Name: A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions (Video) | JoVE Journal
Uploaded: 2025-04-18T14:30:00.000+00:00
Duration: 9 min
Description: Learn a streamlined mass spectrometry-based proteomics method for analyzing specific regions in FFPE tissue samples. This optimized protocol enhances accuracy for pancreatic disease research and biomarker discovery.

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5 minutes

All figures in this article were created with BioRender (http://www.biorender.com). This work&#160;was supported by a National Research&#160;Foundation of Korea (NRF) grants (Grant No.&#160;RS-2023-00253403 and RS-2024-00454407).

This study was reviewed and approved by the Institutional Review Board of Seoul National University Hospital (IRB No. 1904-114-1028). All participants provided written informed consent to participate in the study. Detailed information on all materials used in this protocol is presented in the Table of Materials.
1. FFPE tissue antigen retrieval for proteomics sample preparation
NOTE: Ensure that the scalpels and all materials, such as the tube used, are sterile to avoid any cross-contamination. Protocols of this study can be adapted for any FFPE tissue with minor modifications based on the laboratory setup.
<ol>
	<li>Cut 10-&#181;m FFPE tissue sections from whole-mount FFPE tissue blocks and place them onto glass slides. 
	NOTE: In this study, human pancreatic cyst FFPE tissue (two different types of cystic tissue-SCN and IPMN) was used for proteomics sample preparation.</li>
	<li>Remove paraffin wax of FFPE tissue (deparaffinize) with two washes in xylene with caution: One for 5 min and another for 2 min.</li>
	<li>Rehydrate the tissue through a serial wash with graded ethanol mixture: 3 min each in 100%, 85%, 70%, and 50% ethanol, followed by a rinse in deionized water. 
	NOTE: Ensure xylene and ethanol are handled in a chemical fume hood.</li>
</ol>
2. FFPE tissue protein extraction
<ol>
	<li>Prepare an HE- or IHC-stained tissue slide on which ROI is indicated by pathologists.</li>
	<li>Place the unstained tissue slide and the stained tissue slide with their back sides facing each other, aligning them together. Ensure ROI is observed through the glass slide.</li>
	<li>Remove non-interest tissue regions using the scalpel. 
	NOTE: If the adjacent normal tissue should be analyzed, collect them in the other tubes.</li>
	<li>Scrape the tissue ROIs to the center of the slide using the scalpel and transfer them into the clean 1.5-mL low protein binding tubes.</li>
	<li>Add 180 &#181;L of sodium dodecyl sulfate (SDS) lysis buffer (5 % SDS, 2 mM tris (2-carboxyethyl)phosphine) [TCEP], 300 mM pH 8.5 Tris-HCl in deionized water) to each tube. 
	NOTE: Ensure the volume of lysis buffer is sufficient to solubilize the tissue during sonication and to suspend the extracted proteins. Insufficient buffer can lead to incomplete tissue lysis, while excessive buffer may dilute the protein lysate.</li>
	<li>Perform probe sonication at an amplitude of 20%, applying 10 cycles of 5 s on and 5 s off.</li>
	<li>Incubate the samples at 100 &#176;C for 3.5 h with 1,000 x g. 
	NOTE: Perform water sonication of the samples for 1 min every hour during the incubation for efficient protein extraction.</li>
	<li>After incubation, cool the sample at room temperature (RT) for 10 min. Centrifuge the samples at 16,000 x g for 10 min at RT to separate tissue debris from the supernatant.</li>
	<li>Collect the supernatant into a clean, labeled tube and store it at -80 &#176;C until further use.</li>
</ol>
3. Protein quantification of FFPE tissue lysate
NOTE: Most bicinchoninic acid assay steps for protein quantification are based on the manufacturer&#39;s instructions with minor modifications. It is recommended that reagents be prepared according to the manufacturer&#39;s guidelines.
<ol>
	<li>Prepare bovine serum albumin (BSA) standards of varying concentration by serially diluting the stock solution (2 mg/mL of BSA). If necessary, dilute samples with a dilution factor of 20 or 40.</li>
	<li>Prepare the deionized water as the blank and the SDS lysis buffer as sample control.</li>
	<li>Pipette 9 &#181;L of standards, blank, sample control, and samples to the center of the microplate well.</li>
	<li>Add 4 &#181;L of compatibility reagent solution to the sample in each well.</li>
	<li>Cover the plate and mix on a plate shaker at medium speed for 1 min. After that, incubate the plate at 37 &#176;C for 15 min.</li>
	<li>Add 260 &#181;L of the BCA working reagent to each well, and then incubate the plate at 37 &#176;C for 30 min.</li>
	<li>Cool the plate at RT for 3 min.</li>
	<li>Measure the absorbance of the wells at 562 nm on a plate reader.</li>
	<li>Subtract the 562 nm absorbance value of the blank from that of all samples and sample control.</li>
	<li>Further, subtract the 562 nm absorbance value of blank-subtracted sample control from that of all samples.</li>
	<li>Plot and use the standard curve to determine the protein concentration of each sample. 
	NOTE: Ensure that the estimated 200-250 &#181;g of proteins are extracted from three glass slides of FFPE tissues, each with an approximate area of 1 cm2.</li>
</ol>
4. Acetone precipitation of protein
NOTE: Ensure that a total of 100-300 &#181;g of protein is used for acetone precipitation and suspension trapping-based protein digestion.
<ol>
	<li>Place the protein sample (corresponding to 100-300 &#181;g) in an acetone-compatible tube.</li>
	<li>Add -20 &#176;C acetone in a volume five times the sample volume to the tube.</li>
	<li>Incubate the mixture at -20 &#176;C for 18 h.</li>
	<li>Centrifuge the tube at 16,000 x g for 15 min.</li>
	<li>Carefully dispose of the supernatant without disturbing the protein pellet.</li>
	<li>Add 500 &#181;L of -20 &#176;C acetone and repeat steps 4.4-4.5.</li>
	<li>Air-dry the sample.</li>
</ol>
5. Suspension trapping-based protein digestion
NOTE: The suspension trapping filter-based protein digestion procedure was adapted from the manufacturer&#39;s instructions with minor modifications.
<ol>
	<li>Prepare suspension trapping lysis buffer (5 % SDS, 5 mM TCEP, 50 mM pH 8.5 TEAB in deionized water).</li>
	<li>Add 40 &#181;L of the buffer to the sample tube and vortex thoroughly to dissolve the air-dried protein pellet.</li>
	<li>Incubate the sample at 100 &#176;C with shaking at 1,000 x g for 35 min.</li>
	<li>Add 10 &#181;L of the alkylating reagent (100 mM chloroacetamide [CAA] in 100 mM pH 8.5 Tetraethylammonium bromide [TEAB]) to the sample.</li>
	<li>Incubate at RT with shaking at 300 x g for 1 h.</li>
	<li>Prepare an acidifier (10% trifluoroacetic acid [TFA] in deionized water) with caution. Ensure that TFA, a strong acid, is handled in a chemical fume hood.</li>
	<li>Add 5 &#181;L of acidifier to the sample to achieve a final concentration of 1% TFA (final sample volume: 55 &#181;L).</li>
	<li>Check the pH of the sample using pH paper. Ensure the pH is less than 1.</li>
	<li>Add 350 &#181;L of binding/wash buffer-1 (0.1 M pH 8.5 TEAB in 90% MeOH) to the sample to trap proteins. 
	NOTE: Avoid vortexing and centrifugation during the protein trapping (step 5.9) to prevent sample loss. Sufficient amounts of protein ensure the formation of visible colloidal protein particulate with a translucent appearance.</li>
