molecular signature and mechanisms of hepatitis d …...hepatitis d virus (hdv) promotes liver...

Genomics

Molecular Signature and Mechanisms of HepatitisD Virus–Associated Hepatocellular CarcinomaGiacomo Diaz1, Ronald E. Engle2, Ashley Tice2, Marta Melis2,Stephanie Montenegro2, Jaime Rodriguez-Canales3, Jeffrey Hanson3,Michael R. Emmert-Buck3, Kevin W. Bock4, Ian N. Moore4, Fausto Zamboni5,Sugantha Govindarajan6, David E. Kleiner7, and Patrizia Farci2

Abstract

There is limited data on the molecular mechanisms wherebyhepatitis D virus (HDV) promotes liver cancer. Therefore,serum and liver specimens obtained at the time of liver trans-plantation from well-characterized patients with HDV-HCC(n¼ 5) and with non-HCCHDV cirrhosis (n¼ 7) were studiedusing an integrated genomic approach. Transcriptomic profil-ing was performed using laser capture–microdissected (LCM)malignant and nonmalignant hepatocytes, tumorous and non-tumorous liver tissue from patients with HDV-HCC, and livertissue from patients with non-HCC HDV cirrhosis. HDV-HCCwas also compared with hepatitis B virus (HBV) HBV-HCCalone, and hepatitis C virus (HCV) HCV-HCC. HDVmalignanthepatocytes were characterized by an enrichment of upregu-lated transcripts associated with pathways involved in cell-cycle/DNA replication, damage, and repair (Sonic Hedgehog,GADD45, DNA-damage-induced 14-3-3s, cyclins and cell-cycle regulation, cell cycle: G2–M DNA-damage checkpointregulation, and hereditary breast cancer). Moreover, a largenetwork of genes identified functionally relate to DNA repair,

cell cycle, mitotic apparatus, and cell division, including 4cancer testis antigen genes, attesting to the critical role of geneticinstability in this tumor. Besides being overexpressed, thesegenes were also strongly coregulated. Gene coregulation washigh not onlywhen comparedwith nonmalignant hepatocytes,but also to malignant hepatocytes from HBV-HCC alone orHCV-HCC. Activation and coregulation of genes critically asso-ciated with DNA replication, damage, and repair point togenetic instability as an important mechanism of HDV hepa-tocarcinogenesis. This specific HDV-HCC trait emerged alsofrom the comparison of the molecular pathways identified foreach hepatitis virus–associated HCC. Despite the dependenceof HDV on HBV, these findings suggest that HDV and HBVpromote carcinogenesis by distinct molecular mechanisms.

Implications: This study identifies a molecular signature ofHDV-associated hepatocellular carcinoma and suggests thepotential for new biomarkers for early diagnostics. Mol CancerRes; 16(9); 1406–19. �2018 AACR.

IntroductionHepatocellular carcinoma (HCC) is the fifth most common

human cancer and the second leading cause of cancer-relateddeathworldwide (1). Although themajor etiologic agents and riskfactors for HCC are well defined, the molecular mechanismsof hepatocarcinogenesis remain elusive (2, 3). The increasing

incidence of HCC worldwide (4), along with the lack of earlydiagnostic markers and effective therapies, has made this diseaseone of themost challenging to control. Cirrhosis is the singlemostimportant risk factor, being present in 80% of individuals withHCC (5), and infection with hepatitis viruses account for over60% of all cases globally (5). The application of genomic tech-nologies has provided valuable tools to investigate the pathogen-esis of complex diseases using a global approach (6), and manystudies of gene expression on HCC-associated with hepatitis Bvirus (HBV; ref. 7) or hepatitis C virus (HCV; refs. 8, 9) have beenreported. However, there are no data on themolecular profiling ofhepatitis D virus (HDV)-associated HCC.

HDV is a unique defective RNA virus that requires the helperfunctionofHBV for viral assembly and in vivo transmission (10). Itis highly pathogenic and causes the least commonbutmost severeand rapidly progressive form of chronic viral hepatitis, leading tocirrhosis in about 80% of the cases within 10 years (11). HDV-related cirrhosismay be a stable disease formany years, but a highproportion of patients eventually die of hepatic decompensationor HCC unless they undergo liver transplantation (LT). However,the proportion of patients who will develop each of these long-term complications remains uncertain due to the lack of largeprospective studies on the natural history of HDV. In two longi-tudinal studies, the annual incidence rates were 2.5% and 2.7%for liver decompensation and 1% to 2.8% for HCC (12, 13).

1Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy.2Hepatic Pathogenesis Section, Laboratory of Infectious Diseases, NationalInstitute of Allergy and Infectious Diseases, NIH, Bethesda, Maryland. 3LaserCapture Microdissection Core Facility, Laboratory of Pathology, National CancerInstitute, NIH, Bethesda, Maryland. 4Infectious Disease Pathogenesis Section,Comparative Medicine Branch, National Institutes of Allergy and InfectiousDiseases, NIH, Bethesda, Maryland. 5Liver Transplantation Center, BrotzuHospital, Cagliari, Italy. 6Department of Pathology, Rancho LosAmigos Hospital,University of Southern California, Downey, California. 7Laboratory of Pathology,National Cancer Institute, NIH, Bethesda, Maryland.

Note: Supplementary data for this article are available at Molecular CancerResearch Online (http://mcr.aacrjournals.org/).

Corresponding Author: Patrizia Farci, Hepatic Pathogenesis Section,Laboratory of Infectious Diseases, National Institute of Allergy and InfectiousDiseases, NIH, Bethesda, MD 20892. Phone: 240-669-5921; Fax: 301-402-0524;E-mail: [email protected]

doi: 10.1158/1541-7786.MCR-18-0012

�2018 American Association for Cancer Research.

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Owing to the vital dependence ofHDVonHBV, the specific roleof HDV in promoting HCC remains to be fully elucidated. It isunknownwhetherHCC is the result of the underlying cirrhosis, ofa direct oncogenic effect of HDV, or of a cumulative effect of HBVandHDV. Access to a unique collectionof liver samples fromwell-characterized patients withHDV-associatedHCCwho underwentLT provided us with the opportunity to study the role of host andviral factors in HDV-associated HCC. Gene expression profilingwas performed on selected laser capture–microdissected (LCM)malignant and nonmalignant hepatocytes (hereafter abbreviatedas MH and NMH), and from multiple whole liver tissue (WLT)specimens obtained from the tumor and surrounding nontumor-ous tissue of individual livers containing HCC. Additional WLTspecimens were obtained from livers with non-HCCHDV cirrho-sis. Because HDV is invariably associated with HBV, we have alsocompared the gene expression profiles of patients withHDV-associated HCC with those from patients with HCC asso-ciatedwithHBV alone (7), aswell aswith those frompatientswithHCC associated with HCV, to identify distinct molecular signa-tures for each hepatitis virus-associated HCC, which may shednew light on pathogenesis and facilitate the discovery of newbiomarkers for the early detection of these deadly tumors.

Materials and MethodsPatients

Multiple liver specimens and serum were obtained from acohort of 5 male patients, aged 57 � 3 years (mean � SEM) whounderwent LT forHDV-associatedHCC, and 7patients, 3 females,and 4males, aged 56�1 years, withHDVnon-HCC cirrhosis whounderwent LT for end-stage liver disease. For comparative pur-poses, the study also included liver specimens from 11 patients,1 female, and 10 males, aged 56.7 � 3.6 years, with HCV-associated HCC who underwent LT, and from 11 patients withHBV-associated HCC, all males, aged 60 � 8 years, whose datawere included in a recent report (7). All patients were followedbetween 2004 and 2009 at the Liver Transplantation Center of theBrotzu Hospital in Cagliari, Italy. The patient characteristics aredescribed in the Results section. All patients provided writteninformed consent, and the protocol was approved by the ethicalCommittee of the Hospital Brotzu (Cagliari, Italy). The study wasalso approved by the Office of Human Subjects Research of theNIH, granted on the condition that all samples were deidentified.

