Differentiating Psoriatic Arthritis From Psoriasis Without Psoriatic Arthritis Using Novel Serum Biomarkers

Objective

There is a high prevalence of undiagnosed psoriatic arthritis (PsA) in patients with psoriasis. Identifying soluble biomarkers for PsA will help in screening psoriasis patients for appropriate rheumatology referral. We therefore aimed to investigate whether serum levels of novel markers previously discovered by quantitative mass spectrometric analysis of synovial fluid and skin biopsies performs better than the C‐reactive protein (CRP) level in differentiating PsA patients from those with psoriasis without PsA (PsC).

Methods

In this case–control study, serum samples were obtained from 100 subjects with PsA, 100 with PsC, and 100 healthy controls. Patients with PsA and PsC were group matched for age, sex, psoriasis duration, and Psoriasis Area and Severity Index and were not currently receiving biologic treatment. Using enzyme‐linked immunosorbent assay, 4 high‐priority markers (Mac‐2‐binding protein [M2BP], CD5‐like protein [CD5L], myeloperoxidase [MPO], and integrin β5 [ITGβ5]), as well as previously established markers (matrix metalloproteinase 3 [MMP‐3] and CRP level) were assayed. Data were analyzed using logistic regression. Receiver operating characteristic (ROC) curves were plotted.

Results

In comparisons to controls, CD5L, ITGβ5, M2BP, MPO, MMP‐3, and CRP level were independently associated with PsA, while only CD5L, M2BP, and MPO were independently associated with PsC alone. In comparisons to PsC, ITGβ5, M2BP, and CRP level were independently associated with PsA. ROC analysis of this model shows an area under the curve (AUC) of 0.85 (95% confidence interval [95% CI] 0.80–0.90). The model that included CRP level alone had an AUC of 0.71 (95% CI 0.64–0.78).

Conclusion

CD5L, ITGβ5, M2BP, MPO, MMP‐3, and CRP level are markers for PsA. The combination of ITGβ5, M2BP, and CRP level differentiates PsA from PsC, and performs better than CRP level alone.

     

A multiparametric panel for ovarian cancer diagnosis, prognosis, and response to chemotherapy.

PURPOSE: Our goal was to examine a panel of 11 biochemical variables, measured in cytosolic extracts of ovarian tissues (normal, benign, and malignant) by quantitative ELISAs for their ability to diagnose, prognose, and predict response to chemotherapy of ovarian cancer patients. EXPERIMENTAL DESIGN: Eleven proteins were measured (9 kallikreins, B7-H4, and CA125) in cytosolic extracts of 259 ovarian tumor tissues, 50 tissues from benign conditions, 35 normal tissues, and 44 tissues from nonovarian tumors that metastasized to the ovary. Odds ratios and hazard ratios and their 95% confidence interval were calculated. Time-dependent receiver operating characteristic curves for censored survival data were used to evaluate the performance of the biomarkers. Resampling was used to validate the performance. RESULTS: Most biomarkers effectively separated cancer from noncancer groups. A composite marker provided an area under the curve of 0.97 (95% confidence interval, 0.95-0.99) for discriminating normal and cancer groups. Univariately, hK5 and hK6 were positively associated with progression. After adjusting for clinical variables in multivariate analysis, both hK10 and hK11 significantly predicted time to progression. Increasing levels of hK13 were associated with chemotherapy response, and the predictive power of hK13 to chemotherapy response was improved by a panel of five biomarkers. CONCLUSIONS: The evidence shows that a group of kallikreins and multiparametric combinations with other biomarkers and clinical variables can significantly assist with ovarian cancer classification, prognosis, and response to platinum-based chemotherapy. In particular, we developed a multiparametric strategy for predicting ovarian cancer response to chemotherapy, comprising several biomarkers and clinical features.     

