Original Article
Autoantibody Signatures in Prostate Cancer
N Engl J Med 2005; 353:1224-1235September 22, 2005
- Abstract
Background
New biomarkers, such as autoantibody signatures, may improve the early detection of prostate cancer.
Methods
With a phage-display library derived from prostate-cancer tissue, we developed and used phage protein microarrays to analyze serum samples from 119 patients with prostate cancer and 138 controls, with the samples equally divided into training and validation sets. A phage-peptide detector that was constructed from the training set was evaluated on an independent validation set of 128 serum samples (60 from patients with prostate cancer and 68 from controls).
Results
A 22-phage-peptide detector had 88.2 percent specificity (95 percent confidence interval, 0.78 to 0.95) and 81.6 percent sensitivity (95 percent confidence interval, 0.70 to 0.90) in discriminating between the group with prostate cancer and the control group. This panel of peptides performed better than did prostate-specific antigen (PSA) in distinguishing between the group with prostate cancer and the control group (area under the curve for the autoantibody signature, 0.93; 95 percent confidence interval, 0.88 to 0.97; area under the curve for PSA, 0.80; 95 percent confidence interval, 0.71 to 0.88). Logistic-regression analysis revealed that the phage-peptide panel provided additional discriminative power over PSA (P<0.001). Among the 22 phage peptides used as a detector, 4 were derived from in-frame, named coding sequences. The remaining phage peptides were generated from untranslated sequences.
Conclusions
Autoantibodies against peptides derived from prostate-cancer tissue could be used as the basis for a screening test for prostate cancer.
Media in This Article
Figure 1
Schematic Representation of the Development of Phage-Protein Microarrays to Characterize Autoantibody Signatures in Prostate Cancer (Discovery Phase).Figure 3
Autoantibody Signatures in Prostate Cancer.Article Activity
- Article
Limitations of the prostate-specific antigen (PSA) test for the early detection of prostate cancer1 indicate the need for other means of screening for this neoplasm. The finding that patients with cancer produce autoantibodies against antigens in their tumors2-7 suggests that such autoantibodies could have diagnostic and prognostic value.4,5,8-10 For example, mutant forms of the p53 protein elicit anti-p53 antibodies in 30 to 40 percent of patients with various types of cancers.11 Recently, we found that patients with prostate cancer produce antibodies against α-methylacyl-coenzyme A racemase,12 an overexpressed protein in epithelial cells in prostate cancer.13-15 This autoantibody had 72 percent specificity and 62 percent sensitivity in detecting prostate cancer.12 The use of additional prostate-cancer antigens could improve the sensitivity and specificity of an autoantibody-based screening test for prostate cancer.
Here we report the use of a technique that combines phage-display technology with protein microarrays to identify and characterize new autoantibody-binding peptides derived from prostate-cancer tissue. A similar approach has been used to identify selected antigens for the diagnosis of breast cancer.16 This emerging area of research, termed “cancer immunomics,” allows a global analysis of the autoantibodies against antigens in a neoplasm (see the Glossary
Glossary for definitions of terms).Methods
Populations and Samples
This study, which was approved by the institutional review board of the University of Michigan Medical School, started in March 2003 and ended in December 2004. It had discovery, training, and validation phases. All serum samples, unless otherwise indicated, were obtained from patients in the University of Michigan Health System. Written informed consent was obtained from all patients.
The tissue and serum bank at the University of Michigan Specialized Research Program in Prostate Cancer has collected more than 2000 serum samples since 1995. Of these, 331 samples, which were collected from 1995 to 2004, met the following eligibility criteria: they were obtained immediately before surgery from patients with biopsy-proven, clinically localized prostate cancer who were at least 40 years old and who had received no previous prostate-cancer therapy. Of the 331 samples, 150 were randomly chosen for the discovery, training, and validation phases of the study. Four samples were excluded because proteins had precipitated in the serum vials. Twelve samples that fulfilled the criteria were obtained from the Dana – Farber Cancer Institute for the validation phase in order to explore the robustness of the assay across institutions. These samples were chosen randomly from 236 samples that met the eligibility criteria.
The University of Michigan Clinical Pathology Laboratories provided 159 control samples of serum from men between the ages of 46 and 83 years who had no history of cancer. These samples were collected from 2001 to 2004 in three independent collection periods. An additional 55 samples (designated as the “other” category) were collected from patients after prostatectomy (14 samples) or from men with either advanced hormone-refractory prostate cancer (11) or lung cancer (30, randomly selected from 74 samples obtained from male patients). Details regarding the serum samples that were used in our “other” cohort are in the Supplementary Appendix (available with the full text of this article at www.nejm.org).
In the discovery phase (biopanning and 2304-element microarrays), 39 prostate-cancer samples and 21 control samples were used. The training phase involved the use of 59 prostate-cancer samples and 70 control samples. To evaluate the phage-peptide detectors that we developed in the discovery and training phases, we used an independent validation set of 60 prostate-cancer samples (48 from the University of Michigan and 12 from the Dana – Farber Cancer Institute) and 68 control samples. In addition, 55 samples in the “other” category were assessed exclusively in the validation phase.
In the 257 prostate-cancer samples and control samples (which included the training and validation sets [Table 1Table 1
Clinical and Pathological Information for the Training and Validation Samples.]), the median levels of PSA were 6.3 ng per milliliter (range, 0.1 to 46.3) and 1.7 ng per milliliter (range, 0.1 to 24.5), respectively.Autoantibody Profiling
By iterative biopanning (see Glossary) of a phage-display library derived from prostate-cancer tissues, we developed phage protein microarrays and used them to develop an autoantibody signature to distinguish samples with prostate cancer from those of controls. Details concerning the construction of phage-display libraries and preparation of the phage-protein microarrays are given in the Supplementary Appendix and shown in Figure 1Figure 1
Schematic Representation of the Development of Phage-Protein Microarrays to Characterize Autoantibody Signatures in Prostate Cancer (Discovery Phase)..Statistical Analysis
Statistical analyses were performed with SPSS software, version 11.5, and R 2.0. Details are given in the Supplementary Appendix.
Results
Development of Phage-Protein Microarrays (Discovery Phase)
To develop a phage-display library of prostate-cancer peptides, we isolated messenger RNA (mRNA) from prostate-cancer tissue obtained from six patients with clinically localized disease (Table 1 of the Supplementary Appendix). After the insertion of the complementary DNA (cDNA) fragments into the T7 phage system, peptides that were encoded by the prostate cancer cDNA were expressed and displayed on the surface of the phage fused to the C-terminal of the capsid 10B protein of the phage. This surface complex functioned as bait to capture autoantibodies in serum.
Serum samples from 39 patients with prostate cancer and 21 controls were selected randomly from the University of Michigan serum cohorts for the discovery phase. To enrich the library for peptides that bind specifically to autoantibodies in patients with prostate cancer, we carried out successive rounds of selection (Figure 1). The procedure entailed removal of irrelevant phages from the library with the use of protein A/G beads that were coated with a pool of IgG antibodies isolated from 10 randomly selected control serum samples (Figure 1, and Table 2 of the Supplementary Appendix). These beads were incubated with the phage particles, and the supernatant, which contained unbound phage particles, was collected. These residual phages, now freed of phage particles that bind to irrelevant antibodies in normal serum, were enriched for phage particles that express prostate-cancer–specific peptides by incubation with protein A/G beads coated with a pool of IgG antibodies from 19 patients with prostate cancer who were chosen randomly from the University of Michigan serum collection (Figure 1, and Table 2 of the Supplementary Appendix). Finally, the adherent phages were eluted from the beads and propagated in bacterial cells.
We carried out five such rounds of purification (biopanning). Phage clones, each bearing a single fusion peptide derived from the prostate-cancer cDNA library, were selected randomly from the purified library to generate protein microarrays on coated glass slides with the use of a robotic spotter. Once in a microarray format, the enriched phage clones were used to test serum for autoantibodies against prostate cancer peptides.
Initially, we selected 2304 individual phage clones, including 5 empty clones as negative controls, from the enriched phage library and constructed a high-density protein microarray (Figure 3 of the Supplementary Appendix). To decrease the complexity of subsequent validation studies and develop a focused array, we randomly selected 20 serum samples from patients with cancer and 11 samples from controls from the respective University of Michigan collections (Table 3 of the Supplementary Appendix) and screened the high-density phage microarray. Of the 20 samples from patients with prostate cancer, 19 contained antibodies that reacted with phage-peptide clones on the microarrays, whereas only 1 of 11 controls had such antibodies (Figure 3 of the Supplementary Appendix). After normalization of all values obtained by the scanner, we selected phage-peptide clones that yielded a ratio of Cy5 to Cy3 greater than 1.2 in at least one of the serum samples. This analysis identified 186 phage-peptide clones that reacted with serum samples from patients with prostate cancer. These clones, along with negative-control phage clones, were used to construct a smaller, focused protein microarray for subsequent screening of serum samples (training and validation phases).
