Galectin-7 as a potential predictive marker of chemo- and/or radio-therapy resistance in oral squamous cell carcinoma.

Treatment of advanced oral squamous cell carcinoma (OSCC) requires the integration of multimodal approaches. The aim of this study was to identify predictors of tumor sensitivity to preoperative radiotherapy/chemotherapy for OSCC in order to allow oncologists to determine optimum therapeutic strategies without the associated adverse effects. Here, the protein expression profiles of formalin-fixed paraffin-embedded (FFPE) tissue samples from 18 OSCC patients, termed learning cases, who received preoperative chemotherapy and/or radiotherapy followed by surgery were analyzed by quantitative proteomics and validated by immunohistochemistry in 68 test cases as well as in the 18 learning cases. We identified galectin-7 as a potential predictive marker of chemotherapy and/or radiotherapy resistance, and the sensitivity and specificity of the galectin-7 prediction score (G7PS) in predicting this resistance was of 96.0% and 39.5%, respectively, in the 68 test cases. The cumulative 5-year disease-specific survival rate was 75.2% in patients with resistant prediction using G7PS and 100% in patients with sensitive prediction. In vitro overexpression of galectin-7 significantly decreased cell viability in OSCC cell line. Therefore, our findings suggest that galectin-7 is a potential predictive marker of chemotherapy and/or radiotherapy resistance in patients with OSCC.

Plasma biomarker discovery and validation for colorectal cancer by quantitative shotgun mass spectrometry and protein microarray.

The development of a new plasma biomarker for early detection would be necessary to improve the overall outcome of colorectal cancer. Here we report the identification and validation of the ninth component of complement (C9) as a novel plasma biomarker for colorectal cancer by cutting-edge proteomic technologies. Plasma proteins were enzymatically digested into a large array of peptides, and the relative quantity of a total of 94,803 peptide peaks was compared between 31 colorectal cancer patients and 59 age/sex-matched healthy controls using 2D image-converted analysis of liquid chromatography and mass spectrometry. The selected biomarker candidates were validated in 345 subjects (115 colorectal cancer patients and 230 age/sex-matched healthy controls) using high-density reverse-phase protein microarrays. Plasma levels of Apo AI and C9 in colorectal cancer patients significantly differed from healthy controls with P values of 7.94×10(-4) and 1.43×10(-12) (Student's t-test), respectively. In particular, C9 was elevated in patients with colorectal cancer, including those with stage-I and -II diseases (P=3.01×10(-3) and P=1.13×10(-5) , respectively). Although the significance of the present study must be validated in an independent clinical study, the increment of plasma C9 may be applicable to the early detection of colorectal cancer.

Survival prediction for pancreatic cancer patients receiving gemcitabine treatment.

Although gemcitabine monotherapy is the standard treatment for advanced pancreatic cancer, patient outcome varies significantly, and a considerable number do not benefit adequately. We therefore searched for new biomarkers predictive of overall patient survival. Using LC-MS, we compared the base-line plasma proteome between 29 representative patients with advanced pancreatic cancer who died within 100 days and 31 patients who survived for more than 400 days after receiving at least two cycles of the same gemcitabine monotherapy. Identified biomarker candidates were then challenged in a larger cohort of 304 patients treated with the same protocol using reverse-phase protein microarray. Among a total of 45,277 peptide peaks, we identified 637 peaks whose intensities differed significantly between the two groups (p < 0.001, Welch's t test). Two MS peaks with the highest statistical significance (p = 2.6 x 10(-4) and p = 5.0 x 10(-4)) were revealed to be derived from alpha(1)-antitrypsin and alpha(1)-antichymotrypsin, respectively. The levels of alpha(1)-antitrypsin (p = 8.9 x 10(-8)) and alpha(1)-antichymotrypsin (p = 0.001) were significantly correlated with the overall survival of the 304 patients. We selected alpha(1)-antitrypsin (p = 0.0001), leukocyte count (p = 0.066), alkaline phosphatase (p = 8.3 x 10(-8)), and performance status (p = 0.003) using multivariate Cox regression analysis and constructed a scoring system (nomogram) that was able to identify a group of high risk patients having a short median survival time of 150 days (95% confidence interval, 123-187 days; p = 2.0 x 10(-15), log rank test). The accuracy of this model for prognostication was internally validated and showed good calibration and discrimination with a bootstrap-corrected concordance index of 0.672. In conclusion, an increased level of alpha(1)-antitrypsin is a biomarker that predicts short overall survival of patients with advanced pancreatic cancer receiving gemcitabine monotherapy. Although an external validation study will be necessary, the current model may be useful for identifying patients unsuitable for the standardized therapy.

Prolyl 4-hydroxylation of alpha-fibrinogen: a novel protein modification revealed by plasma proteomics.

