Good Genes Gone Bad: Understanding the Genetic Basis of Lung

Report
“Inbred mice are the troops
which literally by the tens of
thousands occupy posts on
the firing line of investigation
[into the] nature and cure of
cancer.“
Clarence Cook Little,
Founder of The Jackson Laboratory
1937
U.S. Science Wars Against Cancer
The Jackson Laboratory
Bar Harbor, Maine
Bar Harbor, Maine
• Non-profit mammalian genetics
research
• Founded in 1929
• 38 principal investigators
• 1,300+ employees
•Locations in Bar Harbor, Maine and
Sacramento, California
•Expansion to Connecticut underway
•NCI-designated Cancer Center
Sacramento, California
Farmington, Connecticut
Mission
Mission
We discover the genetic basis for
preventing, treating and curing human
disease, and we enable research and
education for the global biomedical
community.
Research
Resource
Education
Research
JAX Quick Facts: Research Programs
Research
• 38 Principal Investigator
lead research groups in:
• Cancer
• Neurobiology
• Computational biology
and Bioinformatics
• Developmental and
reproductive biology
• Immunology
• Complex trait genetics
Resource
JAX Quick Facts: Research
Resource
• Distribute 4,000 lines of genetically defined mice to
16,000 laboratories around the world
• Provide unique services for developing and testing in
vivo mouse models to advance drug discovery and
pre-clinical testing
Outreach and Education
Outreach
•
•
•
•
Courses & Conferences
Precollege/College Internships
Pre- and Postdoctoral training
Graduate programs with the
University of Maine Graduate
School for Biomedical Sciences
(GSBS) & Tufts University
Sackler School
• Visiting Investigator Program
Why Mice?
•
•
•
•
•
•
•
Mice get many of the same genetic disease as humans
Mammalian physiology is highly conserved
>95% of human genes have an ortholog in mouse
Conservation of gene content and organization
Experimentally tractable
Small, “easy” to breed
Short generation time
“The mouse is the
biomedical research platform for the
21st Century.”
- Harold Varmus, Director, National
Cancer Institute
genomics of normal lung development as
a framework for understanding disease
processes
Carol Bult, Ph.D.
Professor
Program Leader, JAX Cancer Center
Sr. Advisor for Research IT
A National Cancer Institute Designated Cancer Center
development and disease
• is there a gene expression signature that is
common to lung development and lung cancer?
• are developmental gene expression signatures
tissue specific?
Rudolf Virchow, 1859
old question; new approaches
genomes
genomics
informatics
lung development in mouse
Embryonic (E9 – E12)
– Primitive lung buds emerge from
ventral gut epithelium
Pseudoglandular (E12-E15)
– Stereo-specific branching of the
lung bronchi. Differentiation of
epithelial cells to form
prealveolate saccules
Canalicular (E15-E17)
– Formation of terminal sacs and
vasculature
Saccular (Terminal Sac) (E17 – P0)
– Expansion in the numbers of
terminal sacs and capillaries.
Differentiation of Type I and II
alveolar cells
Alveolar (P1-P30)
– terminal sacs develop into mature
alveolar ducts and alveoli
http://www.cincinnatichildrens.org/research/div/p
ulmonary-biology/faculty-research/whitsettlab/projects.htm
lung development stages are similar
in mouse and human
Developmental Stage
Timeline for mouse
Timeline for human
http://www.aups.org.au/Proceedings/36/9-13/
approach:
compare global gene expression during of normal
development (mouse) to global gene expression of
tumors (human)
transcriptional profiling of lung development
E11.5
E13.5
E14.5
E16.5
P5
E = embryonic
P = postnatal
Images from Malpel S,
Development (2000) 127:3057-67
Extract total mRNA from the target cell/tissue
- presence of mRNA means a gene is “active”
Modify the mRNA with a tag
Hybridize modified mRNAs to the probes on the gene chip
- successful hybridization generates a fluorescent signal
Scan for fluorescence
Quantitate expression
1. Bright spots indicates
positive hybridization
events (i.e. active
genes)
2. The analysis software
“knows” the address of
every gene and
generates a report of
gene activity
(expression)
time course analysis
Which genes have
sustained
transcriptional
activity changes
over time?
