Research Article Global Gene Expression Analyses Support...

Hindawi Publishing CorporationEvidence-Based Complementary and Alternative MedicineVolume 2013 Article ID 471739 13 pageshttpdxdoiorg1011552013471739

Research ArticleIn Vitro Global Gene Expression Analyses Supportthe Ethnopharmacological Use of Achyranthes aspera

Pochi R Subbarayan1 Malancha Sarkar2 Lubov Nathanson34 Nikesh Doshi2

Balakrishna L Lokeshwar5 and Bach Ardalan3

1 Division of Hematology and Oncology Department of Medicine University of Miami Miller School of Medicine1550 NW 10th Avenue Fox 431A (D8-4) Miami FL 33136 USA

2Department of Biology University of Miami Miami FL 33124 USA3Department of Medicine University of Miami Miller School of Medicine Miami FL 33136 USA4 Institute for Neuro Immune Medicine College of Osteopathic Medicine Nova Southeastern University Fort LauderdaleFL 33328 USA

5Department of Urology University of Miami Miller School of Medicine and VA Medical Center Miami FL 33136 USA

Correspondence should be addressed to Pochi R Subbarayan spochimedmiamiedu

Received 6 June 2013 Revised 2 October 2013 Accepted 8 October 2013

Academic Editor Yong-Qing Yang

Copyright copy 2013 Pochi R Subbarayan et al This is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work is properlycited

Achyranthes aspera (family Amaranthaceae) is known for its anticancer properties We have systematically validated the in vitroand in vivo anticancer properties of this plant However we do not know its mode of action Global gene expression analyses mayhelp decipher its mode of action In the absence of identified active molecules we believe this is the best approach to discover themode of action of natural products with known medicinal properties We exposed human pancreatic cancer cell line MiaPaCa-2(CRL-1420) to 34 120583gmL of LE for 24 48 and 72 hours Gene expression analyses were performed using whole human genomemicroarrays (Agilent Technologies USA) In our analyses 82 (5428) genes passed the quality control parameter set at FDR le 001and FC of geplusmn2 LE predominantly affected pathways of immune response metabolism development gene expression regulationcell adhesion cystic fibrosis transmembrane conductance regulation (CFTR) and chemotaxis (MetaCore tool (Thomson ReutersNY)) Disease biomarker enrichment analysis identified LE regulated genes involved in Vasculitismdashinflammation of blood vesselsArthritis and pancreatitis are two of many etiologies for vasculitisThe outcome of disease network analysis supports the medicinaluse of A aspera viz to stop bleeding as a cure for pancreatic cancer as an antiarthritic medication and so forth

1 Introduction

Large sections of the world population depend on medic-inal plants (natural products) for their health care needsThe indigenous population use crude preparations of nat-ural products in the form of decoction paste or as foodsupplement The prevailing belief is that crude mixturescontainmany compounds Several of these compoundsmightbe inactive by themselves but are essential for the effec-tiveness of the ldquoactive moleculerdquo in the crude preparationsIn other words synergism negates the additive effect ofindividual molecules [1] Global gene expression changeseffected by nonstandardized (crude) preparations as used by

communities at large may not be directly attributed solelyto the ldquoactive moleculerdquo Understandably this approach willnot facilitate deciphering the mechanism of action of theactive molecules in a crude preparation However globalgene expression analyses will give a snapshot of the overalleffect of crude extract onmultiple cellular pathways [2] Suchapproachesmay explain the possiblemode of action of herbalpreparations as used in indigenous medicine

Modern scientific standards emphasize thorough under-standing of themolecularmechanismof action of single agentdrugs However this approach is limited to single moleculeswhich have been chemically characterized Even these drugsmodulate the activities of disparate metabolicsignaling

2 Evidence-Based Complementary and Alternative Medicine

pathways [3] These results suggest that a drug with specifictarget can have wide ranging physiological effects

Analytical methods like microarray pathway focusedPCR arrays RNA seq and cGH array give a snapshot of largescale changes at genome level These methodologies generatelarge data sets The development of data mining software hasenabled discovery of molecular markers from the mass ofdata possible Thus the ability to analyze gene expressionchanges at genome level had revolutionized the molecularinvestigations that until now were difficult For exampleunderstanding global gene expression changes that accom-pany certain diseases like cancer has enabled the developmentof personalized medicine Data analysis of microarray resultsalso facilitated deciphering molecular pathways that areaffected by both existing aswell as newly discovered drugs [2]

Achyranthes aspera (Family Amaranthaceae) is a medici-nal plant in Ayurvedic pharmacopoeia It is an annual shrubfound in India Southeast Asia America and Sub-SaharanAfrica It is classified as a weed [5] Traditionally the plantextract is used as a cure for arthritis as blood clotting agentto induce labor (fetal expulsion) and as an abortifacient [6]Earlier we demonstrated that methanol-extract of A asperaleaves (LE) has antiproliferative activity against a variety ofhuman cancer cell lines cultured in vitro Our results alsoshowed pancreatic cancer cells to be the most sensitive toLE These exciting outcomes indicate the presence of activeanticancer molecule(s) in A aspera Unpublished anecdotalobservations suggest that A aspera benefited pancreaticcancer patients Animal studies carried out with A asperaextract confirm LE to be nontoxic to mice Most importantlythese studies have shown that LE inhibited human tumorgrowth in mice [7] In preliminary gene expression studieswe demonstrated LE differentially modulated the expressionof key genes involved in vasculogenesis (VEGFs) metasta-sis (MMPs TIMPS) apoptosis (Caspase) cell proliferation(Akt-1) and so forth [7 8]These preliminary results supportthe idea that LE regulates the function of specific signalingmolecules Except for the above two reports no additionalinformation is available regarding the global molecularchanges caused by LE in human cancer cells Clearly simul-taneous analysis of global gene expression changes effectedby LE would shine light on different pathways affected Suchanalyses would help select key genes that can be used asresponse markers and predict its effect on different illnessesBased on this premise we used Agilent Whole HumanGenome microarrays to examine the global gene expressionchanges effected by LE on cultured human pancreatic cancercell line MIA PaCa-2 (CRL-1420) that were treated with LEfor 24 48 and 72 hours In this paper we summarize theeffect of methanol extract (LE) of dried powdered leaves ofAaspera on global gene expression pattern in human pancreaticcancer cell line MIA PaCa-2 Using MetaCore software wenarrowed down the pathways affected in MIA PaCa-2 cellstreated with LE for three different time points

2 Materials and Methods

We have recently published the details about the col-lection authentication of Achyranthes aspera leaves and

the preparation of whole leaf extract [7 8] Briefly A asperaleaf powder was serially extracted in 100 hexane followedby 100 acetone over night at room temperatureThe acetoneextract was concentrated in a rotary evaporator The residuewas dissolved in 100 methanol and called leaf extract (LE)

21 Cell Lines and Culture Conditions Thehuman pancreaticcancer cell line MIA PaCa-2 (CRL-1420) was purchased fromATCC (USA) andmaintained in our laboratory in RPMI 1640medium supplemented with 10 FBS (Invitrogen USA) at37∘C in a humidified 5 CO

2atmosphere It was seeded in a

six-well plate at an initial density of 5 times 105 in 2mL mediumOvernight cultures were exposed to 34 120583gmL of LE for 2448 and 72 hours respectively Two percentmethanol exposedcells served as a control Control and experimental groupswere set up in duplicate

22 Isolation and Quality Control of Total RNA Total RNAwas prepared from control and LE treated MiaPaCa-2 cellsusing TriReagent (Sigma USA) At the end of the treatmentcells were directly lysed in TriReagent and total RNA isolatedFrom this point the rest of the gene expression relatedprocedures were performed at the microarray and geneexpression Core facility of the University of MiamiThe qual-ity of the extracted RNA was evaluated using BioAnalyzer2100 (Agilent Technologies CA) RNA samples with RNAintegrity number (RIN)ge9 have been used for themicroarrayexperiments [9]

