayexpress/). The data source used is shown in the web interface. We favored cancer types above two different cohorts and datasets containing survival data over 30 samples in which censoring indicator and time to death, recurrence, relapse, or metastasis were provided. Clinical data was provided by dataset authors via personal email when not available online in corresponding repositories. Datasets were annotated from provider files as found up to September 2012, and were quantile-normalized and log2 transformed when needed. From TCGA, all datasets were obtained at the gene level (level 3). RNA-Seq counts data were log2 transformed. In some cancer types where many datasets were found for the same gene expression platform, we also provide a merged meta-base. In meta-bases, datasets were quantile normalized; probesets means were equalized conserving the standard deviation by each cohort; and datasets were merged by probeset id. At the moment we provide meta-bases for breast, lung, and ovarian cancer. To facilitate gene searches and conversions between gene identifiers, human gene information was used and obtained from the NCBI FTP site (ftp://ftp.ncbi.nih.gov/gene/DATA/GENE_INFO/Mammalia/Homo_sapiens.gene_info.gz). To simplify the user interface, datasets were grouped by related organ or tissue using disease ontologies [10] (link).
Aguirre-Gamboa R., Gomez-Rueda H., Martínez-Ledesma E., Martínez-Torteya A., Chacolla-Huaringa R., Rodriguez-Barrientos A., Tamez-Peña J.G, & Treviño V. (2013). SurvExpress: An Online Biomarker Validation Tool and Database for Cancer Gene Expression Data Using Survival Analysis. PLoS ONE, 8(9), e74250.
Full text: Click here
Publication 2013
Breast Gene Conversion Gene Expression Genes Homo sapiens Lung Malignant Neoplasms Mammals Neoplasm Metastasis Ovarian Cancer Recurrence Relapse RNA-Seq Tissues
3
Comparative Evaluation of Immune Deconvolution Methods
Cited 134 times
We implemented an R package, immunedeconv, that provides a unified interface to all seven deconvolution methods compared in this paper. The CIBERSORT R source code was obtained from their website on 2018-03-26. The xCell, EPIC, MCP-counter, TIMER and quanTIseq source codes were obtained from GitHub from the following commits: dviraran/xCell@870ddc39, GfellerLab/EPIC@e5ae8803, ebecht/MCPcounter@e7c379b4, hanfeisun/TIMER@a030bac73, FFinotello/quanTIseq@ee9f4036.
We ran CIBERSORT with disabled quantile normalization, as recommended on their website for RNA-seq data. While quanTIseq provides an entire pipeline, starting with read-mapping and estimation of gene expression, we only ran the last part of that pipeline, which estimates the immune cell fractions from gene expression data. We ran TIMER with ‘OV’ on ovarian cancer ascites samples and with ‘SKCM’ on melanoma samples. We ran quanTIseq with the option tumor = TRUE on all tumor samples and tumor = FALSE on the PBMC samples. We ran EPIC with the TRef signature set on all tumor samples and with BRef on the PBMC samples. We ran xCell with the cell.types.use parameter to avoid overcompensation by the spillover correction. For simulated tumor data, cell.types.use was set to B, CAF, DC, Endo, Mac/Mono, NK, T CD4+ n.r., T CD8+, T reg. For the validation datasets, it was set to B, DC, Mono, NK, T CD4+, T CD8+, T. We disabled the mRNA scaling options of quanTIseq and EPIC for the single cell simulation benchmark using the mRNAscale and mRNA_cell options, respectively. Notably, this only has an effect on the absolute values, but not on the correlations used to compare all methods. For each of the datasets (simulated, Hoek, Schelker, Racle), we submitted all samples in a single run.
Sturm G., Finotello F., Petitprez F., Zhang J.D., Baumbach J., Fridman W.H., List M, & Aneichyk T. (2019). Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics, 35(14), i436-i445.
Publication 2019
