Transcript Presentation

Tumor Heterogeneity
Nature Insight series (19 September 2013 / Vol 501 / Issue No 7467)
Erez Persi
Journal Club - Prof. Eytan Ruppin’s lab
Nov 2013
Outline
1. Clonal Evolution:
Paradigm, stem-cell model
2. Genomic Mechanisms:
Clonal
Evolution
Genomic instability, Epigenetics
3. Metastasis, Resistance
Microenvironment,
Clinics & Therapeutic challenges
Heterogeneity
Metastasis,
Resistance
Genomic
Mechanisms
Clonal Evolution
1. Genetic disease (of the
aged)
2. Evolving « system »
(time & space).
3. Heterogeneity
Clonal Evolution
(stepwise acquisition
of mutations)
Interaction
(cell-cell, microenviroment)
Epigenetics
(DNA methylation,
histone deacetylation )
Peter C. Nowell. The Clonal Evolution of Tumor Cell Populations. Science (1976)  side by side with John Cairns , Nature (1975)
(Almost)
40 years later
1. Comparative study of 8 acute myeloid leukemia (AML) patients
Ding L. Et al. Clonal evolution in relapsed acutemyeloid leukaemia revealed by whole-genome sequencing. Nature (2012).
2. Exome sequencing, 4 patients (primary renal carcinoma & associate
metastatic sites)
GE: Good / Poor Prognostic
signatures differs by region
Gerlinger M. Et al. Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing. New Eng J Med (2012).
1. Cancer Stem Cell (or like) – only few founders with tumorgenic potential
2. Therapeutic importance – target the few
3. BUT, although most evidence supports CSC - we don’t really know 
Felipe De Sousa E Melo. Cancer heterogeneity - a multifaceted view. EMBO report (2013).
Genomic Mechanisms
1.
Intertumor heterogeneity:
a)
Between tumors types, and between tumors that originate from the same tissue & cell type.
b)
Leads to variability in response to drugs. EX: target BRAF oncoprotein => works in melanoma but
less in colorectal cancer (may be attributed to EGFR exp’ following BRAF inhibition in epithelial
vs. low basal levels in melanoma ).
c)
=> classify to subgroups (on the basis of mutation, CNV, GE…) => specificity (i.e, BC: ER,
HER2, LU: 10% harbour EGFR-activating mutation).
d)
But, the heterogeneity is huge: NGS reveals that few mutations observed in more than 5-10% of
tumors of a specific tissue. Genes may be defected differently (mutation, cnv, methyl..) In addition:
epistasis, for example in AML, NPM1 mutation confer favourable prognosis only in the presence
of co-occuring IDH1, IDH2 mutations.
e)
And the hope: still, same cellular pathways often repeatedly affected => histone-modifying genes
& (another unifying feature) is genomic instability (deregulation of G1-S transition…)
-
Microsatellite instability (more in proximal colon <=> suggests association with epigenetic/env factors)
-
Defective homologous recombination (more in breast & ovarian)
-
A given instability can be caused by multiple mechanisms
-
Prognosis <=> instability(immune infiltration in microsatellite unstable tumours vs. Chr instability tumor)
Identify biomarkers to define phenotypic similarity, yet genetically
diverse, to guide treatment – Still A Challenge
2.
Intartumor heterogeneity:
a)
Within tumors: diversity in GE, genetic, epigenetic.
b)
Genetically distinct subclones arise through intercellular genetic variation, followed by
selection within a given micro-env context. Fluctuations in sublonal architecture occur through
disease progression.
c)
Branched evolution I: adenoma-to-carcinoma transition (colon); ALL, CLL (distinct leukemia
propagating cells – responsible for sustaining each subclones).
d)
Branched evolution II: clonal diversity between different regions of the same tumor and
between primary and metastatic sites (mutation, CNV) - observed in renal (slide 5),
glioblastoma, breast, pancreatic. (CNV diversity between regions can be larger than observed
between patients).
e)
How come ? => At metastatic sites – micro-env + selection contribute.
