Proteomics-based identification of HSP60 as a tumor-associated antigen in colorectal cancer

Patients with cancer frequently develop autoantibodies. The identification of tumor autoantigens may have utility in early cancer diagnosis and immunotherapy. In this study, we used serological proteomics analysis (SERPA) to identify tumor proteins that elicit humoral response in colorectal cancer (CRC). The CRC cell line HCT116 was used as a source of proteins for 2-DE and subsequent Western blot analysis in which individual serum from patients with CRC was analyzed for autoantibodies. An autoantibody against HSP60 identified by MS was detected in 13 out of 25 patients with CRC and 1 out of 15 healthy subjects. In addition, the HSP60 expressions in tumor tissues collected from 40 patients with CRC were assessed by immunohistochemistry, and serum specimens from 100 patients with cancer and 30 healthy controls were screened for antibody titer to HSP60 by ELISA. The results showed that expressions of HSP60 in tumor tissue and serum antibody titer to HSP60 were significantly higher in patients with CRC than in healthy subjects. Thus, we conclude that the SERPA is an excellent assay for the identification of tumor-associated antigens and tumor markers. The detection of HSP60 may have clinical utility in CRC screening, diagnosis, and immunotherapy.     

Shotgun immunoproteomics to identify disease‐associated bacterial antigens: Application to human colon cancer

Circulating antibodies reflect a mirror view of invading antigens that are related to infection and cancer. This was recently exemplified by using serum antibodies to capture Streptococcus bovis antigens followed by MS to generate antigen profiles that were diagnostic for colon cancer. These bacterial antigen profiles have a high potential to aid in the immuno‐diagnosis of this disease, as the magnitude of the immune response to bacterial antigens is, in general, superior to the immune response against tumor (self) antigens. In this study, the identity of individual colon cancer‐associated streptococcal antigens was revealed by enrichment of these “diagnostic” antigens by selected patient antibodies followed by high‐accuracy nanoLC‐MS/MS peptide identification. This showed that both the histone‐like protein HlpA and the ribosomal protein Rp L7/L12 are members of the colon cancer‐associated S. bovis immunome. Both antigens also seem to belong to the group of anchorless surface proteins, like 14 additional proteins that were co‐identified in S. bovis cell wall extracts. Among these were the known streptococcal anchorless surface proteins GAPDH and Enolase. Taken together, these data show that shotgun immunoproteomics, combining immunocapture in‐line with LC MS/MS, is a convenient approach for the rapid identification of disease‐associated bacterial antigens.     

Analysis of the HLA class I associated peptide repertoire in a hepatocellular carcinoma cell line reveals tumor-specific peptides as putative targets for immunotherapy

HLA class I molecules present peptides on the cell surface to CD8(+) T cells. The repertoire of peptides that associate to class I molecules represents the cellular proteome. Therefore, cells expressing different proteomes could generate different class I-associated peptide repertoires. A large number of peptides have been sequenced from HLA class I alleles, mostly from lymphoid cells. On the other hand, T cell immunotherapy is a goal in the fight against cancer, but the identification of T cell epitopes is a laborious task. Proteomic techniques allow the definition of putative T cell epitopes by the identification of HLA natural ligands in tumor cells. In this study, we have compared the HLA class I-associated peptide repertoire from the hepatocellular carcinoma (HCC) cell line SK-Hep-1 with that previously described from lymphoid cells. The analysis of the peptide pool confirmed that, as expected, the peptides from SK-Hep-1 derive from proteins localized in the same compartments as in lymphoid cells. Within this pool, we have identified 12 HLA class I peptides derived from HCC-related proteins. This confirms that tumor cell lines could be a good source of tumor associated antigens to be used, together with MS, to define putative epitopes for cytotoxic T cells from cancer patients.     