Identification of a Phage-Peptide Detector (Training Phase)
Figure 2Figure 2
Overview of the Strategy Used for the Development and Validation of Autoantibody Signatures to Identify Prostate Cancer (Training and Validation Phases). shows the training and validation phases of this study. A total of 257 serum samples from 119 patients with clinically localized prostate cancer and 138 controls, plus 55 samples in the “other” category, were tested on the 186-element focused arrays (Table 1 and Table 4 through Table 9 of the Supplementary Appendix). In the training phase, we analyzed 59 samples from patients with prostate cancer and 70 control samples (Figure 2). An algorithm17 was used to evaluate whether the sample size we profiled was sufficient to build a classifier for clinical diagnosis. On the basis of this algorithm and with the use of the specific measures of our phage-protein microarray data, we found that a mean (±SD) of 46±40 samples from 1000 simulation runs would be sufficient to ensure with 95 percent confidence that the probability of the misclassification of a future sample would be less than 0.15. Figure 3Figure 3Autoantibody Signatures in Prostate Cancer. depicts representative scanned arrays. To create a “class detector,” we used a nonparametric-pattern-recognition approach that consisted of a genetic algorithm combined with k-nearest neighbor to select a subgroup of “informative” phage peptides based on leave-one-out cross-validation on the training samples. We identified a panel of 22 phage-peptide clones that could best distinguish serum samples from patients with prostate cancer from those of controls, with 97.1 percent specificity (2 of 70 control samples were misclassified) and 88.1 percent sensitivity (7 of 59 prostate-cancer samples were misclassified) in the training set (Table 10 and Table 11 of the Supplementary Appendix). Figure 4AFigure 4
Supervised Analyses and Validation of Autoantibody Signatures in Prostate Cancer. shows a heatmap of the results with the 22 phage-peptide clones in the training set.Validation of the Phage-Peptide Detector
With the use of a 22-phage-peptide detector derived from the training phase, we applied a weighted voting scheme to classify samples in the independent validation set (128 patients) as either prostate cancer or control (Figure 2). In total, 8 of 68 serum samples from controls and 11 of 60 samples from patients with prostate cancer were misclassified in this validation set (Figure 4B, and Table 12 of the Supplementary Appendix). These results yielded a specificity of 88.2 percent (95 percent confidence interval, 78 to 95) and a sensitivity of 81.6 percent (95 percent confidence interval, 70 to 90). Similar performance criteria were observed with the use of different class-prediction models and a second randomization of the data set (Section II of the Supplementary Appendix).
We next calculated receiver-operating-characteristic curves for the 22-phage-peptide detector and PSA levels in the validation set. Different cutoff values of weighted voting scores were used as threshold points to plot the true positive rate against the false positive rate for the prediction model. The ability of the panel of 22 phage peptides to discriminate between prostate-cancer samples and control samples was significant (P<0.001), with an area under the curve equal to 0.93 (95 percent confidence interval, 0.88 to 0.97) (Figure 4C). The area under the curve for PSA was 0.80 (P<0.001; 95 percent confidence interval, 0.71 to 0.88). This result was expected, since these patients were identified primarily by elevated PSA levels. Among patients with PSA levels of 4 to 10 ng per milliliter in the validation set, the phage-peptide detector had significant discriminatory power (P<0.001) as compared with PSA (P=0.50) in distinguishing serum samples from patients with prostate cancer from those of controls. The area under the curve was 0.93 (95 percent confidence interval, 0.86 to 1.00) for the phage-display method and 0.56 (95 percent confidence interval, 0.38 to 0.74) for PSA (Figure 4D). When the lower limit of PSA was decreased to 2.5 ng per milliliter, the discriminatory power of the phage-peptide profile was maintained (P<0.001), with an area under the curve of 0.94 (95 percent confidence interval, 0.88 to 1.00), whereas that for PSA decreased slightly to 0.50 (95 percent confidence interval, 0.33 to 0.66) (Figure 4E, and Section III of the Supplementary Appendix).
We also used the 22-phage-peptide detector to test the 55 serum samples in the “other” category. Among the samples obtained from patients after prostatectomy, 5 of 14 samples were classified as prostate cancer, and 3 of 11 samples from patients with hormone-refractory disease were classified as prostate cancer (Table 13 of the Supplementary Appendix). Of the 30 samples from patients with lung adenocarcinoma, 9 were classified as having prostate cancer, which suggests some cross-reactivity of autoantibodies across tumor types.
Characterization of the Phage-Peptide Detector
The panel of 22 phage-peptide clones was sequenced. Of these, five were in-frame and within known expressed sequences (Table 16 of the Supplementary Appendix). These five included bromodomain-containing protein 2 (BRD2), eukaryotic translation initiation factor 4 gamma 1 (eIF4G1), ribosomal protein L22 (RPL22), ribosomal protein L13a (RPL13a), and hypothetical protein XP_373908. Except for hypothetical protein XP_373908, these structures were derived from intracellular proteins involved in regulating either transcription or translation. The remaining 17 phage-peptide clones were either in untranslated regions of expressed genes or out of frame in the coding sequence of known genes. These clones may express peptides that are structurally similar to peptides in expressed proteins but are unrelated or weakly related at the protein-sequence level (Table 17 and section IV of the Supplementary Appendix).
To determine whether the four in-frame phage-peptide clones (Figure 5AFigure 5
Meta-Analysis of Gene Expression of Humoral-Immune-Response Candidates.) are deregulated in prostate cancer, we performed a meta-analysis of publicly available data regarding gene expression in prostate cancer.18-24 These analyses and a preliminary immunoblot analysis suggested that the four in-frame phage epitopes are overexpressed in prostate cancer (Figure 5B and Figure 5C, and sections V and VI of the Supplementary Appendix).Discussion
In this study, we used protein microarrays to identify autoantibodies against tumor antigens in patients with prostate cancer. Specifically, we constructed phage-protein microarrays in which peptides derived from a prostate-cancer cDNA library were expressed as a prostate-cancer – phage fusion protein. The phage-protein microarrays were screened to identify phage-peptide clones that bind autoantibodies in serum samples from patients with prostate cancer but not in those from controls.
The use of PSA-based screening for prostate cancer has risen dramatically since its introduction in the late 1980s.25,26 However, reliance on PSA for the detection of early prostate cancer is still unsatisfactory, especially because of a high rate of false positive results27 — as high as 80 percent.28,29 This rate results in many unnecessary prostate biopsies.30 To circumvent this and other problems of screening for prostate cancer, we have begun to evaluate the use of autoantibody signatures to detect prostate cancer. By relying on multiple immunogenic prostate-cancer peptides, this approach may be an improvement over a single biomarker such as PSA.
Serologic analysis of recombinant cDNA expression libraries of human tumors with autologous serum (SEREX) has demonstrated that antibodies in the serum of patients with cancer can be used to isolate new tumor antigens.3,4 This technique, however, relies on one-step screening without affinity-selection steps and requires a large volume of serum to screen phage clones blotted onto membrane filters. The SEREX approach has limited clinical use, since it is not conducive to the analysis of hundreds of serum samples of small amounts.
By taking advantage of combinatorial screening and high throughput analysis of autoantibody repertoires, we developed a technique that overcomes the disadvantages of SEREX for cancer diagnosis. However, like gene-expression profiling and pattern-recognition approaches with serum proteomics, our method may have the limitations of background signals, sample-selection bias, and limited reproducibility.31 To minimize these problems, immunoreactivity for each phage peptide was measured in relation to an internal control signal detected by antibody against phage capsid proteins. The discriminatory power of autoantibody signatures was validated by reshuffling and analyzing the training and validation sets with the use of various class-prediction models. The reproducibility of the assay was investigated by the use of experimental assays both within and among the arrays. The difference between duplicate peptides in the same array was less than 5 percent for 98 percent of the spots. Analyses of repeated experiments with the use of the same serum samples revealed that the results were very consistent, with a correlation coefficient greater than 98 percent.
The autoantibody signature was detected in only 5 of 14 serum samples from patients who had undergone prostatectomy and in 3 of 11 serum samples from patients with hormone-refractory disease — a finding suggesting that the autoantibody profile is attenuated on removal of the “immunogen” or treatment with antiandrogens, chemotherapeutic agents, or both. Of 30 serum samples from patients with lung cancer, 9 were classified as prostate cancer. This result is in contrast to the more than 80 percent sensitivity for prostate cancer with the use of the phage-peptide system, suggesting that the autoantibody profile has relative specificity for prostate cancer (P<0.001 by the proportion test).
Our results were consistent across a range of clinical and pathological features, including PSA level, Gleason grade, stage, and presence or absence of PSA recurrence (Table 18 of the Supplementary Appendix), with sensitivities and specificities ranging from 80 to 90 percent in discriminating between patients with prostate cancer and controls. This diagnostic performance was maintained in the intermediate ranges of PSA (i.e., 4 to 10 ng per milliliter or 2.5 to 10 ng per milliliter).
Autoantibody signatures may be useful in combination with initial PSA screening; our data show that the 22-phage-peptide detector significantly adds to the diagnostic power of PSA alone (P<0.001). The use of such a “supplementary” autoantibody panel might be important at PSA levels of 10 ng per milliliter or less. This additional discriminatory power could improve the information used to make decisions about biopsy of the prostate.
