Colorectal cancer proteomics, molecular characterization and biomarker discovery

Benefits of FAIMS to Improve the Proteome Coverage of Deteriorated and/or Cross-Linked TMT 10-Plex FFPE Tissue and Plasma-Derived Exosomes Samples

The proteome characterization of complex, deteriorated, or cross-linked protein mixtures as paired clinical FFPE or exosome samples isolated from low plasma volumes (250 µL) might be a challenge. In this work, we aimed at investigating the benefits of FAIMS technology coupled to the Orbitrap Exploris 480 mass spectrometer for the TMT quantitative proteomics analyses of these complex samples in comparison to the analysis of protein extracts from cells, frozen tissue, and exosomes isolated from large volume plasma samples (3 mL). TMT experiments were performed using a two-hour gradient LC-MS/MS with or without FAIMS and two compensation voltages (CV = -45 and CV = -60). In the TMT experiments of cells, frozen tissue, or exosomes isolated from large plasma volumes (3 mL) with FAIMS, a limited increase in the number of identified and quantified proteins accompanied by a decrease in the number of peptides identified and quantified was observed. However, we demonstrated here a noticeable improvement (>100%) in the number of peptide and protein identifications and quantifications for the plasma exosomes isolated from low plasma volumes (250 µL) and FFPE tissue samples in TMT experiments with FAIMS in comparison to the LC-MS/MS analysis without FAIMS. Our results highlight the potential of mass spectrometry analyses with FAIMS to increase the depth into the proteome of complex samples derived from deteriorated, cross-linked samples and/or those where the material was scarce, such as FFPE and plasma-derived exosomes from low plasma volumes (250 µL), which might aid in the characterization of their proteome and proteoforms and in the identification of dysregulated proteins that could be used as biomarkers.

p53 and p63 Proteoforms Derived from Alternative Splicing Possess Differential Seroreactivity in Colorectal Cancer with Distinct Diagnostic Ability from the Canonical Proteins

Colorectal cancer (CRC) is the third most common cancer and the second most frequent cause of cancer-related death worldwide. The detection in plasma samples of autoantibodies against specific tumor-associated antigens has been demonstrated to be useful for the early diagnosis of CRC by liquid biopsy. However, new studies related to the humoral immune response in cancer are needed to enable blood-based diagnosis of the disease. Here, our aim was to characterize the humoral immune response associated with the different p53 and p63 proteoforms derived from alternative splicing and previously described as aberrantly expressed in CRC. Thus, here we investigated the diagnostic ability of the twelve p53 proteoforms and the eight p63 proteoforms described to date, and their specific N-terminal and C-terminal end peptides, by means of luminescence HaloTag beads immunoassays. Full-length proteoforms or specific peptides were cloned as HaloTag fusion proteins and their seroreactivity analyzed using plasma from CRC patients at stages I-IV (n = 31), individuals with premalignant lesions (n = 31), and healthy individuals (n = 48). p53γ, Δ40p53β, Δ40p53γ, Δ133p53γ, Δ160p53γ, TAp63α, TAp63δ, ΔNp63α, and ΔNp63δ, together with the specific C-terminal end α and δ p63 peptides, were found to be more seroreactive against plasma from CRC patients and/or individuals with premalignant lesions than from healthy individuals. In addition, ROC (receiver operating characteristic) curves revealed a high diagnostic ability of those p53 and p63 proteoforms to detect CRC and premalignant individuals (AUC higher than 85%). Finally, electrochemical biosensing platforms were employed in POC-like devices to investigate their usefulness for CRC detection using selected p53 and p63 proteoforms. Our results demonstrate not only the potential of these biosensors for the simultaneous analysis of proteoforms’ seroreactivity, but also their convenience and versatility for the clinical detection of CRC by liquid biopsy. In conclusion, we here show that p53 and p63 proteoforms possess differential seroreactivity in CRC patients in comparison to controls, distinctive from canonical proteins, which should improve the diagnostic panels for obtaining a blood-based biomarker signature for CRC detection.

