Role of cancer antigen-125 from pleural & ascitic fluid samples in non malignant conditions
CA-125, an ovarian tumor marker is known to increase in non malignant conditions such as tubercular and non tubercular pleuritis and ascites. We undertook this study to evaluate non-specific rise in CA-125 levels in conditions associated with pleural effusion and ascites and also to understand the mechanism of its secretion.
CA-125 levels in 38 pleural and 46 ascitic fluid samples from non malignant cases and 10 blood samples from pulmonary tuberculosis cases were estimated by ELISA. The ascitic fluid samples were collected from cases of bacterial peritonitis, tuberculosis, hepatitis, cirrhosis of other aetiology and pleural fluid samples were from cases of tubercular, pyogenic, cardiomegaly and other conditions.
Both ascitic and pleural fluid samples (transudative and exudative) showed elevated CA- 125 levels. The CA-125 levels were significantly higher in ascitic fluid samples than in pleural fluid samples.
Our findings showed that elevated levels of CA-125 in pleural and ascitic fluid could be because of varied aetiologies which need to be ruled out before considering malignancy. Peritoneum has a greater capacity to secrete CA-125 than the pleural epithelium and the secretion occurs following inflammation or mechanical distress. Pulmonary tuberculosis as a closed lesion without involvement of pleural epithelium does not evoke high CA-125 release.
Available from: Greg P Bertenshaw
- "However in this setting, the performance of CA-125 varies widely, depending on the cut-off selected, and the patient population, with sensitivities ranging from 29–100%. A further complication is that CA-125 gives many false positives in a wide variety of normal, benign and other malignancies, leading to low specificity , , . "
[Show abstract] [Hide abstract]
ABSTRACT: FDA-cleared ovarian cancer biomarkers are limited to CA-125 and HE4 for monitoring and recurrence and OVA1, a multivariate panel consisting of CA-125 and four additional biomarkers, for referring patients to a specialist. Due to relatively poor performance of these tests, more accurate and broadly applicable biomarkers are needed. We evaluated the dysregulation of 259 candidate cancer markers in serum samples from 499 patients. Sera were collected prospectively at 11 monitored sites under a single well-defined protocol. All stages of ovarian cancer and common benign gynecological conditions were represented. To ensure consistency and comparability of biomarker comparisons, all measurements were performed on a single platform, at a single site, using a panel of rigorously calibrated, qualified, high-throughput, multiplexed immunoassays and all analyses were conducted using the same software. Each marker was evaluated independently for its ability to differentiate ovarian cancer from benign conditions. A total of 175 markers were dysregulated in the cancer samples. HE4 (AUC=0.933) and CA-125 (AUC=0.907) were the most informative biomarkers, followed by IL-2 receptor α, α1-antitrypsin, C-reactive protein, YKL-40, cellular fibronectin, CA-72-4 and prostasin (AUC>0.800). To improve the discrimination between cancer and benign conditions, a simple multivariate combination of markers was explored using logistic regression. When combined into a single panel, the nine most informative individual biomarkers yielded an AUC value of 0.950, significantly higher than obtained when combining the markers in the OVA1 panel (AUC 0.912). Additionally, at a threshold sensitivity of 90%, the combination of the top 9 markers gave 88.9% specificity compared to 63.4% specificity for the OVA1 markers. Although a blinded validation study has not yet been performed, these results indicate that alternative biomarker combinations might lead to significant improvements in the detection of ovarian cancer.
Available from: Robert W Holloway
[Show abstract] [Hide abstract]
ABSTRACT: In previous studies we described the use of a retrospective collection of ovarian cancer and benign disease samples, in combination with a large set of multiplexed immunoassays and a multivariate pattern recognition algorithm, to develop an 11-biomarker classification profile that is predictive for the presence of epithelial ovarian cancer. In this study, customized, Luminex-based multiplexed immunoassay kits were GMP-manufactured and the classification profile was refined from 11 to 8 biomarkers (CA-125, epidermal growth factor receptor, CA 19-9, C-reactive protein, tenascin C, apolipoprotein AI, apolipoprotein CIII, and myoglobin). The customized kits and the 8-biomarker profile were then validated in a double-blinded manner using prospective samples collected from women scheduled for surgery, with a gynecologic oncologist, for suspicion of having ovarian cancer. The performance observed in model development held in validation, demonstrating 81.1% sensitivity (95% CI 72.6 – 87.9%) for invasive epithelial ovarian cancer and 85.4% specificity (95% CI 81.1 – 88.9%) for benign ovarian conditions. The specificity for normal healthy women was 95.6% (95% CI 83.6 – 99.2%). These results have encouraged us to undertake a second validation study arm, currently in progress, to examine the performance of the 8-biomarker profile on the population of women not under the surgical care of a gynecologic oncologist.
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.