The sequences in the phage display system are probably those of relatively short peptides rather than full-length proteins, since the cDNAs were enzyme-digested and fragmented before ligation into the phage vector. The average stretch of peptides in the 22-phage-peptide detector was 53±34 amino acids, with a maximum length of 134 residues and a minimum of 11 residues.
Four of the phage clones representing known proteins — BRD2, eIF4G1, RPL13a, and RPL22 — were substantially more reactive with serum from patients with prostate cancer than with that from controls (Figure 5A). Both meta-analysis and immunoblot analysis of tissue extracts suggest that all four proteins are deregulated in prostate tumors. Immunofluorescence of tissue sections and immunohistochemical analysis of tissue microarrays showed that eIF4G1 was overexpressed in prostate-cancer epithelial tissue, as compared with benign epithelial tissue (Figure 5D and Figure 5E, and Figure 5 and Section VI of the Supplementary Appendix).
Of the 22 phage peptides identified in this study, 17 are not present in peptide stretches in known proteins. These 17 peptides may be weakly homologous to known proteins or may have no distinct homology to the primary sequences of known proteins and thus may be “mimotopes” (i.e., stretches of amino acids that mimic an antigen but are not homologous at the sequence level).
We have not tested the phage-microarray system for screening for prostate cancer; this requires extension and confirmation in community-based screening cohorts. It will be important to evaluate the autoantibody signatures associated with prostate cancer in patients with prostatitis, autoimmune conditions, and other diseases. Although the technique is promising, how it will perform in prospective and multiinstitutional studies remains to be determined.
Supported by National Cancer Institute grants (UO1CA111275, to Drs. Chinnaiyan, Rubin, Ghosh, Sanda, and Wei, and P50 CA69568, to Drs. Pienta, Chinnaiyan, Montie, Rubin, Sanda, and Ghosh); National Institutes of Health grants (R01 CA8241901-A1, to Dr. Sanda, and R01GM72007-01, to Dr. Ghosh); a grant (RSG-02-179-MGO, to Drs. Chinnaiyan, Rubin, and Ghosh) from the American Cancer Society; a grant (to Dr. Chinnaiyan) from the V Foundation; grants (W81XWH-04-1-0886, to Dr. Wang; DMAD17-03-0105, to Dr. Sreekumar, and PC040517, to Dr. Mehra) from the Department of Defense; and a grant (5P30CA46592) from the Cancer Center Bioinformatics Core. Dr. Chinnaiyan is a Pew Biomedical Scholar.
Drs. Wang and Yu contributed equally to this article.
We are indebted to Dr. Saravana M. Dhanasekaran for providing samples of prostate-cancer mRNA, to Dr. Paul L. Fox of the Lerner Research Institute in Cleveland for providing anti-RPL13a antibody, to Jason Harwood and Srilakshmi Bhagavathula of the Prostate Tissue and Informatics Core for the collection of serum samples and integration of associated clinical information, to Drs. David Beer and Guoan Chen for providing serum samples from patients with lung cancer as control samples for nonprostate cancer, to Drs. Francesca Demichelis and Jeremy Taylor for providing additional statistical consultation, to Jeffrey Fielhauer for his help with sequence analysis and preparation of the manuscript, and to the staff of the microscopy and image analyses laboratory at the University of Michigan.
Source Information
From the Departments of Pathology (X.W., J.Y., A.S., S.V., R.S., D. Giacherio, R.M., A.M.C.), Biostatistics (R.S., D. Ghosh), Urology (J.E.M., K.J.P., J.T.W., A.M.C.), and Internal Medicine (K.J.P.), and the Comprehensive Cancer Center (A.S., S.V., J.E.M., K.J.P., J.T.W., A.M.C.), University of Michigan Medical School, Ann Arbor; and Beth Israel – Deaconess Medical Center (M.G.S.), Dana – Farber Cancer Institute (P.W.K.), and Brigham and Women's Hospital (M.A.R.), Harvard Medical School — all in Boston.
Address reprint requests to Dr. Chinnaiyan at the Department of Pathology and Urology, University of Michigan Medical School, 1301 Catherine St., MSI 4237, University of Michigan, Ann Arbor, MI 48109, or at arul@umich.edu.
- References
References
1
Thompson IM ,Pauler DK ,Goodman PJ , et al. Prevalence of prostate cancer among men with a prostate-specific antigen level ≤4.0 ng per milliliter. N Engl J Med 2004;350:2239-2246[Erratum, N Engl J Med 2004;351:1470.]
Full Text | Web of Science | Medline2
Sahin U ,Tureci O ,Schmitt H , et al. Human neoplasms elicit multiple specific immune responses in the autologous host. Proc Natl Acad Sci U S A 1995;92:11810-11813
CrossRef | Web of Science | Medline3
Chen YT ,Gure AO ,Tsang S , et al. Identification of multiple cancer/testis antigens by allogeneic antibody screening of a melanoma cell line library. Proc Natl Acad Sci U S A 1998;95:6919-6923
CrossRef | Web of Science | Medline4
Stockert E ,Jager E ,Chen YT , et al. A survey of the humoral immune response of cancer patients to a panel of human tumor antigens. J Exp Med 1998;187:1349-1354
CrossRef | Web of Science | Medline5
Brichory FM ,Misek DE ,Yim AM , et al. An immune response manifested by the common occurrence of annexins I and II autoantibodies and high circulating levels of IL-6 in lung cancer. Proc Natl Acad Sci U S A 2001;98:9824-9829
CrossRef | Web of Science | Medline6
Minenkova O ,Pucci A ,Pavoni E , et al. Identification of tumor-associated antigens by screening phage-displayed human cDNA libraries with sera from tumor patients. Int J Cancer 2003;106:534-544
CrossRef | Web of Science | Medline7
Zhong L ,Peng X ,Hidalgo GE ,Doherty DE ,Stromberg AJ ,Hirschowitz EA . Antibodies to HSP70 and HSP90 in serum in non-small cell lung cancer patients. Cancer Detect Prev 2003;27:285-290
CrossRef | Web of Science | Medline8
Old LJ ,Chen YT . New paths in human cancer serology. J Exp Med 1998;187:1163-1167
CrossRef | Web of Science | Medline9
Nilsson BO ,Carlsson L ,Larsson A ,Ronquist G . Autoantibodies to prostasomes as new markers for prostate cancer. Ups J Med Sci 2001;106:43-49
CrossRef | Web of Science | Medline10
Mintz PJ ,Kim J ,Do KA , et al. Fingerprinting the circulating repertoire of antibodies from cancer patients. Nat Biotechnol 2003;21:57-63
CrossRef | Web of Science | Medline11
Soussi T . p53 Antibodies in the sera of patients with various types of cancer: a review. Cancer Res 2000;60:1777-1788
Web of Science | Medline12
Sreekumar A ,Laxman B ,Rhodes DR , et al. Humoral immune response to alpha-methylacyl-CoA racemase and prostate cancer. J Natl Cancer Inst 2004;96:834-843[Erratum, J Natl Cancer Inst 2004;96:1112.]
CrossRef | Web of Science | Medline13
Luo J ,Zha S ,Gage WR , et al. Alpha-methylacyl-CoA racemase: a new molecular marker for prostate cancer. Cancer Res 2002;62:2220-2226
Web of Science | Medline14
Jiang Z ,Woda BA ,Rock KL , et al. P504S: a new molecular marker for the detection of prostate carcinoma. Am J Surg Pathol 2001;25:1397-1404
CrossRef | Web of Science | Medline15
Rubin MA ,Zhou M ,Dhanasekaran SM , et al. alpha-Methylacyl coenzyme A racemase as a tissue biomarker for prostate cancer. JAMA 2002;287:1662-1670
CrossRef | Web of Science | Medline16
Fernandez-Madrid F ,Tang N ,Alansari H , et al. Autoantibodies to annexin XI-A and other autoantigens in the diagnosis of breast cancer. Cancer Res 2004;64:5089-5096
CrossRef | Web of Science | Medline17
Fu WJ ,Dougherty ER ,Mallick B ,Carroll RJ . How many samples are needed to build a classifier: a general sequential approach. Bioinformatics 2005;21:63-70
CrossRef | Web of Science | Medline18
Dhanasekaran SM ,Barrette TR ,Ghosh D , et al. Delineation of prognostic biomarkers in prostate cancer. Nature 2001;412:822-826
CrossRef | Web of Science | Medline19
LaTulippe E ,Satagopan J ,Smith A , et al. Comprehensive gene expression analysis of prostate cancer reveals distinct transcriptional programs associated with metastatic disease. Cancer Res 2002;62:4499-4506
Web of Science | Medline20
Luo JH ,Yu YP ,Cieply K , et al. Gene expression analysis of prostate cancers. Mol Carcinog 2002;33:25-35
CrossRef | Web of Science | Medline21
Luo J ,Duggan DJ ,Chen Y , et al. Human prostate cancer and benign prostatic hyperplasia: molecular dissection by gene expression profiling. Cancer Res 2001;61:4683-4688
Web of Science | Medline22
Singh D ,Febbo PG ,Ross K , et al. Gene expression correlates of clinical prostate cancer behavior. Cancer Cell 2002;1:203-209
CrossRef | Web of Science | Medline23
Welsh JB ,Sapinoso LM ,Su AI , et al. Analysis of gene expression identifies candidate markers and pharmacological targets in prostate cancer. Cancer Res 2001;61:5974-5978
Web of Science | Medline24
Rhodes DR ,Yu J ,Shanker K , et al. ONCOMINE: a cancer microarray database and integrated data-mining platform. Neoplasia 2004;6:1-6
Web of Science | Medline25
Jemal A ,Tiwari RC ,Murray T , et al. Cancer statistics, 2004. CA Cancer J Clin 2004;54:8-29
CrossRef | Web of Science | Medline26
Dennis LK ,Resnick MI . Analysis of recent trends in prostate cancer incidence and mortality. Prostate 2000;42:247-252
CrossRef | Web of Science | Medline27
Schmid HP ,Prikler L ,Semjonow A . Problems with prostate-specific antigen screening: a critical review. Recent Results Cancer Res 2003;163:226-231
CrossRef | Medline28
Catalona WJ ,Smith DS ,Ratliff TL , et al. Measurement of prostate-specific antigen in serum as a screening test for prostate cancer. N Engl J Med 1991;324:1156-1161[Erratum, N Engl J Med 1991;325:1324.]
