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Comparative Proteomic Profiling Using Two-Dimensional Gel Electrophoresis and Identification via LC-MS/MS Reveals Novel Protein Biomarkers to Identify Aggressive Subtypes of WHO Grade I Meningioma.

ABSTRACT: Background Meningomas represent the most common primary intracranial tumor. The majority are benign World Health Organization (WHO) Grade I lesions, but a subset of these behave in an aggressive manner. Protein biomarkers are needed to distinguish aggressive from benign Grade I lesions. Materials and Methods Pooled protein lysates were derived from five clinically aggressive Grade I and five typically benign WHO Grade I tumors snap frozen at the time of surgery. Proteins were separated in each group using two-dimensional gel electrophoresis (2DGE) and protein spots of interest were identified using liquid chromatography-mass spectrometry (LC-MS). Potential biomarker candidates were validated using western blot assays in individual tumor samples and by tissue microarray (TMA). Results Seven candidate biomarkers were obtained from the 2DGE and validated via western blot and TMA. Biomarker validation data allowed for the creation of predictive models using binary logistical regression that correctly identified 85.9% of aggressive tumors within the larger cohort of Grade I meningioma. Conclusion Simple protein separation by 2DGE and identification of candidate biomarkers by LC-MS allowed for the identification of seven candidate biomarkers that when used in predictive models accurately distinguish aggressive from benign behavior in WHO Grade I meningioma.

SUBMITTER: Osbun JW

PROVIDER: S-EPMC5582960 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Breast cancer is a complex heterogeneous disease and is a leading cause of death in women. Early diagnosis and monitoring progression of breast cancer are important for improving prognosis. The aim of this study was to identify protein biomarkers in urine for early screening detection and monitoring invasive breast cancer progression.We performed a comparative proteomic analysis using ion count relative quantification label free LC-MS/MS analysis of urine from breast cancer patients (n = 20) and healthy control women (n = 20).Unbiased label free LC-MS/MS-based proteomics was used to provide a profile of abundant proteins in the biological system of breast cancer patients. Data analysis revealed 59 urinary proteins that were significantly different in breast cancer patients compared to the normal control subjects (p<0.05, fold change >3). Thirty-six urinary proteins were exclusively found in specific breast cancer stages, with 24 increasing and 12 decreasing in their abundance. Amongst the 59 significant urinary proteins identified, a list of 13 novel up-regulated proteins were revealed that may be used to detect breast cancer. These include stage specific markers associated with pre-invasive breast cancer in the ductal carcinoma in-situ (DCIS) samples (Leucine LRC36, MAST4 and Uncharacterized protein CI131), early invasive breast cancer (DYH8, HBA, PEPA, uncharacterized protein C4orf14 (CD014), filaggrin and MMRN2) and metastatic breast cancer (AGRIN, NEGR1, FIBA and Keratin KIC10). Preliminary validation of 3 potential markers (ECM1, MAST4 and filaggrin) identified was performed in breast cancer cell lines by Western blotting. One potential marker MAST4 was further validated in human breast cancer tissues as well as individual human breast cancer urine samples with immunohistochemistry and Western blotting, respectively.Our results indicate that urine is a useful non-invasive source of biomarkers and the profile patterns (biomarkers) identified, have potential for clinical use in the detection of BC. Validation with a larger independent cohort of patients is required in the following study.

Project description:Background and purposeMeningiomas are very commonly diagnosed intracranial primary neoplasms, of which the chordoid subtype is seldom encountered. Our aim was to retrospectively review preoperative MR imaging of intracranial chordoid meningiomas, a rare WHO grade II variant, in an effort to determine if there exist distinguishing MR imaging characteristics that can aid in differentiating this atypical variety from other meningioma subtypes.Materials and methodsTen cases of WHO grade II chordoid meningioma were diagnosed at our institution over an 11-year span, 8 of which had preoperative MR imaging available for review and were included in our analysis. Chordoid meningioma MR imaging characteristics, including ADC values and normalized ADC ratios, were compared with those of 80 consecutive cases of WHO grade I meningioma, 21 consecutive cases of nonchordoid WHO grade II meningioma, and 1 case of WHO grade III meningioma.ResultsPreoperative MR imaging revealed no significant differences in size, location, signal characteristics, or contrast enhancement between chordoid meningiomas and other meningiomas. There were, however, clear differences in the ADC values and normalized ADC ratios, with a mean absolute ADC value of 1.62 ± 0.33 × 10(-3) mm(2)/s and a mean normalized ADC ratio of 2.22 ± 0.47 × 10(-3) mm(2)/s in chordoid meningiomas compared with mean ADC and normalized ADC values, respectively, of 0.88 ± 0.13 × 10(-3) mm(2)/s and 1.17 ± 0.16 × 10(-3) mm(2)/s in benign WHO grade I meningiomas, 0.84 ± 0.11 × 10(-3) mm(2)/s and 1.11 ± 0.15 × 10(-3) mm(2)/s in nonchordoid WHO grade II meningiomas, and 0.57 × 10(-3) mm(2)/s and 0.75 × 10(-3) mm(2)/s in the 1 WHO grade III meningioma.ConclusionsChordoid meningiomas have statistically significant elevations of ADC and normalized ADC values when compared with all other WHO grade I, II, and III subtypes, which enables reliable preoperative prediction of this atypical histopathologic diagnosis.

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Comparative Proteomic Profiling Using Two-Dimensional Gel Electrophoresis and Identification via LC-MS/MS Reveals Novel Protein Biomarkers to Identify Aggressive Subtypes of WHO Grade I Meningioma.

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