Systems Oncology: Cancer as a Network of Metabolism, Immunity, Genetics and the Tumor Microenvironment (2026)
Cancer is not simply a mass of abnormal cells.
It is an evolving biological system in which cancer cells interact continuously with immune cells, stromal cells, blood vessels, extracellular matrix, metabolites, hormones, microbes and the host environment.
Systems oncology attempts to understand cancer by studying these interconnected networks rather than examining individual pathways in isolation.
This perspective is becoming increasingly important because cancer progression, metastasis and treatment resistance rarely result from a single mutation or pathway. Tumor genetics influence metabolism. Metabolism influences immune function. Immune pressure shapes tumor evolution. The tumor microenvironment changes nutrient availability and signaling. Stromal cells can support cancer growth. Systemic metabolism and host factors can influence the tumor environment.
Recent research increasingly describes these interactions as dynamic networks connecting the tumor, its microenvironment and the whole-body host.
Instead of asking only "Which mutation caused this cancer?", systems oncology asks:
"How are genetics, metabolism, immunity, the tumor microenvironment and the host interacting to produce this cancer's behavior—and how can those interactions be therapeutically exploited?"
Table of Contents
- What Is Systems Oncology?
- The Cancer Network
- 1. Cancer Genetics and Evolution
- 2. Epigenetics Connects Genetics and Metabolism
- 3. Cancer Metabolism
- 4. Immunometabolism
- 5. Cancer and the Immune System
- 6. The Tumor Microenvironment
- 7. Cancer-Associated Fibroblasts
- 8. Tumor-Associated Macrophages
- 9. Hypoxia, Angiogenesis and Oxygen
- 10. The Gut Microbiome
- 11. Cancer Stem Cells
- 12. Tumor Heterogeneity and Evolution
- 13. Systems Biology of Treatment Resistance
- 14. Metastasis as a Systems Process
- 15. Why Single Biomarkers Are Often Insufficient
- 16. From Precision Oncology to Systems Oncology
- 17. Therapeutic Strategies
- 18. What Is Clinically Established?
- 19. The Future of Systems Oncology
- Frequently Asked Questions
What Is Systems Oncology?
Systems oncology is an interdisciplinary approach to cancer that studies the interactions between multiple biological systems involved in tumor development, progression and treatment response.
It draws on concepts from:
- Cancer genetics
- Genomics
- Epigenetics
- Systems biology
- Cancer metabolism
- Immunology
- Immunometabolism
- Tumor microenvironment biology
- Computational biology
- Multi-omics
- Precision medicine
- Evolutionary biology
The goal is not to replace conventional oncology with a single theory.
Rather, systems oncology provides a framework for understanding why tumors behave differently even when they share the same broad diagnosis.
The Cancer Network
A simplified systems model can be represented as follows:
The arrows should not be interpreted as a simple one-way chain.
These systems form feedback loops.
For example, tumor genetics can alter metabolism. Altered metabolism can change the immune microenvironment. Immune pressure can eliminate sensitive tumor clones. Resistant clones can then expand and acquire additional adaptations.
This dynamic interaction is central to modern cancer biology.
1. Cancer Genetics and Evolution
Genetic alterations remain fundamental to cancer.
Mutations and other genomic changes can activate growth pathways, disable tumor suppressors, alter DNA repair and influence treatment sensitivity.
Examples include alterations involving:
- TP53
- KRAS
- EGFR
- PIK3CA
- BRAF
- ALK
- ROS1
- HER2
- BRCA1/2
- APC
- MYC
- RB1
But a mutation should not be viewed in isolation.
The biological effect of a mutation depends on its interaction with other genomic alterations, cell state, tissue context and environmental conditions.
Genetics also influences the immune system
Mutations can affect whether cancer cells produce recognizable neoantigens, how antigens are presented and how tumors interact with immune cells.
Immune pressure can then influence which cancer clones survive.
Recent work on immunoediting shows how immune-mediated selection can shape intratumoral heterogeneity and contribute to resistance to immune checkpoint blockade.
2. Epigenetics Connects Genetics and Metabolism
Genes do not operate independently of cellular state.
Epigenetic regulation determines which genes are accessible and active without necessarily changing the underlying DNA sequence.
