Heterogeneous Nuclear Ribonucleoproteins and Their Interactors Are

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Heterogeneous Nuclear Ribonucleoproteins and Their Interactors Are a Major Class of Deregulated Proteins in Anaplastic Astrocytoma: A Grade III Malignant Glioma Ravindra Varma Polisetty,†,‡ Poonam Gautam,†,§ Manoj Kumar Gupta,†,‡ Rakesh Sharma,‡ Megha S. Uppin,∥ Sundaram Challa,∥ Praveen Ankathi,∥ Aniruddh K. Purohit,∥ Durairaj Renu,⊥ H. C. Harsha,‡ Akhilesh Pandey,‡ and Ravi Sirdeshmukh*,†,‡,⊗ †

Centre for Cellular and Molecular Biology (CSIR), Hyderabad, India Institute of Bioinformatics, Bangalore, India § National Institute of Pathology (ICMR), New Delhi, India ∥ Nizam’s Institute of Medical Sciences, Hyderabad, India ⊥ Strand Life Sciences, Bangalore, India ‡

S Supporting Information *

ABSTRACT: Anaplastic astrocytoma is a high grade malignant glioma (WHO grade III) of the central nervous system which arises from a low grade II tumor and invariably progresses into lethal glioblastoma (WHO grade IV). We have studied differentially expressed proteins from the microsomal fraction of the clinical specimens of these tumors, using iTRAQ and high-resolution mass spectrometry followed by immunohistochemistry for representative proteins on tissue sections. A total of 2642 proteins were identified, 266 of them with minimum 2 peptide signatures and 2-fold change in expression. The major groups of proteins revealed to be differentially expressed were associated with key cellular processes such as post transcriptional processing, protein translation, and acute phase response signaling. A distinct inclusion among these important proteins is 10 heterogeneous nuclear ribonucleoproteins (hnRNPs) and their interacting partners which have regulatory functions in the cell. hnRNP-mediated post transcriptional events are known to play a major role in mRNA processing, stability, and distribution. Their altered levels have also been observed by us in lower (diffused astrocytoma) and higher (glioblastoma) grades of gliomas, and membrane localization of hnRNPs has also been documented in the literature. hnRNPs may thus be major factors underlying global gene expression changes observed in glial tumors while their differential presence in the microsomal fraction suggests yet additional and unknown roles in tumorigenesis. KEYWORDS: anaplastic astrocytoma, glioma, proteomics, mass spectrometry, iTRAQ, microsomal proteins, hnRNP

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INTRODUCTION Anaplastic astrocytoma (WHO grade III) is a high-grade malignant tumor of astrocytic origin in the central nervous system. It commonly occurs in the age group of 30−50 years, usually arises from the diffuse infiltrating astrocytoma (WHO grade II), and invariably progresses into the most malignant phenotype, glioblastoma (WHO grade IV) with poor prognosis. The median survival of the patients is 3−5 years after diagnosis. The disease management involves surgery, chemotherapy, and radiotherapy depending on tumor response to treatment and the site of location. Several gene expression studies using cDNA or oligonucleotide microarrays on gliomas have been reported previously. In one of the early studies, Freije et al. performed large-scale gene expression analysis of 85 gliomas of all histologic types using oligonucleotide arrays.1 They identified 44 genes whose © XXXX American Chemical Society

expression patterns were used to classify gliomas into previously unrecognized biological and prognostic groups. Chang et al. investigated gene expression profiles of Taiwanese patients with anaplastic astrocytoma and identified nearly 52 differentially expressed genes compared to normal brain.2 In another interesting study, Van et al. analyzed the transcriptional profile of approximately 6800 genes in primary grade II gliomas and corresponding recurrent high-grade gliomas (grade III or IV) from eight patients using oligonucleotide-based microarray analysis.3 A total of 66 differentially expressed genes were identified between the primary and recurrent tumors. On the proteomics front, Iwadate et al. compared the protein profiling patterns between low and high grade glioma tumors Received: December 19, 2012

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dx.doi.org/10.1021/pr400339h | J. Proteome Res. XXXX, XXX, XXX−XXX

Journal of Proteome Research

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by the 2DE-MS approach.4 They showed correlation of differentially expressed protein-based clustering of gliomas with patient survival. In our earlier studies, we have reported differentially expressed proteins studied by the 2DE-MS approach in all grades of gliomas and identified 72 differentially expressed proteins in multiple tumor samples.5 A major finding of this study was fragmentation of the overexpressed protein glial fibrillary acidic protein (GFAP) in the grade III tumors which further intensifies in grade IV tumors. Interestingly GFAP has been subsequently reported as a serum marker for grade IV tumors.6 A speculative model of tumorigenesis implicating the role of some of the differentially expressed proteins observed has been discussed in the review by Sirdeshmukh et al.7 In the present study, we have carried out deeper proteomic analysis of the microsomal fraction of anaplastic astrocytomas (WHO grade III) by the quantitative liquid chromatography−tandem mass spectrometry (LC−MS/ MS) approach using isobaric tags for relative and absolute quantification (iTRAQ) and identified differentially expressed microsomal proteins to understand altered pathways, networks, and cellular processes involved in these tumors. Our study reveals a large portfolio of differentially expressed regulatory proteins in anaplastic astrocytoma and provides important molecular insights.