Liver pathologyLiver biopsies were evaluated blindly by two expert hepato-

pathologists (S. Govindarajan and D.E. Kleiner). For each liverbiopsy specimen, activity grade, and stage of fibrosis were estab-lished according to Ishak scoring system (14). The grade of tumordifferentiation was evaluated according to the Edmondson andSteiner grading system (15).

Serologic and virological assaysSerologic markers of infection with hepatitis viruses were

available for all patients at the time of LT or partial hepatectomy.HBsAg, anti-HBs, anti-HBc, IgM anti-HBc, HBeAg, anti-HBe,antibody to HCV (anti-HCV), and antibody to human immuno-deficiency virus (anti-HIV) were measured with a commercialenzyme immunoassay (Abbott Laboratories). Antibodies againsthepatitis delta antigen (HDAg), IgG, and IgM anti-HD, weremeasured using commercial enzyme immunoassays (Sorin

Biomedica). Serum HBV DNA was quantified by a commercialassay (Amplicor, HBV Monitor test; Roche Diagnostics). SerumHCV RNAwasmeasured by a commercial assay (Cobas AmplicorHCV Monitor 2.0, Roche Diagnostics). Serum HDV RNA wasevaluated by PCR as reported previously (16).

Quantification of liver HDV RNA by real-time PCRTotal RNA was extracted from stored frozen liver specimens

using QIAzol (Qiagen) reagent according to the manufacturer'srecommendations, and RNA quality and integrity were assessedusing the RNA 6000 Nano assay on the Agilent 2100 Bioanalyzer.HDV RNA was measured by TaqMan, as described previously(17), with cycling conditions based on themanufacturer's recom-mendations; the forward, reverse primer, and probe concentra-tions were 900, 900 and 225 nmol/L, respectively. The primersand probe were: forward primer GAC CCG AAG AGG AAA GAAGGA (position 894), reverse complementary primer AGA GTTGTC GAC CCC AGT GAA TAA (position 971) and MGB probe6-FAM-CGA GAC GCA AAC CTG TGA (position 917). A second-ary quantity standard was developed on the basis of a plasmidgenerously provided by Dr. John Taylor (Fox Chase CancerCenter, Philadelphia, PA). HDV RNA quantity was expressed asgenome equivalents (GE) per ng of total RNA.

Quantification of liver HBV DNA by real-time PCRHBV DNA in liver was quantified using a modification of a

previously describedmethod (7). The primers/probewere locatednear the 50 end of the S gene. Each 20-mL reaction contained 50ngof DNA, 45 pmol of forward (50- GGA CCC CTG CTC GTG TTACA-30) and reverse (30- TTG AGAGAAGTCCACCACGAG TC-50)primers, 12.5 pmol of nonfluorogenic-quenched probe (6FAM-TGT TGA CAA GAA TCC TCA), and TaqMan Fast Universal PCRMaster Mix (Applied Biosystems). PCR was performed using anABI PRISM 7900HT Sequence Detection System (Applied Biosys-tems). Conditions included incubation at 95�C for 20 secondsfollowed by 45 PCR cycles of 1 second at 95�C and 20 seconds at60�C. Viral titers were expressed as log10 GE per ng of DNA.

Detection of intrahepatic HDV and HBV markers by IHCFormalin-fixed, paraffin-embedded liver biopsy sections from

five paired liver biopsies obtained from both the tumor and thesurrounding nontumorous tissue of five patients with HDV-associated HCC, and 14 liver biopsies obtained from 7 patientswith non-HCC HDV cirrhosis, including one biopsy from theright and one from the left lobe of the cirrhotic liver, were stainedfor intrahepatic HBsAg, HBcAg, and HDAg. HBsAg (Thermopredilute, clone 3E7) and HBcAg (Dako B0586, 1:500) stainswere performedon a Ventana BenchmarkUltra.HDAg stainswereperformed by manual staining using a high titer patient serumdiluted at 1:1,000 and detected using a biotinylated goat anti-human IgG (1:200, Vector Laboratories). Detection was per-formed using an avidin–biotin complex and diaminobenzidinechromagen.

Gene expression profilingWhole liver tissue. To investigate the molecular heterogeneitywithin and outside the tumor of HDV-associated HCC, we ana-lyzed from each patient with HCC one liver specimen obtainedfrom the tumor and one from the surrounding nontumoroustissue (Supplementary Fig. S1A and S1B). In addition, we had theunique opportunity to study multiple liver specimens from 2 of

Genomics of HDV-HCC Suggests Potential Drivers

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the 5patients (patients 104 and 129), including 5 specimens fromthe tumor and 12 from the surrounding nontumorous areas takenin all 4 directions, which for simplicity we defined north, south,east, and west, and at different distances from the center of thetumor (Supplementary Fig. S1C). Specifically, 5 biopsies weretaken from the tumor, one at the center (area A) and 4 in theperiphery of the tumor (area B) in all 4 directions; 4 were takenfrom the perilesional area (area C); 4 were taken 2–3 cm from thetumor (area D); and 4 from the edges of the liver (area E). In total,the whole liver tissue (WLT) samples collected from the patientswith HDV included 11 from the tumor and 24 from the non-tumorous tissue. In addition, we also studied liver specimensobtained from the right and the left lobe of 7 patients with non-HCC cirrhosis for a total of 29 specimens (SupplementaryFig. S1D). Each liver specimen was divided into two pieces: onewas snap-frozen formolecular studies and theotherwas formalin-fixed and paraffin-embedded (FFPE) for pathologic examination.Importantly, FFPE sections obtained from the tumor or theperilesional area were also observed microscopically to check thehomogeneous histologic composition of the samples. A mixedpopulation of malignant and nonmalignant hepatocytes wasfound only in two sections, and the corresponding frozen liverspecimens were excluded from microarray analysis.

Laser capture microdissection. Because the liver contains a hetero-geneous cell population, gene expression profilingwas performedonMHandNMHisolated by laser capturemicrodissection (LCM)in all 5 HDV-associated HCC livers. For each patient, two pairedsamples for LCMwere obtained, one from the center of the tumorand one from the most distant nontumorous tissue (Supplemen-tary Fig. S1E and S1F). We optimized the LCMmethod as recentlyreported (7) based on the procedure described by Erickson andcolleagues (18).

HBV- and HCV-associated HCC samplesTo further elucidate the role of HDV in hepatocarcinogenesis,

data from HDV-associated HCC were compared with the datafrom 11 patients with HCV-associated HCC and 11 patients withHBV-associated HCC (7). HCV-HCC data included 44 WLTsamples from the tumor and 31 from the nontumorous tissue,and 9 paired LCM samples of MH and NMH. HBV-HCC dataincluded 39 WLT samples from the tumor and 81 from thenontumorous tissue, and 10 paired LCM samples of MH andNMH.

