supporting information · 2013-12-24 · supporting information mathew et al....
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Supporting InformationMathew et al. 10.1073/pnas.1314341111SI Material and MethodsCell Culture Reagents and Treatments.Glioblastoma (GBM) “stem-like” cells (GSCs) were maintained in neurobasal medium sup-plemented with B27 1:50 (Invitrogen), 20 ng/mL EGF (Sigma),and 20 ng/mL basic fibroblast growth factor, as previously de-scribed (1). U87MG, U373, and T98G cells (American TypeCulture Collection) were cultured in DMEM containing 10%(vol/vol) FBS and antibiotics. For the intracranial xenograft tu-mor studies, temozolomide (TMZ) (Tocris Bioscience) was in-jected i.p. into mice at 10 mg/kg body weight continuously for 3d. To combine serum starvation with hypoxia, cells were exposedto hypoxia (0.5% O2) using a Ruskin In Vivo 400 work station, inserum-free medium. The EGF receptor (EGFR) inhibitor (AG1478;Tocris Bioscience) and receptor tyrosine kinase (RTK) inhibitor(Sunitinib malate; Tocris Bioscience) were used at a final con-centration of 10 μM for 24 h. The JNK inhibitor (JNKi; SP 600125,Tocris Bioscience) was used at a final concentration of 25 μM for24 h. EGFRvIII plasmid was a gift from Matthew Lazzara (Uni-versity of Pennsylvania, Philadelphia).
In Vivo Xenograft Tumor Assays. All experiments in mice wereapproved by the University of Pennsylvania Institutional AnimalCare andUse Committee and were performed in accordance withNational Institutes of Health guidelines. Intracranial xenografttumor assays were performed in Nu/Nu mice, as described (2).Briefly, GSC T3691 tumor spheres (50,000 cells; T3691-SCR orT3691-218) in a total volume of 5 μL were implanted into theright frontal lobes of nude mice. The animals were killed on day25 after implantation. Similarly, 500,000 U87-SCR or U87-218cells were used for the parallel intracranial study to analyze theeffect of increased microRNA-218 (miR-218) expression onsurvival. Mice were screened for neurological symptoms andkilled upon exhibition of detectable signs. For the rescue ex-periments, EGFRvIII was re-expressed in U87-SCR or U87-218cells, and intracranial experiments were performed as describedabove. MedCalc software was used to produce a Kaplan–Meiersurvival curve. Measurements of tumor area were calculatedusing Image J software.
Statistics. Statistical analyses to evaluate the differences betweenthe control and experimental groups were assessed using anunpaired two-tailed Student’s t test for most of the studies, unlessspecified. Quantified data shown represent at least three in-dependent experiments. MedCalc software was used to conductall statistical analyses.
Transient or Stable Expression of miR-218 or jun proto-oncogeneInhibition. For in vitro cell culture studies, cells were trans-fected with negative or mature miR-218 mimics (Dharmacon)with HiPerfect reagent (Invitrogen). Scrambled plasmids (SCR)and plasmids overexpressing miR-218 were created by cloningscrambled or mature miR-218 sequences into pcDNA 6.2-GW/EmGFP-miR plasmid (Invitrogen) according to the manu-facturer’s instructions. U87MG cells were transfected with SCRand plasmids overexpressing miR-218 and were selected withBlasticidin to create a pool of stable SCR or miR-218–over-expressing cells. For GSCs, cells were transduced with lentiviralparticles bearing pCDH-miR-218 plasmids generated in HEK-293T cells. 293T cells were transfected with pCDH-miR-218/SCR(System Biosciences) and viral packaging plasmids, according tothe Fugene reagent protocol (Roche). T3691 and T4302 cells were
transfected with siRNA targeting jun proto-oncogene (c-JUN)(Dharmacon).
TUNEL Staining.Paraffin-embedded sections of mouse brain tumorwere stained for TUNELusing anApopTag Plus Fluorescein In SituApoptosis Detection Kit (Chemicon) according to the manu-facturer’s instructions.
Luciferase Reporter Assay. The 3′ UTR of phospholipase C-γ1(PLCγ1), EGFR, phorphorhositide-B-IDnase, class 2, tar-poly-peptide (P1K3C2A), and v-raf murine sarcoma 3611 viral onco-gene homolog (ARAF) were cloned into the pMIR-REPORTmicroRNA (miRNA) expression reporter vector (ABI). Forty-eight hours after stable miR-218 expression in T98G cells, therespective plasmids were transfected into cells with the Fugene 6transfection reagent (Roche) in 24-well plates. A plasmid ex-pressing Renilla Luciferase was cotransfected and used to nor-malize the firefly Luciferase values expressed from the pMIR-REPORT expression vector. Luciferase assays were performedusing the dual luciferase protocol (Promega) 48 h after trans-fection of the corresponding plasmids containing the 3′ UTRregions. To test the role of specific seed sequences in the 3′ UTRof miR-218 target genes, mutations were introduced into themiR-218–binding seed sequences and were compared with thewild-type sequence. The duplex sequences were cloned intopMIR-REPORT expression vector for further luciferase analysis(Table S2).