Expectations:
• genes/pathways for cell division/cell cycle
should go down over time
•
genes/pathways for differentiation and lung
specific pathways go up over time
Number of
genes that
match the
expression
profile
312
349
320
139
196
141
431
28,000+ genes on chip
~20,000 genes don’t change
~5,000 genes assigned to profiles
http://www.cs.cmu.edu/~jernst/stem/
Aldh1l1, Aldoc, Alg14, Alg6, Amph, Aox3, Aplp2, Appbp2, Aqp5, Arf2, Arf4, Arhgap6, Art3, Atf6, Atm,
Atp1b1, Atp6v0b, Atp6v1e1, Atp7a, Atp8a1, Atp8b2, B230118G17Rik, BC016495, Bbs4, Bcat1,
Bcl2l2, Bclaf1, Bid, Bpgm, Bphl, *Braf, Brunol4, Btbd4, Bzw1, C1qtnf3, C730048C13Rik, Cacna1d,
Cadps2, Calm2, Camk2d, Camkk2, Cart1, Casp7, Cav1, Ccnb1, Ccni, Cd36, Cdc26, Cdca5,
Cdkn1b, Cdkn1c, Cdkn3, Cdx2, Cebpg, Ches1, Cited1, Clca1, Clta, Clu, Cmpk, Cnot6, Cntn4,
Col18a1, Col3a1, Col4a1, Col4a6, Col9a1, Cox6b2, Cpm, Cpne5, Crbn, Crls1, Cse1l, *Ctnnb1,
Ctps2, Ctse, Cul3, Cyp11a1, D11Ertd333e, D1Ertd161e, D230025D16Rik, D830007F02Rik,
Daam2, Dab1, Dach1, Dapk2, Dcamkl1, Dhfr, Dhrs8, Dnajc15, Dtymk, Dusp4, Dyrk1a, E2f7, Eda2r,
Ednra, Ell2, Elmo3, Enah, Enpep, Enpp2, Epb4.1, Eps8, Esm1, Etv5, Eya1, Fabp3, Fabp5, Fank1,
Fath, Fblim1, Fbxl20, Fbxl3, Fbxw7, Fem1c, Fgfr2, Fhit, Fhl2, Fkbp6, Folr1, Foxp1, Frk, Fusip1,
Fxyd6, Fzd9, Gas7, Gata2, Gdpd2, Gja1, Gpc3, Gpx3, Gstk1, Gstp1, H2-Aa, H3f3a, Hdac9,
Hel308, Hesx1, Heyl, Hhip, Hif3a, Hipk2, Hist1h2bc, Hnrpf, Hook1, Hoxd8, Hsd17b12, Hsp90b1,
Hspa1b, Htra3, Ifitm3, Ifnar2, Igf1, Igfbp2, Igfbp3, Igfbp7, Ing3, Ipo7, Itga4, Itgb1, Itpr2, Jarid1d,
Kcnab1, Kcnb1, Kcnip1, Kcnip4, Kcnj16, Kcns2, Kdr, Keap1, Kif2a, Klf6, Klf7, Klk1, Krt2-7, Krt2-8,
Lama5, Lass6, Lcn2, Lgals7, Lgtn, Lhx1, Lhx9, Lmo4, Lrrc16, Lrrk1, Lsp1, Lss, Ltf, Madd, Mafa,
Man1a2, Mapk1, Mapre1, Masp1, Mef2c, Mlph, Mmp19, Mod1, Morf4l1, Morf4l2, Mrpl18, Mrpl44,
Mt1, Mt2, Mtdh, Mterf, Mthfd1, Mtm1, Mtr, Mtx2, Myef2, Myl1, Mylc2b, Mylk, Myo1b, Myo5b, Narg1,
Nedd9, Neo1, Nfe2l2, Npc1, Npepl1, Npr2, Nr2f2, Nrg1, Nusap1, Ogt, Otx2, Pak1, Pak3, Papss2,
Pard6b, Parp1, Pbx3, Pcbd1, Pcmtd1, Pcsk5, Pctk1, Pctk3, Pdcd6ip, Pdia3, Pfdn4, Pftk1, Phb2,
Phca, Phf8, Phka1, Pitx2, Pja1, Pja2, Pnck, Pomgnt1, Porcn, Ppargc1a, Ppfibp1, Ppih, Ppp1r16b,
Prc1, Prcp, Prkag2, Prkar2b, Prkcd, Psmb3, *Psrc1, Ptch1, Pten, Ptgds, Ptk2b, Ptp4a1, Ptp4a2,
Ptp4a3, Ptpn13, Ptx3, Qscn6, Rab2b, Rab31, Rab3a, Rab3b, Rad51l3, Rec8L1, Ren2, Rims4,
Rkhd3, Rnf11, Rnf20, Robo2, Rpl39, Rps6ka3, Runx1, Runx2, Rxrb, Ryr2, S100a6, S100a9, Sat1,