Plasma proteome analysis requires sufficient power to compare numerous samples and detect changes in protein modification, because the protein content of human samples varies significantly among individuals, and many plasma proteins undergo changes in the bloodstream. A label-free proteomics platform developed in our laboratory, termed "Two-Dimensional Image Converted Analysis of Liquid chromatography and mass spectrometry (2DICAL)," is capable of these tasks. Here, we describe successful detection of novel prolyl hydroxylation of alpha-fibrinogen using 2DICAL, based on comparison of plasma samples of 38 pancreatic cancer patients and 39 healthy subjects. Using a newly generated monoclonal antibody 11A5, we confirmed the increase in prolyl-hydroxylated alpha-fibrinogen plasma levels and identified prolyl 4-hydroxylase A1 as a key enzyme for the modification. Competitive enzyme-linked immunosorbent assay of 685 blood samples revealed dynamic changes in prolyl-hydroxylated alpha-fibrinogen plasma level depending on clinical status. Prolyl-hydroxylated alpha-fibrinogen is presumably controlled by multiple biological mechanisms, which remain to be clarified in future studies.

Quantitative proteomics using formalin-fixed paraffin-embedded tissues of oral squamous cell carcinoma.

Clinical proteomics using a large archive of formalin-fixed paraffin-embedded (FFPE) tissue blocks has long been a challenge. Recently, a method for extracting proteins from FFPE tissue in the form of tryptic peptides was developed. Here we report the application of a highly sensitive mass spectrometry (MS)-based quantitative proteome method to a small amount of samples obtained by laser microdissection from FFPE tissues. Cancerous and adjacent normal epithelia were microdissected from FFPE tissue blocks of 10 squamous cell carcinomas of the tongue. Proteins were extracted in the form of tryptic peptides and analyzed by 2-dimensional image-converted analysis of liquid chromatography and mass spectrometry (2DICAL), a label-free quantitative proteomics method developed in our laboratory. From a total of 25 018 peaks we selected 72 mass peaks whose expression differed significantly between cancer and normal tissues (P < 0.001, paired t-test). The expression of transglutaminase 3 (TGM3) was significantly down-regulated in cancer and correlated with loss of histological differentiation. Hypermethylation of TGM3 gene CpG islands was observed in 12 oral squamous cell carcinoma (OSCC) cell lines with reduced TGM3 expression. These results suggest that epigenetic silencing of TGM3 plays certain roles in the process of oral carcinogenesis. The method for quantitative proteomic analysis of FFPE tissue described here offers new opportunities to identify disease-specific biomarkers and therapeutic targets using widely available archival samples with corresponding detailed pathological and clinical records.

Identification of a predictive biomarker for hematologic toxicities of gemcitabine.

PURPOSE: Gemcitabine monotherapy is the current standard for patients with advanced pancreatic cancer, but the occurrence of severe neutropenia and thrombocytopenia can sometimes be life threatening. This study aimed to discover a new diagnostic method for predicting the hematologic toxicities of gemcitabine. PATIENTS AND METHODS: Using quantitative mass spectrometry (MS), we compared the baseline plasma proteomes of 25 patients who had developed severe hematologic adverse events (grade 3 to 4 neutropenia and/or grade 2 to 4 thrombocytopenia) within the first two cycles of gemcitabine with those of 22 patients who had not (grade 0). RESULTS: We identified 757 peptide peaks whose intensities were significantly different (P < .001, Welch t test) among a total of 60,888. The MS peak with the highest statistical significance (P = .0000282) was revealed to be derived from haptoglobin by tandem MS. A scoring system (nomogram) based on the values of haptoglobin, haptoglobin phenotype, neutrophil count, platelet count, and body-surface area was constructed to estimate the risk of hematologic adverse events (grade 3 to 4 neutropenia and/or grade 2 to 4 thrombocytopenia) with an area under curve value of 0.782 in a cohort of 166 patients with pancreatic cancer. Predictive ability of the system was confirmed in two independent validation cohorts consisting of 87 and 52 patients with area under the curve values of 0.655 and 0.747, respectively. CONCLUSION: Although the precise mechanism responsible for the correlation of haptoglobin with the future onset of hematologic toxicities remains to be clarified, our prediction model seems to have high practical utility for tailoring the treatment of patients receiving gemcitabine.

Large-scale quantitative clinical proteomics by label-free liquid chromatography and mass spectrometry.

We previously reported the development of an integrated proteome platform, namely 2-Dimensional Image Converted Analysis of Liquid chromatography and mass spectrometry (2DICAL), for quantitative comparison of large peptide datasets generated by nano-flow liquid chromatography (LC) and mass spectrometry (MS). The key technology of 2DICAL was the precise adjustment of the retention time of LC by dynamic programming. In order to apply 2DICAL to clinical studies that require comparison of a large number of patient samples we further refined the calculation algorithm and increased the accuracy and speed of the peptide peak alignment using a greedy algorithm, which had been used for fast DNA sequence alignment. The peptide peaks of each sample with the same m/z were extracted every 1 m/z and displayed with along the horizontal axis. Here we report a precise comparison of more than 150,000 typtic peptide ion peaks derived from 70 serum samples (40 patients with uterine endometrial cancer and 30 controls). The levels of 49 MS peaks were found to differ significantly between cancer patients and controls (P < 0.01, Welch's t-test and interquartile range [IQR] of >40), and the differential expression and identification of selected three proteins was validated by immunoblotting. 2DICAL was is highly advantageous for large-scale clinical proteomics because of its simple procedure, high throughput, and quantification accuracy.