Detection of colorectal adenoma and cancer based on transthyretin and C3a-desArg serum levels

Analysis of the Relationship between the Expression Level of TTR and APOH and Prognosis in Patients with Colorectal Cancer Metastasis Based on Bioinformatics

The expression of TTR and apolipoprotein H (APOH) genes and their relationship with prognosis in patients with colorectal cancer (CRC) metastasis by using bioinformatics analysis techniques are explored. The expression profiles of related genes in patients with CRC metastasis are retrieved from the Gene Expression Omnibus (GEO) database. The core genes transthyretin (TTR) and APOH are screened by constructing protein-protein interaction (PPI) network, and the corresponding patient data of 327 patients are extracted and included in the metastasis group. The TTR and APOH genes of 300 patients without CRC metastasis are screened and included in the control group. The relationship between the expression levels of TTR and APOH and the clinicopathological parameters of patients with CRC metastasis is analyzed. Kaplan-Meier survival curve is drawn to observe the influence of overexpression and low expression of TTR and APOH on the prognosis and survival of patients in the metastatic group. Receiver operating characteristic (ROC) curve is drawn to observe the prognostic efficacy of combined TTR and APOH detection in patients with CRC metastasis. The experimental results show that bioassay can confirm the close relationship between TTR, APOH, and patients with CRC metastasis. Regular detection of serum TTR and APOH expression can effectively assess the patient's condition and take measures to improve the prognosis of the patients.

Diagnostic value of apolipoprotein C-I, transthyretin and apolipoprotein C-III in gastric cancer

Diagnostic value of apolipoprotein C-I (ApoC-I), transthyretin (TTR) and ApoC-III in gastric cancer were evaluated. Retrospective analysis methods were used to collect 60 patients with gastric cancer first diagnosed in The First Affiliated Hospital of Jiaxing University. There were 60 patients with chronic atrophic gastritis in the benign lesion group and 60 healthy individuals in the control group. The expression levels of serum ApoC-I, TTR and ApoC-III was detected by enzyme-linked immunosorbent assay. Differences existed in the expression levels of ApoC-I, TTR and ApoC-III in the gastric cancer group, benign lesion group and control group (P<0.001), with the expression levels of ApoC-I, TTR and ApoC-III in the gastric cancer group being lower than that of the benign lesion group (P<0.05), and the expression levels of ApoC-I, TTR and ApoC-III in the benign lesion group being lower than that of the control group (P<0.05). The expression levels of ApoC-I, TTR and ApoC-III in the gastric cancer group were to a certain degree correlated with the clinical stage, lymph node metastasis and differentiation of patients in the gastric cancer group (P<0.05). The specificity and negative predictive value of combined detection were proven to be higher than the separate detection of the three factors (P<0.05). The detection of serum ApoC-I, TTR and ApoC-III was of great significance in the diagnosis of gastric cancer and the estimation of its severity. The method of combined detection is worth a further in-depth study as it could improve the specificity of diagnosis and have a higher negative predictive value.

Role of the complement system in the tumor microenvironment

The complement system has traditionally been considered a component of innate immunity against invading pathogens and "nonself" cells. Recent studies have demonstrated the immunoregulatory functions of complement activation in the tumor microenvironment (TME). The TME plays crucial roles in tumorigenesis, progression, metastasis and recurrence. Imbalanced complement activation and the deposition of complement proteins have been demonstrated in many types of tumors. Plasma proteins, receptors, and regulators of complement activation regulate several biological functions of stromal cells in the TME and promote the malignant biological properties of tumors. Interactions between the complement system and cancer cells contribute to the proliferation, epithelial-mesenchymal transition, migration and invasion of tumor cells. In this review, we summarize recent advances related to the function of the complement system in the TME and discuss the therapeutic potential of targeting complement-mediated immunoregulation in cancer immunotherapy.

