Tumor Heterogeneity Nature Insight series (19 September 2013 / Vol 501 / Issue No 7467)

1. Tumor HeterogeneityNature Insight series (19 September 2013 / Vol 501 / Issue No 7467) Erez Persi Journal Club - Prof. Eytan Ruppin’s lab Nov 2013

2. Outline Clonal Evolution: Paradigm, stem-cell model Genomic Mechanisms: Genomic instability, Epigenetics Metastasis, Resistance Microenvironment, Clinics & Therapeutic challenges Clonal Evolution Heterogeneity Metastasis, Resistance Genomic Mechanisms

3. Clonal Evolution Genetic disease (of the aged) Evolving « system » (time & space). Heterogeneity Clonal Evolution (stepwise acquisition of mutations) Interaction (cell-cell, micro-enviroment) 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)

4. (Almost) 40 years later 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).

5. 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).

6. Cancer Stem Cell (or like) – only few founders with tumorgenic potential • Therapeutic importance – target the few • BUT, although most evidence supports CSC - we don’t really know  Felipe De Sousa E Melo. Cancer heterogeneity - a multifaceted view. EMBO report (2013).

7. Genomic Mechanisms

11. Intertumor heterogeneity: • Between tumors types, and between tumors that originate from the same tissue & cell type. • 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 ). • => classify to subgroups (on the basis of mutation, CNV, GE…) => specificity (i.e, BC: ER, HER2, LU: 10% harbour EGFR-activating mutation). • 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. • 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

12. Intartumor heterogeneity: • Within tumors: diversity in GE, genetic, epigenetic. • Genetically distinct subclonesarise through intercellular genetic variation, followed by selection within a given micro-env context. Fluctuations in sublonal architecture occur through disease progression. • Branched evolution I: adenoma-to-carcinoma transition (colon); ALL, CLL (distinct leukemia propagating cells – responsible for sustaining each subclones). • 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). • 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” • Instability <=> tumorgenesis ? • From mouse models: genomic instability increases risk for carcinogenesis; promotes loss of heterozygosity of tumor suppressors. • High fidelity: • Somatic mutation: ~10e-9 per site per cell division • chromosomal segregation error: 1 per 100 cell division • Still most tumors display at least one form of instability. 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)

13. Genomic Instability & Evolution: • True level of diversity is underestimated ( studies rely on pooled population of cells => sampling bias + inability to resolve heterogeneity between single cells) • 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 • 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). • 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).

14. …. Temporal • 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… • 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) • 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 afterchr 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)

15. Pause I • More studies from human biopsies & over space - time. • Understanding mechanisms driving genomic instability • To develop approaches to limit cancer diversity, adaptation, resistance • A need to develop clinically useful measures • of heterogeneity • Additionally ? • Drug Combination & Mechanisms • Efficacy of combined mechanisms • Gobal (first strike?) + specific (knockout?) • Spontaneous relapse vs. Drug-mediated relapse • Pan cancer hierarchal investigation: • inter-tumor type & inter-patient (same tumor type) => what is common at each level • Intratumor variability => what is common Genomicinstability Therapeutic potential All the rest ? All the rest ? Mechanism ? What metabolsim may further teach us about the potential of such combinations… if/how metabolism is involved in shaping the mechanisms ?

16. Metastasis & Microenvironment

17. « Hard Life » • Most cancer cells that leave a tumor die during the attempt to infiltrate distant organs: • Stress of passing throughendothelialbarriers • Lack of survival signal & supportive stroma in the host • Immune system Vanharanta S, Massagué J. Origins of Metastatic Traits. Cancer Cell Rev (2013)

18. 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

19. Cancer-associated fibroblasts (CAF) • Respond to damage (wound) & support repair. Typically suppress tumor formation. CAFs promote tumorgenesis( via increased proliferation, enhanced ECM production & unique cytokine ) • Phenotypic differences in fibroblasts lead to tissue remodeling, deposition of ECM and augmented angiogenesis • Abundance of stromal cells correlates with poor prognosis in several cancer types • Elevated expression of matrix metalloproteinases correlates with poor prognosis • 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 WNT-16B (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

20. Vasculature • 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) • Tissue-specific vascular function (in healthy and tumor env). • Inadequate function results in areas of hypoxia and limited nutrient supply • 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-angiogenicligand VEGFA is associated with poor prognosis • 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

21. Immune cells • Tumor cells mediate immune suppression • 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 • Immune infiltration distribution is not uniform (Clustering on the leading edge of a lesion has prognostic consequences) => Crucial role of intratumor localization. • :T-cell activation / inhibition • direct: continousengagment 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 • Analysis of the micro-env signatures showed that angiogenesis, hypoxia and immune suppressive signatures were associated with poor outcome • Therapy: • Cancer: Chemoevokesrecuirtmentsupressive macrophages • Melanoma, following BRAF inhibition, increasedtumorantigen expression. At time of progression thisreverted + emergence of markers of immune cell exhaustion. • Transplanting T cells – works but not always

22. Pause II The complexity of a tumor is a result of continous crosstalk between tumor cells and the environment => can’t see “all” from pretreatment biopspies Heterogeneity <=> Resistance <=> Biomarkers identification New therapeutic strategy: target the stroma and avoid messing with the genomic instability “lost-fight” Genomicinstability Therapeuvtic potential Micro-env All the rest ? All the rest ? Mechanism ? Stroma Metabolism ?

23. Perspective

26. Supplementary Material

27. Clonal Evolution Genetic disease (of the aged) Evolving « system » (time & space). Heterogeneity ! Clonal Evolution (stepwise acquisition of mutations) Interaction (cell-cell, micro-enviroment) 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).

28. 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.

29. 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.

30. 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

31. 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.