Ascites Cells Endometriosis Gene Expression Melanoma Neoplasms Ovarian Cancer RNA, Messenger RNA-Seq
4
Ovarian Carcinoma Somatic Mutation Analysis
Cited 108 times
We analyzed whole-exome hybrid capture Illumina sequencing (WES) 36 (link) data from 214 ovarian carcinoma tumor-normal pairs previously analyzed by the TCGA consortium 33 (link). We used the program muTect (K. Cibulskis, et al., in preparation.) We have used a newer version of the program muTect than used in previous analysis of this data 33 (link). The primary improvement in the new version is a reduction in the prior that somatic mutations be at an allelic fraction of 0.5, allowing greater sensitive at low allelic-fraction mutations, such as clonal events in impure samples, or to subclonal mutations. This procedure resulted in 29,268 somatic mutations.
Carter S.L., Cibulskis K., Helman E., McKenna A., Shen H., Zack T., Laird P.W., Onofrio R.C., Winckler W., Weir B.A., Beroukhim R., Pellman D., Levine D.A., Lander E.S., Meyerson M, & Getz G. (2012). Absolute quantification of somatic DNA alterations in human cancer. Nature biotechnology, 30(5), 413-421.
Publication 2012
Alleles Carcinoma Clone Cells Diploid Cell Hybrids Mutation Neoplasms Ovarian Cancer Ovarian Neoplasm
5
Comprehensive Cancer Genomics Analysis Pipeline
Cited 85 times
Thousands of specimens are available from the TCGA; we arbitrarily selected the first 10 ovarian serous carcinomas (OVCA) and 20 clear-cell renal cell carcinomas (KIRC) sample IDs as of May 2013, when sorted alphabetically. The SNP arrays for ovarian serous carcinomas and renal clear-cell carcinomas were obtained on 22 January 2010 and 17 November 2011, respectively. Exome sequence data, previously aligned to the human genome version hg19, was obtained in BAM format in May 2013.
The SNP array files were preprocessed using the aroma.affymetrix package [15 (link)] as described [16 (link)], and copy number variations were determined using ASCAT version 2.1 [3 (link)]; sex chromosomes were excluded from the analysis.
The Sequenza results were obtained using version 2.1.0 with default parameters; the input was generated by the python script sequenza-utils.py version 2.1.0 with default binning size of 50 bases for the exome sequencing or 200 bases for the whole-genome sequencing. The absCN-seq results were obtained using version 1.0 with default parameters; the input was the same genomic segments used by Sequenza as well as high-quality somatic mutations calls detected by VarScan2 as described in the software documentation. The ABSOLUTE results were obtained using software version 1.0.6 with default parameters except that the platform was specified as ‘Illumina_WES’; the input was the same genomic segments used with Sequenza and absCN-seq.
Exome sequencing data from 31 of the NCI-60 tumor cell lines, aligned to the genome version hg19, were downloaded in May 2014 in the BAM format [17 (link)].
Whole-genome sequencing, aligned to the hg19 genome in the BAM format at ×30 of coverage, of two cell lines HCC1143 and HCC1954, matching normal blood, and simulated admixtures at tumor cellularity of 20%, 40%, 60%, and 80%, were obtained in March 2014 from the TCGA4 benchmark cohort (https://cghub.ucsc.edu/datasets/benchmark_download.html).
All BAM files were processed to remove PCR duplicates and low-quality mappings with Picard, and then converted to pileup format using SAMtools [12 (link)].
Favero F., Joshi T., Marquard A.M., Birkbak N.J., Krzystanek M., Li Q., Szallasi Z, & Eklund A.C. (2014). Sequenza: allele-specific copy number and mutation profiles from tumor sequencing data. Annals of Oncology, 26(1), 64-70.
Publication 2014
BLOOD Cell Line, Tumor Cell Lines Cells Copy Number Polymorphism Diploid Cell Exome Genome Genome, Human Hypernephroid Carcinomas Mutation Neoplasms Ovarian Cancer Python Scents Serum Sex Chromosomes