Metabolism and epigenetics are closely connected because metabolites can act as substrates or cofactors for enzymes that modify chromatin.
Examples include metabolites associated with:
- Acetyl-CoA
- S-adenosylmethionine
- NAD+
- α-ketoglutarate
- Succinate
- Fumarate
- 2-hydroxyglutarate
This creates a powerful systems-level concept:
Metabolism can influence gene regulation, while gene regulation can reshape metabolism.
Recent research describes interconnected metabolic, epigenetic and immune mechanisms contributing to tumor plasticity, immune evasion and treatment resistance.
3. Cancer Metabolism
Cancer cells frequently reprogram metabolism to support growth, survival and adaptation.
The classic example is increased glucose consumption and glycolytic activity, often discussed through the Warburg effect.
But cancer metabolism is far more complicated than simply "cancer cells use sugar."
Tumors can alter:
- Glucose metabolism
- Glycolysis
- Glutamine metabolism
- Fatty-acid synthesis
- Fatty-acid oxidation
- Nucleotide synthesis
- One-carbon metabolism
- Mitochondrial respiration
- Lactate production
- Redox metabolism
- Amino-acid metabolism
- Autophagy-related nutrient recycling
These metabolic adaptations are not fixed. Cancer cells can switch metabolic strategies depending on tissue, nutrient availability, oxygen levels and treatment pressure.
Recent reviews emphasize that metabolic reprogramming influences not only tumor growth but also immune evasion and treatment response.
4. Immunometabolism: Where Cancer Metabolism Meets Immunity
Immunometabolism studies how metabolic pathways influence immune-cell behavior.
This is particularly important inside tumors because cancer cells and immune cells share the same constrained environment.
They compete for nutrients and are exposed to the same metabolites, oxygen levels and pH conditions.
For example, high nutrient consumption by tumor cells can alter the availability of substrates required by immune cells.
Lactate and other metabolites can also influence immune-cell function.
Reviews of the tumor microenvironment describe nutrient depletion, waste-product accumulation and altered metabolic signaling as mechanisms that can impair T-cell and macrophage activity.
The fact that metabolism influences immunity does not mean that a particular diet, supplement or metabolic drug has been proven to improve cancer outcomes.
The mechanistic biology is increasingly compelling, but therapeutic translation remains cancer-, pathway- and intervention-specific.
5. Cancer and the Immune System
The immune system can recognize and eliminate malignant cells.
But tumors can evolve mechanisms that suppress or evade immune attack.
Major components of anti-tumor immunity include:
- CD8+ cytotoxic T cells
- CD4+ T cells
- Natural killer cells
- Dendritic cells
- B cells
- Macrophages
- Antigen-presenting cells
At the same time, tumors can recruit or manipulate immune populations that support immune suppression.
This creates a dynamic competition:
Immune pressure can suppress cancer, while cancer evolution can suppress immunity.
Immune checkpoint inhibitors such as PD-1, PD-L1 and CTLA-4 inhibitors exploit this biology by removing inhibitory signals.
However, checkpoint blockade does not solve every component of immune dysfunction.
This is why immunotherapy resistance remains a major challenge.
6. The Tumor Microenvironment
The tumor microenvironment (TME) is the ecosystem surrounding cancer cells.
It includes:
- Immune cells
- Fibroblasts
- Endothelial cells
- Blood vessels
- Extracellular matrix
- Oxygen gradients
- Metabolites
- Cytokines
- Growth factors
- Extracellular vesicles
The TME is not merely passive scaffolding.
It actively influences cancer growth, invasion, metastasis, immune evasion and treatment response.
Recent research increasingly describes the TME as a metabolic ecosystem in which cancer cells, immune cells and cancer-associated fibroblasts exchange nutrients and metabolites.
7. Cancer-Associated Fibroblasts
Cancer-associated fibroblasts (CAFs) are important stromal cells within many solid tumors.
They can influence:
- Extracellular matrix structure
- Tumor stiffness
- Growth-factor signaling
- Angiogenesis
- Immune-cell infiltration
- Metabolism
- Drug penetration
CAFs are heterogeneous rather than a single uniform cell type.