23 cDNA Synthesis and RNA Labeling for Microarray Anal-yses Target RNA was amplified using Amino Allyl MessageAmp kit (Ambion USA) Amplified RNA from the controlgroup was labeled with Cy-3 and the test group with Cy-5dye (Amersham USA) Duplicate microarray hybridizationwas set up using biological replicates that were labeled bydye-swap that is control RNA was labeled with Cy-5 andtest RNA with Cy-3 The dye labeled cDNA samples werehybridized to the whole human genome microarray (Catno G4112F Design ID 014850 Agilent Technologies USA)We followed the experimental instructions provided by thekit supplier for RNA amplification cDNA preparation dyelabeling and array hybridization

24 Microarray Image Analyses and Data Processing Themicroarrays were scanned at 5120583mresolution using aGenePix4000B scanner (Molecular Devices USA) The scannedimages were analyzed with GenePix Pro 61 the softwarepackage provided by Molecular Devices USA Quality con-trol of the images was performed with Acuity 40 (Molec-ular Devices USA) software package The following qualitycriteria have been used (1) at least 90 of the pixels inthe spot had intensity higher than background plus twostandard deviations (2) less than 2 saturated pixels inthe spot (3) signal to noise ratio (defined as ratio of thebackground subtracted mean pixel intensity to standarddeviation of background) was 3 or above for each channel(4) the spot diameter was between 45 and 70 120583m (5) theregression coefficient of ratios of pixel intensity was 06or above and (6) feature has opposite change direction

Evidence-Based Complementary and Alternative Medicine 3

Table 1 Eight genes were analyzed to validate the microarray data The fold changes in gene expression as obtained by microarray analyseswere verified by quantitative RT-PCR Experimental details are given in the materials and methods

No Gene symbol Gene name Microarray FC RT PCR FC1 TBP TATA box binding protein 237 1292 APOL1 Apolipoprotein L 164 3593 ICAM1 Intercellular adhesion molecule 1 263 1944 POLR2A Polymerase (RNA) II (DNA directed) polypeptide A minus199 0695 SLA Src-like-adaptor minus185 0436 HYAL1 Hyaluronoglucosaminidase 1 minus212 0427 IRF5 Interferon regulatory factor 5 minus225 0898 IL2 Interleukin 2 minus210 058

at dye-swap Only features that passed all quality controlcriteria in all microarrays were analyzed further To identifysignificantly expressed genes the R package ldquolimmardquo wasused ldquoWithin arrayrdquo normalization was carried out withLowess method and ldquobetween arraysrdquo normalization withldquoquantilerdquo algorithm in the ldquolimmardquo package Features thatdid not pass the quality control criteria in all arrayswere givenweight of 0 and were excluded from the analyses Differentialexpression and false discovery rate (FDR)were assessed usinga linear model and empirical Bayes moderated F statisticsGenes that passed FDR le 001 in all time points with afold change of 2 or more in at least one time point and inthe same direction in all time points were uploaded intoMetaCore tool (Thomson Reuters NY) for the identificationof pathways affected by LEThe same data sets were uploadedto TM4 microarray data management and analysis softwareto generate the heat map [4]

25 Verification of Microarray Data The microarray geneexpression data were verified by quantitative RT-PCR Pre-made validated RT-PCR primers (Table 1) used for datavalidation were purchased from Real Time Primers USACustom made primers were synthesized by Invitrogen USAReal-timeRT-PCRwas performedwith gene-specific primersusing the QuantiTect SYBR Green PCR kit (Qiagen USA)on an Applied Biosystem 5700 RT PCR machine The PCRconditions were as follows 10min at 95∘C 35 cycles at94∘C for 15 seconds and 30 seconds each at 60∘C and72∘C respectively The measured transcript abundance wasnormalized to the level of GAPDH or 120573-actin The meannormalized expression (MNE) was calculated using themethod developed by Muller et al [10] The fold change (FC)in gene expression was calculated using the formula FC =MNE of the LE treatedMNE of the control

3 Results

The whole genome microarray (Agilent USA) featuredapproximately 41000 60 nucleotide long oligonucleotideprobesThese probes represent all known human transcriptsThemicroarray data were deposited in NCBIrsquos ldquoGene Expres-sion Omnibusrdquo database repository accession number isGSE44290 [11]

Seven genes differentially regulated in microarray wereselected for validation using quantitative real time PCR Thedirection of fold change in gene expression observed inmicroarray analyses matched with the real time PCR data(Table 1)

31 Primary Screening ofMicroarrayData Yielded 17135GenesThat Passed Technical QC in All Microarrays and Have BeenAnalyzed Further 17135 features including replicated spotspassed technical QC (see ldquoSection 24rdquo) in all microarraysHybridization signals that passed all the quality controlcriteria as mentioned in the materials and methods werecompared to the signals obtained by dye-swap hybridizationWe combined biological replicates for dye swap in each treat-ment time point By this method of data filtering we selected2724 2730 and 5463 genes for 24 48 and 72 h respectively(see Supplementary File S-1 in Supplementary Materialsavailable online at httpdxdoiorg1011552013471739) Bythis screening we found that 1178 genes were common forall the three time points irrespective of the direction ofexpression change viz up or down regulation Details of thesecommon genes are listed in the Supplementary File S-1 Inthis data table the same gene may be upregulated at onetime point and downregulated at other time points These1178 genes represented expression data that passed initialQC for all the three time points irrespective of direction ofgene expression change triggered by LE treatment Exceptfor the QC described above no preset fold change (FC) orfalse discovery rate (FDR) parameters were applied to thesedata sets The lists of genes thus identified to be common forall three time points are detailed in ldquoSpot testrdquo sheet in theSupplementary File S-1

32 Application of FDR le 001 to Data Set Identified 221Genes From this data set we selected genes that passedFDR le 001 at each of the three treatment time pointsThis analyses yielded 971 (637334) 806 (325481) and 3075(17581317) genes that were unique to 24 h 48 h and 72 htime points respectively (Supplementary File S-1) The num-bers in parenthesis indicate the number of underexpressedand over expressed genes respectively A detailed gene listcorresponding to the three time points is listed in sheets


72 hr(3075)

24 hr(971)

48 hr(806)

2009

489

221

356

191

223

38

Figure 1 Venn diagram depicting the number of genes regulated by LE at different time points and the number of genes that are commonbetween the time segments (FDR le 001) 223 191 and 2009 genes were unique to 24 48 and 72 hours respectively 259 (221+38) genes werecommon between 24 and 48 h 356 between 48 and 72 h 489 between 24 and 72 h 221 genes were common among all the three time pointsExcept for FDR le 001 neither fold change nor the direction of regulation is accounted in this representation

24hFDR001 48hFDR001 and 72hFDR001 respectively (Sup-plementary File S-1) The genes selected by this methodwere compared for commonly regulated genes between thedifferent treatment time points This analysis found 223 191and 2009 genes to be unique to 24 48 and 72 h respectively38 genes were established to be common between 24 and48 h 489 between 24 and 72 hours and 356 genes between72 and 48 h 221 genes were common for all the three timepoints Though the genes may be common for the indicatedparameters the direction of regulation may not be the samefor these genes at the compared time points In this list onlythe gene names were common Other than FDR le 001 the FCwas not factored in this selection Therefore the same genemay have a positive and negative fold change at different timepoints (Sheet ldquoFDRle 001rdquo Supplementary File S-1)This datais graphically represented in Figure 1

33 Application of Dual Filter to the Data Set Identified 82Genes to Be Differentially Regulated by LE Next we limitedthe data analyses to genes that showed similar expressiontrend either up or down regulated over the three differentexperimental time points This analysis yielded the followingresults From across three different time points 941 (516425)out of 1178 genes showed similar expression pattern (SheetldquoFC Same trendrdquo Supplementary File S-1) From this list362 (248114) genes showed FC ge plusmn2 (Sheet ldquoFC ge plusmn2rdquoSupplementary File S-1) This list was further screened forgenes with FDR le 001 and thus we picked 89 (5831) genes(Sheet ldquoFDR le 001 and FC ge plusmn2rdquo Supplementary File S-1)Of the 89 genes 82 had known valid accession IDs Thusfrom 41000 probe sets on Human Genome microarray wesuccessfully selected 82 (5428) genes that showed similartrend across all the three time points with FDR 001 Inthis list all the genes in at least one of the three pointsqualified FDR le 001 and FC ge plusmn2 (Tables 2(a) and 2(b)) Therelatedness of the expression of 89 genes that are significantlydown (58) or up (31) regulated at all the three time points isdepicted in the heat map (Figure 2)