Mass spectrometry based translational proteomics for biomarker discovery and application in colorectal cancer

Colorectal cancer (CRC) is a leading cause of cancer-related death in the world. Clinically, early detection of the disease is the most effective approach to tackle this tough challenge. Discovery and development of reliable and effective diagnostic tools for the assessment of prognosis and prediction of response to drug therapy are urgently needed for personalized therapies and better treatment outcomes. Among many ongoing efforts in search for potential CRC biomarkers, MS-based translational proteomics provides a unique opportunity for the discovery and application of protein biomarkers toward better CRC early detection and treatment. This review updates most recent studies that use preclinical models and clinical materials for the identification of CRC-related protein markers. Some new advances in the development of CRC protein markers such as CRC stem cell related protein markers, SRM/MRM-MS and MS cytometry approaches are also discussed in order to address future directions and challenges from bench translational research to bedside clinical application of CRC biomarkers.

Two-temperature formalin fixation preserves activation states efficiently

Modern pathology is built around the principle of preserving tissues such that the in vivo molecular status is maintained at levels representative of the disease state. Tissues are immersed in a solution of fixative which slowly inactivates biological activities, thus preserving the sample. Further processing ultimately allows the tissue to be embedded into wax for thin sectioning and staining for interpretation microscopically. Every year, around 7 billion tissue samples are submitted for processing in the United States alone. With this huge workload, histology laboratories are looking for faster methods of performing fixation, which currently require from several hours to days to complete. Ideally, this procedure could be standardized and would be quicker with better preservation over a wide range of biologically relevant molecules.

Prediction of individual response to anticancer therapy: historical and future perspectives

Since the introduction of chemotherapy for cancer treatment in the early 20th century considerable efforts have been made to maximize drug efficiency and at the same time minimize side effects. As there is a great interpatient variability in response to chemotherapy, the development of predictive biomarkers is an ambitious aim for the rapidly growing research area of personalized molecular medicine. The individual prediction of response will improve treatment and thus increase survival and life quality of patients. In the past, cell cultures were used as in vitro models to predict in vivo response to chemotherapy. Several in vitro chemosensitivity assays served as tools to measure miscellaneous endpoints such as DNA damage, apoptosis and cytotoxicity or growth inhibition. Twenty years ago, the development of high-throughput technologies, e.g. cDNA microarrays enabled a more detailed analysis of drug responses. Thousands of genes were screened and expression levels were correlated to drug responses. In addition, mutation analysis became more and more important for the prediction of therapeutic success. Today, as research enters the area of -omics technologies, identification of signaling pathways is a tool to understand molecular mechanism underlying drug resistance. Combining new tissue models, e.g. 3D organoid cultures with modern technologies for biomarker discovery will offer new opportunities to identify new drug targets and in parallel predict individual responses to anticancer therapy. In this review, we present different currently used chemosensitivity assays including 2D and 3D cell culture models and several -omics approaches for the discovery of predictive biomarkers. Furthermore, we discuss the potential of these assays and biomarkers to predict the clinical outcome of individual patients and future perspectives.

Biomarkers for early detection of colorectal cancer and polyps: systematic review

There is growing interest in early detection of colorectal cancer as current screening modalities lack compliance and specificity. This study systematically reviewed the literature to identify biomarkers for early detection of colorectal cancer and polyps. Literature searches were conducted for relevant papers since 2007. Human studies reporting on early detection of colorectal cancer and polyps using biomarkers were included. Methodologic quality was evaluated, and sensitivity, specificity, and the positive predictive value (PPV) were reported. The search strategy identified 3,348 abstracts. A total of 44 papers, examining 67 different tumor markers, were included. Overall sensitivities for colorectal cancer detection by fecal DNA markers ranged from 53% to 87%. Combining fecal DNA markers increased the sensitivity of colorectal cancer and adenoma detection. Canine scent detection had a sensitivity of detecting colorectal cancer of 99% and specificity of 97%. The PPV of immunochemical fecal occult blood test (iFOBT) is 1.26%, compared with 0.31% for the current screening method of guaiac fecal occult blood test (gFOBT). A panel of serum protein biomarkers provides a sensitivity and specificity above 85% for all stages of colorectal cancer, and a PPV of 0.72%. Combinations of fecal and serum biomarkers produce higher sensitivities, specificities, and PPVs for early detection of colorectal cancer and adenomas. Further research is required to validate these biomarkers in a well-structured population-based study.