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Sample Processing for iTRAQ Labeling and SCX Fractionation

Microsomal proteins were subjected to trypsin digestion and the peptides were labeled with iTRAQ reagents according to the manufacturer’s instructions (iTRAQ Reagents Multiplex kit; Applied Biosystems/MDS Sciex, Foster City, CA) and as described previously.9 Tumor tissue samples were labeled with 116 and 117 tags and control samples with 114 and 115 tags providing internal technical replicates for the two types of samples. All the four labeled samples were pooled, vacuumdried, and subjected to strong cation exchange (SCX) chromatography as also described previously.9 Peptides eluting from the column were collected, and consecutive fractions were pooled to obtain a total of eight fractions for LC−MS/MS analysis. LC−MS/MS Analysis

Nanoflow electrospray ionization tandem mass spectrometric analysis was carried out using LTQ Orbitrap Velos (Thermo Scientific, Bremen, Germany) interfaced with Agilent’s 1200 series nanoflow LC system. Peptides from SCX fractions were enriched using a C18 Trap column and separated on an analytical column (75 μm × 10 cm) at a flow rate of 350 nL/ min using a linear gradient of 7−30% acetonitrile (ACN) over 65 min. Mass spectrometric analysis was carried out in a data dependent manner with full scans acquired using the Orbitrap mass analyzer at a mass resolution of 60 000 at m/z 400. From each MS scan, the 20 most intense precursor ions were selected for MS/MS fragmentation and detected at a mass resolution of 15 000 at m/z 400. The fragmentation was carried out using higher-energy collision dissociation (HCD) with 40% normalized collision energy. The ions selected for fragmentation were excluded for 30 s. The automatic gain control for full Fourier transform mass spectrometry (FT MS) was set to 1 million ions and for FT MS/MS was set to 0.1 million ions with a maximum time of accumulation of 500 ms. For accurate mass measurements, the lock mass option was enabled.

EXPERIMENTAL PROCEDURES

Sample Collection and Processing

All the samples were collected at the time of surgery with informed consent from patients and approval of the Institutional Ethics Committee, Nizam’s Institute of Medical Sciences (NIMS), Hyderabad. Tumor tissue specimens were snap frozen in liquid nitrogen and stored at −80 °C until use. Multiple sections from the temporal neocortex were studied and the grade (anaplastic astrocytoma) assigned on the basis of clinical evaluation and histopathology as per WHO guidelines. Brain tissue obtained from temporal lobe epilepsy surgeries were collected as experimental controls. These patients were in the 20−30 year old age group. The temporal cortex used as a control did not show any abnormalities by light microscopy. Further, immunohistochemistry (IHC) with antibodies directed against phosphorylated neurofilament and synaptophysin proteins did not reveal any abnormal neurons in the cortex. For implementing well-monitored procedures, the specimens were collected from one clinical center over a period of 18 months. Out of over 100 surgical biopsies collected, 45 were astrocytomas, 13 of them being grouped as anaplastic astrocytomas. Six age matched samples (30−50 years) of either sex were selected for the present study.

Bioinformatics Analysis

Protein identifications, quantifications, and annotations of differentially expressed proteins were carried out as follows. The MS data was analyzed using Proteome Discoverer (Thermo Fisher Scientific, version 1.3). MS/MS search was carried out using the Sequest search algorithm against the NCBI RefSeq database (release 45) containing 31 811 proteins. Search parameters included trypsin as an enzyme with 1 missed cleavage allowed; precursor and fragment mass tolerance were set to 20 ppm and 0.1 Da, respectively; methionine oxidation was set as a dynamic modification while methylthio modification at cysteine and iTRAQ modification at the Nterminus of the peptide and epsilon amino group of the lysine side chain were set as static modifications. The peptide and protein information were extracted using high peptide confidence and top one peptide rank filters. The false discovery rate (FDR) was calculated by enabling the peptide sequence analysis using a decoy database. High confidence peptide identifications were obtained by setting a target FDR threshold of 1% at the peptide level. Relative quantitation of proteins was carried out based on the relative intensities of reporter ions released during MS/MS fragmentation of peptides. Unique peptides for each protein identified were used to determine relative protein content in control and tumor samples. The average relative intensities of the two reporter ions for each of the peptide identifiers for a protein were used to determine