Protein Microarray-Based Proteomics for Disease Analysis

As we approach the twentieth anniversary of completing the international Human Genome Project, the next (and arguably most significant) frontier in biology consists of functionally understanding the proteins, which are encoded by the genome and play a crucial role in all of biology and medicine. To accomplish this challenge, different proteomics strategies must be devised to examine the activities of gene products (proteins) at scale. Among them, protein microarrays have been used to accomplish a wide variety of investigations such as examining the binding of proteins and proteoforms to DNA, small molecules, and other proteins; characterizing humoral immune responses in health and disease; evaluating allergenic proteins; and profiling protein patterns as candidate disease-specific biomarkers. In Protein Microarray for Disease Analysis: Methods and Protocols, expert researchers involved in the field of protein microarrays provide concise descriptions of the methodologies that they currently use to fabricate microarrays and how they apply them to analyze protein interactions and responses of proteins to dissect human disease.

Analysis of Protein-Protein Interactions by Protein Microarrays

The analysis of the proteome and the interactome would be useful for a better understanding of the pathophysiology of several disorders, allowing the identification of potential specific markers for early diagnosis and prognosis, as well as potential targets of intervention. Among different proteomic approaches, high-density protein microarrays have become an interesting tool for the screening of protein-protein interactions and the interactome definition of disease-associated dysregulated proteins. This information might contribute to the identification of altered signaling pathways and protein functions involved in the pathogenesis of a disease. Remarkably, protein microarrays have been already satisfactorily employed for the study of protein-protein interactions in cancer, allergy, or neurodegenerative diseases. Here, we describe the utilization of recombinant protein microarrays for the identification of protein-protein interactions to help in the definition of disease-specific dysregulated interactomes.

Multiplexed monitoring of a novel autoantibody diagnostic signature of colorectal cancer using HaloTag technology-based electrochemical immunosensing platform

Background and Purpose: The humoral immune response in cancer patients can be used for early detection of the disease. Autoantibodies raised against tumor-associated antigens (TAAs) are promising clinical biomarkers for reliable cancer diagnosis, prognosis, and therapy monitoring. In this study, an electrochemical disposable multiplexed immunosensing platform able to integrate difficult- and easy-to-express colorectal cancer (CRC) TAAs is reported for the sensitive determination of eight CRC-specific autoantibodies. Methods: The electrochemical immunosensing approach involves the use of magnetic microcarriers (MBs) as solid supports modified with covalently immobilized HaloTag fusion proteins for the selective capture of specific autoantibodies. After magnetic capture of the modified MBs onto screen-printed carbon working electrodes, the amperometric responses measured using the hydroquinone (HQ)/H2O2 system were related to the levels of autoantibodies in plasma. Results: The biosensing platform was applied to the analysis of autoantibodies against 8 TAAs described for the first time in this work in plasma samples from healthy asymptomatic individuals (n=3), and patients with high-risk of developing CRC (n=3), and from patients already diagnosed with colorectal (n=3), lung (n=2) or breast (n=2) cancer. The developed bioplatform demonstrated an improved discrimination between CRC patients and controls (asymptomatic healthy individuals and breast and lung cancer patients) compared to an ELISA-like luminescence test. Conclusions: The proposed methodology uses a just-in-time produced protein in a simpler protocol, with low sample volume, and involves cost-effective instrumentation, which could be used in a high-throughput manner for reliable population screening to facilitate the detection of early CRC patients at affordable cost.

Identification of tumor-associated antigens with diagnostic ability of colorectal cancer by in-depth immunomic and seroproteomic analysis

Colorectal cancer (CRC) is the third most common cancer and the second leading cause of cancer related death worldwide. Its diagnosis at early stages would significantly improve the survival of CRC patients. The humoral immune response has been demonstrated useful for cancer diagnosis, predating clinical symptoms up to 3 years. Here, we employed an in-depth seroproteomic approach to identify proteins that elicit a humoral immune response in CRC patients. The seroproteomic approach relied on the immunoprecipitation with patient-derived autoantibodies of proteins from CRC cell lines with different metastatic properties followed by LC-MS/MS. After bioinformatics, we focused on 31 targets of CRC autoantibodies. After WB and IHC validation, ERP44 and TALDO1 showed potential to discriminate disease-free and metastatic CRC patients, and time to recurrence of CRC patients in stage II. Using plasma samples of 30 healthy individuals, 28 premalignant individuals, and 32 CRC patients, nine out of 13 selected targets for seroreactive analysis showed significant diagnostic ability to discriminate either CRC patients or premalignant subjects from controls. Our results suggest that the here defined panel of CRC autoantibodies and their target proteins should be included in CRC blood-based biomarker panels to get a clinically useful blood-based diagnostic signature for CRC detection. SIGNIFICANCE: Colorectal cancer is one of the deadliest cancer types mainly due to its late diagnosis. Its early diagnosis, therefore, is of great importance since it would significantly improve the survival of CRC patients. In our work, the in-depth seroproteomic analysis of colorectal cancer using isolated IgGs from colorectal cancer patients and controls and protein extract of colorectal cancer cells provide the identification of valuable biomarkers with diagnostic and prognostic ability of the disease.