Gene expression profilingAll liver specimens were analyzed by microarray using Affyme-

trix Human U133 Plus 2.0 arrays (Affymetrix), which contain54,675 transcripts representing approximately 27,000 uniquehuman genes. Total RNA from WLT was extracted from frozenliver specimens as described previously (19) using TRIzol reagent(Invitrogen) according to the manufacturer's recommendations;total RNA from microdissected hepatocytes was extracted usingthe Arcturus PicoPure RNA Isolation Kit (Life Technologies), asreported previously (7). The specimens used for RNA extractionand LCM were derived from the same frozen liver samples. TotalRNA quality and integrity were assessed using the Agilent 2100Bioanalyzer. To maintain comparability between LCM and WLT,gene expression profiling was performed using the same tech-nique as reported previously (19). Total liver RNA (50 ng)obtained from WLT and microdissected hepatocytes was

subjected to two successive rounds of amplification (20), andthe resultant RNA was then subjected to biotin labeling, hybrid-ization, staining, washing, and scanning procedures according tostandard Affymetrix protocols. All microarray datasets are avail-able at the following Gene Expression Omnibus link: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc¼GSE107170

Statistical analysisMicroarray data were analyzed using BRB-Array Tools Version

4.2 (21). Microarray raw data (CEL files) were summarized andnormalized by the RMA method. Transcripts showing minimalvariation (less than 1.5-fold deviations from the median in morethan 80% of the arrays) were excluded from the analysis. Afterfiltering, only 7,000 genes were eligible for subsequent analyses.Differentially expressed genes were identified by comparing thetumor versus the nontumorous tissue, orMHversusNMH,using at test with a FDR <10%. Gene expression fold changes werecalculated as the ratio between the geometric means of tumorand nontumorous tissues, or between MH and NMH. Statisticaltests and heatmaps were performed using single patients as unitdata. All methods were identical to those applied to the micro-array data analysis of patients with HBV-HCC (7). Multidimen-sional scaling was performed using individual samples from eachpatient. Pathway and network analysis was performed usingIngenuity Pathway Analysis (IPA, v 9.0, Qiagen Redwood City,www.qiagen.com/ingenuity). The association of genes to path-ways was evaluated as the ratio between the number of genespresent in the dataset and the total number of genes that map tothe same pathway. The Fisher exact test was also used to calculatethe probability of such association. Additional gene annotationswere obtained from theMolecular SignatureDatabase (Hallmark,Reactome andGeneOntology BP gene sets, available from http://www.broadinstitute.org/gsea/msigdb). Clusters of coregulatedgenes were investigated by the t-distributed stochastic neighborembedding (t-SNE) method (22) that enables a dimensionalityreduction more defined than other classical methods such asprincipal component analysis or multidimensional scaling, andhas been already successfully applied to transcriptomic data(23, 24). For t-SNE, we used the Rtsne function available fromthe CRAN repository (25), with the following parameters:perplexity ¼ 20, number of PCA components before t-SNE ¼5, and number of iterations ¼ 10,000.

IHC staining for BRCA1 and H2AFXFormalin-fixed, paraffin-embedded human liver biopsy sec-

tions were labeled with mouse monoclonal anti-BRCA1(MS110) from Millipore-Sigma and rabbit polyclonal anti-H2AFX (Ab A11361) from ABclonal. Staining was carried outon the Bond RX (Leica Biosystems) platform according tomanufacturer-supplied protocols. Briefly, 5-mm-thick sectionswere deparaffinized and rehydrated. Heat-induced epitoperetrieval (HIER) was performed using Epitope Retrieval Solu-tion 1, pH 6.0, heated to 100�C for 20 minutes. The specimenwas then incubated with hydrogen peroxide to quench endog-enous peroxidase activity prior to applying the primary anti-body. Both primary antibodies were applied at a dilution of1:200. Detection with DAB chromogen was completed usingthe Bond Polymer Refine Detection kit (Leica Biosystems),which included a hematoxylin counterstain. Slides were finallycleared through gradient alcohol and xylene washes prior tomounting and coverslipping.

Diaz et al.

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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE107170



www.qiagen.com/ingenuity

http://www.broadinstitute.org/gsea/msigdb

http://www.broadinstitute.org/gsea/msigdb


ResultsThe demographic, clinical, serologic, and virologic features of

the 12 individuals with HDV-associated liver disease, including5 patients with HCC and 7 with non-HCC cirrhosis, are reportedin Table 1.None of the featureswere statistically different betweenthe two groups of patients, except for a lower number of plateletsin those with non-HCC cirrhosis who underwent LT for end-stageHDV liver disease. Chronic hepatitis D is typically associated withsplenomegaly (10). All patientswere positive for serumHDVRNAand IgG anti-HDV, whereas IgM anti-HD was positive in 3 of 5patients with HCC and in all patients with HDV non-HCCcirrhosis. Regarding the serologic HBV profile, there was nodifference between the two groups with HDV-associated disease.All were positive for hepatitis B surface antigen (HBsAg), antibodytohepatitis B core antigen (anti-HBc) andantibody tohepatitis B eantigen (anti-HBe), andnegative for hepatitis B e antigen (HBeAg)and antibody toHBsAg (anti-HBs). The levels of serumHBVDNAwere very low in all cases (Table 1). The activity grade and stage of

fibrosis of the surrounding nontumorous tissue are reportedin Table 1, and there were no significant differences between thetwo groups. The grade of tumor differentiation was G3 in 4patients, and G2 in the remaining patient. The tumor size wasless or equal to 3 cm in 3 patients and larger than 3 cm in theremaining 2 patients. The clinical and histopathologic features ofthe 11 patients with HBV-associated HCC have been reportedpreviously (7), whereas those from the 11 patients withHCV-associated HCC are shown in Table 1. The higher activitygrade seen in patients with chronic hepatitis D compared withthose with chronic hepatitis C (Table 1) confirmed that HDVinduces the most severe form of chronic viral hepatitis (10).

HDV RNA and HBV DNA levels in different areas of liverscontaining HCC and in controls with non-HCC HDV cirrhosis

The levels ofHDVRNAwithin the tumorwere lower than in thesurrounding nontumorous tissue in 2 patients (patient 104 and129) in whom up to 16 and 17 liver specimens (SupplementaryFig. S1C), respectively, were available for intrahepatic HDV RNA

Table 1. Demographic, clinical, serologic, virological, and pathologic features of the 12 individuals with HDV-associated liver disease, including 5 patients with HCCand 7 with non-HCC cirrhosis, and the 11 individuals with HCV-associated HCC

HDV- associated HCC HDV- associated non-HCC cirrhosis HCV- associated HCC

Patients, no. 5 7 Patients, no. 11Age, y 57 � 3 56 � 1 Age, y 58 � 4Male, no. (%) 5 (100) 4 (57) Male, no. (%) 10 (90.9)Alanine aminotransferase, U/La 87 � 25 78 � 23 Alanine aminotransferase, U/La 81 � 13Aspartate aminotransferase, U/Lb 82 � 21 81 � 14 Aspartate aminotransferase, U/Lb 86 � 16g-glutamyltransferase, U/Lc 98 � 22 67 � 20 g-glutamyltransferase, U/Lc 104 � 26Prothombin time, INRd 1.4 � 0.0 1.6 � 0.1 Prothombin time, INRd 1.4 � 0.1Total bilirubin, mg/dLe 2.3 � 1.3 2.4 � 0.4 Total bilirubin, mg/dLe 1.9 � 0.5Platelets (103/mL)f 101.4 � 16.1j 53.6 � 11.5 Platelets (103/mL)f 138.8 � 24a-fetoprotein, ng/mgg 17.4 � 10.5 13.0 � 6.2 a-fetoprotein, ng/mgg 898 � 495Liver pathology Liver pathologyNontumorous tissueh Nontumorous tissueh

Activity grade 9.1 � 1.1 11.0 � 1.6 Activity grade 6.9 � 0.8Fibrosis stage 6.0 � 0.0 6.0 � 0.0 Fibrosis stage 5.2 � 0.5F5, no. 0 0 F5, no. 2F6, no. 5 7 F6, no. 8

Tumor gradei Tumor gradei

G2, no. 1 G2, no. 5G2/G3, no. 0 G2/G3, no. 1G3, no. 4 G3, no. 5

Tumor size Tumor size�2 and � 3 cm, no. 3 �2 and � 3 cm, no. 6>3 cm, no. 2 >3 cm, no. 5

Serum HDV RNA positive, no. 5 7 Serum HCV RNAk

IgG anti-HDag positive, no. 5 7 positive, no. 9IgM anti-HD positive, no. 3 7 negative, no. 1Serum HBV DNA (Log10 IU/mL) 1.6 � 0.4 1.7 � 0.3 Anti-HCV positive, no. 11

HCV genotypel

1a/1B, no. 72a/2c, no. 14 1

NOTE: Plus–minus values are means � SEM.aNormal range, �43 UI per liter.bNormal range, �42 UI per liter.cNormal range, �38 UI per liter.dNormal range, 0.80–1.20 international normalized ratio (INR).eTo convert serum bilirubin values to micromoles per liter, multiply by 17.1.fNormal values range � 159–�388 (103/mL).gNormal range, <10.0 ng/mL.hThe degree of activity and stage of fibrosis were assessed according to Ishak scoring system (14)iThe tumors were graded using the Edmondson–Steiner grading system (15).jStatistically significant difference between HDV-HCC and HDV-non-HCC (P ¼ 0.032).kDetermined in 10 patients out of 11.lDetermined in 9 patients out of 11.






testing (Fig. 1A). This decrease in HDV replication was observedbetween the periphery of the tumor and the perilesional area,whereas no changes were documented in the different areas of the

surrounding nontumorous areas. The levels of HDV RNA tendedto be higher in non-HCC cirrhosis compared with patients withHCC, with no differences among different liver areas, spanning

Figure 1.