Subcellular Fractionation for Enrichment of Microsomal Proteins

Tissues from tumor patients (n = 6; 4 males and 2 females) or control subjects (n = 3; 2 males and 1 female) were pooled separately and the microsomal fraction was prepared according to the procedure of Cox et al.8 and described by Polisetty et al.9 The procedure yields a preparation which consists of proteins of endoplasmic reticulum (ER), golgi, intracellular vesicles, plasma membrane, and their interacting proteins. The protein amount in the preparation was estimated using the Bradford method. B



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Figure 1. (A) Experimental workflow for iTRAQ labeling and LC−MS/MS analysis of microsomal proteins from anaplastic astrocytomas. Details of preparation of the microsomal fraction, iTRAQ labeling, SCX prefractionation, and nano RPLC−MS/MS are provided under Experimetal Procedures. (B) Western blot of calreticulin showing microsomal protein enrichment. The microsomal protein fraction and the cytoplasmic protein fraction were immunoblotted using commercial calreticulin antibodies as described previously.9

Immunohistochemistry

relative quantity of a protein and percentage variability. Appropriate filters at the level of peptides/peptide spectral matches (PSMs) and then at the protein level were applied to the quantification values. (a) First, only peptide/PSMs that are unique for a protein were included for fold change calculation. (b) Next, peptide/PSMs with higher than 30% variability between the replicate label measurements (i.e., 114 and 115 for control) or (i.e., 116 and 117 for tumor) were removed programmatically from the entire set of raw files. (c) We then selected a protein subset with 1.5-fold change cut off and then curated it further for 1.5-fold cutoff even at their respective peptide/PSMs level and protein fold changes were recalculated based on quantitative ratio values of the selected peptides/ PSMs. (d) Even the upper threshold at the level of peptide/ PSM was manually checked and filters were applied wherever necessary (about 10% of proteins) to permit all values within 40% variability. (e) At the end, to evaluate the applied filters, we calculated four independent ratios (116/114, 117/114, 116/ 115, and 117/115 derived from internal technical replicates) for all PSMs and the relative standard deviation (RSD) value was determined for four ratios of each PSM included in the data set. Similarly we calculated RSD values across all PSMs with each of the four ratios, contributing to a protein in the data set (n = 266). For more than 95% of the proteins, the RSDs calculated as above in two dimensions were found to be below 40% and none above 50%, including RSDs for all hnRNPs highlighted (see Discussion). All RSD values are shown in columns I, J, K, L, and AH of Supplementary Table S2 in the Supporting Information (see Results). Annotations of the proteins identified were carried out based on the Human Protein Reference Database10 (HPRD, http:// www.hprd.org). Mapping of molecular functions and pathways was done using the Ingenuity Pathway Knowledge Base (Ingenuity Systems, Redwood City, CA) tool. Proteins containing signal peptide and transmembrane domains were identified by SignalP 3.0 and TMHMM 2.0 software tools, respectively.

Verification of iTRAQ results was carried out by IHC on tissue sections for select proteins. Details of the antibodies used for specific proteins are given in Supplementary Table S1 in the Supporting Information. After deparaffinization and rehydration of formalin-fixed paraffin-embedded individual tumor tissue sections, antigen retrieval was performed by immersing the slide in antigen retrieval buffer (10 mM sodium citrate, 0.05% Tween 20, pH 6.0) at 95 °C for 5 min. Endogenous peroxidases were blocked with 0.03% hydrogen peroxide, and nonspecific binding was blocked with 2% fetal calf serum in Tris-buffered saline with 0.1% Triton X-100 (TBST, pH 7.6). Sections were then incubated for 1 h at room temperature (RT) with primary antibodies followed by peroxidase-labeled polymer conjugated to antimouse or antirabbit immunoglobulins compatible with the primary antibody for 1 h and developed with the DAB system. Sections were counter stained with the Mayer’s hematoxylin and dehydrated, and images were taken under microscope. The distribution of staining across the section was observed under microscope. Each tissue section was scored as negative (0), mild (1+), moderate (2+), and strong (3+) based on the staining intensity.

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RESULTS Microsomal protein fraction consists of proteins of endoplasmic reticulum (ER), golgi, intracellular vesicles, plasma membrane, and their interacting proteins. These proteins are involved in diverse cellular functions such as cell signaling, cellular movement, and morphology, and their altered expression is known to be associated with tumor cell development and metastasis.11 We have used the microsomal fraction from pooled tumor tissue specimens from clinically diagnosed anaplastic astrocytoma patients for analysis of differentially expressed proteins. The workflow of the analysis is given in Figure 1A. Enrichment of microsomal proteins in the microsomal preparation was assessed by comparing the relative levels of the membrane protein, calreticulin (55 kDa), in C



