Antigen Retrieval for Proteomic Characterization of Formalin-Fixed and Paraffin-Embedded Tissues Haifeng Xu,† Li Yang,† Weijie Wang,† Shan-Rong Shi,‡ Cheng Liu,‡ Ying Liu,‡ Xueping Fang,§ Clive R. Taylor,‡ Cheng S. Lee,§ and Brian M. Balgley*,† Calibrant Biosystems, 910 Clopper Road, Suite 220N, Gaithersburg, Maryland 20878, Department of Pathology, Keck School of Medicine, University of Southern California, Los Angeles, California 90033, and Department of Chemistry and Biochemistry, University of Maryland, College Park, Maryland 20742 Received October 17, 2007
Formalin-fixed and paraffin-embedded tissues represent the vast majority of archived tissue. Access to such tissue specimens via shotgun-based proteomic analyses may open new avenues for both prospective and retrospective translational research. In this study, we evaluate the effects of fixation time on antigen retrieval for the purposes of shotgun proteomics. For the first time, we demonstrate the capability of a capillary isotachophoresis (CITP)-based proteomic platform for the shotgun proteomic analysis of proteins recovered from FFPE tissues. In comparison to our previous studies utilizing capillary isoelectric focusing, the CITP-based analysis is more robust and increases proteome coverage. In this case, results from three FFPE liver tissues yield a total of 4098 distinct Swiss-Prot identifications at a 1% false-discovery rate. To judge the accuracy of these assignments, immunohistochemistry is performed on a panel of 17 commonly assayed proteins. These proteins span a wide range of protein abundances as inferred from relative quantitation via spectral counting. Among the panel were 4 proteins identified by a single peptide hit, including three clusters of differentiation (CD) markers: CD74, CD117, and CD45. Because single peptide hits are often regarded with skepticism, it is notable that all proteins tested by IHC stained positive. Keywords: capillary isotachophoresis • mass spectrometry • antigen retrieval • immunohistochemistry • archival tissue
Introduction In spite of the remarkable advances prompted by recent microarray studies,1–13 there remains marked individual variation in survival and response to therapy in cancer patients when individual genes or larger gene sets identified by microarray or comparative genomic hybridization are considered. Furthermore, biological systems comprise protein components resulting from transcriptional and post-transcriptional control, post-translational modifications, and shifts in proteins among the different cellular compartments. In addition to complementing transcript profiling studies, the ability to monitor the presence or absence of particular proteins, an increase or decrease in protein expression, changes in post-translational modifications, or a combination of these variations is expected to provide a more accurate snapshot of the molecular basis of cancer due to a systematic understanding of complex cellular networks driving differentiation and proliferation. Formalin has been used as a fixative in pathology for more than a hundred years. The criteria employed by pathologists * To whom correspondence should be addressed. Calibrant Biosystems, 910 Clopper Road, Suite 220N, Gaithersburg, MD 20878. Phone: (301) 9777900 ext. 14. Fax: (301) 977-7981. E-mail:
[email protected]. † Calibrant Biosystems. ‡ University of Southern California. § University of Maryland.
1098 Journal of Proteome Research 2008, 7, 1098–1108 Published on Web 02/08/2008
for the diagnosis of essentially all cancers have been established in formalin-fixed and paraffin-embedded (FFPE) tissue sections stained by hematoxylin and eosin. Because the knowledge of disease outcome is critical in the evaluation of the significance of phenotypic or genotypic profiles as well as the response to therapy, the ability to analyze documented archival tumor cases with known outcome is highly desirable. Accessibility of macromolecules in the fixed tissue specimens is therefore a critical issue, exemplified by the growth of immunohistochemistry (IHC) for protein antigens, and in situ hybridization for DNA and RNA. Because the capacity to store large numbers of catalogued clinical samples under optimal conditions is limited by cost, space, and personnel limitations, among others, the development of technologies to analyze traditional pathological specimens, such as FFPE tissues, is an important priority. However, too often molecular analysis techniques are applied directly to these formalin-paraffin materials, or extracts thereof, without an understanding of the variables introduced by the effects of tissue fixation and processing, whether upon the structure and availability of DNA, RNA, and proteins. Although formalin-induced cross-linking of protein serves as an effective means of in situ preservation of protein, it is apparent that sample preparation is critical for effective and reproducible IHC applied to FFPE tissues.14,15 Early IHC 10.1021/pr7006768 CCC: $40.75
2008 American Chemical Society
Antigen Retrieval for Proteomic Characterization of FFPE Tissues measurements often included unmasking procedures such as enzymatic digestion that were difficult to control,16 providing a powerful incentive for the development of more reproducible approaches. In the antigen retrieval methodology, boiling the FFPE tissue sections in buffer solutions dramatically reduced the detection thresholds of IHC staining, thereby increasing sensitity for a wide range of antibodies.17–20 This antigen retrieval mechanism appears to involve a renaturation of the structure of fixed proteins through a series of conformational changes, including the possible breaking (hydrolysis) of formalin-induced cross-linkages, the entire process being driven by thermal energy from the heat source.18,19 While IHC is capable of providing proteomic information from FFPE tissues, IHC requires a priori knowledge of the individual proteins being analyzed as well as the availability of paraffin-compatible antibodies. To increase the amounts of protein extractable from FFPE tissues, the heat-induced antigen retrieval approach17–20 was combined with the application of a radioimmunoprecipitation buffer containing sodium dodecyl sulfate (SDS)21 or a