HDV RNA and HBV DNA in tumor and nontumorous tissuesof liver containing HDV-associated HCC and IHC staining of HDVand HBV markers. A, HDV RNA levels in tumorous andnontumorous tissues of individual patients with HCC. B, HDVRNA in the left and right lobes of individual controls withnon-HCC HDV cirrhosis. C, HBV DNA levels in tumorous andnontumorous tissues of individual patients with HDV-associatedHCC. D, HBV DNA in the left and right lobes of individualcontrols with non-HCC HDV cirrhosis. In all plots, bars indicatethe mean � SEM. E, Staining for HBsAg and HDAg within thetumor and in the surrounding nontumorous tissue, and in arepresentative control with non-HCC HDV cirrhosis. The whitearrow indicates a positive nuclear staining for HDAg.

Diaz et al.





both the right and left lobes (Fig. 1B). The levels of intrahepaticHBV DNA were markedly lower in all patients with HDV, includ-ing both patients with HCC and non-HCC cirrhosis (Fig. 1C andD). In contrast, the levels of HBV DNA in patients with HBV-associated HCC were consistently higher than in patients withHDV-HCC, both within and outside the tumor (SupplementaryFig. S7).

Intrahepatic HDV and HBV markersAmong patients with HDV-associated HCC, IHC staining for

HBsAg, HBcAg, and HDAg showed absence of HBcAg staining inall but one patient, a finding consistent with the typically lowlevels of HBV replication in patients with chronic HDV infection(10).Within theHDV tumor,HBsAg andHDAgwere detected in 2and 3 patients, respectively, whereas the prevalence of thesemarkers was higher in the surrounding nontumorous area as wellas in non-HCC cirrhosis (Table 2; Fig. 1E).

Differential gene expression in WLT and LCM tumor samplesAn unsupervised multidimensional scaling (MDS) using all

genes (about 7,000) that passed the filtering criteria showed aclear separation between tumorous and nontumorous areasfrom WLT samples, as well as between MH and NMH fromLCM samples (Fig. 2A). However, only a relatively small num-ber of genes were found to be differentially expressed in tumorsamples from WLT (n ¼ 385, listed in Supplementary TableS1A) and LCM (n ¼ 547, listed in Supplementary Table S1B)with a prevalence of downregulated genes in both cases (Fig.2B). No significant changes were found between differentnontumorous areas (Fig. 2E). Conversely, an abrupt changewas detected between the tumor and nontumorous areas, justoutside of the tumor boundaries (Fig. 2E). The gene expressionprofile of nontumorous areas was very similar to that of liversof patients with HDV cirrhosis without HCC (Fig. 2D), con-sistent with the presence of cirrhosis in the surrounding non-tumorous tissue.

Approximately 50% of the genes differentially expressed inWLT samples were also differentially expressed in LCM samples.Interestingly, the fold changes of all genes common to WLT andLCM samples were closely correlated (R2 ¼ 0.97; Fig. 2C).

Molecular pathways of HDV-associated HCCThe 20 top-scored pathways associated with MH genes in

HDV-associatedHCC are shown in Fig. 3A, and all genes includedin these 20 pathways are shown in Supplementary Fig. S2. Thetop-scored pathway was represented by hepatic fibrosis andhepatic stellate cell activation (P ¼ 0.00015), with all genesdownregulated, suggesting that the extracellular matrix produc-tion was indeed inhibited in the tumor. The second pathway wasSTAT3 (P¼ 0.0005), which plays an important role in the normaldevelopment, as well as in the regulation of cancer metastases(26). However, the most significant finding was represented by agroup of 6 pathways (sonic hedgehog, GADD45, DNA damage-induced 14-3-3s, cyclins, and cell-cycle regulation, cell cycle: G2–

M DNA damage checkpoint regulation, hereditary breast cancer;P values ranging between 0.0008 and 0.016), with a majority(80%) of upregulated genes, involved in several interrelatedfunctions inherent to cell cycle/DNA replication, damage, andrepair (e.g., BARD1, BRCA1, CCNA2, CCNB1, CCNE2, CDK1,CDKN2C, GSK3B, H2AFX, MSH2, NPM1, PRKDC and TOP2A).We also identified additional genes not included in the 6 molec-ular pathways but functionally related to cell kinetics and mitoticapparatus (ANLN, ASPM, BUB1B, CASC5, CDCA3, CDK5R1,CDKN1C, CENPJ, CENPF, CEP55, CENPW, DSCC1,FEN1,HMMR, KIF20A, MAP2K3, MAP3K9, MELK, MPHOSPH9,NCAPD2, NDC80, NEK2, NUF2, PRC1, RMI1, RPS27, TAF10,TRIP13 and TTK). Some of these genes (CDK1, H2AFX, TOP2A,FEN1, KIF20A, MELK, NCAPD2, PRC1, RMI1, TRIP13 and TTK)have been also associated with chromosome instability andcorrelated with enhanced tumor progression, early tumor recur-rence and poor survival of patients with HCC (27, 28). Consid-ering that the majority of genes are downregulated in HDV-HCC,it is worth noting that the vast majority (88%) of this subset ofgenes were upregulated.

Because HDV is a defective virus that always coexists with HBV,we also investigated the molecular pathways identified in MHderived from patients with HCC associated with HBV alone. Inaddition, the availability of liver specimens from well-character-ized patients with HCV-associated HCC provided us with theunique opportunity to extend the analysis of the pathways also toMH derived from HCV-associated HCC. Remarkably, among the

Table 2. Detection of HBsAg, HBcAg, and HDAg in liver tissue of patients with HDV-associated HCC, both in tumor and nontumorous area, and in patients withnon-HCC HDV cirrhosis

Tumor NontumorHCC Patient no. HBsAg HBcAg HDAg HBsAg HBcAg HDAg

5 0 0 0 1 0 119 3 0 1 1 0 227 1 0 1 1 0 1104 0 0 1 1 0 2129 0 0 0 2 0 0

Total positive patients (%) 2/5 (40) 0/5 3/5(60) 5/5(100) 0/5 4/5(80)

Left lobe Right lobeNon-HCC Patient no. HBsAg HBcAg HDAg HBsAg HBcAg HDAg

6 0 0 0 NA NA NA73 1 0 3 1 0 290 1 0 1 1 0 1113 1 0 0 1 0 0134 2 1 1 1 1 1152 2 0 1 1 0 1177 1 0 1 1 0 1

Total positive patients (%) 6/7 (86) 1/7 (14) 5/7 (71) 6/6 (100) 1/6 (17) 5/6(83)

NOTE: 0, no staining; 1, <10% positive; 2, 10%–50% positive; 3, >50% positive.Abbreviation: NA, not available.






Figure 2.

