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To elucidate cancer pathogenesis and its mechanisms at the molecular level, the collecting and characterization of large individual patient tissue cohorts are required. Since most pathology institutes routinely preserve biopsy tissues by standardized methods of formalin fixation and paraffin embedment, these archived FFPE tissues are important collections of pathology material that include patient metadata, such as medical history and treatments. FFPE blocks can be stored under ambient conditions for decades, while retaining cellular morphology, due to modifications induced by formalin. However, the effect of long-term storage, at resource-limited institutions in developing countries, on extractable protein quantity/quality has not yet been investigated. In addition, the optimal sample preparation techniques required for accurate and reproducible results from label-free LC-MS/MS analysis across block ages remains unclear. This study investigated protein extraction efficiency of 1, 5, and 10-year old human colorectal carcinoma resection tissue and assessed three different gel-free protein purification methods for label-free LC-MS/MS analysis. A sample size of n = 17 patients per experimental group (with experiment power = 0.7 and
Tissues from biopsies, resections and/or surgery are routinely taken from patients as a treatment option and/or to facilitate more accurate diagnosis. The current universal tissue preservation method of choice is formalin-fixation and paraffin-embedment, to avoid tissue auto-proteolysis and putrefaction, and to allow tissue specimens to be analyzed and examined at a later stage [
The protein profiling of FFPE tissues has immense potential for biomarker discovery and validation. Tumor tissue represents the ideal biological material for cancer proteomics studies and biomarker discovery, since tumor-specific protein markers are typically present at elevated concentrations in patient biopsy tissue [
[
Due to formalin-induced protein cross-linking, strong detergents such as sodium dodecyl sulfate (SDS) are required for total tissue solubilization and protein extraction from FFPE tissues [
One of the aims of this study was to methodically characterize the effects of storage time (over 1, 5, and 10 years) on the quality of data produced
FFPE tissue blocks, which consist of human CRC resection samples, were obtained from the Anatomical Pathology department at Tygerberg Hospital (Western Cape, South Africa) after obtaining ethics approval from the Biomedical Science Research Ethics Committee (BMREC) of the University of the Western Cape, as well as the Health Research Ethics Committee (HREC) of Stellenbosch University. The FFPE blocks were anonymized prior to processing. The 1-year-old blocks were archived since approximately 2016 (when the tissue was resected), 5-year-old blocks were archived since 2012, and 10-year-old blocks were archived since 2007 (experiments/protein extractions were performed in 2017/2018). Tissue processing and fixation times/conditions and storage conditions are unknown, since specimens were retrospectively collected. Seventeen patient cases, per block age, were reviewed and selected (
Information of the FFPE specimens selected for analysis.
Patient number | Block age (years) | Patient age (years) | Gender | Diagnosis | Grade | Stage | Location |
---|---|---|---|---|---|---|---|
1 | 1 | 75 | M | Adenocarcinoma | Low-grade | IIA | Left colon |
2 | 1 | 81 | M | Adenocarcinoma | Low-grade | IIA | Left colon |
