Immune response proteins as predictive biomarkers of doxorubicin-induced cardiotoxicity in breast cancer patients.

Cancer treatment with doxorubicin (DOX) can induce cumulative dose-dependent cardiotoxicity. Currently, there are no specific biomarkers that can identify patients at risk during the initial doses of chemotherapy. The aim of this study was to examine plasma cytokines/chemokines and potential cardiovascular biomarkers for the prediction of DOX-induced cardiotoxicity. Plasma samples were collected before (T0), and after the first (T1) and the second (T2) cycles of DOX-based chemotherapy of 27 breast cancer patients, including five patients who presented with >10% decline of left ventricular ejection fraction (LVEF), five patients with LVEF decline of 5-10%, and 17 patients who maintained normal LVEF at the end of chemotherapy (240 mg/m2 cumulative dose of DOX from four cycles of treatment). Multiplex immunoassays were used to screen plasma samples for 40 distinct chemokines, nine matrix metalloproteinases, 33 potential markers of cardiovascular diseases, and the fourth-generation cardiac troponin T assay. The results showed that the patients with abnormal decline of LVEF (>10%) had lower levels of CXCL6 and sICAM-1 and higher levels of CCL23 and CCL27 at T0; higher levels of CCL23 and lower levels of CXCL5, CCL26, CXCL6, GM-CSF, CXCL1, IFN-γ, IL-2, IL-8, CXCL11, CXCL9, CCL17, and CCL25 at T1; and higher levels of MIF and CCL23 at T2 than the patients who maintained normal LVEF. Patients with LVEF decline of 5-10% had lower plasma levels of CXCL1, CCL3, GDF-15, and haptoglobin at T0; lower levels of IL-16, FABP3, and myoglobin at T1; and lower levels of myoglobin and CCL23 at T2 as compared to the patients who maintained normal LVEF. This pilot study identified potential biomarkers that may help predict which patients are vulnerable to DOX-induced cardiotoxicity although further validation is needed in a larger cohort of patients. Impact statement Drug-induced cardiotoxicity is one of the major concerns in drug development and clinical practice. It is critical to detect potential cardiotoxicity early before onset of symptomatic cardiac dysfunction or heart failure. Currently there are no qualified clinical biomarkers for the prediction of cardiotoxicity caused by cancer treatment such as doxorubicin (DOX). By using multiplex immunoassays, we identified proteins with significantly changed plasma levels in a group of breast cancer patients who were treated with DOX-based chemotherapy and produced cardiotoxicity. These proteins were associated with immune response and were identified before DOX treatment or at early doses of treatment, thus they could be potential predictive biomarkers of cardiotoxicity although further validation is required to warrant their clinical values.

Regulatory perspective on translating proteomic biomarkers to clinical diagnostics.

Issues associated with the translation of complex proteomic biomarkers from discovery to clinical diagnostics have been widely discussed among academic researchers, government agencies, as well as assay and instrumentation manufacturers. Here, we provide an overview of the regulatory framework and type of information that is typically required in order to evaluate in vitro diagnostic tests regulated by the Office of In Vitro Diagnostic Device Evaluation and Safety (OIVD) at the US Food and Drug Administration (FDA), with the focus on some of the issues specific to protein-based complex tests. Technological points pertaining to mass spectrometry platforms and assessment of potential concerns important for assurance of safety and effectiveness of this type of assays when introduced into clinical diagnostic use, as well as general approaches for evaluating the performance of these devices, are discussed.

Analytical performance of 4 automated assays for measurement of cystatin C.

