Plasma biomarker profiles differ depending on breast cancer subtype but RANTES is consistently increased.

BACKGROUND: Current biomarkers for breast cancer have little potential for detection. We determined whether breast cancer subtypes influence circulating protein biomarkers. METHODS: A sandwich ELISA microarray platform was used to evaluate 23 candidate biomarkers in plasma samples that were obtained from subjects with either benign breast disease or invasive breast cancer. All plasma samples were collected at the time of biopsy, after a referral due to a suspicious screen (e.g., mammography). Cancer samples were evaluated on the basis of breast cancer subtypes, as defined by the HER2 and estrogen receptor statuses. RESULTS: Ten proteins were statistically altered in at least one breast cancer subtype, including four epidermal growth factor receptor ligands, two matrix metalloproteases, two cytokines, and two angiogenic factors. Only one cytokine, RANTES, was significantly increased (P < 0.01 for each analysis) in all four subtypes, with areas under the curve (AUC) for receiver operating characteristic values that ranged from 0.76 to 0.82, depending on cancer subtype. The best AUC values were observed for analyses that combined data from multiple biomarkers, with values ranging from 0.70 to 0.99, depending on the cancer subtype. Although the results for RANTES are consistent with previous publications, the multi-assay results need to be validated in independent sample sets. CONCLUSIONS: Different breast cancer subtypes produce distinct biomarker profiles, and circulating protein biomarkers have potential to differentiate between true- and false-positive screens for breast cancer. IMPACT: Subtype-specific biomarker panels may be useful for detecting breast cancer or as an adjunct assay to improve the accuracy of current screening methods.

Development of a fibrinogen-specific sandwich enzyme-linked immunosorbent assay microarray assay for distinguishing between blood plasma and serum samples.

We have developed a fibrinogen-specific sandwich enzyme-linked immunosorbent assay (ELISA) microarray assay for use in qualitatively distinguishing between blood plasma and serum samples. Three capture antibodies (49D2, HPA001900, and F8512) were evaluated in conjunction with 1D6 as the detection antibody. The data show that 49D2 and (to a lesser extent) F8512 successfully identify previously unknown plasma and serum samples based on approximately a 28-fold difference in signal intensity between the sample types. This assay has utility in rapidly identifying previously archived clinical samples with incomplete annotation in a high-throughput manner prior to proteomic analyses.

Protein secretion in human mammary epithelial cells following HER1 receptor activation: influence of HER2 and HER3 expression.

BACKGROUND: Protein secretion by mammary cells results in autocrine and paracrine signaling that defines cell growth, migration and the extracellular environment. Even so, we have a limited understanding of the cellular processes that regulate protein secretion. METHODS: In this study, we utilize human epithelial mammary cell (HMEC) lines that were engineered to express different levels of HER1, HER2 and HER3. Using an ELISA microarray platform, we evaluate the effects of epidermal growth factor family receptor (HER) expression on protein secretion in the HMEC lines upon initiation of HER1 receptor activation. The secreted proteins include three HER1 ligands, interleukins 1α and 18, RANTES, vascular-endothelial and platelet-derived growth factors, matrix metalloproteases 1, 2 and 9, and the extracellular portion of the HER1 and HER2 proteins. In addition, we investigate whether MAPK/Erk and PI3K/Akt signaling regulate protein secretion in these cell lines and if so, whether the involvement of HER2 or HER3 receptor alters their response to MAPK/Erk and PI3K/Akt signal pathway inhibition in terms of protein secretion. RESULTS: Differential expression of HER2 and HER3 receptors alters the secretion of a variety of growth factors, cytokines, and proteases. Some alterations in protein secretion are still observed when MAPK/Erk or PI3K/Akt signaling is inhibited. CONCLUSION: This study suggests that HER overexpression orchestrates broad changes in the tumor microenvironment by altering the secretion of a diverse variety of biologically active proteins.

An internal calibration method for protein-array studies.

Nuisance factors in a protein-array study add obfuscating variation to spot intensity measurements, diminishing the accuracy and precision of protein concentration predictions. The effects of nuisance factors may be reduced by design of experiments, and by estimating and then subtracting nuisance effects. Estimated nuisance effects also inform about the quality of the study and suggest refinements for future studies.We demonstrate a method to reduce nuisance effects by incorporating a non-interfering internal calibration in the study design and its complemental analysis of variance. We illustrate this method by applying a chip-level internal calibration in a biomarker discovery study. The variability of sample intensity estimates was reduced 16% to 92% with a median of 58%; confidence interval widths were reduced 8% to 70% with a median of 35%. Calibration diagnostics revealed processing nuisance trends potentially related to spot print order and chip location on a slide. The accuracy and precision of a protein-array study may be increased by incorporating a non-interfering internal calibration. Internal calibration modeling diagnostics improve confidence in study results and suggest process steps that may need refinement. Though developed for our protein-array studies, this internal calibration method is applicable to other targeted array-based studies.

Methylation and protein expression of DNA repair genes: association with chemotherapy exposure and survival in sporadic ovarian and peritoneal carcinomas.

