I work at the intersection of philosophy of science, philosophy of biology, and philosophy of medicine, with a focus on the explanatory structure of contemporary oncology. My research examines competing theories of cancer — somatic mutation theory, metabolic theory, tissue organisation field theory, and clonal evolution models — asking whether these frameworks reflect divergent ontological commitments about what cancer fundamentally is, and whether they generate genuine causal conflicts that integrative frameworks such as the Hallmarks of Cancer leave unresolved.
I completed my M.A. at Leibniz Universität Hannover under the supervision of Dr. Uljana Feest and Dr. Thomas Reydon, and have been a regular participant in seminars and research exchanges at the IHPST (Université Paris 1 Panthéon-Sorbonne) since 2024. I was an invited attendee of the SIRIC EpiCure laboratory research group at the Hôpital Gustave Roussy under the direction of Dr. Lucie Laplane.
Affiliations & Engagements
Contemporary oncology is characterised by the coexistence of multiple explanatory frameworks — somatic mutation theory, clonal evolution models, cancer stem cell theory, tissue organisation field theory, ecological models, and metabolic approaches. Standard accounts treat these frameworks as complementary mechanisms within a broadly unified research programme. This thesis examines whether such treatments are adequate to the actual structure of theoretical disagreement in the field: specifically, whether the frameworks in question merely emphasise different causal pathways or whether they reflect divergent ontological commitments about what kind of thing cancer fundamentally is.
The thesis distinguishes five ontological types in cancer research — cellular-genetic, hierarchical, tissue-organisational, ecological, and energetic — and analyses how each generates distinct experimental practices and therapeutic strategies. It examines why the coexistence of these commitments is not dissolved by appeal to integrative frameworks such as the Hallmarks of Cancer (Hanahan & Weinberg, 2000; 2011; 2022).
Drawing on Woodward's (2003) interventionist theory of causation and Craver's (2007) account of mechanistic explanation, the thesis develops a diagnostic framework for identifying when competing explanatory models generate genuine alethic conflicts — cases where both cannot be true of the same system under the same conditions. The variable-selection problem in interventionism is examined as a diagnostic tool for locating where the frameworks diverge not merely in emphasis but in causal ontology.
The following papers are currently in preparation for submission to journals in philosophy of science and philosophy of biology. Each paper extends and develops arguments from the master's thesis, targeting distinct aspects of theoretical pluralism in oncology. Click any paper to access interactive explanatory visuals.
Multistage progression of cancer from normal epithelium to invasive/metastatic disease. Each stage represents an accumulation of cellular alterations. Classification adapted from standard TNM staging (Brierley et al., 2017) and Vogelstein & Kinzler's (2004) multistep carcinogenesis model.
Vogelstein, B. & Kinzler, K.W. (2004). Cancer genes and the pathways they control. Nature Medicine, 10, 789–799. · Hanahan, D. & Weinberg, R.A. (2000; 2011; 2022). Hallmarks of Cancer. Cell.
The five ontological types of cancer theory, each reflecting a distinct answer to the question: what is the primary unit of disease? Each type generates a different set of experimental targets and therapeutic strategies.
Türkyilmaz, Y. (2024). Competing Theories of Cancer (M.A. Thesis). · Sonnenschein, C. & Soto, A.M. (2011). The tissue organisation field theory. BioEssays. · Hanahan, D. (2022). Hallmarks of Cancer: New Dimensions. Cancer Discovery.
Ontological commitment: Cancer is fundamentally a disease of the cell — specifically, of the cell's DNA. The primary unit of disease is the individual somatic cell bearing one or more driver mutations.
Causal locus: Intracellular — the nucleus, the genome.
Therapeutic implication: Identify and target specific mutant proteins (precision oncology); eliminate mutant clones.
Experimental practice: Genome sequencing, mutation profiling, CRISPR knockout models, targeted drug development.
