Ovarian Cancer Biomarkers: Advancing Early Detection and Guiding Treatment

June 18, 2024

Ovarian Cancer Biomarkers: Advancing Early Detection and Guiding Treatment

Ovarian cancer is a challenging disease that often develops without evident symptoms, making early detection difficult. While the impact of this cancer is significant, researchers are making tremendous strides in understanding the disease and improving diagnostic and treatment strategies. Central to these efforts is the study of ovarian cancer biomarkers: biological clues that can signal the presence of cancer and guide the selection of the most promising therapies for each individual patient.

There is an urgent need for better tools to detect ovarian cancer early and to personalize treatment for each unique patient. That’s why it’s exciting to explore the latest advances in ovarian cancer biomarker research and how these discoveries are bringing us closer to a future where no woman has to face this disease alone.

What are Ovarian Cancer Biomarkers?

Imagine you’re about to embark on a journey through unfamiliar territory. You’ll want a reliable map to guide you, with clear markers indicating where you are and what lies ahead.

In the world of ovarian cancer, biomarkers serve as our map. These measurable indicators in blood, tissue, or other bodily fluids can tell us if cancer is present (diagnostic biomarkers), predict how the disease may progress (prognostic biomarkers), and help us choose the most promising treatment for a particular patient (predictive biomarkers).

By detecting these molecular clues, we can potentially catch ovarian cancer in its earliest, most treatable stages.

According to recent estimates, only about 20% of ovarian cancers are found at an early stage, when the 5-year survival rate is a hopeful 94%. However, for the majority of women diagnosed at a later stage, the 5-year survival drops to 31%. This stark difference highlights the lifesaving potential of early detection through biomarkers.

Current and Emerging Biomarkers for Ovarian Cancer Detection

For many years, a protein called CA125 has been the most widely used biomarker for ovarian cancer. CA125 is a protein produced by some ovarian cancer cells and released into the bloodstream. In a healthy person, the level of CA125 in the blood is usually low. However, in many women with ovarian cancer, the level of CA125 in the blood is elevated, making it a useful indicator of the potential presence of the disease.

When a woman is diagnosed with ovarian cancer, doctors can use CA125 to monitor how well the treatment is working. If the treatment is effective, the level of CA125 in the blood should decrease over time. After treatment, regular monitoring of CA125 levels can also help doctors detect if the cancer has come back (recurred).

However, CA125 is not a perfect biomarker. It can be elevated in other non-cancerous conditions, such as endometriosis, fibroids, and even during menstruation. Additionally, not all ovarian cancers cause an increase in CA125 levels, particularly in the early stages of the disease. These limitations have led researchers to search for other biomarkers that can complement or improve upon CA125 for detecting and monitoring ovarian cancer.

To improve upon CA125, researchers have been exploring other promising biomarkers:

  • HE4: This protein is less likely than CA125 to be elevated in benign conditions, making it a more specific marker for ovarian cancer. Studies suggest that combining CA125 and HE4 could boost detection rates.
  • Osteopontin (OPN): Levels of this protein are significantly higher in the blood of women with epithelial ovarian cancer compared to healthy women or those with benign ovarian disease. High OPN is also associated with more advanced disease.
  • Kallikreins (KLKs): This family of proteins, particularly KLK6 and KLK7, is overexpressed in ovarian tumor cells and shows potential as a diagnostic and prognostic marker.
  • Bikunin: Low levels of this protein before surgery have been linked to later-stage disease, larger residual tumors after surgery, and poorer response to chemotherapy.

Beyond these individual proteins, researchers are exploring novel biomarkers like the copper (Cu) isotope ratio, which is lower in ovarian cancer patients’ blood than in healthy women. Tiny vesicles called exosomes, which are shed by ovarian cancer cells and carry unique molecular cargo, are also being investigated for their diagnostic potential.

With advances in genomic sequencing and computational analysis, researchers are discovering new types of biomarkers, such as lncRNAs and mRNAs, that are differentially expressed in ovarian cancer.

For example, a recent study identified an 8-marker panel including KIAA1324, PAM, PGR, and WT1 that could distinguish between endometrioid and high-grade serous ovarian carcinomas with 90% accuracy.

