Development of a novel multiplex beads-based assay for autoantibody detection for colorectal cancer diagnosis.

Humoral response in cancer patients can be used for early cancer detection. By screening high-density protein microarrays with sera from colorectal cancer (CRC) patients and controls, we identified 16 tumor-associated antigens (TAAs) exhibiting high diagnostic value. This high number of TAAs requires the development of multiplex assays combining different antigens for a faster and more accurate prediction of CRC. Here, we have developed and optimized a bead-based assay using nine selected TAAs and two controls to provide a multiplex test for early CRC diagnosis. We screened a collection of 307 CRC patients' and control sera with the beads assay to identify and validate the best TAA combination for CRC detection. The multiplex bead-based assay exhibited a similar diagnostic performance to detect the humoral response in comparison to multiple ELISA analyses. After multivariate analysis, a panel composed of GTF2B, EDIL3, HCK, PIM1, STK4, and p53, together with gender and age, was identified as the best combination of TAAs for CRC diagnosis, achieving an AUC of 89.7%, with 66% sensitivity at 90.0% fixed specificity. The model was validated using bootstrapping analysis. In summary, we have developed a novel multiplex bead assay that after validation with a larger independent cohort of sera could be utilized in a high-throughput manner for population screening to facilitate the detection of early CRC patients.

In-depth characterization of the secretome of colorectal cancer metastatic cells identifies key proteins in cell adhesion, migration, and invasion.

Liver metastasis in colorectal cancer is the major cause of cancer-related deaths. To identify and characterize proteins associated with colon cancer metastasis, we have compared the conditioned serum-free medium of highly metastatic KM12SM colorectal cancer cells with the parental, poorly metastatic KM12C cells using quantitative stable isotope labeling by amino acids in cell culture (SILAC) analyses on a linear ion trap-Orbitrap Velos mass spectrometer. In total, 1337 proteins were simultaneously identified in SILAC forward and reverse experiments. For quantification, 1098 proteins were selected in both experiments, with 155 proteins showing >1.5-fold change. About 52% of these proteins were secreted directly or using alternative secretion pathways. GDF15, S100A8/A9, and SERPINI1 showed capacity to discriminate cancer serum samples from healthy controls using ELISAs. In silico analyses of deregulated proteins in the secretome of metastatic cells showed a major abundance of proteins involved in cell adhesion, migration, and invasion. To characterize the tumorigenic and metastatic properties of some top up- and down-regulated proteins, we used siRNA silencing and antibody blocking. Knockdown expression of NEO1, SERPINI1, and PODXL showed a significant effect on cellular adhesion. Silencing or blocking experiments with SOSTDC1, CTSS, EFNA3, CD137L/TNFSF9, ZG16B, and Midkine caused a significant decrease in migration and invasion of highly metastatic cells. In addition, silencing of SOSTDC1, EFNA3, and CD137L/TNFSF9 reduced liver colonization capacity of KM12SM cells. Finally, the panel of six proteins involved in invasion showed association with poor prognosis and overall survival after dataset analysis of gene alterations. In summary, we have defined a collection of proteins that are relevant for understanding the mechanisms underlying adhesion, migration, invasion, and metastasis in colorectal cancer.

Label-free nanoplasmonic sensing of tumor-associate autoantibodies for early diagnosis of colorectal cancer.

Colorectal cancer is treatable and curable when detected at early stages. However there is a lack of less invasive and more specific screening and diagnosis methods which would facilitate its prompt identification. Blood circulating autoantibodies which are immediately produced by the immune system at tumor appearance have become valuable biomarkers for preclinical diagnosis of cancer. In this work, we present the rapid and label-free detection of colorectal cancer autoantibodies directly in blood serum or plasma using a recently developed nanoplasmonic biosensor. Our nanoplasmonic device offers sensitive and real-time quantification of autoantibodies with excellent selectivity and reproducibility, achieving limits of detection around 1 nM (150-160 ng mL(-1)). A preliminary evaluation of clinical samples of colorectal cancer patients has shown good correlation with ELISA. These results demonstrate the reliability of the nanobiosensor strategy and pave the way towards the achievement of a sensitive diagnostic tool for early detection of colorectal cancer.

