Case-control breast cancer study of MALDI-TOF proteomic mass spectrometry data on serum samples.

We introduce mass spectrometry proteomic research for diagnosis from a clinical perspective, with special reference to early-stage breast cancer detection. The nature of SELDI and MALDI mass spectrometric measurement is discussed. We explain how the mass spectral data arising from this technology may be viewed as a new data type. Some of the properties of the data are discussed and we show how such spectra may be interpreted. Sample preprocessing for mass spectrometry is introduced and a literature review of research in clinical proteomics is presented. Finally, we provide a detailed description of the study design on the breast cancer case-control study which is investigated in this special issue.

Detection of colorectal cancer using MALDI-TOF serum protein profiling.

Serum protein profiling is a promising approach for classification of cancer versus non-cancer samples. The objective of our study was to assess the feasibility of mass spectrometry based protein profiling for the discrimination of colorectal cancer (CRC) patients from healthy individuals. In a randomized block design, pre-operative serum samples obtained from 66 colorectal cancer patients and 50 controls were used to generate MALDI-TOF protein profiles. After pre-processing of the spectra, linear discriminant analysis with double cross-validation was used to classify protein profiles. A total recognition rate (92.6%), sensitivity (95.2%) and specificity (90.0%) for the detection of CRC were shown. The area under the curve of the classifier was 97.3%, and demonstrated the high, significant separation power of the classifier. Double cross-validation shows that classification can be attributed to information in the protein profile. Although preliminary, the high sensitivity and specificity indicate the potential usefulness of serum protein profiles for the detection of colorectal cancer.

Quantitative analysis of methylation of genomic loci in early-stage rectal cancer predicts distant recurrence.

PURPOSE: There are no accurate prognostic biomarkers specific for rectal cancer. Epigenetic aberrations, in the form of DNA methylation, accumulate early during rectal tumor formation. In a preliminary study, we investigated absolute quantitative methylation changes associated with tumor progression of rectal tissue at multiple genomic methylated-in-tumor (MINT) loci sequences. We then explored in a different clinical patient group whether these epigenetic changes could be correlated with clinical outcome. PATIENTS AND METHODS: Absolute quantitative assessment of methylated alleles was used to assay methylation changes at MINT 1, 2, 3, 12, 17, 25, and 31 in sets of normal, adenomatous, and malignant tissues from 46 patients with rectal cancer. Methylation levels of these biomarkers were then assessed in operative specimens of 251 patients who underwent total mesorectal excision (TME) without neoadjuvant radiotherapy in a multicenter clinical trial. RESULTS: Methylation at MINT 2, 3, and 31 increased 11-fold (P = .005), 15-fold (P < .001), and two-fold (P = .02), respectively, during adenomatous transformation in normal rectal epithelium. Unsupervised grouping analyses of quantitative MINT methylation data of TME trial patients demonstrated two prognostic subclasses. In multivariate analysis of node-negative patients, this subclassification was the only predictor for distant recurrence (hazard ratio [HR], 4.17; 95% CI, 1.72 to 10.10; P = .002), cancer-specific survival (HR, 3.74; 95% CI, 1.4 to 9.43; P = .003), and overall survival (HR, 2.68; 95% CI, 1.41 to 5.11; P = .005). CONCLUSION: Methylation levels of specific MINT loci can be used as prognostic variables in patients with American Joint Committee on Cancer stage I and II rectal cancer. Quantitative epigenetic classification of rectal cancer merits evaluation as a stratification factor for adjuvant treatment in early disease.