denaturing solution containing both urea and SDS.22 A commercial Liquid Tissue kit was introduced for processing FFPE tissues also in the presence of heating at 95 °C for 90 min.23 Two recent FFPE proteome studies have involved the use of lysis buffers containing either guanidine hydrochloride24 or organic solvent25 at high temperature. Still, the minimal quantity of available proteins extracted from FFPE tissue sections has restricted most proteomic analyses24–30 to the use of only a single chromatography separation prior to tandem MS analysis and greatly limited the ability to mine deeper into the tissue proteome. Combined capillary isoelectric focusing (CIEF) and nanoreversed phase liquid chromatography (nano-RPLC) separations coupled with electrospray ionization-mass spectrometry (ESI-MS) have been demonstrated in our laboratory to enable ultrasensitive analysis of minute proteins extracted from whole and microdissected FFPE tissue specimens.31,32 Besides investigating effects of fixation time during FFPE preparation on protein recovery, a capillary isotachophoresis (CITP)-based proteomic platform, capable of selective analyte enrichment and high resolving power,33,34 is employed in this study to further address the challenges of protein complexity and relative abundance inherent in FFPE tissues. As validated by IHC measurements, the selective enrichment of low-abundance proteins as the result of the CITP stacking process greatly enhances tissue proteome coverage over wide ranges of isoelectric point (pI) and molecular mass.
Experimental Section Materials and Reagents. Fused-silica capillaries (50 µm i.d./ 375 µm o.d. and 100 µm i.d./375 µm o.d.) were acquired from Polymicro Technologies (Phoenix, AZ). Acetic acid, dithiothreitol (DTT), formalin, iodoacetamide (IAM), and octane were obtained from Sigma (St. Louis, MO). Acetonitrile, ammonium acetate, hematoxylin, hydroxypropyl cellulose (average MW 100 000), SDS, tris(hydroxymethyl)aminomethane (Tris), and urea were purchased from Fisher Scientific (Pittsburgh, PA). Pharmalyte 8–10 was acquired from Amersham Pharmacia Biotech (Uppsala, Sweden). Sequencing grade trypsin was obtained from Promega (Madison, WI). All solutions were prepared using water purified by a Nanopure II system (Dubuque, IA) and further filtered with a 0.22 µm membrane (Millipore, Billerica, MA).
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Mouse Tissue Sample Preparation. To study effects of fixation time during FFPE preparation on protein retrieval/ extraction, a mouse model system was established at the Keck School of Medicine, University of Southern California (USC). Six-week-old BALB/c female mice were purchased from Harlan Sprague–Dawley (Indianapolis, IN). Institutional Animal Care and Use Committee-approved protocols (IACUC Protocol #10901) and institutional guidelines for the proper humane care and use of animals in research were followed in all experiments. A total of 8 mice were euthanized by CO2 gas chamber. Tissues of liver and spleen obtained from 7 mice were immediately fixed in 10% neutral buffered formalin by manipulating the fixation time for 6 h, 24 h, 7 days, and 14 days. Liver and spleen tissues from one mouse were immediately snap-frozen and embedded in optimal cutting temperature compound (Miles Laboratories, Elkhart, IN), and stored at -80 °C as control sample. Sections of fixed tissues (1 cm × 1 cm × 10 µm) were all treated with a 20 mM Tris buffer containing 2% SDS, followed by heating at 100 °C on a heat block (VWR Scientific Products, West Chester, PA) for 20 min, then incubation at 60 °C in an incubator (Robbins Scientific, Sunyvale, CA) for 2 h. The proteins were collected in the supernatant by centrifugation at 20 000g for 30 min and quantified using a modified Bradford assay kit available from Pierce Biotechnology (Rockford, IL). The level of protein retrieved was evaluated under the influence of various retrieval pHs of Tris buffer at 2, 7, and 10. Human Tissue Sample Preparation. FFPE tissue blocks of human liver were obtained from the Norris Cancer Hospital and Institute at the Keck School of Medicine, USC. All three human liver tissue sections were stained by hematoxylin and eosin, and observed microscopically to rule out malignant lesions. This study of human archival tissue specimens was exempted under 45 CFR 46.101 (b), and was approved by the Institutional Review Board (IRB #009071) at USC. The entire sample preparation and proteomic workflow is summarized in Figure 1. FFPE tissues were deparaffinized using octane, followed by vortexing and centrifugation.31 Proteins were recovered from tissue sections of 1 cm × 1 cm × 10 µm by following heat-induced retrieval conditions described previously with a 20 mM Tris buffer at pH 9. The proteins collected in the supernatant were placed in a dialysis cup (Pierce) and dialyzed overnight at 4 °C against 100 mM Tris-HCl at pH 8.2. The retrieved and dialyzed proteins were denatured, reduced, and alkylated by sequentially adding urea, dithiothreitol, and iodoacetamide with final concentrations of 8 M, 10 mg/mL, and 20 mg/mL, respectively. The solution was incubated at 37 °C for 1 h in the dark and then diluted 8-fold with 100 mM ammonium acetate at pH 8.0. Trypsin was added at a 1:40 (w/ w) enzyme-to-substrate ratio, and the solution was incubated at 37 °C overnight. Tryptic digests were desalted using a Peptide MacroTrap column (Michrom Bioresources, Auburn, CA), lyophilized to dryness using a SpeedVac (Thermo, San Jose, CA), and then stored at -80 °C. Transient CITP/Capillary Zone Electrophoresis (CZE)Based Multidimensional Separations. The CITP apparatus was constructed in-house using a CZE 1000R high-voltage power supply (Spellman High-Voltage Electronics, Plainview, NY). A 80-cm long CITP capillary (100 µm i.d./365 µm o.d.) coated with hydroxypropyl cellulose was initially filled with a background electrophoresis buffer of 0.1 M acetic acid at pH 2.8. The sample containing protein digests retrieved and processed from FFPE human liver tissues was prepared in a 2% Pharmalyte pH 8–10 Journal of Proteome Research • Vol. 7, No. 3, 2008 1099
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Figure 1. The FFPE tissue sample preparation and proteomic workflow.