Full Text | Web of Science | Medline29
Makinen T ,Tammela TL ,Stenman UH , et al. Second round results of the Finnish population-based prostate cancer screening trial. Clin Cancer Res 2004;10:2231-2236
CrossRef | Web of Science | Medline30
Cohen L ,Fouladi RT ,Babaian RJ , et al. Cancer worry is associated with abnormal prostate-specific antigen levels in men participating in a community screening program. Cancer Epidemiol Biomarkers Prev 2003;12:610-617
Medline31
Ransohoff DF . Bias as a threat to the validity of cancer molecular-marker research. Nat Rev Cancer 2005;5:142-149
CrossRef | Web of Science | Medline
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Bradley T. Messmer, Talia S. Nour-Omid, Emanuela Ghia, Ana B. Sanchez, Thomas J. Kipps. (2011) Autoantibodies against p53 are associated with chromosome 17p deletions in chronic lymphocytic leukemia. Leukemia Research 35:7, 965-967
CrossRef14
Caroline Desmetz, Jérôme Lacombe, Alain Mange, Thierry Maudelonde, Jérôme Solassol. (2011) Autoanticorps et diagnostic précoce des cancers. médecine/sciences 27:6-7, 633-638
CrossRef15
H Benjamin Larman, Zhenming Zhao, Uri Laserson, Mamie Z Li, Alberto Ciccia, M Angelica Martinez Gakidis, George M Church, Santosh Kesari, Emily M LeProust, Nicole L Solimini, Stephen J Elledge. (2011) Autoantigen discovery with a synthetic human peptidome. Nature Biotechnology 29:6, 535-541
CrossRef16
William H Robinson, Lawrence Steinman. (2011) Human peptidome display. Nature Biotechnology 29:6, 500-502
CrossRef17
Jerome Solassol, Thierry Maudelonde, Alain Mange, Jean-Louis Pujol. (2011) Clinical Relevance of Autoantibody Detection in Lung Cancer. Journal of Thoracic Oncology 6:5, 955-962
CrossRef18
Chung-Wei Fan, Chung-Chuan Chan, Kuei-Tien Chen, Jen Twu, Ya-Shu Huang, Chia-Li Han, Yu-Ju Chen, Jau-Song Yu, Yu-Sun Chang, Yung-Bin Kuo, Err-Cheng Chan. (2011) Identification of SEC61β and its autoantibody as biomarkers for colorectal cancer. Clinica Chimica Acta 412:11-12, 887-893
CrossRef19
Mi-Kyung Woo, Chang-Kyu Heo, Hae-Min Hwang, Jeong-Heon Ko, Hyang-Sook Yoo, Eun-Wie Cho. (2011) Optimization of phage-immobilized ELISA for autoantibody profiling in human sera. Biotechnology Letters 33:4, 655-661
CrossRef20
Shashi A Gujar, Da Pan, Paola Marcato, Katy A Garant, Patrick WK Lee. (2011) Oncolytic Virus-initiated Protective Immunity Against Prostate Cancer. Molecular Therapy 19:4, 797-804
CrossRef21
Nicole Ludwig, Andreas Keller, Sabrina Heisel, Petra Leidinger, Stefanie Rheinheimer, Claudia Andres, Bernhard Stephan, Wolf-Ingo Steudel, Erich Donauer, Norbert Graf, Bernhard Burgeth, Joachim Weickert, Hans-Peter Lenhof, Eckart Meese. (2011) Novel immunogenic antigens increase classification accuracy in meningioma to 93.84%. International Journal of Cancer 128:6, 1493-1501
CrossRef22
Burcu Ayoglu, Anna Häggmark, Maja Neiman, Ulrika Igel, Mathias Uhlén, Jochen M Schwenk, Peter Nilsson. (2011) Systematic antibody and antigen-based proteomic profiling with microarrays. Expert Review of Molecular Diagnostics 11:2, 219-234
CrossRef23
Brett B. Maricque, Jens C. Eickhoff, Douglas G. McNeel. (2011) Antibody responses to prostate-associated antigens in patients with prostatitis and prostate cancer. The Prostate 71:2, 134-146
CrossRef24
Klaartje Somers, Piet Geusens, Dirk Elewaut, Filip De Keyser, Jean-Luc Rummens, Marieke Coenen, Marlies Blom, Piet Stinissen, Veerle Somers. (2011) Novel autoantibody markers for early and seronegative rheumatoid arthritis. Journal of Autoimmunity 36:1, 33-46
CrossRef25
Jana Schmitt, Sabrina Heisel, Andreas Keller, Petra Leidinger, Nicole Ludwig, Nunja Habel, Rhoikos Furtwängler, Nasenien Nourkami-Tutdibi, Jenny Wegert, Paul Grundy, Manfred Gessler, Norbert Graf, Hans-Peter Lenhof, Eckart Meese. (2011) Multicenter study identified molecular blood-born protein signatures for Wilms Tumor. International Journal of Cancern/a-n/a
CrossRef26
M. Muralidhar Reddy, Rosemary Wilson, Johnnie Wilson, Steven Connell, Anne Gocke, Linda Hynan, Dwight German, Thomas Kodadek. (2011) Identification of Candidate IgG Biomarkers for Alzheimer's Disease via Combinatorial Library Screening. Cell 144:1, 132-142
CrossRef27
Christina Backes, Nicole Ludwig, Petra Leidinger, Christian Harz, Jana Hoffmann, Andreas Keller, Eckart Meese, Hans-Peter Lenhof. (2011) Immunogenicity of autoantigens. BMC Genomics 12:1, 340
CrossRef28
Heath A. Smith, Brett B. Maricque, John Eberhardt, Benjamin Petersen, James L. Gulley, Jeffrey Schlom, Douglas G. McNeel. (2011) IgG Responses to Tissue-Associated Antigens as Biomarkers of Immunological Treatment Efficacy. Journal of Biomedicine and Biotechnology 2011, 1-10
CrossRef29
Chong Xie, Hyun J Kim, Jonathan G Haw, Anusha Kalbasi, Brian K Gardner, Gang Li, Jianyu Rao, David Chia, Monty Liong, Rubio R Punzalan, Leonard S Marks, Allan J Pantuck, Alexandre de la Taille, Guomin Wang, Hideki Mukouyama, Gang Zeng. (2011) A novel multiplex assay combining autoantibodies plus PSA has potential implications for classification of prostate cancer from non-malignant cases. Journal of Translational Medicine 9:1, 43
CrossRef30
T. Liu, R. Xue, L. Dong, H. Wu, D. Zhang, X. Shen. (2011) Rapid determination of serological cytokine biomarkers for hepatitis B virus-related hepatocellular carcinoma using antibody microarrays. Acta Biochimica et Biophysica Sinica 43:1, 45-51
CrossRef31
Daniel J. Zabransky, Heath A. Smith, Christopher J. Thoburn, Marianna Zahurak, Daniel Keizman, Michael Carducci, Mario A. Eisenberger, Douglas G. McNeel, Charles G. Drake, Emmanuel S. Antonarakis. (2011) Lenalidomide modulates IL-8 and anti-prostate antibody levels in men with biochemically recurrent prostate cancer. The Prostaten/a-n/a
CrossRef32
Magdalena Kowalewska, Radoslawa Nowak, Magdalena Chechlinska. (2010) Implications of cancer-associated systemic inflammation for biomarker studies. Biochimica et Biophysica Acta (BBA) - Reviews on Cancer 1806:2, 163-171
CrossRef33
Elfriede Simon. (2010) Biological and chemical sensors for cancer diagnosis. Measurement Science and Technology 21:11, 112002
CrossRef34
Pengfei Zhou, Junzhuan Qiu, Lawrence LʼItalien, Danling Gu, Douglas Hodges, Cheng-Chi Chao, Xiao Min Schebye. (2010) Mature B Cells Are Critical to T-cell-mediated Tumor Immunity Induced by an Agonist Anti-GITR Monoclonal Antibody. Journal of Immunotherapy 33:8, 789-797
CrossRef35
D. Bianchini, A. Zivi, S. Sandhu, J. S. de Bono. (2010) Horizon scanning for novel therapeutics for the treatment of prostate cancer. Annals of Oncology 21:Supplement 7, vii43-vii55
CrossRef36
Maarten Naesens, Minnie M. Sarwal. (2010) Molecular diagnostics in transplantation. Nature Reviews Nephrology 6:10, 614-628
CrossRef37
Vincent Ricchiuti. 2010. Immunoassay-Based Technologies for the Measurement of Biological Materials Used for Biomarkers Discovery and Translational Research. , 425-455.