The specific seroreactivity to ∆Np73 isoforms shows higher diagnostic ability in colorectal cancer patients than the canonical p73 protein

The p53-family is tightly regulated at transcriptional level. Due to alternative splicing, up to 40 different theoretical proteoforms have been described for p73 and at least 20 and 10 for p53 and p63, respectively. However, only the canonical proteins have been evaluated as autoantibody targets in cancer patients for diagnosis. In this study, we have cloned and expressed in vitro the most upregulated proteoforms of p73, ΔNp73α and ΔNp73β, for the analysis of their seroreactivity by a developed luminescence based immunoassay test using 145 individual plasma from colorectal cancer, premalignant individuals and healthy controls. ∆Np73α seroreactivity showed the highest diagnostic ability to discriminate between groups. The combination of ∆Np73α, ∆Np73β and p73 proteoforms seroreactivity were able to improve their individual diagnostic ability. Competitive inhibition experiments further demonstrated the presence of unique specific epitopes in ΔNp73 isoforms not present in p73, with several colorectal patients showing unique and specific seroreactivity to the ΔNp73 proteoforms. Overall, we have increased the complexity of the humoral immune response to the p53-family in cancer patients, showing that the proteoforms derived from the alternative splicing of p73 possess a higher diagnostic ability than the canonical protein, which might be extensive for p53 and p63 proteins.

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.

Clinical value of integrated-signature miRNAs in colorectal cancer: miRNA expression profiling analysis and experimental validation

MicroRNA (miRNA) expression profiling of colorectal cancer (CRC) are often inconsistent among different studies. To determine candidate miRNA biomarkers for CRC, we performed an integrative analysis of miRNA expression profiling compared CRC tissues and paired neighboring noncancerous colorectal tissues. Using robust rank aggregation method, we identified a miRNA set of 10 integrated-signature miRNAs. In addition, the qRT-PCR validation demonstrated that 9 miRNAs were consistent dysregulated with the integrative analysis in CRC tissues, 4 miRNAs (miR-21-5p, miR-183-5p, miR-17-5p and miR-20a-5p) were up-regulated expression, and 5 miRNAs (miR-145-5p, miR-195-5p, miR-139-5p, miR-378a-5p and miR-143-3p) were down-regulated expression (all p < 0.05). Consistent with the initial analysis, 7 miRNAs were found to be significantly dysregulated in CRC tissues in TCGA data base, 4 miRNAs (miR-21-5p, miR-183-5p, miR-17-5p and miR-20a-5p) were significantly up-regulated expression, and 3 miRNAs (miR-145-5p, miR-139-5p and miR-378a-5p) were significantly down-regulated expression in CRC tissues (all p < 0.001). Furthermore, miR-17-5p (p = 0.011) and miR-20a-5p (p = 0.003) were up-regulated expression in the III/IV tumor stage, miR-145-5p (p = 0.028) and miR-195-5p (p = 0.001) were significantly increased expression with microscopic vascular invasion in CRC tissues, miR-17-5p (p = 0.037) and miR-145-5p (p = 0.023) were significantly increased expression with lymphovascular invasion. Moreover, Cox regression analysis of CRC patients in TCGA data base showed miR-20a-5p was correlated with survival (hazard ratio: 1.875, 95%CI: 1.088-3.232, p = 0.024). Hence, the finding of current study provides a basic implication of these miRNAs for further clinical application in CRC.