solution. A 50-cm long sample plug, corresponding to 4.0 µL sample volume, was hydrodynamically injected into the capillary. A positive electric voltage of 24 kV was then applied to the inlet reservoir, which was filled with a 0.1 M acetic acid solution. The cathodic end of the capillary was housed inside a stainless steel needle using a coaxial liquid sheath flow configuration.35,36 A sheath liquid composed of 0.1 M acetic acid was delivered at a flow rate of 1 µL/min using a Harvard Apparatus 22 syringe pump (South Natick, MA). The stacked and resolved peptides in the CITP/CZE capillary were sequentially fractionated and loaded into individual wells on a moving microtiter plate. The entire capillary content was separated and sampled into 30 individual fractions in less than 2 h. To couple transient CITP/CZE with nano-RPLC, peptides collected in individual wells were sequentially injected into dual trap columns (3 cm × 200 µm i.d. × 365 µm o.d.) packed with 5 µm porous C18 reversed-phase particles. Each peptide fraction was subsequently analyzed by nano-RPLC equipped with an Ultimate dual-quaternary pump (Dionex, Sunnyvale, CA) and a dual nanoflow splitter connected to two pulled-tip, fusedsilica capillary columns (50 µm i.d. × 365 µm o.d.). These two 15-cm long capillaries were packed with 3-µm Zorbax Stable Bond (Agilent, Palo Alto, CA) C18 particles. Nano-RPLC separations were performed in parallel in which a dual-quaternary pump delivered two identical 2-h organic solvent gradients with an offset of 1 h. Peptides were eluted at a flow rate of 200 nL/min using a 5–45% linear acetonitrile gradient over 100 min with the remaining 20 min for column regeneration and equilibration. The peptide eluants were monitored using a linear ion-trap mass spectrometer (LTQ, ThermoFinnigan, San Jose, CA) operated in a data-dependent mode. Full scans were collected from 400–1400 m/z, and 5 data1100
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Xu et al. dependent MS/MS scans were collected with dynamic exclusion set to 30 s. A moving stage housing two nano-RPLC columns was employed to provide electrical contacts for applying ESI voltages, and to position the columns in-line with the ESI inlet at each chromatography separation and data acquisition cycle. MS Data Analysis. Raw LTQ data were converted to peak list files by msn_extract.exe (ThermoFinnigan). Open Mass Spectrometry Search Algorithm (OMSSA)37 developed at the National Center for Biotechnology Information was used to search the peak list files against the UniProt sequence library (April 20, 2006) with decoyed sequences appended. This decoyed database was constructed by reversing all sequences and appending them to the end of the sequence library. Searches were performed using the following parameters: fully tryptic, 1.5 Da precursor ion mass tolerance, 0.4 Da fragment ion mass tolerance, 1 missed cleavage, alkylated Cys as a fixed modification, and variable modification of Met oxidation. Searches were run in parallel on a 12 node, 24 CPU Linux cluster (Linux Networx, Bluffdale, UT). False-discovery rates (FDRs) were determined using a targetdecoy search strategy introduced by Elias and co-workers38 and employed in our previous study for a comparative evaluation among commonly used tandem MS identification search algorithms.39 An E-value threshold corresponding to a 1% FDR was used as a cutoff in this analysis as this correlates with the maximum sensitivity versus specificity, as previously shown.38,39 No other cutoffs, such as requiring a minimum number of distinct peptides per protein, were performed. The UniProt sequence library consists of entries from both Swiss-Prot and TrEMBL. Because of the minimally redundant nature of SwissProt, only peptides mapping to the Swiss-Prot subset are reported here. After generation of search data, the OMSSA XML result files were parsed using a Java parser and loaded into an Oracle 10 g database for analysis and