A, Unsupervised multidimensional scaling (MDS) plot of WLT and LCM samples obtained from HDV-associated HCC livers. The plot shows a completeseparation between tumor and nontumor liver samples. In addition, WLT samples denote a greater dispersion in both groups, which is consistent with thegreater heterogeneity of WLT compared with LCM hepatocytes. B, Pie charts showing the number of upregulated and downregulated genes identified in WLTand LCM samples of HDV-associated HCC. C, Correlation of fold changes of differentially expressed genes in both LCM andWLT samples fromHDV-associated HCC.Fold changes were calculated as the ratio between malignant and nonmalignant hepatocytes (LCM) or between tumor and nontumorous samples (WLT).Red and green points represent upregulated and downregulated genes, respectively. D and E, Heatmaps of the 385 genes differentially expressed in WLT samplesfrom HDV-associated HCC. D, Tumor and nontumor tissues of 5 patients with HDV-HCC and, for comparative purposes, of 7 patients with HDV-associatedcirrhosis without HCC. E, Multiple samples of two patients with HDV-HCC, obtained from the center and the periphery of the tumor (heatmap columns A andB, respectively), and from the nontumorous tissue at increasing distances from the tumor (heatmap columns C, D, E). Gene expression levels were log2-transformedand row-wise standardized. Upregulated genes are shown in shades of red; downregulated genes in shades of green.

Diaz et al.





6 pathways involved in cell cycle/DNA replication, damage, andrepair detected in HDV-MH, two (GADD45 and cell cycle) werealso found in HCV-MH, while none of them was found inHBV-MH. Thus, despite the dependence of HDV on HBV, ourfindings suggest that the molecular signature of HDV-HCC ismarkedly different from that of HBV-HCC and that geneticinstability is a specific feature of HDV-associated HCC. Themolecular pathways of HBV-MH were primarily associated withmetabolic processes, retinoic acid receptor, cell remodeling, andmotility functions (Fig. 3B). Pathways associated with retinoicacid receptor functionswere also found inHCV-MH, but only twoof them were in common with HBV-MH. Moreover, HCV-MHshowed several amino acid degradation pathways, all withmostlydownregulated genes (Fig. 3C). A synopsis of the pathwaysidentified in MH derived from the three tumors is shown inSupplementary Fig. S3.

The BRCA1 network in HDV-associated HCCAmong the 20 top-scored pathways detected in HDV-associat-

ed HCC, hereditary breast cancer signaling was one of the mostclosely associated with various common tumors (breast, ovarian,prostate, and colorectal). Thus, we extended the analysis toinvestigate the network of genes functionally associated withBRCA1, one of the most studied genes in breast cancer suscepti-bility, which is involved inDNAdamage repair, regardless of theirinclusion in the hereditary breast cancer pathway. A large number(88%) of genes associated with the BRCA1 network were found tobedifferentially expressedbyMHinHDV-associatedHCC(Fig. 4).In contrast, this pathway did not emerge in the other viralassociated HCC, and BRCA1 was not differentially expressed inHBV- HCC nor in HCV-HCC, highlighting its specific associationwith HDV-HCC.

Gene coregulation in HDV-associated HCCGene co-regulationwas visualized using the t-SNE (22) applied

to all 547 genes differentially expressed in HDV MH. The t-SNEplot showed a prominent clustering of 37 genes involved in cellproliferation and DNA damage/repair (Fig. 5). Interestingly, thecluster included BRCA1, BARD1, and MSH2, which were alreadyfound in the 6 related pathways, and HMMR, an oncogeneassigned by IPA to a different top-scored pathway (glioma inva-siveness signaling, see Supplementary Fig. S3), but also implicat-ed in the progression of several tumors by promoting genomicinstability in association with BRCA1 and BARD1 (29). It isworth noting that all 37 clustered genes were upregulated. Thecomparison with HDV-NMH showed that 11 genes, includingBRCA1, BARD1, TIMELESS, DSCC1, and MSH2, were not clus-tered in NMH (Fig. 5, top inset). This suggests that, in addition tooverexpression, coregulation of this subset of genes is a specifictrait of HDV-MH. Next, the coregulation of these 37 genes wasalso investigated in HBV-MH and HCV-MH, although 4 impor-tant genes, BRCA1, BARD1, TIMELESS, and DSCC1, were notdifferentially expressed in HBV-MH, and BRCA1 was not differ-entially expressed in HCV-MH. The t-SNE plots showed that the37 genes were less intensely clustered in both HBV-MH andHCV-MH (Supplementary Fig. S4). This suggests that genes involved inthemaintenance of genome stability, DNA replication, and repairare more upregulated and coregulated in HDV-MH comparedwith HBV- and HCV-MH. A possible interpretation of thesefindings is that in HBV- and HCV-MH, these genes may beinvolved in different functions, not strictly associated to the

functions identified forHDV-MH. This hypothesis is in agreementwith the differences observed at the level of molecular pathways.

Among the 37 genes of the HDV cluster, we also found threecancer testis antigen (CTA) genes, all closely related to the spindle-centromere complex: NUF2 (component of the NDC80 kineto-chore complex), CEP55 (centrosome component), and TTK(essential for chromosome alignment at the centromere duringmitosis).However, theseCTA geneswere upregulated inMHof allthree tumors (7). A fourthCTA gene,CASC5 (required for creationof kinetochore-microtubule attachments and chromosome seg-regation), not comprised in the cluster, was upregulated in HDV-but not in HBV-MH nor in HCV-MH. To the best of our knowl-edge, this is thefirst time thatCASC5 is found tobe associatedwithhuman HCC.

None of the 5 genes (HN1, RAN, RAMP3, KRT19, and TAF9)proposed by Nault and colleagues (30) to predict patient survivalafter HCC resection was found to be differentially expressed inMH. However, no HCC case was related to HDV infection in thatstudy. This finding further confirmed the presence of specific traitsin the gene expression profile of HDV-associated HCC.

Twenty-five paired liver biopsies obtained fromboth the tumorand the surroundingnontumorous tissueof all patientswith viral-associated HCC were stained for BRCA1 and H2AFX. A very weaknuclear BRCA1 positivity was found only in 1 (4%) tumor sampleand in 5 (20%) nontumorous samples. Similar data wereobtained forH2AFX,which showedonly aweak nuclear positivityin 7 (28%) tumor samples and in 2 (8%) nontumorous samples.No significant differences were found between HDV, HBV, andHCV HCC samples.

Genes identified in WLT but not in MH (LCM)We also investigated the genes that were expressed in WLT, but

not in microdissected malignant hepatocytes, which we referredto as "WLT-unique" genes. The WLT-unique genes in HDV-HCCwere nearly 50% of the total number of WLT genes (Supplemen-tary Fig. S5A). The 20 top-scored pathways of WLT-unique geneswere mainly associated with biosynthetic pathways (spermine,spermidine, inosine-50-phosphate, serine, and glycine) with100% of the genes upregulated, as well as with IFN signaling anddegrading processes (GAGs, glycerol, ceramide), with genes prev-alently downregulated (Fig. 3D). Conversely, the WLT-uniquegenes of HBV-HCC were only 26% of the total number of WLTgenes (Supplementary Fig. S5B). Among the 20 top-scored path-ways identified, only one (the superpathway of serine and glycinebiosynthesis I) was in common with the pathways of HDV WLT-unique genes (Figs. 3D and 2E; Supplementary Fig. S6). However,in HDV-HCC the genes of this pathway were all upregulated,whereas in HBV the genes were all downregulated. Other path-ways identified inHBVWLT-unique geneswere involved in aminoacid biosynthesis and degradation, LXR/RXR activation, extrinsicand intrinsic prothrombin activation, coagulation system, acutephase response signaling and amino acid (arginine, glutamate)biosynthesis, all with 100% of genes downregulated. Only twobiosynthetic pathways showed a minority of upregulated genes.The WLT-unique genes of HCV-HCC were 62% of the totalnumber of WLT genes (Supplementary Fig. S5C). The 20top-scored pathways (Fig. 3F; Supplementary Fig. S6) included12 pathways associated with cytokine signaling and immuneresponse, with the vast majority of genes downregulated. Thesedata further confirmed the differences in gene expression profilingbetween HDV-, HBV-, and HCV-associated HCC.






