Mass spectrometry protein expression profiles in colorectal cancer tissue associated with clinico-pathological features of disease

Abstract

BackgroundStudies of several tumour types have shown that expression profiling of cellular protein extracted from surgical tissue specimens by direct mass spectrometry analysis can accurately discriminate tumour from normal tissue and in some cases can sub-classify disease. We have evaluated the potential value of this approach to classify various clinico-pathological features in colorectal cancer by employing matrix-assisted laser desorption ionisation time of-flight-mass spectrometry (MALDI-TOF MS).MethodsProtein extracts from 31 tumour and 33 normal mucosa specimens were purified, subjected to MALDI-Tof MS and then analysed using the 'GenePattern' suite of computational tools (Broad Institute, MIT, USA). Comparative Gene Marker Selection with either a t-test or a signal-to-noise ratio (SNR) test statistic was used to identify and rank differentially expressed marker peaks. The k-nearest neighbours algorithm was used to build classification models either using separate training and test datasets or else by using an iterative, 'leave-one-out' cross-validation method.Results73 protein peaks in the mass range 1800-16000Da were differentially expressed in tumour verses adjacent normal mucosa tissue (P ≤ 0.01, false discovery rate ≤ 0.05). Unsupervised hierarchical cluster analysis classified most tumour and normal mucosa into distinct cluster groups. Supervised prediction correctly classified the tumour/normal mucosa status of specimens in an independent test spectra dataset with 100% sensitivity and specificity (95% confidence interval: 67.9-99.2%). Supervised prediction using 'leave-one-out' cross validation algorithms for tumour spectra correctly classified 10/13 poorly differentiated and 16/18 well/moderately differentiated tumours (P = < 0.001; receiver-operator characteristics - ROC - error, 0.171); disease recurrence was correctly predicted in 5/6 cases and disease-free survival (median follow-up time, 25 months) was correctly predicted in 22/23 cases (P = < 0.001; ROC error, 0.105). A similar analysis of normal mucosa spectra correctly predicted 11/14 patients with, and 15/19 patients without lymph node involvement (P = 0.001; ROC error, 0.212).ConclusionsProtein expression profiling of surgically resected CRC tissue extracts by MALDI-TOF MS has potential value in studies aimed at improved molecular classification of this disease. Further studies, with longer follow-up times and larger patient cohorts, that would permit independent validation of supervised classification models, would be required to confirm the predictive value of tumour spectra for disease recurrence/patient survival.

Identification of Serum Peptidome Signatures of Non-Small Cell Lung Cancer

“…A number of global metabolic profiling studies of non-small cell lung cancer (NSCLC) patients using gas chromatography-mass spectrometry [ 6 , 7 , 8 , 9 , 10 ] or liquid-chromatography-mass spectrometry [ 7 , 9 , 11 , 12 ] was presented. Mass spectrometry-based targeted metabolomic approach revealed altered levels of some plasma free amino acids in NSCLC subjects [ 13 , 14 ]. Another promising approach in discovery of candidate LC biomarkers represents proteomic research.…”

“…In proteomic and metabolomic research and the analysis of exhaled breath it was indicated that a panel of biomarkers has a higher discriminatory power in LC detection than a single compound alone [ 13 , 24 , 25 , 26 ]. The use of a single compound for cancer diagnosis has a higher risk of producing false-positive results caused by links with other disorders.…”

Comparative Evaluation of Strategies for Quantifying Signaling Pathway Proteins in Ewing Sarcoma

“…However, the mass spectrometry technique does define a lower limit of sensitivity and it may be that the low success rate also represents clinically insignificant levels of detection in these samples. Given previous success with this technique in other tumor types using frozen tissue 26,27 , it is possible that the formalin fixation and, in a subset of cases, decalcification, may have interfered with this approach. While the protein expression levels in our study using tissue from skeletal and extraskeletal sources appeared similar, more samples would be needed to confirm this finding.…”

MALDI-TOF MS Combined With Magnetic Beads for Detecting Serum Protein Biomarkers and Establishment of Boosting Decision Tree Model for Diagnosis of Colorectal Cancer

“…As whole patterns of proteins in the serum samples were analyzed, more than one biomarker would be detected. Combination of several biomarkers for the evaluation of a patient's status could lead to enhanced sensitivity and specificity 37 , 38 , 39 , 40 , 41 .…”