reporting using in-house software. Definitions. For the purposes of this manuscript, a spectral count is defined as the identification within the applied falsediscovery rate of a single tandem mass spectrum. Additional identifications of the same peptide, for example, via fragmentation of another charge state, are each counted as additional spectral counts. A distinct peptide is defined as the identification of a peptide sequence different from other identifications. So multiple spectral counts to the same peptide sequence count as only a single distinct peptide. Modified peptides do not count as additional distinct peptides. A distinct peptide may map to multiple protein sequences. A distinct protein is defined as a protein with at least one distinct peptide mapping to a Swiss-Prot sequence library entry. Validation of Proteins Retrieved and Identified from FFPE Tissues Using IHC. A panel of 17 proteins (Table 1) was selected from MS-based proteomic measurements for validation using IHC. Adjacent sections from the same tissue blocks used for the MS-based experiments were used for IHC. The normal human liver tissues employed for IHC validation were incorporated into one multi-tissue block for consistent comparison, and to ensure equivalent protocols for IHC staining. The Elite avidin–biotin-peroxidase complex (ABC) detection system (Vector Laboratories, Burlingame, CA) was used by following the manufacturer’s instructions. Primary antibodies used for IHC study were purchased from suppliers listed in Table 1 except CD74 and CD75 that were provided by Dr. Allan Epstein’s laboratory at the Department
Antigen Retrieval for Proteomic Characterization of FFPE Tissues Table 1. Primary Antibodies and Positive Controls Employed in IHC Validations Studies antibody
dilution
sourcea
positive control
Lymph node Lymph node Lymph node Colon carcinoma Muscle Spleen Gastrointestinal stromal tumor Bone marrow
Vimentin CD74 (LN2) CD75 (LN1) Villin
1:15000 1:2 1:4 1:50
Chemicon Dr. A. Epstein Dr. A. Epstein Cell Marque
Desmin Lysozyme CD117
1:100 1:8000 1:100
Cell Marque DAKO DAKO
Hemaglobin alpha CD44
1:1,000
DAKO
Prediluted
BioCare
CD45 Cox 2
1:500 1:100
Cell Marque NeoMarkers
PCNA S-100 C3 Myeloperoxidase GRP-78
1:2000 1:200 1:100 1:600 1:100
DAKO Cell Marque DAKO Cell Marque Santa Cruz
E-cadherin
1:100
Zymed
Breast carcinoma Lymph node Breast carcinoma Lymph node Melanoma Lymph node Bone marrow Breast carcinoma Prostate carcinoma
a Chemicon (Temecula, CA); Cell Marque (Sacramento, CA); DAKO Cytomation (Carpinteria, CA); BioCare Medical (Concord, CA); NeoMarkers (Fremont, CA); Santa Cruz Biotechnology (Santa Cruz, CA); Invitrogen/Zymed (Carlsbad, CA).
of Pathology, USC. Normal goat or horse serum diluted 1:20 was used for a 20 min incubation to block the nonspecific background binding of polyclonal (only Cox-2 and myeloperoxidase) and monoclonal antibodies, respectively. All primary antibodies were incubated at room temperature for 1 h, except PCNA, GRP-78, and E-cadherin, which were overnight. The biotinylated anti-rabbit and mouse immunoglobulins were employed as the link antibody for the polyclonal and monoclonal antibodies, respectively, and were incubated for 45 min. The ABC was utilized as the labeling reagent and incubated for 30 min. A 10-min wash step with phosphate buffered saline (PBS) at pH 7.2 was carried out between each step. 3,3′-Diaminobenzidine tetrahydrocholoride was utilized as the chromogen. Slides were counterstained using hematoxylin and mounted for examination. Positive controls in comparable microtissue arrays were employed to confirm the positive pattern for each antibody tested. Negative controls on all four human liver tissue blocks were conducted using PBS instead of the primary antibody. Immunostained slides were evaluated by microscopy. The intensity of immunostaining was graded as + and – for positive and negative, respectively. A score of ( was used to represent very weak positive staining.
