Optimization Of Secretome Methodology And Applications In Cancer Research

Early diagnosis, cancer metastasis and chemotherapy effectiveness playdecisive roles in the therapeutic outcome and survival rate of cancer patient.Secreted proteins play critical roles in tumorigenesis, metastasis and drugresistance. Systematically characterizing the relevant secreted proteinsthrough cancer secretome researches will lead to discovery of novel therapytargets and novel serum biomarkers for diagnosis. In the present work, weestablished a series of methods for secretome researches, and conducted thesecretome studies focusing on the aforementioned factors which contributesignificantly to the therapeutic outcome and survival rate of cancer patient.Firstly, we optimized the cell secretome research method and establishedthe proteomic strategy of one-dimensional gel electrophoresis followed byliquid chromatography-tandem mass spectrometry (GeLC-MS/MS) toefficiently identify the secreted proteins. We applied the strategy to comparethe secretome of MCF-7and doxorubicin-resistant MCF-7/Dox tosystematically characterize the secreted proteins related to chemotherapyresistance. By quantification with label-free spectral counting,89differentially expressed secreted proteins (DESPs) between the two cell lineswere found. Among them,57DESPs were firstly found to be related todoxorubicin resistance in this work. We further focused on13novel DESPswith confirmed roles in tumor metastasis. These proteins with potential dualfunctions in tumor metastasis and drug resistance represent novel useful drugtargets for breast cancer therapy. Among them, the elevated expression ofIL-18in doxorubicin-resistant cell lines and breast tumor tissues wasvalidated and its role in doxorubicin resistance was further confirmed by cellviability experiments in the presence or absence of this protein. These results suggested that IL-18is a novel dual functional protein with roles in both drugresistance and tumor metastasis. When performing the specific researchproject, we established the data analysis methods which were commonly usedin the secretome research, including the protein subcellular localizationanalysis method and label-free spectral counting quantification strategy. Thus,a complete set of methods for secretome research was established in our lab,including experimental technology and data analysis methods.Then, we applied the lectin affinity capture method to the cellculture-based secretome study, established an approach which could be usedto significantly reduce the contamination of intracellular proteins andincrease the detection efficiency of secreted proteins. When we performed theprevious secretome study, we encountered similar difficulty experienced byother researchers: the effective proteomic detection of low-abundant secretedproteins was shielded by the presence of a large amount of intracellularproteins released from unavoidable dead cells during cell culture. In thepresent work, we applied lectin affinity capture method to enrich the secretedproteins in the conditioned media (CM) of two human breast cell lines(MCF-10A and MDA-MB-231). Lectin affinity capture approach displayedefficient enrichment of the secreted proteins in the CM of the cell lines andsignificantly increased the number of secreted proteins detected: from183to292for MCF-10A, and194to368for MDA-MB-231. And we identifiedmore DESPs between MCF-10A and MDA-MB-231after lectin capture.These results indicated that the lectin capture approach is a powerful meansto move toward more comprehensive analysis and comparison of secretomes.At last, based on the lectin capture strategy, we were able to perform thesecretome study based on fresh tissue culture, analyzing the cancer secretomeunder near-physiological conditions. In the present work, nine groups of CMwere collected from colorectal cancer (CRC) tumor tissues at the early stageand their paired normal tissues. The secreted proteins were enriched via thelectin affinity capture method and the captured proteins were analyzed by theproteomic strategy of GeLC-MS/MS. By quantification with label-free spectral counting, we found123DESPs with68DESPs up-regulated in CRCtumor tissues. EFEMP2, one of the top10up-regulated DESPs, was furthervalidated by immunohistochemistry at tissue level and enzyme-linkedimmunosorbent assay at serum level. We found the expression level ofEFEMP2was dramatically increased in CRC patients, even at the early stage.Moreover, the diagnostic accuracy of EFEMP2was superior to theestablished CRC biomarker carcinoembryonic antigen evidenced by the areaunder the receiver operating characteristic curve for the two biomarkers were0.923and0.728, respectively. These results indicated that EFEMP2is apromising serum biomarker for CRC early detection.In conclusion, the methods for cell secretome analysis were optimizedand applied to characterize the secreted proteins associated with drugresistance, a list of secreted proteins was identified, which have potential dualfunctions in drug resistance and tumor metastasis. We further established thelectin capture approach to enrich the secreted proteins in the CM of cell lines.It was also suggested that this method is an effective way to reduce thecontamination of interfering proteins and increase the detection efficiency ofsecreted proteins. We further applied this method in the secretome analysis offresh cultured CRC tumor tissues and paired normal tissues, and found a listof proteins which have the potential to be used for CRC early detection.