The Immunome of Colon Cancer: Functional In Silico Analysis of Antigenic Proteins Deduced from IgG Microarray Profiling.

Characterization of the colon cancer immunome and its autoantibody signature from differentially-reactive antigens (DIRAGs) could provide insights into aberrant cellular mechanisms or enriched networks associated with diseases. The purpose of this study was to characterize the antibody profile of plasma samples from 32 colorectal cancer (CRC) patients and 32 controls using proteins isolated from 15,417 human cDNA expression clones on microarrays. 671 unique DIRAGs were identified and 632 were more highly reactive in CRC samples. Bioinformatics analyses reveal that compared to control samples, the immunoproteomic IgG profiling of CRC samples is mainly associated with cell death, survival, and proliferation pathways, especially proteins involved in EIF2 and mTOR signaling. Ribosomal proteins (e.g., RPL7, RPL22, and RPL27A) and CRC-related genes such as APC, AXIN1, E2F4, MSH2, PMS2, and TP53 were highly enriched. In addition, differential pathways were observed between the CRC and control samples. Furthermore, 103 DIRAGs were reported in the SEREX antigen database, demonstrating our ability to identify known and new reactive antigens. We also found an overlap of 7 antigens with 48 "CRC genes." These data indicate that immunomics profiling on protein microarrays is able to reveal the complexity of immune responses in cancerous diseases and faithfully reflects the underlying pathology.

The prostate cancer immunome: In silico functional analysis of antigenic proteins from microarray profiling with IgG.

The study of the immunome of prostate cancer (PCa) and characterization of autoantibody signature from differentially reactive antigens can uncover disease stage proteins, reveal enriched networks and even expose aberrant cellular mechanisms during the disease process. By conducting plasma IgG profiling on protein microarrays presenting 5449 unique human proteins expressed in 15 417 E. coli human cDNA expression clones, we elucidated 471 (21 higher reactive in PCa) differentially reactive antigens in 50 PCa versus 49 patients with benign prostate hyperplasia (BPH) at initial diagnosis. Functional analyzes show that the immune-profile of PCa compared to BPH control samples is significantly enriched in features targeting Cellular assembly, Cell death and pathways involved in Cell cycle, translation, and assembly of proteins as EIF2 signaling, PCa related genes as AXIN1 and TP53, and ribosomal proteins (e.g. RPS10). An overlap of 61 (out of 471) DIRAGs with the published 1545 antigens from the SEREX database has been found, however those were higher reactive in BPH. Clinical relevance is shown when antibody-reactivities against eight proteins were significantly (p < 0.001) correlated with Gleason-score. Herewith we provide a biological and pathophysiological characterization of the immunological layer of cancerous (PCa) versus benign (BPH) disease, derived from antibody profiling on protein microarrays.

The pre-analytical processing of blood samples for detecting biomarkers on protein microarrays.

UNLABELLED: Specimen collection method and quality insurance are pivotal in biomarker discovery. Pre-analytical variables concerning blood collection and sample handling might affect analytical results and should be standardised prior application. In this study, we examine pre-analytical characteristics of blood samples using protein microarray. The influences of 1) standby times until centrifugation (1 h, 4 h, 24 h and 48 h), 2) four blood collection methods, and 3) IgG purified from those samples on differentially reactive antigens between samples ("DIRAGs") were investigated. Spearman correlation analyses of intra-individual arrays demonstrated remarkable differences (0.75-0.98 vs. 0.5-0.75) of antibody reactivities within and between serum and plasma samples. Class comparison showed that reactive antigen profiles were best preserved using IgG purified samples of serum tubes without separation gel as after 24h 83% of the 1h baseline DIRAGs were re-found. Testing dilution series with protein microarrays and Luminex xMap® Technology, we found linear correlations (R(2) = 0.94-0.99) between IgG concentration and read-out when using purified IgG instead of serum. Therefore, we highly recommend standardising pre-analytics and proposing the use of purified IgG for autoantibody immune-profiling with protein microarrays to reduce potential unspecific binding of matrix proteins abundant in serum and plasma samples. SIGNIFICANCE: Although purified IgG cannot completely compensate the influence of pre-analytics, in highly parallel immune-profiling IgG enables reduction of unspecific effects, which occur when using serum or plasma for analysis on protein microarrays. Reproducibility problems due to pre-analytical processing of blood samples might explain discrepant results reported in various biomarker studies.

The current status of cancer biomarker research using tumour-associated antigens for minimal invasive and early cancer diagnostics.

Tumour-associated antigens (TAA) can be detected prior to clinical diagnosis and thus would be ideal biomarkers for early detection of cancer using only a few microliters of a patient's serum. In this article we provide a summary of TAA screening and serum-profiling conducted for breast, prostate, lung and colon cancers. Different methodological approaches, including SEREX, SERPA, and phage display for TAA identification and TAA panels are summarised, and a revision of array based techniques is provided. The most promising studies performed on these cancers (performed with 80-400 serum samples, including controls) obtained sensitivities in a range of 44-95% and specificities of 80-100%. From the various studies reviewed, only one performed cross validation (AUC=0.71) in a prostate cancer study. Thus, albeit receiver operation characteristics are very promising, cross validation of most studies is still missing. Additionally, the concerted action of research groups for standardization of serum-TAA testing and cross validation is required. Along with today's technological options, the chances of establishing TAA biomarkers are now higher than ever before. This may also be true for confirmation and validation of already existing data, which is a prerequisite for implementation of TAA biomarkers into clinical diagnostics. This article is part of a Special Issue entitled: Integrated omics.