CrossRef38
Ting-hu CAO, Wen-jun CHANG, Jin-xin HU, Jun ZHU, Guang-wen CAO. (2010) Prediction of B cell epitopes of tumor-associated protein EIF4G1 subtypes. Academic Journal of Second Military Medical University 30:8, 822-825
CrossRef39
Beihai Jiang, Tingting Ren, Bin Dong, Like Qu, Genglin Jin, Jianning Li, Hong Qu, Lin Meng, Caiyun Liu, Jian Wu, Chengchao Shou. (2010) Peptide Mimic Isolated by Autoantibody Reveals Human Arrest Defective 1 Overexpression Is Associated with Poor Prognosis for Colon Cancer Patients. The American Journal of Pathology 177:3, 1095-1103
CrossRef40
Antonietta Parracino, Maria Teresa Neves-Petersen, Ane Kold di Gennaro, Kim Pettersson, Timo Lövgren, Steffen B. Petersen. (2010) Arraying prostate specific antigen PSA and Fab anti-PSA using light-assisted molecular immobilization technology. Protein Science 19:9, 1751-1759
CrossRef41
R M Parry, W Jones, T H Stokes, J H Phan, R A Moffitt, H Fang, L Shi, A Oberthuer, M Fischer, W Tong, M D Wang. (2010) k-Nearest neighbor models for microarray gene expression analysis and clinical outcome prediction. The Pharmacogenomics Journal 10:4, 292-309
CrossRef42
Fernanda I. Staquicini, Benjamin J. Moeller, Wadih Arap, Renata Pasqualini. (2010) Combinatorial vascular targeting in translational medicine. PROTEOMICS - Clinical Applications 4:6-7, 626-632
CrossRef43
Sebastian Kobold, Tim Lütkens, Yanran Cao, Carsten Bokemeyer, Djordje Atanackovic. (2010) Autoantibodies against tumor-related antigens: Incidence and biologic significance. Human Immunology 71:7, 643-651
CrossRef44
Ling-ling WU, Fu-ao CAO, Wen-jun CHANG, Chuan-gang FU, Guang-wen CAO. (2010) Screening of molecular markers for early diagnosis of colorectal cancer by phage-peptide library. Academic Journal of Second Military Medical University 30:5, 549-552
CrossRef45
Yoshiya Yonekubo, Ping Wu, Aimalohi Esechie, Yueqiang Zhang, Guangwei Du. (2010) Characterization of new serum biomarkers in breast cancer using lipid microarrays. Tumor Biology 31:3, 181-187
CrossRef46
Rui Liu, Kui Wang, Kefei Yuan, Yuquan Wei, Canhua Huang. (2010) Integrative oncoproteomics strategies for anticancer drug discovery. Expert Review of Proteomics 7:3, 411-429
CrossRef47
Emmanuel S Antonarakis, Charles G Drake. (2010) Current status of immunological therapies for prostate cancer. Current Opinion in Urology 20:3, 241-246
CrossRef48
Charles G. Drake, Emmanuel S. Antonarakis. (2010) Update: Immunological Strategies for Prostate Cancer. Current Urology Reports 11:3, 202-207
CrossRef49
Emmanuel S. Antonarakis, Michael A. Carducci, Mario A. Eisenberger. (2010) Novel targeted therapeutics for metastatic castration-resistant prostate cancer. Cancer Letters 291:1, 1-13
CrossRef50
Marta Sanchez-Carbayo. (2010) Antibody array-based technologies for cancer protein profiling and functional proteomic analyses using serum and tissue specimens. Tumor Biology 31:2, 103-112
CrossRef51
Jian-Ying Zhang, Eng M Tan. (2010) Autoantibodies to tumor-associated antigens as diagnostic biomarkers in hepatocellular carcinoma and other solid tumors. Expert Review of Molecular Diagnostics 10:3, 321-328
CrossRef52
Peter A. Ward, Kent J. Johnson. 2010. Integrating Academic Laboratories Into Pharmaceutical Development. .
CrossRef53
Yao Chen, Yusen Zhou, Suimin Qiu, Kaijuan Wang, Siwei Liu, Xuan-Xian Peng, Junfeng Li, Eng M. Tan, Jian-Ying Zhang. (2010) Autoantibodies to tumor-associated antigens combined with abnormal alpha-fetoprotein enhance immunodiagnosis of hepatocellular carcinoma. Cancer Letters 289:1, 32-39
CrossRef54
Xiao Yao, Hua Jiang, Cuizhen Zhang, Huamao Wang, Lin Yang, Yongfeng Yu, Junming Yu, Bizhi Shi, Zhijun Shen, Huiping Gao, Zhiwei Chen, Shujun Tian, Shun Lu, Zonghai Li, Jianren Gu. (2010) Dickkopf-1 autoantibody is a novel serological biomarker for non-small cell lung cancer. Biomarkers 15:2, 128-134
CrossRef55
Rodrigo Barderas, Ingrid Babel, José Ignacio Casal. (2010) Colorectal cancer proteomics, molecular characterization and biomarker discovery. PROTEOMICS - CLINICAL APPLICATIONS 4:2, 159-178
CrossRef56
Sebastian Kobold, Tim Luetkens, Yanran Cao, Carsten Bokemeyer, Djordje Atanackovic. (2010) Prognostic and Diagnostic Value of Spontaneous Tumor-Related Antibodies. Clinical and Developmental Immunology 2010, 1-8
CrossRef57
Sunghoon Kim, HanByoul Cho, Eun Ji Nam, Sang Wun Kim, Young Tae Kim, Yong Won Park, Bo Wook Kim, Jae-Hoon Kim. (2010) Autoantibodies against stress-induced phosphoprotein-1 as a novel biomarker candidate for ovarian cancer. Genes, Chromosomes and CancerNA-NA
CrossRef58
Amanda Beth Reed, Dipen J Parekh. (2010) Biomarkers for prostate cancer detection. Expert Review of Anticancer Therapy 10:1, 103-114
CrossRef59
Lucas Nogueira, Renato Corradi, James A. Eastham. (2010) Other biomarkers for detecting prostate cancer. BJU International 105:2, 166-169
CrossRef60
Chung-Chuan Chan, Chung-Wei Fan, Yung-Bin Kuo, Yu-Han Chen, Pi-Yueh Chang, Kuei-Tien Chen, Ray-Ping Hung, Err-Cheng Chan. (2010) Multiple serological biomarkers for colorectal cancer detection. International Journal of CancerNA-NA
CrossRef61
Michael A. Tainsky. 2009. Oncology Biomarkers. .