3 | 1 | 68 | F | Adenocarcinoma | Low-grade | IIA | Left colon |
4 | 1 | 42 | M | Adenocarcinoma | Low-grade | IVA | Left colon |
5 | 1 | 80 | F | Adenocarcinoma | Low-grade | I | Left colon |
6 | 1 | 79 | M | Adenocarcinoma | Low-grade | IIA | Left colon |
7 | 1 | 49 | M | Adenocarcinoma | Low-grade | IIA | Left colon |
8 | 1 | 40 | F | Adenocarcinoma | Low-grade | IIA | Left colon |
9 | 1 | 56 | M | Adenocarcinoma | Low-grade | IIA | Left colon |
10 | 1 | 79 | F | Adenocarcinoma | Low-grade | IIA | Left colon |
11 | 1 | 64 | F | Adenocarcinoma | Low-grade | IIA | Left colon |
12 | 1 | 53 | M | Adenocarcinoma | Low-grade | IIIB | Left colon |
13 | 1 | 78 | M | Adenocarcinoma | Low-grade | IIA | Left colon |
14 | 1 | 51 | F | Adenocarcinoma | Low-grade | IIIB | Left colon |
15 | 1 | 31 | M | Adenocarcinoma | Low-grade | IIIB | Left colon |
16 | 1 | 73 | F | Adenocarcinoma | Low-grade | IIIB | Left colon |
17 | 1 | 54 | F | Adenocarcinoma | Low-grade | IIIC | Left colon |
18 | 5 | 51 | F | Adenocarcinoma | Low-grade | IIA | Left colon |
19 | 5 | 56 | F | Adenocarcinoma | Low-grade | IIIB | Left colon |
20 | 5 | 86 | M | Adenocarcinoma | Low-grade | IIA | Left colon |
21 | 5 | 59 | M | Adenocarcinoma | Low-grade | IIC | Left colon |
22 | 5 | 67 | M | Adenocarcinoma | Low-grade | IIA | Left colon |
23 | 5 | 82 | M | Adenocarcinoma | Low-grade | IIA | Left colon |
24 | 5 | 49 | F | Adenocarcinoma | Low-grade | IIIB | Left colon |
25 | 5 | 54 | M | Adenocarcinoma | Low-grade | IIA | Left colon |
26 | 5 | 58 | M | Adenocarcinoma | Low-grade | IIC | Left colon |
27 | 5 | 44 | F | Adenocarcinoma | Low-grade | I | Left colon |
28 | 5 | 50 | M | Adenocarcinoma | Low-grade | IIA | Left colon |
29 | 5 | 74 | F | Adenocarcinoma | Low-grade | IIA | Left colon |
30 | 5 | 54 | M | Adenocarcinoma | Low-grade | IIA | Left colon |
31 | 5 | 47 | F | Adenocarcinoma | Low-grade | IIIA | Left colon |
32 | 5 | 55 | M | Adenocarcinoma | Low-grade | IIIB | Left colon |
33 | 5 | 83 | M | Adenocarcinoma | Low-grade | IIA | Left colon |
34 | 5 | 60 | M | Adenocarcinoma | Low-grade | IIA | Left colon |
35 | 10 | 69 | M | Adenocarcinoma | Low-grade | IIIB | Left colon |
36 | 10 | 47 | F | Adenocarcinoma | Low-grade | IIA | Left colon |
37 | 10 | 58 | F | Adenocarcinoma | Low-grade | IIA | Left colon |
38 | 10 | 83 | M | Adenocarcinoma | Low-grade | IIA | Left colon |
39 | 10 | 57 | F | Adenocarcinoma | High-grade | IIA | Right colon |
40 | 10 | 46 | F | Adenocarcinoma | High-grade | IIA | Right colon |
41 | 10 | 77 | F | Adenocarcinoma | Low-grade | IIA | Left colon |
42 | 10 | 63 | F | Adenocarcinoma | Low-grade | IIA | Left colon |
43 | 10 | 67 | M | Adenocarcinoma | Low-grade | IIIB | Left colon |
44 | 10 | 50 | F | Adenocarcinoma | Low-grade | IIA | Left colon |
45 | 10 | 42 | M | Adenocarcinoma | Low-grade | IIA | Left colon |
46 | 10 | 71 | F | Adenocarcinoma | Low-grade | IIA | Left colon |
47 | 10 | 70 | M | Adenocarcinoma | Low-grade | IIA | Left colon |
48 | 10 | 69 | M | Adenocarcinoma | Low-grade | IIA | Left colon |
49 | 10 | 62 | F | Adenocarcinoma | Low-grade | IIA | Right colon |
50 | 10 | 78 | M | Adenocarcinoma | Low-grade | IIIB | Left colon |
51 | 10 | 33 | M | Adenocarcinoma | Low-grade | IIA | Left colon |
Patients diagnosed with colorectal adenocarcinoma, after H&E staining, were reviewed by a pathologist to ensure tissue quality and comparability (
Colonic adenocarcinoma resection tissue samples. Representative H&E stained sections of patient cases/block ages analyzed in this study.