This matters because targeting all fibroblasts indiscriminately could theoretically remove stromal populations that restrain rather than promote cancer.
Systems oncology therefore emphasizes cellular context and functional state rather than assuming that every component of the TME is inherently harmful.
8. Tumor-Associated Macrophages
Macrophages are abundant in many solid tumors.
Depending on context, macrophages can contribute to immune suppression, tumor growth, tissue remodeling and metastasis.
Recent research emphasizes that macrophage metabolism and local signals influence their functional state within the TME.
Potential therapeutic strategies include:
- Reducing recruitment of suppressive macrophage populations
- Changing macrophage functional states
- Targeting macrophage survival pathways
- Combining macrophage-directed therapies with immunotherapy
Most such approaches remain areas of active clinical research.
9. Hypoxia, Angiogenesis and Oxygen
Rapidly growing tumors can outpace their blood supply.
This produces regions of hypoxia.
Low oxygen can activate cellular programs that promote survival, angiogenesis, metabolic adaptation and immune suppression.
Abnormal tumor blood vessels can simultaneously create regions of poor perfusion and restrict immune-cell access.
This produces another systems feedback loop:
Hypoxia therefore connects metabolism, blood vessels, immune biology and tumor evolution.
10. The Gut Microbiome
The cancer ecosystem extends beyond the tumor itself.
The gut microbiome can influence systemic immunity, inflammation, metabolism and potentially responses to cancer therapy.
Research has identified associations between certain microbial communities and response to immune checkpoint blockade.
Akkermansia muciniphila has attracted particular interest in immunotherapy research, although the field remains far from establishing a universally effective microbiome intervention.
Potentially relevant mechanisms include:
- Microbial metabolites
- Short-chain fatty acids
- Bile-acid signaling
- Immune-cell maturation
- Intestinal barrier integrity
- Systemic inflammatory signaling
Microbiome research is therefore an excellent example of why cancer cannot always be understood solely by analyzing tumor DNA.
11. Cancer Stem Cells
Cancer stem cells (CSCs) are a proposed subset of tumor cells with stem-like properties, including self-renewal and the capacity to generate heterogeneous tumor populations.
CSCs are being investigated as contributors to:
- Tumor initiation
- Metastasis
- Recurrence
- Treatment resistance
- Phenotypic plasticity
- Immune escape
The CSC field is complex because the identity and behavior of stem-like cancer cells can be dynamic rather than permanently fixed.
Nevertheless, CSC biology fits naturally into a systems oncology framework because stem-like states can be influenced by hypoxia, metabolism, signaling pathways and the microenvironment.
See: Cancer Stem Cells: The Hidden Driver of Metastasis, Relapse and Drug Resistance.
12. Tumor Heterogeneity and Evolution
A major mistake in simplistic cancer models is treating a tumor as genetically uniform.
In reality, tumors can contain multiple subclones.
These populations may differ in:
- Driver mutations
- Metabolic state
- Antigen expression
- Growth rate
- Drug sensitivity
- Immune visibility
- Stem-like properties
Treatment creates selection pressure.
Sensitive populations may be eliminated while resistant populations survive.
Immune surveillance can produce similar evolutionary selection.
Research on immunoediting shows that immune pressure can select tumor populations with immune-evasive characteristics, contributing to intratumoral heterogeneity and resistance.
13. Systems Biology of Treatment Resistance
Cancer treatment resistance is rarely caused by one pathway.
Resistance can involve:
New mutations or expansion of pre-existing resistant clones.
Changes in gene regulation and cellular state.
Reprogramming of nutrient use, redox balance and energy production.
Protection provided by stromal cells, extracellular matrix and local signaling.
Immune escape, T-cell dysfunction and alternative inhibitory pathways.
Reversible changes in cell state that allow cancer cells to survive treatment.
This is why a tumor can become resistant to chemotherapy, targeted therapy or immunotherapy through multiple simultaneous mechanisms.
See the OneDayMD pillar: Cancer Treatment Resistance: Why Cancer Comes Back and How to Fight It.
14. Metastasis as a Systems Process
Metastasis is not simply cancer cells traveling from one organ to another.
Successful metastasis requires multiple coordinated steps.