	<li>Place the suspension trapping column into a 2-mL tube and transfer the entire sample, including any insoluble material, into the suspension trapping column.</li>
	<li>Centrifuge the column at 4,000 x g for 50 s to trap proteins. 
	NOTE: Ensure all sample passes through the column; if not, repeat centrifugation until complete filtration.</li>
	<li>Add 400 &#181;L of the wash buffer-2 (50 % CHCl3/50 % MeOH) to the column, centrifuge at 4000 x g for 50 s, and discard the flow-through.</li>
	<li>Repeat step 5.12 three times.</li>
	<li>Add 400 &#181;L of the buffer-1, centrifuge at 4000 x g for 50 s, and discard the flow-through.</li>
	<li>Repeat step 5.14 three times.</li>
	<li>Centrifuge at 4000 x g for 1.25 min to ensure the entire passage of buffer-1.</li>
	<li>Transfer the suspension trapping column to a new sample tube for enzymatic digestion.</li>
	<li>Add 125 &#181;L of digestion buffer (0.16 &#181;g/&#181;L of trypsin/Lys-C in 50 mM pH 8.5 TEAB) to the suspension trapping column and cap it to prevent evaporation. 
	NOTE: The trypsin/Lys-C ratio should be 1:10 (weight/weight). Ensure a minimum of 10 &#181;g of trypsin/Lys-C for effective digestion.</li>
	<li>Incubate at 37 &#176;C for 18 h without shaking.</li>
	<li>Prepare the following elution buffers: buffer-1 (50 mM pH 8.5 TEAB in deionized water), buffer-2 (0.2 % FA in deionized water), and buffer-3 (50 % acetonitrile [ACN] in deionized water).</li>
	<li>Add 80 &#181;L of elution buffer-1 to the suspension trapping column and centrifuge at 4000 x g for 1.25 min.</li>
	<li>Repeat the step 5.20 with 80 &#181;L of elution buffer-2 and buffer-3.</li>
	<li>Pool eluted peptides and transfer them to a clean, new tube.</li>
</ol>
6. Peptide quantification
NOTE: Most of the steps of quantitative colorimetric peptide assay are adapted from the manufacturer&#39;s instruction with minor modifications. It is recommended that reagents be prepared according to the manufacturer&#39;s guidelines.
<ol>
	<li>Prepare a series of standards by serially diluting the stock solution of the standard (1 mg/mL). If needed, dilute samples using a dilution factor of 4 or 5.</li>
	<li>Prepare the deionized water as the blank and a mixture of elution buffer-1, buffer-2, and buffer-3 in equal proportions as sample control.</li>
	<li>Place 20 &#181;L of standards, blank, sample control, and samples into the center of each microplate well.</li>
	<li>Add 180 &#181;L of the working reagent to each well and mix the plate thoroughly on a plate shaker for 1 min.</li>
	<li>Cover the plate and incubate the plate at 37 &#176;C for 20 min.</li>
	<li>Allow the plate to cool at RT for 3 min.</li>
	<li>Measure the absorbance of the wells at 480 nm using a plate reader.</li>
	<li>Subtract the 480 nm absorbance value of the blank from that of all samples and sample control.</li>
	<li>Further, subtract the 480 nm absorbance value of blank-subtracted sample control from that of all samples.</li>
	<li>Plot and use the standard curve to calculate the peptide concentration for each sample.</li>
</ol>
7. Liquid chromatography-mass spectrometry analysis
<ol>
	<li>After peptide quantification, lyophilize 20 &#181;g of peptides.</li>
	<li>Redissolve peptides in 40 &#181;L of aqueous buffer (3 % ACN in 0.1 % formic acid [FA] water) for 10 min in a sonication bath. The resulting peptide concentration will be 0.5 &#181;g/ &#181;L.</li>
	<li>Centrifuge the sample at 16,000 x g for 60 min and transfer the samples to vials for MS analysis.</li>
	<li>Inject 2 &#181;L of each sample using the autosampler of the nano LC-MS/MS system.</li>
	<li>Separate peptides on a reversed-phase column (0.075 mm ID x 150 mm column, packed with 3 &#181;m C18 material, using a 127-min gradient of 5%-35% acetonitrile at 100 nL/min. Ionize the peptides via a nanospray ion source and transfer them into an orbitrap-based mass spectrometer.</li>
	<li>Analyze peptides using a narrow-range data-independent acquisition method21.</li>
	<li>Apply the following MS parameter setting: MS m/z range: 495-745, resolution target: 15000, AGC target: 3 x 10E6, max injection time: auto, MS/MS window: User defined (Supplementary File 1), resolution target: 45000, AGC target 3 x 10E6, max injection time: auto, HCD Collision Energy: 22%, 26%, 30%. 
	NOTE: It is recommended to perform an initial quality check of the instrument by analyzing standard samples before analysis. Use the MS data acquisition software to configure parameters (refer to Table of Materials).</li>
</ol>
8. Data analysis for proteomics search
NOTE: For proteomic search of MS raw data, open-source tools were used to convert LC-MS data format and perform proteome search (refer to Table of Materials). The parameters used for data analysis are detailed in Supplementary File 2. For basic usage instructions for open-source tools, refer to the link included in the Table of Materials.
<ol>
	<li>Covert the raw MS/MS spectrum files (*.raw) obtained from the LC-MS to the *.mzML format using open-source software.</li>
	<li>Use the format-converted raw files (*.mzML) as input for an open-source search engine to perform the proteome search.</li>
	<li>Initiate proteomic search based on the parameters specified in Supplementary File 2.</li>
</ol>
9. Statistical analysis
NOTE: For statistical analysis to identify differentially expressed proteins, an open-source tool was used to perform univariate analysis (e.g., Student&#39;s t-test; refer to Table of Materials). It is recommended to refer to basic usage instructions for the open-source tool via the link provided in the Table of Materials.
<ol>
	<li>Import the list of identified proteins (*.txt) into the open-source tool.</li>
	<li>Categorize samples into groups. For this study, two groups were designated: SCN and IPMN.</li>
	<li>Perform Log2 transformation of the abundance values to adjust the data distribution to approximate normal distribution.</li>
	<li>Apply a filtering step to remove proteins with missing values. In this study, a minimum of two valid values in each group was required for inclusion.</li>
	<li>Impute missing values using a normal distribution-based approach to generate a comprehensive list of quantified proteins for subsequent univariate analysis.</li>
	<li>Perform a Student&#39;s t-test to identify differentially expressed proteins between the two groups. In this study, Benjamini-Hochberg false discovery rate (FDR) correction was applied.</li>
	<li>Extract the differentially expressed proteins satisfying the following criteria: Benjamini-Hochberg FDR &#60; 0.05 and |fold- change| &#8805; 2.</li>
</ol>
10. Bioinformatics analysis
NOTE: A commercial bioinformatics tool was used for over-representation analysis (e.g., Ingenuity pathway analysis, refer to Table of Materials). Before using this tool, it is recommended to refer to the manufacturer&#39;s instructions.
<ol>
	<li>Import the list of DEPs (*.txt) into the commercial tool.</li>
	<li>Initiate core analysis to conduct over-representation analysis.</li>
	<li>Export significant canonical pathways enriched from the DEPs using Fisher&#39;s exact test (adjusted p-value &#60; 0.05). Identify pathways of interest that are relevant to the research.</li>
</ol>