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Figure 2. Verification of differential expression observed in LC−MS/MS analysis with immunohistochemistry on the tissue section. (A) MS/MS spectra of peptides with their reporter ions for representative differentially expressed proteins ANXA5, SPARC, hnRNP K, and HMGB1. MS and MS/MS spectra acquisition is described in Experimental Procedures. (B) Immunohistochemistry for these proteins was performed on individual tissue sections. The staining and scoring details are shown in Supplementary Table S3 in the Supporting Information.

comparison to the cytoplasmic fraction by Western blot analysis (Figure 1B). We have verified iTRAQ results by immunohistochemistry on 10 individual tumor tissue sections. For clinical validation, larger patient cohorts will be used. Analysis of eight peptide fractions of multiplexed iTRAQ labeled tryptic digests of the microsomal fractions of grade III tumor tissues, by the reversed-phase liquid chromatography (RPLC)−MS/MS approach, a total of 21 004 iTRAQ labeled peptides were identified which mapped to 2642 proteins. Quantitative ratios for each of these proteins were extracted, and quality control measures applied at the peptide/PSM and protein level resulted in the identification of 266 highconfidence differentially expressed proteins with a minimum of 2 unique peptides and a 2-fold expression change, all within 40% variability. The relative standard deviation (RSD) calculated for the four ratios (116/114, 117/114, 116/115, and 117/115) at PSM level were also found to be less than 40% for most of the proteins (see Experimental Procedures). We identified 66 proteins with 2 peptides, 41 with 3 peptides, and the remaining 159 proteins with 4 or more peptides. Supplementary Table S2 in the Supporting Information provides the list of these proteins along with their peptide information, quantity ratios (fold change), molecular or biological functions, and localizations. The improvement in data quality is represented for the hnRNPs, a protein group

highlighted in this study and is shown in Supplementary Figure S1 in the Supporting Information. Further, the differential expression of 10 hnRNPs observed here is also consistent with transcriptomic studies on grade III glioma tumors (http:// www.oncomine.org). To confirm the quantitative differences observed by iTRAQ analysis, the expression levels of select proteins in the tumor tissue samples were further examined using IHC. We selected candidates on the basis of (1) the extent of altered expression, (2) the biological function of the protein, or (3) novel identification in the context of these tumors. Immunohistochemical analysis of 6 representative proteins on 10 individual tumor tissue specimens showed positive correlation supporting iTRAQ results. They include upregulated proteins such as Ferritin light chain (FTL), Heterogeneous nuclear ribonucleoprotein K (hnRNP K), Myristoylated alanine-rich C-kinase substrate (MARCKS), High mobility group protein B1 (HMGB1), Annexin A5 (ANXA5), and Secreted protein acidic and rich in cysteine (SPARC). Details of the IHC results from 10 individual specimens and 3 controls are provided in Supplementary Table S3 in the Supporting Information. Moderate to strong staining intensities were observed in tumor specimens for proteins ANXA5, SPARC, HMGB1, FTL, hnRNP K, and MARCKS compared to controls. The distribution of staining was above 70% in most of the cases. D



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Figure 3. Ingenuity Pathway Analysis to identify altered cellular processes and canonical pathways in anaplastic astrocytomas: (A) canonical pathways and (B) major cellular processes. The 266 differentially expressed proteins listed in Supplementary Table S2 in the Supporting Information were used for the analyses.

Figure 4. The hnRNPs and their interacting partners present in the networks assessed by the Ingenuity Pathway Knowledge Base. The interactions of hnRNPs with other important molecules are identified by merging the three networks given in Supplementary Table S5 in the Supporting Information. Known tumor proteins such as EGFR, ERK1/2, NF-kB complex, and AKT are identified as major hub molecules and connected to several other proteins identified in the study. Proteins upregulated are shown in red while proteins down regulated are shown in green.

To illustrate correlation between the MS quantification and IHC, MS/MS spectra along with reporter ions of the representative peptides for some of these proteins are shown in Figure 2A and corresponding IHC images in Figure 2B. Several proteins known to be associated with tumor proliferation and metastasis were identified in the study. They include EGFR, a known oncogene with membrane receptor tyrosine kinase activity. In order to identify additional proteins from the data set with oncogenic and tumor suppressor potential, we used the Integrative Oncogenomics (IntOGen)

software tool. It is a resource that integrates multidimensional oncogenomics data for the identification of genes involved in cancer development.12 The prioritization of oncogenes and tumor suppressor genes is based on computational classifiers that use different combinations of sequence and functional data including sequence conservation, protein domains, interactions, and regulatory aspects. EGFR was identified as the top oncogene from the data set which is consistent with the known information. Other proteins from this list could be examined to understand their tumor regulatory functions in a E



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Figure 5. Peptide and peptide spectral match (PSM) information of hnRNPs overexpressed in anaplastic astrocytomas. Their differential expression values are also shown.