Figure 3.

Top-scored canonical pathways of genes differentially expressed in LCM samples (malignant hepatocytes, MH, top row) and genes differentially and uniquelyexpressed inWLT samples (bottom row) obtained fromHDV-, HBV-, and HCV-HCC.A, Themost significant pathways of HDV-MH are represented by hepatic fibrosisand hepatic stellate cell activation, followed by pathways mostly involved in cell-cycle/DNA replication, damage, (Continued on the following page.)

Diaz et al.





DiscussionIn this study, we characterized the molecular signature of

HDV-associated HCC using an integrated analysis of microarraydata obtained from LCM-isolated MH and NMH, and from WLTsamples. By LCM and WLT, we identified a number of genes withstrongly correlated fold changes (R2 ¼ 0.97), indicating that asignificant proportion of genes expressed by MH may also beidentified in WLT, despite the presence of a heterogeneous cellpopulation within the liver tissue. On the other hand, about twothirds of MH genes were not identified in WLT samples, and thisunderlines the importance of using LCM to unravel genes asso-ciatedwithmalignant cells. The different origin of genes identifiedin LCM (attributable to MH) and genes uniquely identified inWLT (attributable to nonmalignant hepatocytes, Kupffer cells,stromal cells, vascular cells, cholangiocytes, stellate cells, lympho-cytes, polymorphonuclear leukocytes, and macrophages) is sup-ported by critical differences between the functional profiles ofLCM vs.WLT. Four independent analyses ofMH genes (canonicalpathways, biological functions, relational networks and coregula-tion clusters) indicated that the proliferation of tumoral cells isassociated with dysregulation of genes that control genomeinstability, whichmodulates themechanisms that recognizeDNAdamage, prevent cells with damaged DNA from entering mitosisor promote DNA repair. Several pathways (GADD45; DNA dam-age-induced 14-3-3s; cell cycle: G2–M DNA damage checkpointregulation; hereditary breast cancer) and in particular 5 genes(BRCA1, BARD1, HMMR, MSH2, and RMI1) were significantlyinvolved in these crucial processes. BRCA1 and BARD1 form acomplex that is required for arresting cells inG1/S followingDNAdamage (31). HMMR (alias RHAMM) is upregulated in manyhuman tumors and is associated with BRCA1 and BARD1. Suchassociation dysregulates theHMMR control of the normalmitoticspindle, whichmay promote tumor progression (29).BRCA1 alsointeracts with MSH2 to participate in the formation of the BASCcomplex, which recognizes and repairs damaged DNA structures(32). RMI1 (alias BLAPT75) is involved in the control of genomeinstability in association with TOP3 topoisomerase III (33). Wealso found that a large majority (88%) of genes in the BRCA1network were differentially expressed in MH. A comparison withHBV-associated HCC, using data from a previous study (7),showed that BRCA1 and BARD1were not differentially expressedin HBV-MH. Likewise, BRCA1 was not differentially expressed inMH of HCV-associated HCC. However, upregulation was not theonly feature of genes associated with genomic instability in HDV-

HCC. A second important feature was the coregulation of a largecluster of 37 genes, including BRCA1, BARD1HMMR, andMSH2,associated with the cell cycle. Conversely, HBV-MH andHCV-MHexhibited a lower level of coregulation of genes associated withcell cycle.

A 25-gene signature associated with chromosome instability(CIN) has been identified by Carter (34) in various tumors,predominantly breast and ovarian carcinomas, and recently alsoin human HCC (28). The CIN25 signature was associated withenhanced tumor progression, early tumor recurrence, and poorsurvival of patients with HCC (28), but the etiology of HCC caseswas not indicated. We found that 9 of the 25 CIN genes (MELK,TOP2A, PRC1, KIF20A, CDK1, TTK, FEN1, TRIP13, NCAPD2) aredifferentially expressed in HDV-HCC. Moreover, all these genes,with the only exception ofNCAPD2, were present in the cluster ofcoregulated genes that characterizes and differentiates HDV-HCCfromHBV- andHCV-HCC. Surprisingly, BRCA1was not includedin the CIN25 signature, although the general consensus thatBRCA1 is associated with genomic instability (35, 36), as alsoreflected by its full name "BRCA1, DNA Repair Associated." Theabsence of BRCA1 from the CIN25 signature cannot be attributedto lack of studies on this topic, because at the time the CIN25signature was formulated, in 2006, over 2,000 reports on BRCA1had already been published (37). This suggests that the genomicinstability resulting from the BRCA1dysregulation does not resultin detectable chromosomal aberrations.

In contrast to the increased BRCA1 gene expression observedin HDV-HCC compared with both HBV- and HCV-HCC, theexpression of BRCA1 by IHC was negative in all but one HCCsample. These negative results are consistent with a previousreport in which the expression of BRCA1 in breast cancer pro-gressively decreased from low-grade to high-grade breast carci-noma to eventually become undetectable (38). In our series, theHCC stage was G3 in 4 of 5 patients.

Insights into the levels of viral replication within the tumorof patients with viral-associated HCC may shed light on therole of hepatitis viruses in hepatocarcinogenesis. Althoughthere is a strong epidemiologic link between chronic infectionwith hepatitis viruses and the risk of developing HCC (5), themechanisms whereby these viruses promote hepatic carcino-genesis remain elusive (3). Thus, the question remains whetherHBV, HCV, and HDV elicit liver cancer indirectly, throughchronic inflammation, fibrosis, and liver regeneration, ordirectly, through the expression of tumor-promoting viralgenes. Our collection of multiple liver specimens from patients

(Continued.) and repair (sonic hedgehog, GADD45, DNA damage-induced 14-3-3s, cyclins, and cell-cycle regulation, cell cycle: G2–M DNA damage checkpointregulation, hereditary breast cancer), with a vast majority of upregulated genes, and other pathways involved in transcription, growth, and inflammation. B,Conversely, HBV-MH show pathways mainly associated with retinoic acid receptor functions and metabolic processes, with a predominance of downregulatedgenes, and pathways associated with cell remodeling and motility functions, with a predominance of upregulated genes. C, HCV-MH show pathways associatedwith retinoic acid receptor functions, in common with HBV-MH, and pathways associated to amino acid degradation, in all cases mostly downregulated. In addition,HCV-MH show two pathways (GADD45 and cell cycle: G2–M DNA damage checkpoint regulation) that were also identified in HDV-MH, although with lowerpercentages of upregulated genes. A detailed list of the pathways identified in HDV, HBV, and HCV-MH is shown in Supplementary Fig. S3. D, Top-scored canonicalpathways of WLT-unique genes of HDV-HCC include several biosynthetic pathways (spermine, inosine-50-phosphate, spermidine, serine, and glycine biosynthesis)with 100% of genes upregulated. Other pathways, with genesmostly downregulated, are involved in IFN signaling and in GAGs, glycerol, and ceramide degradation.E, WLT-unique pathways of HBV-HCC are mostly involved in amino acid metabolism (biosynthesis, degradation, and transformation), activation of LXR/RXRNR, prothrombin activation, coagulation, and acute-phase response signaling, with all genes downregulated. F, WLT-unique pathways of HCV-HCC include 13pathways associated with cytokine signaling and immune response, mostly downregulated. It should be noted that the pathways associated with HDV-, HBV-, andHCV-HCC WLT-unique genes are all different except one (superpathway of serine and glycine biosynthesis I) that was common to HDV- and HBV-HCC(Supplementary Fig. S6). Columns (quoted on the left y-axes) represent the percent ratio between the number of genes present in the dataset and the total numberof genes present in the database, for each pathway. The green and red portions of columns indicate down- and upregulated genes, respectively. The bluecurves (quoted on the right y-axes) show the statistical significance of each pathway, expressed as the negative log of the P value of Fisher exact test. The arrowspoint to the significance threshold corresponding to P ¼ 0.05 on the log scale. Pathways were obtained by Ingenuity Pathway Analysis (www.ingenuity.com).





www.ingenuity.com


with HDV-HCC allowed us to investigate the levels of HDVreplication in multiple compartments of individual liverscontaining HCC and compared with the levels measured incontrol livers with non-HCC HDV cirrhosis. Analysis of liver

specimens demonstrated that the level of HDV replication inthe tumors tended to be lower than in the surrounding non-tumorous tissues, and markedly lower than in non-HCC HDVcirrhotic livers. The levels of HBV DNA were extremely low

Figure 4.