BACKGROUND: We evaluated the analytical performance of 4 cystatin C assays (Siemens N Latex on BNII, Roche Tina-quant on Cobas c501, Genzyme on Cobas c501, and Tosoh ST AIA-PACK on Tosoh AIA-600II) according to guidelines published by the Clinical and Laboratory Standards Institute. METHODS: We evaluated total imprecision, limit of detection, and limit of quantification for each assay using patient serum pools and linearity/recovery using serial dilutions of a patient serum pool with cystatin C-free serum. We compared patients (n = 102) using the Siemens assay as a comparison method. RESULTS: All assays had limits of detection and quantification <0.08 and <0.39 mg/L, respectively. Total CVs were generally higher than the manufacturers' claims for all assays. The Roche assay overrecovered cystatin C, particularly at low concentrations (mean recovery 119%, 142% at 0.587 mg/L). Deming regression equations were y = 1.184x + 0.089, S(y|x) = 0.246 for Genzyme; y = 0.937x + 0.231, S(y|x) = 0.231 for Roche; and y = 1.010x + 0.216, S(y|x) = 0.115 for Tosoh. The Genzyme assay appeared to report higher results than the Siemens assay, which is consistent with a higher reference interval specified by the manufacturer. CONCLUSIONS: Although all assays were acceptable for clinical use, their diagnostic performances were not optimal. Limitations include imprecision greater than claimed, overrecovery for the Roche assay on low concentration samples, and differences in results for patient samples. The latter situation requires assay-specific cystatin C-based glomerular filtration rate prediction equations at least until calibration is standardized using the international cystatin C calibrator now being developed.

A unique proteolytic fragment of alpha1-antitrypsin is elevated in ductal fluid of breast cancer patient.

By comparison of mass spectra from a small cohort of nipple aspiration fluids (NAF), we previously discovered a panel of five candidate breast cancer biomarkers among them an unidentified 4.7 kD peptide BF5. The purposes of the present study were to verify the presence of BF5 in an independent cohort; to determine the protein identity of BF5; and to provide insight into the biology of BF5 production and elevation in tumor-associated NAF. We prospectively collected bilaterally matched NAF from patients with unilateral Stage I/II breast cancer (IBC-31), ductal carcinoma in situ (DCIS-6), atypical ductal hyperplasia (ADH-5), and presumed healthy women who came to routine mammography and had a normal exam (31). Following the consolidation of its cancer-associated expression on SELDI-mass spectrometry, BF5 was isolated by gel electrophoresis and sequenced by tandem mass spectrometry. BF5 was elevated in 15-25% of women with IBC, DCIS, or ADH vs. 0% of controls. This elevation was restricted to the affected breasts. BF5 was identified as 41/42-aa C-terminal peptide of alpha1-antitrypsin (AAT), the principle inhibitor of serine protease neutrophile elastase. The full length AAT showed a consistent expression pattern as C-41/42, and C-41/42 can be generated in vitro by MMP-7 cleavage. In conclusion, elevated C-41/42 is likely the result of elevated AAT synthesis, and the activity of specific MMPs present within the tumor. As other C-terminal fragments of AAT are reported to function as tumor-derived suppressors to the host immune-system, elevated C-41/42 may also be predictive of a poor outcome.

Identification of biomarkers for breast cancer in nipple aspiration and ductal lavage fluid.

PURPOSE: To establish a comprehensive proteomic approach for biomarker discovery and validation in breast fluid. EXPERIMENTAL DESIGN: A total of 95 specimens from three institutions were used including 10 nipple aspiration fluid (5 stage I/II cancerous breasts and 5 age-matched healthy controls), 42 ductal lavage fluid from 14 patients with unilateral stage I/II cancer (25 from 9 cancerous breasts and 17 from 7 contralateral breasts), and 42 ductal lavage fluid from 14 high-risk women (multiple ducts repeated lavage). Differentially expressed protein/peptides were discovered by proteomic analysis of training sample, using ProteinChip arrays and surface-enhanced laser desorption ionization (SELDI) time-of-flight mass spectrometry, and validated on independently collected testing samples. After protein identification, ELISA was done to confirm the SELDI findings. RESULTS: We were able to obtain reproducible protein profiles using minimal amount of protein (1 mug) by applying an optimized chip protocol and SELDI. We were able to select cancer-associated biomarkers despite large individual variability by applying both unsupervised and supervised cluster analysis. Furthermore, we were able to train and test candidate biomarkers on independently collected samples and identified one component of a multimarker panel as human neutrophil peptides 1 to 3. CONCLUSIONS: Breast fluid is a rich source of breast cancer biomarkers. In combination with high-throughput novel proteomic profiling technology and multicenter study design, markers that are highly specific to breast cancer can be discovered and validated. Our observations also suggest that persistent elevation of human neutrophil peptide in high-risk women may imply early onset of cancer not yet detectable by current detection method. Proof of this hypothesis requires follow-up on a larger study population.