Scd1, Scmh1, Scn3a, Scn7a, Scn8a, Scrn1, Sdk2, Sec24a, Sec61a2, Sema3a, Sept11, Serpina3g,
Sesn3, Sf4, Sfrs1, http://www.informatics.jax.org
Sgk3, Shb, Sin3b, Slc11a2, Slc16a10, Slc16a7, Slc18a2, Slc25a5, Slc26a1,
Slc2a13, Slc38a5, Slc39a10, Slc41a2, Slc6a14, Slc6a15, Slc6a6, Slc7a4, Slc9a2, Smc2l1, Smg5,
Snapap, Sncaip, Snrk, Soat1, Sorl1, Sox10, Sox11, Sox9, Spp1, Srp54, St3gal5, Star, Strbp,
Stxbp1, Sulf1, Suv420h1, Sv2b, Sycp3, Syn2, Sypl, Tacc1, Tcea3, Tcf12, Tdgf1, Tesc, Tfrc, Tgfa,
finding common biological themes in lists of genes
analyze biological systems
and processes, not individual
genes.
biological systems represented by
genes whose expression levels….
decrease during
murine lung
development:
increase during
murine lung
development:
Cell Adhesion
Cell Cycle
Cell Division
DNA Repair
Mitosis
Regulation of transcription
“Early expression group”
System Development
Anatomical System Development
Vasculature Development
Blood Vessel Development
Angiogenesis
“Late expression group”
gene expression in human lung tumors
Which genes are
differentially
expressed in tumors
compared to normal
lung tissue?
Expectations:
• genes/pathways for cell division/cell cycle
should go up over time
•
genes/pathways for differentiation and lung
specific pathways go down over time
transcriptional profiling in human lung tumors
compared to normal human lung
Adenocarcinoma
Dehan and Kaminski, 2004. (GSE1987)
NCBI’s GEO http://www.ncbi.nlm.nih.gov/geo/
Normal
differential gene expression:
tumor vs normal
A vs N (q<0.05)
• Microarray Analysis of
Variance
(MAANOVA)**
** http://www.jax.org/staff/churchill/labsite/software/anova/index.html
Aldh1l1, Aldoc, Alg14, Alg6, Amph, Aox3, Aplp2, Appbp2, Aqp5, Arf2, Arf4, Arhgap6, Art3, Atf6, Atm,
Atp1b1, Atp6v0b, Atp6v1e1, Atp7a, Atp8a1, Atp8b2, B230118G17Rik, BC016495, Bbs4, Bcat1,
Bcl2l2, Bclaf1, Bid, Bpgm, Bphl, *Braf, Brunol4, Btbd4, Bzw1, C1qtnf3, C730048C13Rik, Cacna1d,
Cadps2, Calm2, Camk2d, Camkk2, Cart1, Casp7, Cav1, Ccnb1, Ccni, Cd36, Cdc26, Cdca5,
Cdkn1b, Cdkn1c, Cdkn3, Cdx2, Cebpg, Ches1, Cited1, Clca1, Clta, Clu, Cmpk, Cnot6, Cntn4,
Col18a1, Col3a1, Col4a1, Col4a6, Col9a1, Cox6b2, Cpm, Cpne5, Crbn, Crls1, Cse1l, *Ctnnb1,
Ctps2, Ctse, Cul3, Cyp11a1, D11Ertd333e, D1Ertd161e, D230025D16Rik, D830007F02Rik,
Daam2, Dab1, Dach1, Dapk2, Dcamkl1, Dhfr, Dhrs8, Dnajc15, Dtymk, Dusp4, Dyrk1a, E2f7, Eda2r,
Ednra, Ell2, Elmo3, Enah, Enpep, Enpp2, Epb4.1, Eps8, Esm1, Etv5, Eya1, Fabp3, Fabp5, Fank1,