Sporadic colon cancer murine models demonstrate the value of autoantibody detection for preclinical cancer diagnosis.

Although autoantibody detection has been proposed for diagnosis of colorectal cancer, little is known about their initial production and development correlation with cancer progression. Azoxymethane/dextran sodium sulfate (AOM/DSS)-treated mice developed colon adenocarcinoma in the distal colon similar to human sporadic colon cancer. We assessed this model together with AOM and DSS-only models for their applicability to early detection of cancer. All AOM/DSS-treated mice produced autoantibodies to tumor-associated antigens analogous to those observed in human colon cancer patients. Autoantibody response was related to tumor antigen overexpression. Cancer autoantibodies were detected 21 days after starting treatment, when no malignant histopathological features were detectable, and they increased according to tumor progression. When carcinogenesis was induced separately by AOM or DSS, only those mice that developed malignant lesions produced significant levels of autoantibodies. These findings demonstrate that autoantibody development is an early event in tumorigenesis and validates its use for preclinical colon cancer diagnosis.

Proteome profiling of cancer-associated fibroblasts identifies novel proinflammatory signatures and prognostic markers for colorectal cancer.

PURPOSE: Cancer-associated fibroblasts (CAF) are essential components of the stroma that play a critical role in cancer progression. This study aimed to identify novel CAFs markers that might contribute to the invasion and the prognosis of colorectal cancer. EXPERIMENTAL DESIGN: The azoxymethane/dextran sodium sulfate mouse model of sporadic colon cancer represents an adequate source for the isolation of CAFs and normal fibroblasts. By using the explants technique, we purified CAFs and normal fibroblasts from colon tissues. Whole-cell extracts and supernatants were subjected to in-depth quantitative proteomic analysis by tandem mass spectrometry. Further validations of upregulated proteins in CAFs were carried out by chemokine microarray and immunohistochemical analyses of mouse and human tissues. RESULTS: Using a fold-change of 1.4 or more, we found 132 and 125 differentially expressed proteins in whole-cell extracts and supernatants, respectively. We found CAFs-associated proinflammatory and desmoplastic signatures. The proinflammatory signature was composed of several cytokines. Among them, CCL2 and CCL8 caused an increase in migration and invasion of colorectal cancer KM12 cells. The desmoplastic signature was composed of 30 secreted proteins. In mouse and human samples, expression of LTBP2, CDH11, OLFML3, and, particularly, FSTL1 was significantly increased in the tumoral stroma, without significant expression in the cancer epithelial cells. The combination of CALU and CDH11 stromal expression showed a significant association with disease-free survival and poor prognosis. CONCLUSION: We have identified LTBP2, CDH11, OLFML3, and FSTL1 as selective biomarkers of cancer stroma, and CALU and CDH11 as candidate stromal biomarkers of prognostic significance in colon cancer.

An optimized predictor panel for colorectal cancer diagnosis based on the combination of tumor-associated antigens obtained from protein and phage microarrays.

Humoral response in cancer patients appears early in cancer progression and can be used for diagnosis, including early detection. By using human recombinant protein and T7 phage microarrays displaying colorectal cancer (CRC)-specific peptides, we previously selected 6 phages and 6 human recombinant proteins as tumor-associated antigens (TAAs) with high diagnostic value. After completing validation in biological samples, TAAs were classified according to their correlation, redundancy in reactivity patterns and multiplex diagnostic capabilities. For predictor model optimization, TAAs were reanalyzed with a new set of samples. A combination of three phages displaying peptides homologous to GRN, NHSL1 and SREBF2 and four proteins PIM1, MAPKAPK3, FGFR4 and ACVR2B, achieved an area under the curve (AUC) of 94%, with a sensitivity of 89.1% and specificity of 90.0%, to correctly predict the presence of cancer. For early colorectal cancer stages, the AUC was 90%, with a sensitivity of 88.2% and specificity of 82.6%. In summary, we have defined an optimized predictor panel, combining TAAs from different sources, with highly improved accuracy and diagnostic value for colorectal cancer. This article is part of a Special Issue entitled: Translational Proteomics.