Low-mass-ion discriminant equation: a new concept for colorectal cancer screening

Blood metabolites can be detected as low-mass ions (LMIs) by mass spectrometry (MS). These LMIs may reflect the pathological changes in metabolism that occur as part of a disease state, such as cancer. We constructed a LMI discriminant equation (LOME) to investigate whether systematic LMI profiling might be applied to cancer screening. LMI information including m/z and mass peak intensity was obtained by five independent MALDI-MS analyses, using 1,127 sera collected from healthy individuals and cancer patients with colorectal cancer (CRC), breast cancer (BRC), gastric cancer (GC) and other types of cancer. Using a two-stage principal component analysis to determine weighting factors for individual LMIs and a two-stage LMI selection procedure, we selected a total of 104 and 23 major LMIs by the LOME algorithms for separating CRC from control and rest of cancer samples, respectively. CRC LOME demonstrated excellent discriminating power in a validation set (sensitivity/specificity: 93.21%/96.47%). Furthermore, in a fecal occult blood test (FOBT) of available validation samples, the discriminating power of CRC LOME was much stronger (sensitivity/specificity: 94.79%/97.96%) than that of the FOBT (sensitivity/specificity: 50.00%/100.0%), which is the standard CRC screening tool. The robust discriminating power of the LOME scheme was reconfirmed in screens for BRC (sensitivity/specificity: 92.45%/96.57%) and GC (sensitivity/specificity: 93.18%/98.85%). Our study demonstrates that LOMEs might be powerful noninvasive diagnostic tools with high sensitivity/specificity in cancer screening. The use of LOMEs could potentially enable screening for multiple diseases (including different types of cancer) from a single sampling of LMI information.

Comparative proteomic study for profiling differentially expressed proteins between Chinese left- and right-sided colon cancers

The aim of the present study is to profile differentially expressed protein markers between left-sided colon cancer (LSCC) and right-sided colon cancer (RSCC). Fresh tumor tissue samples from LSCC (n = 7) and RSCC (n = 7) groups were analyzed by two-dimensional electrophoresis coupled with MALDI-TOF-MS, followed by Western blotting. In 50 paraffin embedded samples from each group, levels of four differentially expressed proteins (identified by proteomics analysis) were measured by tissue microarray with immunohistochemistry staining to compare the different protein markers between LSCC and RSCC. Sixteen proteins were found to be differentially expressed between LSCC and RSCC. Ten proteins including HSP-60 and PDIA1 were identified to be highly expressed in LSCC (P < 0.01 or P < 0.05), while the expression of six proteins including EEF1D and HSP-27 were higher in RSCC (P < 0.01 or P < 0.05). Virtually all of the indentified proteins were involved in cellular energy metabolism, protein folding/unfolding, and/or oxidative stress. Human colon tumors at various locations have different proteomic biomarkers. Differentially expressed proteins associated with energy metabolism, protein folding/unfolding and oxidative stress contribute to different tumorigenesis, tumor progression, and prognosis between left- and right-sided colon cancer.