Quantitative Real-Time PCR. Total RNA was isolated using themiRNeasy mini kit (Qiagen) and was reverse transcribed intocDNA using the High Capacity RNA-to-cDNA kit (ABI). Toanalyze miR-218 expression, the TaqMan MicroRNA ReverseTranscription Kit (ABI) was used according to the manu-facturer’s instructions. Taqman primers were used to measuretranscript levels, and analyses were performed on the ABI7900HT system (ABI) (Table S2). All target mRNA levels werenormalized to 18s expression levels. Sequences for the 18s SYBRGreen primer set are GAATTCCCAGTAAGTGCGGG for-ward and GGGCAGGGACTTAATCAACG reverse. The quan-titative RT-PCR (qRT-PCR) data reflect average mRNA levelsfrom three independent RNA extractions and reverse transcrip-tion reactions with error bars showing SEM. miR-218 target ex-pression in orthotopic xenograft tumors was analyzed using RNAisolated from 10-μM paraffin sections using the Recover All TotalNucleic Acid Isolation Kit (Ambion).
Western Blot, Immunohistochemistry, and Immunofluorescence.According to the experimental time points, cells were lysed bystandard procedures in lysis buffer containing a protease inhibitormixture. Protein lysates (40 μg) were resolved on SDS/PAGEgels followed by immunoblot detection and visualization with theECL kit (PerkinElmer). Antibodies and concentrations used forimmunoblots were rabbit PIK3C2A (1:100; Abgent) and rabbitPLCγ1, rabbit β-tubulin, rabbit EGFR, and rabbit ARAF (all at1:1,000 dilution; Cell Signaling). For immunohistochemistry(IHC) and immunofluorescence (IF) analysis, mice were killedand were whole-body perfused by PBS and 4% (wt/vol) para-formaldehyde (PFA), followed by fixing in 4% (wt/vol) PFA for24 h at 4 °C. Mouse brain sections with xenograft tumors weredehydrated through an inclining EtOH series into 100% (vol/vol)EtOH, treated with Xylene, and embedded in paraffin (n = 3–5).H&E staining was performed by standard protocols. IHC and IFwere performed on 5-μm sections based on standard procedures.
Mathew et al. www.pnas.org/cgi/content/short/1314341111 1 of 13
Antibodies and the concentrations used for IHC and IF wererabbit PLCγ1 (1:100; Novus Biologicals), rabbit Ki67 (1:100; BDBiosciences), smooth muscle actin (SMA) (1:250; Sigma), rabbitCD31 (1:50; Abcam), cleaved caspase 3 (1:50; Cell Signaling),and rabbit high-mobility group protein B1 (HMGB1) (1:100;Abcam). Brain glioblastoma and normal tissue array (40 cases; 80cores) was purchased from Biomax (GL806). The paraffin-em-bedded tissue array processing for IHC analysis was performed asdescribed earlier. IF analysis was performed on cells grown oncoverslips by fixing the cells with 4% (wt/vol) PFA for 10 min,followed by permeabilizing with 0.1% Triton-X for 10 min. Pri-mary rabbit HMGB1 (1:100; Abcam) and secondary antibodyincubations were performed according to standard protocols.Image analyses and quantifications were performed using a Leica500 microscope (Leica) as well as Image J.
The Cancer Genome Atlas Microarray Data Analysis. Available datafor gene expression, miRNA expression, methylation, and copynumber were downloaded from the Cancer Genome Atlas(TCGA) data portal. All microarray data were analyzed usingPartek software (Partek Inc.). For gene expression, data gener-ated on Affymetrix microarray platform HT_HG-U133A for 385tumor and 10 normal samples were subjected to GC robustmultiarray average (GCRMA) normalization (GCRMA back-ground correction, quantile normalization, log2 transformation,and Median polish probeset summarization). In the case ofmiRNA expression, previously normalized TCGA level 2 datafrom 426 tumor samples and 10 normal samples run on Agilent’smiRNA microarray were used.Sample classification into different subtypes. Samples were classifiedinto proneural, neural, classical, andmesenchymal subtypes basedon a robust 840-gene expression signature developed and de-scribed by Neil Hayes and his group (3). Training and predictionwere carried out using an R implementation of ClaNC software,a nearest centroid-based classifier (4). A training set comprising173 samples and 840 genes was used to predict classes in 385TCGA gene-expression samples exactly as described by Hayeset al. The resulting proportions of classes were similar to those inthe training and to the validation set of 260 samples that theauthors used in their study. Similarly, the clustering classificationof Phillips et al. (5) was performed using the published genesignature.Survival analysis. All available patient survival data includingtreatment response were integrated with miR-218 expression.The predicted GBM subtypes were integrated also. Kaplan–Meier survival analysis was carried out to determine an associ-ation between survival and miR-218 expression in all GBM typesor in different GBM subtypes. An association was consideredsignificant if the P value of association analysis was <0.05.Correlation analysis for identification of miR-218 targets. For TCGAgene expressions, we chose the probe with the maximum varia-tion. For miRNA, level 2 Agilent data were downloaded and usedfor the analysis. From the TCGA database, a standardized geneand miRNA set consisting of GBM patients was collated. Thepatients were ranked according to miR-218 expression levels.