Ontological commitment: Cancer is a disease of tissue organisation — a disruption in the default state of cellular proliferation caused by altered extracellular signalling fields. The primary unit of disease is tissue architecture, not the individual cell.
Causal locus: Extracellular — the tissue microenvironment, stroma-epithelium signalling.
Therapeutic implication: Normalise tissue organisation; restore epithelial–stromal relationships rather than killing mutant cells.
Experimental practice: 3D organoid culture, ECM disruption models, transplant-reversal experiments.
SMT and TOFT do not merely describe different aspects of the same phenomenon. They make incompatible claims about the primary locus of causal responsibility for cancer initiation. Under SMT, a mutant cell transplanted into normal tissue should give rise to cancer; under TOFT, normal cells placed in a disrupted tissue microenvironment should become tumourigenic. The empirical evidence from transplantation experiments (Mintz & Illmensee, 1975; Sonnenschein & Soto, 2011) is interpreted differently by each framework. This is not a difference in emphasis — it is a difference in what would count as a cause of cancer, which is a paradigmatic case of alethic conflict between competing causal ontologies.
Sonnenschein, C. & Soto, A.M. (1999). The Society of Cells. Bios Scientific. · Sonnenschein, C. & Soto, A.M. (2011). The tissue organisation field theory of cancer. BioEssays, 33, 332–340. · Vogelstein, B. et al. (2013). Cancer genome landscapes. Science, 339, 1546–1558. · Mintz, B. & Illmensee, K. (1975). Normal genetically mosaic mice produced from malignant teratocarcinoma cells. PNAS, 72, 3585–3589.
Each theoretical framework in oncology identifies a different primary site of causal origin and a different sequence of events leading to cancer. These are not merely different descriptions of the same process — they locate the disease in different biological entities and attribute causal priority to different variables.
Hanahan, D. & Weinberg, R.A. (2011). Cell, 144, 646–674. · Sonnenschein & Soto (2011). BioEssays. · Seyfried, T.N. (2012). Cancer as a Metabolic Disease. Wiley. · Laplane, L. (2016). Cancer Stem Cells: Philosophy and Therapies. Harvard UP. · Nowell, P.C. (1976). Science, 194, 23–28.
Random mutations → clonal expansion of fitter variants. Classic Darwinian logic.
States, not just genes, are heritable. Cells can revert to stem-like states.
Fitness is relational. Competition and cooperation within the tumour ecosystem drive progression.
Darwinian selection acts on genetically variant clones. Fitness is determined by mutation-driven replication advantages. Inheritance is vertical, via cell division.
Selection operates on cellular states and stemness capacities. Cancer stem cells (CSCs) sit atop a differentiation hierarchy; non-CSCs may revert to stemness.
Tumour progression is governed by ecological dynamics within the tumour microenvironment. Fitness is relational, not intrinsic — determined by niche availability and competition.
Three distinct instantiations of evolutionary theory in oncology. Each answers differently: what evolves? what is inherited? what determines fitness? These are not merely different levels of analysis — they generate incompatible predictions about therapeutic resistance and clonal dynamics.
Nowell, P.C. (1976). The clonal evolution of tumor cell populations. Science, 194, 23–28. · Greaves, M. & Maley, C. (2012). Clonal evolution in cancer. Nature, 481, 306–313. · Laplane, L. (2016). Cancer Stem Cells: Philosophy and Therapies. Harvard UP. · Aktipis, A. et al. (2015). Cancer across the tree of life. Phil Trans R Soc B, 370.
The three evolutionary models in oncology each instantiate the basic Darwinian triad — variation, selection, inheritance — differently. These differences are not matters of emphasis but of what counts as a valid evolutionary unit and mechanism.
Nowell (1976) · Greaves, M. & Maley, C. (2012). Clonal evolution in cancer. Nature, 481, 306–313. · Marusyk, A. et al. (2012). Intra-tumour heterogeneity. Nature Reviews Cancer.