Independent validation of candidate breast cancer serum biomarkers identified by mass spectrometry.

BACKGROUND: We previously selected a panel of 3 breast cancer biomarkers (BC1, BC2, and BC3) from serum samples collected at a single hospital based on their collective contribution to the optimal separation of breast cancer patients and noncancer controls by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS). The identities and general applicability of these markers, however, were unknown. In this study, we performed protein expression profiling on samples obtained from a second hospital, included a greater number of ductal carcinoma in situ (DCIS) cases, and performed purification and identification of the 2 confirmed markers. METHODS: Using a case-control study design, we performed protein expression profiling on serum samples from the National Cancer Institute (Milan, Italy). The validation sample cohort consisted of 61 women with locally invasive breast cancer, 32 with DCIS, 37 with various benign breast diseases (including 13 atypical), and 46 age-matched apparently healthy women (age range, 44-68 years). Validated biomarkers were purified and identified with serial chromatography, 1-dimensional gel electrophoresis, in-gel ASP-N digestion, peptide mass fingerprinting, and tandem mass peptide sequencing. RESULTS: The BC3 and BC2 expression patterns in this sample set were consistent with the first study sample set. BC3 and BC2 were identified to be complement component C3a(desArg) and a C-terminal-truncated form of C3a(desArg), respectively. CONCLUSIONS: Evaluation of biomarkers in independent sample sets can help determine the broader utility of candidate markers, and protein identification permits understanding of their molecular basis. C3a(desArg) appears to lack specificity among patients with benign diseases, limiting its utility as a stand-alone tumor marker, but it may still be useful in a multimarker panel for early detection of breast cancer.

Fatty acid synthase as a tumor marker: its extracellular expression in human breast cancer.

Overexpression of fatty acid synthase (FAS EC 2.3.1.85) is associated with certain cancers and therefore is a putative tumor marker. The presence of FAS in patients with breast, prostate, colon, ovarian, and other cancers has been reported. The mechanism of FAS overexpression in malignancies remains unknown. Here, we show that FAS is released into the extracellular space in cancer cells. The extracellular FAS are present in various immunoreactive forms, and show different expression patterns in various cancer cells. In serum of breast cancer patients, the FAS is a small molecule similar to the form in breast cancer cell lysate but not conditioned medium of cultured cells. The extracellular expression of FAS in breast cancer cells is time dependent and may be hormone independent. These results indicate that the FAS are an ordered cellular response of a living cell and actively exclude excess intracellular FAS molecules from the cell. This phenomenon is up-regulated in breast and may be in other cancer cells as well. Significant elevation of FAS was detected in serum of breast cancer patients compared to healthy subjects. In comparison with CA27.29, no correlation between these two tumor markers was found. Thus, the extracellular FAS may serve as a potential diagnostic and prognostic marker.

Three biomarkers identified from serum proteomic analysis for the detection of early stage ovarian cancer.

Early detection remains the most promising approach to improve long-term survival of patients with ovarian cancer. In a five-center case-control study, serum proteomic expressions were analyzed on 153 patients with invasive epithelial ovarian cancer, 42 with other ovarian cancers, 166 with benign pelvic masses, and 142 healthy women. Data from patients with early stage ovarian cancer and healthy women at two centers were analyzed independently and the results cross-validated to discover potential biomarkers. The results were validated using the samples from two of the remaining centers. After protein identification, biomarkers for which an immunoassay was available were tested on samples from the fifth center, which included 41 healthy women, 41 patients with ovarian cancer, and 20 each with breast, colon, and prostate cancers. Three biomarkers were identified as follows: (a) apolipoprotein A1 (down-regulated in cancer); (b) a truncated form of transthyretin (down-regulated); and (c) a cleavage fragment of inter-alpha-trypsin inhibitor heavy chain H4 (up-regulated). In independent validation to detect early stage invasive epithelial ovarian cancer from healthy controls, the sensitivity of a multivariate model combining the three biomarkers and CA125 [74% (95% CI, 52-90%)] was higher than that of CA125 alone [65% (95% CI, 43-84%)] at a matched specificity of 97% (95% CI, 89-100%). When compared at a fixed sensitivity of 83% (95% CI, 61-95%), the specificity of the model [94% (95% CI, 85-98%)] was significantly better than that of CA125 alone [52% (95% CI, 39-65%)]. These biomarkers demonstrated the potential to improve the detection of early stage ovarian cancer.

