| BackgroundColorectal cancer(CRC)is one of the leading sources of cancer-related mortality worldwide.About 50% of treated cases relapse within 5 years of initial diagnosis and result in death.Early detection of CRC provides the best opportunity to prevent CRC death: For metastatic CRC patients,the 5-year survival rate after surgical resection of the local tumor is 90%,significantly reduced to 10%.Although colorectal cancer screening techniques,sigmoidoscopy,and colonoscopy are now widely used to reduce the mortality of CRC patients,the number of patients undergoing screening is still limited,in part because of invasive testing and fear of discomfort associated with testing.Therefore,the search for new biomarkers as targets for non-invasive molecular detection helps to introduce CRC screening into the routine procedures of clinical analysis.Protein biomarkers are well suited for the development of novel in vitro molecular assays based on blood and stool analysis.Currently,CEA and Fecal hemoglobin(f-Hb)are the only soluble protein biomarkers approved for clinical use in CRC.However,CEA may also be overexpressed in healthy,heavy smokers in response to inflammatory conditions,type I and type II diabetes,ulcerative colitis,pancreatitis,and cirrhosis.Therefore,CEA test can be used to monitor the progress of CRC and therefore can be used as a prognostic marker.But this is not a reliable method for early detection of CRC.The most commonly used screening method for CRC is the guaiacin chemical fecal occult blood test(g FOBT).Unfortunately,this test does not detect most polyps and cancers,and requires multiple stool samples to interpret the results well.In addition,g FOBT is prone to false positive results,which are the result of a normal benign environment,such as intake of certain foods and anti-inflammatory drugs.Extensive research is currently underway to find useful biomarkers,improve current diagnostic approaches to CRC screening,and can be used to predict treatment outcomes.The discovery of new tools for non-invasive early detection methods is a priority.The National Cancer Institute(USA)defines biomarkers or characteristic molecules as any biomolecules that can be objectively measured in blood,other body fluids or tissues and can serve as indicators of normal/abnormal biological processes or pathological states.Biomarkers can reveal disease,predict prognosis or predict response to drug or therapeutic interventions.In general,for a given biomarker to be used in clinical practice,it must have the function of extending life expectancy or improving quality of life.Based on the purposes for which they are used,three main types of biomarkers can be distinguished: diagnosis,prognosis,and prediction.Any detectable molecular variation in the DNA,RNA,protein,or metabolite levels of a cancer cell can be considered a "cancer biomarker." Cancer is caused by the accumulation of genetic mutations that lead to changes in cellular processes,such as angiogenesis,proliferation,apoptosis,and aging.Thus,the initial use of genomics and transcriptome methods to search for markers detailed the genetic basis of cancer.By selectively splicing m RNA and combining with extensive post-translational modification,one gene can encode multiple proteins.On average,a given gene can encode four selective splicing variants with different sequences and activities.he proteome is more dynamic than the genome;Therefore,it more accurately reflects the mechanism of the cell.Through proteomics,thousands of cancer cell proteins can be analyzed to generate new therapeutic targets and markers for CRC.In this context,proteomics is an ideal,highly translatable research tool for the discovery of new cancer biomarkers.Proteomics has been widely used to find new CRC biomarkers and elucidate the molecular mechanism of CRC.This has led to the identification of many proteins that may be used as biomarkers to address clinical needs,and the analysis of various samples from different sources using proteomics methods.How to effectively obtain and preserve human tumor resources for scientific research without violating ethics is a problem that has not been properly solved.Cryopreservation is recognized as one of the most effective methods for long-term preservation of tissues and organs.The principle of cryopreservation is to protect tissue cells and cell components by reducing the metabolic rate of cells.However,due to the high cost and complexity of preservation of fresh specimens,it is difficult to develop in the department of pathology of most prefecture-level hospitals.Timely preservation of tumor tissue is the basis for pathologists and clinicians to carry out clinical research work.Formalin Fixed Paraffin Embedded(FFPE)is a widely used method for tissue treatment and