Whole-genome analysis by Comparative Marker Selection (CMS,gene pattern suite, Broad Institute, MIT) revealed the top-down–regulated and inversely correlated genes in patients with highmiR-218 expression. Then this list was compared with predicted miR-218 gene targets using miRWalk. Genes were ranked accordingto both the predictive power of miR-218 binding and averageP value across the four discovery sets (6). For visualization, a gene-expression heatmap was created using dChip software (http://www.biostat.harvard.edu/~cli/dchip_2010_01.exe).Correlation of necrosis with miRNA expression. TCGA Glioblastomalevel 1 expression data were obtained for mRNA expression(http://cancergenome.nih.gov/). Robust multiarray analysis wasperformed in R (R Project, www.r-project.org/). Histopathologyannotation for the percent of necrosis was downloaded from thepublic TCGA data portal. The percent of necrosis was averagedacross the available sections for each patient and matched to thecorresponding TCGA dataset. Then the percent of necrosis wasplotted against the miRNA expression. Significance was calcu-lated using Student’s t test and ANOVA with SAS JMP Pro-10software (SAS Institute Inc.).Correlating miR-218 expression with the hypoxia-inducible factor signatureand miR-218 target genes. To determine the association betweenmiR-218 and expression of the hypoxia-inducible factor (HIF)signature, we used the Gene Set Analysis (GSA) implementation(version 1.03) of Gene Set Enrichment Analysis (GSEA). TheHIF signature was defined by using established HIF-regulatedgenes (7). For GSA, the expression value of miR-218 was used asa quantitative response variable and compared with gene setscomprised of the HIF signature and sets of random genes ofequal size. Restandardization using the entire expression datawas performed, and the maxmean statistic was used. The sig-nificance for the HIF signature enrichment was calculated basedon 1,000 permutations. To determine the association betweenmiR-218 expression and our list of miR-218 target genes, GSAwas repeated using a gene set of the four newly identified miR-218 targets.To create a single value that represents the expression of the
HIF signature (HIF metagene), the average expression of all thegenes in the HIF signature was calculated for each tumor sample(using TCGA GBM data). This HIF metagene then was used asa continuous variable for various comparisons between groups.Similarly, an miR-218 target metagene was generated using theaverage expression of PLCγ1, EGFR, P1K3C2A, and ARAF foreach tumor sample (TCGA data). All analysis was performedusing the R language and environment for statistical computing.Correlation of reverse phase protein array data with miR-218 expression.Reverse phase protein array (RPPA) data were downloaded fromthe TCGA (http://app1.bioinformatics.mdanderson.org/tcpa/_design/basic/index.html). Phospho-proteins that are significantly associ-ated with miR-218 expression were determined by SignificanceAnalysis of Microarray using a median false-discovery rate of 0.05.Only TCGA GBM samples for which RPPA data are availablewere used for the analysis.
1. Kamal MM, et al. (2012) REST regulates oncogenic properties of glioblastoma stemcells. Stem Cells 30(3):405–414.
2. Ikushima H, et al. (2009) Autocrine TGF-beta signaling maintains tumorigenicity ofglioma-initiating cells through Sry-related HMG-box factors. Cell Stem Cell 5(5):504–514.
3. Verhaak RG, et al.; Cancer Genome Atlas Research Network (2010) Integrated genomicanalysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalitiesin PDGFRA, IDH1, EGFR, and NF1. Cancer Cell 17(1):98–110.
4. Dabney AR (2006) ClaNC: Point-and-click software for classifying microarrays to nearestcentroids. Bioinformatics 22(1):122–123.
5. Phillips HS, et al. (2006) Molecular subclasses of high-grade glioma predict prognosis,delineate a pattern of disease progression, and resemble stages in neurogenesis.Cancer Cell 9(3):157–173.
6. Zinn PO, et al. (2012) A novel volume-age-KPS (VAK) glioblastoma classificationidentifies a prognostic cognate microRNA-gene signature. PLoS ONE 7(8):e41522.