For each selected patient case (
Experimental design and workflow used to evaluate the effects of block age and different sample processing methods. FFPE human colorectal carcinoma resection tissues from 17 patients per block age (1, 5, and 10-year old blocks) were cut and tumor areas were manually micro-dissected for analysis. From each patient, tissue sections, which corresponded to approximately 25 mm3 tissue per patient/sample, were cut per sample. Protein was extracted and quantified, after which each patient sample was split in three, for subsequent sample processing by either the APFAR, DRP, or SP3/HILIC methods. Resultant peptides were analyzed
Detergent removal was carried out using detergent removal spin plates (Pierce Biotechnology, Thermo Fisher Scientific, United States) according to the manufacturer’s instructions. Briefly, a detergent removal plate was placed on top of a wash plate and the shipping solution spun out at 1,000 x g for 2 min. The resin bed was equilibrated with 300 µl of 50 mm Triethylammonium bicarbonate (TEAB) and spun through as before, and this was repeated twice. Thereafter, 100 µg of protein was loaded onto the columns and incubated at room temperature for 2 min before spinning through at 1,000 x g for 2 min into the sample collection plate. Samples were then transferred to protein Lobind tubes and dried down by vacuum centrifugation. Once dried, samples were resuspended in 30 µl of 50 mm TEAB.
A total of 100 µg protein was transferred to each protein Lobind microcentrifuge tube and precipitated by addition of four volumes of ice cold acetone (Sigma-Aldrich, United States) followed by overnight incubation at −20°C. Samples were then centrifuged at 21,000 x g for 15 min at 4°C. The supernatant was discarded and the pellet washed with ice cold acetone. This process was repeated for a total of three pelleting steps. Thereafter, the pellets were air-dried and subsequently solubilized by resuspension in 50 mm TEAB.
In-solution digestion was carried out on samples processed by the APFAR and DRP methods. The protein was reduced by the addition of 0.1 volumes of 100 mm tris(2-carboxyethyl)phosphine (TCEP) (Sigma-Aldrich, United States) to each sample followed by incubation at 60°C for 1 h. Alkylation was accomplished by addition of 0.1 volumes of 100 mm methyl methanethiosulphonate (MMTS) (Sigma-Aldrich, United States), which was prepared in isopropanol (Sigma-Aldrich, United States), to each sample and subsequent incubation at room temperature for 15 min. Protein digestion was accomplished by addition of 1:50 (trypsin: final protein ratio) trypsin (Promega, United States) in a solution with 50 mm TEAB, and overnight incubation at 37°C. Samples were dried down and resuspended in 0.1% trifluoroacetic acid (TFA) (Sigma-Aldrich, United States) prior to clean-up
In preparation for the SP3/HILIC magnetic bead workflow, MagReSyn® HILIC beads (ReSyn Biosciences, South Africa) were aliquoted into a new tube and the shipping solution removed. Beads were then washed with 250 µl wash buffer (15% ACN, 100 mm Ammonium acetate (Sigma-Aldrich, United States) pH 4.5) for 1 min then resuspended in loading buffer (30% ACN, 200 mm Ammonium acetate, pH 4.5). The rest of the process, described hereafter, was performed using a Hamilton MassSTAR robotics liquid handler (Hamilton, Switzerland). A total of 50 µg of protein from each sample was transferred to a protein LoBind plate (Merck, Germany). Protein was reduced with 10 mm TCEP (Sigma-Aldrich, United States) and incubated at 60°C for 1 h. Samples were cooled to room temperature and alkylated with 10 mm MMTS (Sigma-Aldrich, United States) at room temperature for 15 min. MagReSyn® HILIC magnetic beads were added at an equal volume to that of the sample and a ratio of 5:1 total protein. The plate was incubated at room temperature on a shaker at 900 RPM for 30 min for binding of protein to beads. After binding, the beads were washed four times with 500 µl of 95% ACN for 1 min each. For digestion, trypsin (Promega, United States) made up in 50 mm TEAB was added at a ratio of 1:10 total protein, and the plate was incubated at 37°C on the shaker for 4 h. After digestion, the supernatant containing the peptides was removed and dried down. The samples were then resuspended in LC loading buffer [0.1% FA (Sigma-Aldrich, United States), 2% ACN (Burdick & Jackson, United States)].