Identification of potential complementary serum biomarkers to differentiate prostate cancer from benign prostatic hyperplasia using gel- and lectin-based proteomics analyses

Diagnosis of prostate cancer (PCa) is currently much reliant on the invasive and time-consuming transrectal ultrasound-guided biopsy of the prostate gland, particularly in light of the inefficient use of prostate-specific antigen as its biomarker. In the present study, we have profiled the sera of patients with PCa and benign prostatic hyperplasia (BPH) using the gel- and lectin-based proteomics methods and demonstrated the significant differential expression of apolipoprotein AII, complement C3 beta chain fragment, inter-alpha-trypsin inhibitor heavy chain 4 fragment, transthyretin, alpha-1-antitrypsin, and high molecular weight kininogen (light chain) between the two groups of patients' samples. Our data are suggestive of the potential use of the serum proteins as complementary biomarkers to effectively discriminate PCa from BPH, although this requires further extensive validation on clinically representative populations.

Human urine proteomics: building a list of human urine cancer biomarkers

In the last decade, several reports have focused on the identification and characterization of proteins present in urine. In an effort to build a list of proteins of interest as biomarkers, we reviewed the largest urine proteomes and built two updated lists of proteins of interest (available as supplementary tables). The first table includes a consensus list of 443 proteins found in urine by independent laboratories and reported on the top three largest urine proteomes currently published. This consensus list of proteins could serve as biomarkers to diagnose, monitor and manage a number of diseases. Here, we focus on a reduced list of 35 proteins with potential interest as cancer biomarkers in urine following two criteria: first, proteins previously detected in urine using bottom-up proteomic experiments, and second, those suggested as cancer protein biomarkers in human plasma. In an effort to standardize the information presented and its use in future studies, here we include the updated International Protein Index (v. 3.80) and primary Swiss-Prot accession numbers, official gene symbols and recommended full names. The main variables that influence urine proteomic experiments are also discussed.

Murine fecal proteomics: a model system for the detection of potential biomarkers for colorectal cancer

Tumor related products shed into the feces offer a potential source of biomarkers for the detection of colorectal cancer (CRC). Using SDS-PAGE followed by nanoflow reversed-phased LC-MS/MS to analyse fecal samples from Apc(Min/+) mice (that develop spontaneous multiple intestinal neoplasia with age) we have identified 336 proteins (115 proteins of murine origin, 201 from fecal bacteria, 18 associated with food intake and 2 of apparent parasitic origin). 75% of the murine proteins identified in this study are predicted to be extracellular or associated with the cell plasma membrane. Of these proteins, a number of the murine homologues of colorectal cancer associated proteins (CCAP) such as hemoglobin, haptoglobin, hemopexin, alpha-2-macroglobulin and cadherin-17 have been identified, demonstrating the potential of fecal proteomics for detecting potential biomarkers and paving the way for subsequent MS/MS based biomarker studies on similar human samples.

Quantification of Serum Proteins of Metastatic Oral Cancer Patients Using LC-MS/MS and iTRAQ Labeling

Metastasis is a critical event in oral squamous cell carcinoma (OSCC) progression. In this study, we have performed quantitative analysis of serum proteins from non-metastatic (lymph-node metastasis free) and metastatic OSCC patients using liquid chromatography-tandem mass spectrometry (LC-MS/MS) with iTRAQ labeling (isobaric tagging for relative and absolute quantitation). To eliminate highly abundant proteins, the serum samples were initially separated by SDS-PAGE and only low abundant protein bands were excised for subsequent in-gel tryptic digestion. The resulting peptides were then extracted from each sample gels and labeled with iTRAQ reagent 114 (control), 116 (non-metastatic) and 117 (metastatic), respectively. Afterwards, the labeled samples were combined and subjected to LC-MS/MS analysis using linear ion trap (LIT) MS with pulsed Q collision induced dissociation (PQD). A total of 64 proteins were identified and quantified by this approach. Our study showed that iTRAQ labeling and LIT-MS with PQD is a valuable approach to quantification of serum proteins. We also demonstrated the presence of differentially expressed serum proteins between non-metastatic and metastatic OSCCs that may be further validated as biomarkers for metastatic OSCC. However, in order to comprehensively quantify low abundant serum proteins, a more efficient approach is needed to deplete highly abundant proteins prior to quantitative serum proteome analysis of OSCC.