- Local invasion
- Entry into blood or lymphatic vessels
- Survival during circulation
- Exit into distant tissue
- Adaptation to the new environment
- Establishment of a supportive niche
- Angiogenesis
- Immune evasion
- Metabolic adaptation
A metastatic cancer cell therefore enters a new ecological environment.
Its survival depends partly on whether it can adapt to the metabolic and immune conditions of that organ.
Recent work on tumor-host metabolic interactions emphasizes that metastatic cells can adapt their metabolism according to the environment of the distant organ.
15. Why Single Biomarkers Are Often Insufficient
Traditional precision oncology often asks whether a patient has a particular mutation.
That remains extremely important.
But systems oncology adds another question:
What is the functional state of the entire tumor ecosystem?
For example, two tumors may both contain the same driver mutation but differ in:
- Immune-cell infiltration
- PD-L1 expression
- TMB
- Metabolic phenotype
- Stromal composition
- Hypoxia
- Microbiome exposure
- Additional mutations
- Epigenetic state
These differences may contribute to different treatment responses.
It puts biomarkers into context.
The future is likely to involve combinations of genomic, transcriptomic, proteomic, metabolic, spatial and immune measurements rather than relying on a single number.
16. From Precision Oncology to Systems Oncology
Precision oncology generally attempts to match treatment to the molecular characteristics of a patient's tumor.
Systems oncology expands this framework.
Which mutation or biomarker does the tumor have?
How do genetics, cell states, metabolism, immunity and the microenvironment interact?
Neither approach replaces the other.
Systems oncology can be viewed as an expansion of precision medicine from molecular matching toward network-level understanding.
17. Therapeutic Strategies in Systems Oncology
The systems approach raises an important therapeutic possibility:
Can cancer be attacked at multiple biological levels simultaneously?
Potential strategies include:
Targeting the cancer driver
Examples include targeted therapies directed against actionable genomic alterations.
Targeting the immune system
Checkpoint inhibitors, cellular therapies, cancer vaccines and other immunotherapies attempt to restore or enhance anti-tumor immunity.
Targeting the tumor microenvironment
Researchers are investigating fibroblasts, macrophages, vasculature, extracellular matrix and immunosuppressive signaling.
Targeting metabolism
Metabolic pathways involving glucose, amino acids, lipids, nucleotides and immunosuppressive metabolites are being studied as therapeutic targets.
Targeting multiple systems simultaneously
Combination approaches may attempt to block tumor growth while simultaneously improving immune activity or altering the microenvironment.
Biological synergy in laboratory experiments does not automatically translate into clinical benefit.
Combining multiple treatments can also increase toxicity, drug interactions, cost and treatment complexity.
Systems oncology therefore requires evidence-based combination design, not simply adding more therapies together.
Cancer Metabolism: A Systems Opportunity, Not a Single "Cancer Diet"
OneDayMD's metabolic oncology content fits naturally within this framework.
However, systems oncology requires a more nuanced interpretation of cancer metabolism.
There is no single metabolic state shared by every cancer.
Cancer metabolism varies according to:
- Cancer type
- Tissue of origin
- Genotype
- Stage
- Metastatic site
- Nutrient availability
- Oxygen availability
- Prior therapy
- Microenvironment
Therefore, the statement "cancer feeds on sugar" is an oversimplification.
Cancer cells can use multiple metabolic pathways, and normal cells—including immune cells—also require nutrients.
Recent reviews emphasize that therapeutic manipulation of metabolism must consider the metabolism of immune cells as well as cancer cells.
18. What Is Clinically Established?
Systems oncology is a powerful scientific framework, but not every component of the framework is a clinically validated treatment strategy.
Some applications are already routine:
- Genomic testing for actionable cancer alterations
- Biomarker-guided targeted therapy
- PD-L1 testing in appropriate cancer settings
- MSI/MMR testing
- Selected TMB applications
- Immune checkpoint inhibitors
- Targeted therapies
- Radiation and systemic therapy combinations in appropriate settings
Other areas remain investigational:
- Metabolic reprogramming as a generalized cancer treatment
- Microbiome manipulation to improve immunotherapy
- Many metabolic-immunotherapy combinations
- Systems-level dietary interventions as cancer treatments
- Many CSC-targeting therapies
- AI-derived multi-omics treatment selection
- Many repurposed-drug combinations
A biological mechanism can be scientifically plausible without being clinically proven.