Results and Discussion From a practical point of view, one of the most difficult issues in the standardization of IHC, as applied to FFPE tissues, relates to extreme variability in tissue sample preparation, particularly the time of fixation in formalin. It is therefore not surprising to notice that the preservation of antigenicity in FFPE tissues may vary greatly, and may result in variable intensity of immunostaining for formalin sensitive antigens.40 On the basis of the maximal retrieval level, it may also be possible to equalize
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the immunoreactivity in a variety of archival FFPE tissue sections that are fixed in formalin for various period of time. In fact, studies have suggested that increased heating may reverse the effects of longer fixation.41 By employing samples of representative fresh tissues from normal mice, including liver and spleen, the extent of fixation time during the preparation of FFPE tissue sections was varied for the period of 0 h (fresh), 6 h, 24 h, 7 days, and 14 days. In addition to manipulating the fixation time, the level of protein retrieved was also evaluated under the influence of various AR conditions including different pH values of 2, 7, and 10. Proteins retrieved from a total of 90 extraction experiments (5 fixation times × 3 solution pHs × 3 replicates × 2 organs) were individually analyzed and quantified using SDS-PAGE and modified Bradford assay. There were no significant differences in protein quality and quantity extracted from FFPE tissues treated by various fixation times. In fact, a protein yield of approximately 325–375 µg was typically obtained from a FFPE tissue sample (containing 5 tissue sections of 1 cm × 1 cm × 10 µm) for all of fixation and retrieval conditions investigated and was comparable (∼95%) to those extracted from an equal amount of fresh-frozen tissue. Following the protocol outlined in Figure 1, CITP-based analyses were performed on a subset of samples to survey the effects of differing fixation times and antigen retrieval pH conditions on shotgun proteomic analysis. These results, depicted in Figure 2, demonstrate that the effects of varying fixation time and antigen retrieval pH conditions have a minimal effect on this form of analysis. Proteins’ retrieval at pH 10 at fixation time points from 0 h (fresh) to 14 days shows variances in spectral counts, distinct peptides of 4%, 16%, and 10%, respectively. Similarly, proteins retrieved from samples fixed for 24 h at pH 2, 7, and 10 showed variances in spectral counts, distinct peptides, and proteins of 12%, 6%, and 7%, respectively. Such variances are within those of the analytical platform. The ability to achieve excellent protein recovery from FFPE tissues was attributed to the use of both heating and a detergent such as SDS as supported by our previous work.31,32 In fact, Fowler et al.42 have compared 6 different protocols for protein extraction from FFPE tissues, and concluded that the most effective protein extraction buffer tested was a 20 mM Tris solution containing 2% SDS at high temperature31 which is the same method utilized here. Following the optimization studies of protein retrieval/ extraction, comprehensive analysis of protein expression profiles within FFPE tissues of normal human liver was conducted using transient CITP-based multidimensional separations coupled with ESI-LTQ-MS. The amount of protein digests loaded into the CITP capillary was less than 4 µg (CITP injection volume of 4 µL × peptide concentration of 0.8 µg/µL) for performing each of FFPE tissue proteome analyses. A 1% FDR of total peptide identifications led to the identification of 17 074, 17 547, and 19 441 fully tryptic peptides covering 3209, 3302, and 3350 distinct human Swiss-Prot protein entries from each of three biological samples. The large sequence coverage among identified proteins was evident by an average of 5.4 peptides per run leading to each protein identification. This compares favorably to our CIEF-based results in which 8408 and 14 748 distinct peptides were identitified mapping to 1796 and 2733 distinct proteins with per run protein coverage averaging 5.0 distinct peptides.32 The improved results based on the CITP method are attributed to the capability of the method to selectively enrich analytes.33,34 Additionally, the Journal of Proteome Research • Vol. 7, No. 3, 2008 1101
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Figure 3. A pseudo 2-D PAGE display of a representative proteomic data set obtained from the analysis of FFPE human liver tissues. The size of the circles represents the degree of protein abundance determined by the spectral counting approach.44–46
Figure 2. (A) Plot of spectral counts, distinct peptides, and proteins identified in samples extracted at pH 10 and fixed in buffered formalin for the indicated time. In each case, a single CITP/CZE-RPLC-MS/MS analysis was performed. (B) In this case, the samples were fixed for 24 h, and antigen retrieval conditions were done at the indicated pH value. Similarly, a single CITP/ CZE-RPLC-MS/MS analysis was performed for each case.
CITP-based separation proved more robust than CIEF in that CIEF is prone to precipitation as analytes near their isoelectric point and a zero net charge. This is particularly noted in the case of FFPE samples, possibly due to the presence of persistent cross-linked peptides which did not undergo cross-link reversal during the AR process. A pseudo 2-D PAGE display of one of three proteomic data sets is shown in Figure 2 to illustrate the broad tissue proteome coverage over wide ranges of pI and molecular mass. Compared to our previous work employing combined CIEF/nano-RPLC separations31,32 and several recently reported FFPE tissue-based proteomics studies,24–30 our results presented the largest catalog of proteins retrieved and identified from FFPE tissues reported to date. Application of only a single-dimension separation in these recent studies24–30 due to sample amount constraints has significantly limited the dynamic range and detection sensitivity of MS measurements compared to what is achievable by two-dimensional peptide separations. The ability to mine deeper into the tissue proteome was attributed to the high resolving power of transient CITP/CZE with even lower peptide fraction overlap than that typically observed in the CIEF separation.34 For example, the number of peptides identified uniquely in 1 or 2 fractions ranged from 84.6 to 86.9% in the CIEF-based FFPE analyses previously reported,43 where 15 fractions were sampled. CITP/CZE, in contrast, was able to 1102
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Figure 4. Venn diagram comparing the FFPE tissue proteome results obtained from three normal human liver specimens.
increase resolution such that 88.6–91.6% of peptides identified were detected uniquely in 1 or 2 fractions despite a doubling in the number of fractions sampled to 30. To highlight the relatively low degree of protein redundancy in the Swiss-Prot database employed in this study, the combined proteomic results obtained from three FFPE liver tissues yielded a total of 4098 distinct human protein entries (Figure 3), corresponding to 3895 nonredundant proteins. The Venn diagram shown in Figure 4 presented a core set of 2544 distinct proteins identified among three FFPE tissue blocks examined in this study, corresponding to greater than 76% of proteins measured within each of the distinct liver specimens. In addition to protein identification, the CITP-based proteomic platform was coupled with the spectral counting quantification approach44–46 for determining and comparing protein expression profiles within these liver tissue blocks. This label-free protein quantification approach is based on the number of peptides derived from protein digestion and sequenced by tandem MS (MS2) in a shotgun proteomic
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Figure 5. The Pearson correlation coefficient plot of two proteomic runs analyzing two different FFPE human liver tissue specimens.
