Biomarker Discovery for Ovarian Cancer
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Biomarker Discovery for Ovarian Cancer

Biomarker discovery services for ovarian cancer are dedicated to identifying and validating molecular markers that facilitate early detection, accurate diagnosis, prognosis, and effective treatment of the disease. With a team of expert researchers, Alfa Cytology is at the cutting edge of advancing the research and development of ovarian cancer biomarkers.

Overview of Biomarker Discovery

Biomarkers play a crucial role in the diagnosis and treatment of ovarian cancer. They enable early detection, assess disease progression, and monitor treatment response. For instance, fluctuations in CA-125 and HE4 levels can signal the presence or recurrence of a tumor. Gene mutations can reveal genetic risk, and specific miRNA expression patterns provide insights into the disease's biology. The combined application of these biomarkers not only enhances the accuracy of ovarian cancer identification but also supports the development of individualized treatment strategies.

Schematic representation of multi-omics approaches towards biomarker discovery for early diagnosis in ovarian cancer.Fig 1. Schematic representation of multi-omics approaches towards biomarker discovery for early diagnosis in ovarian cancer. (XIAO Y, et al., 2022)

Biomarkers of Ovarian Cancer

Biomarkers for ovarian cancer are crucial for early diagnosis, prognostic assessment, and treatment monitoring. Key biomarkers include:

  • CA-125 (Cancer Antigen 125): The most commonly used biomarker for ovarian cancer, CA-125 is utilized to monitor treatment response and disease progression. However, its sensitivity and specificity for early-stage screening are limited.
  • HE4 (Human Epididymis Protein 4): When combined with CA-125, HE4 enhances the accuracy of ovarian cancer detection and is particularly useful in differentiating malignant ovarian tumors from benign conditions.
  • AFP (Alpha-Fetoprotein): AFP is primarily used to detect germ cell tumors of the ovary, such as choriocarcinoma, and is not indicative of all types of ovarian cancer.
  • Beta-HCG (Human Chorionic Gonadotropin): Along with AFP, Beta-HCG is employed to evaluate germ cell tumors, including choriocarcinomas and ovarian teratomas.

Our Services

Alfa Cytology employs advanced instrumentation and extensive research expertise to propel the development of biomarkers for ovarian cancer. Our mission is to utilize cutting-edge technologies and deep scientific knowledge to facilitate the discovery, validation, and preclinical application of biomarkers, thereby enhancing early detection, diagnosis, and treatment outcomes for ovarian cancer.

Workflow of Biomarker Discovery

We offer comprehensive services for developing ovarian cancer biomarkers, encompassing the entire process from discovery to preclinical validation.

Biomarker Discovery

Employ advanced technologies like high-throughput sequencing to identify gene mutations and expression changes associated with ovarian cancer pathogenesis.

Biomarker Validation

Investigate the roles and underlying mechanisms of identified markers in ovarian cancer progression, confirming their biological significance and functional relevance.

Development of Detection Methods

Design and optimize experimental techniques for marker detection, including ELISA, PCR, and immunohistochemistry, ensuring sensitivity and specificity.

Data Analysis

Utilize computational tools for comprehensive analysis of big data, uncovering expression patterns and clinical correlations of markers to derive actionable insights.

Alfa Cytology is committed to advancing cutting-edge research on ovarian cancer biomarkers. By employing systematic genomics, proteomics, and transcriptomics techniques, we rigorously explore and identify key molecular markers associated with ovarian cancer. If you have any questions regarding our related services, please do not hesitate to contact us.

Reference

  1. XIAO Y, BI M, GUO H, et al. Multi-omics approaches for biomarker discovery in early ovarian cancer diagnosis [J]. EBioMedicine, 2022, 79: 104001.

! For research use only.