Most recents protocols related to «Ovarian Cancer»

1
Evaluating PARG Inhibitor CHP20-25 Efficacy
Not available on PMC !

Example 8

The efficacy of CHP20-25 against PARG activity was examined by dot blot assays. PARG was incubated with PAR for 20 min at room temperature with or without inhibitors. PAR-digestion results were analyzed using dot blotting with anti-PAR antibody. IC50 values of CHP20-25 were measured by dot blotting with anti-PAR antibody in a dose course of CHP20-25. Colony formation assays were performed using HCC1937 (BRCA1-mutant breast cancer cells) and PARPi-resistant UWB1.289 (BRCA1-mutant ovarian cancer cells) with 2.5-20 μM PARG inhibitors (CHP20-25, FIG. 6A). The IC50 and EC50 values of CHP20-25 were summarized in the table (FIG. 6B).

US11858879B2. PARG inhibitors and method of use thereof (2024-01-02). City of Hope [US]. Inventors: Xiaochun Yu [US], Shih-Hsun Chen [US], Yate-Ching Yuan [US], Hongzhi Li [US], David Horne [US].
Full text: Click here
Patent 2024
Antibodies, Anti-Idiotypic Biological Assay BRCA1 protein, human Cells Cell Survival Digestion Dot Immunoblotting inhibitors Malignant Neoplasm of Breast Ovarian Cancer Psychological Inhibition
2
MSLN-BiTE Binding Affinity Assay
Not available on PMC !

Example 10

Binding of MSLN-BiTE to membrane-bound target expressed in cells was determined with an on-cell affinity assay. 3×104 cells per well of a microtiter plate were incubated with MSLN-BiTE protein in a dose response for 16-22 h at 4° C. Cells were washed twice with flow buffer (PBS that contained 2% fetal calf serum and 0.01% sodium azide), and then resuspended in flow buffer and incubated with an anti-His Fab labeled with Alexa Fluor-647 for 50 minutes at 4° C. Cells were fixed after incubation to optimize detection of the fluorescent signal. Cells were then washed twice and resuspended in flow buffer that contained propidium iodide at 1 ug/ml. Cells were analyzed by flow cytometry for live cells that were positive for Alexa Fluor-647. EC50 values were determined from the dose response curve of Alexa Fluor-647 positive cells.

FIG. 20 shows the results of binding of representative MSLN-BiTE proteins to human MSLN in NCI-N87 gastric cancer cells and to human CD3 in HPB-ALL cells. Solid lines in the graphs below indicate VH-VL orientation and dotted lines indicate the VL-VH orientation. FIG. 22 shows the results of binding of representative MSLN-BiTE proteins to human MSLN in OVCAR-8 ovarian cancer cells and to human or cyno MSLN in 293T cells that are transiently transfected with human MSLN or cyno MSLN.

US11866508B2. Anti-mesothelin binding proteins (2024-01-09). AMGEN INC. [US]. Inventors: William Christian Fanslow, III [US], Carl Kozlosky [US], Jean Gudas [US].
Full text: Click here
Patent 2024
Alexa Fluor 647 Binding Proteins Biological Assay Buffers Cells Dental Occlusion Fetal Bovine Serum Flow Cytometry Gastric Cancer HEK293 Cells Homo sapiens MSLN protein, human Ovarian Cancer Propidium Iodide Proteins Signal Detection (Psychology) Sodium Azide Tissue, Membrane
3
PARG Inhibitor Effects on Colony Formation
Not available on PMC !

Example 4

Colony formation assay was performed using HCC1937 (BRCA1-deficient breast cancer cells), HCC1937 BRCA1 (BRCA1-reconstituted HCC1937 cells) cells, PEO-1 (BRCA2-deficient ovarian cancer cells), and PEO-4 (BRCA2-reconstituted PEO-1 cells) with indicated concentrations of PARG inhibitor (#34).

Colony formation assay: HCC1937, HCC1937-BRCA1, PEO-1 or PEO-4 (˜1000 cells) were seeded into six-well plates and then treated by various doses of PARG inhibitor (#34). After 14-21 days of culture, the viable cells were fixed by methanol and stained with crystal violet. The number of colonies (>50 cells for each colony) was calculated.

US11858879B2. PARG inhibitors and method of use thereof (2024-01-02). City of Hope [US]. Inventors: Xiaochun Yu [US], Shih-Hsun Chen [US], Yate-Ching Yuan [US], Hongzhi Li [US], David Horne [US].
Full text: Click here
Patent 2024
Biological Assay BRCA1 protein, human Cells Gene, BRCA2 Malignant Neoplasm of Breast Malignant Neoplasms Methanol Ovarian Cancer Violet, Gentian
4
Antagonistic TNFR2 Polypeptides Modulate Immune Responses
Not available on PMC !

Example 18

Antagonistic TFNR2 polypeptides, such as antibodies, antigen-binding fragments thereof, single-chain polypeptides, and constructs described herein, may exert biological activities on T-reg cells and T effector cells. To investigate these effects, antagonistic TNFR2 antibodies TNFRAB1 and TNFRAB2 were incubated with cultured T-reg cells at ascending concentrations of antibody, and the percentage change in the quantity of T-reg cells in culture was subsequently recorded. The results of these experiments are shown in FIGS. 21A and 21B, and demonstrate that antagonistic TNFR2 antibodies TNFRAB1 and TNFRAB2 reduce or inhibit the proliferation of T-reg cells in culture in a dose-dependent fashion.