34 LE Regulates Key Pathways Involved in Immune ResponseDevelopment and So Forth The 82 genes thus selected wereuploaded to MetaCore tool in GeneGo suite (GeneGo USA)to determine the possible signaling pathways affected byLE This enrichment analysis identified 98 pathways to beregulated by LE We grouped these 98 pathways that havesimilar effect The top ten pathway maps of the 98 identifiedas above are given in Figure 3 A detailed list of all the 98pathways affected by LE is given in Table 3 Overall thedata suggested LE predominantly affected immune response(27) followed by metabolism (17) developmental (12)gene expression regulation (6) cell adhesion (5) cysticfibrosis transmembrane conductance regulation (CFTR) andchemotaxis (4) pathways

In this analysis the transcription assembly of RNA Poly-merase II preinitiation complex on TATA-less promoterspathway passed QC set at FDR le 005 The 119875 value was1216times10

minus5 (Figure 4)Three objects from the uploaded datawere found common among the 18 genes that are listed tobe involved in this regulation The key genes involved in thispathway are RNApol II that is important for the transcriptionof TATA less promoters This gene was underexpressed inLE treated cells It suggests the deregulation of TATA lesspromoter genes In genome wide analyses only 15 of thehuman genes have been reported to be regulated by clas-sical TATA box containing promoter Redundancyoverlapof these regulations has been observed in several genesTherefore even though it appears that the regulation ofTATA less gene transcription is altered complete loss of theiractivity may be limited Otherwise LE treatment must resultin unacceptably high toxicity which was not encounteredin animal studies [7] Figure 4 illustrates the TF-II and thestatus of the three genes that are directly involved in thispathway

Besides the above additional 11 pathways were signif-icantly affected by LE They are immune response MIF-mediated glucocorticoid regulation (119875 le 1437119864 minus 03)immune response IL-27 signaling (119875 le 1712119864minus03) immune


Table 2 (a) List of genes whose expression was downregulated at all the three time points (b) List of genes whose expression was up regulatedat all the three time points Average fold change in gene expression and the corresponding SD for the three different time points is given Genesthat showed FC of plusmn2 and FDR of lt001 were selected

(a)

No Gene name NCBI description AVE FC SD1 SYTL5 Synaptotagmin-like 5 minus292 1882 KGFLP1 Fibroblast growth factor 7 pseudogene minus280 1423 ARPC3P5 Actin related protein 23 complex subunit 3 pseudogene 5 minus263 1884 OSBPL8 Oxysterol binding protein-like 8 minus262 0015 C11orf10 Chromosome 11 open reading frame 10 minus256 1096 DHX9 DEAH (Asp-Glu-Ala-His) box polypeptide 9 minus251 0777 C1orf53 Chromosome 1 open reading frame 53 minus245 1168 VWF VonWillebrand factor minus240 0599 AF038194 Homo sapiens clone 23821 mRNA sequence minus235 05110 POM121 POM121 transmembrane nucleoporin minus233 03611 THC2671048 Q3DWD9 CHLAU (Q3DWD9) YLP motif partial (6) minus233 07112 TOM1L2 Target of myb1-like 2 (chicken) minus233 07613 CAPZA3 Capping protein (actin filament) muscle Z-line alpha 3 minus233 08214 CYSLTR2 Cysteinyl leukotriene receptor 2 minus230 05415 ANKRD33B Ankyrin repeat domain 33B minus227 061

16 AA889371 am40h08s1 Soares NFL T GBC S1 Homo sapiens cDNA clone IMAGE1471263 31015840 similarto SWCOQ1 YEAST P18900 HEXAPRENYL PYROPHOSPHATE SYNTHETASE minus226 067

17 FAM101A Family with sequence similarity 101 member A minus226 09118 IRF5 Interferon regulatory factor 5 minus225 06819 EGFLAM EGF-like fibronectin type III and laminin G domains minus225 07220 SIRT3 NAD-dependent protein deacetylase sirtuin-3 mitochondrial isoform a minus220 06521 NEK8 NIMA (never in mitosis gene a)mdashrelated kinase 8 minus219 10722 ROD1 Polypyrimidine tract binding protein 3 minus218 06023 RBM26 RNA binding motif protein 26 minus218 10524 HYAL1 Hyaluronoglucosaminidase 1 (HYAL1) transcript variant 1 noncoding RNA minus212 04525 IL2 Interleukin 2 minus210 01726 LRRC20 Leucine-rich repeat-containing protein 20 isoform 3 minus210 06727 THC2635921 minus209 09028 GJD4 Gap junction protein delta 4 401 kDa minus209 05229 SNAPC1 Small nuclear RNA activating complex polypeptide 1 43 kDa minus206 05030 GNG13 Guanine nucleotide binding protein (G protein) gamma 13 minus200 04531 POLR2A Polymerase (RNA) II (DNA directed) polypeptide A 220 kDa minus199 02332 CD44 CD44 molecule (Indian blood group) minus197 087

33 CR742006 CR742006 Soares testis NHT Homo sapiens cDNA clone IMAGp971J1256 IMAGE104873751015840 mRNA sequence minus196 053

34 THC2709441 Q4VIX2 DROBU (Q4VIX2) Dbuzabd-A-PB partial (4) minus195 07735 PIGU Phosphatidylinositol glycan anchor biosynthesis class U minus195 02536 KRT14 Keratin 14 minus191 062

37 BE564275 601343077F1 NIH MGC 53 Homo sapiens cDNA clone IMAGE3685338 51015840 mRNAsequence minus190 059

38 ZNF622 Zinc finger protein 622 minus189 076

39 BQ060012 AGENCOURT 6793913 NIH MGC 99 Homo sapiens cDNA clone IMAGE5816175 51015840mRNA sequence minus188 028

40 LCE1D Late cornified envelope 1D minus188 01341 BC034623 Homo sapiens cDNA clone IMAGE4837603 minus186 045


(a) Continued

No Gene name NCBI description AVE FC SD42 SLA Src-like-adaptor minus185 03043 HLA-DOB Major histocompatibility complex class II DO beta minus185 05744 FOXL1 Forkhead box L1 minus184 03445 B3GNT9 UDP-GlcNAcbetaGal beta-1 3-N-acetylglucosaminyltransferase 9 minus184 06646 SLC15A1 Solute carrier family 15 (oligopeptide transporter) member 1 minus182 043

47 HADHB hydroxyacyl-CoA dehydrogenase3-ketoacyl-CoA thiolaseenoyl-CoA hydratase(trifunctional protein) beta subunit minus179 061

48 HSPA14 Heat shock 70 kDa protein 14 minus178 04349 BC092421 Homo sapiens cDNA clone IMAGE30378758 minus176 03950 POC1A POC1 centriolar protein homolog A (Chlamydomonas) minus175 02751 ACVR1 Activin A receptor type I minus172 04152 TPSD1 Tryptase delta 1 minus168 03353 MAPK8IP3 Mitogen-activated protein kinase 8 interacting protein 3 minus167 04054 UCHL5 Ubiquitin carboxyl-terminal hydrolase L5 minus161 041

(b)

No Gene name NCBI description AVE FC SD1 MBD6 Methyl-CpG binding domain protein 6 158 044

2 BG536553 602564961F1 NIH MGC 77 Homo sapiens cDNA clone IMAGE4689518 51015840 mRNAsequence 164 034

3 APOL1 Apolipoprotein L 1 164 0444 LOC728537 Uncharacterized LOC728537 169 0525 THC2624002 Q9BXR7 HUMAN (Q9BXR7) Interleukin 10 (Fragment) partial (93) 172 0496 CASKIN2 CASK interacting protein 2 177 0417 PML Promyelocytic leukemia 178 0668 ZC3HAV1L Zinc finger CCCH-type antiviral 1-like 181 025

9 THC2653001 BX098637 Soares fetal liver spleen 1NFLS Homo sapiens cDNA clone IMAGp998F16386IMAGE200847 mRNA sequence 181 067