Proteomic analysis of cerebrospinal fluid: toward the identification of biomarkers for gliomas

Gliomas are the most common primary brain tumors in adults and, despite advances in the understandings of glioma pathogenesis in the genetic era, they are still ineradicable, justifying the need to develop more reliable diagnostic and prognostic biomarkers for this malignancy. Because changes in cerebrospinal fluid (CSF) are suggested to be capable of sensitively reflecting pathological processes, e.g., neoplastic conditions, in the central nervous system, CSF has been deemed a valuable source for potential biomarkers screening in this era of proteomics. This systematic review focused on the proteomic analysis of glioma CSF that has been published to date and identified a total of 19 differentially expressed proteins. Further functional and protein-protein interaction assessments were performed by using Protein Analysis Through Evolutionary Relationships (PANTHER) website and Ingenuity Pathway Analysis (IPA) software, which revealed several important protein networks (e.g., IL-6/STAT-3) and four novel focus proteins (IL-6, galanin (GAL), HSPA5, and WNT4) that might be involved in glioma pathogenesis. The concentrations of these focus proteins were subsequently determined by enzyme-linked immunosorbent assay (ELISA) in an independent set of CSF and tumor cyst fluid (CF) samples. Specifically, glioblastoma (GBM) CF had significantly lower GAL, HSPA5, and WNT4 levels than CSF from different grades of glioma. In contrast, IL-6 level was significantly higher in GBM CF when compared with CSF and, among different CSF groups, was highest in GBM CSF. Therefore, these candidate protein biomarkers, identified from both the literatures and in silico analysis, may have potentials in clinical diagnosis, prognosis evaluation, treatment response monitoring, and novel therapeutic targets identification for patients with glioma.

Proteomics for discovery of candidate colorectal cancer biomarkers

Colorectal cancer (CRC) is the second most common cause of cancer-related deaths in Europe and other Western countries, mainly due to the lack of well-validated clinically useful biomarkers with enough sensitivity and specificity to detect this disease at early stages. Although it is well known that the pathogenesis of CRC is a progressive accumulation of mutations in multiple genes, much less is known at the proteome level. Therefore, in the last years many proteomic studies have been conducted to find new candidate protein biomarkers for diagnosis, prognosis and as therapeutic targets for this malignancy, as well as to elucidate the molecular mechanisms of colorectal carcinogenesis. An important advantage of the proteomic approaches is the capacity to look for multiple differentially expressed proteins in a single study. This review provides an overview of the recent reports describing the different proteomic tools used for the discovery of new protein markers for CRC such as two-dimensional electrophoresis methods, quantitative mass spectrometry-based techniques or protein microarrays. Additionally, we will also focus on the diverse biological samples used for CRC biomarker discovery such as tissue, serum and faeces, besides cell lines and murine models, discussing their advantages and disadvantages, and summarize the most frequently identified candidate CRC markers.

Developing proteomics-based biomarkers for colorectal neoplasms for clinical practice: opportunities and challenges

Colorectal cancer (CRC) arises from the normal colon epithelium through the accumulation of genetic mutations and epigenetic alterations that are associated with progression along the histological adenoma-adenocarcinoma sequence. Elucidating the molecular alterations underlying disease progression will not only provide insight into the behavior of the tumors, but also could lead to the discovery of useful biomarkers for diagnosis, monitoring treatment responsiveness, or predicting disease outcomes. In the past a few years, there have been several evaluating differentially expressed protein biomarkers by employing proteomics technologies coupled with mass spectrometry. In the current review, we will briefly summarize the results from selected recent studies using tissue or serum samples from CRC patients in the past 5 years and discuss the opportunities and challenges in translating these findings from the research setting to clinical practice.

Quantitative mass spectrometry for colorectal cancer proteomics

This review documents the uses of quantitative MS applied to colorectal cancer (CRC) proteomics for biomarker discovery and molecular pathway profiling. Investigators are adopting various labeling and label-free MS approaches to quantitate differential protein levels in cells, tumors, and plasma/serum. We comprehensively review recent uses of this technology to examine mouse models of CRC, CRC cell lines, their secretomes and subcellular fractions, CRC tumors, CRC patient plasma/serum, and stool samples. For biomarker discovery these approaches are uncovering proteins with potential diagnostic and prognostic utility, while in vitro cell culture experiments are characterizing proteomic and phosphoproteomic responses to disrupted signaling pathways due to mutations or to inhibition of drugable enzymes.