-
Growing evidence that to forecast outcome there is need for identification of low-frequency genetically &
functionally distinct subclones at diagnosis
-
Non genetic factors: Same subclone can have functionally distinct behaviors following “interaction”
High fidelity:
Instability <=> tumorgenesis ?
•
Somatic mutation: ~10e-9 per site per cell division
From mouse models: genomic instability
•
chromosomal segregation error: 1 per 100 cell division
increases risk for carcinogenesis; promotes
•
Still most tumors display at least one form of instability.
loss of heterozygosity of tumor suppressors.
Weaver BA et al. Aneuploidy acts both oncogenically and as a tumor suppressor. Cancer Cell (2007).
Baker DJ et al. Whole chromosome instability caused by Bub1 insufficiency drives tumorgenesis through tumor suppressor loss of heterozigosity.
Cancer Cell (2009)
3.
Genomic Instability & Evolution:
a)
True level of diversity is underestimated ( studies rely on pooled population of cells => sampling
bias + inability to resolve heterogeneity between single cells)
b)
Chromosomal instability (in many cancer types) is associated with aggressive disease, drug
resistance and poor prognosis3 (mitotic defects – inaccurate whole chromosome partitioning
between daughter cells; and pre-mitotic defects – defective repair or increased rate of (mostly
endogenous)DNA damage lead to structural changes <=> still under study). Chromosome
gain/loss => more likely to have functional consequences
c)
Increased rate of specific mutation depending on the instability mechanism (colorectal cancer:
defective mismatch vs. Intact repair1; lung cancer (smoking -DNA damage) increased in C*G->A*T
transversions such that mutations in TP53 can be attributed to DNA damage => frequent mutation
in one pattern of instability selects for other specific mutations).
d)
Different instabilities lead to particular distributions of point mutations (replication stress =
mutations in large genes; microsatellite = specific genes; chromosomal rearrangement = highly
localized clusters of mutations (kataegis)2 )
The cancer genome atlas research net. Comprehensive molecular characterization of human colon and rectal. Nature (2012).
Nik-Zainal S et al. Mutational processes molding the genomes of 21 breast cancers. CELL (2012)
Gordon DJ et al. Causes and consequences of aneuploidy in cancer. Nat Rev Genet (2012).
…. Temporal
a)
Changing patterns of instability during tumor progression (chromosomal unstable metastases
tetraploid, while primary subclones were diploid – renal, slide 5; breast – altered mutational
spectrum at later times during progression, involving decreased transitions CG-> TA1) – strikingly
different genomic landscape…
b)
Therapy & genomic instability: (increased relapsed-specific mutations (+ base transverstions) after
therapy – AML, slide 4; glioblastoma – mutations in the mismatch repair gene MSH6 appear solely
in relapse 2)
c)
Existence of mutational bursts. On-going instability occurs in most cancers all the time, but there
are drastic changes considered to be contributing to progression (10-100 chr rearrangement
across few chr; transient telomere dysfunction; genome doubling providing new material to act
upon - observed after chr instability)
Nik-Zainal S et al. The life history of 21 breast cancers. CELL (2012)
Hunter et al. A hypermutation phenotype and somatic MSH6 mutations in recurrent human malignant gliomas after alkylator chemothreapy. Cancer
Res (2006)
Pause I
1. More studies from human biopsies & over space - time.
•
Understanding mechanisms driving genomic instability
•
To develop approaches to limit cancer diversity, adaptation, resistance
of heterogeneity
Additionally ?
1. Drug Combination & Mechanisms
•
Efficacy of combined mechanisms
•
Gobal (first strike?) + specific (knockout?)
•
Spontaneous relapse vs. Drug-mediated relapse
Therapeutic potential
2. A need to develop clinically useful measures
Genomic
instability
All the rest
?
All the rest
?
Mechanism
2. Pan cancer hierarchal investigation:
•
inter-tumor type & inter-patient (same tumor type) => what is common at each level
•
Intratumor variability => what is common
? What metabolsim may further teach us about the potential of such
combinations… if/how metabolism is involved in shaping the mechanisms ?