Cell studies → animal studies → observational studies → clinical trials → randomized trials represent progressively stronger evidence for determining whether an intervention actually benefits patients.
Repurposed Drugs Through a Systems Oncology Lens
Drug repurposing is particularly interesting from a systems perspective because an existing drug may affect several pathways simultaneously.
Examples investigated in cancer research include agents affecting:
- AMPK
- mTOR
- Autophagy
- Inflammation
- Angiogenesis
- DNA repair
- Cellular stress
- Immune signaling
- Metabolism
However, multi-target activity creates both opportunities and risks.
A drug that affects several pathways may produce unexpected interactions with chemotherapy, targeted therapy or immunotherapy.
Ivermectin, fenbendazole, mebendazole, niclosamide, metformin, statins and other repurposed agents have generated various cancer hypotheses or preclinical findings, but evidence strength differs substantially between agents and indications.
Laboratory activity or case reports should not be presented as proof that these drugs overcome cancer resistance or improve survival.
Multi-Omics: Measuring the Cancer System
Systems oncology increasingly depends on multi-omics.
Different technologies measure different layers of biology.
DNA mutations, copy-number changes and structural alterations.
Which genes are being actively expressed.
Regulatory changes affecting gene accessibility and expression.
Protein abundance and signaling activity.
Metabolites and metabolic state.
Where cells, proteins and molecular signals are located within tissue.
Combining these datasets could provide a more complete representation of tumor biology than any single test.
Artificial Intelligence and Systems Oncology
Systems oncology generates extremely complex datasets.
This makes artificial intelligence and machine learning potentially valuable tools for identifying patterns that are difficult to detect using conventional analysis.
Potential applications include:
- Predicting treatment response
- Identifying resistance mechanisms
- Integrating multi-omics data
- Analyzing digital pathology
- Predicting cancer evolution
- Identifying patient subgroups
- Discovering drug combinations
- Modeling tumor ecosystems
However, AI predictions require clinical validation.
An algorithm can discover a statistical association without proving that changing the associated biological pathway will improve patient outcomes.
19. The Future of Systems Oncology
The next stage of oncology may increasingly move from static tumor classification toward dynamic biological monitoring.
Instead of asking only:
"What mutations does this tumor have?"
future oncology may increasingly ask:
How is this tumor changing?
Which clones are expanding?
Which immune cells are active?
Which metabolic pathways are dominant?
Which resistance mechanisms are emerging?
Which treatment combination is most likely to disrupt the network?
This could lead to more dynamic treatment strategies based on repeated molecular and biological measurements.
The Systems Oncology Treatment Model
A useful conceptual model is:
This is not a replacement for evidence-based oncology.
It is a framework for making oncology increasingly mechanism-informed, biomarker-driven and adaptive.
Frequently Asked Questions
What is systems oncology?
Systems oncology is an approach to cancer that studies interactions among genetics, epigenetics, metabolism, immunity, the tumor microenvironment, microbiome and host biology rather than focusing on one pathway in isolation.
How is systems oncology different from precision oncology?
Precision oncology commonly matches treatment to molecular features such as mutations or biomarkers. Systems oncology expands the model by considering how multiple biological systems interact and change over time.
What role does cancer metabolism play in systems oncology?
Cancer metabolism influences tumor growth, adaptation and interactions with immune and stromal cells. Metabolic competition and metabolite signaling can also influence immune function within the tumor microenvironment.
Why is the tumor microenvironment important?
The tumor microenvironment contains immune cells, fibroblasts, blood vessels, extracellular matrix and signaling molecules that can influence tumor growth, immune escape, metastasis and treatment response.
Can changing cancer metabolism cure cancer?
There is currently no universal metabolic intervention proven to cure cancer. Metabolic pathways are important therapeutic research targets, but effectiveness depends on cancer type, molecular context and the specific intervention.
Does cancer always use glucose as its main fuel?