Advances in the proteomic discovery of novel therapeutic targets in cancer

Proteomic approaches are continuing to make headways in cancer research by helping to elucidate complex signaling networks that underlie tumorigenesis and disease progression. This review describes recent advances made in the proteomic discovery of drug targets for therapeutic development. A variety of technical and methodological advances are overviewed with a critical assessment of challenges and potentials. A number of potential drug targets, such as baculoviral inhibitor of apoptosis protein repeat-containing protein 6, macrophage inhibitory cytokine 1, phosphoglycerate mutase 1, prohibitin 1, fascin, and pyruvate kinase isozyme 2 were identified in the proteomic analysis of drug-resistant cancer cells, drug action, and differential disease state tissues. Future directions for proteomics-based target identification and validation to be more translation efficient are also discussed.

Differential protein analysis of lymphocytes between children with acute lymphoblastic leukemia and healthy children

We identified differential proteins in lymphocytes between patients with childhood acute lymphoblastic leukemia (c-ALL) and healthy children. Samples of bone marrow lymphocytes from children with c-ALL and peripheral blood lymphocytes from healthy children were collected, and total proteins were extracted and separated from these samples followed by two-dimensional gel electrophoresis for comparative analysis. The differential protein spots in c-ALL cells were digested in situ, and then analyzed with matrix-assisted laser desorption ionization/time of flight mass spectrometry (MALDI-TOF-MS) followed by identification using the relevant database. Fifteen differential expression proteins were obtained by comparative proteomics analysis. Of the 15 differential proteins, eight were identified. Of the eight proteins, two had high expression and six low expression in c-ALL cells. The eight differential proteins are expected to become new diagnostic markers and drug targets for c-ALL.

Laser microdissection and two-dimensional difference gel electrophoresis reveal proteomic intra-tumor heterogeneity in colorectal cancer

We examined the proteins for intra-tumor heterogeneity in colorectal cancer. Tumor cells localized in the ulcer floor, the central area, and the invasive front, as well as normal colorectal epithelial cells were recovered from surgical specimens by laser microdissection. Proteome data were generated by 2D-DIGE and mass spectrometry. By distinguishing the tumor cells based on tissue localization, we observed 88 protein spots at a different intensity in tumor cell groups compared to normal epithelial cells. On the contrary, when the tissue localization of the tumor cells was not taken into account, only 1 protein spot was newly detected with a different intensity. The identified proteins corresponded functionally to the expected phenotypes in that particular region: proteins for stress response were identified in the ulcer floor, glucose metabolism proteins were found in the central area, and apoptosis proteins were associated with the invasive front. These results suggested the following: (1) proteome data may reflect the effects of the tissue microenvironment on tumor cells, (2) the tissue localization of tumor cells should be considered in the sampling process when comparing normal and tumor cells, and (3) we can expect novel findings on the backgrounds of intra-tumor heterogeneity by using the proteomic approach.

Expression of cell cycle regulators p21 and p27 as predictors of disease outcome in colorectal carcinoma

BACKGROUND

Recent studies suggest that aberrations in cell cycle checkpoint controllers are a common feature in human malignancies and predict prognosis independent of stage.

OBJECTIVES

This study correlated two cell cycle regulators (p27 and p21) with clinical and pathological variables in colorectal cancer (CRC) patients to assess their role as prognostic factors.

PATIENTS AND METHODS

A series of 65 CRC patients were analyzed for p27 and p21 expression in their tumors using immunohistochemistry.

RESULTS

Forty-six percent of tumors showed positive nuclear p27 expression, whereas 72% of cases were completely p21 negative. There were no significant correlations between p27 and p21 expression and gender, age, lymph node involvement, stage, and grade. However, p27 (but not p21) expression revealed highly significant correlation with tumor location (p < 0.01), depth of invasion (p < 0.03), and lympho-vascular invasion (p < 0.02). Tumors with high p27 expression showed a higher recurrence rate than tumors with no expression (p < 0.03). In Kaplan-Meier survival analysis, there was a significant (p = 0.046) difference in disease-free survival (DFS) between p27-positive and p27-negative tumors in favor of the latter. p21 did not show any predictive value of DFS (p < 0.7). Neither p27 nor p21 did predict disease-specific survival (DSS) in Kaplan-Meier analysis, but DSS time was much shorter for p27-positive tumors. In multivariate (Cox) model, p27 lost its value as independent predictor of DFS, and none of the covariates were independent predictors of DSS.