Network of genes functionally associated with BRCA1, obtained from the IPA database. The network shows genes that are connected to BRCA1 by one-nodestep (25 genes, forming the yellow-highlighted inner circle) or two-node steps (44 genes, forming the outer circle). Shapes represent functional categories, asexplained in the bottom. A large majority of these genes (61 of 69, indicated by colored shapes) were differentially expressed in MH of HDV-HCC. Red and greencolors indicate upregulated (n ¼ 40) and downregulated (n ¼ 21) genes, the color intensity being roughly proportional to the fold change. Fourteen of the61 differentially expressed genes (BRCA1, ANLN, BARD1, CCNA2, CCNB1, CCNE2, CDK1, CDKN1C, FEN1, GSK3B, H2AFX, PRKCD, RPS27, and TAF10) are involved in theDNA damage and repair, according to IPA, Gene Ontology, Reactome, and Hallmark databases. Genes are clock-wise alphabetically sorted by the gene symbol.

Diaz et al.





or undetectable both in serum and in liver of all patients withHDV-HCC, as well as of non-HCC HDV cirrhotic livers, inagreement with the low HBV replication levels that are typicalof chronic HDV disease, as reported previously (39). Accord-ingly, HBcAg was not detected in any tumor and nontumoroustissues, as well as in all but one patient with non-HCC HDVcirrhosis. The fact that HDV does not replicate well in somepatients is consistent with the dramatic reduction in viralreplication that we recently documented in the tumor ofpatients with HCV-associated HCC, where a sharp and signif-icant drop in HCV RNA levels was observed in all of thepatients with HCC when perilesional tissue was comparedwith tissue inside the tumor margin (40). Collectively, ourdata indicate that hepatitis viruses do not grow well in malig-nant hepatocytes in vivo, in line with the inability or limitedefficiency of primary isolates to grow in hepatoma cell linesin vitro, suggesting that malignant hepatocytes express or lackfactors that are critical for viral replication.

Although the number of patients that could be included in thisintensive study was limited, our patients were well characterizedand we emphasize the difficulties in obtaining liver samples frompatients with HDV-associated HCC. As a consequence, there areno studies published to date inwhich themolecular profile of thistype of cancer has been investigated. Despite the limited numberof patients studied, however, our findings were highly consistentin all patients studied, corroborating the conclusions of our study.Moreover, comparative analysis extended to all three differentviral hepatitis-associated HCC provided the first evidence that themolecular signature of HDV-HCC is distinct not only from HBV-HCC, despite theobligatory dependence ofHDVonHBV, but alsofrom HCV-associated HCC.

In conclusion, by performing an integrated comparativeanalysis of transcriptomics of LCM hepatocytes and WLT, ourstudy illustrates the critical role of LCM in identifying genesthat may play a role in the molecular pathogenesis of livercancer. The activation and coregulation of genes associated

Figure 5.

t-SNE plots of the 547 genes differentially expressed in MH of HDV-associated HCC. Each gene is surrounded by genes that have similar expression, so thatclusters represent groups of coregulated genes. Genes involved in the cell cycle, found in Gene Ontology (GO), are indicated by red and green points, with colortones representing the fold change. HMMR (alias RHAMM) and MLF1IP (alias CENPU) were not associated with the cell cycle in GO; however, they wereincluded in the plot in view of their relationships with the mitotic spindle and BRCA1/BARD1 complex (3). Thirty-seven genes, about 50% of all genes associatedwith the cell cycle, all upregulated, form a compact cluster (enlarged in the circular inset) at the periphery of the whole cloud of points. This means that theseupregulated genes are strongly coregulated, and their coregulation is independent of the coregulation of other genes. On the right, the t-SNE plot of MH iscompared with that of NMH. In NMH, the same subset of genes involved in the cell cycle is conventionally identified by the same colors corresponding to thefold changes calculated for MH genes. In NMH, some genes tend to aggregate, but the clusters (encircled by the ovals) are much more scattered than amongMH genes. The contrast between the two patterns is also denoted by the different location of BRCA1, BARD1, and MSH2 in the two plots.






with DNA damage and repair point to genetic instability as akey mechanism of HDV-induced hepatocarcinogenesis. Bycomparing HCC-associated with HDV versus that associatedwith HBV alone, a major highlight of this study is thatdistinct molecular mechanisms appear to be involved in HDVversus HBV hepatocarcinogenesis, even though patients withHDV-HCC also harbor HBV. Finally, the study of multipleliver specimens from both the tumor and the surroundingnontumor tissue may help to identify genes that are importantfor elucidating the molecular pathogenesis of HDV-associatedHCC, as well as for identifying new diagnostic markersthat may predict the development of HCC or permit anearly diagnosis.

Disclosure of Potential Conflicts of InterestJ. Rodriguez-Canales is a senior pathologist at MedImmune. No potential

conflicts of interest were disclosed by the other authors.

Authors' ContributionsConception and design: G. Diaz, P. FarciDevelopment of methodology: G. Diaz, J. Rodriguez-Canales, J. Hanson,M.R. Emmert-Buck, D. Kleiner

Acquisition of data (provided animals, acquired and managed patients,provided facilities, etc.): R.E. Engle, A. Tice, M. Melis, J. Hanson, K.W. Bock,F. Zamboni, S. GovindarajanAnalysis and interpretation of data (e.g., statistical analysis, biostatistics,computational analysis): G. Diaz, M. Melis, J. Hanson, M.R. Emmert-Buck,D. Kleiner, P. FarciWriting, review, and/or revision of the manuscript: G. Diaz, R.E. Engle,M.R. Emmert-Buck, K.W. Bock, D. Kleiner, P. FarciAdministrative, technical, or material support (i.e., reporting or organizingdata, constructing databases): A. Tice, S. MontenegroStudy supervision: G. Diaz, P. FarciOther (IHC for liver samples): I.N. Moore

AcknowledgmentsThis research was supported by the Intramural Research Program of the NIH,

National Institute of Allergy and Infectious Diseases, and National CancerInstitute.

The costs of publication of this articlewere defrayed inpart by the payment ofpage charges. This article must therefore be hereby marked advertisement inaccordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Received January 4, 2018; revised April 19, 2018; accepted May 24, 2018;published first June 1, 2018.

References1. Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D. Global cancer

statistics. CA Cancer J Clin 2011;61:69–90.2. LevreroM.Viral hepatitis and liver cancer: the case of hepatitis C.Oncogene

2006;25:3834–47.3. McGivern DR, Lemon SM. Virus-specific mechanisms of carcinogenesis in

hepatitis C virus associated liver cancer. Oncogene 2011;30:1969–83.4. Centers for Disease Control and Prevention. Hepatocellular carcinoma -

United States, 2001–2006. MMWR Morb Mortal Wkly Rep 2010;59:517–20.

5. El-Serag HB. Hepatocellular carcinoma. N Engl J Med 2011;365:1118–27.6. Schena M, Shalon D, Davis RW, Brown PO. Quantitative monitoring of

gene expression patterns with a complementary DNA microarray. Science1995;270:467–70.