Fath, Fblim1, Fbxl20, Fbxl3, Fbxw7, Fem1c, Fgfr2, Fhit, Fhl2, Fkbp6, Folr1, Foxp1, Frk, Fusip1,
Fxyd6, Fzd9, Gas7, Gata2, Gdpd2, Gja1, Gpc3, Gpx3, Gstk1, Gstp1, H2-Aa, H3f3a, Hdac9,
Hel308, Hesx1, Heyl, Hhip, Hif3a, Hipk2, Hist1h2bc, Hnrpf, Hook1, Hoxd8, Hsd17b12, Hsp90b1,
Hspa1b, Htra3, Ifitm3, Ifnar2, Igf1, Igfbp2, Igfbp3, Igfbp7, Ing3, Ipo7, Itga4, Itgb1, Itpr2, Jarid1d,
Kcnab1, Kcnb1, Kcnip1, Kcnip4, Kcnj16, Kcns2, Kdr, Keap1, Kif2a, Klf6, Klf7, Klk1, Krt2-7, Krt2-8,
Lama5, Lass6, Lcn2, Lgals7, Lgtn, Lhx1, Lhx9, Lmo4, Lrrc16, Lrrk1, Lsp1, Lss, Ltf, Madd, Mafa,
Man1a2, Mapk1, Mapre1, Masp1, Mef2c, Mlph, Mmp19, Mod1, Morf4l1, Morf4l2, Mrpl18, Mrpl44,
Mt1, Mt2, Mtdh, Mterf, Mthfd1, Mtm1, Mtr, Mtx2, Myef2, Myl1, Mylc2b, Mylk, Myo1b, Myo5b, Narg1,
Nedd9, Neo1, Nfe2l2, Npc1, Npepl1, Npr2, Nr2f2, Nrg1, Nusap1, Ogt, Otx2, Pak1, Pak3, Papss2,
Pard6b, Parp1, Pbx3, Pcbd1, Pcmtd1, Pcsk5, Pctk1, Pctk3, Pdcd6ip, Pdia3, Pfdn4, Pftk1, Phb2,
Phca, Phf8, Phka1, Pitx2, Pja1, Pja2, Pnck, Pomgnt1, Porcn, Ppargc1a, Ppfibp1, Ppih, Ppp1r16b,
Prc1, Prcp, Prkag2, Prkar2b, Prkcd, Psmb3, *Psrc1, Ptch1, Pten, Ptgds, Ptk2b, Ptp4a1, Ptp4a2,
Ptp4a3, Ptpn13, Ptx3, Qscn6, Rab2b, Rab31, Rab3a, Rab3b, Rad51l3, Rec8L1, Ren2, Rims4,
Rkhd3, Rnf11, Rnf20, Robo2, Rpl39, Rps6ka3, Runx1, Runx2, Rxrb, Ryr2, S100a6, S100a9, Sat1,
Scd1, Scmh1, Scn3a, Scn7a, Scn8a, Scrn1, Sdk2, Sec24a, Sec61a2, Sema3a, Sept11, Serpina3g,
Sesn3, Sf4, Sfrs1, Sgk3, Shb, Sin3b, Slc11a2, Slc16a10, Slc16a7, Slc18a2, Slc25a5, Slc26a1,
Slc2a13, Slc38a5, Slc39a10, Slc41a2, Slc6a14, Slc6a15, Slc6a6, Slc7a4, Slc9a2, Smc2l1, Smg5,
Snapap, Sncaip, Snrk, Soat1, Sorl1, Sox10, Sox11, Sox9, Spp1, Srp54, St3gal5, Star, Strbp,
Stxbp1, Sulf1, Suv420h1, Sv2b, Sycp3, Syn2, Sypl, Tacc1, Tcea3, Tcf12, Tdgf1, Tesc, Tfrc, Tgfa,
similar biological systems;
opposite gene expression trends
human lung tumor
(adenocarcinoma)
Cell Adhesion
Cell Cycle
System Development
Cell Division
Anatomical System Development
Mitosis
Vasculature Development
Blood Vessel Development
Angiogenesis
normal mouse lung development
Cell Adhesion
System Development
Anatomical System Development
Vasculature Development
Blood Vessel Development
Angiogenesis
“Late expression group”
Cell Cycle
Cell Division
DNA Repair
Mitosis
Regulation of transcription
“Early expression group”
integrating development and cancer genomics
• For genes regulated in lung tumors, when are the orthologous mouse
genes expressed during development?