Additionally, antagonistic TNFR2 antibodies TNFRAB1 and TNFRAB2 promote the proliferation of T effector cells. To investigate this activity, antagonistic TNFR2 antibodies TNFRAB1 and TNFRAB2 were incubated with cultured CD8+ T cells at ascending concentrations of antibody, and the percentage change in the quantity of CD8+ T cells in culture was subsequently recorded. The results of these experiments are shown in FIG. 21C, and demonstrate that antagonistic TNFR2 antibodies TNFRAB1 and TNFRAB2 increase the proliferation of T effector cells in a dose-dependent fashion.

The antagonistic TNFR2 antibodies TNFRAB1 and TNFRAB2 also directly kill TNFR2-expressing cancer cells. The antagonistic TNFR2 antibody TNFRAB1, was incubated with cultured OVCAR3 cells, a line of TNFR2+ ovarian cancer cells, at ascending concentrations of antibody, and the percentage change in the quantity of CD8+ T cells in culture was subsequently recorded. The results of this experiments are shown in FIG. 21D, and demonstrate that the antagonistic TNFR2 antibody TNFRAB1 suppresses the proliferation of TNFR2+ cancer cells in a dose-dependent fashion.

Taken together, the data shown in FIGS. 21A-21D demonstrate that antagonistic TNFR2 polypeptides, such as anti-TNFR2 antibodies, antigen-binding fragments thereof, single-chain polypeptides, and constructs described herein, are capable of exerting therapeutic effects through several distinct mechanisms. Antagonistic TNFR2 polypeptides can suppress T-reg cell proliferation and increase the proliferation of T effector cells, which can then mount an immune response against, for example, a cancer cell or a cell of an infectious pathogen. Additionally, antagonistic TNFR2 polypeptides can directly kill cancer cells that express TNFR2. Through these mechanisms, for example, antagonistic TNFR2 polypeptides, such as those described herein, can be used to treat patients suffering from a variety of cancers and infectious diseases, such as those conditions described herein.

US11859002B2. Antagonistic anti-tumor necrosis factor receptor 2 antibodies (2024-01-02). The General Hospital Corporation [US]. Inventors: Denise L. Faustman [US].
Full text: Click here
Patent 2024
antagonists Anti-Antibodies Antibodies Biopharmaceuticals Cardiac Arrest CD8-Positive T-Lymphocytes Cell Lines Cell Proliferation Cells Communicable Diseases Cultured Cells Figs Immunoglobulins Immunoglobulins, Fab Infection Malignant Neoplasms Ovarian Cancer pathogenesis Patients Polypeptides Receptors, Tumor Necrosis Factor, Type II Response, Immune Therapeutic Effect
5
Protein Expression Analysis of CLDN6
Not available on PMC !

Example 2

For Western blot analysis 20 μg of total protein extracted from cells lyzed with Laemmli-lysis buffer was used. Extracts were diluted in reducing sample buffer (Roth), subjected to SDS-PAGE and subsequently electrotransferred onto PVDF membrane (Pall). Immunostaining was performed with polyclonal antibodies reactive to CLDN6 (ARP) and beta-Actin (Abcam) followed by detection of primary antibodies with horseradish-peroxidase conjugated goat anti-mouse and goat anti-rabbit secondary antibodies (Dako).

Tissue lysates from up to five individuals were tested for each normal tissue type. No CLDN6 protein expression was detected in any of the normal tissues analyzed. In contrast to normal tissues, high expression of CLDN6 protein was detected in samples from ovarian cancer and lung cancer. CLDN6 expression was detected in NIH-OVCAR3 (ovarian cancer), MKN7 (gastric cancer), AGS (gastric cancer), CPC-N (SCLC), HCT-116 (colon cancer), FU97 (gastric cancer), NEC8 (testicular embryonal carcinoma), JAR (placental choriocarcinoma), JEG3 (placental choriocarcinoma), BEWO (placental choriocarcinoma), and PA-1 (ovarian teratocarcinoma).