An experimental strategy for quantitative analysis of the humoral immune response to prostate cancer antigens using natural protein microarrays

The identification of human tumor antigens has potential utility in the diagnosis and treatment of cancers. We demonstrate here a complete strategy to profile immunoreactivity and identify tumor antigens from proteins derived from tumor cell lines. Microarrays of proteins produced from 2-D LC fractionation of prostate tumor cell-line lysates were used to profile immunoreactivity in the sera of prostate cancer patients and control subjects. Cancer-associated immunoreactivity to distinct groups of chromatography fractions was present in about 50% of the patients, with greater immunoreactivity present in patients with non-organ-confined cancer than in patients with organ-confined cancer. We grouped the immunoreactive fractions by similarities in elution order and patterns of immunoreactivity to guide and interpret the MS analysis of selected fractions, which was used to identify the proteins that may be responsible for the immunoreactivity. As a complementary method to further characterize and validate the immunoreactivity of the proteins identified by mass spectrometry, we demonstrate the use of focused microarrays of recombinant proteins. Disease-associated immunoreactivity was confirmed for one of the identified proteins, human Kallikrein 11. These results demonstrate a practical approach to screening, identifying, and validating immunoreactive proteins that could be applied to diverse studies on humoral immune responses.     

Tracking humoral responses using self assembling protein microarrays

The humoral immune response is a highly specific and adaptive sensor for changes in the body's protein milieu, which responds to novel structures of both foreign and self antigens. Although Igs represent a major component of human serum and are vital to survival, little is known about the response specificity and determinants that govern the human immunome. Historically, antigen-specific humoral immunity has been investigated using individually produced and purified target proteins, a labor-intensive process that has limited the number of antigens that have been studied. Here, we present the development of methods for applying self-assembling protein microarrays and a related method for producing 96-well formatted macroarrays for monitoring the humoral response at the proteome scale. Using plasmids encoding full-length cDNAs for over 850 human proteins and 1700 pathogen proteins, we demonstrate that these microarrays are highly sensitive, specific, reproducible, and can simultaneously measure immunity to thousands of proteins without a priori protein purification. Using this approach, we demonstrate the detection of humoral immunity to known and novel self-antigens, cancer antigens, autoimmune antigens, as well as pathogen-derived antigens. This represents a powerful and versatile tool for monitoring the immunome in health and disease.     

Overexpression and elevated plasma level of tumor-associated antigen 90K/Mac-2 binding protein in colorectal carcinoma

The cancer cell secretome may contain potentially useful biomarkers. Previously, we have analyzed the colorectal carcinoma (CRC) cell secretome. In this study, tumor‐associated antigen 90K (TAA90K)/Mac‐2 binding protein (Mac‐2BP), one of the CRC cell secreted proteins, was chosen for evaluation as a potential CRC biomarker because its mRNA level was also found to be significantly elevated in CRC tissues and in a more metastatic CRC cell line from the analysis of two public domain array‐based datasets. Immunohistochemical analysis of 241 CRC specimens showed that TAA90K/Mac‐2BP was positively detected in 52.7% of the tumors, but weakly or not detected in over 95% of the adjacent nontumor epithelial cells. The plasma TAA90K/Mac‐2BP levels were significantly higher in CRC patients (N = 280) versus healthy controls (N = 147) (7.77 ± 3.49 vs. 5.72 ± 2.67 μg/mL, p<0.001). Moreover, combination of TAA90K/Mac‐2BP and carcinoembryonic antigen (CEA) could outperform CEA alone in discriminating CRC patients from healthy persons in this case‐control study. Our results collectively indicate that analysis of cancer cell secretome is a feasible strategy for identifying cancer biomarker candidates, and the TAA90K/Mac‐2BP may be a potential CRC biomarker.     

