Ingrid Babel

Identification of tumor-associated autoantigens for the diagnosis of colorectal cancer in serum using high density protein microarrays.

There is a mounting evidence of the existence of autoantibodies associated to cancer progression. Antibodies are the target of choice for serum screening because of their stability and suitability for sensitive immunoassays. By using commercial protein microarrays containing 8000 human proteins, we examined 20 sera from colorectal cancer (CRC) patients and healthy subjects to identify autoantibody patterns and associated antigens. Forty-three proteins were differentially recognized by tumoral and reference sera (p value <0.04) in the protein microarrays. Five immunoreactive antigens, PIM1, MAPKAPK3, STK4, SRC, and FGFR4, showed the highest prevalence in cancer samples, whereas ACVR2B was more abundant in normal sera. Three of them, PIM1, MAPKAPK3, and ACVR2B, were used for further validation. A significant increase in the expression level of these antigens on CRC cell lines and colonic mucosa was confirmed by immunoblotting and immunohistochemistry on tissue microarrays. A diagnostic ELISA based on the combination of MAPKAPK3 and ACVR2B proteins yielded specificity and sensitivity values of 73.9 and 83.3% (area under the curve, 0.85), respectively, for CRC discrimination after using an independent sample set containing 94 sera representative of different stages of progression and control subjects. In summary, these studies confirmed the presence of specific autoantibodies for CRC and revealed new individual markers of disease (PIM1, MAPKAPK3, and ACVR2B) with the potential to diagnose CRC with higher specificity and sensitivity than previously reported serum biomarkers.

Differential protein expression on the cell surface of colorectal cancer cells associated to tumor metastasis

Progression to metastasis is the critical point in colorectal cancer (CRC) survival. However, the proteome associated to CRC metastasis is very poorly understood at the moment. In this study, we used stable isotope labeling by amino acids in cell culture to compare two CRC cell lines: KM12C and KM12SM, representing poorly versus highly metastatic potential, to find and quantify the differences in protein expression, mostly at the cell surface level. After biotinylation followed by affinity purification, membrane proteins were separated by SDS‐PAGE and analyzed using nanoflow LC‐ESI‐LTQ. A total of 291 membrane and membrane‐associated proteins were identified with a p value<0.01, from which 60 proteins were found to be differentially expressed by more than 1.5‐fold. We identified a number of cell signaling, CDs, integrins and other cell adhesion molecules (cadherin 17, junction plakoglobin (JUP)) among the most deregulated proteins. They were validated by Western blot, confocal microscopy and flow cytometry analysis. Immunohistochemical analysis of paired tumoral samples confirmed that these differentially expressed proteins were also altered in human tumoral tissues. A good correlation with a major abundance in late tumor stages was observed for JUP and 17‐β‐hydroxysteroid dehydrogenase type 8 (HSD17B8). Moreover, the combined increase in JUP, occludin and F11 receptor expression together with cadherin 17 expression could suggest a reversion to a more epithelial phenotype in highly metastatic cells. Relevant changes were observed also at the metabolic level in the pentose phosphate pathway and several amino acid transporters. In summary, the identified proteins provide us with a better understanding of the events involved in liver colonization and CRC metastasis.

Identification of MST1/STK4 and SULF1 proteins as autoantibody targets for the diagnosis of colorectal cancer by using phage microarrays

The characterization of the humoral response in cancer patients is becoming a practical alternative to improve early detection. We prepared phage microarrays containing colorectal cancer cDNA libraries to identify phage-expressed peptides recognized by tumor-specific autoantibodies from patient sera. From a total of 1536 printed phages, 128 gave statistically significant values to discriminate cancer patients from control samples. From this, 43 peptide sequences were unique following DNA sequencing. Six phages containing homologous sequences to STK4/MST1, SULF1, NHSL1, SREBF2, GRN, and GTF2I were selected to build up a predictor panel. A previous study with high-density protein microarrays had identified STK4/MST1 as a candidate biomarker. An independent collection of 153 serum samples (50 colorectal cancer sera and 103 reference samples, including healthy donors and sera from other related pathologies) was used as a validation set to study prediction capability. A combination of four phages and two recombinant proteins, corresponding to MST1 and SULF1, achieved an area under the curve of 0.86 to correctly discriminate cancer from healthy sera. Inclusion of sera from other different neoplasias did not change significantly this value. For early stages (A+B), the corrected area under the curve was 0.786. Moreover, we have demonstrated that MST1 and SULF1 proteins, homologous to phage-peptide sequences, can replace the original phages in the predictor panel, improving their diagnostic accuracy.

Colorectal cancer proteomics, molecular characterization and biomarker discovery

Colorectal cancer (CRC) is a widespread disease, whose major genetic changes and mutations have been well characterized in the sporadic form. Much less is known at the protein and proteome level. Still, CRC has been the subject of multiple proteomic studies due to the urgent necessity of finding clinically relevant markers and to elucidate the molecular mechanisms underlying the progression of the disease. These proteomic approaches have been limited by different technical issues, mainly related with sensitivity and reproducibility. However, recent advances in proteomic techniques and MS systems have rekindled the quest for new biomarkers in CRC and an improved molecular characterization. In this review, we will discuss the application of different proteomic approaches to the identification of differentially expressed proteins in CRC. In particular, we will make a critical assessment about the use of 2‐D DIGE, MS and protein microarray technologies, in their different formats, to identify up‐ or downregulated proteins and/or autoantibodies profiles that could be useful for CRC characterization and diagnosis. Despite a wide list of potential biomarkers, it is clear that more scientific efforts and technical advances are still needed to cover the range of low‐abundant proteins, which may play a key role in CRC diagnostics and progression.

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.

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.

Antibodies on demand: a fast method for the production of human scFvs with minimal amounts of antigen

BackgroundAntibodies constitute a powerful tool to study protein function, protein localization and protein-protein interactions, as well as for diagnostic and therapeutic purposes. High-throughput antibody development requires faster methodologies with lower antigen consumption.ResultsHere, we describe a novel methodology to select human monoclonal recombinant antibodies by combining in vitro protein expression, phage display antibody libraries and antibody microarrays. The application of this combination of methodologies permitted us to generate human single-chain variable fragments (scFvs) against two proteins: green fluorescent protein (GFP) and thioredoxin (Trx) in a short time, using as low as 5 μg of purified protein. These scFvs showed specific reactivity against their respective targets and worked well by ELISA and western blot. The scFvs were able to recognise as low as 31 ng of protein of their respective targets by western blot.ConclusionThis work describes a novel and miniaturized methodology to obtain human monoclonal recombinant antibodies against any target in a shorter time than other methodologies using only 5 μg of protein. The protocol could be easily adapted to a high-throughput procedure for antibody production.