<ol><li>Van Maldegem, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Effects+of+processing+delay%2C+formalin+fixation%2C+and+immunohistochemistry+on+RNA+recovery+from+formalin-fixed+paraffin-embedded+tissue+sections%5BTitle%5D)+AND+%22Diagn+Mol+Pathol%22%5BJournal%5D)">Effects of processing delay, formalin fixation, and immunohistochemistry on RNA recovery from formalin-fixed paraffin-embedded tissue sections.</a> Diagn Mol Pathol. 17 (1), 51-58 (2008).</li>
<li>Fox, C. H., Johnson, F. B., Whiting, J., Roller, P. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Formaldehyde+fixation%5BTitle%5D)+AND+%22J+Histochem+Cytochem%22%5BJournal%5D)">Formaldehyde fixation.</a> J Histochem Cytochem. 33 (8), 845-853 (1985).</li>
<li>Fraenkel-Conrat, H., Olcott, H. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+reaction+of+formaldehyde+with+proteins%3B+cross-linking+between+amino+and+primary+amide+or+guanidyl+groups%5BTitle%5D)+AND+%22J+Am+Chem+Soc%22%5BJournal%5D)">The reaction of formaldehyde with proteins; cross-linking between amino and primary amide or guanidyl groups.</a> J Am Chem Soc. 70 (8), 2673-2684 (1948).</li>
<li>Basyuni, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Large-scale+analysis+of+whole+genome+sequencing+data+from+formalin-fixed+paraffin-embedded+cancer+specimens+demonstrates+preservation+of+clinical+utility%5BTitle%5D)+AND+%22Nat+Commun%22%5BJournal%5D)">Large-scale analysis of whole genome sequencing data from formalin-fixed paraffin-embedded cancer specimens demonstrates preservation of clinical utility.</a> Nat Commun. 15 (1), 7731(2024).</li>
<li>Gracia Villacampa, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Genome-wide+spatial+expression+profiling+in+formalin-fixed+tissues%5BTitle%5D)+AND+%22Cell+Genomics%22%5BJournal%5D)">Genome-wide spatial expression profiling in formalin-fixed tissues.</a> Cell Genomics. 1 (3), 100065(2021).</li>
<li>Zhang, X., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Characterization+of+the+genomic+landscape+in+large-scale+Chinese+patients+with+pancreatic+cancer%5BTitle%5D)+AND+%22EBioMedicine%22%5BJournal%5D)">Characterization of the genomic landscape in large-scale Chinese patients with pancreatic cancer.</a> EBioMedicine. 77, 103897(2022).</li>
<li>Ren, Z., Ordway, B., Lin, P. -H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Archival+FFPE+blocks%3A+the+gift+that+keeps+giving%5BTitle%5D)+AND+%22Innov%22%5BJournal%5D)">Archival FFPE blocks: the gift that keeps giving.</a> Innov. 5 (1), 100532(2024).</li>
<li>Magdeldin, S., Yamamoto, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Toward+deciphering+proteomes+of+formalin-fixed+paraffin-embedded+%28FFPE%29+tissues%5BTitle%5D)+AND+%22Proteomics%22%5BJournal%5D)">Toward deciphering proteomes of formalin-fixed paraffin-embedded (FFPE) tissues.</a> Proteomics. 12 (7), 1045-1058 (2012).</li>
<li>Soni, R. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Protocol+for+deep+proteomic+profiling+of+formalin-fixed+paraffin-embedded+specimens+using+a+spectral+library-free+approach%5BTitle%5D)+AND+%22STAR+Protoc%22%5BJournal%5D)">Protocol for deep proteomic profiling of formalin-fixed paraffin-embedded specimens using a spectral library-free approach.</a> STAR Protoc. 4 (3), 102381(2023).</li>
<li>Gustafsson, O. J. R., Arentz, G., Hoffmann, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Proteomic+developments+in+the+analysis+of+formalin-fixed+tissue%5BTitle%5D)+AND+%22Biochim+Biophys+Acta+Proteins+Proteomics%22%5BJournal%5D)">Proteomic developments in the analysis of formalin-fixed tissue.</a> Biochim Biophys Acta Proteins Proteomics. 1854 (6), 559-580 (2015).</li>
<li>O'Rourke, M. B., Padula, M. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Analysis+of+formalin-fixed%2C+paraffin-embedded+%28FFPE%29+tissue+via+proteomic+techniques+and+misconceptions+of+antigen+retrieval%5BTitle%5D)+AND+%22Biotechniques%22%5BJournal%5D)">Analysis of formalin-fixed, paraffin-embedded (FFPE) tissue via proteomic techniques and misconceptions of antigen retrieval.</a> Biotechniques. 60 (5), 229-238 (2016).</li>
<li>Ye, X., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Integrated+proteomics+sample+preparation+and+fractionation%3A+method+development+and+applications%5BTitle%5D)+AND+%22TrAC+Trends+Anal+Chem%22%5BJournal%5D)">Integrated proteomics sample preparation and fractionation: method development and applications.</a> TrAC Trends Anal Chem. 120, 115667(2019).</li>
<li>Nwosu, A. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((In-depth+mass+spectrometry-based+proteomics+of+formalin-fixed%2C+paraffin-embedded+tissues+with+a+spatial+resolution+of+50-200+%C2%B5m%5BTitle%5D)+AND+%22J+Proteome+Res%22%5BJournal%5D)">In-depth mass spectrometry-based proteomics of formalin-fixed, paraffin-embedded tissues with a spatial resolution of 50-200 µm.</a> J Proteome Res. 21 (9), 2237-2245 (2022).</li>