Construction of human monoclonal single-chain Fv antibodies against small-cell lung cancer by phage display libraries derived from cell-immunized SCID mice engrafted with human peripheral blood lymphocytes

In this study, we describe a phage display strategy to obtain human monoclonal single-chain Fv (scFv) antibodies binding target cancer cell surface proteins. By developing a cancer cell immunization protocol for SCID mice engrafted with human peripheral blood lymphocytes in combination with an antibody phage display method, we have isolated phage antibodies binding small-cell lung cancer cell line H889 by subtractive selection. One of the isolated scFv antibodies, 12EAb, recognized the E2 component of pyruvate dehydrogenase complex (PDC-E2) by immunoprecipitation according to MALDI-TOF MS analysis. Furthermore, we have confirmed the plasma membrane localization of PDC-E2 in small-cell lung cancer cells by immunocytochemistry and cell surface protein biotinylation, although PDC-E2 is usually located in the mitochondrial matrix. These results, including unique localization of identified antigens, were obtained by proteomic approaches. The present methods can be applied to generate human monoclonal scFv antibodies against tumor cells and to identify new molecular targets for immunotherapy and markers for diagnosis.     

Structure-based prediction of MHC-peptide association: algorithm comparison and application to cancer vaccine design

Peptide vaccination for cancer immunotherapy requires identification of peptide epitopes derived from antigenic proteins associated with the tumor. Such peptides can bind to MHC proteins (MHC molecules) on the tumor-cell surface, with the potential to initiate a host immune response against the tumor. Computer prediction of peptide epitopes can be based on known motifs for peptide sequences that bind to a certain MHC molecule, on algorithms using experimental data as a training set, or on structure-based approaches. We have developed an algorithm, which we refer to as PePSSI, for flexible structural prediction of peptide binding to MHC molecules. Here, we have applied this algorithm to identify peptide epitopes (of nine amino acids, the common length) from the sequence of the cancer-testis antigen KU-CT-1, based on the potential of these peptides to bind to the human MHC molecule HLA-A2. We compared the PePSSI predictions with those of other algorithms and found that several peptides predicted to be strong HLA-A2 binders by PePSSI were similarly predicted by another structure-based algorithm, PREDEP. The results show how structure-based prediction can identify potential peptide epitopes without known binding motifs and suggest that side chain orientation in binding peptides may be obtained using PePSSI.     

In this issue: Proteomics – Clinical Applications 4/2008

In this issue of Proteomics you will find the following highlighted articles: MALDI and methyl groups take on lysosomal storage disease diagnosis Lysosomal storage disorders (LSD) result from the absence or loss of any of a wide variety of glycan‐processing enzymes that lead to accumulation of incompletely processed glyco‐molecules in lysosomes. Diagnosis of the particular type of LSD requires identification of the accumulated species, usually from urine. LSD diagnosis has been a target for many years, including use of GC/MS, TLC, NMR, HPLC, FACE and other techniques. Faid et al. take a simple approach that is quite successful and much less time consuming. After permethylating crude urine, a sample is first run on GC/MS to look for free sialic acid, an indicator of one set of diseases, then a cleaned up sample (C_1–8) is analyzed by MALDI/TOF to characterize glycoproteins and glycopeptides present. The glycans were further analyzed by sequential exoglucosidase digestion on the MALDI target. Sulfated glycocompound analysis requires a desulfation step prior to permethylation. Faid, V. et al., Proteomics Clin. Appl. 2008, 2, 528–542. Popular prostate problem receives piercing look Prostate cancer (PCa) is one of the most frequent male cancers. It is also one of the most frequently misdiagnosed cancers. Prostate specific antigen (PSA) has improved the accuracy somewhat but still generates 700 000 false positives requiring biopsies per year in the US. And very low PSA levels don’t assure freedom from PCa. In short, there is no good biomarker for PCa. Theodorescu et al. recognized that anything recovered from blood had a good chance of being at least partially degraded so they looked at first void urine as a more likely source of stable material. Applying capillary electrophoresis coupled to TOF‐MS, the authors developed an “informative” panel of eight peptides that distinguished between first void and mid‐stream samples and a PCa‐specific panel of 12 proteins that detected the disease. Incorporating the 12 proteins with age and free PSA, sensitivity was 91%, specificity 69%. Theodorescu, D. et al., Proteomics Clin. Appl. 2008, 2, 556–570. No candy in candidiasis Candida albicans is a unicellular yeast that is the third most common nosocomial agent in ICU’s, costing ～US$ 40 000 per incident. Early diagnosis of systemic candidiasis (SC) is crucial for successful control of the infection by antifungal therapies. Blood cultures are not fast and tissue biopsies are not sensitive but are the current “gold standards.” Pitarch et al. report here a serum protein marker for SC: anti‐Candida enolase (Eno1p) IgG. Comparing healthy with SC patients for antibodies against Candida cytoplasmic antigens, 15 antigens were recognized by the SC patients. The strongest response was to Eno1p which was the only antigen to produce a response in all 12 patients. The IgG was tested for its suitability as an antigen in Western and capture ELISA tests. Although the tests appear reliable for detecting SC, they were not good for prognosis. A considerable amount of work remains for full qualification of the test. Pitarch, A. et al., Proteomics Clin. Appl. 2008, 2, 596–618.     

