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Slide 1-

CANCER: focus on tradeoffs, mismatches, evolution of causes & *somatic evolution within the body*
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Evolutionary biology of cancer SEVEN PRINCIPLES OF EVOLUTION & CANCER Cancer is mediated by somatic evolution Cancer is many tissue-specific and age-associated diseases, with one commonality in uncontrolled cell replication (3) The somatic evolution of cancer is mediated by the population-genetic forces of mutation, selection & genetic drift, in a phylogenetic, phylogeographic context (4) Cancer is a polygenic, heritable, and environmental disease, mediated in part by mismatches between current and ancestral conditions (5) The ultimate causes of cancer involve evolutionary tradeoffs & co-option of normal evolved functions involving growth, maintenance, and reproduction (6) Anticancer adaptations have evolved (7) Cancer cell populations evolve in response to therapies
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Genetic, epigenetic, genomic, and cytogenetic changes YOU SOMATIC EVOLUTION Your somatic cell lineages birth YOUR KIDS GERMLINE EVOLUTION
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Frank, 2010, PNAS
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Evolutionary biology of cancer SEVEN PRINCIPLES OF EVOLUTION & CANCER Cancer is mediated by somatic evolution Cancer is many tissue-specific and age-associated diseases, w/ one commonality in uncontrolled cell replication (3) The somatic evolution of cancer is mediated by the population-genetic forces of mutation, selection & genetic drift, in a phylogenetic, phylogeographic context (4) Cancer is a polygenic, heritable, and environmental disease, mediated in part by mismatches between current and ancestral conditions (5) The ultimate causes of cancer involve evolutionary tradeoffs & co-option of normal evolved functions involving growth, maintenance, and reproduction (6) Anticancer adaptations have evolved (7) Cancer cell populations evolve in response to therapies
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The simplest definition is from the American Cancer Society (ACS). According to the ACS, cancer is a group of diseases characterized by uncontrolled growth and spread of abnormal cells. If the spread is not controlled, it can result in death The Hallmarks of Cancer, all of which evolve somatically (1) self-sufficiency in growth signals (2) insensitivity to anti-growth signals (3) evading apoptosis (4) sustained angiogenesis (5) limitless replicative potential (6) invasion and metastasis (7) escaping immunosurveillance
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ppt slide no 7 content not found
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Some cancer terminology Classification by tissue type: carcinoma epithelial cell 90% of all tumours derived from ectoderm (mostly) or endoderm (some) sarcoma connective tissue 2% of all tumours derived from mesoderm leukaemia circulatory or lymphatic 8% of all tumours derived from mesoderm Classification by the type of cells: Adenomatous cells ductal or glandular cells Squamous cells flat cells Myeloid blood cell Lymphoid lymphocytes or macrophages Cancer is many diseases with one commonality
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Childhood cancers differ from adult cancers Classification by tissue type: carcinoma epithelial cell 90% of all tumours derived from ectoderm (mostly) or endoderm (some) sarcoma connective tissue 2% of all tumours derived from mesoderm leukaemia circulatory or lymphatic 8% of all tumours derived from mesoderm MOST ADULT CANCERS (stem cells, progenitor cells, de-differentiation, increased risk with age) MOST CHILDHOOD CANCERS (failures of differentiation, other losses of replication control, decreased risk with age except for osteosarcoma)
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‘Types’ of genes that undergo alterations in cancer I ‘ONCOGENES’ -undergo dominant gains of function (e.g., increased activity or higher expression of gene product) -often involved in stimulating cell replication (eg IGF2) (2) ‘TUMOR SUPPRESSOR’ GENES -undergo losses of function via genetic or epigenetic inactivation, such that cell survival, replication are less controlled; loss of one copy may have no or minor effects, loss of both copies is major alteration -often involved in cell cycle regulation (eg RB1, CDKN1C) NOTE: (a) all of these genes generally have OTHER primary functions (b) genes may be tumor suppressor or oncogene in one tissue, at one time point, NOT in other (c) effects of such genes are subject to TRADEOFFS w/ other functions
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PNAS 2008 Bioch Biophys Acta 2010 H19 gene product: normal primary function: in placenta, restricts growth and cell migration, and regulates angiogenesis under hypoxic conditions; promotes differentiation of cytotrophoblast cells; also regulates post-natal growth ADAPTIVE FUNCTIONS Acts as growth restraint/tumor suppressor gene *If P53 suffers loss of function, then H19 acts as an oncogene in hypoxic environment of tumors MALADAPTATIVE FUNCTION
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‘Types’ of genes that undergo alterations in cancer II GATEKEEPER GENES: genes that regulate growth and differentiation; include oncogenes and tumor suppressor genes (2) CARETAKER GENES: genes that help to maintain genetic integrity; their loss of function mutations lead to -microsatellite instability (due to mismatch repair deficiency) -chromosomal instability (gain or loss of chromosomes or parts thereof) (3) LANDSCAPER GENES: genes that when mutated lead to abnormal extracellular or intracellular environment that contributes to carcinogenesis
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Adult Cancer Risk Increases with Age (~40% get it, in lifetime) due to sequential accumulation of mutations over a long time (2) senescence-related tissue changes that can promote cancer development
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Crespi 2011 PRSLB Pediatric Cancer Risk decreases with age & parallels growth velocity; 2nd leading cause of child death in developed countries osteosarcoma