LC-MS/MS analysis was conducted with a Q-Exactive quadrupole-Orbitrap mass spectrometer (Thermo Fisher Scientific, United States) coupled with a Dionex Ultimate 3,000 nano-UPLC system. All samples run by LC-MS/MS were in a randomized order. Peptides were dissolved in a solution of 0.1% FA and 2% ACN and loaded on a C18 trap column (PepMap100, 300 µm × 5 mm × 5 µm). Samples were trapped onto the column and washed for 3 min before the valve was switched and peptides eluted onto the analytical column as described hereafter. A gradient of increasing organic proportion was used for peptide separation - chromatographic separation was performed with a Waters nanoease (Zenfit) M/Z Peptide CSH C18 column (75 µm × 25 cm × 1.7 µm) and the solvent system employed was solvent A [0.1% FA in LC water (Burdick and Jackson, United States)] and solvent B (0.1% FA in ACN). The multi-step gradient for peptide separation was generated at 300 nl/min as follows: time change 5 min, gradient change: 2–5% solvent B, time change 40 min, gradient change 5–18% solvent B, time change 10 min, gradient change 18–30% solvent B, time change 2 min, gradient change 30–80% solvent B. The gradient was then held at 80% solvent B for 10 min before returning it to 2% solvent B and conditioning the column for 15 min. All data acquisition was obtained using Proxeon stainless steel emitters (Thermo Fisher, United States). The mass spectrometer was operated in positive ion mode with a capillary temperature of 320°C. The applied electrospray voltage was 1.95 kV. The mass spectra were acquired in a data-dependent manner using Xcalibur™ software version 4.2 (Thermo Fisher, United States) (Details of data acquisition parameters are shown in
Raw data containing centroid MS/MS spectra were converted into mgf (Matrix Science, United Kingdom) files using msconvert from the Proteo-Wizard software suite [
Qualitative and quantitative data were exported from PeptideShaker and parsed using in-house scripts and graphs generated in Jupyter lab (using Pandas, NumPy, and Matplotlib Python packages), as well as Microsoft® Excel. Additional statistical analyses were performed using SAS® university edition and SAS® Studio version 3.8 (results of the statistical tests that were performed are listed in
Spectrum counting abundance indexes were estimated using the Normalized Spectrum Abundance Factor (NSAF) [
The physicochemical properties of the identified peptides, including the hydropathicity (Kyte-Doolittle scale), molecular weight, and isoelectric point were calculated for each sample using the Protein property analysis software (ProPAS) version 1.1 [
Venny version 2.1.0 [
Protein annotations regarding subcellular localization were retrieved from Ensembl
Inkscape Version 0.92.4 (5da689c313, 2019–01-14) (
The mass spectrometry proteomics data [
Default PeptideShaker protein reports for each sample and quality controls are listed in
The objectives of this study were to evaluate three different sample processing methods (the APFAR or DRP methods followed by in-solution digestion, or the SP3/HILIC method with magnetic bead-based digestion) as well as the effect of storage time (FFPE tissue block age) on protein extraction efficiency and reproducibility. Subsequent proteomic analysis by label-free LC-MS/MS evaluated the proteome coverage, proportion of missed cleavages, and enrichment/selection bias based on sample processing method used.
The BCA total protein quantitation assay results of all samples (after protein was extracted from approximately 25 mm3 patient tumor tissue using 500 µl of protein extraction buffer per sample) are shown in
BCA total protein quantitation assay results for the different block ages. Protein was extracted from approximately 25 mm3 patient tumor tissue using 500 µl protein extraction buffer per sample (
A Kruskal–Wallis test was conducted to examine the differences in protein yield between block ages (
The 10-year-old FFPE tissues generated overall lower protein yields (an average of 1.65 ± 0.04 mg/ml) compared to the 5-year-old FFPE tissues, which generated an average of 2.46 ± 0.03 mg/ml protein, and the 1-year-old FFPE tissues, which generated an average of 3.82 ± 0.03 mg/ml protein. This corresponds to approximately 825 μg, 1,230 μg, and 1910 µg protein extracted from the 10, 5 and 1-year-old FFPE tissues, respectively, by using approximately 25 mm3 tissue per sample [
Although approximately 25 mm3 of manually microdissected tumor tissue per sample was used for protein extraction, and the volume of protein extraction buffer kept constant at 500 µl per sample, the total amount of extractable protein and protein yield still differed among the patient samples within the same block ages (
The efficiency and reproducibility for each protein purification method, as well as the effect of storage time/block age, at both peptide and protein level, was assessed with regards to proteome coverage (number of peptides and proteins identified) (
Comparison of the number of peptides and proteins identified for the different protein purification methods for each block age.