10 LOC728344 Glutaredoxin 3 pseudogene 188 05611 METRNL Meteorin glial cell differentiation regulator-like 189 08912 C8orf75 Long intergenic nonprotein coding RNA 589 191 08113 AK021715 Homo sapiens cDNA FLJ11653 fis clone HEMBA1004538 191 08614 TMCO1 Transmembrane and coiled-coil domains 1 199 03615 UQCC Ubiquinol-cytochrome c reductase complex chaperone 200 04116 RPL7P48 Ribosomal protein L7 pseudogene 48 214 073

17 AF483645 Homo sapiens capacitative calcium channel protein Trp1 mRNA partial cds alternativelyspliced 217 067

18 TAF9B TAF9B RNA polymerase II TATA box binding protein (TBP)-associated factor 31 kDa 231 03719 AK026477 Homo sapiens cDNAFLJ22824 fis clone KAIA3991 234 03920 BBS12 Bardet-Biedl syndrome 12 237 04821 THC2624048 Q964F8 PLAFA (Q964F8) Merozoite surface protein 8 partial (3) 237 04422 TBP TATA box binding protein 237 05023 BC034627 Homo sapiens cDNA clone IMAGE4839213 238 03624 JAG2 Jagged 2 242 04925 TMEM8 Transmembrane protein 8A 242 04326 CARD18 Caspase recruitment domain family member 18 251 059

27 AA020958 ze65a02s1 Soares retina N2b4HR Homo sapiens cDNA clone IMAGE363818 31015840 mRNAsequence 252 048

28 ICAM1 Intercellular adhesion molecule 1 263 077


OSBPL8VWF

KGFLP1 CYSLTR2

POM121 DHX9 ROD 1THC2671048

C1orf53 LOC651746 SYTL5 IRF5 TOM1L2 SLAHSPA14 AF038194 EGFLAM PIGUAA889371 LCE1D FAM101A ROLR2A LOC441131

KRT14 HYAL1 ACVR1 SLC15A1 THC2635921 GNG13 LRRC20 CX401 CAPZA3 C11orf10 BQ060012

WDR51A TPSD1MLA-DOBSIRT3BC092421ENST00000377131SNAPC1CD44FOXL1NEK8CR742006MGC4655HADHBBCO34623BE564275THC2709441UCHL5ZNF622MAPK8IP3MBD6METRNLBC089454PMLLOC643450THC2653001AK021715LOC728537APOL1CASKIN2C8orf75

THC2624002 LOC388401 C20orf44 ZC3HAV1LTMCO1THC2712447AF483645BG536553TBPBBS12TAF9BICAM1AK026477JAG2ICEBERGTHC2624048BC034627TMEM8AA020958

A 32 P103162

A 32 P192586

Il 2

A 24 P408981

A 24 P818378

A 24 P940375

minus60 0060FC24 FC48 FC72

Figure 2 Heat map depicting the relatedness of gene expression pattern inMIAPaCa-2 cells treated with LEThis image was generated usingthe fold changes in the expression of 89 genes that are significantly down (58 green) or up (31 red) regulated at all the three time points Theintensity of the color is proportional to the fold change in gene expression level between untreated and LE treated MiaPaCa-2 cells The heatmap was generated using TM4 microarray data management and analysis software [4]


Table 3 Signaling pathways affected by LE in Pancreatic cancer cells The experimental data of 82 genes (see ldquoSection 33rdquo) were uploadedto Metacore tool It identified 98 pathways to be regulated by LE The number of pathways affected under each category is indicated inparenthesis

No Pathway map 119875 value RatioImmune response (27)

1 Immune response MIF-mediated glucocorticoid regulation 1437119864 minus 03 2 222 Immune response IL-27 signaling pathway 1712119864 minus 03 2 243 Immune response HSP60 and HSP70TLR signaling pathway 8466119864 minus 03 2 544 Immune response IFN alphabeta signaling pathway 6049119864 minus 02 1 245 Immune response role of HMGB1 in dendritic cell maturation and migration 6780119864 minus 02 1 276 Immune response CD137 signaling in immune cell 7265119864 minus 02 1 297 Immune response Delta-type opioid receptor signaling in T-cells 7265119864 minus 02 1 298 Immune response IL-22 signaling pathway 8465119864 minus 02 1 349 CCR4-dependent immune cell chemotaxis in asthma and atopic dermatitis 8465119864 minus 02 1 3410 Mechanism of action of CCR4 antagonists in asthma and atopic dermatitis (Variant 1) 8465119864 minus 02 1 3411 Immune response regulation of T cell function by CTLA-4 8941119864 minus 02 1 3612 Immune response role of integrins in NK cells cytotoxicity 9415119864 minus 02 1 3813 Immune response Th1 andTh2 cell differentiation 9886119864 minus 02 1 4014 Immune response IL-5 signalling 1082119864 minus 01 1 4415 Immune response PGE2 signaling in immune response 1105119864 minus 01 1 4516 Immune response NF-AT signaling and leukocyte interactions 1129119864 minus 01 1 4617 Immune response histamine H1 receptor signaling in immune response 1175119864 minus 01 1 4818 Immune response IL-2 activation and signaling pathway 1198119864 minus 01 1 4919 Immune response function of MEF2 in T lymphocytes 1221119864 minus 01 1 5020 Immune response HMGB1RAGE signaling pathway 1289119864 minus 01 1 5321 Immune response IFN gamma signaling pathway 1312119864 minus 01 1 5422 Immune response CCR5 signaling in macrophages and T lymphocytes 1402119864 minus 01 1 5823 Immune response immunological synapse formation 1425119864 minus 01 1 5924 Immune response TREM1 signaling pathway 1425119864 minus 01 1 5925 Immune response IL-17 signaling pathways 1447119864 minus 01 1 6026 Immune response CD40 signaling 1558119864 minus 01 1 6527 Immune response CD16 signaling in NK cells 1646119864 minus 01 1 69

Metabolism (17)28 Mitochondrial ketone bodies biosynthesis and metabolism 6780119864 minus 02 1 2729 Propionate metabolism p1 9651119864 minus 02 1 3930 Selenoamino acid metabolism 1312119864 minus 01 1 5431 Phenylalanine metabolismrodent version 1580119864 minus 01 1 6632 Propionate metabolism p2 1580119864 minus 01 1 6633 Phenylalanine metabolism 1602119864 minus 01 1 6734 Leucine isoleucine and valine metabolismp2 1841119864 minus 01 1 7835 Leucine isoleucine and valine metabolismRodent version 1884119864 minus 01 1 8036 Tyrosine metabolism p2 (melanin) 1947119864 minus 01 1 8337 Lysine metabolism 1968119864 minus 01 1 8438 Lysine metabolismrodent version 2010119864 minus 01 1 8639 GTP-XTP metabolism 2094119864 minus 01 1 9040 Tryptophan metabolism 2319119864 minus 01 1 10141 Tryptophan metabolismrodent version 2339119864 minus 01 1 10242 CTPUTP metabolism 2459119864 minus 01 1 10843 NAD metabolism 2674119864 minus 01 1 11944 ATPITP metabolism 2770119864 minus 01 1 124


Table 3 Continued

No Pathway map 119875 value RatioDevelopment (12)

45 Development glucocorticoid receptor signaling 6049119864 minus 02 1 2446 Development cross-talk between VEGF and angiopoietin 1 signaling pathways 6537119864 minus 02 1 2647 Development osteopontin signaling in osteoclasts 7506119864 minus 02 1 3048 Development BMP signaling 8226119864 minus 02 1 3349 Development lipoxin inhibitory action on PDGF EGF and LTD4 signaling 8941119864 minus 02 1 3650 Development beta-adrenergic receptors transactivation of EGFR 9179119864 minus 02 1 3751 Development notch signaling pathway 1059119864 minus 01 1 4352 Development S1P3 receptor signaling pathway 1059119864 minus 01 1 4353 Development VEGF signaling and activation 1059119864 minus 01 1 4354 Development S1P1 signaling pathway 1082119864 minus 01 1 4455 Development beta-adrenergic receptors regulation of ERK 1152119864 minus 01 1 4756 Development WNT signaling pathway part 2 1289119864 minus 01 1 53