To harness the power of multiple biomarkers, researchers have developed algorithms that integrate different variables into a risk score:

  • The Risk of Malignancy Index (RMI) combines serum CA125 level, ultrasound score, and menopausal status into a numerical score. An RMI above 200 suggests a high risk of ovarian malignancy. A 2016 analysis found that using the RMI in a two-step strategy could improve ovarian cancer detection rates from 72% to 85%.
  • The Risk of Ovarian Malignancy Algorithm (ROMA) calculates a risk score based on a woman’s CA125 and HE4 levels and menopausal status. ROMA has demonstrated higher sensitivity than CA125 alone, although its specificity is slightly lower.

While these multi-marker approaches show promise, more validation is needed to confirm their usefulness in diverse patient populations. Non-profit organizations like Not These Ovaries are working tirelessly to fund research and clinical trials that can accelerate the development and implementation of these life-saving tools.

Biomarker Testing for Ovarian Cancer

So, how do we actually test for ovarian cancer biomarkers? The most common approach is a simple blood test to measure levels of proteins like CA125 and HE4. These tests use antibodies that specifically attach to the biomarker of interest, allowing us to measure its amount in blood samples.

Advancements in technology are opening up new possibilities for biomarker testing. One such technique is called mass spectrometry-based proteomics, which allows scientists to analyze a large number of proteins from a small sample of blood or tissue. By comparing the protein patterns of women with ovarian cancer to those of healthy women, researchers can identify specific “fingerprints” that are unique to the disease.

In one promising study, a panel of proteins, including CA125, was able to correctly identify early-stage ovarian cancer with a high degree of accuracy – correctly identifying 94% of women with the disease (sensitivity) and 98% of women without it (specificity).

While these new approaches are exciting, it’s crucial to thoroughly test and validate potential biomarkers to ensure they perform well in a clinical setting. Sometimes, complex statistical models can overfit a specific dataset, leading to overestimating a biomarker panel’s accuracy.

To determine whether biomarkers can truly predict ovarian cancer, it’s important to conduct studies that collect samples from women before they are diagnosed with the disease.

There are also other hurdles to overcome in biomarker testing. These include making sure that testing methods are standardized across different laboratories to ensure consistent results, determining the appropriate cutoff values for a positive or negative test result, and taking into account factors like age, menopausal status, and other health conditions that may impact biomarker levels. Scientists are actively addressing these challenges to develop reliable and reproducible biomarker tests for clinical practice.

Prognostic and Predictive Biomarkers for Ovarian Cancer Therapy

Beyond detecting the presence of ovarian cancer, biomarkers can also guide treatment decisions and provide valuable prognostic information. One of the most important predictive biomarkers in ovarian cancer is BRCA mutation status.

BRCA1 and BRCA2 are genes that normally help repair damaged DNA and prevent tumor growth. When these genes are mutated, they can’t function properly, increasing the risk of developing certain cancers, including ovarian cancer.

Women who carry inherited ovarian cancer mutations in the BRCA1 or BRCA2 genes have a significantly higher risk of developing the disease, with estimated lifetime risks of 39-44% for BRCA1 and 11-17% for BRCA2 mutation carriers.

Women with ovarian cancers that have BRCA mutations respond particularly well to a group of medications known as PARP inhibitors. These drugs work by targeting a specific weakness in BRCA-mutated cancer cells. In normal cells, BRCA genes help repair damaged DNA. However, in cancer cells with BRCA mutations, this repair process is already impaired. PARP inhibitors further block DNA repair in these cells, causing them to accumulate so much damage that they eventually die.

The U.S. Food and Drug Administration (FDA) has approved three PARP inhibitors — niraparib, olaparib, and rucaparib — for treating ovarian cancer that has returned after initially responding to platinum-based chemotherapy. These drugs are used as maintenance therapy, which means they are given to help keep the cancer from coming back after successful treatment.

Olaparib has shown particularly impressive results when used as the first treatment for advanced ovarian cancer with BRCA mutations. In a clinical trial, olaparib reduced the risk of the cancer growing or spreading, or the patient dying, by 70% compared to placebo. This significant benefit highlights the potential of using biomarkers like BRCA status to guide treatment decisions and improve outcomes for women with ovarian cancer.