D, K, U, DL, A3, A2B1, AB, and A0 proteins were found to be upregulated. The peptide coverage of individual hnRNPs and the number of corresponding PSMs for these molecules are shown in Figure 5, showing their relative abundance. An additional seven hnRNPs (hnRNP H3, R, UL1, UL2, L, M, and H1) were also identified in the study but with single peptides or with less than a 2 fold-change in expression (Supplementary Table S6 in the Supporting Information). Anaplastic astrocytomas are not very responsive to drugs or radiation and have the strong possibility of developing into higher grade glioblastoma with poor outcome. The median survival of these patients is 2−3 years. Convenient methods as alternatives to imaging for monitoring the disease progression would be useful. Of the 266 altered proteins identified by us, 50% could be classified as the plasma membrane associated or extracellular. Further bioinformatics analysis of these 266 proteins using SignalP 3.0 and TMHMM 2.0 software yielded a total of 119 signal or transmembrane domain containing proteins with several of them detectable in normal cerebrospinal fluid (CSF) and plasma16,17 (Supplementary Table S7 in the Supporting Information). Of them, 35 proteins were found to be detectable in both CSF and plasma (Table 1). Some of the important proteins include Chitinase 3-like 1 (also known as YKL-40), Secreted protein acidic and rich in cysteine (SPARC), Annexin A5 (ANXA5), Alpha 1B glycoprotein (A1BG), and a group of Apolipoproteins (APOH, APOA1, APOC1, APOB, and APOE1) all of which are found to be upregulated in the present study. They could be further investigated in blood plasma from patients in a targeted manner as biomarkers.

targeted way. The list of potential tumor regulatory proteins from our data set as predicted by IntOGen is given in Supplementary Table S4 in the Supporting Information. Subcellular classification of the 266 differentially expressed proteins using Gene Ontology information from the Human Protein Reference Database (HPRD) revealed 69% of proteins known to be associated with the microsomal fraction as defined in Experimental Procedures. Although the microsomal association of the remaining 31% proteins may be debatable, the significance of their differential status in the tumor context cannot be ignored. Therefore, we subjected all 266 proteins to Ingenuity Pathway Knowledge Base classification to assign molecular and cellular functions, networks, and canonical pathways. Eukaryotic initiation factor 2 signaling (EIF2) and Acute phase response (APR) signaling were the major canonical pathways enriched in this data set (Figure 3A). Cell-to-cell signaling and interactions and RNA post-transcriptional modification were the major molecular and cellular functions identified (Figure 3B). The protein IDs and P-values associated with networks, canonical pathways, and molecular and cellular processes are shown in Supplementary Table S5A− C in the Supporting Information. EIF2 signaling is associated with stress induced regulation of translation in eukaryotic cells. It is reported to regulate the translation of specific mRNAs belonging to the pro inflammatory cytokine class.13 Acute phase proteins associated with inflammation were also identified in the study. Acute phase response (APR) proteins are known to be produced in response to cancer associated inflammation.14 The Acute phase response pathway was also found to be enriched in glioblastoma at tissue and plasma levels as recently reported by us.9,15 The top network identified includes molecules associated with DNA replication, recombination, and repair, RNA post transcriptional modification, cellto-cell signaling, and interaction. To have a global view of the protein interaction network, the top three networks given in Supplementary Table S5 in the Supporting Information were merged and shown in Figure 4. Notably, heterogeneous nuclear ribonucleoproteins (hnRNPs) were the major group of molecules within this network. Many hnRNPs such as A1, C,

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DISCUSSION In the present study, we have identified 266 differentially expressed proteins with high confidence from the microsomal fraction of pooled clinical specimens of anaplastic astrocytoma, a high-grade malignant glioma (WHO Gr III). Selected proteins have been verified by IHC on tissue sections as an alternative assay. Some distinct identification includes proteins such as SPARC, GFAP, CHI3L1, PHB, EGFR, and ANXA2 F



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Table 1. Differentially Expressed Proteins with Signal Sequence or Transmembrane Domains (TMD) and Their Detectability in Normal Cerebrospinal Fluid (CSF) or Plasmaa

a

gene symbol

protein

peptides

fold change

signal/TM

CSF

plasma

ITIH2 CD14 F2 HP APOH ANXA5 ALB SPARC ORM2 ORM1 EGFR A1BG APOA1 ITIH1 SERPINA1 CFB HPX APOC1 APOB CP PPIB CHI3L1 TF A2M LGALS3BP GSN APOE PLG FN1 OMG RNF170 PCDH1 CRYM CPE CADM3 SCG2 ATP1A3 PAM LY6H IGSF8 DPP6 PCSK1N CD200 NPTX1 PTPRN ICAM5

