Comparative serum proteomic analysis of serum diagnosis proteins of colorectal cancer based on magnetic bead separation and maldi-tof mass spectrometry.

BACKGROUND: At present, the diagnosis of colorectal cancer (CRC) requires a colorectal biopsy which is an invasive procedure. We undertook this pilot study to develop an alternative method and potential new biomarkers for diagnosis, and validated a set of well-integrated tools called ClinProt to investigate the serum peptidome in CRC patients. METHODS: Fasting blood samples from 67 patients diagnosed with CRC by histological diagnosis, 55 patients diagnosed with colorectal adenoma by biopsy, and 65 healthy volunteers were collected. Division was into a model construction group and an external validation group randomly. The present work focused on serum proteomic analysis of model construction group by ClinProt Kit combined with mass spectrometry. This approach allowed construction of a peptide pattern able to differentiate the studied populations. An external validation group was used to verify the diagnostic capability of the peptidome pattern blindly. An immunoassay method was used to determine serum CEA of CRC and controls. RESULTS: The results showed 59 differential peptide peaks in CRC, colorectal adenoma and health volunteers. A genetic algorithm was used to set up the classification models. Four of the identified peaks at m/z 797, 810, 4078 and 5343 were used to construct peptidome patterns, achieving an accuracy of 100% (> CEA, P < 0. 05). Furthermore, the peptidome patterns could differentiate the validation group with high accuracy close to 100%. CONCLUSIONS: Our results showed that proteomic analysis of serum with MALDI-TOF MS is a fast and reproducible approach, which may provide a novel approach to screening for CRC.

Identification of tubulin beta chain, thymosin beta-4-like protein 3, and cytochrome b-c1 complex subunit 1 as serological diagnostic biomarkers of gastric cancer.

OBJECTIVE: Despite major advances in its diagnosis and treatment, gastric cancer (GC) remains a major life-threatening disease. Treatment of the disease is further aggravated by the lack of diagnostic biomarkers that can aid in the early detection of GC and promote its favorable prognosis. The present work aims to identify novel diagnostic biomarkers for GC. DESIGN AND METHODS: The present work is a case-control study that focuses on proteomic analysis of serum from healthy volunteers and GC patients using ClinProt profiling technology based on mass spectrometry. A pattern of proteins/peptides with the ability to differentiate the studied populations was identified. Deregulated proteins/peptides differentially expressed in the serum of patients compared with healthy volunteers were identified by mass spectroscopy. RESULTS: A pattern of proteins/peptides consisting of four protein/peptide peaks at m/z 1467, 1867, 2701, and 2094 was identified. These protein/peptide peaks were able to differentiate the studied populations with close to 100% sensitivity and specificity. Three of the deregulated proteins/peptides at m/z 1867, 2701, and 2094 were identified by mass spectroscopy (LTQ Orbitrap XL) as tubulin beta chain, thymosin beta-4-like protein 3, and cytochrome b-c1 complex subunit 1, respectively. CONCLUSIONS: The pattern of proteins/peptides identified in the present work shows great potential for GC diagnosis. Deregulated proteins of tubulin beta chain, thymosin beta-4-like protein 3, and cytochrome b-c1 complex subunit 1 may be involved in the pathogenesis of GC and serve as potential serological diagnostic biomarkers.

Serum peptidome patterns of colorectal cancer based on magnetic bead separation and MALDI-TOF mass spectrometry analysis.

Background. Colorectal cancer (CRC) is one of the most common cancers in the world, identification of biomarkers for early detection of CRC represents a relevant target. The present study aims to determine serum peptidome patterns for CRC diagnosis. Methods. The present work focused on serum proteomic analysis of 32 health volunteers and 38 CRC by ClinProt Kit combined with mass spectrometry. This approach allowed the construction of a peptide patterns able to differentiate the studied populations. An independent group of serum (including 33 health volunteers, 34 CRC, 16 colorectal adenoma, 36 esophageal carcinoma, and 31 gastric carcinoma samples) was used to verify the diagnostic and differential diagnostic capability of the peptidome patterns blindly. An immunoassay method was used to determine serum CEA of CRC and controls. Results. A quick classifier algorithm was used to construct the peptidome patterns for identification of CRC from controls. Two of the identified peaks at m/z 741 and 7772 were used to construct peptidome patterns, achieving an accuracy close to 100% (>CEA, P < 0.05). Furthermore, the peptidome patterns could differentiate validation group with high accuracy. Conclusions. These results suggest that the ClinProt Kit combined with mass spectrometry yields significantly higher accuracy for the diagnosis and differential diagnosis of CRC.

Serum peptidome patterns of breast cancer based on magnetic bead separation and mass spectrometry analysis.

BACKGROUND: Breast cancer is one of the most common cancers in the world, and the identification of biomarkers for the early detection of breast cancer is a relevant target. The present study aims to determine serum peptidome patterns for screening of breast cancer. METHODS: The present work focused on the serum proteomic analysis of 36 healthy volunteers and 37 breast cancer patients using a ClinProt Kit combined with mass spectrometry (MS). This approach allows the determination of peptidome patterns that are able to differentiate the studied populations. An independent group of sera (36 healthy volunteers and 37 breast cancer patients) was used to verify the diagnostic capabilities of the peptidome patterns blindly. An immunoassay method was used to determine the serum mucin 1 (CA15-3) of validation group samples. RESULTS: Support Vector Machine (SVM) Algorithm was used to construct the peptidome patterns for the identification of breast cancer from the healthy volunteers. Three of the identified peaks at m/z 698, 720 and 1866 were used to construct the peptidome patterns with 91.78% accuracy. Furthermore, the peptidome patterns could differentiate the validation group achieving a sensitivity of 91.89% (34/37) and a specitivity of 91.67% (33/36) (> CA 15-3, P < 0.05). CONCLUSIONS: These results suggest that the ClinProt Kit combined with MS shows great potentiality for the diagnosis of breast cancer. VIRTUAL SLIDES: The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1501556838687844.

Discovery and verification of gelsolin as a potential biomarker of colorectal adenocarcinoma in the Chinese population: Examining differential protein expression using an iTRAQ labelling-based proteomics approach.

OBJECTIVE: To identify and validate potential biomarkers of colorectal adenocarcinoma using a proteomic approach. METHODS: Multidimensional liquid chromatography/mass spectrometry was used to analyze biological samples labelled with isobaric mass tags for relative and absolute quantitation to identify differentially expressed proteins in human colorectal adenocarcinoma and paired normal mucosa for the discovery of cancerous biomarkers. Cancerous and noncancerous samples were compared using online and offline separation. Protein identification was performed using mass spectrometry. The downregulation of gelsolin protein in colorectal adenocarcinoma samples was confirmed by Western blot analysis and validated using immunohistochemistry. RESULTS: A total of 802 nonredundant proteins were identified in colorectal adenocarcinoma samples, 82 of which fell outside the expression range of 0.8 to 1.2, and were considered to be potential cancer-specific proteins. Immunohistochemistry revealed a complete absence of gelsolin expression in 86.89% of samples and a reduction of expression in 13.11% of samples, yielding a sensitivity of 86.89% and a specificity of 100% for distinguishing colorectal adenocarcinoma from normal tissue. CONCLUSIONS: These findings suggest that decreased expression of gelsolin is a potential biomarker of colorectal adenocarcinoma.