Cover Picture: Proteomics – Clinical Applications 4/2008

In this issue of Proteomics you will find the following highlighted articles: MALDI and methyl groups take on lysosomal storage disease diagnosis Lysosomal storage disorders (LSD) result from the absence or loss of any of a wide variety of glycan‐processing enzymes that lead to accumulation of incompletely processed glyco‐molecules in lysosomes. Diagnosis of the particular type of LSD requires identification of the accumulated species, usually from urine. LSD diagnosis has been a target for many years, including use of GC/MS, TLC, NMR, HPLC, FACE and other techniques. Faid et al. take a simple approach that is quite successful and much less time consuming. After permethylating crude urine, a sample is first run on GC/MS to look for free sialic acid, an indicator of one set of diseases, then a cleaned up sample (C_1–8) is analyzed by MALDI/TOF to characterize glycoproteins and glycopeptides present. The glycans were further analyzed by sequential exoglucosidase digestion on the MALDI target. Sulfated glycocompound analysis requires a desulfation step prior to permethylation. Faid, V. et al., Proteomics Clin. Appl. 2008, 2, 528–542. Popular prostate problem receives piercing look Prostate cancer (PCa) is one of the most frequent male cancers. It is also one of the most frequently misdiagnosed cancers. Prostate specific antigen (PSA) has improved the accuracy somewhat but still generates 700 000 false positives requiring biopsies per year in the US. And very low PSA levels don’t assure freedom from PCa. In short, there is no good biomarker for PCa. Theodorescu et al. recognized that anything recovered from blood had a good chance of being at least partially degraded so they looked at first void urine as a more likely source of stable material. Applying capillary electrophoresis coupled to TOF‐MS, the authors developed an “informative” panel of eight peptides that distinguished between first void and mid‐stream samples and a PCa‐specific panel of 12 proteins that detected the disease. Incorporating the 12 proteins with age and free PSA, sensitivity was 91%, specificity 69%. Theodorescu, D. et al., Proteomics Clin. Appl. 2008, 2, 556–570. No candy in candidiasis Candida albicans is a unicellular yeast that is the third most common nosocomial agent in ICU’s, costing ～US$ 40 000 per incident. Early diagnosis of systemic candidiasis (SC) is crucial for successful control of the infection by antifungal therapies. Blood cultures are not fast and tissue biopsies are not sensitive but are the current “gold standards.” Pitarch et al. report here a serum protein marker for SC: anti‐Candida enolase (Eno1p) IgG. Comparing healthy with SC patients for antibodies against Candida cytoplasmic antigens, 15 antigens were recognized by the SC patients. The strongest response was to Eno1p which was the only antigen to produce a response in all 12 patients. The IgG was tested for its suitability as an antigen in Western and capture ELISA tests. Although the tests appear reliable for detecting SC, they were not good for prognosis. A considerable amount of work remains for full qualification of the test. Pitarch, A. et al., Proteomics Clin. Appl. 2008, 2, 596–618.     

Proteomics of endometrial cancer diagnosis,treatment, and prognosis

This review discusses the current status of proteomics technology in endometrial cancer diagnosis, treatment and prognosis. The first part of this review focuses on recently identified biomarkers for endometrial cancer, their importance in clinical use as well as the proteomic methods used in their discovery. The second part highlights some of the emerging mass spectrometry based proteomic technologies that promise to contribute to a better understanding of endometrial cancer by comparing the abundance of hundreds or thousands of proteins simultaneously.     