Known proteins deregulated in colon cancer.
% Occurrence within 17 patient samples | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
APFAR | DRP | HILIC | |||||||||||
Main accession | Gene name | Protein name | MW (kDa) | Comments | 1 year old | 5 year old | 10 year old | 1 year old | 5 year old | 10 year old | 1 year old | 5 year old | 10 year old |
O95994 | AGR2 | Anterior gradient protein 2 homologue | 19.97 | Downregulated in CRC [ |
88 | 100 | 94 | 94 | 100 | 94 | 100 | 94 | 100 |
Q13951 | CBFB | Core-binding factor subunit beta | 21.49 | Frequently overexpressed in CRC [ |
12 | 41 | 24 | 35 | 35 | 47 | 0 | 12 | 6 |
P08174 | CD55; DAF | Complement decay-accelerating factor | 41.37 | Upregulated in CRC [ |
0 | 0 | 6 | 0 | 0 | 0 | 0 | 0 | 0 |
P10645 | CHGA | Chromogranin-A | 50.66 | Downregulated in CRC [ |
29 | 29 | 18 | 18 | 18 | 18 | 24 | 18 | 18 |
A8K7I4 | CLCA1 | Calcium-activated chloride channel regulator 1 | 100.16 | Regulator of calcium channels, frequently downregulated in CRC [ |
59 | 53 | 41 | 59 | 59 | 47 | 53 | 53 | 47 |
Q96KP4 | CNDP2 | Cytosolic non-specific dipeptidase | 52.84 | Overexpressed in CRC [ |
82 | 88 | 94 | 100 | 88 | 100 | 94 | 94 | 100 |
P07148 | FABP1 | FABP1 protein | 14.20 | Downregulated in CRC [ |
100 | 100 | 71 | 94 | 100 | 88 | 94 | 100 | 88 |
Q9Y6R7 | FCGBP | IgGFc-binding protein | 571.64 | Downregulated in CRC [ |
76 | 94 | 82 | 76 | 94 | 76 | 82 | 88 | 82 |
P56470 | LGALS4 | Galectin-4 | 35.92 | Downregulated in CRC [ |
100 | 100 | 100 | 100 | 100 | 100 | 94 | 100 | 100 |
P09429 | HMGB1 | High mobility group protein B1 | 24.88 | Overexpression in CRC correlates with poor prognosis [ |
76 | 88 | 76 | 100 | 100 | 94 | 94 | 82 | 94 |
P01042 | KNG1 | Kininogen-1 | 71.91 | Frequently overexpressed in CRC [ |
29 | 41 | 53 | 53 | 59 | 82 | 29 | 47 | 65 |
Q9UHB6 | LIMA1 | LIM domain and actin-binding protein 1 | 85.17 | Downregulated in CRC [ |
0 | 0 | 6 | 0 | 0 | 24 | 6 | 6 | 0 |
P15941 | MUC-1 | Mucin-1 | 122.03 | Frequently overexpressed in CRC, marker of poor prognosis [ |
0 | 6 | 12 | 6 | 6 | 12 | 0 | 6 | 6 |
Q02817 | MUC-2 | Mucin-2 | 539.96 | Downregulation correlates with proliferation markers and with poor prognosis [ |
59 | 59 | 76 | 71 | 65 | 71 | 65 | 71 | 76 |
P06748 | NPM1 | Nucleophosmin | 32.55 | Protein involved in carcinogenesis, overexpressed in CRC [ |
100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 |
Q6UX06 | OLFM4 | Olfactomedin-4 | 57.24 | Protein overexpressed in CRC [ |
29 | 18 | 29 | 35 | 24 | 29 | 29 | 24 | 29 |
Q9Y617 | PSAT1 | Phosphoserine aminotransferase | 40.40 | Upregulated in CRC [ |
0 | 0 | 6 | 18 | 12 | 12 | 18 | 12 | 18 |
P53992 | Sec24C | Protein transport protein Sec24C | 118.25 | Overexpressed in early CRC stages, while downregulated in advanced CRC stages [ |
0 | 0 | 0 | 0 | 6 | 6 | 6 | 0 | 0 |
P36952 | SERPIN B5 | Serpin B5 | 42.07 | Upregulated in CRC [ |
29 | 6 | 29 | 35 | 6 | 29 | 29 | 6 | 29 |
P10599 | TXN | Thioredoxin | 11.73 | Frequently overexpressed in CRC [ |
94 | 100 | 100 | 94 | 100 | 100 | 94 | 94 | 94 |
Average results for all samples (
One-way ANOVA or Kruskal–Wallis tests were conducted (results and conclusions are listed in
Statistical analyses comparing protein purification method performance per block age indicated the following: For the 1-year-old blocks, based on post hoc Bonferroni (Dunn) t tests, the DRP method differs significantly (F (2) = 12.78,
