Ovarian cancer is often a silent disease, showing no obvious signs until late in its development. The 5-year survival rate is only 15-20%, with most tumors ultimately becoming resistant to treatment due to the late stage at diagnosis. However, if diagnosed and treated early, the survival rate is 90%. Therefore, prevention and early detection represent our best hope to overcome this disease. Under the aegis of the original award R01CA108990 """"""""Multianalyte assay for early diagnosis of ovarian cancer"""""""", we have identified and validated a 4-biomarker panel that recognizes early stages (I-IIB) ovarian cancer with high sensitivity of 86% at 98% specificity. We have further observed that same biomarkers measured in urine confer additional sensitivity to the test while maintaining the required 98% specificity. Recently published data indicated that performance biomarker combinations with added classification power for ovarian cancer as compared with CA 125 alone that were identified in the sets of samples from patients with clinically diagnosed cancer was similar to CA 125 alone in pre-diagnostic samples.. We hypothesize that to develop and effective screening algorithm for identification of preclinical (pre-diagnostic) stages of ovarian cancer, algorithm training should be performed on samples collected prior to diagnosis. We also hypothesize that measuring biomarkers in urine instead of serum could substaitally improve classification power of screening and diagnostic assays. Our primary objectives are to develop and validate reliable and highly sensitive multimarker assays for early (preclinical) detection and diagnosis of ovarian cancer. To achieve these Objectives, the following Specific Aims are proposed:
Aim 1. Identify and validate serum panel(s) for classification of preclinical ovarian cancer.
Aim 2. Identify and validate urine and serum biomarkers in a multimarker panel to detect early stage ovarian cancer.
Aim 3. Evaluate the performance of urine or urine/serum multimarker panel for triage of ovarian cancer patients to specially trained surgeons. At the conclusion of this study, we expect to develop strategies for the early detection of ovarian cancer that are practical and efficient and can be projected to offer the best opportunity to reduce the mortality from this disease.
Ovarian cancer is often a silent disease, showing no specific signs or symptoms until late in its progression. The 5-year survival rate is only 15-20%, with most tumors ultimately becoming resistant to treatment due to the late stage at diagnosis. However, if diagnosed and treated early, the survival rate is 90%. Therefore, prevention and early detection represent our best hope to overcome this disease. Under the aegis of the original award R01CA108990 Multianalyte assay for early diagnosis of ovarian cancer, we have identified and validated a 4- biomarker panel that recognizes early stage (I-IIB) ovarian cancer with high sensitivity of 86% at 98% specificity. We have further observed that same biomarkers measured in urine confer additional sensitivity to the test while maintaining the required 98% specificity. Recently, published data indicated that performance biomarker combinations with added classification power for ovarian cancer as compared with CA 125 alone that were identified in the sets of samples from patients with clinically diagnosed cancer was similar to CA 125 alone in pre-diagnostic samples.. We hypothesize that to develop an effective screening algorithm for identification of preclinical (pre-diagnostic) ovarian cancer, algorithm training should be performed on samples collected prior to diagnosis. We also hypothesize that measuring biomarkers in urine instead of serum could substantially improve classification power of screening and diagnostic assays. Our primary objectives are to develop and validate reliable and highly sensitive multimarker assays for early (preclinical) detection and diagnosis of ovarian cancer. To achieve these Objectives, the following Specific Aims are proposed: Aim 1. Identify and validate serum panel(s) for classification of preclinical ovarian cancer. (a) Identify serum multimarker panel for ovarian cancer that can reliably recognize preclinical disease. (b) Validate performance of serum multimarker panel with high classification power for preclinical ovarian cancer in PLCO and UKCTOCS sets. (c) Validate performance of a multimarker serum panel in a high-risk cohort. Aim 2. Identify and validate urine and serum biomarkers in a multimarker panel to detect early stage ovarian cancer. (a) Acquire an adequate number of urine and serum samples. (b) Identify an optimal urine and serum biomarker panel with high classification power for early stage ovarian cancer (c) Validate the performance of the selected urine/serum multi-biomarker panel(s) in an independent blinded set of samples from women with or without early and late stages ovarian cancer. (d) Validate the predictive power of a selected multimarker panel in women with other benign and malignant conditions (e) Identify and validate performance of urine-based multimarker panel in a high-risk cohort. (f) Determine the nature of urine biomarkers. Aim 3. Evaluate the performance of urine or urine/serum multimarker panel for triage of ovarian cancer patients to specially trained surgeons. (a) Acquire urine and serum samples from patients with ovarian cancer and benign pelvic mass (b) Develop an algorithm that uses both urine and serum biomarkers to distinguish malignant from benign pelvic masses. (c) Test the performance of the algorithm in a blinded validation set. (d) Test the performance of the algorithm in a prospective study. At the conclusion of this study, we expect to develop strategies for the early detection of ovarian cancer that are practical and efficient and can be projected to offer the best opportunity to reduce the mortality from this disease.
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