preservation in pathology.Tissue samples can be preserved for a long time after being processed by sampling,fixation,dehydration,transparency,wax immersion and embedding.Different from fresh specimens,FFPE tissue has simple operation process,easy to master,can achieve a high degree of automation,and low cost,suitable for most hospitals to carry out the department of pathology.Therefore,FFPE tissue has been widely used in the routine pathological clinical work of pathology department.Compared with fresh frozen tissue and OCT tissue,FFPE tissue has many advantages,but it also has obvious disadvantages as a research sample.Covalent cross-linking,low protein solubility and low peptide recovery rate are the bottlenecks that researchers are unable to break through at present.How to break through the bottleneck as soon as possible seems particularly important.Part Ⅰ Comparison of protein extraction efficiency and protein quantification method of FFPE protein extraction buffer in colon cancerObjective: In order to optimize the extraction efficiency of FFPE tissue protein and provide a better sample preparation for the mass spectrometry analysis of proteomics,In the absence of a reliable and reproducible FFPE proteomics standard sample preparation method,we intend to seek an efficient and robust FFPE tissue protein extraction method.Methods: Based on the cost,ease of use and whether it is suitable for mass spectrometry analysis,a variety of protein extraction buffers containing a certain concentration of non-ionic,ion stain remover(sodium dodecyl sulfate,SDS)and reductant(dithiothreitol,DTT)were selected.The components of these buffers were modified to increase the solubility of the tissue.Meanwhile,during protein lysis,methods such as high-temperature incubation and ultrasonic fragmentation were used to maximize the opening of covalent bond cross-linking.After protein extraction,BCA protein quantitative analysis method and SDS-PAGE method were used to detect the relative concentration of the extracted protein for the next step.Results: We compared the protein extraction efficiency of three protein extraction buffers containing different concentrations of non-ionic,ion stain remover SDS and reducer DTT on FFPE tissue of colon cancer.BCA test results and SDS-PAGE results showed that the buffer containing 2% SDS had higher extraction efficiency than the buffer with lower SDS concentration.Conclusions: By optimizing and improving the components of FFPE tissue protein extraction buffer and protein extraction process,we successfully obtained a relatively high concentration of protein solution from FFPE tissue,and found that the buffer containing relatively higher detergent SDS has a higher protein extraction efficiency.Part Ⅱ Comparison of the efficiency of FFPE digestion in solution,gel digestion and suspension S-trap peptide recoveryObjective: The bottom-up proteomics strategy relies on the efficient digestion of proteins into peptides for mass spectrometry,In this study we will develop a new and robust FFPE tissue digestion method for obtaining a whole proteome from clinical FFPE tissues for mass spectrometry analysis.Methods: In-solution digestion and in-gel digestion have been routinely used for protein digestion in fresh frozen tissue and OCT tissue.For FFPE tissues,due to chemical cross-linking and the low solubility of conventional protein lysis buffer and the high concentration of SDS in the extracted protein,there is no reliable and robust protein digestion method at present.Although in recent years,the popular method of detergent removal and digestion is the Filter Assistant Sample Preparation method(FASP),which can remove SDS and other detergents to a certain extent,the complexity of the experimental protocol and the instability of the experimental results often hinder its application in high-throughput proteomics research.For these reasons,we have developed a new technique to assist the preparation of SDS-based proteome samples.We extracted the FFPE tissue protein of colon cancer from the FFPE protein extraction method described in the first chapter,and then digested the protein samples in solution,in gel and the newly reported S-trap digestion method to seek the most effective sample preparation method by liquid chromatography mass spectrometry.For each digestion method,we used the same 8 clinical FFPE samples of primary colorectal adenocarcinoma,each sample had a protein amount of 100 m g,and all samples were digested with trypsin and lysin-c mixed enzyme.Because the sample contains a high concentration of detergent SDS,which is incompatible with the mass spectrometer,the residual SDS is removed by Pierce detergent spin column before the C18 desalting step is digested in the solution.In gel digestion and S-trap digestion