7. Koivunen P, et al. (2012) Transformation by the (R)-enantiomer of 2-hydroxyglutaratelinked to EGLN activation. Nature 483(7390):484–488.
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Fig. S1. miR-218 is modestly inhibited by hypoxia in GBM cells. miR-218 expression in GBM cells treated with 21% or 0.5% O2 for 24 h. For all statisticalanalyses, *P < 0.05, **P < 0.005, ***P < 0.0005. Data are presented as mean ± SEM.
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Fig. S2. HIF signature in GBM subtypes. Hierarchical clustering and heatmap illustrating the expression of HIF-regulated genes (HIF signature) in eithermesenchymal (MSN) or proneural (PN) subtypes as denoted by the black hatches below the heatmap. Orange color indicates high expression; blue depicts lowexpression.
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Fig. S4. Effects of miR-218 + TMZ on GBM/GSC tumor growth. (A) Frozen sections of GSC Tum-3691-SCR/218 tumors from mice killed 12 d after trans-plantation revealed the presence of tumor (GFP+ area). (Scale bar: 1 mm.) n = 4. (B) Cleaved caspase 3 staining analyzed in Tum-3691-SCR-TMZ and Tum-3691–218-TMZ tumors. (Scale bar: 100 μm.) n = 4. (C and D) Ki67+ (C) and phospho-H3+ (D) cells in T3691-SCR-TMZ and T3691-218-TMZ tumors. (Scale bars: 20 μm.) n =4. (E) Ki67+ cells in U87-SCR-TMZ and U87-218-TMZ tumors. (Scale bar: 20 μm.) n = 4. (F) Representative images and quantitation of TUNEL+ cells in U87-SCR-TMZ and U87-218-TMZ tumors. (Scale bar: 100 μm.) n = 4. (G) HMGB1 nuclear staining in T3691-SCR and T3691-218 GSC spherical cryosections after treatmentwith TMZ (250 μM) for 96 h. (Scale bar: 2 μm.) n = 3. (H) HMGB1 nuclear staining in U87-SCR and U87-218 cells exposed to TMZ (250 μM) + SFM + 0.5% O2. (Scalebar: 2 μm.) n = 3. (I) Representative image of brain section from the U87-218-TMZ group killed at day 288. n = 4. (Scale bar: 1 mm.) For all statisticalanalyses, *P < 0.05, **P < 0.005, ***P < 0.0005. Data are presented as mean ± SEM. SFM, serum-free medium.
Mathew et al. www.pnas.org/cgi/content/short/1314341111 5 of 13
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Fig. S5. Survival curve based onmiR-218 expression in patients with mesenchymal and proneural GBM. (A) Kaplan–Meier survival curve based on high and lowmiR-218 expression in patients with proneural GBM treated with radiation or chemotherapy (P = 0.2448). (B) Kaplan–Meier survival curve based on miR-218levels in patients with recurrent or progressive proneural GBM based on the clustering methods of Verhaak et al. (3) (P = 0.457) and Phillips et al. (5) (P = 0.824).(C) Kaplan–Meier survival curve based on miR-218 levels in patients with recurrent or progressive mesenchymal GBM (Verhaak et al. clustering, P = 0.0438;Phillips et al. clustering, P = 0.0327).
Mathew et al. www.pnas.org/cgi/content/short/1314341111 6 of 13
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Fig. S6. Regulation of RTK pathway components by miR-218. (A) Schematic diagram depicting miR-218 seed sequences in EGFR, PLCγ1, ARAF, and PIK3C2A 3′UTRs based on TargetScan predictions. T98G GBM cells transfected with pMIR-REPORT with intact or mutated seed sequences were tested for luciferase activityin the presence of stable miR-218 expression. (n = 3) (B) Western blot showing the abundance of PLCγ1, EGFR, ARAF, and PIK3C2A proteins after miR-218mimictransfection in U87MG and U373 cells. β-Tubulin was used as a loading control. (C and D) Analysis of EGFR, PLCγ1, ARAF, and PIK3C2A mRNA isolated fromT3691-SCR and Tum-3691–218 orthotopic brain tumor sections from mice treated or not treated with TMZ (n = 3). (E) Western blot showing the abundance ofphosphorylated v-akt murine thymoma viral oncogene homolog 1 (AKT) (T308) and PRAS40 as well as HIF1α in U87-NS and U87-218 cells exposed to SFM + TMZor SFM + 0.5% O2 + TMZ (250 μM) for 24 h. For all statistical analyses, *P < 0.05, **P < 0.005, ***P < 0.0005. Data are presented as mean ± SEM. SFM, serum-free medium.