CrossRef62
Joshua M Lang, Adin-Cristian Andrei, Douglas G McNeel. (2009) Prioritization of cancer antigens: keeping the target in sight. Expert Review of Vaccines 8:12, 1657-1661
CrossRef63
Hossein Borghaei, Mitchell R. Smith, Kerry S. Campbell. (2009) Immunotherapy of cancer. European Journal of Pharmacology 625:1-3, 41-54
CrossRef64
Michael A. Tainsky. (2009) Genomic and proteomic biomarkers for cancer: A multitude of opportunities. Biochimica et Biophysica Acta (BBA) - Reviews on Cancer 1796:2, 176-193
CrossRef65
Hwee Tong Tan, Jiayi Low, Seng Gee Lim, Maxey C. M. Chung. (2009) Serum autoantibodies as biomarkers for early cancer detection. FEBS Journal 276:23, 6880-6904
CrossRef66
Joaquim Bellmunt, Jonathan E. Rosenberg, Toni K. Choueiri. (2009) Recent Progress and Pitfalls in Testing Novel Agents in Castration-Resistant Prostate Cancer. European Urology 56:4, 606-608
CrossRef67
Jin-feng ZHAO, Ling-ling WU, Wen-jun CHANG, Sheng-dong HUANG, Yong-wei YU, Li-jun ZHAO, Yi-jia CHEN, Guang-wen CAO. (2009) Screening for molecular markers for early diagnosis of lung cancer by bacteriphage display. Academic Journal of Second Military Medical University 28:10, 1157-1161
CrossRef68
Sejal S. Hall, Patrick S. Daugherty. (2009) Quantitative specificity-based display library screening identifies determinants of antibody-epitope binding specificity. Protein Science 18:9, 1926-1934
CrossRef69
Andreas Keller, Nicole Ludwig, Sabrina Heisel, Petra Leidinger, Claudia Andres, Wolf-Ingo Steudel, Hanno Huwer, Bernhard Burgeth, Matthias Hein, Joachim Weickert, Eckart Meese, Hans-Peter Lenhof. (2009) Large-scale antibody profiling of human blood sera: The future of molecular diagnosis. Informatik-Spektrum 32:4, 332-338
CrossRef70
Caroline Desmetz, Thierry Maudelonde, Alain Mangé, Jerome Solassol. (2009) Identifying autoantibody signatures in cancer: a promising challenge. Expert Review of Proteomics 6:4, 377-386
CrossRef71
Phillip G. Febbo. (2009) Genomic approaches to outcome prediction in prostate cancer. Cancer 115:S13, 3046-3057
CrossRef72
Albert Hsiao, Michael D. Kuo. (2009) High-throughput Biology in the Postgenomic Era. Journal of Vascular and Interventional Radiology 20:7, S488-S496
CrossRef73
Dimitra Sasaroli, George Coukos, Nathalie Scholler. (2009) Beyond CA125: the coming of age of ovarian cancer biomarkers. Biomarkers in Medicine 3:3, 275-288
CrossRef74
Brian Nolen, Matt Winans, Adele Marrangoni, Anna Lokshin. (2009) Aberrant tumor-associated antigen autoantibody profiles in healthy controls detected by multiplex bead-based immunoassay. Journal of Immunological Methods 344:2, 116-120
CrossRef75
Yves Fradet. (2009) Biomarkers in prostate cancer diagnosis and prognosis: beyond prostate-specific antigen. Current Opinion in Urology 19:3, 243-246
CrossRef76
Borros M. Arneth. (2009) Error calculation for the PSA quotient. Clinical Biochemistry 42:7-8, 722-724
CrossRef77
George Botchorishvili, Mika P Matikainen, Hans Lilja. (2009) Early prostate-specific antigen changes and the diagnosis and prognosis of prostate cancer. Current Opinion in Urology 19:3, 221-226
CrossRef78
Mohd. Fahad Ullah, Mohammad Aatif. (2009) The footprints of cancer development: Cancer biomarkers. Cancer Treatment Reviews 35:3, 193-200
CrossRef79
Marcel Ferrer-Alcón, David Arteta, M.ª José Guerrero, Dietmar Fernandez-Orth, Laureano Simón, Antonio Martinez. (2009) The use of gene array technology and proteomics in the search of new targets of diseases for therapeutics. Toxicology Letters 186:1, 45-51
CrossRef80
Jon Ladd, Hailing Lu, Allen D. Taylor, Vivian Goodell, Mary L. Disis, Shaoyi Jiang. (2009) Direct detection of carcinoembryonic antigen autoantibodies in clinical human serum samples using a surface plasmon resonance sensor. Colloids and Surfaces B: Biointerfaces 70:1, 1-6
CrossRef81
David Knight, Amy C. Peterson, Brian I. Rini, Helena Harlin, Thomas F. Gajewski, Walter M. Stadler. (2009) The HLA-A2-restricted PSMA peptide LLHETDSAV is poorly immunogenic in patients with metastatic prostate cancer. The Prostate 69:2, 142-148
CrossRef82
Robert J. Caiazzo, Andrew J. Maher, Michael P. Drummond, Corey I. Lander, Oliver W. Tassinari, Bryce P. Nelson, Brian C.-S. Liu. (2009) Protein microarrays as an application for disease biomarkers. PROTEOMICS - CLINICAL APPLICATIONS 3:2, 138-147
CrossRef83
Sacha Gnjatic, Colin Wheeler, Martin Ebner, Erika Ritter, Anne Murray, Nasser K. Altorki, Cathy A. Ferrara, Henry Hepburne-Scott, Sarah Joyce, Jens Koopman, Michael B. McAndrew, Nicholas Workman, Gerd Ritter, Rachel Fallon, Lloyd J. Old. (2009) Seromic analysis of antibody responses in non-small cell lung cancer patients and healthy donors using conformational protein arrays. Journal of Immunological Methods 341:1-2, 50-58
CrossRef84
W. Liu, P. Wang, Z. Li, W. Xu, L. Dai, K. Wang, J. Zhang. (2009) Evaluation of Tumour-Associated Antigen (TAA) Miniarray in Immunodiagnosis of Colon Cancer. Scandinavian Journal of Immunology 69:1, 57-63
CrossRef85
Alyona Sukhanova, Igor Nabiev. (2008) Fluorescent nanocrystal-encoded microbeads for multiplexed cancer imaging and diagnosis. Critical Reviews in Oncology/Hematology 68:1, 39-59
CrossRef86
Petra Leidinger, Andreas Keller, Nicole Ludwig, Stefanie Rheinheimer, Jürg Hamacher, Hanno Huwer, Ingo Stehle, Hans-Peter Lenhof, Eckart Meese. (2008) Toward an early diagnosis of lung cancer: An autoantibody signature for squamous cell lung carcinoma. International Journal of Cancer 123:7, 1631-1636
CrossRef87
Niroshan Ramachandran, Sanjeeva Srivastava, Joshua LaBaer. (2008) Applications of protein microarrays for biomarker discovery. PROTEOMICS - CLINICAL APPLICATIONS 2:10-11, 1444-1459
CrossRef88
Niroshan Ramachandran, Karen S. Anderson, Jacob V. Raphael, Eugenie Hainsworth, Sahar Sibani, Wagner R. Montor, Marcin Pacek, Jessica Wong, Mariam Eljanne, Martin G. Sanda, Yanhui Hu, Tanya Logvinenko, Joshua LaBaer. (2008) Tracking humoral responses using self assembling protein microarrays. PROTEOMICS - CLINICAL APPLICATIONS 2:10-11, 1518-1527
CrossRef89
Vathany Kulasingam, Eleftherios P Diamandis. (2008) Strategies for discovering novel cancer biomarkers through utilization of emerging technologies. Nature Clinical Practice Oncology 5:10, 588-599
CrossRef90
M L Ramírez, E C Nelson, C P Evans. (2008) Beyond prostate-specific antigen: alternate serum markers. Prostate Cancer and Prostatic Diseases 11:3, 216-229
CrossRef91
L. Beneduce, G. Pesce, A. Gallotta, F. Zampieri, A. Biasiolo, N. Tono, N. Boscato, A. Gatta, P. Pontisso, G. Fassina. (2008) Tumour-specific induction of immune complexes: DCP-IgM in hepatocellular carcinoma. European Journal of Clinical Investigation 38:8, 571-577
CrossRef92
Yong-Qing Tong, Zhi-Jie Zhang, Bei Liu, Jian Huang, Hui Liu, Yan Liu, Feng-Jie Guo, Guo-Hua Zhou, Ping-Li Xie, Yue-Hui Li, Chao-Hu Zuo, Jin-Yue Hu, Guan-Cheng Li. (2008) Autoantibodies as potential biomarkers for nasopharyngeal carcinoma. PROTEOMICS 8:15, 3185-3193
CrossRef93
Donald B. Bloch, Thomas J. Wang, Robert E. Gerszten. (2008) Novel antibody markers of unstable atherosclerotic lesions. Journal of Clinical Investigation
CrossRef94
Kitty B.J.M. Cleutjens, Birgit C.G. Faber, Mat Rousch, Ruben van Doorn, Tilman M. Hackeng, Cornelis Vink, Piet Geusens, Hugo ten Cate, Johannes Waltenberger, Vadim Tchaikovski, Marc Lobbes, Veerle Somers, Anneke Sijbers, Darcey Black, Peter J.E.H.M. Kitslaar, Mat J.A.P. Daemen. (2008) Noninvasive diagnosis of ruptured peripheral atherosclerotic lesions and myocardial infarction by antibody profiling. Journal of Clinical Investigation
CrossRef95
Thomas Steuber, Matthew Frank O’Brien, Hans Lilja. (2008) Serum Markers for Prostate Cancer: A Rational Approach to the Literature. European Urology 54:1, 31-40
CrossRef96
Tomasz M. Beer, Alshad S. Lalani, Stella Lee, Motomi Mori, Kristine M. Eilers, John G. Curd, W. David Henner, Christopher W. Ryan, Peter Venner, J. Dean Ruether, Kim N. Chi, . (2008) C-reactive protein as a prognostic marker for men with androgen-independent prostate cancer. Cancer 112:11, 2377-2383
CrossRef97
K Bensalah, Y Lotan, J A Karam, S F Shariat. (2008) New circulating biomarkers for prostate cancer. Prostate Cancer and Prostatic Diseases 11:2, 112-120
CrossRef98
Aristo Vojdani. (2008) Antibodies as predictors of autoimmune diseases and cancer. Expert Opinion on Medical Diagnostics 2:6, 593-605
CrossRef99
Ole Johan Halvorsen. (2008) Molecular and prognostic markers in prostate cancer. APMIS 116, 1-62
CrossRef100
Zane Kalniņa, Karīna Siliņa, Irēna Meistere, Pawel Zayakin, Alexander Rivosh, Artūrs Ābols, Mārcis Leja, Olga Minenkova, Dirk Schadendorf, Aija Linē. (2008) Evaluation of T7 and lambda phage display systems for survey of autoantibody profiles in cancer patients. Journal of Immunological Methods 334:1-2, 37-50
CrossRef101
Andrew J. Vickers, Kwang Jang, Daniel Sargent, Hans Lilja, Michael W. Kattan. (2008) Systematic review of statistical methods used in molecular marker studies in cancer. Cancer 112:8, 1862-1868
CrossRef102
Charles L. Sawyers. (2008) The cancer biomarker problem. Nature 452:7187, 548-552
CrossRef103
Samir M. Hanash, Sharon J. Pitteri, Vitor M. Faca. (2008) Mining the plasma proteome for cancer biomarkers. Nature 452:7187, 571-579
CrossRef104
Dan Theodorescu, Eric Schiffer, Hartwig W. Bauer, Friedrich Douwes, Frank Eichhorn, Reinhard Polley, Thomas Schmidt, Wolfgang Schöfer, Petra Zürbig, David M. Good, Joshua J. Coon, Harald Mischak. (2008) Discovery and validation of urinary biomarkers for prostate cancer. PROTEOMICS – CLINICAL APPLICATIONS 2:4, 556-570
CrossRef105
Per-Anders Abrahamsson, Martina Tinzl. (2008) Do We Need PSA and Early Detection of Prostate Cancer?. European Urology Supplements 7:5, 393-395
CrossRef106
Alexander A. Parikh, J. Chad Johnson, Nipun B. Merchant. (2008) Genomics and Proteomics in Predicting Cancer Outcomes. Surgical Oncology Clinics of North America 17:2, 257-277
CrossRef107
Marta Sanchez-Carbayo. (2008) Discovery of cancer biomarkers using antibody arrays. Expert Opinion on Medical Diagnostics 2:3, 249-262
CrossRef108
Lene Alsøe, John Erik Stacy, Alexander Fosså, Steinar Funderud, Ole Henrik Brekke, Gustav Gaudernack. (2008) Identification of prostate cancer antigens by automated high-throughput filter immunoscreening. Journal of Immunological Methods 330:1-2, 12-23
CrossRef109
Hye Jin Lee, Alastair W. Wark, Robert M. Corn. (2008) Microarray methods for protein biomarker detection. The Analyst 133:8, 975
CrossRef110
Dipen J. Parekh, Donna Pauler Ankerst, Dean Troyer, Sudhir Srivastava, Ian M. Thompson. (2007) Biomarkers for Prostate Cancer Detection. The Journal of Urology 178:6, 2252-2259
CrossRef111
Gilbert S. Omenn, Peipei Ping. 2007. The Future: Translation from Discovery to the Clinic - Roles of HUPO and Industry in Biomarker Discovery. , 593-613.