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Evolutionary biology of cancer SEVEN PRINCIPLES OF EVOLUTION & CANCER Cancer is mediated by somatic evolution Cancer is many tissue-specific and age-associated diseases, with one commonality in uncontrolled cell replication (3) The somatic evolution of cancer is mediated by the population-genetic forces of mutation, selection & genetic drift, in a phylogenetic, phylogeographic context (4) Cancer is a polygenic, heritable, and environmental disease, mediated in part by mismatches between current and ancestral conditions (5) The ultimate causes of cancer involve evolutionary tradeoffs & co-option of normal evolved functions involving growth, maintenance, and reproduction (6) Anticancer adaptations have evolved (7) Cancer cell populations evolve in response to therapies
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populations cancer cells
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Somatic evolution of cancer cell populations Stepwise, nested generation of hierarchical among-cell genetic, epigenetic, cytogenetic diversity leading to evolution of six hallmarks of cancer via mutation, epimutation, chromosomal alterations; evolution in response to selective pressures including immune system, ‘competition’ between cells, ‘cooperation’ between cancer cell lineages Origin of genomic instability, leading to much higher mutation rate (2) Evolution of cancer cell populations in response to therapeutic agents
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CANCER CELLS EVOLVING BY NATURAL SELECTION Variation in the population of cells: Somatic mutations. Variation amongst cells is Heritable: Mutations in DNA, chromosomes, methylation patterns. Variation affects Reproduction and Survival of the cells: e.g., suppression of apoptosis etc. ‘ADAPTATION?’ sort of, but not in usual sense
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Evolution Within a Neoplasm
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Cancer cells evolve via genetic, epigenetic, genomic and cytogenetic changes in large numbers of genes CLASSIC LINEAR MODEL:
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But classic, unitary linear model fails due to high diversity of genetic, epigenetic, cytogenetic pathways whereby the hallmarks of cancer can be acquired
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One example of progression to cancer
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Constant population One example of progression to cancer
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‘Advantageous’ ‘driver’ mutant (increases net proliferation of lineage) - in any number of genes; genetic, epigenetic or chromosomal One example of progression to cancer
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Clonal expansion
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Saturation
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Another ‘advantageous’ mutant
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Wave of clonal expansion
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How Might Diversity Change During Progression? Genetic, Phylogenetic and Demographic Change Waves of Clonal Expansion Population Subdivisions No Selective Sweeps Lineages Divergence Number of Clones
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PNAS 2008 The results of cancer cell population-level evolution, for two patients Other patients? Other cancers? Regularities, for therapeutic targets?
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Population Genetics of Cancer: Rate of Evolution What is the probability of a new cellular/genetic variant emerging and expanding in a population? Function of: Mutation rate (rate of variant generation) Population size (numbers of mutational targets) Generation time (rate of turnover) Strength of selection (rate of clonal expansion) EFFECTS OF GENETIC VARIABILITY ON PROGRESSION ->
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Genetic Diversity Predicts Progression - Number of Clones, in Barrett’s esophagous Median: progressors 3 (range: 1 - 9) non-progressors 1 (range: 1 - 7) RR = 1.40 per clone (95% CI:1.13 - 1.73) p < 0.01 Controlling for p53 LOH, aneuploidy and tetraploidy Maley et al. (2006) Nat. Gen. 38:468–73 N=267 Carlo Maley
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Genetic Diversity Predicts Progression Mean Pairwise Divergence Median: progressors 7% (range: 0–54%), non-progressors 0% (range: 0–27%) RR = 1.45 per 10% divergence (95% CI:1.08 - 1.95) p < 0.05 Controlling for p53 LOH, aneuploidy and tetraploidy Maley et al. (2006) Nat. Gen. 38:468–73 N=267
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Genetic, epigenetic, genomic, and cytogenetic changes Your cell lineages birth SOMA LINE GERM LINE, genetic variation, inherited and de novo
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Evolutionary biology of cancer SEVEN PRINCIPLES OF EVOLUTION & CANCER Cancer is mediated by somatic evolution Cancer is many tissue-specific and age-associated diseases, with one commonality in uncontrolled cell replication (3) The somatic evolution of cancer is mediated by the population-genetic forces of mutation, selection & genetic drift, in a phylogenetic, phylogeographic context (4) Cancer is a polygenic, heritable, and environmental disease, mediated in part by mismatches between current and ancestral conditions (5) The ultimate causes of cancer involve evolutionary tradeoffs & co-option of normal evolved functions involving growth, maintenance, and reproduction (6) Anticancer adaptations have evolved (7) Cancer cell populations evolve in response to therapies
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Hematology/Oncology Clinics of North America Volume 24, Issue 5, October 2010, Pages 973-996 -Many common alleles of small effect found by GWAS -Small % of heritability ‘explained’ so far -Rare variants being studied now -High genetic heterogeneity likely -Epigenetics virtually unstudied -Gene x Env’t interactions unstudied Heritabilities 10-50% depending on form of cancer Galvan et al. 2010 Trends Genet.