Statistical analyses comparing the differences between block ages (effect of block age on the number of peptide/protein identifications) within each protein purification method indicated the following: Both the APFAR and SP3/HILIC methods performed most consistently across block ages, with no significant difference between 1, 5 and 10-year-old blocks [APFAR method: F (2,48) = 0.88,
The protein purification methods that did not show any significant differences between block ages, are in accordance with the findings of other studies [
The qualitative reproducibility for each sample and experimental condition was also measured in terms of peptide identification overlap (shown in
The shared peptides for each protein purification method within a specific block age are shown in
The effect of archival time/block age as well as protein purification method protein selection/enrichment bias was assessed with regards to peptide sequence physicochemical properties in
Physicochemical properties of identified peptides for all experimental conditions (
Overall, a comparison of the majority (upper and lower quartiles) of all peptides of all experimental conditions shows that they share similar hydropathicity scales (
There is a significant difference (
These results are in accordance with previous studies that used the APFAR and SP3/HILIC methods [
The quantitative reproducibility between experimental conditions were expressed as PCC dot plots (
Correlation of protein abundance between all protein purification methods for each patient sample.
PCA plots for all block ages and protein purification methods. The NSAF values for proteins identified from each patient case were normalized and dimensionality reduced by principal component analysis of the datasets.
For 5-year-old blocks, the PCC values for the APFAR and SP3/HILIC, as well as DRP and SP3/HILIC methods are approximately equal, 0.838 and 0.839, respectively. The APFAR and DRP method has a higher PCC value of 0.859, indicating slightly higher correlation in proteome composition between these two protein purification methods.
For 10-year-old blocks, the PCC values for the APFAR and DRP as well as DRP and SP3/HILIC methods were the same. The APFAR and SP3/HILIC method has a lower PCC value of 0.804, indicating slightly lower correlation in proteome composition between these two protein purification methods. These results indicate that sample processing with the different methods introduces an observable bias with regard to proteome composition. This bias is also more pronounced for 1-year-old blocks, compared to older blocks.
PCA plots showing clusters of samples, based on their similarities, were generated for all block ages and protein purification methods (
For the protein purification methods (
The effect of storage time/block age as well as the protein purification methods’ protein selection biases were assessed with regards to the main biological processes and cellular components present within the identified proteins, using Gene Ontology (GO) annotation. The distribution of the percentages of proteins belonging to each GO term was plotted for GO terms that occurred at >15% frequency for all samples and experimental conditions (
Gene Ontology annotation profiles for proteins identified from all block ages and protein purification methods.
Overall, similar GO profiles were obtained for all samples, therefore only the GO terms that showed some observable difference between experimental conditions were plotted.