<li>Coscia, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((A+streamlined+mass+spectrometry-based+proteomics+workflow+for+large-scale+FFPE+tissue+analysis%5BTitle%5D)+AND+%22J+Pathol%22%5BJournal%5D)">A streamlined mass spectrometry-based proteomics workflow for large-scale FFPE tissue analysis.</a> J Pathol. 251 (1), 100-112 (2020).</li>
<li>Makhmut, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((A+framework+for+ultra-low-input+spatial+tissue+proteomics%5BTitle%5D)+AND+%22Cell+Syst%22%5BJournal%5D)">A framework for ultra-low-input spatial tissue proteomics.</a> Cell Syst. 14 (11), 1002-1014.e5 (2023).</li>
<li>Shin, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Identification+of+TUBB2A+by+quantitative+proteomic+analysis+as+a+novel+biomarker+for+the+prediction+of+distant+metastatic+breast+cancer%5BTitle%5D)+AND+%22Clin+Proteomics%22%5BJournal%5D)">Identification of TUBB2A by quantitative proteomic analysis as a novel biomarker for the prediction of distant metastatic breast cancer.</a> Clin Proteomics. 17 (1), 16(2020).</li>
<li>Lee, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Dual+oxidase+2+%28DUOX2%29+as+a+proteomic+biomarker+for+predicting+treatment+response+to+chemoradiation+therapy+for+locally+advanced+rectal+cancer%3A+using+high-throughput+proteomic+analysis+and+machine+learning+algorithm%5BTitle%5D)+AND+%22Int+J+Mol+Sci%22%5BJournal%5D)">Dual oxidase 2 (DUOX2) as a proteomic biomarker for predicting treatment response to chemoradiation therapy for locally advanced rectal cancer: using high-throughput proteomic analysis and machine learning algorithm.</a> Int J Mol Sci. 23 (21), 12923(2022).</li>
<li>Tüshaus, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Towards+routine+proteome+profiling+of+FFPE+tissue%3A+insights+from+a+1%2C220-case+pan-cancer+study%5BTitle%5D)+AND+%22EMBO+J%22%5BJournal%5D)">Towards routine proteome profiling of FFPE tissue: insights from a 1,220-case pan-cancer study.</a> EMBO J. 44 (1), 304-329 (2024).</li>
<li>Schweizer, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Quantitative+multiorgan+proteomics+of+fatal+COVID-19+uncovers+tissue-specific+effects+beyond+inflammation%5BTitle%5D)+AND+%22EMBO+Mol+Med%22%5BJournal%5D)">Quantitative multiorgan proteomics of fatal COVID-19 uncovers tissue-specific effects beyond inflammation.</a> EMBO Mol Med. 15 (9), e17459(2023).</li>
<li>Kobayashi, G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Proteomic+profiling+of+FFPE+specimens%3A+discovery+of+HNRNPA2%2FB1+and+STT3B+as+biomarkers+for+determining+formalin+fixation+durations%5BTitle%5D)+AND+%22J+Proteomics%22%5BJournal%5D)">Proteomic profiling of FFPE specimens: discovery of HNRNPA2/B1 and STT3B as biomarkers for determining formalin fixation durations.</a> J Proteomics. 301, 105196(2024).</li>
<li>Kawashima, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Single-shot+10k+proteome+approach%3A+over+10%2C000+protein+identifications+by+data-independent+acquisition-based+single-shot+proteomics+with+ion+mobility+spectrometry%5BTitle%5D)+AND+%22J+Proteome+Res%22%5BJournal%5D)">Single-shot 10k proteome approach: over 10,000 protein identifications by data-independent acquisition-based single-shot proteomics with ion mobility spectrometry.</a> J Proteome Res. 21 (6), 1418-1427 (2022).</li>
<li>Li, W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Identification+and+prognostic+analysis+of+biomarkers+to+predict+the+progression+of+pancreatic+cancer+patients%5BTitle%5D)+AND+%22Mol+Med%22%5BJournal%5D)">Identification and prognostic analysis of biomarkers to predict the progression of pancreatic cancer patients.</a> Mol Med. 28 (1), 43(2022).</li>
<li>Martinelli, P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((GATA6+regulates+EMT+and+tumour+dissemination%2C+and+is+a+marker+of+response+to+adjuvant+chemotherapy+in+pancreatic+cancer%5BTitle%5D)+AND+%22Gut%22%5BJournal%5D)">GATA6 regulates EMT and tumour dissemination, and is a marker of response to adjuvant chemotherapy in pancreatic cancer.</a> Gut. 66 (9), 1665-1676 (2017).</li>
<li>Racu, M. -L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Smad4+positive+pancreatic+ductal+adenocarcinomas+are+associated+with+better+outcomes+in+patients+receiving+FOLFIRINOX-based+neoadjuvant+therapy%5BTitle%5D)+AND+%22Cancers%22%5BJournal%5D)">Smad4 positive pancreatic ductal adenocarcinomas are associated with better outcomes in patients receiving FOLFIRINOX-based neoadjuvant therapy.</a> Cancers. 15 (15), 3765(2023).</li>
