Quantitative proteomic approaches for biomarker discovery

Profiling immunity to HIV vaccines with systems biology

PURPOSE OF REVIEW

The recent modest success of the RV144 HIV vaccine trial in Thailand has shown that development of an HIV vaccine is possible. Designing a vaccine that achieves better protection, however, will require a more complete understanding of vaccine mechanisms of action and correlates of protection. Systems biology approaches enable integration of large datasets from a variety of assays and offer new approaches to understanding how vaccine-induced immune responses are coordinately regulated. In this review, we discuss the recent advances in clinical trial design, specimen collection, and assay standardization that will generate datasets for systems analyses of immune responses to HIV vaccines.

RECENT FINDINGS

Several recently published HIV vaccine trials have shown that different HIV vaccine prime/boost combinations can greatly affect the immune response generated, but mechanistic insights into their modes of action are lacking. Novel systems biology studies of efficacious, licensed vaccines provide a new template for analysis of HIV vaccines. To generate datasets appropriate for systems analysis, current HIV vaccine clinical trials are undergoing design modifications and increased standardization of specimen collection and immune response assays.

SUMMARY

Systems biology approaches to HIV vaccine evaluation are driving new methods of HIV vaccine immune response profiling in clinical trials and will hopefully lead to new improved HIV vaccines in the near future.

Moving towards high density clinical signature studies with a human proteome catalogue developing multiplexing mass spectrometry assay panels

A perspective overview is given describing the current development of multiplex mass spectrometry assay technology platforms utilized for high throughput clinical sample analysis. The development of targeted therapies with novel personalized medicine drugs will require new tools for monitoring efficacy and outcome that will rely on both the quantification of disease progression related biomarkers as well as the measurement of disease specific pathway/signaling proteins.The bioinformatics developments play a key central role in the area of clinical proteomics where targeted peptide expressions in health and disease are investigated in small-, medium- and large-scaled clinical studies.An outline is presented describing applications of the selected reaction monitoring (SRM) mass spectrometry assay principle. This assay form enables the simultaneous description of multiple protein biomarkers and is an area under a fast and progressive development throughout the community. The Human Proteome Organization, HUPO, recently launched the Human Proteome Project (HPP) that will map the organization of proteins on specific chromosomes, on a chromosome-by-chromosome basis utilizing the SRM technology platform. Specific examples of an SRM-multiplex quantitative assay platform dedicated to the cardiovascular disease area, screening Apo A1, Apo A4, Apo B, Apo CI, Apo CII, Apo CIII, Apo D, Apo E, Apo H, and CRP biomarkers used in daily diagnosis routines in clinical hospitals globally, are presented. We also provide data on prostate cancer studies that have identified a variety of PSA isoforms characterized by high-resolution separation interfaced to mass spectrometry.

Identification of transgelin-2 as a biomarker of colorectal cancer by laser capture microdissection and quantitative proteome analysis

To search for potential protein markers of colorectal cancer (CRC), the changes in protein expression levels between microdissected tumor cells and normal mucosa epithelia were analyzed by an acetylation stable isotopic labeling method coupled with linear quadrupole ion trap fourier transform mass spectrometry (LTQ-FTMS). In total, 137 proteins were up-regulated or down-regulated significantly in cancer by at least two-fold. Based on gene ontology analysis, the largest part of differential proteins were unknown for both subcellular localization and biological process. In particular, the significant up-regulation of transgelin-2 (TAGLN2) in CRC was validated by Western blot analysis and further evaluated by immunohistochemistry in paired tumor and normal mucosa samples from 120 consecutive CRC patients, 20 adenomas, and eight synchronous hepatic metastases of CRC. TAGLN2 expression was frequently observed in cancer cells, precancerous lesions, and hepatic metastases, whereas in normal epithelia expression was rarely observed. The overexpression of TAGLN2 was associated with lymph node and distant metastasis, advanced clinical stage (P < 0.001), and shorter overall survival in CRCs. Cox regression analysis indicated that high tumor-TAGLN2 expression represents an independent prognostic factor. Consequently, over-expression of TAGLN2 may serve as a new biomarker for predicting progression and prognosis of CRC.

LC-MS Based Detection of Differential Protein Expression

While several techniques are available in proteomics, LC-MS based analysis of complex protein/peptide mixtures has turned out to be a mainstream analytical technique for quantitative proteomics. Significant technical advances at both sample preparation/separation and mass spectrometry levels have revolutionized comprehensive proteome analysis. Moreover, automation and robotics for sample handling process permit multiple sampling with high throughput.For LC-MS based quantitative proteomics, sample preparation turns out to be critical step, as it can significantly influence sensitivity of downstream analysis. Several sample preparation strategies exist, including depletion of high abundant proteins or enrichment steps that facilitate protein quantification but with a compromise of focusing on a smaller subset of a proteome. While several experimental strategies have emerged, certain limitations such as physiochemical properties of a peptide/protein, protein turnover in a sample, analytical platform used for sample analysis and data processing, still imply challenges to quantitative proteomics. Other aspects that make analysis of a proteome a challenging task include dynamic nature of a proteome, need for efficient and fast analysis of protein due to its constant modifications inside a cell, concentration range of proteins that exceed dynamic range of a single analytical method, and absence of appropriate bioinformatics tools for analysis of large volume and high dimensional data.This paper gives an overview of various LC-MS methods currently used in quantitative proteomics and their potential for detecting differential protein expression. Fundamental steps such as sample preparation, LC separation, mass spectrometry, quantitative assessment and protein identification are discussed.For quantitative assessment of protein expression, both label and label free approaches are evaluated for their set of merits and demerits. While most of these methods edge on providing "relative abundance" information, absolute quantification is achieved with limitation as it caters to fewer proteins. Isotope labeling is extensively used for quantifying differentially expressed proteins, but is severely limited by successful incorporation of its heavy label. Lengthy labeling protocols restrict the number of samples that can be labeled and processed. Alternatively, label free approach appears promising as it can process many samples with any number of comparisons possible but entails reproducible experimental data for its application.

Systems biology and cancer stem cells

The identification, purification and characterization of cancer stem cells (CSCs) holds tremendous promise for improving the treatment of cancer. Mounting evidence is demonstrating that only certain tumour cells (i.e. the CSCs) can give rise to tumours when injected and that these purified cell populations generate heterogeneous tumours. While the cell of origin is still not determined definitively, specific molecular markers for populations containing these CSCs have been found for leukaemia, brain cancer and breast cancer, among others. Systems approaches, particularly molecular profiling, have proven to be of great utility for cancer diagnosis and characterization. These approaches also hold significant promise for identifying distinctive properties of the CSCs, and progress is already being made.