Mathew et al. www.pnas.org/cgi/content/short/1314341111 7 of 13
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Fig. S7. Expression of miR-218 targets in GBM. (A) Transcript levels of EGFR, PLCγ1, ARAF, and PIK3C2A analyzed by qRT-PCR in samples from patients withGBM (red; n = 20) and normal human brain tissue (green; n = 5). (B) Expression of EGFR, PLCγ1, ARAF, and PIK3C2A in patients with GBM compared withnormal brain tissues (TCGA). (C) IHC staining and quantification of GBM and normal brain tissue microarrays (n = 40 each) showing EGFR, PLCγ1, ARAF, andPIK3C2A expression in patients with GBM. (Scale bar: 20 μm.)
Mathew et al. www.pnas.org/cgi/content/short/1314341111 8 of 13
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Fig. S8. Effects of miR-218 on RTK signaling and HIF activity in GBM. (A and B) Expression of HIF target genes (A) and HIF-1α and HIF-2α transcript levels (B) inT4302 GSCs after ectopic miR-218 expression. (C) HIF target gene expression upon either specific EGFR inhibition (EGFRi) or general RTK inhibition (RTKi). (D)Phosphorylation of AKT (S473) in T3691 tumor spheres treated with EGFRi or RTKi demonstrating the efficiency of these inhibitors. (E) Western blot showingc-JUN levels after siRNA-mediated inhibition in T3691 and T4302 GSCs. (F) HIFα transcripts and c-JUN (protein) levels after suppression of c-JUN using a secondset of siRNA in T3691 GSCs. (G) HIF-1α and HIF-2α mRNA levels upon JNK inhibition (JNKi) in T4302 GSCs. (H) Western blot showing p-JNK levels after JNKinhibition in T3691 and T4302 GSCs. (I) HIF-1α and HIF-2α mRNA levels analyzed after 24-h exposure to 21% O2, 0.5% O2, or 0.5% O2 + JNK inhibition (JNKi) inT3691 GSCs. (J) Low-magnification images of CD31 and SMA immunofluorescence in T3691-SCR and T3691-218 orthotopic brain tumor sections (correspondingto Fig. 4G). (Scale bar: 20 μm.) (K) Quantification of CD31+ areas in T3691-SCR-TMZ and T3691-218-TMZ sections. n = 4. For all statistical analyses, *P < 0.05,**P < 0.005, ***P < 0.0005. Data are presented as mean ± SEM.
Mathew et al. www.pnas.org/cgi/content/short/1314341111 9 of 13
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Fig. S9. Mesenchymal GBM express higher levels of HIF-regulated genes than do proneural GBM. GSEA demonstrating a negative correlation between an HIFsignature and miR-218 expression for mesenchymal (A) and proneural (B) tumors. The heatmap shows the expression of the HIF signature genes (columns) foreach patient (rows) with orange indicating high expression, and blue indicating low expression. For each patient, the corresponding expression level of miR-218 is indicated in the dot plot to the right of the heatmap. The gene score for each gene is displayed in the plot above the heatmap along with the overallscore and P value. Negative gene scores represent inverse correlation with miR-218.
Mathew et al. www.pnas.org/cgi/content/short/1314341111 10 of 13
Table S1. miRNAs that are associated with necrosis (group 1), that are differentially expressed in normal vs. GBM samples (group 2)(TCGA), and that are found in both groups 1 and 2 (group 3)
Group 1: top 100 miRNAsassociated with necrosis Inverse correlation
Group 2:target ID
P-value, tumorvs. normal
Description of fold-change,tumor vs. normal
Group 3: miRNAsfound in bothgroups 1 and 2