Prostate specific antigen in breast cancer,benign breast disease and normal breast tissue

Prostate specific antigen (PSA) is a tumor marker used widely for the diagnosis and monitoring of prostatic adenocarcinoma. Recently, we provided evidence that PSA may also be produced by breast tumors. In this report we examined quantitatively the PSA levels in 199 breast tumors, 48 tissues with benign breast disease (BBD, 34 fibroadenomas), and 36 normal breast tissues. Significant amounts of PSA (≥ 0.030 ng of PSA per mg of total protein) were found in 28% of breast tumors, 65% of BBD tissues, and 33% of normal breast tissues. PSA positivity in breast tumors was highest in stage I disease (34%) and decreased with disease stage (24% in stage II and 18% in stage III–IV). Using polymerase chain reaction amplification we have shown PSA mRNA presence in patients with PSA protein-positive tissues (benign and malignant) but not in patients with PSA protein-negative tissues. Our data suggest that PSA is expressed frequently by normal breast tissue, by tissue of benign breast diseases, and by breast cancer tissue. Highest expression is seen in benign breast disease and lowest expression in advanced stage cancerous tissue. As PSA production is mediated by steroid hormones and their receptors, we propose that PSA may be a new marker of steroid hormone action in the normal or diseased female breast. The role of this enzyme in the development of breast diseases including breast cancer is currently unknown.     

Higher expression of human kallikrein 10 in breast cancer tissue predicts tamoxifen resistance

The human tissue kallikreins are secreted serine proteases, encoded by a group of homologous genes clustered in tandem on chromosome 19q13.3-4. Human kallikrein 6 and human kallikrein 10 are two new members of this family. Recently, we developed highly sensitive and specific immunofluorometric assays for human kallikrein 6 and human kallikrein 10, which allow for their quantification in tissue extracts and biological fluids. Both human kallikrein 6 and human kallikrein 10 are found to be down-regulated in breast cancer cell lines, suggesting that they may be involved in breast cancer pathogenesis and progression. In this study, we investigated the potential value of human kallikrein 6 and human kallikrein 10 as prognostic and predictive factors in breast cancer. We quantified human kallikrein 6 and human kallikrein 10 protein levels in 749 breast tumour cytosolic extracts and correlated this data with various clinicopathological variables and patient outcomes. Human kallikrein 6 and human kallikrein 10 are positively correlated with each other. Higher human kallikrein 6 and human kallikrein 10 protein levels are associated with younger age, pre-menopausal, status and tumours which are negative for oestrogen and progesterone receptors. No correlation was found between human kallikrein 6 and human kallikrein 10 levels and tumour size, grade, and nodal status. Survival analysis showed that neither human kallikrein 6 nor human kallikrein 10 are related to the rate of relapse-free and overall survival. In the analysis with respect to response to tamoxifen therapy, although human kallikrein 6 levels were not associated with tamoxifen responsiveness, higher levels of human kallikrein 10 were significantly associated with a poor response rate. This association remained significant in the multivariate analysis. Furthermore, higher human kallikrein 10 levels were significantly related with a short progression-free and post-relapse overall survival after start of tamoxifen treatment for advanced disease. Taken together, our results suggest that although human kallikrein 6 and human kallikrein 10 are not prognostic markers for breast cancer, human kallikrein 10 is an independent predictive marker for response of tamoxifen therapy.     

Measurement of serum levels of macrophage inhibitory cytokine 1 combined with prostate-specific antigen improves prostate cancer diagnosis.

PURPOSE: Current serum testing for the detection of prostate cancer (PCa) lacks specificity. On diagnosis, the optimal therapeutic pathway is not clear and tools for adequate risk assessment of localized PCa progression are not available. This leads to a significant number of men having unnecessary diagnostic biopsies and surgery. A search for novel tumor markers identified macrophage inhibitory cytokine 1 (MIC-1) as a potentially useful marker. Follow-up studies revealed MIC-1 overexpression in local and metastatic PCa whereas peritumoral interstitial staining for MIC-1 identified lower-grade tumors destined for recurrence. Consequently, we sought to assess serum MIC-1 measurement as a diagnostic tool. EXPERIMENTAL DESIGN: Using immunoassay determination of serum MIC-1 concentration in 1,000 men, 538 of whom had PCa, we defined the relationship of MIC-1 to disease variables. A diagnostic algorithm (MIC-PSA score) based on serum levels of MIC-1, total serum prostate-specific antigen, and percentage of free prostate-specific antigen was developed. RESULTS: Serum MIC-1 was found to be an independent predictor of the presence of PCa and tumors with a Gleason sum > or =7. We validated the MIC-PSA score in a separate population and showed an improved specificity for diagnostic blood testing for PCa over percentage of free prostate-specific antigen, potentially reducing unnecessary biopsies by 27%. CONCLUSIONS: Serum MIC-1 is an independent marker of the presence of PCa and tumors with a Gleason sum of > or =7. The use of serum MIC-1 significantly increases diagnostic specificity and may be a future tool in the management of PCa.