OCLN: A Drug Target / Disease Biomarker (G100506658)

Target Name: OCLN

NCBI ID: G100506658

OCLN

OCLN: A Drug Target / Disease Biomarker

OCLN, short for Ovarian Cancer-associated Protein, is a protein that is expressed in high levels in the ovaries, and is associated with the development and progression of ovarian cancer. It is also a potential drug target and biomarker for this disease.

The discovery of OCLN as a potential drug target comes as a promising development for the treatment of ovarian cancer. Ovarian cancer is the most common gynecological malignancy in the United States, and its incidence is expected to reach 2,215,000 cases in 2020, with a fatality rate of 1,927 deaths per 100,000 cases. Currently, there are only a few treatment options available for ovarian cancer, and these options are often limited in their effectiveness and safety.

One of the potential benefits of OCLN as a drug target is its ability to be targeted specifically to the cells that contain the protein. This is because OCLN is expressed in high levels in the ovaries, and it is typically present in the cells that are most vulnerable to cancer development. By targeting OCLN, a drug could potentially inhibit its activity and reduce the growth and spread of ovarian cancer cells.

Another potential benefit of OCLN as a drug target is its potential to be used as a biomarker. OCLN is often expressed in the urine and blood of patients with ovarian cancer, and its levels can be used as a indicator of the disease. This could make OCLN an attractive biomarker for the treatment of ovarian cancer, as it could be used to monitor the effectiveness of a drug and identify patients who are most likely to respond to treatment.

In addition to its potential as a drug target and biomarker, OCLN is also a promising candidate as a potential therapeutic target for ovarian cancer. Studies have shown that OCLN can interact with several other proteins that are involved in the development and progression of ovarian cancer. This suggests that targeting OCLN could potentially be an effective way to treat ovarian cancer by targeting the underlying mechanisms of the disease.

Despite the promising potential of OCLN as a drug target and biomarker for ovarian cancer, further research is needed to fully understand its effects and potential uses. Currently, there are only a few studies that have investigated the effects of OCLN as a potential drug or biomarker for ovarian cancer. Further research, including larger and more diverse studies, is needed to determine the effectiveness and safety of OCLN as a potential treatment for this disease.

In conclusion, OCLN is a protein that is associated with the development and progression of ovarian cancer and has the potential to be used as a drug target or biomarker for this disease. Further research is needed to fully understand its effects and potential uses. If OCLN is found to be an effective drug target or biomarker for ovarian cancer, it could potentially be used to treat this disease and improve outcomes for patients.

Protein Name: Occludin

Functions: May play a role in the formation and regulation of the tight junction (TJ) paracellular permeability barrier. It is able to induce adhesion when expressed in cells lacking tight junctions

The "OCLN Target / Biomarker Review Report" is a customizable review of hundreds up to thousends of related scientific research literature by AI technology, covering specific information about OCLN comprehensively, including but not limited to:
•   general information;
•   protein structure and compound binding;
•   protein biological mechanisms;
•   its importance;
•   the target screening and validation;
•   expression level;
•   disease relevance;
•   drug resistance;
•   related combination drugs;
•   pharmacochemistry experiments;
•   related patent analysis;
•   advantages and risks of development, etc.
The report is helpful for project application, drug molecule design, research progress updates, publication of research papers, patent applications, etc. If you are interested to get a full version of this report, please feel free to contact us at BD@silexon.ai

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