Interalpha globulin inhibitor H2 polypeptide CD14 antigen precursor Prothrombin preproprotein Haptoglobin isoform 1 preproprotein Apolipoprotein H precursor Annexin A5 Albumin preproprotein SPARC precursor Orosomucoid 2 precursor Orosomucoid 1 precursor Epidermal growth factor receptor isoform a precursor Alpha 1B-glycoprotein precursor Apolipoprotein A-I preproprotein Interalpha (globulin) inhibitor H1 isoform a Serine proteinase inhibitor, clade A, member 1 precursor Complement factor B preproprotein Hemopexin precursor Apolipoprotein C−I precursor Apolipoprotein B precursor Ceruloplasmin precursor Peptidylprolyl isomerase B precursor Chitinase 3-like 1 precursor Transferrin precursor Alpha-2-macroglobulin precursor Galectin-3-binding protein Gelsolin isoform b Apolipoprotein E precursor Plasminogen isoform 1 precursor Fibronectin 1 isoform 6 preproprotein Oligodendrocyte-myelin glycoprotein precursor Ring finger protein 170 isoform c Protocadherin 1 isoform 1 precursor Mu-Crystallin homologue isoform 1 Carboxypeptidase E preproprotein Cell adhesion molecule 3 isoform 2 Secretogranin II precursor Sodium/potassium-transporting atpase subunit alpha-3 Peptidylglycine alpha-amidating monooxygenase isoform c preproprotein Lymphocyte antigen 6H isoform a Immunoglobulin superfamily, member 8 Dipeptidyl aminopeptidase-like protein 6 isoform 3 Proprotein convertase subtilisin/kexin type 1 inhibitor precursor CD200 antigen isoform a precursor Neuronal pentraxin I precursor Protein tyrosine phosphatase, receptor type, N precursor Intercellular adhesion molecule 5 precursor

2 3 2 10 4 10 41 5 3 3 7 5 10 2 11 2 6 3 7 6 7 2 23 22 4 10 7 2 4 4 16 2 4 9 5 7 19 2 3 7 8 5 3 3 3 6

4.62 3.76 3.42 3.32 3.08 3.05 2.99 2.76 2.70 2.61 2.60 2.54 2.53 2.48 2.47 2.40 2.29 2.29 2.25 2.25 2.23 2.23 2.23 2.13 2.12 2.04 2.04 2.03 2.01 0.50 0.50 0.50 0.49 0.47 0.46 0.45 0.45 0.44 0.44 0.43 0.42 0.39 0.38 0.35 0.35 0.28

SP SP SP SP SP SP SP SP SP SP TM, SP SP SP SP SP SP SP SP SP SP SP SP SP SP SP SP SP SP SP SP TM, SP TM, SP

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + -

SP TM, SP TM TM, SP TM, TM SP TM, SP TM, TM,

SP

SP SP

SP SP SP

The protein list was extracted from Supplementary Table S7 in the Supporting Information after comparison with data from refs 16 and 17.

that were reported in various transcriptomic or proteomic studies of these tumors. Five differentially expressed apolipoproteins, APOH, APOA1, APOC1, APOB, and APOE1, involved in lipid transport were also identified. Among them, APOE1 has been extensively studied and implicated in the context of cancers of the prostate gland, large intestine, and breast. Intense immunostaining of Apolipoprotein E1 was also observed in the necrotic areas of GBM.18 In ovarian tumor cells, APOE1 knockdown resulted in cell cycle arrest and apoptosis.19 It is possible APOE1 and lipid trafficking may have an important role in tumor growth. Many

others are novel identifications in the context of these tumors, and together they represent major hallmarks of cancer. Proteins such as PRCP, HDGF, HMGB1, and PHB are involved in tumor growth;20−23 proteins such as MYOF, GSN, and MARCKS in metastasis24−26 and NCL and NAMPT are implicated in angiogenesis.27,28 By applying the IntOGen software tool, we were able to predict additional proteins with potential oncogenic and tumor suppressor functions (Supplementary Table S4 in the Supporting Information). The results are thus consistent with the previously published G



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Table 2. Interacting partners of hnRNPs That Are Differentially Expressed in Anaplastic Astrocytomasa

a

hnRNPs

interacting partners of hnRNPs

fold change

HPRD/(ref 40)

hnRNP D, K, U hnRNP K hnRNP K hnRNP A1, A2B1, C, K, U hnRNP K, U hnRNPA1, A2B1, A3, AB, C, D, K hnRNP K hnRNP K hnRNP AB, D, K, U hnRNPA1, A2B1, A3, AB, C, D, K, U hnRNPA1, A2B1, A3, C, K, U hnRNP K hnRNP K hnRNP K hnRNP K hnRNP K hnRNP K hnRNP K hnRNPA1, A2B1, A3, AB, C, D, K, U hnRNP K hnRNPA1 hnRNP K