7. MelisM,DiazG,KleinerDE, Zamboni F, Kabat J, Lai J, et al. Viral expressionandmolecular profiling in liver tissue versusmicrodissected hepatocytes inhepatitis B virus-associated hepatocellular carcinoma. J Transl Med 2014;12:230.

8. Shirota Y, Kaneko S, Honda M, Kawai HF, Kobayashi K. Identification ofdifferentially expressed genes in hepatocellular carcinoma with cDNAmicroarrays. Hepatology 2001;33:832–40.

9. Ueda T, Honda M, Horimoto K, Aburatani S, Saito S, Yamashita T, et al.Gene expression profiling of hepatitis B- and hepatitis C-related hepato-cellular carcinoma using graphical Gaussian modeling. Genomics2013;101:238–48.

10. Taylor JM, Purcell RH, Farci P.HepatitisD (Delta) virus. In:KnipeDM,MaHPM, editors. Fields virology. Philadelphia, PA: Lippincott Williams &Wilkins; 2013.

11. Rizzetto M, Verme G, Recchia S, Bonino F, Farci P, Arico S, et al. Chronichepatitis in carriers of hepatitis B surface antigen, with intrahepatic expres-sion of the delta antigen. An active and progressive disease unresponsive toimmunosuppressive treatment. Ann Intern Med 1983;98:437–41.

12. Niro GA, Smedile A, Ippolito AM, Ciancio A, Fontana R, Olivero A, et al.Outcome of chronic delta hepatitis in Italy: a long-term cohort study.J Hepatol 2010;53:834–40.

13. Romeo R, Del Ninno E, Rumi M, Russo A, Sangiovanni A, de Franchis R,et al. A 28-year study of the course of hepatitis Delta infection: a risk factorfor cirrhosis and hepatocellular carcinoma. Gastroenterology 2009;136:1629–38.

14. Ishak K, Baptista A, Bianchi L, Callea F, De Groote J, Gudat F, et al.Histological grading and staging of chronic hepatitis. J Hepatol1995;22:696–9.

15. Edmondson HA, Steiner PE. Primary carcinoma of the liver: a study of 100cases among 48,900 necropsies. Cancer 1954;7:462–503.

16. Farci P, Roskams T, Chessa L, Peddis G, Mazzoleni AP, Scioscia R, et al.Long-term benefit of interferon alpha therapy of chronic hepatitis D:regression of advanced hepatic fibrosis. Gastroenterology 2004;126:1740–9.

17. Engle RE, Bukh J, Alter HJ, Emerson SU, Trenbeath JL, Nguyen HT, et al.Transfusion-associated hepatitis before the screening of blood for hepatitisrisk factors. Transfusion 2014;54:2833–41.

18. Erickson HS, Albert PS, Gillespie JW, Rodriguez-Canales J, MarstonLinehan W, Pinto PA, et al. Quantitative RT-PCR gene expressionanalysis of laser microdissected tissue samples. Nat Protoc 2009;4:902–22.

19. Farci P, Diaz G, Chen Z, Govindarajan S, Tice A, Agulto L, et al. B cell genesignature withmassive intrahepatic production of antibodies to hepatitis Bcore antigen in hepatitis B virus-associated acute liver failure. Proc NatlAcad Sci U S A 2010;107:8766–71.

20. Wang E, Miller LD, Ohnmacht GA, Liu ET, Marincola FM. High-fidelitymRNA amplification for gene profiling. Nat Biotechnol 2000;18:457–9.

21. Simon R, Lam A, Li MC, Ngan M, Menenzes S, Zhao Y. Analysis of geneexpression data using BRB-ArrayTools. Cancer Inform 2007;3:11–7.

22. van derMaaten L,HintonG. Visualizing data using t-SNE. JMach Learn Res2008;9:2579–605.

23. BushatiN, Smith J, Briscoe J,WatkinsC.An intuitive graphical visualizationtechnique for the interrogation of transcriptome data. Nucleic Acids Res2011;39:7380–9.

24. Grun D, Lyubimova A, Kester L, Wiebrands K, Basak O, Sasaki N, et al.Single-cell messenger RNA sequencing reveals rare intestinal cell types.Nature 2015;525:251–5.

25. RCoreTeam. R: A language and environment for statistical computing.Vienna, Austria: R Foundation for Statistical Computing; 2014.

26. Huang S. Regulation of metastases by signal transducer and activator oftranscription 3 signaling pathway: clinical implications. Clin Cancer Res2007;13:1362–6.

27. Carloni V, Lulli M, Madiai S, Mello T, Hall A, Luong TV, et al. CHK2overexpression and mislocalisation within mitotic structures enhanceschromosomal instability and hepatocellular carcinoma progression. Gut2018;67:348–61.

28. Weiler SME, Pinna F, Wolf T, Lutz T, Geldiyev A, Sticht C, et al.Induction of chromosome instability by activation of yes-associated


Diaz et al.




protein and Forkhead box M1 in liver cancer. Gastroenterology2017;152:2037–51e22.

29. Maxwell CA, McCarthy J, Turley E. Cell-surface and mitotic-spindleRHAMM: moonlighting or dual oncogenic functions? J Cell Sci 2008;121:925–32.

30. Nault JC, De Reynies A, Villanueva A, Calderaro J, Rebouissou S, CouchyG,et al. A hepatocellular carcinoma 5-gene score associated with survival ofpatients after liver resection. Gastroenterology 2013;145:176–87.

31. Fabbro M, Savage K, Hobson K, Deans AJ, Powell SN, McArthur GA, et al.BRCA1-BARD1 complexes are required for p53Ser-15 phosphorylationand a G1/S arrest following ionizing radiation-induced DNA damage.J Biol Chem 2004;279:31251–8.

32. Wang Y, CortezD, Yazdi P,Neff N, Elledge SJ, Qin J. BASC, a super complexof BRCA1-associated proteins involved in the recognition and repair ofaberrant DNA structures. Genes Dev 2000;14:927–39.

33. Raynard S, Bussen W, Sung P. A double Holliday junction dissolvasomecomprising BLM, topoisomerase IIIalpha, and BLAP75. J Biol Chem2006;281:13861–4.

34. Carter SL, Eklund AC, Kohane IS, Harris LN, Szallasi Z. A signature ofchromosomal instability inferred from gene expression profiles predictsclinical outcome in multiple human cancers. Nat Genet 2006;38:1043–8.

35. Jang ER, Lee JS. DNA damage response mediated through BRCA1. CancerRes Treat 2004;36:214–21.

36. Negrini S, Gorgoulis VG,Halazonetis TD.Genomic instability–an evolvinghallmark of cancer. Nat Rev Mol Cell Biol 2010;11:220–8.

37. PubMed. National Center for Biotechnology Information. Bethesda, MD.Available from: www.ncbi.nlm.nih.gov/pubmed.

38. Wilson CA, Ramos L, Villasenor MR, Anders KH, Press MF, Clarke K, et al.Localization of human BRCA1 and its loss in high-grade, non-inheritedbreast carcinomas. Nat Genet 1999;21:236–40.

39. Farci P, Niro GA. Clinical features of hepatitis D. Semin Liver Dis2012;32:228–36.

40. Harouaka D, Engle RE, Wollenberg K, Diaz G, Tice AB, Zamboni F, et al.Diminished viral replication and compartmentalization of hepatitis Cvirus in hepatocellular carcinoma tissue. Proc Natl Acad Sci U S A 2016;113:1375–80.





www.ncbi.nlm.nih.gov/pubmed


2018;16:1406-1419. Published OnlineFirst June 1, 2018.Mol Cancer Res Giacomo Diaz, Ronald E. Engle, Ashley Tice, et al. Associated Hepatocellular Carcinoma

−Molecular Signature and Mechanisms of Hepatitis D Virus

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