In the clone-selectionist model, heritable variation arises through random mutation — not in response to environmental pressure. Selection acts after variation has arisen. Inheritance is strictly vertical: parent cell → daughter cells. The environment (the tumour microenvironment) acts as a selective filter, not a generator of heritable variation.
Key prediction: Resistance mutations pre-exist treatment; they are selected for, not induced by, the therapeutic environment (Luria-Delbrück logic applied to oncology).
In the plasticity-hierarchical and eco-evolutionary models, cellular states can shift in response to environmental signals — and these state-changes can be heritable across cell generations via epigenetic mechanisms (DNA methylation, histone modification). This constitutes a form of environmentally induced heritable variation: a structural parallel to Lamarckian inheritance.
Key prediction: Resistance can be induced by therapeutic pressure through epigenetic reprogramming, not merely selected from pre-existing variants. This has direct consequences for adaptive therapy strategies.
The coexistence of Darwinian and quasi-Lamarckian inheritance mechanisms in cancer cells is not philosophically trivial. It corresponds to a genuine incompatibility within evolutionary oncology about the causal structure of heritable variation. If resistance mutations are pre-selected (Darwinian), sequencing before therapy predicts outcome. If resistance is epigenetically induced (quasi-Lamarckian), pre-therapeutic sequencing has limited predictive value. The frameworks generate conflicting clinical recommendations.
This is not merely a question about mechanisms but about what kind of interventions — on what variables — would be effective. In Woodwardian terms, the two frameworks disagree about which variables are invariantly connected to therapeutic outcomes across the relevant intervention range.
Flavahan, W.A. et al. (2017). Epigenetic plasticity and the hallmarks of cancer. Science, 357. · Laplane, L. (2016). Cancer Stem Cells: Philosophy and Therapies. Harvard UP. · Gould, S.J. (2002). The structure of evolutionary theory. · Woodward, J. (2003). Making Things Happen. Oxford UP.
Primary claim: Driver mutations in oncogenes and tumour suppressor genes are the initiating and sustaining cause of cancer. Metabolic reprogramming is a downstream consequence of genetic change.
Causal direction: Mutation → altered gene expression → metabolic reprogramming
Therapeutic target: Mutant proteins (e.g., BRAF V600E, KRAS G12C inhibitors)
Dominance factors: Technological infrastructure (NGS, CRISPR), actionability in clinical oncology, alignment with pharmaceutical industry investment, institutional embodiment in TCGA, ICGC
Primary claim: Cancer originates from irreversible damage to mitochondrial oxidative phosphorylation. Somatic mutations are a downstream consequence of metabolic dysfunction, not the primary cause. The cell's compensatory shift to fermentation is the initiating event.
Causal direction: Mitochondrial dysfunction → reactive oxygen species → nuclear genome instability → somatic mutations
Therapeutic target: Metabolic environment — ketogenic diet, hyperbaric oxygen, press-pulse strategy (Seyfried et al., 2017)
SMT and MTC agree that cancer cells exhibit both somatic mutations and metabolic reprogramming (the Warburg effect). They disagree about the causal direction of this association. This is not a factual disagreement about whether the association exists, but a disagreement about which variable is the upstream cause and which is the downstream effect. In Woodwardian terms: an intervention on the metabolic state would, under MTC but not SMT, be expected to alter mutation rates; an intervention on key driver mutations would, under SMT but not MTC, be expected to reverse metabolic phenotype. These are empirically distinct predictions with different intervention targets — a paradigmatic case of frameworks generating different answers to the same interventionist question about causal structure.
Vander Heiden, M.G. et al. (2009). Understanding the Warburg Effect. Science, 324, 1029–1033. · Seyfried, T.N. (2012). Cancer as a Metabolic Disease. Wiley. · Warburg, O. (1956). On the origin of cancer cells. Science, 123, 309–314.