Metastasis & Microenvironment
« Hard Life »
•
Most cancer cells that leave a tumor die during the attempt to
infiltrate distant organs:
•
Stress of passing through endothelial barriers
•
Lack of survival signal & supportive stroma in the host
•
Immune system
Vanharanta S, Massagué J. Origins of Metastatic Traits. Cancer Cell Rev (2013)
Determinants of metastatic Organ Tropism
2 distinct temporal phases,
dissemination & colonization
May be seperated by Weeks
(e.g. lung adenocarcinoma), to
decades (BC ER+, prostate)
Treatment may cause
metastases in other places
1.
Cancer-associated fibroblasts (CAF)
a)
Respond to damage (wound) & support repair. Typically suppress tumor formation. CAFs promote
tumorgenesis( via increased proliferation, enhanced ECM production & unique cytokine )
b)
Phenotypic differences in fibroblasts lead to tissue remodeling, deposition of ECM and augmented
angiogenesis
c)
Abundance of stromal cells correlates with poor prognosis in several cancer types
d)
Elevated expression of matrix metalloproteinases correlates with poor prognosis
e)
Affect therapy:
-
Stromal derived HGF render tumor cells resistant to BRAF inhibition (via increased
phosphorylation of its cognate receptor)
-
Secreted factors from normal human fibroblasts can suppress/promote tumor growth via of WNT16B (secrets proteins that regulate cell fate) <=> depends on pathway that mediates stress and
inflammatory response)
Tumor cells presence can convert the micro-env
from being suppressive to being supportive
2.
Vasculature
a)
Tumor vascular network is dynamic and can limit growth (derived through formation of new
vessels, co-option and modification of existing vessels, recruitment and differentiation of
endothelial precursors)
b)
Tissue-specific vascular function (in healthy and tumor env).
c)
Inadequate function results in areas of hypoxia and limited nutrient supply
d)
Generates distinct micro-env within the tumor, ultimately affecting clinical outcome
-
Microvessel density is a significant predictor of poor prognosis in several cancer types
-
Elevated expression of pro-angiogenic ligand VEGFA is associated with poor prognosis
e)
Also interacts with treatment:
-
Endothelial cells in tumor respond to therapy through secreted factors => production of growth
factors … rendering the tissue a protective env (niche)
-
Observation: tumor re-initiating cells along tumor vessels
3.
Immune cells
a)
Tumor cells mediate immune suppression
b)
Immune cell recruitment and localization vary widely in and among lesions. Influenced by various
factors (including those secreted by CAFs, permeability of the vasculature…)
-
Colorectal: microsatellite instability leads to increased neoantigen & T-cell infiltration
-
Ovarian: endothelial cells regulate cell migration <=> immune contexture depends on the specifics
of the vasculature
c)
Immune infiltration distribution is not uniform (Clustering on the leading edge of a lesion has
prognostic consequences) => Crucial role of intratumor localization.
d)
:T-cell activation / inhibition
-
direct: continous engagment of inhibitory receptors on T-cells by upregulation of their ligands
-
Indirect: generation of immunosuppressive-environment. Upon tumor implantation - expansion of
myeloid-derived suppressor cell populaion (neutrophils, immature dendritic cells…)
-
Immune-tumor com early on through CAF secretion of chemokines
-
In parallel this fosters angiogenesis through secretion of VEGFA, inhibits natural killer function
e)
Analysis of the micro-env signatures showed that angiogenesis, hypoxia and immune suppressive
signatures were associated with poor outcome
f)
Therapy:
Transplanting T cells –
-
Cancer: Chemo evokes recuirtment supressive macrophages
works but not always
-
Melanoma, following BRAF inhibition, increased tumor antigen expression. At time of progression
this reverted + emergence of markers of immune cell exhaustion.
Pause II
1. The complexity of a tumor is a result of continous crosstalk between
tumor cells and the environment => can’t see “all” from pretreatment
biopspies
2. Heterogeneity <=> Resistance <=> Biomarkers identification
3. New therapeutic strategy: target the stroma and avoid messing with
? Stroma Metabolism ?
Therapeuvtic potential
the genomic instability “lost-fight”
Genomic
instability
Micro-env
All the rest
?
All the rest
?