<li>Roy, L. D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((MUC1+enhances+invasiveness+of+pancreatic+cancer+cells+by+inducing+epithelial+to+mesenchymal+transition%5BTitle%5D)+AND+%22Oncogene%22%5BJournal%5D)">MUC1 enhances invasiveness of pancreatic cancer cells by inducing epithelial to mesenchymal transition.</a> Oncogene. 30 (12), 1449-1459 (2011).</li>
<li>Shi, H., Tsang, Y., Yang, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Identification+of+CEACAM5+as+a+stemness-related+inhibitory+immune+checkpoint+in+pancreatic+cancer%5BTitle%5D)+AND+%22BMC+Cancer%22%5BJournal%5D)">Identification of CEACAM5 as a stemness-related inhibitory immune checkpoint in pancreatic cancer.</a> BMC Cancer. 22 (1), 1291(2022).</li>
<li>Waters, A. M., Der, C. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((KRAS%3A+the+critical+driver+and+therapeutic+target+for+pancreatic+cancer%5BTitle%5D)+AND+%22Cold+Spring+Harb+Perspect+Med%22%5BJournal%5D)">KRAS: the critical driver and therapeutic target for pancreatic cancer.</a> Cold Spring Harb Perspect Med. 8 (9), a031435(2018).</li>
<li>Yao, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Glypican-3+and+KRT19+are+markers+associating+with+metastasis+and+poor+prognosis+of+pancreatic+ductal+adenocarcinoma%5BTitle%5D)+AND+%22Cancer+Biomark%22%5BJournal%5D)">Glypican-3 and KRT19 are markers associating with metastasis and poor prognosis of pancreatic ductal adenocarcinoma.</a> Cancer Biomark. 17 (4), 397-404 (2016).</li>
<li>Zhan, L., Chen, L., Chen, Z. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Knockdown+of+FUT3+disrupts+the+proliferation%2C+migration%2C+tumorigenesis+and+TGF%CE%B2+induced+EMT+in+pancreatic+cancer+cells%5BTitle%5D)+AND+%22Oncol+Lett%22%5BJournal%5D)">Knockdown of FUT3 disrupts the proliferation, migration, tumorigenesis and TGFβ induced EMT in pancreatic cancer cells.</a> Oncol Lett. 16 (1), 924-930 (2018).</li>
<li>Frohlich, K., Furrer, R., Schori, C., Handschin, C., Schmidt, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Robust%2C+precise%2C+and+deep+proteome+profiling+using+a+small+mass+range+and+narrow+window+data-independent-acquisition+scheme%5BTitle%5D)+AND+%22J+Proteome+Res%22%5BJournal%5D)">Robust, precise, and deep proteome profiling using a small mass range and narrow window data-independent-acquisition scheme.</a> J Proteome Res. 23 (3), 1028-1038 (2024).</li>
<li>Li, K. W., Gonzalez-Lozano, M. A., Koopmans, F., Smit, A. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Recent+developments+in+data+independent+acquisition+%28DIA%29+mass+spectrometry%3A+application+of+quantitative+analysis+of+the+brain+proteome%5BTitle%5D)+AND+%22Front+Mol+Neurosci%22%5BJournal%5D)">Recent developments in data independent acquisition (DIA) mass spectrometry: application of quantitative analysis of the brain proteome.</a> Front Mol Neurosci. 13, 564446(2020).</li>
<li>Searle, B. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Chromatogram+libraries+improve+peptide+detection+and+quantification+by+data+independent+acquisition+mass+spectrometry%5BTitle%5D)+AND+%22Nat+Commun%22%5BJournal%5D)">Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry.</a> Nat Commun. 9 (1), 5128(2018).</li>
<li>Prakash, J., Shaked, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+interplay+between+extracellular+matrix+remodeling+and+cancer+therapeutics%5BTitle%5D)+AND+%22Cancer+Discov%22%5BJournal%5D)">The interplay between extracellular matrix remodeling and cancer therapeutics.</a> Cancer Discov. 14 (8), 1375-1388 (2024).</li>
<li>Perez, V. M., Kearney, J. F., Yeh, J. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+PDAC+extracellular+matrix%3A+a+review+of+the+ECM+protein+composition%2C+tumor+cell+interaction%2C+and+therapeutic+strategies%5BTitle%5D)+AND+%22Front+Oncol%22%5BJournal%5D)">The PDAC extracellular matrix: a review of the ECM protein composition, tumor cell interaction, and therapeutic strategies.</a> Front Oncol. 11, 751311(2021).</li>
<li>Ferrara, B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+extracellular+matrix+in+pancreatic+cancer%3A+description+of+a+complex+network+and+promising+therapeutic+options%5BTitle%5D)+AND+%22Cancers%22%5BJournal%5D)">The extracellular matrix in pancreatic cancer: description of a complex network and promising therapeutic options.</a> Cancers. 13 (17), 4442(2021).</li>
<li>Weniger, M., Honselmann, K. C., Liss, A. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+extracellular+matrix+and+pancreatic+cancer%3A+a+complex+relationship%5BTitle%5D)+AND+%22Cancers%22%5BJournal%5D)">The extracellular matrix and pancreatic cancer: a complex relationship.</a> Cancers. 10 (9), 316(2018).</li>
</ol>