CrossRef112
John M. Astle, Thomas Kodadek. 2007. Microarray Approaches to Autoantibody Profiling. , 511-532.
CrossRef113
Ross L. Prentice. (2007) Epidemiologic Methods Developments: A Look Forward to the Year 2032. Annals of Epidemiology 17:11, 906-910
CrossRef114
Steve Mohr, Choong-Chin Liew. (2007) The peripheral-blood transcriptome: new insights into disease and risk assessment. Trends in Molecular Medicine 13:10, 422-432
CrossRef115
Jason A. Dubovsky, Mark R. Albertini, Douglas G. McNeel. (2007) MAD-CT-2 Identified as a Novel Melanoma Cancer-testis Antigen Using Phage Immunoblot Analysis. Journal of Immunotherapy 30:7, 675-683
CrossRef116
Madhumita Chatterjee, Nancy K Levin, Jay P Shah, Alexei Ionan, Harry E Grates, Michael A Tainsky. (2007) Pathways to implementation of serum proteomics for cancer. Expert Opinion on Medical Diagnostics 1:1, 3-15
CrossRef117
Amit S. Dhamoon, Elise C. Kohn, Nilofer S. Azad. (2007) The ongoing evolution of proteomics in malignancy. Drug Discovery Today 12:17-18, 700-708
CrossRef118
William G. Finn. (2007) Diagnostic Pathology and Laboratory Medicine in the Age of “Omics”. The Journal of Molecular Diagnostics 9:4, 431-436
CrossRef119
Nima Sharifi, Barnett S. Kramer. (2007) Screening for Prostate Cancer: Current Status and Future Prospects. The American Journal of Medicine 120:9, 743-745
CrossRef120
Carlyle Hamsher, Anna M. Smith, Zia A. Dehqanzada, Steven Khoo, Sathibalan Ponniah, George E. Peoples, Maria Moroni. (2007) Pattern of serum immunoreactivity against breast cancer cell lysates may predict severity of disease in breast cancer patients. Cancer Immunology, Immunotherapy 56:11, 1711-1721
CrossRef121
Yu. V. Shebzukhov, P. V. Belousov, S. V. Khlgatyan, A. Yu. Sazykin, D. V. Kuprash, S. A. Nedospasov. (2007) Modern molecular biological methods of diagnosing and monitoring oncological diseases, based on the phenomenon of the humoral immune response to tumor-associated antigens. Molecular Genetics, Microbiology and Virology 22:2, 41-44
CrossRef122
Jennifer A Maynard, Ryan Myhre, Benjamin Roy. (2007) Microarrays in infection and immunity. Current Opinion in Chemical Biology 11:3, 306-315
CrossRef123
Danilo Villalta, Renato Tozzoli, Elio Tonutti, Nicola Bizzaro. (2007) The laboratory approach to the diagnosis of autoimmune diseases: Is it time to change?. Autoimmunity Reviews 6:6, 359-365
CrossRef124
Sara Forrester, Ji Qiu, Leslie Mangold, Alan Partin, David Misek, Brett Phinney, Douglas Whitten, Philip Andrews, Eleftherios Diamandis, Gilbert S. Omenn, Samir Hanash, Brian B. Haab. (2007) An experimental strategy for quantitative analysis of the humoral immune response to prostate cancer antigens using natural protein microarrays. PROTEOMICS – Clinical Applications 1:5, 494-505
CrossRef125
Lawrence Fong, Eric J. Small. (2007) Immunotherapy for prostate cancer. Current Oncology Reports 9:3, 226-233
CrossRef126
Joshua R. Ehrlich, Robert J. Caiazzo, Weiliang Qiu, Oliver W. Tassinari, Michael P. O'Leary, Jerome P. Richie, Brian C.-S. Liu. (2007) A native antigen “reverse capture” microarray platform for autoantibody profiling of prostate cancer sera. PROTEOMICS – Clinical Applications 1:5, 476-485
CrossRef127
Martin Fischlechner, Edwin Donath. (2007) Viren als Bauelemente für Materialien und Strukturen. Angewandte Chemie 119:18, 3246-3255
CrossRef128
Martin Fischlechner, Edwin Donath. (2007) Viruses as Building Blocks for Materials and Devices. Angewandte Chemie International Edition 46:18, 3184-3193
CrossRef129
Thomas W. Flaig, Steven K. Nordeen, M. Scott Lucia, Gail S. Harrison, L. Michael Glodé. (2007) Conference Report and Review: Current Status of Biomarkers Potentially Associated With Prostate Cancer Outcomes. The Journal of Urology 177:4, 1229-1237
CrossRef130
C. Geeth Gunawardana, Eleftherios P. Diamandis. (2007) High throughput proteomic strategies for identifying tumour-associated antigens. Cancer Letters 249:1, 110-119
CrossRef131
Robert J Caiazzo Jr, Oliver W Tassinari, Joshua R Ehrlich, Brian CS Liu. (2007) Autoantibody microarrays for biomarker discovery. Expert Review of Proteomics 4:2, 261-272
CrossRef132
Eddy S. Leman, Grant W. Cannon, Bruce J. Trock, Lori J. Sokoll, Daniel W. Chan, Leslie Mangold, Alan W. Partin, Robert H. Getzenberg. (2007) RETRACTED: EPCA-2: A Highly Specific Serum Marker for Prostate Cancer. Urology 69:4, 714-720
CrossRef133
Thomas Steuber, Pauliina Helo, Hans Lilja. (2007) Circulating biomarkers for prostate cancer. World Journal of Urology 25:2, 111-119
CrossRef134
Nicholas J Fitzsimons, Leon Sun, Judd W Moul. (2007) Medical technologies for the diagnosis of prostate cancer. Expert Review of Medical Devices 4:2, 227-239
CrossRef135
Michael W. Shafer, Leslie Mangold, Alan W. Partin, Brian B. Haab. (2007) Antibody array profiling reveals serum TSP-1 as a marker to distinguish benign from malignant prostatic disease. The Prostate 67:3, 255-267
CrossRef136
Sudhir Srivastava, Paul D Wagner. (2007) Risk-based and diagnostics-linked personalized medicine for cancer. Personalized Medicine 4:1, 33-43
CrossRef137
Bin Ye, Audrey Gagnon, Samuel C Mok. (2007) Recent technical strategies to identify diagnostic biomarkers for ovarian cancer. Expert Review of Proteomics 4:1, 121-131
CrossRef138
Hailing Lu, Vivian Goodell, Mary L Disis. (2007) Targeting serum antibody for cancer diagnosis: a focus on colorectal cancer. Expert Opinion on Therapeutic Targets 11:2, 235-244
CrossRef139
Lawrence Fong, Eric J. Small. (2007) Immunotherapy for prostate cancer. Current Prostate Reports 5:1, 5-12
CrossRef140
Julie Hardouin, Jean-Paul Lasserre, Ludovic Canelle, Magalie Duchateau, Céline Vlieghe, Geneviève Choquet-Kastylevsky, Raymonde Joubert-Caron, Michel Caron. (2007) Usefulness of autoantigens depletion to detect autoantibody signatures by multiple affinity protein profiling. Journal of Separation Science 30:3, 352-358
CrossRef141
Valérie Paradis, Pierre Bedossa. (2007) In the new area of noninvasive markers of hepatocellular carcinoma. Journal of Hepatology 46:1, 9-11
CrossRef142
Karen S. Anderson. 2007. Tumor Vaccines for Breast Cancer. , 297-312.