No. Cancer metabolism is heterogeneous and can involve glucose, glutamine, fatty acids, amino acids and mitochondrial pathways. Different tumors and even different regions of the same tumor can use different metabolic strategies.
Can the immune system change cancer evolution?
Yes. Immune pressure can eliminate susceptible cancer-cell populations and select for cells with immune-evasive properties, contributing to tumor evolution and heterogeneity.
Are cancer stem cells part of systems oncology?
Yes. Stem-like tumor-cell states can interact with metabolism, hypoxia, signaling pathways and the tumor microenvironment, making cancer stem-cell biology relevant to a systems model of cancer.
Can AI improve systems oncology?
Potentially. AI can help integrate large genomic, imaging, transcriptomic, proteomic and clinical datasets. However, AI-derived predictions require prospective clinical validation before they should guide treatment decisions.
Is systems oncology already used clinically?
Some components are already standard oncology practice, including molecular testing, biomarker-guided treatment and immunotherapy selection. The broader integration of multi-omics, dynamic monitoring and systems-level modeling remains an active area of research.
Related OneDayMD Research
Explore the relationship between cancer metabolism and anti-tumor immunity.
How cancer evolves resistance to chemotherapy, targeted therapy and immunotherapy.
Mechanisms of primary and acquired checkpoint inhibitor resistance.
The potential role of stem-like tumor cells in recurrence and resistance.
Why the immune state of the tumor can influence immunotherapy response.
Explore the wider immuno-oncology evidence library.
Conclusion: Cancer Is an Ecosystem
The most important contribution of systems oncology is conceptual:
Cancer is not simply a genetic disease, a metabolic disease or an immune disease.
It is an evolving biological ecosystem in which these systems continuously interact.
Genetic alterations influence cell signaling and metabolism.
Metabolism influences immune-cell function.
The immune system creates evolutionary pressure on tumors.
The tumor microenvironment determines which cells can survive.
Fibroblasts, macrophages and blood vessels can reshape the local ecosystem.
The microbiome and whole-body host environment can influence systemic immunity and metabolism.
These interactions can ultimately determine whether a tumor remains localized, metastasizes, responds to treatment or becomes resistant.
The future of oncology is therefore unlikely to be about finding one universal cancer pathway.
It is more likely to involve identifying the specific biological network sustaining an individual patient's cancer and then selecting evidence-based interventions capable of disrupting that network.
That is the promise of systems oncology: moving from a static description of cancer toward a dynamic understanding of how the tumor, immune system, metabolism and host continuously interact.
Selected Scientific References
- Altea-Manzano P, Decker-Farrell A, Janowitz T, Erez A. Metabolic interplays between the tumour and the host shape the tumour macroenvironment. Nature Reviews Cancer. 2025;25:274–292.
- Roerden M, Spranger S. Cancer immune evasion, immunoediting and intratumour heterogeneity. Nature Reviews Immunology. 2025;25:353–369.
- De Martino M, Rathmell JC, Galluzzi L, Vanpouille-Box C. Cancer cell metabolism and antitumour immunity. Nature Reviews Immunology. 2024;24:654–669.
- Trefny MP, Kroemer G, Zitvogel L, et al. Metabolites as agents and targets for cancer immunotherapy. Nature Reviews Drug Discovery. 2025;24:764–784.
- Mao Y, Xia W, Jiang P. Metabolites as signalling molecules in the tumour immune microenvironment. Nature Reviews Immunology. 2026;26:422–438.
- Jin R, Neufeld L, McGaha TL. Linking macrophage metabolism to function in the tumor microenvironment. Nature Cancer. 2025;6:239–252.
- Kay E, Zanivan S. The tumor microenvironment is an ecosystem sustained by metabolic interactions. Cell Reports. 2025.
- Hathaway ES, et al. Immunometabolic maladaptations to the tumor microenvironment. Cold Spring Harbor Perspectives in Medicine. 2024.
- You L, et al. Targeting metabolic-epigenetic-immune axis in cancer: molecular mechanisms and therapeutic implications. Signal Transduction and Targeted Therapy. 2026;11:28.
- Suleiman H, et al. Harnessing nucleotide metabolism and immunity in cancer: a tumour microenvironment perspective. FEBS Journal. 2025;292:2155–2172.
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