Heterogeneous nuclear ribonucleoprotein A/B isoform b Glial fibrillary acidic protein isoform 1 Annexin A2 isoform 2 Heterogeneous nuclear ribonucleoprotein A3 Elongation factor 1-alpha 1 Heterogeneous nuclear ribonucleoprotein U isoform b High mobility group protein B1 Ribosomal protein P1 isoform 1 Heterogeneous nuclear ribonucleoprotein D0 isoform d Nucleolin Nucleophosmin isoform 2 Ribosomal protein L28 isoform 5 Ribosomal protein l23a 60S acidic ribosomal protein P2 Probable ATP-dependent RNA helicase DDX17 isoform 1 40S ribosomal protein S2 Ribosomal protein S5 Ribosomal protein S19 Heterogeneous nuclear ribonucleoprotein K isoform b Ribosomal protein S20 isoform 2 Ribosomal protein L21 Ribosomal protein L23

4.33 3.35 2.77 2.74 2.57 2.42 2.39 2.31 2.31 2.31 2.30 2.27 2.27 2.25 2.18 2.17 2.16 2.15 2.10 2.10 2.00 2.00

HPRD ref 40 ref 40 HPRD ref 40 HPRD HPRD ref 40 HPRD HPRD HPRD ref 40 ref 40 ref 40 ref 40 ref 40 ref 40 ref 40 HPRD ref 40 HPRD ref 40

The group of interacting partners was derived from the HPRD database10 (http://www.hprd.org) and ref 40.

findings with gliomas or other cancers as well as offer new findings. An intriguing but distinct observation in our analysis has been the changes in a number of hnRNPs. hnRNPs generally are localized in the nucleus or cytoplasm of the cell, interact with different classes of proteins or mRNAs to form complexes, and regulate post transcriptional events such as splicing, stability, or translation of mRNA in the gene expression cascade. Several specific hnRNPs have been implicated in cancer. hnRNP K and hnRNP C localized in the cytoplasm during different stages of cell cycle were shown to bind to cmyc mRNA increasing its translation, a possible mechanism by which overexpression of hnRNP K contributes to multiple myeloma.29,30 Post translational SUMO modification of hnRNP K protein is also known to play a crucial role in p53 transcriptional coactivation associated with UV mediated DNA damage.31,32 In lung tumor tissues, the elevated expression of hnRNP A1 changes the splicing of target CD44 pre-mRNA involved in tumor metastasis.33 In transgenic mice, overexpression of hnRNP D was reported to increase mRNA levels of c-myc, c-fos, and c-jun through a mRNA-stabilizing effect, leading to tumor development.34 All these studies not only demonstrate the importance of splicing and other post transcription events in tumorigenesis but also reveal the mechanisms of how hnRNPs may be involved in these processes underlying cell proliferation. Although hnRNPs are largely nucleo-cytoplasmic proteins, their localization on membranes and membrane-associated functions has been documented at least for some hnRNPs and it would not be surprising if more would fall in this list. For example, Foster et al. reported five hnRNPs (hnRNP C1/C2, G, K, Q, and U) in the membrane proteome and discussed their role in osteoblast differentiation.35 Earlier these investigators also demonstrated the localization of hnRNP K and E1 on the cell surface and their role in cell adhesion.36 In another study, a number of hnRNPs (A1, A3, A2/B1, B1, and

C1) have been reported to be plasma membrane-localized in tumor cell lines (CCRF-CEM, MV3, and MCF7).37 In another study, by confocal microscopy, cell-surface localization of hnRNP M4 (also called CEA receptor or CEAR) was shown in HT29 colon cancer cells.38 hnRNPs perform functions through their interactions with other hnRNP members, other proteins, or binding to mRNAs. Denisenko et al. reported direct interaction between transcriptional repressor Zik1 and hnRNP K by employing a yeast two hybrid system.39 Mikula et al. reported the localization of hnRNP K in nucleus, cytoplasm, mitochondria, and in the vicinity of the plasma membrane using electron microscopy. They identified nearly 102 proteins interacting with hnRNP K by employing affinity purification and mass spectrometry.40 Many of these 102 proteins belong to the class of membrane proteins. In the present study, we observed an altered expression of several hnRNP and their interacting partners based on the HPRD database and Mikula study.10,40 A total of 85 hnRNP interacting partners were identified of which 22 proteins showed 2-fold change in expression, with others being in the lower range (Table 2). Some of the important proteins include Annexin A2 (ANXA2), Glial fibrillary acidic protein (GFAP), Eukaryotic elongation factor 1a1 (EEF1a1), High mobility group box 1 (HMGB1), nucleolin, and other hnRNP family proteins. ANXA2 is a known candidate cancer marker, and its increased expression is confirmed in high grade glioma tumors. Its role in angiogenesis during tumor progression has been recently reported.41 Increased expression of GFAP, an intermediate filament protein, is reported in grade III glioma tumors in our earlier studies.5 Dynamic interactions between GFAP and many cytoplasmic proteins may be important in maintenance of the differentiated state of the cells. HMGB1 is a multifunctional protein also implicated in tumor growth and metastasis.22 Recently, its role as an autocrine stimulus in the growth and migration of the GBM cell line is reported.42 Nucleolin is a multifunctional protein found to be involved in H