Gene expression regulation (6)57 Transcription assembly of RNA polymerase II preinitiation complex on TATA-less promoters 1204119864 minus 05 3 1858 Translation IL-2 regulation of translation 5066119864 minus 02 1 2059 Transcription role of akt in hypoxia induced HIF1 activation 6780119864 minus 02 1 2760 Transcription ligand-dependent transcription of retinoid-target genes 8226119864 minus 02 1 3361 Transcription role of AP-1 in regulation of cellular metabolism 9415119864 minus 02 1 3862 Translation (L)-selenoaminoacids incorporation in proteins during translation 1012119864 minus 01 1 41

Cell adhesion (5)63 Cell adhesion IL-8-dependent cell migration and adhesion 8226119864 minus 02 1 3364 Cell adhesion cell-matrix glycoconjugates 9415119864 minus 02 1 3865 Cell adhesion ephrin signaling 1105119864 minus 01 1 4566 Cell adhesion ECM remodeling 1267119864 minus 01 1 5267 Cell adhesion chemokines and adhesion 2299119864 minus 01 1 100

CFTR regulation (4)68 CFTR folding and maturation (norm and CF) 3572119864 minus 02 1 1469 wtCFTR and delta F508 trafficlate endosome and lysosome (norm and CF) 3823119864 minus 02 1 1570 Regulation of degradation of delta F508 CFTR in CF 6780119864 minus 02 1 2771 Mechanisms of CFTR activation by S-nitrosoglutathione (normal and CF) 1129119864 minus 01 1 46

Chemotaxis (4)72 Chemotaxis CCR4-induced chemotaxis of immune cells 8465119864 minus 02 1 3473 Chemotaxis lipoxin inhibitory action on fMLP-induced neutrophil chemotaxis 1129119864 minus 01 1 46

74 Chemotaxis inhibitory action of lipoxins on IL-8- and leukotriene B4-induced neutrophilmigration 1244119864 minus 01 1 51

75 Chemotaxis leukocyte chemotaxis 1777119864 minus 01 1 75Oxidative stress (4)

76 Oxidative stress role of ASK1 under oxidative stress 8465119864 minus 02 1 3477 Mitochondrial unsaturated fatty acid beta-oxidation 1105119864 minus 01 1 4578 Mitochondrial long chain fatty acid beta-oxidation 1947119864 minus 01 1 8379 Peroxisomal branched chain fatty acid oxidation 1947119864 minus 01 1 83

Protein degradation (4)

80 Protein folding membrane trafficking and signal transduction of G-alpha (i) heterotrimericG-protein 4819119864 minus 02 1 19

81 Proteolysis putative ubiquitin pathway 5804119864 minus 02 1 2382 Proteolysis role of parkin in the ubiquitin-proteasomal pathway 6049119864 minus 02 1 2483 Proteolysis putative SUMO-1 pathway 7265119864 minus 02 1 29


Table 3 Continued

No Pathway map 119875 value RatioBlood coagulation (3)

84 Blood coagulation blood coagulation 9651119864 minus 02 1 3985 Blood coagulation GPVI-dependent platelet activation 1335119864 minus 01 1 5586 Blood coagulation GPIb-IX-V-dependent platelet activation 1798119864 minus 01 1 76

DNA damage (3)87 DNA damage role of SUMO in p53 regulation 4322119864 minus 02 1 1788 DNA damage NHEJ mechanisms of DSBs repair 4819119864 minus 02 1 1989 DNA damage nucleotide excision repair 8941119864 minus 02 1 36

Apoptosis (2)90 Apoptosis and survival role of IAP-proteins in apoptosis 7747119864 minus 02 1 3191 Apoptosis and survival lymphotoxin-beta receptor signaling 1036119864 minus 01 1 42

Cytoskeleton remodeling (2)92 Cytoskeleton remodeling keratin filaments 8941119864 minus 02 1 3693 Cytokine production byTh17 cells in CF 9651119864 minus 02 1 39

Other (3)94 Transport RAB3 regulation pathway 3572119864 minus 02 1 1495 Inhibitory action of lipoxin A4 on PDGF EGF and LTD4 signaling 8704119864 minus 02 1 3596 Signal transduction calcium signaling 1105119864 minus 01 1 4597 Inhibitory action of lipoxins on neutrophil migration 1380119864 minus 01 1 57

Cell cycle (1)98 Cell cycle role of Nek in cell cycle regulation 3037119864 minus 03 2 32

response HSP60 and HSP70TLR signaling (119875 le 8466119864 minus03) translation IL-2 regulation of translation (119875 le 5066119864 minus02) CFTR folding and maturation (norm and CF) (119875 le3572119864 minus 02) wtCFTR and delta F508 trafficLate endosomeand lysosome (norm and CF) (119875 le 3823119864 minus 02) proteinfolding membrane trafficking and signal transduction of G-alpha (i) heterotrimeric G-protein (119875 le 4819119864 minus 02) DNAdamage role of SUMO in p53 regulation (119875 le 4322119864 minus02) DNA damage NHEJ mechanisms of DSBs repair (119875 le4819119864 minus 02) transport RAB3 regulation pathway (119875 le3572119864minus02) and cell cycle role of Nek in cell cycle regulation(119875 le 3037119864 minus 03) The rest of the 86 pathways possiblyaffected by LE had a 119875 value ge005

35 Disease Biomarker Analysis Suggests LE Affects VasculitisThe expression of 82 genes that were identified to be influ-enced by LE was subjected to disease biomarker enrichmentanalysis in MetaCore tool This investigation picked up alarge number of diseases from this data set The top 10diseases along with the corresponding 119875-values are listedin Table 4 It also contains the number of genes found inthe microarray data that matched genes cataloged in Meta-Core disease biomarker enrichment database It appears thatLE predominantly affected genespathways involved in theinflammation of blood vessels a condition called VasculitisAutoimmune disorders like arthritis and pancreatitis areattributed to be two of many etiology for vasculitis [12 13]In this table arthritis is the second most disease affectedby LE (119875 le 6185119864 minus 12) As reported in the literature

Table 4 A partial list of diseases that may be affected by LE Thetop ten diseases identified by MetaCore tool in the microarray dataset of MiaPaCa-2 cells treated with LE are listed in this table Thelist is arranged per descending 119875 value The number of genes in theuploaded microarray data versus the genes cataloged in MetaCoredisease biomarker enrichment database is indicated as ratio

No Diseases 119875-value Ratio1 Rheumatoid vasculitis 4375119864 minus 13 6 102 Arthritis experimental 6185119864 minus 12 6 143 Papilloma intraductal 1789119864 minus 10 4 44 Systemic vasculitis 3926119864 minus 10 7 475 DNA virus infections 9529119864 minus 09 15 6546 Herpesviridae infections 1106119864 minus 08 12 3787 Vasculitis 1573119864 minus 08 10 2388 Lymphangiomyoma 3694119864 minus 08 4 109 Smooth muscle tumor 3694119864 minus 08 4 1010 Lymphangioleiomyomatosis 3694119864 minus 08 4 10

A aspera is used as a cure for pancreatic cancer [7] asan antiarthritic medication [14] and to stop bleeding Theoutcome of disease network analysis supports its medicinaluse It is notable that LE decreased the CD44 expression(Table 2(a)) The cell surface glycoprotein CD44 is involvedin a wide variety of interactions that include receptors cell-cell interaction adhesion and migration (metastasis) Alongwith CD44 MMPs VEGF and hyaluronoglucosaminidase 1


1 2 3 4

1

2

3

4

5

6

7

8

9

10Maps

minuslog(P value)(1) Transcription assembly of RNA polymerase II preinitiation complex on TATA-less promoters

(2) Immune response MIF-mediated glucocorticoid regulation

(3) Immune response IL-27 signaling pathway

(4) Cell cycle role of nek in cell cycle regulation

(5) Immune response HSP60 and HSP70 TLR signaling pathway

(6) Transport RAB3 regulation pathway

(7) CFTR folding and maturation (norm and CF)