methods do not need detergent removal and C18 desalination step.After the protein was digested into peptides,the amount of each sample was determined by Pierce quantitative colorimetry peptide assay and Q-exactive mass spectrometer,the average peptide recovery rates of the three methods were compared.Results: The results of Pierce quantitative colorimetric determination of peptides suggest that the average recovery rates of peptides in solution,in gel and S-trap digestion are 9.1%,9.5% and 93.5%,respectively.The results of Q-exactive mass spectrometry showed that the number of protein,peptide and spectra obtained by in-solution digestion were 443,1126 and 1423,respectively.The number of protein,peptide and spectra obtained by digestion in gel were 418,1211 and 1229,respectively.The number of protein,peptide and spectra obtained by S-Trap digestion method were 1855,9433 and 11311,respectively.Conclusions: Compared with the traditional in-solution and in-gel digestion methods,the new S-trap digestion method has a significantly higher recovery rate of peptides in FFPE samples than the other two methods.The simple operation method of S-Trap allows the solution to contain a relatively high concentration of detergent SDS,and the peptide recovery rate is high,providing a good mass spectrum sample for in-depth proteomics research.Part Ⅲ Detection of differentially expressed protein and understanding of liver metastasis process for colon cancer FFPE tissue based on proteomics by liquid chromatography-mass spectrometryObjective: In this study,FFPE archive sa mples will be analyzed by ultra-high resolution Fourier transform mass spectrometry for in-depth proteomics analysis.A robust in-depth proteome assay was developed for FFPE and it would be applied to the detection of differential expression protein matching primary and metastatic colon cancer and to understand the process of tumor metastasis.Methods: We selected a total of 58 samples from 18 patients with colorectal adenocarcinoma matched with normal,primary tumor and liver metastatic tissue,including 18 samples of normal,21 samples of primary tumor and 19 samples of liver metastatic tissue.All samples were taken from the biobank of Memorial Sloan Kettering Cancer Center(MSKCC).For protein extraction methods,please refer to the comparison of protein extraction efficiency and protein quantitative methods of FFPE buffer for multiple protein extraction from colon cancer tissues in chapter 2.The protein extraction buffer was buffer 1 containing 2%SDS.Quality control samples were obtained from pooled samples.S-trap method was used for protein digestion,and trypsin/lysine mixed enzyme was used for digestive enzymes.For detailed methods,see chapter 3 S-trap method for sample preparation.Label free quantitative(LFQ)method was used to perform mass spectrometry(LC/MS/MS).The mass spectrometer is the latest generation of the Fourier transform Orbitrap Fusion Lumos.Max Quant searched the database for matching proteins,Perseus software was used for statistical analysis,and DAVID and other related database tools were used for GO functional annotation and KEGG pathway analysis.Results: A total of 6,052 proteins were detected in 58 colon cancer FFPE samples,and 3,200 of these proteins were present in normal tissues,primary tumor tissues and liver metastatic tissues.However,373,923 and 764 proteins were specific to normal tissues,primary tumor tissues and liver metastatic tissues.GO functional annotation can find common proteins such as primary tumor and metastatic tumor,and more specifically proteins specific to metastatic tissue.Similarly,KEGG signaling pathway analysis revealed various specific signaling pathways in tumor tissues.Unsupervised cluster analysis of the metastatic samples detected 590 differentially expressed proteins,which were Shared by 70% or more of the colon cancer samples.Three clusters with obvious expression were found in the metastases,with 188 proteins in cluster 1,118 proteins in cluster 2 and 284 proteins in cluster 3.Further analysis of the drug-gene interaction database(DGIdb)showed that Cluster 1 matched 66 upregulated proteins with 137 FDA approved drug treatment targets,cluster 2 matched 54 upregulated proteins with 230 FDA approved drug treatment targets and cluster 3 matched 42 upregulated proteins with 148 FDA approved drug treatment targets with metastasis specificity.Conclusions: Deep proteomic analysis was applied to the synchronous group of primary and liver metastatic colon cancer,revealing new specific signaling pathways and clustering in metastasis.These results enhance our understanding of the biological nature of cancer metastasis and may lead to new drug targets and prognostic markers. |
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