CONCLUSION

p27 expression seems to be more powerful than p21 expression in providing useful prognostic information in CRC, particularly in predicting the patients at high risk for recurrent disease. Larger cohort and longer follow-up are needed to fully elucidate the value of p27 (and p21) as independent predictors of disease outcome.

Proteomic-based identification of the APC-binding protein EB1 as a candidate of novel tissue biomarker and therapeutic target for colorectal cancer

Novel candidates of biomarker and therapeutic target in colorectal cancer (CRC) were investigated using a proteomic approach. The proteome of normal colorectal epithelial tissues was compared with that of the tumor ones in 59 CRC patients using two-dimensional difference gel electrophoresis. Of 3458 protein spots, 110 exhibited statistically significant (p<0.01) differences in intensity (more than 2.5-folds) between the normal and tumor tissue groups. Of 67 unique gene products that were identified for 105 of the 110 protein spots, we focused on the higher expression of the adenoma polyposis coli-binding protein EB1 (EB1). EB1 was originally discovered as a binding protein of APC, which is a tumor suppressor gene product, and the expression of EB1 has been associated with poor prognosis in several malignancies but not in CRC. Immunohistochemical analysis of the 132 CRC cases revealed that EB1 was overexpressed in tumor cells in correlation with poor prognosis. Suppression of EB1 by RNAi inhibited CRC cell proliferation and invasion. In this study, the overexpression of EB1 in CRC tissues correlating with prognosis, and its functional contribution to the malignant phenotypes of CRC cells are described. The present findings indicate that EB1 is a potential biomarker and therapeutic target in CRC.

Apoptotic activity in Libyan breast cancer

BACKGROUND

We evaluated the relationship of the apoptotic activity index (AI) and the standardized mitotic-apoptotic ratio (SMI/AI) with clinicopathological features and prognosis in Libyan female breast cancer (BC) patients. We then compared our results with corresponding results in Finnish and Nigerian female BC patients.

METHODS

Histological samples of breast carcinoma from 130 patients were retrospectively studied: an estimation of the apoptotic activity per square millimeter (expressed as apoptotic activity index (AI)), and standardized mitotic-apoptotic ratio (SMI/AI) was made, and the results compared with the clinicopathological features and the patient's survival.

RESULTS

There was a statistically significant correlation between the AI and most of the clinicopathological features; the strongest association was observed for clinical stage lymph node (LN) status (P = 0.005). There were also correlations between AI and histological grade (P = 0.035), large tumor size (P = 0.011) and the clinical stage (P = 0.009). There were, however, prominent AI differences between Libyan, Nigerian and Finnish populations. The mean values of AI and SMI/AI in Libyan BC patients were 12.8 apoptotic figures per square millimeter and 2.8, respectively. The Libyan AI is slightly higher than in Nigeria, but much higher than in Finland. The differences between countries are seen throughout the samples as well as being present in certain subgroups. The survival analysis indicated that short survival time was associated with high apoptotic indices values and so can identify aggressive tumors and provide significant prognostic support. The cutoff (4 and 18 apoptosis/mm2) of AI might be applied as a quantitative criterion for Libyan BC to separate the patients into good, moderate and bad prognosis groups.

CONCLUSIONS

The results indicated that the differences in AI among the three countries may be due to the known variation in the distribution of genetic markers in these populations. Improvement in health care and introduction of screening programs, however, could be very helpful in the Libyan population.

