Detecting New Cancer Biomarker Candidates From Alternative Splice...

A recent study published in the Journal of Proteomics describes research that is working to bridge structural biology with proteomics through the investigation of alternative splice variants.¹ The strategy of identifying alternative splice variants gives more information during a specific point in time, or pathological state than earlier methods of identifying which proteins are up- or downregulated. During disease states, such as in cancer for example, there is typically a mixture of protein isoforms present that can have different biological functions. The identification of splice variants could lead to the discovery of new biomarker candidates. Microarray, targeted proteomics involving SRM, and antibody studies are included with common strategies used to identify cancer biomarker candidates.

Previous LC-MS/MS data sets obtained using an LTQ ion trap mass spectrometer (Thermo Scientific), in a mouse model for Her2/neu-driven breast cancer, found 608 distinct alternative splice variants, including 540 known and 68 novel variants.² Building on this research, the Omenn group performed a structural prediction strategy known as I-TASSER , which can construct full-length protein models by reassembling protein fragments.³

I-TASSER was employed first using solvable proteins from the Protein Database and later with three cancer-related variant pairs reported to have opposite functions but lacking experimentally derived structures. The third analysis applied this technique to five splice variant pairs overexpressed in the mouse Her2/neu mammary tumor. The I-TASSER method was able to produce predictive structures for variants that explore new roles and functions. Two other methods, QUARK⁴ and COFACTOR,⁵ were developed to predict structures containing ab initio protein folding and structures of protein molecules, respectively. Collectively, these computational methods are a promising new direction in computational biology, proteomics, and in the discovery of new cancer biomarker candidates.

References

1. Omenn, G.S., et al. (2013) ‘Innovations in proteomic profiling of cancers: alternative splice variants as a new class of cancer biomarker candidates and bridging of proteomics with structural biology‘, Journal of Proteomics, April 17, 2013, doi/10.1016/j.jprot.2013.04.007

2. Menon, R., et al. (2011) ‘Functional implications of structural predictions for alternative splice proteins expressed in Her2/neu-induced breast cancers‘, Journal of Proteome Research, 10 (12), (pp. 5503-5511)

3. Roy, A., et al. (2010) ‘I-TASSER: a unified platform for automated protein structure and function prediction‘, Nature Protocols, 5 (4), (pp. 725-738)

4. Xu, D., and Zhang, Y. (2012) ‘Ab initio protein structure assembly using continuous structure fragments and optimized knowledge-based force field‘, Proteins, 80 (7), (pp. 1715-1735)

5. Roy, A., and Zhang, Y. (2012) ‘Recognizing protein-ligand binding sites by global structural alignment and local geometry refinement‘, Structure, 20 (6), (pp. 987-997)