The authors have no conflict of interest to declare

This protocol outlines a rapid and efficient proteomics method that utilizes ROIs isolated from FFPE tissue sections mounted on glass slides for pathological diagnosis. When surgical intervention is advantageous, solid neoplasms such as cancers and cysts are surgically resected and preserved for pathological evaluation. For long-term storage, tissues are fixed in formalin and embedded in paraffin (FFPE). FFPE tissue blocks are then sectioned to a thickness of 4-10 &#181;m, mounted on glass slides, subjected to antigen re...

For decades, surgically excised human tissues have been archived as formalin-fixed, paraffin-embedded (FFPE) blocks. These tissue blocks initially preserve the three-dimensional (3D) structure embedded in paraffin. The tissues are subsequently sliced using microtomes, mounted onto slides, and stained-commonly with hematoxylin and eosin (HE) or immunohistochemistry (IHC)-to facilitate histopathological diagnosis by experienced pathologists1,2. FFPE tissues offer distinct advantages for long-term storage due to the protein crosslinking induced by formalin, which halts enzymatic and proteolytic activity3. Because they support the construction of large, well-archived sample sets, FFPE tissues have been regarded as a cornerstone for biomarker discovery across diverse fields, including genomics4,5,6,7.
However, their application in liquid chromatography-mass spectrometry (LC-MS)-based proteomics has historically posed challenges. A key limitation is the formalin-induced protein crosslinking, which interferes with tryptic digestion -- a critical step in global proteome analysis8. Furthermore, the small amount of protein retrievable from tissue slides often renders conventional sample preparation methods unsuitable. Despite these challenges, advances have demonstrated that protein crosslinks can be reversed through prolonged high-temperature treatment9,10,11. Concurrently, sample preparation methods optimized for low-amount protein samples have expanded the use of FFPE tissues in proteomics research12,13,14,15.
One significant advantage of using FFPE tissue slides in proteomics lies in their capability to enable a region-specific analysis. FFPE slides typically contain both lesions and adjacent normal tissue (ANT). Analyzing the entire tissue indiscriminately risks confounding results due to mixed molecular signatures. In contrast, isolating and analyzing regions of interest (ROIs) -- lesions versus ANT -- enables more precise characterization of molecular features specific to pathological regions. Consequently, FFPE-based approaches have become increasingly popular in proteomics studies16,17,18,19,20. Despite their growing application, a streamlined workflow that describes the whole proteomic experiment step-by-step still remains scarce. In particular, a video-based protocol has not been published.
In this study, a robust LC-MS-based proteomics workflow tailored for the accurate profiling of molecular changes within lesion-specific regions was established. Using FFPE tissues diagnosed by two pathologists, the ROIs from benign serous cystic neoplasms (SCN) and precancerous intraductal papillary mucinous neoplasms (IPMN) were macrodissected, collected, and analyzed. The protocol incorporates a macrodissection of ROIs, suspension trapping-based sample preparation optimized for minimal protein inputs, and narrow-range data-independent acquisition (DIA)-MS analysis. This method enabled the identification of over 9,000 proteins from tissue areas approximately 1 cm&#178;, deciphering distinct proteomic signatures associated with SCN and IPMN.

