Selection of anti-cancer-associated gene single-chain variable fragments derived from gastric cancer patients using ribosome display

An ego network analysis approach identified important biomarkers with an association to progression and metastasis of gastric cancer

BACKGROUND

Gastric cancer (GC) is the fifth most common cancer type worldwide. The aim of this study was to identify gastric-related therapeutic indicators on the basis of the ego network analysis.

MATERIAL AND METHODS

The microarray data related to GC was downloaded from ArrayExpress database. All human protein-protein interaction (PPI) networks were downloaded from the STRING database. Ego genes were identified on the basis of PPI networks and the gene expression in GC, and then co-expression networks (ego networks) were constructed using these ego genes. On the basis of ego networks, the optimal GO terms and genes were predicted by affinity predictions and cold read predictions. Finally, the predicted genes as effective biomarkers for GC were verified by the bioinformatics analysis.

RESULTS

The differential expression networks were conducted and comprised of 365 edges and 232 nodes, which resulted in 218 ego genes. Although there was no significant difference in the expression of top ten ego genes among different groups of GC samples, it was eventually confirmed that top three optimal GO terms with highest cool read values were translational termination (cool read value = 0.987), translational elongation (cool read value = 0.986), and macromolecular complex disassembly (cool read value = 0.985) and top five optimal genes were UBA52, RPS27A, MAPK1, UBC, and UBB. UBA52, RPS27A, and MAPK1 were verified by the bioinformatics analysis to be related to the progression and metastasis of GC.

CONCLUSIONS

An ego network analysis approach is a very effective method for screening GC and the screened genes might be biomarkers for GC diagnosis and treatment.

A rapid and simple pipeline for synthesis of mRNA-ribosome-V(H)H complexes used in single-domain antibody ribosome display

The single-domain antibody (VHH) is a promising building block for a number of antibody-based applications. Ribosome display can successfully be used in the production of VHH. However, the construction of the expression cassette, confirmation of the translation and proper folding of the nascent chain, and the purification of the ribosome complexes, remain cumbersome tasks. Additionally, selection of the most suitable expression system can be challenging. We have designed primers that will amplify virtually all Camelidae VHH. With the help of a double-overlap extension (OE) polymerase chain reaction (PCR) we have fused VHH with the F1 fragment (T7 promoter and species-independent translation sequence) and the F2 fragment (mCherry, Myc-tag, tether, SecM arrest sequence and 3' stem loop) to generate a full-length DNA cassette. OE-PCR generated fragments were incubated directly with cell-free lysates (Leishmania torentolae, rabbit reticulocyte or E. coli) for the synthesis of mRNA-VHH-mCherry-ribosome complexes in vitro. Alternatively, the cassette was ligated in pQE-30 vector and transformed into E. coli to produce ribosome complexes in vivo. The results showed that the same expression cassette could be used to synthesize ribosome complexes with different expression systems. mCherry reporter served to confirm the synthesis and proper folding of the nascent chain, Myc-tag was useful in the rapid purification of ribosome complexes, and combination of the SecM sequence and 3' stem loop made the cassette universal, both for cells-free and E. coli in vivo. This rapid and universal pipeline can effectively be used in antibody ribosome display and VHH production.