(8) wtCFTR and delta F508 trafficlate endosome and lysosome (norm and CF)

(9) DNA damage role of SUMO in p53regulation

(10) DNA damage NHEJ mechanisms of DSBs repair

Figure 3 Top ten pathway maps identified byMetaCore tool in the microarray data set of MiaPaCa-2 cells treated with LE for three differenttime points The list is arranged per descending 119875 value score A detailed list of all the pathways affected by LE is given in Table 3

(HYAL1 Table 2(a)) levels decreased in MiaPaCa-2 cellstreated with LE Of these molecules the inhibition of HYAL1enzyme was shown to decrease prostate cancer progressionin vivo [15] Therefore LE is likely to suppresses tumorprogression and metastasis as demonstrated earlier in ouranimal studies [7]

4 Discussion

In complementary and alternate medicine (CAM) unrefined(crude) preparations of natural products are used for thetreatment of various illnesses It is believed that compoundspresent in a crude preparation modulate the effect of theactive molecule [16] In this approach the use of crudeextract by CAM practitioners is akin to multidrug ther-apy The difference is in multidrug therapy the chemicalnature as well the mechanisms of action of the componentdrugs are reasonably well studied Even when combinationchemotherapy is practiced the added drugs are effective onlyin a few drug combinations [17] Most of the modern daywonder drugs originated from or derivatives of the activemolecules identified from natural products [18 19] Onceisolated the active components from these natural productseither end up being intolerably toxic lose their activity orneeded in impractically large doses Also the drug discoverypathway is long arduous and expensive [20] While it isideal to identify the active molecule we should note thata majority of the world population depends on naturalremedies Shortcomings in the use of natural products asmedicine are the lack of quality control of these preparationsdosage optimization and contra indications Various nodalagencies have embarked on an effort to validate themedicinalbenefits quality control and dosage standardization of natu-ral products that are widely used by CAM practitioners [1]

We are interested in the anticancer properties of Aaspera It is noteworthy that LE modulates the expressionof genes involved in embryonic development cell adhesiontranscription factors that regulate cell growth and so forthThese effects support itsrsquo use as abortifacient [21]Hitherto wehave systematically demonstrated that A aspera a medicinalplant used in Ayurvedic medicine inhibited the growth ofcancer cells in vitro and orthotopic pancreatic tumor in vivoMany parts of this plant are used as a cure for a wide array ofailments that include fertility control fetal expulsion woundhealing and cancer therapy Since LE is a crude extract weexpected a large number of genes would be affected in thetreated cells However stringent data filtering determinedjust 89 genes were affected by LE Of these seven wereprobes used for quality control Thus effectively we havenarrowed down the number of genes affected by LE to82 The pathway data analyses demonstrated predominantlyimmune response is affected by LE followed by metabolismdevelopment transcription and so forth The effects ondevelopmental gene expression regulation and cell adhesionpathways imply that LE directly affects cancer growth andmetastasis

Mutations in cystic fibrosis gene are identified as a riskfactor for chronic pancreatitis and pancreatic ductal ade-nocarcinoma [22 23] Molecular mechanistic study suggestloss of cystic fibrosis transmembrane conductance regulation(CFTR) and a corresponding increase inMUC4 expression isobserved in about 81 of pancreatic ductal adenocarcinomacell lines [24 25]Themicroarray data suggest genes involvedin CFTR regulation are modulated by LE Though the effectof LE on CFTR pathway is highlighted in the gene expressionstudies the molecular mechanism by which LE regulatesCFTR or related gene function is not knownThe short listingof CFTR and other top 10 pathways as affected by LE is worth


B

CS

Assembly onTATA-less promoters Transcription

TRB

B

B

B

BB

TR TR TR

TR

TR

TR

TR

TR

TRTR

1

1

1

1

Figure 4 Canonical pathway analyses in MetaCore tool identified Transcription assembly of RNA polymerase II preinitiation complex onTATA-less promoters to be the top scored pathway map (119875 le 1204119864 minus 05) in LE treated cells Red thermometers show an object that isupregulated by LE Blue thermometer show the objects downregulated by LE The exact fold change obtained from three time points withthe corresponding SD is given in Table 2 The big arrow indicates the ldquopathway startrdquo TR transcriptional regulation CS complex subunit Bbinding grey arrow technical link green arrows positive effect blue arrows represent positive red negative and grey unspecified interactionsBoxes on lines denote the type of regulation where P is phosphorylation B is binding and TR is transcriptional regulation A detailed legendfor the objects in this figure is given in the Supplementary File SF-1

further investigations The microarray data are consistentwith our experimental findings that LE is preferentiallycytotoxic to pancreatic cancer cell lines in vitro [8] and theuse of LE in the treatment of pancreatic cancer by ayurvedicphysicians

Our results demonstrate that it is possible to pin pointpossible mechanism of action of crude extract using carefullyplanned experiments We applied several assumptions in ourdata analyses For instance we eliminated expressions thatdid not follow the same pattern There are instances wherea group of genes may be up regulated in the short term anddown regulated over long term exposure to LE or vice versaThough less likely another set of genes may be up and downregulated in a cyclical manner By considering unidirectionalregulation we would have eliminated such unique changeseffected by LE Ambiguities in gene expression analysis maybe reduced and the robustness of expression data may beincreased by using several experimental replicates multipledifferent cell lines and different drug concentrations Addi-tionally gene expression analysesmay be performed in tumorsamples obtained from animal model that had been treatedwith LE

The identification of regulation of 82 genes from a largedata set encourages us to think that natural products maytarget a limited set of genes There are evidences to supportsuch observations For instance almost identical results wereobtained in MCF-7 breast cancer cells that were treated with

a crude extract ofAnoectochilus formosanus and a single com-pound drug plumbagin [26] However natural products mayhavemuch broader impact on global gene expression patternTherefore we must be cautious in the universality of thisapproach

In conclusion we have demonstrated that LE affected theexpression of only a few genes Using similar methodologyit is possible to get reasonably good overview of the changesinduced by crude preparation of natural products with medi-cinal properties

Conflict of Interests

Authors indicate no conflict of interests

Acknowledgments

Pochi R Subbarayan thanks Dr Ram Agarwal and DrPradeep Kumar for the supply of A aspera leaf powderUndergraduate students Anthony Fernandez and Ravi Patelhelped in real time PCR validation and proof reading thepaper Funding for this work was provided by the AmericanCancer Society Institutional Research Grant (IRG 98-277-07) Interdisciplinary Research Development Initiative(IRDI 102504) award and the Miami Clinical and Trans-lational Science Institute (CTSI) Pilot Research Grant (CTSI-2013-P03) of the University of Miami to PRS The Pilot and


Collaborative Translational and Clinical Studies componentis supported by Grant no 1UL1TR000460 the Universityof Miami CTSI from the National Center for AdvancingTranslational Sciences and the National Institute on Minor-ity Health and Health Disparities Additional support wasprovided by Sheibar Foundation Grant to BA NIH Grants1R01AT003544 and R01CA156776-01 to BLL

References

[1] J J Shan K Rodgers C-T Lai and S K Sutherland ldquoChal-lenges in natural health product research the importanceof standardizationrdquo Proceedings of the Western PharmacologySociety vol 50 pp 24ndash30 2007

[2] C C Deocaris NWidodo RWadhwa and S C Kaul ldquoMergerof Ayurveda and tissue culture-based functional genomicsinspirations from systems biologyrdquo Journal of TranslationalMedicine vol 6 article 14 2008

[3] V Souza Y B Dong H S Zhou W Zacharias and KM McMasters ldquoSW-620 cells treated with topoisomerase Iinhibitor SN-38 gene expression profilingrdquo Journal of Transla-tional Medicine vol 3 article 44 2005

[4] A I Saeed V Sharov J White et al ldquoTM4 a free open-source system for microarray data management and analysisrdquoBioTechniques vol 34 no 2 pp 374ndash378 2003

[5] A Bagavan A A Rahuman C Kamaraj and K GeethaldquoLarvicidal activity of saponin from Achyranthes aspera againstAedes aegypti and Culex quinquefasciatus (Diptera Culici-dae)rdquo Parasitology Research vol 103 no 1 pp 223ndash229 2008