BACKGROUND: DNA repair genes critically regulate the cellular response to chemotherapy and epigenetic regulation of these genes may be influenced by chemotherapy exposure. Restoration of BRCA1 and BRCA2 mediates resistance to platinum chemotherapy in recurrent BRCA1 and BRCA2 mutated hereditary ovarian carcinomas. We evaluated BRCA1, BRCA2, and MLH1 protein expression in 115 sporadic primary ovarian carcinomas, of which 31 had paired recurrent neoplasms collected after chemotherapy. Additionally, we assessed whether promoter methylation of BRCA1, MLH1 or FANCF influenced response to chemotherapy or explained alterations in protein expression after chemotherapy exposure. RESULTS: Of 115 primary sporadic ovarian carcinomas, 39 (34%) had low BRCA1 protein and 49 (42%) had low BRCA2 expression. BRCA1 and BRCA2 protein expression were highly concordant (p < 0.0001). MLH1 protein loss occurred in 28/115 (24%) primary neoplasms. BRCA1 protein loss in primary neoplasms was associated with better survival (p = 0.02 Log Rank test) and remained significant after accounting for either stage or age in a multivariate model (p = 0.04, Cox proportional hazards). In paired specimens, BRCA1 protein expression increased in 13/21 (62%) and BRCA2 protein expression increased in 15/21 (71%) of recurrent carcinomas with low or intermediate protein in the paired primary. In contrast MLH1 expression was rarely decreased in recurrent carcinomas (1/33, 3%). Similar frequencies of MLH1, BRCA1, and FANCF promoter methylation occurred in primary carcinomas without previous chemotherapy, after neoadjuvant chemotherapy, or in recurrent neoplasms. CONCLUSION: Low BRCA1 expression in primary sporadic ovarian carcinoma is associated with prolonged survival. Recurrent ovarian carcinomas commonly have increased BRCA1 and/or BRCA2 protein expression post chemotherapy exposure which could mediate resistance to platinum based therapies. However, alterations in expression of these proteins after chemotherapy are not commonly mediated by promoter methylation, and other regulatory mechanisms are likely to contribute to these alterations.

Predicting protein concentrations with ELISA microarray assays, monotonic splines and Monte Carlo simulation.

Making sound proteomic inferences using ELISA microarray assay requires both an accurate prediction of protein concentration and a credible estimate of its error. We present a method using monotonic spline statistical models (MS), penalized constrained least squares fitting (PCLS) and Monte Carlo simulation (MC) to predict ELISA microarray protein concentrations and estimate their prediction errors. We contrast the MSMC (monotone spline Monte Carlo) method with a LNLS (logistic nonlinear least squares) method using simulated and real ELISA microarray data sets.MSMC rendered good fits in almost all tests, including those with left and/or right clipped standard curves. MS predictions were nominally more accurate; especially at the extremes of the prediction curve. MC provided credible asymmetric prediction intervals for both MS and LN fits that were superior to LNLS propagation-of-error intervals in achieving the target statistical confidence. MSMC was more reliable when automated prediction across simultaneous assays was applied routinely with minimal user guidance.

Immobilization strategies for single-chain antibody microarrays.

Sandwich ELISA microarrays have great potential for validating disease biomarkers. Each ELISA relies on robust-affinity reagents that retain activity when immobilized on a solid surface or when labeled for detection. Single-chain antibodies (scFv) are affinity reagents that have greater potential for high-throughput production than traditional IgG. Unfortunately, scFv are typically less active than IgG following immobilization on a solid surface and not always suitable for use in sandwich ELISAs. We therefore investigated different immobilization strategies and scFv constructs to determine a more robust strategy for using scFv as ELISA reagents. Two promising strategies emerged from these studies: (i) the precapture of epitope-tagged scFv using an antiepitope antibody and (ii) the direct printing of a thioredoxin (TRX)/scFv fusion protein on glass slides. Both strategies improved the stability of immobilized scFv and increased the sensitivity of the scFv ELISA microarray assays, although the antiepitope precapture method introduced a risk of reagent transfer. Using the direct printing method, we show that scFv against prostate-specific antigen (PSA) are highly specific when tested against 21 different IgG-based assays. In addition, the scFv microarray PSA assay gave comparable quantitative results (R(2) = 0.95) to a commercial 96-well ELISA when tested using human serum samples. In addition, we find that TRX-scFv fusions against epidermal growth factor and toxin X have good LOD. Overall, these results suggest that minor modifications of the scFv construct are sufficient to produce reagents that are suitable for use in multiplex assay systems.

Development and validation of sandwich ELISA microarrays with minimal assay interference.

Sandwich enzyme-linked immunosorbent assay (ELISA) microarrays are emerging as a strong candidate platform for multiplex biomarker analysis because of the ELISA's ability to quantitatively measure rare proteins in complex biological fluids. Advantages of this platform are high-throughput potential, assay sensitivity and stringency, and the similarity to the standard ELISA test, which facilitates assay transfer from a research setting to a clinical laboratory. However, a major concern with the multiplexing of ELISAs is maintaining high assay specificity. In this study, we systematically determine the amount of assay interference and noise contributed by individual components of a multiplexed 24-assay system. We find that nonspecific reagent cross-reactivity problems are relatively rare. We did identify the presence of contaminant antigens in a "purified antigen". We tested the validated ELISA microarray chip using paired serum samples that had been collected from four women at a 6-month interval. This analysis demonstrated that protein levels typically vary much more between individuals than within an individual over time, a result which suggests that longitudinal studies may be useful in controlling for biomarker variability across a population. Overall, this research demonstrates the importance of a stringent screening protocol and the value of optimizing the antibody and antigen concentrations when designing chips for ELISA microarrays.