Proteomics and genomics of urinary bladder cancer

Human urine proteomics: building a list of human urine cancer biomarkers

In the last decade, several reports have focused on the identification and characterization of proteins present in urine. In an effort to build a list of proteins of interest as biomarkers, we reviewed the largest urine proteomes and built two updated lists of proteins of interest (available as supplementary tables). The first table includes a consensus list of 443 proteins found in urine by independent laboratories and reported on the top three largest urine proteomes currently published. This consensus list of proteins could serve as biomarkers to diagnose, monitor and manage a number of diseases. Here, we focus on a reduced list of 35 proteins with potential interest as cancer biomarkers in urine following two criteria: first, proteins previously detected in urine using bottom-up proteomic experiments, and second, those suggested as cancer protein biomarkers in human plasma. In an effort to standardize the information presented and its use in future studies, here we include the updated International Protein Index (v. 3.80) and primary Swiss-Prot accession numbers, official gene symbols and recommended full names. The main variables that influence urine proteomic experiments are also discussed.

Serum proteomic profile analysis for endometrial carcinoma detection with MALDI-TOF MS

INTRODUCTION

Endometrial carcinoma is the one of the leading causes of terminal cancer death in women, and the best way to solve it is through an early diagnosis. Serum proteomic profiling is a promising approach to classify disease versus normal and matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF). This analysis is a new potential tool for the diagnosis of human diseases. The objective of our study was to assess the feasibility of mass spectrometry, based on serum proteomic pattern for the discrimination of endometrial carcinoma patients from healthy control patients.

MATERIAL AND METHODS

By using 30 pre-operative endometrial carcinoma serum samples and 30 healthy controls, we generated MALDI-TOF protein profiles, established the serum detection model, and analyzed the data. Furthermore, we validated the data and got the total sensitivity (97.6%) and specificity (100%), which could classify all the samples well and demonstrated the high, significant separation ability.

RESULTS

Our results indicated that high sensitivity and specificity classify endometrial carcinoma by the serum detection model and showed the potential usefulness of serum protein profiles.

CONCLUSIONS

From these results, we could tell that MALDI-TOF MS is a potential tool for diagnosing diseases by the use of serum samples and will be widely used in the future for clinical work.