Interpreting cancer genomes using systematic host network perturbations by tumour virus proteins.
Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations, and large numbers of somatic genomic alterations, associated with a predisposition to cancer. However, it remains difficult to distinguish background, or 'passenger', cancer mutations from causal, or 'driver', mutations in these data sets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. Here we test the hypothesis that genomic variations and tumour viruses may cause cancer through related mechanisms, by systematically examining host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways, such as Notch signalling and apoptosis, that go awry in cancer. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on a par with their identification through functional genomics and large-scale cataloguing of tumour mutations. Together, these complementary approaches increase the specificity of cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate the prioritization of cancer-causing driver genes to advance the understanding of the genetic basis of human cancer.
Genomic Analysis of Network Perturbations Center of Excellence in Genomic Science, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA.
Orit
O
Rozenblatt-Rosen
Rahul C
RC
Deo
Megha
M
Padi
Guillaume
G
Adelmant
Michael A
MA
Calderwood
Thomas
T
Rolland
Miranda
M
Grace
Amélie
A
Dricot
Manor
M
Askenazi
Maria
M
Tavares
Samuel J
SJ
Pevzner
Fieda
F
Abderazzaq
Danielle
D
Byrdsong
Anne-Ruxandra
AR
Carvunis
Alyce A
AA
Chen
Jingwei
J
Cheng
Mick
M
Correll
Melissa
M
Duarte
Changyu
C
Fan
Mariet C
MC
Feltkamp
Scott B
SB
Ficarro
Rachel
R
Franchi
Brijesh K
BK
Garg
Natali
N
Gulbahce
Tong
T
Hao
Amy M
AM
Holthaus
Robert
R
James
Anna
A
Korkhin
Larisa
L
Litovchick
Jessica C
JC
Mar
Theodore R
TR
Pak
Sabrina
S
Rabello
Renee
R
Rubio
Yun
Y
Shen
Saurav
S
Singh
Jennifer M
JM
Spangle
Murat
M
Tasan
Shelly
S
Wanamaker
James T
JT
Webber
Jennifer
J
Roecklein-Canfield
Eric
E
Johannsen
Albert-László
AL
Barabási
Rameen
R
Beroukhim
Elliott
E
Kieff
Michael E
ME
Cusick
David E
DE
Hill
Karl
K
Münger
Jarrod A
JA
Marto
John
J
Quackenbush
Frederick P
FP
Roth
James A
JA
DeCaprio
Marc
M
Vidal
D000256:Adenoviridae / Q000235:genetics / Q000378:metabolism / Q000472:pathogenicity; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D052138:Genes, Neoplasm / Q000235:genetics*; D015894:Genome, Human / Q000235:genetics*; D004854:Herpesvirus 4, Human / Q000235:genetics / Q000378:metabolism / Q000472:pathogenicity; D054884:Host-Pathogen Interactions / Q000235:genetics; D006801:Humans; D009369:Neoplasms / Q000235:genetics* / Q000378:metabolism* / Q000473:pathology; D009858:Oncogenic Viruses / Q000235:genetics / Q000378:metabolism / Q000472:pathogenicity*; D016366:Open Reading Frames / Q000235:genetics; D027383:Papillomaviridae / Q000235:genetics / Q000378:metabolism / Q000472:pathogenicity; D011120:Polyomavirus / Q000235:genetics / Q000378:metabolism / Q000472:pathogenicity; D051880:Receptors, Notch / Q000378:metabolism; D015398:Signal Transduction; D020798:Two-Hybrid System Techniques; D014764:Viral Proteins / Q000235:genetics / Q000378:metabolism*
D051880:Receptors, Notch; D014764:Viral Proteins