The immunogenicity control axis: a multi-omics framework for integrating epigenetic, DNA damage response, and immune states in cancer.
4 affiliations
- 1Department of Bioscience, Manipal University Jaipur, Jaipur, Rajasthan, India.
- 2Division of Immunobiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States.
- 3Department of Internal Medicine, Marshall University, Huntington, WV, United States.
- 4Department of Zoology, University of Lucknow, Lucknow, India.
Abstract
Immunotherapy has transformed cancer treatment, yet therapeutic responses remain heterogeneous and are incompletely explained by immune-centric biomarkers alone. We propose the Immunogenicity Control Axis (ICA), a testable multi-omics framework integrating three complementary dimensions of tumor state: epigenetic regulation, DNA damage response (DDR), and immune activity. The central hypothesis is that epigenetic permissiveness influences immune-relevant transcription and antigen presentation, while DDR-associated genomic processes contribute to antigenic variation; together, these tumor-intrinsic features interact with the immune state to shape tumor immune visibility. To make this hypothesis quantitatively testable, the ICA is operationalized through independently derived Epigenetic, DDR, and Immune scores that are standardized and integrated into a composite ICA Score. Using cervical cancer as an initial disease context, patient-derived TCGA-CESC analyses provide exploratory assessment of ICA-associated molecular states and prognostic relationships, while synthetic analyses are used separately to illustrate specific analytical procedures. The framework is further extended to perturbational analysis, in which CMap/LINCS transcriptional signatures and network information are used to prioritize candidate natural compounds predicted to oppose ICA-associated molecular states. These computational analyses are intended as hypothesis-generating operationalizations rather than biological or clinical validation. ICA therefore provides a falsifiable framework for testing whether coordinated epigenetic, DDR, and immune information captures tumor immunogenic variation beyond individual molecular dimensions and for prioritizing perturbational hypotheses for subsequent experimental validation.
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BibTeX
@article{srivastava2026immunogenicity,
title = {{The immunogenicity control axis: a multi-omics framework for integrating epigenetic, DNA damage response, and immune states in cancer.}},
author = {Manyata Srivastava and Shishir Singh and Diksha Ameta and Aesha Singh and Monisha Banerjee and Atar Singh Kushwah},
journal = {Frontiers in genetics},
year = {2026},
month = oct,
doi = {10.3389/fgene.2026.1944709},
url = {https://europepmc.org/article/MED/42948523},
note = {CC BY},
}
RIS
TY - JOUR
TI - The immunogenicity control axis: a multi-omics framework for integrating epigenetic, DNA damage response, and immune states in cancer.
AU - Manyata Srivastava
AU - Shishir Singh
AU - Diksha Ameta
AU - Aesha Singh
AU - Monisha Banerjee
AU - Atar Singh Kushwah
PY - 2026
DA - 2026/10/14
JO - Frontiers in genetics
DO - 10.3389/fgene.2026.1944709
UR - https://europepmc.org/article/MED/42948523
AB - Immunotherapy has transformed cancer treatment, yet therapeutic responses remain heterogeneous and are incompletely explained by immune-centric biomarkers alone. We propose the Immunogenicity Control Axis (ICA), a testable multi-omics framework integrating three complementary dimensions of tumor state: epigenetic regulation, DNA damage response (DDR), and immune activity. The central hypothesis is that epigenetic permissiveness influences immune-relevant transcription and antigen presentation, while DDR-associated genomic processes contribute to antigenic variation; together, these tumor-intrinsic features interact with the immune state to shape tumor immune visibility. To make this hypothesis quantitatively testable, the ICA is operationalized through independently derived Epigenetic, DDR, and Immune scores that are standardized and integrated into a composite ICA Score. Using cervical cancer as an initial disease context, patient-derived TCGA-CESC analyses provide exploratory assessment of ICA-associated molecular states and prognostic relationships, while synthetic analyses are used separately to illustrate specific analytical procedures. The framework is further extended to perturbational analysis, in which CMap/LINCS transcriptional signatures and network information are used to prioritize candidate natural compounds predicted to oppose ICA-associated molecular states. These computational analyses are intended as hypothesis-generating operationalizations rather than biological or clinical validation. ICA therefore provides a falsifiable framework for testing whether coordinated epigenetic, DDR, and immune information captures tumor immunogenic variation beyond individual molecular dimensions and for prioritizing perturbational hypotheses for subsequent experimental validation.
SN - 1664-8021
ER -