Proteomic profiling of 13 paired ductal infiltrating breast carcinomas and non-tumoral adjacent counterparts

According to recent statistics, breast cancer remains one of the leading causes of death among women in Western countries. Breast cancer is a complex and heterogeneous disease, presently classified into several subtypes according to their cellular origin. Among breast cancer histotypes, infiltrating ductal carcinoma represents the most common and potentially aggressive form. Despite the current progress achieved in early cancer detection and treatment, including the new generation of molecular therapies, there is still need for identification of multiparametric biomarkers capable of discriminating between cancer subtypes and predicting cancer progression for personalized therapies. One established step in this direction is the proteomic strategy, expected to provide enough information on breast cancer profiling. To this aim, in the present study we analyzed 13 breast cancer tissues and their matched non-tumoral tissues by 2-DE. Collectively, we identified 51 protein spots, corresponding to 34 differentially expressed proteins, which may represent promising candidate biomarkers for molecular-based diagnosis of breast cancer and for pattern discovery. The relevance of these proteins as factors contributing to breast carcinogenesis is discussed.     

Proteomics of nipple aspirate fluid, breast cyst fluid, milk, and colostrum

Proteomic analysis of breast fluids has wide-ranging clinical applications. Protein expression in nipple aspirate fluid and breast cyst fluid may prove valuable for the detection and monitoring of breast cancer, but has been hampered by the lack of a single marker with sufficient breast cancer sensitivity and specificity to be clinically useful. The assessment of multiple proteins may offer a more powerful cancer detection tool. Breast cancer is particularly difficult to detect in women who are lactating. The identification of cancer predicting proteins in milk may prove very helpful in an early cancer detection in this group of women. A better understanding of the protein composition of milk and colostrum should improve infant care and nutrition, and lead to alternatives for individuals with milk allergies.     

DSP based entropy estimation for identification and classification of Homo sapiens cancer genes

Because of advancement of microarray technology in recent years, public domains like NCBI, NIH, NHGRI etc. present extensive range of information rich raw genomic data. Effortless accessibility of these data attracts the researchers from diverse disciplines to process them for the benefit of the society. In the field of signal processing, a new area of research has been introduced namely genomic signal processing (GSP). GSP basically processes genes, proteins and DNA sequences using various signal processing methodologies to extract the information hidden in it. As some genetic abnormalities turn into cancer diseases, proper understanding and analysis of genes and proteins may lead to a new horizon in cancer genomic study. In genomic signal processing, exact identification and classification of diseased gene is a great challenge to the researchers. Hence in the present paper, the crucial job of gene identification and classification is attempted. As a solution to this problem, statistical methods like entropy estimation and mutual information calculation is adopted along with DSP technique. Rayleigh distribution of estimated entropy of gene is treated as identifier of healthy and cancerous Homo sapiens. Once the cancer genes are identified, mutual information estimator based on their minimum entropy is used as classifier to detect different types of cancer genes. The present algorithms are successfully tested on several healthy and cancerous prostate, breast and colon genes collected from NCBI genbank.

     

Proteomics studies of pancreatic cancer

Pancreatic cancer is the fourth leading cause of cancer death in the United States, with 4% survival 5 years after diagnosis. Biomarkers are desperately needed to improve earlier, more curable cancer diagnosis and to develop new effective therapeutic targets. The development of quantitative proteomics technologies in recent years offers great promise for understanding the complex molecular events of tumorigenesis at the protein level, and has stimulated great interest in applying the technology for pancreatic cancer studies. Proteomic studies of pancreatic tissues, juice, serum/plasma, and cell lines have recently attempted to identify differentially expressed proteins in pancreatic cancer to dissect the abnormal signaling pathways underlying oncogenesis, and to detect new biomarkers. It can be expected that the continuing evolution of proteomics technology with better resolution and sensitivity will greatly enhance our capability in combating pancreatic cancer.     

