Cancer proteomics

Networks in proteomics analysis of cancer

Proteomics provides direct biological information on proteins but is still a limited platform. Borrowing from genomics, its cancer-specific applications can be broadly categorized as (1) pure diagnostics, (2) biomarkers, (3) identification of root causes and (4) identification of cancer-specific network rewirings. Biological networks capture complex relationships between proteins and provide an appropriate means of contextualization. While playing significantly larger roles, especially in 1 and 3, progress in proteomics-specific network-based methods is lagging as compared to genomics. Rapid hardware advances and improvements in proteomic identification and quantification have given rise to much better quality data alongside advent of new network-based analysis methods. However, a tighter integration between analytics and hardware is still essential for network analysis to play more significant roles in proteomics analysis.

Mass spectrometry-based proteomics: the road to lung cancer biomarker discovery

Lung cancer is the leading cause of cancer death in men and women in Western nations, and is among the deadliest cancers with a 5-year survival rate of 15%. The high mortality caused by lung cancer is attributable to a late-stage diagnosis and the lack of effective treatments. So, it is crucial to identify new biomarkers that could function not only to detect lung cancer at an early stage but also to shed light on the molecular mechanisms that underlie cancer development and serve as the basis for the development of novel therapeutic strategies. Considering that DNA-based biomarkers for lung cancer showed inadequate sensitivity, specificity, and reproducibility, proteomics could represent a better tool for the identification of useful biomarkers and therapeutic targets for this cancer type. Among the proteomics technologies, the most powerful tool is mass spectrometry. In this review, we describe studies that use mass spectrometry-based proteomics technologies to analyze tumor proteins and peptides, which might represent new diagnostic, prognostic, and predictive markers for lung cancer. We focus in particular on those findings that hold promise to impact significantly on the clinical management of this disease.

Proteomics analysis of tumor microenvironment: Implications of metabolic and oxidative stresses in tumorigenesis

Tumorigenesis is always concomitant with microenvironmental alterations. The tumor microenvironment is a heterogeneous and complex milieu, which exerts a variety of stresses on tumor cells for proliferation, survival, or death. Recently, accumulated evidence revealed that metabolic and oxidative stresses both play significant roles in tumor development and progression that converge on a common autophagic pathway. Tumor cells display increased metabolic autonomy, and the hallmark is the exploitation of aerobic glycolysis (termed Warburg effect), which increased glucose consumption and decreased oxidative phosphorylation to support growth and proliferation. This characteristic renders cancer cells more aggressive; they devour tremendous amounts of nutrients from microenvironment to result in an ever-growing appetite for new tumor vessel formation and the release of more "waste," including key determinants of cell fate like lactate and reactive oxygen species (ROS). The intracellular ROS level of cancer cells can also be modulated by a variety of stimuli in the tumor microenvironment, such as pro-growth and pro-inflammatory factors. The intracellular redox state serves as a double-edged sword in tumor development and progression: ROS overproduction results in cytotoxic effects and might lead to apoptotic cell death, whereas certain level of ROS can act as a second-messenger for regulation of such cellular processes as cell survival, proliferation, and metastasis. The molecular mechanisms for cancer cell responses to metabolic and oxidative stresses are complex and are likely to involve multiple molecules or signaling pathways. In addition, the expression and modification of these proteins after metabolic or oxidative stress challenge are diverse in different cancer cells and endow them with different functions. Therefore, MS-based high-throughput platforms, such as proteomics, are indispensable in the global analysis of cancer cell responses to metabolic and oxidative stress. Herein, we highlight recent advances in the understanding of the metabolic and oxidative stresses associated with tumor progression with proteomics-based systems biology approaches.

Is phosphoproteomics ready for clinical research?

BACKGROUND

For many diseases such as cancer where phosphorylation-dependent signaling is the foundation of disease onset and progression, single-gene testing and genomic profiling alone are not sufficient in providing most critical information. The reason for this is that in these activated pathways the signaling changes and drug resistance are often not directly correlated with changes in protein expression levels. In order to obtain the essential information needed to evaluate pathway activation or the effects of certain drugs and therapies on the molecular level, the analysis of changes in protein phosphorylation is critical.

METHODS

Existing approaches do not differentiate clinical disease subtypes on the protein and signaling pathway level, and therefore hamper the predictive management of the disease and the selection of therapeutic targets.

CONCLUSIONS

The mini-review examines the impact of emerging systems biology tools and the possibility of applying phosphoproteomics to clinical research.