analysis. The spectral counts of individual proteins were normalized against the average number of spectral counts across all runs and termed expression values. As shown in Figure 5, the Pearson correlation plot among two of three liver tissue specimens examined in this study gave a coefficient of greater than 0.97 over a dynamic range of at least 103. This value, obtained from the correlation between two distinct biological samples, compares favorably with a recent report of a Pearson correlation coefficient of 0.88 among technical replicates (repeated analyses of the same proteomic sample) using a multidimensional liquid chromatography system.47 It should be emphasized that one of our research goals is to identify retrievable proteotypic peptides which represent epitopes potentially available to antibodies for the purpose of performing IHC measurements. No attempts were made to discover remaining cross-linked peptides as our searches only sought to detect proteolytic peptides as the result of tryptic digestion
with limited modifications. As demonstrated by the work of Rait and co-workers,48,49 the reduction of immunoreactivity due to formalin-induced intramolecular modifications prevails over the excluded volume effect of intermolecular cross-links. Additionally, the antigen retrieval mechanism appears to involve the hydrolysis of cross-linkages between formalin and proteins driven by thermal energy from the heat source.18,19 Thus, those protein fragments remained in cross-linking conditions after the protein retrieval/extraction and overall sample preparation processes neither are recognizable by antibodies, nor can be identified in our proteomic workflow. Two cases of protein coverage are depicted in Figure 6. The lower panel represents desmin coverage, which is extensive and includes in some cases the C-terminus, which is often used for antibody generation. Note also that coverage is similar for fresh-frozen and formalinfixed tissue. The upper panel depicts ErbB2 coverage which is more modest and which differs considerably between freshJournal of Proteome Research • Vol. 7, No. 3, 2008 1103
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Figure 6. Protein coverage of ErbB2 and desmin in samples extracted at pH 10 and fixed in formalin for the indicated time. Peptide color was determined on a per peptide basis by summing the OMSSA p-value multiplied by the number of spectral counts. Only peptides which meet the 1% FDR cutoff are shown.
frozen and fixed tissue. In such a case, it is not clear from the data gathered that the C-terminus would represent a potential antigenic region, although paraffin-compatible antibodies are available which target the C-terminus. However, the peptide indicated in the boxed region, LLQETELVEPLTPSGAVPNQAQMR, is found in 3 of the 4 cases and is proteotypic50,51 for ErbB2. That is, the peptide uniquely identifies the ErbB2 protein, is observable in our studies, and is therefore a potential candidate for use as an antigen from which to raise an antibody for paraffincompatible IHC or as an ErbB2 marker in shotgun proteomicbased quantitative multiple reaction monitoring studies52 in formalin-fixed tissues. Thus, the data gathered here on over 4000 proteins determined to be expressed in and retrievable from formalin-fixed liver tissue may serve as a potential resource for downstream studies and/or new applications. A panel of 17 proteins selected for IHC validation is summarized in Table 1 together with the source of primary antibodies, their dilution ratios, and positive controls in comparable tissue microarrays. These proteins were chosen on the basis of antibodies available from the IHC facility at USC with abundances ranging from high and moderate to trace amounts as measured by the CITP-based platform coupled with the spectral counting approach.44–46 All proteins which were detected by one or two spectral counts and for which an antibody was available were tested. The results of IHC staining obtained from the same FFPE liver tissue blocks, which were also employed for MS-based proteomic analysis, were summarized in Table 2 and compared with the number of spectral counts determined for each of all 17 proteins. Low-abundance proteins such as CD74, CD45, and S-100 were only identifiable in one or two of three tissue specimens by MS detection, but revealed in all tissues using IHC. This highlights the high sensitivity of IHC assays and the random sampling nature of discovery-based MS assays. The finding also supports evidence indicating that a great majority of single peptide hits are often true.53 Together this suggests 1104
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Table 2. Summary of IHC Staining Results and Comparison with Spectral Counts Measured by MS-Based Proteome Analysisa IHC Staining Intensity (Number of Spectral Counts) protein
sample 1
sample 2
sample 3
Vimentin CD74 (LN2) CD75 (LN1) Villin Desmin Lysozyme CD117 Hemaglobin alpha CD44 CD45 Cox 2 PCNA S-100 C3 Myeloperoxidase GRP-78 E-cadherin
+ (178) + (1) + (3) + (19) + (20) + (1) + (2) + (500) + (3) + (2) + (9) + (2) + (1) + (80) + (13) + (98) + (2)
+ (155) + (0) ( (1) + (24) + (29) + (5) + (1) + (384) + (5) + (0) + (15) + (2) + (0) + (102) + (14) + (135) + (3)
+ (184) + (0) + (3) + (21) + (22) + (4) + (1) + (314) + (3) + (1) ( (5) + (2) + (0) + (116) + (16) + (156) + (6)
a Evaluation of IHC staining results: immunostained slides were evaluated by microscopy. The intensity of positive immunostaining was graded as + or –, for positive or negative, respectively. A score of “(” was used to represent very weak positive staining of IHC staining results. Spectral counts are indicated in parentheses. A value of ‘0’ indicates the protein was not detected.