CrossRef143
Jian-Ying Zhang, Roxanne Megliorino, Xuan-Xian Peng, Eng M. Tan, Yao Chen, Edward K.L. Chan. (2007) Antibody detection using tumor-associated antigen mini-array in immunodiagnosing human hepatocellular carcinoma. Journal of Hepatology 46:1, 107-114
CrossRef144
Jian-Ying Zhang. (2007) Mini-array of multiple tumor-associated antigens to enhance autoantibody detection for immunodiagnosis of hepatocellular carcinoma. Autoimmunity Reviews 6:3, 143-148
CrossRef145
Uriel M. Malyankar. (2007) Tumor-Associated Antigens and Biomarkers in Cancer and Immune Therapy. International Reviews of Immunology 26:3-4, 223-247
CrossRef146
Christine H. Chung, Shawn Levy, Pierre Chaurand, David P. Carbone. (2007) Genomics and proteomics: Emerging technologies in clinical cancer research. Critical Reviews in Oncology/Hematology 61:1, 1-25
CrossRef147
Shen Hu, Joseph A. Loo, David T. Wong. (2006) Human body fluid proteome analysis. PROTEOMICS 6:23, 6326-6353
CrossRef148
Timothy J. Bradford, Scott A. Tomlins, Xiaoju Wang, Arul M. Chinnaiyan. (2006) Molecular markers of prostate cancer. Urologic Oncology: Seminars and Original Investigations 24:6, 538-551
CrossRef149
E.R. Pontes, L.C. Matos, E.A. da Silva, L.S. Xavier, B.L. Diaz, I.A. Small, E.M. Reis, S. Verjovski-Almeida, M.A. Barcinski, E.R.P. Gimba. (2006) Auto-antibodies in prostate cancer: Humoral immune response to antigenic determinants coded by the differentially expressed transcripts FLJ23438 and VAMP3. The Prostate 66:14, 1463-1473
CrossRef150
Lawrence Fong, Eric J. Small. 2006. Immunologic Approaches to Prostate Cancer. , 91-102.
CrossRef151
Thomas F. Gajewski, Yuru Meng, Christian Blank, Ian Brown, Aalok Kacha, Justin Kline, Helena Harlin. (2006) Immune resistance orchestrated by the tumor microenvironment. Immunological Reviews 213:1, 131-145
CrossRef152
Gilbert S. Omenn. (2006) Strategies for plasma proteomic profiling of cancers. PROTEOMICS 6:20, 5662-5673
CrossRef153
Laurence Zitvogel, Antoine Tesniere, Guido Kroemer. (2006) Cancer despite immunosurveillance: immunoselection and immunosubversion. Nature Reviews Immunology 6:10, 715-727
CrossRef154
Michael G Kattah, Golnaz R Alemi, Donna L Thibault, Imelda Balboni, Paul J Utz. (2006) A new two-color Fab labeling method for autoantigen protein microarrays. Nature Methods 3:9, 745-751
CrossRef155
Shijun Li, Suvarna Bhamre, Jacques Lapointe, Jonathan R. Pollack, James D. Brooks. (2006) Application of Genomic Technologies to Human Prostate Cancer. OMICS: A Journal of Integrative Biology 10:3, 261-275
CrossRef156
D. C. Miller, S. B. Gruber, B. K. Hollenbeck, J. E. Montie, J. T. Wei. (2006) Incidence of Initial Local Therapy Among Men With Lower-Risk Prostate Cancer in the United States. JNCI Journal of the National Cancer Institute 98:16, 1134-1141
CrossRef157
Charles J Ryan, Eric J Small. (2006) Prostate cancer update: 2005. Current Opinion in Internal Medicine 5:4, 347-351
CrossRef158
Nader Rifai, Michael A Gillette, Steven A Carr. (2006) Protein biomarker discovery and validation: the long and uncertain path to clinical utility. Nature Biotechnology 24:8, 971-983
CrossRef159
Dean Troyer. (2006) Emerging biomarkers in prostate cancer. Aging Health 2:4, 579-588
CrossRef160
Bala S. Balakumaran, Phillip G. Febbo. (2006) New Insights into Prostate Cancer Biology. Hematology/Oncology Clinics of North America 20:4, 773-796
CrossRef161
Li Zhong, Sarah P. Coe, Arnold J. Stromberg, Nada H. Khattar, James R. Jett, Edward A. Hirschowitz. (2006) Profiling Tumor-Associated Antibodies for Early Detection of Non-small Cell Lung Cancer. Journal of Thoracic Oncology 1:6, 513-519
CrossRef162
Albert Hsiao, Michael D. Kuo. (2006) High-throughput Biology in the Postgenomic Era. Journal of Vascular and Interventional Radiology 17:7, 1077-1085
CrossRef163
O. John Semmes, Gunjan Malik, Mike Ward. (2006) Application of mass spectrometry to the discovery of biomarkers for detection of prostate cancer. Journal of Cellular Biochemistry 98:3, 496-503
CrossRef164
Lawrence Fong, Eric J. Small. (2006) Immunotherapy for prostate cancer. Current Urology Reports 7:3, 239-246
CrossRef165
Joshua R Ehrlich, Shuzhen Qin, Brian C-S Liu. (2006) The 'reverse capture' autoantibody microarray:a native antigen-based platform for autoantibody profiling. Nature Protocols 1:1, 452-460
CrossRef166
Brian CS Liu, Joshua R Ehrlich. (2006) Proteomics approaches to urologic diseases. Expert Review of Proteomics 3:3, 283-296
CrossRef167
Soung-Chul Cha, Larry W. Kwak, Pier Adelchi Ruffini, Hong Qin, Sattva Neelapu, Arya Biragyn. (2006) Cloning of B cell lymphoma-associated antigens using modified phage-displayed expression cDNA library and immunized patient sera. Journal of Immunological Methods 312:1-2, 79-93
CrossRef168
Hani H. Rashid, Kenneth S. Koeneman. (2006) Prostate cancer: Molecular approaches for detection and prognosis, and angiogenic therapeutic targets. Urologic Oncology: Seminars and Original Investigations 24:3, 220-221
CrossRef169
Timothy J. Bradford, Xiaoju Wang, Arul M. Chinnaiyan. (2006) Cancer immunomics: Using autoantibody signatures in the early detection of prostate cancer. Urologic Oncology: Seminars and Original Investigations 24:3, 237-242
CrossRef170
Shuzhen Qin, Weiliang Qiu, Joshua R. Ehrlich, Angeline S. Ferdinand, Jerome P. Richie, Michael P. O'Leary, Mei-Ling Ting Lee, Brian C.-S. Liu. (2006) Development of a “reverse capture” autoantibody microarray for studies of antigen-autoantibody profiling. PROTEOMICS 6:10, 3199-3209
CrossRef171
Thomas F. Gajewski, Yuru Meng, Helena Harlin. (2006) Immune Suppression in the Tumor Microenvironment. Journal of Immunotherapy 29:3, 233-240
CrossRef172
Stephen F. Kingsmore. (2006) Multiplexed protein measurement: technologies and applications of protein and antibody arrays. Nature Reviews Drug Discovery 5:4, 310-321
CrossRef173
Gilbert S Omenn. (2006) Report from the 2nd Annual US HUPO Meeting on the HUPO Human Plasma Proteome Project. Expert Review of Proteomics 3:2, 165-168
CrossRef174
Ludovic Canelle, Jordane Bousquet, Cedric Pionneau, Julie Hardouin, Genevieve Choquet-Kastylevsky, Raymonde Joubert-Caron, Michel Caron. (2006) A proteomic approach to investigate potential biomarkers directed against membrane-associated breast cancer proteins. ELECTROPHORESIS 27:8, 1609-1616
CrossRef175
Geoffrey S Ginsburg, Susanne B Haga. (2006) Translating genomic biomarkers into clinically useful diagnostics. Expert Review of Molecular Diagnostics 6:2, 179-191
CrossRef176
Alexandra King. (2006) Autoantibodies as novel biomarkers for the early detection of prostate cancer. Nature Clinical Practice Oncology 3:1, 7-8
CrossRef177
(2005) Autoantibodies in Prostate Cancer. New England Journal of Medicine 353:26, 2815-2817
Full Text178
Finn, Olivera J., . (2005) Immune Response as a Biomarker for Cancer Detection and a Lot More. New England Journal of Medicine 353:12, 1288-1290
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