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RNA regulatory mechanisms such as transcription, ribosome assembly, mRNA stability and translation, and microRNA processing. The role of nucleolin is implicated in cancer.43 All these observations strongly suggest the importance/significance of deregulation of hnRNPs and their interactors in the tumor context. Gene expression changes reported in gliomas include genes coding for major housekeeping proteins as well as regulatory proteins. hnRNPs are known regulatory proteins, and their altered expression was observed even in other grades of gliomas. We observed significant up regulation of hnRNP A/B in GBM9 or that of hnRNP A/B, A1, A3, C, D, L, and U in diffused astrocytoma (WHO grade II; unpublished). Interestingly, the number of hnRNPs and their interactors showing differential expression is higher in grade III gliomas. Whether the increased levels of proteins observed with subcellular preparations represent their overexpression in whole tissue may invite some discussion. However, in the present study, the IHC result of at least hnRNP K (and even other non hnRNP proteins selected for IHC) does support its overall overexpression in tissue. In addition, mRNA level expression studies have reported overexpression of all the hnRNPs listed by us in grade III glioma tumors (www.oncomine.org). On the other hand, if the observations are viewed more in relevance to membrane association, they may suggest the possibility of additional yet unclear functions for hnRNPs. Multifunctionality of proteins is an interesting aspect. In a recent analysis, many new proteins including even enzymes of intermediary metabolism have been reported to have a RNA binding feature or are shown to be localized in the nucleus implying their yet unknown functions.44,45 Regardless of the functional mechanism, global deregulation of hnRNP protein members and their interactors deserves attention and further investigation. Targeted investigations of the specific hnRNPs in individual patients and in tumor-derived cell lines will provide further important insights to understand hnRNP mediated processes and to explore their clinical implications.

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Present Address ⊗

R.S.: Institute of Bioinformatics, International Technology Park, Bangalore-560066, India. Phone: +91 9885090963. Email: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The work reported here was carried out under the Network Project IAP 001 with financial support from the Council of Scientific and Industrial Research, Govt. of India (CSIR) at the Centre for Cellular and Molecular Biology (CCMB), Hyderabad. M.K.G. was a Senior Research Fellow under this project. R.V.P. was a recipient of Senior Research Fellowship of the Department of Biotechnolgy, Govt. of India (DBT). P.G. was a Research Associate under Network Project NWP 004 of CSIR, Govt. of India. H.C.H. is a Wellcome Trust/DBT India Alliance Early Career Fellow. The mass spectrometric analysis was carried out at the Institute of Bioinformatics (IOB), Bangalore. The facility was established under support from the DBT for a collaborative program between IOB and the National Institute of Mental Health and Neurosciences, Bangalore. Rakesh Sharma is a Research Associate under this program. We gratefully acknowledge Dr. G. R. Chandak from CCMB for support and coordination of IAP 001 during the later years of the project. We thank T. Avinash Raj from CCMB and P. Madhavan from NIMS, Hyderabad, for technical support in IHC studies. SRISTEK Hyderabad was involved in specimen collections, coordination, and clinical documentation. We thank Shyam Kalakoti and Saurabh Gupta from Strand Life Sciences for their help in programming for data analysis.

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ASSOCIATED CONTENT

S Supporting Information *

Tables of representative differentially expressed proteins selected for immunohistochemistry and antibody details; differentially expressed proteins from anaplastic astrocytomas identified in the study; immunohistochemistry data for six differentially expressed proteins; partial list of proteins (major) with oncogenic/tumor suppressor properties predicted by the IntOGen tool; differentially expressed proteins associated with major networks, canonical pathways, and molecular and cellular processes assessed by the Ingenuity Pathway Analysis (IPA) tool; list of hnRNPs identified in the study with single peptides or with lower than a 2-fold change in expression; list of differentially expressed proteins with signal sequences, transmembrane (TM) domains and those potentially detectable in CSF and/or plasma; and standard box plot of the peptide ratios for the highlighted protein group, hnRNPs. This material is available free of charge via the Internet at http://pubs.acs.org.

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REFERENCES

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Corresponding Author

*Address: Ravi Sirdeshmukh, Centre for Cellular and Molecular Biology (CCMB), Uppal Road, HyderabadI



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Heterogeneous Nuclear Ribonucleoproteins and Their Interactors Are

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