that sufficient analyses of technical or, preferably, biological replicates be performed such that statistical tests may be applied for the evaluation of MS data rather than solely relying on per run-based false-discovery thresholds. Despite the fairly homogeneous cellular nature of liver as comprised of mostly parenchymal hepatocytes (∼80% of liver cells), there is substantial presence of other cell types including biliary, endothelial, and Kupffer cells, plus stromal and blood cells. Instead of retrieving proteins from the whole tissue
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Figure 7. IHC staining of 17 proteins selected for validation on the same tissue blocks. (A–Q) Staining results of 17 antibodies as listed in Table 1. (R–T) Negative control on all three human liver tissue blocks. Original magnification ×100.
section containing various cell populations for MS-based proteomic analysis, the subcellular resolution achievable by IHC allows analysis of specific tissue and cellular localizations for enhancing the quality and sensitivity of immunostaining. In consideration of this, we have used tissue microdissection in our previous studies31,32,54–58 to provide enriched and high quality tumor cells, for analyisis by combined CIEF and nanoRPLC MS/MS of glioblastoma multiforme and ovarian carcinoma tissues.
As shown in Figure 7, positive IHC staining results were achieved for all 17 proteins selected from global FFPE tissue proteomic studies for validation. For example, villin was localized in the lumen of bile duct (Figure 7D) which was exactly the localization of the positive control colon cancer sample (data not shown). Typical cell membrane IHC staining patterns were observed in Figure 7, panels C, I, and Q for CD75, CD44, and E-cadherin, respectively. A nuclear IHC staining pattern was found in Figure 7L for PCNA. Additionally, the Journal of Proteome Research • Vol. 7, No. 3, 2008 1105
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cellular or tissue localization of proteins was in agreement with that expected from the knowledge of cell type and function. For example, GRP-78 (Figure 7P) was strongly positive in small cells infiltrating the sinusoids of liver tissue; these small cells appeared to be lymphocytes which frequently contain GRP-78 as an internal positive control. A stronger staining result of E-cadherin (Figure 7Q) was found in bile ducts than that within liver cells. Positively stained Kupffer cells, characterized by their irregular shape, elongated nuclei, and variable amounts of cytoplasm, can be seen in Figure 7, panels B, F, M, and O for CD74, lysozyme, S-100, and myeloperoxidase, respectively. CD117 (Figure 7G) revealed a few strongly positive cells in portal tract areas. As reported by common observation in the literature, most false peptide identifications tend to be ones in which the corresponding protein is only identified by a single peptide. Thus, many proteomic research laboratories routinely discard single peptide identifications to significantly reduce the FDR of distinct protein identifications. However, as previously demonstrated by Dr. Gygi’s59 and our laboratories,39 these single-protein identifications, after filtering at a 1% FDR of total peptide identifications, are mostly correct and often represent 30–50% of a proteomic data set. For example, several lowabundance proteins, including CD74, CD117, CD45, and S-100, were identified by single peptide hits in as few as one of the three runs of the analysis of FFPE liver tissues and were successfully validated by subsequent IHC measurements in each biological sample (Figure 7). The removal of these protein identifications greatly increases the false-negative rate and negatively impacts the coverage and the sensitivity of overall analysis. As advocated by Elias and Gygi59 and also implemented in our proteomic studies, the target-decoy search strategy is employed as routine practice to effect more stringent criteria for single-peptide identifications. As shown in Figure 8, tandem MS spectra of unique peptides leading to the identifications of CD 45, CD74, and S-100 exhibited the E-values of 7.9 × 10-11, 5.0 × 10-7, and 3.3 × 10-7, respectively, from a target-decoy OMSSA search.
Conclusion On the basis of the maximal retrieval level, there were no significant differences in protein quality and quantity extracted from FFPE tissues fixed in formalin for various periods of time. In fact, the amounts of protein extracted from FFPE tissues for all fixation and retrieval conditions investigated in this study were comparable to those obtained from an equal size of matching fresh-frozen tissues. The ability to achieve excellent protein recovery from FFPE tissues was attributed to the use of SDS detergent in combination with the heat-induced antigen retrieval approach. This finding is significant because, while most tissues are fixed in formalin overnight, it is a common occurrence for tissue obtained on a Friday to sit in formalin over the weekend before paraffin embedding. In parts of the world without on-site pathology facilities, tissue samples are routinely placed in formalin and shipped to another site for embedding. Such shipments can take days or weeks. Our data indicate that samples fixed in formalin for anywhere from 6 h to 14 days prior to embedding show no significant difference in protein recovery for the purpose of shotgun proteomics. Because of the ability of the transient CITP/CZE-based shotgun proteomic analysis to achieve high-resolution separations of minute protein digests and selective enrichment of lowabundance proteins, the combined proteomic results obtained 1106
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Figure 8. Tandem mass spectra of unique peptides leading to the identifications of (A) CD45, (B) CD74, and (C) S100.