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Crespi 2011, Evol. Appl. Visualizing inherited genetically- based risk (‘closer to’ vs ‘farther from’ cancer at conception) Allele frequencies vs effect sizes of risk alleles
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Genetic PLUS Environmental impacts; showing importance of chance mutational events Greaves 2007 Nat Rev Cancer
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* How evolutionary mismatches can affect cancer risk Greaves 2008
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* * Effects of mismatches between ancestral and current conditions on chronic disease risk Eaton et al. 1994 QRB
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Mismatches and female reproductive cancers I Eaton et al. 1994 QRB
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Mismatches and female reproductive cancers II Eaton et al. 1994 QRB
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Mismatches and female reproductive cancers III Eaton et al. 1994 QRB
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Urology 2001
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Evolutionary biology of cancer SEVEN PRINCIPLES OF EVOLUTION & CANCER Cancer is mediated by somatic evolution Cancer is many tissue-specific and age-associated diseases, with one commonality in uncontrolled cell replication (3) The somatic evolution of cancer is mediated by the population-genetic forces of mutation, selection & genetic drift, in a phylogenetic, phylogeographic context (4) Cancer is a polygenic, heritable, and environmental disease, mediated in part by mismatches between current and ancestral conditions (5) The ultimate causes of cancer involve evolutionary tradeoffs & co-option of normal evolved functions involving growth, maintenance, and reproduction (6) Anticancer adaptations have evolved (7) Cancer cell populations evolve in response to therapies
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EXAMPLE: tradeoff between cancer and senescence mediated by effects of p53 gene Judy Campisi, UC Berkeley
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Cancer risk trades off with aging in mice p53 alleles in this mouse strain: + = wild type - = loss of function m = mutation Good news! The m allele appears to confer resistance to tumors (6% vs >45%) Bad News! The m allele appears to have a cost in terms of aging (die off sooner than p53+/+ wild types) Tyner et al. 2002
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EXAMPLE: Tradeoffs between cancer risk and risks of neurodegenerative diseases Schizophrenia, Huntington’s, Parkinson’s, Alzheimer’s PLoS Genetics 2010 Genetic basis: PARK2 APC TP53 ATM, etc etc ->identify pathways
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EXAMPLE: CHILDHOOD GROWTH - CANCER TRADEOFF As seen, age-specific growth rate is positively associated with age-specific cancer risk in children Childhood cancer risk positively associated with higher birth weight, faster fetal growth See Crespi 2011 PRSLB
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Rapid cell proliferation DNA repair Apoptosis Cancer risk, rates Senescence, Lifespan SELECTION ON TRADEOFFS: -growth/cancer -repair/proliferation/cancer -senescence/apoptosis/cancer
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Placenta as 1o genetic & developmental source of hallmarks of cancer; Co-option of placentally expressed pathways Ferretti et al. 2006 Hum Rep Update
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Family of X-linked, primate-specific cancer/testis associated genes (CTAs), expressed in normal testis, involved in spermatogenesis, and in tumor cells, promote cancer cell growth. Roles in spermatozoa development and function, cell cycle regulation, and apoptosis. Associated with aggressiveness of skin tumors, inherited testicular and prostate cancer risk. Kleene (2005) provides evidence that many CTAs (such as SPANX) are subject to extremely strong selection in the context of sperm production Cancer cells dedifferentiate and take on properties of immortal male germ cells. sperm function ‘HIJACKING’ of gene expression, functions, networks cancer risk ‘Co-option’ of testis genes, pathways in carcinogenesis
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‘Co-option’ of gene expression patterns, pathways, cell/tissue phenotypes by cancer, from: -Placentation -Male germ cell proliferation (cancer/testis antigens) Stem cells Childhood growth systems (IGF2, other genes) trade off with cancer risk Other reproductive tissues subject to rapid growth, strong selection Wound healing (cell migration, angiogenesis, local cell proliferation) EXPECT TRADEOFFS OF THESE CELL, TISSUE FUNCTIONS WITH CANCER RISK