<table><tbody><tr><td>0.1% FA in ACN (LC-MS grade)</td><td>Fisher Chemical</td><td>LS120-212</td><td></td></tr><tr><td>0.1% FA in Water (LC-MS grade)</td><td>Fisher Chemical</td><td>LS118-4</td><td></td></tr><tr><td>0.5M TCEP</td><td>Thermo Scientific</td><td>77720</td><td></td></tr><tr><td>10% SDS</td><td>Invitrogen</td><td>2679093</td><td></td></tr><tr><td>1M TEAB (pH 8.5)</td><td>Sigma-Aldrich</td><td>102545001</td><td></td></tr><tr><td>1M Tris-cl (pH 8.5)</td><td>BIOSOLUTION</td><td>BTO21</td><td></td></tr><tr><td>A-14C centrifuge</td><td>Satorious</td><td>167709</td><td></td></tr><tr><td>Acetone (HPLC grade)</td><td>Fisher Scientific</td><td>A949-4</td><td></td></tr><tr><td>ACN (HPLC grade)</td><td>J.T.Baker</td><td>9017-88</td><td></td></tr><tr><td>CHCl3 (HPLC grade)</td><td>Thermo Scientific</td><td>022920.k2</td><td></td></tr><tr><td>CR paper</td><td>ADVANTEC</td><td>70406001</td><td></td></tr><tr><td>DIA-NN ver 1.9&amp;nbsp;</td><td>Open source&amp;nbsp;</td><td>https://github.com/vdemichev/DiaNN</td><td>Proteomics Search Engine&amp;nbsp;</td></tr><tr><td>EPOCH2 microplate reader</td><td>Agilent&amp;nbsp;</td><td>2106208</td><td></td></tr><tr><td>Ethanol</td><td>MERCK</td><td>K50505283 836</td><td></td></tr><tr><td>FA (LC-MS grade)</td><td>Fisher Chemical</td><td>A117-50</td><td></td></tr><tr><td>Ingenuity Pathway Analysis (IPA)</td><td>QIAGEN</td><td>830018</td><td>Bioinformatics tool</td></tr><tr><td>Lyophilizer (SRF110R+vaper trap)</td><td>Thermo Scientific</td><td>SRF-110-115</td><td></td></tr><tr><td>MeOH (HPLC grade)</td><td>MERCK</td><td>UN1230</td><td></td></tr><tr><td>Microplate BCA protein Assay kit-Reducing Agent Compatible</td><td>Thermo Scientific</td><td>23252</td><td></td></tr><tr><td>MSConvert&amp;nbsp;</td><td>Open source&amp;nbsp;</td><td>http://proteowizard.sourceforge.net/tools.shtml</td><td>MS data transformation software</td></tr><tr><td>Orbitrap Exploris 480</td><td>Thermo Scientific</td><td>MA10813C</td><td>MS</td></tr><tr><td>PepMAP RSLC C18 separation column&amp;nbsp;</td><td>Thermo Scientific</td><td>ES903</td><td></td></tr><tr><td>Perseus</td><td>Open source</td><td>https://cox-labs.github.io/coxdocs/perseus_instructions.html</td><td>Statistical tool</td></tr><tr><td>PIERCE chloroacetamide No-Weigh Format</td><td>Thermo Scientific</td><td>A39270</td><td></td></tr><tr><td>PIERCE Quantitative colorimetric peptide Assay</td><td>Thermo Scientific</td><td>23275</td><td></td></tr><tr><td>Plate shaker&amp;nbsp;</td><td>Green SSeriker</td><td>VS-202D</td><td></td></tr><tr><td>Probe sonicator</td><td>VibraCellTM</td><td>VCX750</td><td></td></tr><tr><td>Protein LoBind Tube 1.5 mL</td><td>Eppendorf</td><td>22431081</td><td></td></tr><tr><td>QSP 10 &amp;micro;L pipette Tip</td><td>Thermo Scientific</td><td>TLR102RS-Q</td><td></td></tr><tr><td>QSP 300 &amp;micro;L pipette Tip</td><td>Thermo Scientific</td><td>TLR106RS-Q</td><td></td></tr><tr><td>Scalpel</td><td>Bard-Parker</td><td>372615</td><td></td></tr><tr><td>S-Trap: Rapid Universal MS sample Prep</td><td>PROTIFI</td><td>CO2-mini-40</td><td></td></tr><tr><td>SureSTART Vial 0.2 mL</td><td>Thermo Scientific</td><td>6pk1655</td><td></td></tr><tr><td>TFA</td><td>Sigma-Aldrich</td><td>102614284</td><td></td></tr><tr><td>ThermoMixer C</td><td>Eppendorf</td><td>5382</td><td></td></tr><tr><td>Trypsin/Lys-C (LC-MS grade)</td><td>Promega</td><td>V5073</td><td></td></tr><tr><td>Vanquish NEO</td><td>Thermo Scientific</td><td>8348249</td><td>LC</td></tr><tr><td>Water (HPLC grade)</td><td>Honeywell</td><td>AH365-4</td><td></td></tr><tr><td>Xcalibur ver 4.7</td><td>Thermo Scientific</td><td>30966</td><td>MS data acquisition software</td></tr><tr><td>Xylene</td><td>Sigma-Aldrich</td><td>102033629</td><td></td></tr></tbody></table>

a streamlined approach for mass spectrometry-based proteomics using selected tissue regions