hsa-miR-331 −0.2679327 hsa-miR-218 0 Tumor down vs. normal Truehsa-miR-128b −0.2459932 hsa-miR-326 2.80E-45 Tumor down vs. normal Falsehsa-miR-30e-3p −0.2427776 hsa-miR-539 7.57E-39 Tumor down vs. normal Falsehsa-miR-363 −0.2426327 hsa-miR-485–5p 3.18E-38 Tumor down vs. normal Falsehsa-miR-488 −0.2401388 hsa-miR-137 1.02E-37 Tumor down vs. normal Truehsa-miR-33 −0.2379219 hsa-miR-137 9.02E-36 Tumor down vs. normal Truehsa-miR-95 −0.2350514 hsa-miR-218 4.28E-35 Tumor down vs. normal Truehsa-miR-9 −0.2342017 hsa-miR-433 2.28E-34 Tumor down vs. normal Falsehsa-miR-128a −0.2289258 hsa-miR-485–5p 6.43E-31 Tumor down vs. normal Falsehsa-miR-30c −0.2270367 hsa-miR-769–5p 4.42E-30 Tumor down vs. normal Truehsa-miR-98 −0.2185372 hsa-miR-433 6.27E-30 Tumor down vs. normal Falsehsa-miR-30a-3p −0.2170909 hsa-miR-330–3p 6.68E-29 Tumor down vs. normal Falsehsa-miR-181a* −0.2140329 hsa-miR-323–3p 1.60E-24 Tumor down vs. normal Falsehsa-let-7c −0.2100953 hsa-miR-432 2.38E-24 Tumor down vs. normal Falsehsa-miR-182* −0.1994175 hsa-miR-329 1.35E-23 Tumor down vs. normal Falsehsa-miR-181d −0.1974738 hsa-miR-769–5p 3.00E-23 Tumor down vs. normal Truehsa-miR-340 −0.1963264 hsa-miR-432 6.13E-23 Tumor down vs. normal Falsehsa-miR-99a −0.1949743 hsa-miR-21 2.05E-22 Tumor up vs. normal Truehsa-miR-598 −0.1936376 hsa-miR-132 9.85E-22 Tumor down vs. normal Truehsa-miR-9* −0.1927477 hsa-miR-448 2.71E-21 Tumor down vs. normal Falsehsa-miR-20b −0.1866554 hsa-miR-410 4.66E-21 Tumor down vs. normal Falsehsa-miR-181c −0.1857236 hsa-miR-329 2.33E-20 Tumor down vs. normal Falsehsa-let-7f −0.1800647 hsa-miR-383 2.45E-20 Tumor down vs. normal Falsehsa-miR-769–5p −0.1788129 hsa-miR-381 1.71E-19 Tumor down vs. normal Falsehsa-miR-125a −0.1774776 hsa-miR-21 2.56E-19 Tumor up vs. normal Truehsa-miR-652 −0.1746905 hsa-miR-410 2.96E-19 Tumor down vs. normal Falsehsa-miR-342 −0.1738542 hsa-miR-383 3.24E-19 Tumor down vs. normal Falsehsa-miR-124a −0.1703789 hsa-miR-411 2.45E-18 Tumor down vs. normal Falsehsa-miR-218 −0.1650887 hsa-miR-132 2.69E-18 Tumor down vs. normal Truehsa-miR-92b −0.1630909 hsa-miR-203 2.84E-18 Tumor down vs. normal Falsehsa-miR-132 −0.1621784 hsa-miR-326 4.40E-18 Tumor down vs. normal Falsehsa-miR-129 −0.1592884 hsa-miR-25 9.77E-18 Tumor up vs. normal Falsehsa-miR-324–5p −0.1585699 hsa-miR-411 9.92E-17 Tumor down vs. normal Falsehsa-miR-502 −0.1526264 hsa-miR-203 2.98E-16 Tumor down vs. normal Falsehsa-let-7a −0.1509339 hsa-miR-29b 1.97E-15 Tumor down vs. normal Falsehsa-miR-140 −0.1503437 hsa-miR-758 2.21E-15 Tumor down vs. normal Falsehsa-miR-767–5p −0.1474191 hsa-miR-15b 1.10E-14 Tumor up vs. normal Falsehsa-miR-137 −0.1468996 hsa-miR-383 1.76E-14 Tumor down vs. normal Falsehsa-miR-519e −0.1465107 hsa-miR-136 2.29E-14 Tumor down vs. normal Falsehsa-miR-10b −0.1459465 hsa-miR-769–3p 4.29E-14 Tumor down vs. normal Falsehsa-miR-183 −0.145705 hsa-miR-25 4.36E-14 Tumor up vs. normal Falsehsa-miR-18b −0.1436243 hsa-miR-758 1.30E-13 Tumor down vs. normal Falsehsa-miR-542–3p −0.1430719 hsa-miR-93 2.99E-13 Tumor up vs. normal Falsehsa-miR-30e-5p −0.1429252 hsa-miR-27a 3.37E-13 Tumor up vs. normal Falsehsa-miR-99b −0.1424197 hsa-miR-15b 3.41E-13 Tumor up vs. normal Falsehsa-miR-484 −0.1416739 hsa-miR-16 4.95E-13 Tumor up vs. normal Falsehsa-miR-421 −0.1415461 hsa-miR-23a 5.30E-13 Tumor up vs. normal Falsehsa-miR-7 −0.1390475 hsa-miR-95 5.88E-13 Tumor down vs. normal Truehsa-let-7e −0.1378698 hsa-miR-448 1.72E-12 Tumor down vs. normal Falsehsa-miR-454–3p −0.137412 hsa-miR-106b 7.76E-12 Tumor up vs. normal Falsekshv-miR-K12-3 0.1987028 hsa-miR-107 1.78E-11 Tumor down vs. normal Falsehsa-miR-134 0.2011835 hsa-miR-106b 2.90E-11 Tumor up vs. normal Falsehsa-miR-513 0.2013618 hsa-miR-496 6.19E-11 Tumor down vs. normal Falsehsa-miR-567 0.2034811 hsa-miR-136 8.70E-11 Tumor down vs. normal Falsehsa-miR-629 0.2036903 hsa-miR-758 1.73E-10 Tumor down vs. normal Falsehsa-miR-663 0.2036946 hsa-miR-210 2.53E-10 Tumor up vs. normal Truehsa-miR-302c* 0.2054037 hsa-miR-154* 6.55E-10 Tumor down vs. normal Falseebv-miR-BART8-3p 0.2067257 hsa-miR-210 6.99E-10 Tumor up vs. normal Truehsa-miR-492 0.2073576 hsa-miR-377 1.96E-09 Tumor down vs. normal Falseebv-miR-BART7 0.2075306 hsa-miR-154* 5.29E-09 Tumor down vs. normal False
Mathew et al. www.pnas.org/cgi/content/short/1314341111 11 of 13
Table S1. Cont.