US11859008B2. Antibodies for treatment of cancer expressing claudin 6 (2024-01-02). Ganymed Pharmaceuticals GmbH [DE], Johannes Gutenberg-Universitat Mainz [DE]. Inventors: Ugur Sahin [DE], Ozlem Tureci [DE], Michael Koslowski [DE], Korden Walter [DE], Stefan Woll [DE], Maria Kreuzberg [DE], Bernd Hubner [DE], Michael Erdeljan [DE], Michael Weichel [DE].
Full text: Click here
Patent 2024
Anti-Antibodies Antibodies beta-Actin Buffers Cancer of Colon Cell Lines Choriocarcinoma CLDN6 protein, human Embryonal Carcinoma Gastric Cancer Goat Histocompatibility Testing Horseradish Peroxidase Laemmli buffer Lung Cancer Malignant Neoplasms Mus Ovarian Cancer Ovary Placenta polyvinylidene fluoride Proteins Rabbits SDS-PAGE Small Cell Lung Carcinoma Teratocarcinoma Testis Tissue, Membrane Tissues Western Blot

Top products related to «Ovarian Cancer»

1
Fetal bovine serum (fbs) by Thermo Fisher Scientific
Sourced in United States, China, United Kingdom, Germany, Australia, Japan, Canada, Italy, France, Switzerland, New Zealand, Brazil, Belgium, India, Spain, Israel, Austria, Poland, Ireland, Sweden, Macao, Netherlands, Denmark, Cameroon, Singapore, Portugal, Argentina, Holy See (Vatican City State), Morocco, Uruguay, Mexico, Thailand, Sao Tome and Principe, Hungary, Panama, Hong Kong, Norway, United Arab Emirates, Czechia, Russian Federation, Chile, Moldova, Republic of, Gabon, Palestine, State of, Saudi Arabia, Senegal
Fetal Bovine Serum (FBS) is a cell culture supplement derived from the blood of bovine fetuses. FBS provides a source of proteins, growth factors, and other components that support the growth and maintenance of various cell types in in vitro cell culture applications.
2
Skov3 by American Type Culture Collection
Sourced in United States, China, United Kingdom, Germany, Sweden, Canada, Italy, Australia, Israel, Belgium, Cameroon
SKOV3 is a cell line derived from a human ovarian adenocarcinoma. It is commonly used in scientific research as a model for the study of ovarian cancer.
3
Rpmi 1640 medium by Thermo Fisher Scientific
Sourced in United States, China, Germany, United Kingdom, Japan, France, Canada, Australia, Italy, Switzerland, Belgium, New Zealand, Spain, Israel, Sweden, Denmark, Macao, Brazil, Ireland, India, Austria, Netherlands, Holy See (Vatican City State), Poland, Norway, Cameroon, Hong Kong, Morocco, Singapore, Thailand, Argentina, Taiwan, Province of China, Palestine, State of, Finland, Colombia, United Arab Emirates
RPMI 1640 medium is a commonly used cell culture medium developed at Roswell Park Memorial Institute. It is a balanced salt solution that provides essential nutrients, vitamins, and amino acids to support the growth and maintenance of a variety of cell types in vitro.
4
Ovcar3 by American Type Culture Collection
Sourced in United States, China, United Kingdom, Germany
OVCAR3 is a cell line derived from a human ovarian adenocarcinoma. It is commonly used in research for the study of ovarian cancer.
5
Dulbecco modified eagle medium (dmem) by Thermo Fisher Scientific
Sourced in United States, China, United Kingdom, Germany, France, Australia, Canada, Japan, Italy, Switzerland, Belgium, Austria, Spain, Israel, New Zealand, Ireland, Denmark, India, Poland, Sweden, Argentina, Netherlands, Brazil, Macao, Singapore, Sao Tome and Principe, Cameroon, Hong Kong, Portugal, Morocco, Hungary, Finland, Puerto Rico, Holy See (Vatican City State), Gabon, Bulgaria, Norway, Jamaica
DMEM (Dulbecco's Modified Eagle's Medium) is a cell culture medium formulated to support the growth and maintenance of a variety of cell types, including mammalian cells. It provides essential nutrients, amino acids, vitamins, and other components necessary for cell proliferation and survival in an in vitro environment.
6
Penicillin streptomycin by Thermo Fisher Scientific
Sourced in United States, Germany, United Kingdom, China, Canada, France, Japan, Australia, Switzerland, Israel, Italy, Belgium, Austria, Spain, Gabon, Ireland, New Zealand, Sweden, Netherlands, Denmark, Brazil, Macao, India, Singapore, Poland, Argentina, Cameroon, Uruguay, Morocco, Panama, Colombia, Holy See (Vatican City State), Hungary, Norway, Portugal, Mexico, Thailand, Palestine, State of, Finland, Moldova, Republic of, Jamaica, Czechia
Penicillin/streptomycin is a commonly used antibiotic solution for cell culture applications. It contains a combination of penicillin and streptomycin, which are broad-spectrum antibiotics that inhibit the growth of both Gram-positive and Gram-negative bacteria.
7
Rpmi 1640 by Thermo Fisher Scientific
Sourced in United States, China, United Kingdom, Germany, France, Canada, Japan, Australia, Italy, Switzerland, Belgium, New Zealand, Austria, Netherlands, Israel, Sweden, Denmark, India, Ireland, Spain, Brazil, Norway, Argentina, Macao, Poland, Holy See (Vatican City State), Mexico, Hong Kong, Portugal, Cameroon
RPMI 1640 is a common cell culture medium used for the in vitro cultivation of a variety of cells, including human and animal cells. It provides a balanced salt solution and a source of essential nutrients and growth factors to support cell growth and proliferation.
8
A2780 by American Type Culture Collection
Sourced in United States, China, United Kingdom, Cameroon
The A2780 is a cell line derived from human ovarian carcinoma. It is a commonly used in vitro model for studying ovarian cancer.
9
Lipofectamine 2000 by Thermo Fisher Scientific
Sourced in United States, China, Germany, United Kingdom, Canada, Japan, France, Italy, Switzerland, Australia, Spain, Belgium, Denmark, Singapore, India, Netherlands, Sweden, New Zealand, Portugal, Poland, Israel, Lithuania, Hong Kong, Argentina, Ireland, Austria, Czechia, Cameroon, Taiwan, Province of China, Morocco
Lipofectamine 2000 is a cationic lipid-based transfection reagent designed for efficient and reliable delivery of nucleic acids, such as plasmid DNA and small interfering RNA (siRNA), into a wide range of eukaryotic cell types. It facilitates the formation of complexes between the nucleic acid and the lipid components, which can then be introduced into cells to enable gene expression or gene silencing studies.
10
Mcf 7 by American Type Culture Collection
Sourced in United States, United Kingdom, China, Germany, France, Japan, Italy, Switzerland, Sweden, India, Canada, Egypt, Australia, Holy See (Vatican City State), Brazil
MCF-7 is a cell line derived from human breast adenocarcinoma. It is an adherent epithelial cell line that can be used for in vitro studies.