Otto Warburg (1956) observed that cancer cells preferentially ferment glucose to lactate even in the presence of oxygen — aerobic glycolysis. This is energetically inefficient (2 ATP vs. 36–38 ATP per glucose molecule) yet confers biosynthetic advantages for rapidly dividing cells. The metabolic theory of cancer (Seyfried, 2012; Pedersen, 1978) treats this as the proximal cause of cancer — initiated by mitochondrial damage. SMT treats it as a downstream consequence of oncogene activation (e.g., MYC, HIF-1α upregulation). The same biological phenomenon — aerobic glycolysis — is interpreted as cause or effect depending on which theoretical framework is operative. This illustrates the theory-ladenness of cancer data and the structural difficulty of adjudicating between frameworks using shared evidence.
Warburg, O. (1956). On the origin of cancer cells. Science, 123, 309–314. · Pedersen, P.L. (1978). Tumor mitochondria. Progress in Experimental Tumor Research. · Seyfried, T.N. & Shelton, L.M. (2010). Cancer as a metabolic disease. Nutrition & Metabolism.
| Determinant | How it advantages SMT | Effect on alternatives |
|---|---|---|
| Technological infrastructure | Next-generation sequencing, CRISPR, proteomics — all built for genomic analysis. The Cancer Genome Atlas (TCGA) produced >20,000 tumour genomes. Tools embody SMT's ontology. | Metabolic and tissue-level frameworks lack comparable data infrastructure; entry costs to competition are structurally higher. |
| Actionability (clinical) | A mutation is 'actionable' if a licensed drug targets it. This concept is built around mutant proteins. Precision oncology's clinical language is SMT-entrenched. | Metabolic interventions (dietary, metabolic drugs) do not fit 'actionability' criteria, creating a systematic disadvantage in clinical trial design and regulatory approval. |
| Pharmaceutical alignment | Small-molecule inhibitors targeting specific mutant proteins are highly patentable and lucrative. Industry investment massively favours SMT-derived targets. | Metabolic approaches (e.g., dietary intervention, repurposed generic drugs) have low commercial incentive, regardless of efficacy evidence. |
| Institutional embodiment | TCGA, ICGC, most major cancer centres organise data around mutational profiling. Peer review norms, grant structures, and training programmes are SMT-aligned. | Alternative frameworks face structural barriers to achieving comparable institutional presence — a non-epistemic source of asymmetric persistence. |
| Experimental translatability | Mouse models with defined driver mutations (e.g., KRASG12D, TP53R172H) are well-established and widely used. Results translate predictably within SMT. | Metabolic and tissue-level models require different experimental systems (e.g., altered diet models, ECM disruption); less established and harder to fund. |
Non-epistemic determinants of framework dominance in oncology. Each factor independently and jointly reinforces SMT's institutional position without necessarily tracking relative empirical adequacy.
Kuhn, T.S. (1962). The Structure of Scientific Revolutions. · Longino, H.E. (1990). Science as Social Knowledge. · Douglas, H. (2009). Science, Policy, and the Value-Free Ideal. · Topol, E.J. (2012). Individualized medicine from prewomb to tomb. Cell.
SMT: Do mutations → metabolic changes? Yes, necessarily.
MTC: Do metabolic changes → mutations? Yes, necessarily.
Both cannot be the primary initiating cause.
SMT: Intervening on mutations will change cancer phenotype.
MTC: Intervening on metabolic state will change mutation rates.
These are different causal variables.
SMT: Primary locus is the nucleus (genome).
MTC: Primary locus is the mitochondrion.
Nuclear transplant experiments test this directly.
Two causal claims C₁ and C₂ are alethically compossible with respect to a system S if and only if there exists a possible world in which both C₁ and C₂ are simultaneously true of S under the same description.
The three conflicts identified above fail the compossibility criterion: under the same system description (a specific cancer cell at a specific time), both the claim that mutations are causally prior and the claim that metabolic dysfunction is causally prior cannot be simultaneously true.