Detection of prostate cancer using serum proteomics pattern in a histologically confirmed population.

PURPOSE: We retrospectively identified a panel of serum proteins that can discriminate between men with prostate cancer (clinically organ confined) and men with benign prostate disease. MATERIALS AND METHODS: A contemporary set of 345 men who had an archival serum sample available were included in this study. The cancer group consisted of 246 men who underwent radical prostatectomy at the Johns Hopkins Hospital between March 1999 and April 2001. The noncancer group included 99 men with no histological evidence of prostate cancer on biopsy between April 1997 and April 2001 at the same institution. Serum proteomics mass spectra of these patients were generated using ProteinChip arrays and a ProteinChip Biomarker System II surface enhanced laser desorption/ionization time of flight mass spectrometer (Ciphergen Biosystems, Inc., Fremont, California). The cases and controls were randomly split into training and testing groups by a stratified sampling procedure. A combination of bioinformatics tools including ProPeak (3Z Informatics, Charleston, South Carolina) was used to reveal the optimal panel of biomarkers for maximum separation of the prostate cancer and the benign prostate disease cohorts. RESULTS: A panel of 3 proteins (PC-1, PC-2 and PC-3) was selected using the training data. Performance of each of the protein markers and a linear regression derived composite index (PC-com3) were evaluated on the testing data. The area under the curve for prostate specific antigen (PSA), PC-1, PC-2, PC-3 and PC-com3 was 0.542, 0.585, 0.600, 0.636 and 0.643, respectively. Improvement of PC-com3 compared to PSA is observed at specificity range 30% to 80%. At a selected specificity of 45% the sensitivity of PC-com3 is 76%, significantly better than the PSA sensitivity of 57% (p <0.0001). CONCLUSIONS: Serum proteomics patterns may potentially aid in the early detection of prostate cancer.

Proteomics and bioinformatics approaches for identification of serum biomarkers to detect breast cancer.

BACKGROUND: Surface-enhanced laser desorption/ionization (SELDI) is an affinity-based mass spectrometric method in which proteins of interest are selectively adsorbed to a chemically modified surface on a biochip, whereas impurities are removed by washing with buffer. This technology allows sensitive and high-throughput protein profiling of complex biological specimens. METHODS: We screened for potential tumor biomarkers in 169 serum samples, including samples from a cancer group of 103 breast cancer patients at different clinical stages [stage 0 (n = 4), stage I (n = 38), stage II (n = 37), and stage III (n = 24)], from a control group of 41 healthy women, and from 25 patients with benign breast diseases. Diluted serum samples were applied to immobilized metal affinity capture Ciphergen ProteinChip Arrays previously activated with Ni2+. Proteins bound to the chelated metal were analyzed on a ProteinChip Reader Model PBS II. Complex protein profiles of different diagnostic groups were compared and analyzed using the ProPeak software package. RESULTS: A panel of three biomarkers was selected based on their collective contribution to the optimal separation between stage 0-I breast cancer patients and noncancer controls. The same separation was observed using independent test data from stage II-III breast cancer patients. Bootstrap cross-validation demonstrated that a sensitivity of 93% for all cancer patients and a specificity of 91% for all controls were achieved by a composite index derived by multivariate logistic regression using the three selected biomarkers. CONCLUSIONS: Proteomics approaches such as SELDI mass spectrometry, in conjunction with bioinformatics tools, could greatly facilitate the discovery of new and better biomarkers. The high sensitivity and specificity achieved by the combined use of the selected biomarkers show great potential for the early detection of breast cancer.