Group 1: top 100 miRNAsassociated with necrosis Inverse correlation
Group 2:target ID
P-value, tumorvs. normal
Description of fold-change,tumor vs. normal
Group 3: miRNAsfound in bothgroups 1 and 2
hsa-miR-604 0.2104053 hsa-miR-656 6.24E-09 Tumor down vs. normal Falsehsa-miR-572 0.2109427 hsa-miR-299–5p 6.29E-09 Tumor down vs. normal Falsehsa-miR-187 0.2115148 hsa-miR-100 7.06E-09 Tumor up vs. normal Falsehsa-miR-765 0.2123519 hsa-miR-299–5p 1.03E-08 Tumor down vs. normal Falsehsa-miR-516–3p 0.2167647 hsa-miR-598 1.11E-08 Tumor down vs. normal Truehsa-miR-608 0.2207522 hsa-miR-130b 1.48E-08 Tumor up vs. normal Falsehcmv-miR-US25-1 0.2215838 hsa-miR-29b 2.57E-08 Tumor down vs. normal Falsehsa-miR-639 0.2244275 hsa-miR-93 3.50E-08 Tumor up vs. normal Falsehsa-miR-671 0.2260097 hsa-miR-758 4.30E-08 Tumor down vs. normal Falsehsa-miR-617 0.2272516 hsa-miR-485–3p 4.41E-08 Tumor down vs. normal Falsehsa-miR-21 0.2281538 hsa-miR-127–3p 6.89E-08 Tumor down vs. normal Falsehsa-miR-648 0.2291891 hsa-miR-324–5p 7.27E-08 Tumor down vs. normal Truehsa-miR-422a 0.229192 hsa-miR-130a 2.02E-07 Tumor up vs. normal Falsehsa-miR-622 0.2307605 hsa-miR-133b 2.06E-07 Tumor down vs. normal Falseebv-miR-BART13 0.2318694 hsa-miR-130b 2.21E-07 Tumor up vs. normal Falsehsa-miR-223 0.2331784 hsa-miR-377 2.39E-07 Tumor down vs. normal Falsehsa-miR-596 0.2361924 hsa-miR-598 5.11E-07 Tumor down vs. normal Truehsa-miR-498 0.2376258 hsa-miR-20a 5.55E-07 Tumor up vs. normal Falsehsa-miR-188 0.2377578 hsa-miR-107 7.16E-07 Tumor down vs. normal Falsehsa-miR-583 0.240983 hsa-miR-584 9.82E-07 Tumor down vs. normal Truehsv1-miR-H1 0.2409892 hsa-miR-103 1.19E-06 Tumor down vs. normal Falsehsa-miR-584 0.2429275 hsa-miR-20a 1.32E-06 Tumor up vs. normal Falsehsa-miR-638 0.2487752 hsa-miR-324–5p 2.33E-06 Tumor down vs. normal Truekshv-miR-K12-10b 0.2527935 hsa-miR-154 3.31E-06 Tumor down vs. normal Falsehsa-miR-627 0.2529969 hsa-miR-326 3.40E-06 Tumor down vs. normal Falsekshv-miR-K12-10a 0.2536473 hsa-miR-100 3.75E-06 Tumor up vs. normal Falsehsa-miR-575 0.2558419 hsa-miR-19b 6.25E-06 Tumor up vs. normal Falsehcmv-miR-US4 0.2587972 hsa-miR-19b 6.49E-06 Tumor up vs. normal Falsehcmv-miR-UL70-3p 0.2640936 hsa-miR-20b 1.28E-05 Tumor up vs. normal Truehsa-miR-155 0.2647244 hsa-miR-99a 1.73E-05 Tumor up vs. normal Truehsa-miR-210 0.2660878 hsa-miR-424 1.85E-05 Tumor up vs. normal Falsehsa-miR-601 0.267365 hsa-miR-500a* 2.23E-05 Tumor up vs. normal Falsehsa-miR-557 0.2675721 hsa-miR-130a 2.94E-05 Tumor up vs. normal Falsehsa-miR-198 0.2871823 hsa-miR-24 3.28E-05 Tumor up vs. normal Falsehsa-miR-520e 0.2954803 hsa-miR-27b 5.08E-05 Tumor down vs. normal Falsehsa-miR-659 0.2967117 hsa-miR-629* 5.90E-05 Tumor up vs. normal Truehsa-miR-523 0.2973074 hsa-miR-154 7.35E-05 Tumor down vs. normal Falsehsa-miR-560 0.3111432 hsa-miR-592 8.48E-05 Tumor down vs. normal Falsehsa-miR-630 0.3197729 hsa-miR-10a 8.59E-05 Tumor up vs. normal Falsehsa-miR-520b 0.3300342 hsa-miR-23b 9.00E-05 Tumor down vs. normal False
True indicates miRNAs found in both group 1 and group 2.