One-way ANOVA or Kruskal–Wallis tests were conducted (results are listed in
All GO terms (for all block ages and protein purification methods) occurred at >15% frequency for all samples and are clearly represented by
Statistical analyses for protein purification methods showed that some GO terms for 1-year-old blocks processed
Statistical analyses for the different block ages (processed
To assess the reproducibility and digestion efficiency of the different protein purification methods, the percentages of missed cleavages across all samples were analyzed (shown in
The protein purification methods’ digestion efficiency therefore does not appear to be only affected by the age of the sample, since older and newer blocks gave varying results depending on the processing method used [
The oxidation of methionine is a major protein modification, which converts methionine to methionine sulfoxide, and targets the affected protein for degradation, both
Kruskal–Wallis tests were conducted to determine if the percentage of peptides containing methionine oxidation were significantly different between block ages for each protein purification method (
The SP3/HILIC method’s results are in agreement with results reported by [
Archived FFPE tissue repositories are precious sources of clinical material, often stored for decades, for clinical proteomic studies. Since these preserved blocks may be conveniently stored at ambient temperatures, it makes them easily accessible and cost effective. However, standardized protocols for the proteomic analysis of FFPE tissues have not been determined yet. In addition, the effect of block age and storage at resource-limited institutions, on protein quality remains unclear. We have demonstrated, using recently developed protein purification techniques (and FFPE human colorectal cancer resection tissues) that, overall, block age mainly affects protein yields during the protein extraction phase. Therefore, greater amounts of starting material are required for older blocks prior to LC-MS/MS analysis. Analyzed samples’ peptide and protein identifications mainly differed according to the protein purification method used and not block age, which mainly impacted on tissue proteome composition.
This study is also of particular relevance, since it assessed the performance of three different protein purification techniques on tissues derived from samples stored over a long period of time (1–10 years). The comparative analyses of these methods, across different block ages, have not been carried out to our knowledge and therefore this study provides both experimental data for this assessment as well as statistical support. The different methods show differences in the number of peptides and proteins identified and sample proteome composition, differences in reproducibility in terms of peptide identification overlap, PCA variance, as well as protocol digestion efficiency. Overall, the DRP and SP3/HILIC methods performed the best, with the SP3/HILIC method requiring less protein (and therefore less starting material) than the other methods, therefore making it the most sensitive and efficient protein purification method.
These results are encouraging since they indicate that long-term storage of FFPE tissues does not significantly interfere with retrospective proteomic analysis. In addition, variations in pre-analytical factors (spanning a decade), such as tissue harvesting, handling, the fixation protocol used as well as storage conditions (at resource-limited institutions in developing countries), does not affect protein extraction and shotgun proteomic analysis to a significant extent.
The mass spectrometry proteomics data [
FFPE tissue blocks, which consisted of human colorectal resection samples, were retrospectively selected after obtaining ethics clearance from the Biomedical Science Research Ethics Committee (BMREC) of the University of the Western Cape (ethics reference number: BM17/7/15), and the Health Research Ethics Committee (HREC) of Stellenbosch University (ethics reference number: S17/10/203). The FFPE blocks were anonymized prior to processing and archived.
AC provided the funding for the project; AC, SR, LB, RB, and JR contributed conception and design of the study; JR reviewed and selected all samples; SR performed the protein extraction work and wrote the first draft of the manuscript; LB performed the mass spectrometry experiment; SR performed the data and statistical analyses with assistance from HB and RB. All authors contributed to manuscript revision, read and approved the final submitted version.
This work was supported by the South African Research Chairs Initiative of the Department of Science and Innovation and National Research Foundation of South Africa (Grant ID 64751).
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
We thank Gerhard Walzl for making available laboratory bench space at the Stellenbosch University Immunology Group, and Andrea Gutschmidt at the Stellenbosch University Immunology Group for her technical assistance and support during the use of their laboratory space. We also thank Charles Gelderbloem and Yunus Kippie at the University of the Western Cape’s Biotechnology and Pharmacology departments, respectively, for their technical assistance and support during the project.
The Supplementary Material for this article can be found online at:
Acetonitrile
Ammonium bicarbonate
Acetone precipitation and formic acid resolubilization
Bicinchoninic acid
colorectal carcinoma
detergent removal plates
electrospray ionization
Formic acid
False discovery rate
Formalin-fixed, paraffin-embedded
Gene ontology
Hematoxylin and Eosin
Heat-induced antigen retrieval
Hydrophilic interaction liquid chromatography
Liquid chromatography
Liquid chromatography coupled to tandem mass spectrometry
Label-free quantitation
Methylmethanethiosulfonate
Mass spectrometry
Normalized spectrum abundance factor
Principal component analysis
Pearson’s correlation coefficient
Peptide Spectrum Match
Post-translational modification(s)
Sodium dodecyl sulfate
Single-Pot Solid-Phase-enhanced Sample Preparation
Tris(2-carboxyethyl)phosphine
Triethylammonium bicarbonate
Trifluoroacetic acid