[6] I Hedberg O Hedberg P J Madati K E Mshigeni E NMshiu and G Samuelsson ldquoInventory of plants used in tradi-tional medicine in Tanzania I Plants of the families Acantha-ceae-Cucurbitaceaerdquo Journal of Ethnopharmacology vol 6 no1 pp 29ndash60 1982

[7] P R Subbarayan M Sarkar R S Nagaraja et al ldquoAchyranthesaspera (Apamarg) leaf extract inhibits human pancreatic tumorgrowth in athymic mice by apoptosisrdquo Journal of Ethnopharma-cology vol 142 pp 523ndash530 2012

[8] P R Subbarayan M Sarkar S Impellizzeri et al ldquoAnti-proliferative and anti-cancer properties of Achyranthes asperaspecific inhibitory activity against pancreatic cancer cellsrdquoJournal of Ethnopharmacology vol 131 no 1 pp 78ndash82 2010

[9] A Schroeder O Mueller S Stocker et al ldquoThe RIN anRNA integrity number for assigning integrity values to RNAmeasurementsrdquo BMCMolecular Biology vol 7 article 3 2006

[10] P Y Muller H Janovjak A R Miserez and Z DobbieldquoProcessing of gene expression data generated by quantitativereal-time RT-PCRrdquo BioTechniques vol 32 no 6 pp 1372ndash13792002

[11] T Barrett D B Troup S E Wilhite et al ldquoNCBI GEO archivefor functional genomics data sets-10 years onrdquo Nucleic AcidsResearch vol 39 no 1 pp D1005ndashD1010 2011

[12] A Miller M Chan A Wiik S A Misbah and R A LuqmanildquoAn approach to the diagnosis andmanagement of systemic vas-culitis revised version with tracked changes removedrdquo Clinicaland Experimental Immunology vol 160 no 2 pp 143ndash160 2010

[13] P Sharma S Sharma R Baltaro and J Hurley ldquoSystemic vas-culitisrdquo American Family Physician vol 83 no 5 pp 556ndash5652011

[14] S-THan andC-C Lin ldquoCardiac toxicity caused byAchyranthesasperardquo Veterinary and Human Toxicology vol 45 no 4 pp212ndash213 2003

[15] V B Lokeshwar W H Cerwinka T Isoyama and B LLokeshwar ldquoHYAL1 hyaluronidase in prostate cancer a tumorpromoter and suppressorrdquo Cancer Research vol 65 no 17 pp7782ndash7789 2005

[16] B V Subbarayappa ldquoThe roots of ancient medicine an histor-ical outlinerdquo Journal of Biosciences vol 26 no 2 pp 135ndash1432001

[17] B Ardalan P R Subbarayan Y Ramos et al ldquoA phase I studyof 5-fluorouracilleucovorin and arsenic trioxide for patientswith refractoryrelapsed colorectal carcinomardquo Clinical CancerResearch vol 16 no 11 pp 3019ndash3027 2010

[18] G M Cragg and D J Newman ldquoPlants as a source of anti-cancer agentsrdquo Journal of Ethnopharmacology vol 100 no 1-2pp 72ndash79 2005

[19] D J Newman ldquoNatural products as leads to potential drugsan old process or the new hope for drug discoveryrdquo Journal ofMedicinal Chemistry vol 51 no 9 pp 2589ndash2599 2008

[20] M J Balunas and A D Kinghorn ldquoDrug discovery frommedicinal plantsrdquo Life Sciences vol 78 no 5 pp 431ndash441 2005

[21] W Shibeshi E Makonnen L Zerihun and A Debella ldquoEffectof Achyranthes aspera L on fetal abortion uterine and pituitaryweights serum lipids and hormonesrdquo African Health Sciencesvol 6 no 2 pp 108ndash112 2006

[22] N Sharer M Schwarz GMalone et al ldquoMutations of the cysticfibrosis gene in patients with chronic pancreatitisrdquo The NewEngland Journal of Medicine vol 339 no 10 pp 645ndash652 1998

[23] R R McWilliams G M Petersen K G Rabe et al ldquoCysticfibrosis transmembrane conductance regulator (CFTR) genemutations and risk for pancreatic adenocarcinomardquoCancer vol116 no 1 pp 203ndash209 2010

[24] M-P Audrezet J-M Chen C le Marechal et al ldquoDeter-mination of the relative contribution of three genesmdashthecystic fibrosis transmembrane conductance regulator genethe cationic trypsinogen gene and the pancreatic secretorytrypsin inhibitor genemdashto the etiology of idiopathic chronicpancreatitisrdquo European Journal of Human Genetics vol 10 no2 pp 100ndash106 2002

[25] D W Rittenhouse V A Talbott Z Anklesaria J R Brody AK Witkiewicz and C J Yeo ldquoSubject review pancreatic ductaladenocarcinoma in the setting ofmutations in the cystic fibrosistransmembrane conductance regulator gene case report andreview of the literaturerdquo Journal of Gastrointestinal Surgery vol15 no 12 pp 2284ndash2290 2011

[26] N-S Yang L-F Shyur C-H Chen S-Y Wang and C-MTzeng ldquoMedicinal herb extract and a single-compound drugconfer similar complex pharmacogenomic activities in MCF-7cellsrdquo Journal of Biomedical Science vol 11 no 3 pp 418ndash4222004

Submit your manuscripts athttpwwwhindawicom

Stem CellsInternational

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014


MEDIATORSINFLAMMATION

of


Behavioural Neurology

EndocrinologyInternational Journal of



Disease Markers


BioMed Research International

OncologyJournal of



Oxidative Medicine and Cellular Longevity


PPAR Research

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Immunology ResearchHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

ObesityJournal of



Computational and Mathematical Methods in Medicine

OphthalmologyJournal of


Diabetes ResearchJournal of



Research and TreatmentAIDS


Gastroenterology Research and Practice


Parkinsonrsquos Disease

Evidence-Based Complementary and Alternative Medicine

Volume 2014Hindawi Publishing Corporationhttpwwwhindawicom


pathways [3] These results suggest that a drug with specifictarget can have wide ranging physiological effects

Analytical methods like microarray pathway focusedPCR arrays RNA seq and cGH array give a snapshot of largescale changes at genome level These methodologies generatelarge data sets The development of data mining software hasenabled discovery of molecular markers from the mass ofdata possible Thus the ability to analyze gene expressionchanges at genome level had revolutionized the molecularinvestigations that until now were difficult For exampleunderstanding global gene expression changes that accom-pany certain diseases like cancer has enabled the developmentof personalized medicine Data analysis of microarray resultsalso facilitated deciphering molecular pathways that areaffected by both existing aswell as newly discovered drugs [2]

Achyranthes aspera (Family Amaranthaceae) is a medici-nal plant in Ayurvedic pharmacopoeia It is an annual shrubfound in India Southeast Asia America and Sub-SaharanAfrica It is classified as a weed [5] Traditionally the plantextract is used as a cure for arthritis as blood clotting agentto induce labor (fetal expulsion) and as an abortifacient [6]Earlier we demonstrated that methanol-extract of A asperaleaves (LE) has antiproliferative activity against a variety ofhuman cancer cell lines cultured in vitro Our results alsoshowed pancreatic cancer cells to be the most sensitive toLE These exciting outcomes indicate the presence of activeanticancer molecule(s) in A aspera Unpublished anecdotalobservations suggest that A aspera benefited pancreaticcancer patients Animal studies carried out with A asperaextract confirm LE to be nontoxic to mice Most importantlythese studies have shown that LE inhibited human tumorgrowth in mice [7] In preliminary gene expression studieswe demonstrated LE differentially modulated the expressionof key genes involved in vasculogenesis (VEGFs) metasta-sis (MMPs TIMPS) apoptosis (Caspase) cell proliferation(Akt-1) and so forth [7 8]These preliminary results supportthe idea that LE regulates the function of specific signalingmolecules Except for the above two reports no additionalinformation is available regarding the global molecularchanges caused by LE in human cancer cells Clearly simul-taneous analysis of global gene expression changes effectedby LE would shine light on different pathways affected Suchanalyses would help select key genes that can be used asresponse markers and predict its effect on different illnessesBased on this premise we used Agilent Whole HumanGenome microarrays to examine the global gene expressionchanges effected by LE on cultured human pancreatic cancercell line MIA PaCa-2 (CRL-1420) that were treated with LEfor 24 48 and 72 hours In this paper we summarize theeffect of methanol extract (LE) of dried powdered leaves ofAaspera on global gene expression pattern in human pancreaticcancer cell line MIA PaCa-2 Using MetaCore software wenarrowed down the pathways affected in MIA PaCa-2 cellstreated with LE for three different time points