Mathew et al. www.pnas.org/cgi/content/short/1314341111 12 of 13
Table S2. Sequences of wild-type or mutated seed regions in the 3′ UTR of PLCγ1, EGFR, ARAF,and P1K3C2A
PLCγ1 SEED1 F:
GGCACTAGTAGGCAAAAACTGTACTGTGTTTCGCATTAAGCACACACATCTGGCCCTGACTTCTGGAGAAAGCTTGGCPLCγ1 SEED1 R:
GCCAAGCTTTCTCCAGAAGTCAGGGCCAGATGTGTGTGCTTAATGCGAAACACAGTACAGTTTTTGCCTACTAGTGCC
PLCγ1 SEED1 MUT F:
GGCACTAGTAGGCAAAAACTGTACTGTGTTTCGCATTGGTTGTGCACATCTGGCCCTGACTTCTGGAGAAAGCTTGGCPLCγ1 SEED1 MUT R:
GCCAAGCTTTCTCCAGAAGTCAGGGCCAGATGTGCACAACCAATGCGAAACACAGTACAGTTTTTGCCTACTAGTGCC
EGFR SL SEED1 F:
GGCACTAGTGACTGACCTCTTCCTCCTCGCTGCCAGATGATTGTTCAAAGCACAGAATTTGTCAGAAACAAGCTTGGCEGFR SL SEED1 R:
GCCAAGCTTGTTTCTGACAAATTCTGTGCTTTGAACAATCATCTGGCAGCGAGGAGGAAGAGGTCAGTCACTAGTGCC
EGFR SL SEED1 F: MUT
GGCACTAGTGACTGACCTCTTCCTCCTCGCTGCCAGATGATTGTTCAGGAAGAGGAATTTGTCAGAAACAAGCTTGGCEGFR SL SEED1 R: MUT
GCCAAGCTTGTTTCTGACAAATTCCTCTTCCTGAACAATCATCTGGCAGCGAGGAGGAAGAGGTCAGTCACTAGTGCC
PIK3C2A SEED1 F:
GGCACTAGTTGCTATTCATGGAGCTGAAAAACAAAGCACAAATAATAGATAGCTAAGTTAAGAACTACTAAGCTTGGCPIK3C2A SEED1 R:
GCCAAGCTTAGTAGTTCTTAACTTAGCTATCTATTATTTGTGCTTTGTTTTTCAGCTCCATGAATAGCAACTAGTGCC
PIK3C2A SEED1 F: MUT
GGCACTAGTTGCTATTCATGGAGCTGAAAAACAGGATGTCAATAATAGATAGCTAAGTTAAGAACTACTAAGCTTGGCPIK3C2A SEED1 R: MUT
GCCAAGCTTAGTAGTTCTTAACTTAGCTATCTATTATTGACATCCTGTTTTTCAGCTCCATGAATAGCAACTAGTGCC
ARAF SEED1 F:
GCACTAGTCCATTCAAGGACTCCTCTCTTTCTTCACCAAGAAGCACAGAATTCTGCTGGGCCTTTGCTAAGCTTGGCARAF SEED1 R:
GCCAAGCTTAGCAAAGGCCCAGCAGAATTCTGTGCTTCTTGGTGAAGAAAGAGAGGAGTCCTTGAATGGACTAGTGCC
ARAF SEED1 F: MUT
GGCACTAGTCCATTCAAGGACTCCTCTCTTTCTTCACCAAGGGATGTCGAATTCTGCTGGGCCTTTGCTAAGCTTGGCARAF SEED1 R: MUT
GCCAAGCTTAGCAAAGGCCCAGCAGAATTCGACATCCCTTGGTGAAGAAAGAGAGGAGTCCTTGAATGGACTAGTGCC
Mutated seed regions are shown in bold.
Mathew et al. www.pnas.org/cgi/content/short/1314341111 13 of 13