This is not a trivial logical point. It establishes that the apparent pluralism — 'both are true at different levels' — cannot discharge the conflict without either (a) changing the system description or (b) changing what counts as a causal claim.
Woodward, J. (2003). Making Things Happen. Oxford UP. · Baumgartner, M. (2010). Shallow analysis and the causation problem. Philosophy of Science. · Kistler, M. (2006). Causation and Laws of Nature. Routledge. · Craver, C.F. (2007). Explaining the Brain. Oxford UP.
Woodward's interventionism evaluates causal claims by asking: would an ideal intervention on X produce a change in Y? But this presupposes that the variables X and Y have already been selected for inclusion in the model. The variable-selection problem asks: what determines which variables enter the causal model in the first place?
Includes: specific driver mutations (KRAS, TP53, BRCA1/2, APC…), signalling pathway activations, copy number variants, chromatin accessibility
Excludes: systemic metabolic state, dietary environment, mitochondrial integrity as primary variables
Includes: mitochondrial membrane potential, ROS levels, ATP/ADP ratio, lactate output, oxygen availability, respiratory capacity
Includes mutations only as downstream markers, not primary causal variables
The two frameworks do not merely weight the same variables differently — they include different variables in their causal models. A Woodwardian evaluation of SMT claims using MTC variable sets, and vice versa, will produce systematically different causal verdicts. This is the diagnostic function of the variable-selection problem: it reveals that the frameworks are not operating on the same causal domain even when describing the same cancer cell.
Woodward, J. (2003). Making Things Happen. Ch. 2–3. · Spirtes, P. et al. (2000). Causation, Prediction, and Search. MIT Press. · Hausman, D. & Woodward, J. (1999). Independence, invariance, and the causal Markov condition. British Journal for the Philosophy of Science.
Craver's (2007) account of mechanistic multilevel explanation holds that higher-level and lower-level descriptions of the same mechanism are mutually constitutive: the upper level is realised by, and only makes causal claims in virtue of, the lower level. The 'nesting assumption' requires that multi-level causal claims refer to nested components of the same mechanism.
If the assumption holds: SMT and MTC would describe nested levels of a single mechanism — mutations would be higher-level descriptions realised by metabolic lower-level processes, or vice versa. The frameworks would be complementary by definition.
This is the standard integrationist response: Hanahan & Weinberg's Hallmarks framework implicitly assumes that all the causal factors it catalogues are nested within a single mechanistic framework of tumour biology.
If the assumption fails: SMT and MTC describe the same cellular events — metabolic reprogramming and somatic mutation — but attribute different causal roles to them within non-nested mechanistic structures. The upper-level SMT claim (mutations cause cancer) is not realised by but rather in competition with the upper-level MTC claim (metabolic dysfunction causes cancer).
This paper argues the nesting assumption fails for the SMT/MTC comparison in the cancer initiation context.
Nuclear/Cytoplasmic Transfer Experiments as Philosophical Test Cases: A set of transplantation experiments — transferring nuclei and cytoplasm between normal and cancerous cells in various combinations — provides a direct empirical test of SMT vs. MTC. Under SMT, transferring a cancerous nucleus into a normal cytoplasm should produce malignancy. Under MTC, transferring normal cytoplasm into a cancer cell should suppress malignancy. The results of such experiments (reviewed in Seyfried, 2012, ch. 11) have been interpreted as partial support for MTC's predictions, but the interpretation remains contested because the experimental results are theory-laden in ways that prevent straightforward adjudication between frameworks.
Craver, C.F. (2007). Explaining the Brain. Oxford UP. · Seyfried, T.N. (2012). Cancer as a Metabolic Disease. Wiley (ch. 11). · Hanahan, D. & Weinberg, R.A. (2011). Hallmarks of Cancer: The Next Generation. Cell, 144, 646–674.