2 Materials and Methods

We have recently published the details about the col-lection authentication of Achyranthes aspera leaves and

the preparation of whole leaf extract [7 8] Briefly A asperaleaf powder was serially extracted in 100 hexane followedby 100 acetone over night at room temperatureThe acetoneextract was concentrated in a rotary evaporator The residuewas dissolved in 100 methanol and called leaf extract (LE)

21 Cell Lines and Culture Conditions Thehuman pancreaticcancer cell line MIA PaCa-2 (CRL-1420) was purchased fromATCC (USA) andmaintained in our laboratory in RPMI 1640medium supplemented with 10 FBS (Invitrogen USA) at37∘C in a humidified 5 CO

2atmosphere It was seeded in a

six-well plate at an initial density of 5 times 105 in 2mL mediumOvernight cultures were exposed to 34 120583gmL of LE for 2448 and 72 hours respectively Two percentmethanol exposedcells served as a control Control and experimental groupswere set up in duplicate

22 Isolation and Quality Control of Total RNA Total RNAwas prepared from control and LE treated MiaPaCa-2 cellsusing TriReagent (Sigma USA) At the end of the treatmentcells were directly lysed in TriReagent and total RNA isolatedFrom this point the rest of the gene expression relatedprocedures were performed at the microarray and geneexpression Core facility of the University of MiamiThe qual-ity of the extracted RNA was evaluated using BioAnalyzer2100 (Agilent Technologies CA) RNA samples with RNAintegrity number (RIN)ge9 have been used for themicroarrayexperiments [9]

23 cDNA Synthesis and RNA Labeling for Microarray Anal-yses Target RNA was amplified using Amino Allyl MessageAmp kit (Ambion USA) Amplified RNA from the controlgroup was labeled with Cy-3 and the test group with Cy-5dye (Amersham USA) Duplicate microarray hybridizationwas set up using biological replicates that were labeled bydye-swap that is control RNA was labeled with Cy-5 andtest RNA with Cy-3 The dye labeled cDNA samples werehybridized to the whole human genome microarray (Catno G4112F Design ID 014850 Agilent Technologies USA)We followed the experimental instructions provided by thekit supplier for RNA amplification cDNA preparation dyelabeling and array hybridization

24 Microarray Image Analyses and Data Processing Themicroarrays were scanned at 5120583mresolution using aGenePix4000B scanner (Molecular Devices USA) The scannedimages were analyzed with GenePix Pro 61 the softwarepackage provided by Molecular Devices USA Quality con-trol of the images was performed with Acuity 40 (Molec-ular Devices USA) software package The following qualitycriteria have been used (1) at least 90 of the pixels inthe spot had intensity higher than background plus twostandard deviations (2) less than 2 saturated pixels inthe spot (3) signal to noise ratio (defined as ratio of thebackground subtracted mean pixel intensity to standarddeviation of background) was 3 or above for each channel(4) the spot diameter was between 45 and 70 120583m (5) theregression coefficient of ratios of pixel intensity was 06or above and (6) feature has opposite change direction






3 Results






72 hr(3075)

24 hr(971)

48 hr(806)

2009

489

221

356

191

223

38










(a)











(a) Continued




(b)











OSBPL8VWF

KGFLP1 CYSLTR2






A 32 P103162

A 32 P192586

Il 2

A 24 P408981

A 24 P818378

A 24 P940375









Table 3 Continued














Table 3 Continued














1 2 3 4

1

2

3

4

5

6

7

8

9

10Maps













4 Discussion





B

CS


TRB

B

B

B

BB

TR TR TR

TR

TR

TR

TR

TR

TRTR

1

1

1

1









Acknowledgments




References
































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of





















3 Results






72 hr(3075)

24 hr(971)

48 hr(806)

2009

489

221

356

191

223

38










(a)











(a) Continued




(b)











OSBPL8VWF

KGFLP1 CYSLTR2






A 32 P103162

A 32 P192586

Il 2

A 24 P408981

A 24 P818378

A 24 P940375









Table 3 Continued














Table 3 Continued














1 2 3 4

1

2

3

4

5

6

7

8

9

10Maps













4 Discussion





B

CS


TRB

B

B

B

BB

TR TR TR

TR

TR

TR

TR

TR

TRTR

1

1

1

1









Acknowledgments




References
































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of

















72 hr(3075)

24 hr(971)

48 hr(806)

2009

489

221

356

191

223

38










(a)











(a) Continued




(b)











OSBPL8VWF

KGFLP1 CYSLTR2






A 32 P103162

A 32 P192586

Il 2

A 24 P408981

A 24 P818378

A 24 P940375









Table 3 Continued














Table 3 Continued














1 2 3 4

1

2

3

4

5

6

7

8

9

10Maps













4 Discussion





B

CS


TRB

B

B

B

BB

TR TR TR

TR

TR

TR

TR

TR

TRTR

1

1

1

1









Acknowledgments




References
































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of


















(a)











(a) Continued




(b)











OSBPL8VWF

KGFLP1 CYSLTR2






A 32 P103162

A 32 P192586

Il 2

A 24 P408981

A 24 P818378

A 24 P940375









Table 3 Continued














Table 3 Continued














1 2 3 4

1

2

3

4

5

6

7

8

9

10Maps













4 Discussion





B

CS


TRB

B

B

B

BB

TR TR TR

TR

TR

TR

TR

TR

TRTR

1

1

1

1









Acknowledgments




References
































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of

















(a) Continued




(b)











OSBPL8VWF

KGFLP1 CYSLTR2






A 32 P103162

A 32 P192586

Il 2

A 24 P408981

A 24 P818378

A 24 P940375









Table 3 Continued














Table 3 Continued














1 2 3 4

1

2

3

4

5

6

7

8

9

10Maps













4 Discussion





B

CS


TRB

B

B

B

BB

TR TR TR

TR

TR

TR

TR

TR

TRTR

1

1

1

1









Acknowledgments




References
































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of

















OSBPL8VWF

KGFLP1 CYSLTR2






A 32 P103162

A 32 P192586

Il 2

A 24 P408981

A 24 P818378

A 24 P940375









Table 3 Continued














Table 3 Continued














1 2 3 4

1

2

3

4

5

6

7

8

9

10Maps













4 Discussion





B

CS


TRB

B

B

B

BB

TR TR TR

TR

TR

TR

TR

TR

TRTR

1

1

1

1









Acknowledgments




References
































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of






















Table 3 Continued














Table 3 Continued














1 2 3 4

1

2

3

4

5

6

7

8

9

10Maps













4 Discussion





B

CS


TRB

B

B

B

BB

TR TR TR

TR

TR

TR

TR

TR

TRTR

1

1

1

1









Acknowledgments




References
































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of

















Table 3 Continued














1 2 3 4

1

2

3

4

5

6

7

8

9

10Maps













4 Discussion





B

CS


TRB

B

B

B

BB

TR TR TR

TR

TR

TR

TR

TR

TRTR

1

1

1

1









Acknowledgments




References
































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of

















1 2 3 4

1

2

3

4

5

6

7

8

9

10Maps













4 Discussion





B

CS


TRB

B

B

B

BB

TR TR TR

TR

TR

TR

TR

TR

TRTR

1

1

1

1









Acknowledgments




References
































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of

















B

CS


TRB

B

B

B

BB

TR TR TR

TR

TR

TR

TR

TR

TRTR

1

1

1

1









Acknowledgments




References
































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of


















References
































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of





















of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of
















Research Article Global Gene Expression Analyses Support...

Documents

Transcript of Research Article Global Gene Expression Analyses Support...