OBJECTIVETo develop a new bioinformatic tool based on a data-mining approach for extraction of the most informative proteins that could be used to find the potential biomarkers for the detection of cancer.

METHODSTwo independent datasets from serum samples of 253 ovarian cancer and 167 breast cancer patients were used. The samples were examined by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS). The datasets were used to extract the informative proteins using a data-mining method in the discrete stationary wavelet transform domain. As a dimensionality reduction procedure, the hard thresholding method was applied to reduce the number of wavelet coefficients. Also, a distance measure was used to select the most discriminative coefficients. To find the potential biomarkers using the selected wavelet coefficients, we applied the inverse discrete stationary wavelet transform combined with a two-sided t-test.

RESULTSFrom the ovarian cancer dataset, a set of five proteins were detected as potential biomarkers that could be used to identify the cancer patients from the healthy cases with accuracy, sensitivity, and specificity of 100%. Also, from the breast cancer dataset, a set of eight proteins were found as the potential biomarkers that could separate the healthy cases from the cancer patients with accuracy of 98.26%, sensitivity of 100%, and specificity of 95.6%.

CONCLUSIONThe results have shown that the new bioinformatic tool can be used in combination with the high-throughput proteomic data such as SELDI-TOF MS to find the potential biomarkers with high discriminative power.

Biomarkers, Tumor ; blood ; Breast Neoplasms ; blood ; Computational Biology ; methods ; Female ; Humans ; Neoplasm Proteins ; blood ; Ovarian Neoplasms ; blood ; Proteomics ; methods ; Reproducibility of Results ; Sensitivity and Specificity ; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization ; methods

No abstract available.

Prostate cancer is the most common cancer type in men and is the second cause of death, due to cancer, in patients over 50, after lung cancer. Prostate specific antigen (PSA) is a widely used tumor marker for prostate cancer. Recently, PSA is discovered in non-prostatic cancer tissues in men and women raising doubts about its specificity for prostatic tissues. PSA exists in low serum level in healthy men and in higher levels in many prostate disorders, including prostatitis and prostate cancer. Thus, a supplementary tumor marker is needed to accurately diagnose the cancer and to observe the patient after treatment. Recently, soluble human leukocyte antigen-G (sHLA-G) has been introduced as a new tumor marker for different cancer types, including colorectal, breast, lung, and ovary. The present descriptive-experimental study was carried out including patients with malignant prostate tumor, patients with benign prostate tumor, and a group of health men as the control group, as judged by an oncologist as well as a pathologist. After sterile blood sampling, sHLA-G was measured by enzyme-linked immunosorbent assay in each group. The data was then analyzed using one-way ANOVA. P≤0.05 was considered as statistically significant. The results showed that the mean of sHLA-G level was high in patients. Also, it was found that there was a significant difference in sHLA serum level between the three groups. The data revealed that sHLA-G can be a novel supplementary tumor marker in addition to PSA to diagnose prostate cancer.
Breast ; Cause of Death ; Enzyme-Linked Immunosorbent Assay ; Female ; Humans ; Leukocytes ; Lung ; Lung Neoplasms ; Male ; Ovary ; Prostate* ; Prostate-Specific Antigen ; Prostatic Neoplasms* ; Prostatitis ; Sensitivity and Specificity