More about "Ovarian Cancer"

Ovarian neoplasms, ovarian tumors, gynecologic cancer, female reproductive system cancer, BRCA1/BRCA2 mutations, epithelial ovarian cancer, serous ovarian carcinoma, clear cell ovarian carcinoma, endometrioid ovarian carcinoma, mucinous ovarian carcinoma, ovarian germ cell tumors, ovarian sex cord-stromal tumors, FIGO staging, CA-125 biomarker, PARP inhibitors, cytoreductive surgery, platinum-based chemotherapy, RPMI 1640 medium, FBS, SKOV3 cell line, OVCAR3 cell line, A2780 cell line, MCF-7 cell line, DMEM, Penicillin/streptomycin, Lipofectamine 2000.
Ovarian cancer is a complex and challenging disease that affects the ovaries, the female reproductive organs responsible for producing eggs and hormones.
This malignant condition arises from the abnormal growth and proliferation of cells within the ovaries, often leading to the formation of tumors.
Research in ovarian cancer is rapidly evolving, with new advancements in diagnostic techniques, treatment strategies, and preventive measures.
PubCompare.ai, an AI-powered platform, can help optimize your ovarian cancer research by enabling you to effortlessly locate the best protocols from literature, pre-prints, and patents, while providing accurate comparisons to enhance reproducibility and accuracy.
Explore the latest developments in ovarian cancer research and gain a deeper understanding of this disease through the use of PubCompare.ai.
Our platform offers a concise, informative overview to help you stay up-to-date with the latest findings and improve the quality and impact of your ovarian cancer research.