Beyond BRCA, other biomarkers are emerging as potential predictors of response to targeted therapies:

  • Tumors with homologous recombination deficiency (HRD), even without a BRCA mutation, may benefit from PARP inhibitors. New tests are being developed to identify HRD-positive ovarian cancers.
  • Overexpression of proteins that promote blood vessel growth, like VEGF, is associated with more aggressive disease. Bevacizumab, an antibody that targets VEGF, is approved in combination with chemotherapy for advanced ovarian cancer. Measuring VEGF levels might help identify patients most likely to benefit from anti-angiogenic drugs (a type of medication that works by preventing the formation of new blood vessels, a process known as angiogenesis).
  • Immune checkpoint proteins like PD-1 and PD-L1 are potential targets for immunotherapy. Ovarian cancers with high levels of these proteins may be more susceptible to checkpoint inhibitors like pembrolizumab or nivolumab.

On the prognostic side, several biomarkers have been linked to ovarian cancer outcomes:

  • Higher levels of the protein Creatine Kinase B (CKB) in ovarian tumors are associated with worse survival. 
  • Mesothelin, a protein on the surface of some cancer cells, is overexpressed in some ovarian cancers and may promote the spread of tumor cells. Elevated blood levels of mesothelin have been associated with shorter survival times.
  • Apolipoprotein A1 (ApoA1) and transthyretin (TTR) are two proteins found at lower levels in the blood of ovarian cancer patients compared to healthy women. Low ApoA1 or TTR may indicate a poorer prognosis.

By integrating these prognostic and predictive biomarkers, we can envision a future of precision medicine for ovarian cancer, where each patient’s molecular profile guides their individual treatment plan. 

Instead of a one-size-fits-all approach, women with BRCA mutations might receive PARP inhibitors, those with high VEGF could benefit from bevacizumab, and patients with elevated PD-L1 may be good candidates for immunotherapy. This personalized strategy can potentially improve outcomes by matching the right treatment to the right patient at the right time.

Future Directions in Ovarian Cancer Biomarker Research 

As our understanding of ovarian cancer biology deepens, so does our ability to identify and harness novel biomarkers. The future of ovarian cancer biomarker research is multidisciplinary and data-driven, integrating insights from genomics (DNA), transcriptomics (RNA), proteomics (proteins), and other “omics” technologies.

Artificial intelligence and machine learning will play a key role in analyzing these complex datasets to uncover patterns and signatures of disease. 

For example, a recent study used machine learning to analyze protein data from ovarian cancer patients, identifying a panel of just five proteins that could predict early vs. late-stage disease with 83% accuracy. As computational tools become more sophisticated, we may be able to develop predictive models that integrate clinical, imaging, and molecular data to detect ovarian cancer at its earliest, most curable stages.

Scientists are also working on developing new tests for ovarian cancer that are easy to do and less invasive than current methods. While blood tests are the most common, researchers are also looking for unique biomarkers in other body fluids like urine, saliva, and even the breath that a person exhales.

However, turning these exciting biomarker discoveries into tests that can be used in everyday medical care is not a simple task. It involves a lot of detailed work to ensure the tests are accurate and reliable. This includes testing the biomarkers in large groups of people from different backgrounds, ensuring that the testing methods are consistent across different labs, and creating clear guidelines for doctors on how to use these biomarker tests in their practice.

To achieve this, many different groups need to work together. This includes the scientists doing the research, the doctors who treat patients, companies that develop medical tests, and most importantly, the patients and advocates who provide valuable insights and support. By collaborating and sharing their expertise, these groups can overcome the challenges and turn the potential of ovarian cancer biomarkers into a reality that benefits women everywhere.

Ovarian cancer biomarkers represent a beacon of hope in the fight against this devastating disease. Organizations like Not These Ovaries support ovarian cancer research, funding innovative studies and clinical trials that can transform biomarker discoveries into life-saving realities.

With continued investment in biomarker research, we can envision a day when no woman has to face this disease alone: when early detection is the norm, when treatment is tailored to each patient’s unique molecular profile, and when survival rates are measured in decades, not years. Together, we can make this vision a reality and bring hope to the thousands of women affected by ovarian cancer worldwide.