This is a mechanism module, not a specific disease. Disorder entries reference individual nodes via conforms_to (e.g., "immune_checkpoint_blockade#Adaptive Immune Resistance"). The module defines the expected pathophysiology structure; conforming nodes in disorder files should include the corresponding cell types, biological processes, and causal edges, specialized to their tumor context. Key tumor-specific substitutions: MSI-H CRC uses dMMR-driven hypermutation as the neoantigen source; melanoma uses UV-induced mutation burden; virus-associated cancers (NPC, EBV gastric) use viral antigen presentation alongside somatic neoantigens.
Base Tumor-Immune PhysiCell Model
C++/XML/CSV
PhysiCell
AGENT_BASED
Grammar-based PhysiCell agent-based model of a heterogeneous tumor under immune surveillance. Immune cells chemotax toward tumor-derived signals, form physical contacts, and attempt contact-mediated killing, making this a useful executable baseline for the anti-tumor T cell response segment of this module.
Official sample model from the manuscript-synced grammar_samples release. Most relevant to the "Anti-Tumor T Cell Response" and early immune-escape portions of this module.
Extended Tumor-Immune PhysiCell Model
C++/XML/CSV
PhysiCell
AGENT_BASED
Expanded grammar-based PhysiCell tumor-immune model with a richer set of immune-tumor interaction rules than the base example. This is a better executable analogue for adaptive immune resistance and state-dependent suppression within checkpoint-responsive tumors.
Official sample model from the manuscript-synced grammar_samples release. Best treated as a reusable executable reference for checkpoint-sensitive tumor-immune interaction logic rather than a disease-specific digital twin.
Neoantigen Generation
trigger
Tumor cells accumulate somatic mutations, some of which produce novel peptides (neoantigens) presented on MHC class I molecules. The neoantigen source varies by tumor type: mismatch repair deficiency in MSI-H cancers, UV-induced mutations in melanoma, viral antigens in virus-associated cancers, or high tumor mutational burden from other causes. Higher neoantigen load generally correlates with greater immunogenicity and checkpoint inhibitor responsiveness.
Downstream
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Anti-Tumor T Cell Response
Show evidence (1 reference)
"Somatic mutations in cancer cells can generate tumour-specific neoepitopes, which are recognized by autologous T cells in the host. As neoepitopes are not subject to central immune tolerance and are not expressed in healthy tissues, they are attractive targets for therapeutic cancer vaccines."
Review directly describing how somatic mutations generate tumor-specific neoantigens recognized by host T cells, supporting the neoantigen generation mechanism. Evidence source is OTHER because this is a review article.
Anti-Tumor T Cell Response
effector
Dendritic cells present tumor neoantigens to naive T cells, priming CD8+ cytotoxic T lymphocytes that infiltrate the tumor and recognize tumor cells via MHC-I/neoantigen complexes. CTLA-4 acts as a brake at this priming stage in lymph nodes, competing with CD28 for B7 ligand binding. The magnitude of the T cell response depends on neoantigen immunogenicity, dendritic cell function, and the balance of co-stimulatory versus co-inhibitory signals during priming.
Downstream
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Adaptive Immune Resistance
The anti-tumor immune response itself triggers adaptive upregulation of checkpoint ligands by tumor cells, creating a negative feedback loop.
Show evidence (1 reference)
"Blockade of PD-1/PD-L1 by neutralizing antibodies restores T cells activity and enhances anti-tumor immunity, achieving remarkable success in cancer therapy."
Review confirming that anti-tumor T cell responses exist but are suppressed by PD-1/PD-L1 signaling, and can be restored by checkpoint blockade. Evidence source is OTHER because this is a review article.
Adaptive Immune Resistance
central effector
Tumor cells upregulate PD-L1 (and PD-L2) expression in response to interferon-gamma secreted by infiltrating T cells. This adaptive mechanism represents a co-opted physiological immune homeostasis pathway: PD-L1 engagement of PD-1 on effector T cells delivers inhibitory signals that suppress cytotoxicity, cytokine production, and proliferation. Tumors with active adaptive immune resistance are termed "immune-adapted" and are the best candidates for PD-1/PD-L1 blockade therapy, as the underlying anti-tumor immunity exists but is being actively suppressed.
Used by disorders
Thymoma
as PD-L1 Mediated Adaptive Immune Resistance
Downstream
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T Cell Exhaustion and Immune Escape
Chronic checkpoint engagement drives T cells toward an exhausted phenotype with progressive loss of effector function.
Show evidence (1 reference)
"The interaction of PD-1 and PD-L1 negatively regulates adaptive immune response mainly by inhibiting the activity of effector T cells while enhancing the function of immunosuppressive regulatory T cells (Tregs), largely contributing to the maintenance of immune homeostasis that prevents..."
Directly describes the adaptive immune resistance mechanism: tumors co-opt the PD-1/PD-L1 homeostatic pathway to suppress anti-tumor T cell activity. Evidence source is OTHER as this is a review.
T Cell Exhaustion and Immune Escape
consequence
Persistent antigen exposure combined with chronic PD-1 signaling drives tumor-infiltrating T cells toward an exhausted phenotype characterized by progressive loss of cytokine production, cytotoxicity, and proliferative capacity, with upregulation of multiple inhibitory receptors (PD-1, LAG-3, TIM-3, TIGIT). The immunosuppressive tumor microenvironment is further reinforced by recruitment of regulatory T cells, myeloid-derived suppressor cells, and tumor-associated macrophages. This results in functional immune escape despite physical T cell presence in the tumor.
Show evidence (2 references)
"The exhausted T cells in the tumor microenvironment show overexpressed inhibitory receptors, decreased effector cytokine production and cytolytic activity, leading to the failure of cancer elimination."
Review directly describing T cell exhaustion in the tumor microenvironment, including overexpression of inhibitory receptors (PD-1, LAG-3, TIM-3) and loss of effector function leading to immune escape. Evidence source is OTHER as this is a review article.
"Despite the huge success and efficacy of the anti-PD therapy response, it is limited to specific types of cancers, which attributes to the insufficient and heterogeneous expression of PD-1 in the tumor microenvironment."
Establishes that immune escape via checkpoint pathways varies across cancers, with PD-1 expression heterogeneity explaining differential responses to checkpoint blockade.