Comparative proteomic analysis for the insoluble fractions of colorectal cancer patients

We used label-free quantitative proteomics with the insoluble fractions from colorectal cancer (CRC) patients to gain further insight into the utility of profiling altered protein expression as a potential biomarker for cancer. The insoluble fractions were prepared from paired tumor/normal biopsies from 13 patients diagnosed with CRC (stages I to IV). Fifty-six proteins identified in data pooled from the 13 cases were differentially expressed between the tumor and adjacent normal tissue. The connections between these proteins are involved in reciprocal networks related to tumorigenesis, cancer incidence based on genetic disorder, and skeletal and muscular disorders. To assess their potential utility as biomarkers, the relative expression levels of the proteins were validated using personal proteomics and a heat map to compare five individual CRC samples with five normal tissue samples. Further validation of a panel of proteins (KRT5, JUP, TUBB, and COL6A1) using western blotting confirmed the differential expression. These proteins gave specific network information for CRC, and yielded a panel of novel markers and potential targets for treatment. It is anticipated that the experimental approach described here will increase our understanding of the membrane environment in CRC, which may provide direction for making diagnoses and prognoses through molecular biomarker targeting.

Loss of E-cadherin expression predicts disease recurrence and shorter survival in colorectal carcinoma

The traditional staging system is currently inadequate for identifying those patients with colorectal carcinoma (CRC) who carry a high risk for poor outcome. In this study, the expression of E-cadherin was evaluated in CRC to determine its correlation with clinico-pathological variables, and association with disease outcome in patients with long-term follow-up. The present series consisted of tissue samples obtained from 230 patients with stage I, II, III, or IV CRC treated during 1981-1990 at Turku University Hospital. Archival paraffin-embedded samples were used to build up tissue microarray blocks, and E-cadherin expression was assessed by immunohistochemistry using an automated staining system. Different grading systems were tested for expression of E-cadherin. Fifty-nine percent of all tumors were positive for E-Cadherin. There was no significant correlation between E-cadherin expression and gender (p < 0.83), localization (p < 0.45), tumor invasion (p < 0.32), or histologic grade (p < 0.41). However, loss of E-cadherin expression was significantly associated with older age (p < 0.03) and lymph node involvement (p < 0.02), and with borderline significance with advanced stage (p < 0.09) and tumor metastasis (p < 0.09). In univariate (Kaplan-Meier) survival analysis, positive E-cadherin significantly (p = 0.009) predicted longer disease-free survival (DFS), and the same was true with disease-specific survival (DSS) as well (p = 0.007). In multivariate (Cox) survival analysis, E-cadherin retained its significance as independent predictor of DFS (HR = 1.56; 95% CI 1.01-2.42, p = 0.043), but not DSS. A sub-group analysis revealed that E-cadherin expression also predicts DFS (p < 0.01) and DSS (p < 0.04) in stage II CRC. Our results implicate the usefulness of E-cadherin expression in predicting disease recurrence and long-term survival in CRC.

Global proteomics and metabolomics in cancer biomarker discovery

Chromatography and electrophoresis have been used for the last half-century to separate small and large molecules. Advances in MS instrumentation and techniques for sample introduction into the mass analyzer (i.e. matrix-assisted laser desorption/ionization and electrospray ionization), chromatography in all its formats and modes and two-dimensional gel electrophoresis, including two-dimensional difference gel electrophoresis, enabled the separation of complex biological mixtures, such as the proteome and the metabolome, in a biological sample. These advances have made it possible to identify compounds that can be used to discriminate between two samples taken from healthy and diseased individuals. The objective is to find proteins or metabolites that can be used as a clinical test for the early diagnosis, prognosis and monitoring of the disease and the outcome of therapy. In this manuscript, we present an overview of what has been achieved in the search for biomarkers, with emphasis on cancer, using separation science and MS.

Identification of biomarkers for colorectal cancer through proteomics-based approaches

The early detection of colorectal cancer is one of the great challenges in the battle against this disease. However, owing to its heterogeneous character, single markers are not likely to provide sufficient diagnostic power to be used in colorectal cancer population screens. This review provides an overview of recent studies aimed at the discovery of new diagnostic protein markers through proteomics-based approaches. It indicates that studies that start with the proteomic analysis of tumor tissue or tumor cell lines (near the source) have a high potential to yield novel and colorectal cancer-specific biomarkers. In the next step, the diagnostic accuracy of these candidate markers can be assessed by a targeted ELISA assay using serum from colorectal cancer patients and healthy controls. Instead, direct proteomic analysis of serum yields predominantly secondary markers composed of fragments of abundant serum proteins that may be associated with tumor-associated protease activity, and alternatively, immunoproteomic analysis of the serum antibody repertoire provides a valuable tool to identify the molecular imprint of colorectal cancer-associated antigens directly from patient serum samples. The latter approach also allows a relatively easy translation into targeted assays. Eventually, multimarker assays should be developed to reach a diagnostic accuracy that meets the stringent criteria for colorectal cancer screening at the population level.