Mechanism
Perspective
Supplementary Material
Clonal Evolution
1. Genetic disease (of the
aged)
2. Evolving « system »
(time & space).
3. Heterogeneity !
Clonal Evolution
(stepwise acquisition
of mutations)
Interaction
(cell-cell, microenviroment)
Epigenetics
(DNA methylation,
histone deacetylation )
4. Metabolism (almost) everywhere
Peter C. Nowell. The Clonal Evolution of Tumor Cell Populations. Science (1976).
Douglas Hanahan & Robert A. Weinberg. Hallmarks of Cancer: The Next Generation. Cell (2011).
Felipe De Sousa E Melo. Cancer heterogeneity - a multifaceted view. EMBO report (2013).
Cancer Classification
Cancers are classified by the type of cell that the tumor cells resemble and is therefore presumed to be
the origin of the tumor. These types include:
•
Carcinoma:
Cancers derived from epithelial cells.
This group includes many of the most common cancers, particularly in the aged, and include nearly
all those developing in – the breast, prostate, lung, pancreas, and colon.
•
Sarcoma (of the “flesh”):
Cancers arising from connective tissue (i.e. bone, cartilage, fat, nerve), each of which develop from
cells originating in mesenchymal cells (loose connective tissue) outside the bone marrow.
•
Lymphoma and leukemia:
These two classes of cancer arise from hematopoietic (blood-forming) cells
that leave the marrow and tend to mature in the lymph nodes and blood, respectively.
•
Germ cell tumor:
Cancers derived from pluripotent cells, most often presenting in the testicle or the ovary
(seminoma and dysgerminoma, respectively).
•
Blastoma:
Cancers derived from immature "precursor" cells or embryonic tissue.
Blastomas are more common in children than in older adults.
Cancers are usually named using -carcinoma, -sarcoma or -blastoma as a suffix, with the Latin or Greek
word for the organ or tissue of origin as the root.
Cancer Stage
•
Stage 0: carcinoma in situ.
•
Stage I: cancers are localized to one part of the body. Stage I cancer can be surgically removed if small
enough.
•
Stage II: cancers are locally advanced. Stage II cancer can be treated by chemo, radiation, or surgery.
•
Stage III: cancers are also locally advanced. Whether a cancer is designated as Stage II or Stage III
can depend on the specific type of cancer; for example, in Hodgkin's Disease, Stage II indicates
affected lymph nodes on only one side of the diaphragm, whereas Stage III indicates affected lymph
nodes above and below the diaphragm. The specific criteria for Stages II and III therefore differ
according to diagnosis. Stage III can be treated by chemo, radiation, or surgery.
•
Stage IV: cancers have often metastasized, or spread to other organs or throughout the body. Stage IV
cancer can be treated by chemo, radiation, or surgery.
Tumor Grade
In pathology, grading is a measure of the cell appearance in tumors and other neoplasms.
The neoplastic grading is a measure of cell anaplasia (reversion of differentiation)
in the sampled tumor and is based on the resemblance of the tumor to the tissue of origin, i.e. it reflects
how much the tumor cells differ from the cells of the normal tissue they have originated from
Grade 1
Low grade
Well-differentiated
Grade 2
Intermediate grade
Moderately-differentiated
Grade 3
High grade
Poorly-differentiated
Grade 4
Anaplastic
Anaplastic
Tissues / Localization
•
Epithelium is one of the four basic types of animal tissue, along with connective tissue,
muscle tissue and nervous tissue. Epithelial tissues line the cavities and surfaces of structures
throughout the body, and also form many glands. Functions of epithelial cells include secretion,
selective absorption, protection, transcellular transport and detection of sensation. In Greek "epi"
means "on" or "upon", and "thele" means "nipple“. Epithelial layers are avascular, so they must
receive nourishment via diffusion of substances from the underlying connective tissue, through the
basement membrane. Epithelia can also be organized into clusters of cells that function as
exocrine and endocrine glands.
•
Stroma (from Greek, meaning layer, bed, bed covering) refers to the connective, supportive
framework of a biological cell, tissue, or organ. The stroma in animal tissue is contrasted with the
parenchyma. Parenchyma are the functional parts of an organ in the body.