The Need

Ovarian cancer is a significant health concern, being the leading cause of gynecological cancer-related deaths in the developed world. Current treatments, such as platinum-based chemotherapy, have limited success due to issues like late-stage diagnosis and chemoresistance. Identifying molecular markers of ovarian cancer chemoresistance is crucial to improve treatment outcomes and enhance patient survival rates. An innovative technology capable of accurately diagnosing chemoresistant ovarian cancer and determining poor survival prognosis is urgently needed to enable personalized treatment regimens and optimize therapeutic responses.

The Technology

The technology presented here is a cutting-edge method of diagnosing ovarian cancer resistant to chemotherapeutic intervention. The method involves identifying specific microRNA expression levels in a sample obtained from the patient, particularly miR-484, miR-642, and miR-217. Comparing these expression levels to control levels allows for precise diagnosis of chemoresistant ovarian cancer. Additional miRNAs, such as miR-592, miR-302d, miR-491, and others, can further enhance the accuracy of the diagnosis.

Commercial Applications

1. Ovarian Cancer Diagnosis: The technology serves as a reliable diagnostic tool to determine whether a patient has chemoresistant ovarian cancer. This early detection can lead to more effective treatment strategies.

2. Prognosis Prediction: By analyzing miRNA expression profiles, the technology enables the assessment of a patient's survival prognosis for ovarian cancer. This information can guide healthcare professionals in tailoring appropriate treatment plans.

3. Treatment Planning: The technology facilitates the design of personalized treatment plans based on the diagnosis. Healthcare providers can administer targeted therapies to improve patient outcomes.

Benefits/Advantages

1. Early Chemoresistance Detection: The technology's ability to identify miRNA signatures linked to chemoresistance allows for early detection of resistant ovarian cancer, enabling timely interventions and better patient outcomes.

2. Improved Prognostic Accuracy: By determining miRNA expression profiles, the technology enhances prognostic accuracy, providing patients and physicians with more reliable information about the disease's progression and potential response to treatment.

3. Personalized Treatment: With precise diagnoses and prognoses, healthcare providers can tailor treatment regimens to each patient's specific needs, maximizing the chances of successful outcomes and minimizing unnecessary treatments.

4. Enhanced Patient Survival: The timely identification of chemoresistant ovarian cancer and the application of personalized treatment plans contribute to improved survival rates and enhanced overall patient well-being.

5. Advancement in Oncology Research: The technology's use of microRNAs opens up new avenues for oncology research, paving the way for further discoveries and potential breakthroughs in cancer treatment and diagnostics.

In conclusion, the presented technology addresses a critical commercial need by offering a sophisticated method to diagnose chemoresistant ovarian cancer and predict survival prognosis accurately. Its applications in ovarian cancer diagnosis and personalized treatment planning make it a game-changer in the field of oncology, leading to improved patient outcomes and advancements in cancer research.