Global expression study in colorectal cancer on proteins with alkaline isoelectric point by two-dimensional difference gel electrophoresis

Colorectal cancer is one of the leading causes of cancer death worldwide. To identify candidates for biomarkers and therapeutic targets, we investigated the proteome of colorectal cancer tissues. Using 2D-DIGE in combination with our original large format electrophoresis apparatus, we compared surgically resected normal and tumor tissues from 53 patients with colorectal cancer. We focused on proteins with an alkaline pI using IPG gels for the alkaline range. We observed 1687 protein spots, and found 100 spots with statistical (p<0.01) and significant (>2-fold) differences between the normal and the tumor tissue groups. Among these 100 protein spots, five showed a different intensity between tumor tissues from the stage-II and the stage-III patients. MS experiments revealed that these 100 protein spots corresponded to 58 unique proteins. These included six proteins which had not been previously reported to be associated with colorectal cancer. Among these proteins, five were not reported in any type of malignancy. IEF/western blotting confirmed the differences in protein expression between the normal and the tumor tissues. These results may provide an insight for biomarker development and drug target discovery in colorectal cancer.

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.

Cell surface markers in colorectal cancer prognosis

The classification of colorectal cancers (CRC) is currently based largely on histologically determined tumour characteristics, such as differentiation status and tumour stage, i.e., depth of tumour invasion, involvement of regional lymph nodes and the occurrence of metastatic spread to other organs. These are the conventional prognostic factors for patient survival and often determine the requirement for adjuvant therapy after surgical resection of the primary tumour. However, patients with the same CRC stage can have very different disease-related outcomes. For some, surgical removal of early-stage tumours leads to full recovery, while for others, disease recurrence and metastasis may occur regardless of adjuvant therapy. It is therefore important to understand the molecular processes that lead to disease progression and metastasis and to find more reliable prognostic markers and novel targets for therapy. This review focuses on cell surface proteins that correlate with tumour progression, metastasis and patient outcome, and discusses some of the challenges in finding prognostic protein markers in CRC.

Integrating proteomic and transcriptomic high-throughput surveys for search of new biomarkers of colon tumors

To the search of new colon tumor biomarkers in the transition from normal colon (NC) mucosa to adenoma (AD) and adenocarcinoma (AC), we integrated microarray data with the results of a high-throughput proteomic workflow. In proteomic study, we used a modified isoelectric focusing protocol on strips with an immobilized pH gradient to separate peptides labeled with iTRAQ (isobaric tags for relative and absolute quantitation) tags followed by liquid chromatography-tandem mass spectrometry analysis. Gene expression measurements were done using Affymetrix GeneChip HG-U133plus2 microarrays and quantitative reverse transcriptase PCR (q-RT-PCR). We identified 3,886 proteins with at least two peptides. Of them, 1,061 proteins were differentially expressed [FC ≥ 1.5; FDR ≤ 0.01] in two pair-wise comparisons: AD vs. NC and AC vs. AD while 15 and 23 proteins were progressively up-regulated and down-regulated in the NC/AD/AC sequence, respectively. The quantitative proteomic information was subsequently correlated with microarray data. For a collection of genes with the same direction of changes of both mRNA and protein levels, we obtained 785/853/795 genes in AD vs. NC/AC vs. NC/AC vs. AD comparison, respectively. Further evaluation of sequentially altered gene expression by q-RT-PCR on individual samples of 24 NCs, 42 ADs, and 26 ACs confirmed progressive expression of six genes: biglycan, calumenin, collagen type XII, alpha 1 (COL12A1), monoamine oxidase A (MAOA), ectonucleoside triphosphate diphosphohydrolase 5 (ENTPD5), and MOCO sulphurase C-terminal domain-containing 2 (MOSC2). Among them, three continuously down-regulated (MAOA, ENTPD5, and MOSC2) and one continuously overexpressed (COL12A1) are reported, to our best knowledge, for the first time in a connection to colon cancer onset.