from three FFPE liver tissues yielded a total of 4098 distinct human protein entries, corresponding to 3895 nonredundant proteins. Positive IHC staining results were achieved for all 17 proteins selected from MS-based tissue proteomic studies for validation. The cellular or tissue localization of proteins was in agreement with that expected from the knowledge of cell type and function. Furthermore, several low-abundance proteins, including CD74, CD117, CD45, and S-100, were identified by single peptide hits during the proteomic analysis of FFPE liver tissues and were successfully validated by subsequent IHC measurements. Disease is, by and large, defined on the basis of cellular and, increasingly, molecular pathology. The last several decades have seen an accumulation of data describing the characteristics of cancer cells at both the nucleic acid and protein levels (molecular phenotype). Opportunities exist for much more
Antigen Retrieval for Proteomic Characterization of FFPE Tissues extensive characterization than is currently practicable using conventional pathological assays through the use of mass spectrometry-based approaches. Analyte sensitivity and cellular resolution are two areas which require improvement before such methods can be considered for diagnostic use. We have described here a method for improving sensitivity through the use of a very high-resolution, first-dimension separation. Sensitivity may be further improved by minimizing sample complexity as we have done previously through the use of microdissection. Microdissection also addresses to some extent the issue of cellular resolution inasmuch as sensitivity allows. MALDI-based tissue imaging similarly partially addresses both of these issues, with more emphasis given to resolution than sensitivity. Today cellular- and molecular-based pathology methods coexist but, in the absence of any integrated approach to the proper preparation of samples for this form of dual analysis, are not well-coordinated. Thus, there is increasing acceptance of the critical importance of relating the morphological knowledge of tissue with the data obtained from various molecular analysis techniques. Furthermore, proteomic profiling of archived FFPE tissue collections, with the attached clinical and outcome information, has great potential to lead to the discovery of novel protein targets for improved therapeutic treatments. Identification of biomarkers which have accurate, consistent, precise, and reproducible diagnostic, prognostic, or therapeutic utility would be of significant value to the oncology community as outlined by the National Cancer Institute.
Acknowledgment. This work was supported by NIH grants GM073723 to C.S.L. and CA 122715 to B.M.B. We thank Lillian Young and William Win for their kind help with the IHC experiments and Dr. Alan Epstein for his generous gift of paraffin-compatible CD74 and CD75 antibodies for IHC studies. Supporting Information Available: List of identified proteins together with identifying peptides are provided for the mouse analyses. This information is available free of charge via the Internet at http://pubs.acs.org. References (1) Bachoo, R. M.; Maher, E. A.; Ligon, K. L.; Sharpless, N. E.; Chan, S. S.; You, M. J.; Tang, Y.; DeFrances, J.; Stover, E.; Weissleder, R.; Rowitch, D. H.; Louis, D. N.; DePinho, R. A. Cancer Cell 2002, 1, 269–277. (2) Buckner, J. C. Semin. Oncol. 2003, 30, 10–14. (3) Godard, S.; Getz, G.; Delorenzi, M.; Farmer, P.; Kobayashi, H.; Desbaillets, I.; Nozaki, M.; Diserens, A.-C.; Hamou, M.-F.; Dietrich, P.-Y.; Regli, L.; Janzer, R. C.; Bucher, P.; Stupp, R.; de Tribolet, N.; Domany, E.; Hegi, M. E. Cancer Res. 2003, 63, 6613–6625. (4) Mischel, P. S.; Shai, R.; Shi, T.; Horvath, S.; Lu, K. V.; Choe, G.; Seligson, D.; Kremen, T. J.; Palotie, A.; Liau, L. M.; Cloughesy, T. F.; Nelson, S. F. Oncogene 2003, 22, 2361–2373. (5) Freije, W. A.; Castro-Vargas, F. E.; Fang, Z.; Horvath, S.; Cloughesy, T.; Liau, L. M.; Mischel, P. S.; Nelson, S. F. Cancer Res. 2004, 64, 6503–6510. (6) Bredel, M.; Bredel, C.; Juric, D.; Harsh, G. R.; Vogel, H.; Recht, L. D.; Sikic, B. I. Cancer Res. 2005, 65, 8679–8689. (7) Liang, Y.; Diehn, M.; Watson, N.; Bollen, A. W.; Aldape, K. D.; Nicholas, M. K.; Lamborn, K. R.; Berger, M. S.; Botstein, D.; Brown, P. O.; Israel, M. A. Proc. Natl. Acad. Sci. U.S.A. 2005, 102, 5814– 5819. (8) Nigro, J. M.; Misra, A.; Zhang, L.; Smirnov, I.; Colman, H.; Griffin, C.; Ozburn, N.; Chen, M.; Pan, E.; Koul, D.; Yung, W. K. A.; Feuerstein, B. G.; Aldape, K. D. Cancer Res. 2005, 65, 1678–1686. (9) Sanai, N.; Alvarez-Buylla, A.; Berger, M. S. N. Engl. J. Med. 2005, 353, 811–822.
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PR7006768