Identification of circulating endorepellin LG3 fragment: Potential use as a serological biomarker for breast cancer

Comparative proteome analysis was performed on the cultured media of human nontumor and malignant breast cell lines, Hs578Bst and Hs578T, respectively, in search of a serological biomarker(s) for breast cancer. Proteins in the conditioned media were separated by 2‐D PAGE and then visualized by silver‐staining. Eight proteins changed differentially by more than two‐fold were identified by MALDI‐TOF/TOF MS. Among the proteins identified, the terminal laminin‐like globular (LG3) domain of endorepellin, which was recently reported as an antiangiogenesis factor, was decreased in the cancer cell line. We confirmed the bone morphogenic protein‐1 (BMP‐1) mediated cleavage site on the N‐terminus of endorepellin LG3 fragment. This finding suggests that the LG3 fragment is specifically released by a BMP‐1 driven limited proteolytic process. The protein was also detected in plasma by Western blot analysis and selected reaction monitoring (SRM). The plasma level of the endorepellin LG3 fragment was significantly lower in breast cancer patients compared to healthy donors (p = 0.017; n = 12). The LG3 protein concentration in the control plasma was measured at approximately 3.7 pmol/mL compared to 1.8 pmol/mL in plasma from the cancer patients. We suggest that these results support the potential use of the endorepellin LG3 fragment as a new serological biomarker for breast cancer.     

Phosphoproteomics: A possible route to novel biomarkers of breast cancer

Proteomics is rapidly transforming the way that cancer and other pathologies are investigated. The ability to identify hundreds of proteins and to compare their abundance in different clinical samples presents a unique opportunity for direct identification of novel disease markers. Furthermore, recent advances allow us to analyse and compare PTMs. This gives an additional dimension for defining a new class of protein biomarker based not only on abundance and expression but also on the occurrence of covalent modifications specific to a disease state or therapy response. Such modifications are often a consequence of the activation/inactivation of a particular disease related pathway. In this review we evaluate the available information on breast cancer related protein-phosphorylation events, illustrating the rationale for investigating this PTM as a target for breast cancer research with eventual clinical relevance. We present a critical survey of the published experimental strategies to study protein phosphorylation on a system wide scale and highlight recent specific advances in breast cancer phosphoproteomics. Finally we discuss the feasibility of establishing novel biomarkers for breast cancer based on the detection of patterns of specific protein phosphorylation events.     

Human pathogenic streptococcal proteomics and vaccine development

Gram-positive streptococci are non-motile, chain-forming bacteria commonly found in the normal oral and bowel flora of warm-blooded animals. Over the past decade, a proteomic approach combining 2-DE and MS has been used to systematically map the cellular, surface-associated and secreted proteins of human pathogenic streptococcal species. The public availability of complete streptococcal genomic sequences and the amalgamation of proteomic, genomic and bioinformatic technologies have recently facilitated the identification of novel streptococcal vaccine candidate antigens and therapeutic agents. The objective of this review is to examine the constituents of the streptococcal cell wall and secreted proteome, the mechanisms of transport of surface and secreted proteins, and describe the current methodologies employed for the identification of novel surface-displayed proteins and potential vaccine antigens.     

Computational prediction of nucleic acid secondary structure: Methods,applications, and challenges

RNA molecules are crucial in different levels of cellular function, ranging from translation and regulating genes to coding for proteins. Additionally, nucleic acids (RNA and DNA molecules) are designed for novel applications in biotechnology. Understanding the structure of a molecule is important in inferring its function, and computational methods for structure prediction have captured the interest of many researchers.Some functions of RNA molecules in cells, such as gene regulation, result from the binding of one RNA molecule to another, so-called target RNA molecule. This has led to recent interest in prediction of the secondary structure formed from interacting molecules. In this paper, we provide a brief overview of methods, applications, and challenges in computational prediction of nucleic acid secondary structure, both for single strands and for interacting strands.