A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions

Mass spectrometry (MS)-based proteomics enables comprehensive proteome analysis across a wide range of biological samples, including cells, tissues, and body fluids. Formalin-fixed, paraffin-embedded (FFPE) tissue sections, commonly used for long-term archiving, have emerged as valuable resources for proteomic studies. Beyond their storage benefits, researchers can isolate regions of interest (ROIs) from normal tissue regions through collaborative efforts with pathologists. Despite this potential, a streamlined approach for proteomic experiments encompassing ROI isolation, proteomic sample preparation, and MS analysis remains lacking. In this protocol, an integrated workflow that combines macrodissection of ROIs, suspension trapping-based sample preparation, and high-throughput MS analysis is presented. Through this approach, the ROIs of patients' FFPE tissues, consisting of benign serous cystic neoplasms (SCN) and precancerous intraductal papillary mucinous neoplasms (IPMN) diagnosed by pathologists, were macrodissected, collected, and analyzed, resulting in high proteome coverage. Furthermore, molecular differences between the two distinct pancreatic cystic neoplasms were successfully identified, thus demonstrating the applicability of this approach for advancing proteomic research with FFPE tissues.

The established suspension trapping filter-based proteomics sample preparation, combined with label-free quantitation using single-shot data-independent acquisition, were applied to pancreatic cystic FFPE tissues (Figure 1). Precise ROI isolation during the FFPE tissue processing was achieved across different pancreatic cystic FFPE tissues (Figure 2A), resulting in the acquisition of reproducible total ion chromatograms between biological tri-replicates for each...

Here, we establish a mass spectrometry-based proteomic method using isolated regions of interest in formalin-fixed, paraffin-embedded tissue sections. This protocol is used to analyze proteome from specific tissue areas in archived formalin-fixed, paraffin-embedded tissue sections.

Mass spectrometry (MS)-based proteomics enables comprehensive proteome analysis across a wide range of biological samples, including cells, tissues, and ...

a-streamlined-approach-for-mass-spectrometry-based-proteomics-using

Research

JoVE Journal

Biochemistry

In-depth analyses of cancer cell proteomes facilitate identification of novel drug targets and diagnostic biomarkers. We describe an experimental workflow for quantitative analysis of (phospho-)proteomes in cancer cell subpopulations derived from liquid and solid tumors. This is achieved by combining cellular enrichment strategies with quantitative Super-SILAC-based mass spectrometry.

Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors

A protocol for comprehensive extraction of lipids, metabolites and proteins from biological tissues using one sample is presented.

A Simple Fractionated Extraction Method for the Comprehensive Analysis of Metabolites, Lipids, and Proteins from a Single Sample

We present a protocol to accurately quantitate proteins with isobaric labelling, extensive fractionation, bioinformatics tools, and quality control steps in combination with liquid chromatography interfaced to a high-resolution mass spectrometer.

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Here, we present a two-dimensional gel electrophoresis (2DE) coupled with mass spectrometry (MS) to separate and identify human pituitary adenoma tissue proteome, which presents a good and reproducible 2DE pattern. Many proteins are observed in each 2DE spot when analyzing complex cancer proteome with the use of high-sensitivity MS.

Two-dimensional Gel Electrophoresis Coupled with Mass Spectrometry Methods for an Analysis of Human Pituitary Adenoma Tissue Proteome

We present an optimized tandem mass tag (TMT) labeling protocol that includes detailed information for each of the following steps: protein extraction, quantification, precipitation, digestion, labeling, submission to a proteomics facility, and data analyses.

TMT Sample Preparation for Proteomics Facility Submission and Subsequent Data Analysis

The described protocol provides an optimized quantitative proteomics analysis of tissue samples using two approaches: label-based and label free quantitation. Label-based approaches have the advantage of more accurate quantitation of proteins, while a label-free approach is more cost-effective and used to analyze hundreds of samples of a cohort.

Comprehensive Workflow of Mass Spectrometry-based Shotgun Proteomics of Tissue Samples

The protocol aims to introduce the use of a triple quadrupole mass spectrometer for Multiple Reaction Monitoring (MRM) of proteins from clinical samples. We have provided a systematic workflow starting from sample preparation to data analysis for clinical samples with all the necessary precautions to be taken.

Quantitative Proteomics Workflow using Multiple Reaction Monitoring Based Detection of Proteins from Human Brain Tissue

Protein Arginine (R)-methylation is a wide-spread post-translational modification regulating multiple biological pathways. Mass spectrometry is the best technology to globally profile the R-methyl-proteome, when coupled to biochemical approaches for modified peptide enrichment. The workflow designed for the high confidence identification of global R-methylation in human cells is described here.

A Mass Spectrometry-Based Proteomics Approach for Global and High-Confidence Protein R-Methylation Analysis

Mass spectrometry-based proteomic data is available in open databases and accessible using free tools. Given the complexity of database searches and descriptions, many biologists lack the knowledge to utilize these datasets. Here, we provide a guide on using free tools for basic proteomic data searches.

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools

Conformational flexibility plays a critical role in protein function. Herein, we describe the use of time-resolved electrospray ionization mass spectrometry coupled to hydrogen-deuterium exchange for probing the rapid structural changes that drive function in ordered and disordered proteins.

Time-resolved ElectroSpray Ionization Hydrogen-deuterium Exchange Mass Spectrometry for Studying Protein Structure and Dynamics

Learn a streamlined mass spectrometry-based proteomics method for analyzing specific regions in FFPE tissue samples. This optimized protocol enhances accuracy for pancreatic disease research and biomarker discovery.

A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions

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