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Evolutionary biology of cancer SEVEN PRINCIPLES OF EVOLUTION & CANCER Cancer is mediated by somatic evolution Cancer is many tissue-specific and age-associated diseases, with one commonality in uncontrolled cell replication (3) The somatic evolution of cancer is mediated by the population-genetic forces of mutation, selection & genetic drift, in a phylogenetic, phylogeographic context (4) Cancer is a polygenic, heritable, and environmental disease, mediated in part by mismatches between current and ancestral conditions (5) The ultimate causes of cancer involve evolutionary tradeoffs & co-option of normal evolved functions involving growth, maintenance, and reproduction (6) Anticancer adaptations have evolved (7) Cancer cell populations evolve in response to therapies
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Crespi & Summers 2005, TREE Putative anti-cancer adaptations proportions, separation, progression of stem cells, progenitor cells, differentiated cells (2) regenerative ability only in tissues that suffer damage (3) stem cells kept in separate compartments, to limit initial spread via microenvironment effects (4) cell division primarily in early fetal development, in relatively protected conditions (5) cellular senescence and apoptosis in response to DNA damage (6) immunosurveillance
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Colon tissue architecture Crypts of a colon
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Colon tissue crypt architecture Stem cells replenish the tissue; asymmetric divisions Gut Proliferating cells divide symmetrically and differentiate Differentiated cells get shed off into the lumen
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Evolutionary biology of cancer SEVEN PRINCIPLES OF EVOLUTION & CANCER Cancer is mediated by somatic evolution Cancer is many tissue-specific and age-associated diseases, with one commonality in uncontrolled cell replication (3) The somatic evolution of cancer is mediated by the population-genetic forces of mutation, selection & genetic drift, in a phylogenetic, phylogeographic context (4) Cancer is a polygenic, heritable, and environmental disease, mediated in part by mismatches between current and ancestral conditions (5) The ultimate causes of cancer involve evolutionary tradeoffs & co-option of normal evolved functions involving growth, maintenance, and reproduction (6) Anticancer adaptations have evolved (7) Cancer cell populations evolve in response to therapies
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Traditional vs Targeted cancer drugs -Traditional drugs: very toxic agents that kill all dividing cells -Targeted drugs: small molecule inhibitors - target the specific pathways which make cancerous cells cancerous (e. g., Gleevec inhibits a tyrosine kinase)
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Targeted cancer drugs Very effective Not toxic However, evolution of resistance poses a problem Bcr-Abl protein Gleevec Mutation
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Gerlinger & Swanton 2010 Br J Cancer Genetic, epigenetic cytogenetic clonal heterogeneity evolve during carcinogenesis Drug treatments select for resistant clones, via different routes Cancer may undergo remission, but recurs Metastasis & resistance cause death
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DATA: Therapies Select for Resistance Mutations With 109–1012 cells in a neoplasm and 104+ mutations, the presence of a resistance mutation is likely Imatinib (Gleevec) resistance: Point mutations in the kinase domain of BCR-ABL – Gorre & Sawyers. Curr. Opin. Hematol. 9:303-7 (2002) Mutation present before therapy – Roche-Lestienne & Preudhomme. Sem. Hematol. 40:80-2 (2003) Gefitinib resistance: EGFR mutation – Kobayashi et al. NEJM 352:786-92 (2005) MET amplification – Engelman et al. Science 316:1039-43 (2007) 5-fluorouracil resistance: TYMS amplification – - Wang et al. PNAS 101:3089–3094 (2004)
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Implications of cancer somatic evolution, variation for therapy Need to personalize treatment by genotyping the cancer; identify and target the driver mutations and the expected therapy-resistance mutations (2) Genotyping must involve sampling cancer cell population diversity (3) Evolutionary responses to therapies can be monitored (4) Cancer cells can be stabilized rather than maximally killed (reducing selection for evolution of resistant lineages) (5) Genomic instability can be increased to intolerable levels (6) Adaptive immune system and cancers can be manipulated to generate immune recognition of cancer cells (!)
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Interested in career in cancer biology, using evolutionary concepts and tools? Learn cell biology, cancer biology Learn, apply genomic and bioinformatic tools, and/or collaborate (3) Consider an MD or MD-PhD (4) Develop and apply therapies based on evolutionary principles