• For genes down regulated in lung tumors, when are the orthologous
mouse genes expressed during development?
Divide up the developmental timeline into segments,
bin the ~5,000 or so genes that have expression levels
related to development.
Developmental Timeline (DT)
Early
Late
Determine the frequency of genes in each bin where the
human ortholog is overexpressed in tumors.
Determine the frequency of genes in each bin where the
human ortholog is underexpressed in tumors.
Frequency
Frequency
Frequency
No association
Ambiguous association
Strong association
quantifying developmental gene expression
signatures
development and disease
• is there a gene expression signature that is
common to lung development and lung cancer?
• are developmental gene expression signatures
tissue specific?
developmental gene expression signatures
for cancer are not tissue specific
not all cancers exhibit an early
developmental gene expression signature
10 developmental time series
32 disease data sets (mostly cancer)
Naxerova et al. 2008. Genome Biology. 9:R108
novel classification of tumors?
• group 1 – early development gene signatures
– 46% of data sets tested fall into this group
– lung cancer, Wilm’s tumor
• group 2 – ambiguous developmental signature
– early developmental signature plus other
transcriptional programs
– observed in CNS tumors, breast cancer
• group 3 – no early development signature
– genes cluster on the late end of the DT
– ovarian cancer, prostate cancer
functional differences in expressionbased classifications
• group 1 and 2 tumors (early developmental
signatures)
– cell cycle, RNA splicing, DNA repair
– cellular location largely in nucleus
• group 3 tumors (late development signatures)
– immune response, cell adhesion,
– cellular location largely in extracellular matrix and cell
membrane
summary
• genomics of normal lung development is a
useful framework for identifying genes and
networks that are dysregulated in lung cancer
• developmental gene signatures do not appear to
be tissue specific
• not all cancers exhibit the same developmental
gene signature
• the laboratory mouse allow us to investigate
early genetic events in normal development and
cancer that would not otherwise be possible
ongoing studies
• developmental gene signatures in other lung
tumor types
• developmental signatures in other lung diseases
– Interstitial lung disease/ Pulmonary fibrosis
possible clinical relevance
• correlate gene expression patterns of lung
development genes with patient outcomes
– Collaboration between JAX and Cancer Care of
Maine just funded by Maine Cancer Foundation to
develop new models of lung cancer
• different transcriptional profiles may reflect a
variety of strategies used by tumor cells for
survival
– New therapeutic targets?
– Biomarkers?
acknowledgements
Julie Wells
Cecily Swinburne
Jill Recla
Connie Birkenmeier
Kyle Beauchemin
Anne Peaston
Rita Thibodeau
Marge Strobel
Randy Babiuk
Isaac Kohane
Kamila Naxerova
Alvin Kho
Simon Kasif
JAX Scientific Services
Maine Cancer Foundation
TJL Cancer Center Pilot Project Funds
National Cancer Institute

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