Cell-free DNA · Epigenomics · Precision Oncology

Predict who responds
to immunotherapy

Totiomics decodes methylation patterns in circulating cell-free DNA to identify patients most likely to benefit from immune checkpoint therapy — before treatment begins.

78%
3-year survival in predicted responders
~14M
Cancer patients receiving immunotherapy annually
3×
Higher signal vs. TMB alone
<7d
Blood draw to clinical report

From blood draw to clinical insight

Three steps. One tube of blood. Actionable methylome-derived predictions that inform treatment decisions across oncology.

01

Liquid Biopsy Collection

A standard 10 mL blood draw provides circulating cell-free DNA. No tissue biopsy required — minimally invasive and suitable for serial monitoring throughout the treatment journey.

02

Methylome Profiling

Our proprietary cfDNA methylation sequencing pipeline interrogates LINE-1 elements, CpG islands, and immune-regulatory loci — capturing the epigenomic landscape invisible to standard mutation-based tests.

03

ML Response Prediction

Our machine learning models — trained on multi-centre phase II clinical trial data — integrate methylation scores with immune profiling features to generate a patient-level response probability.

Built for every stakeholder in cancer care

Whether you're accelerating a drug programme, investigating tumour immunity, or navigating a treatment decision — Totiomics gives you the epigenomic signal you need.

Pharmaceutical

Drug Development & Clinical Trials

Enrich your immunotherapy trials with predictive biomarker stratification. Reduce cohort sizes, cut development costs, and increase regulatory confidence with validated cfDNA methylation endpoints.

  • Patient stratification for ICI trial enrolment
  • Companion diagnostic development support
  • Pharmacodynamic monitoring during trials
  • Regulatory-grade biomarker qualification data
  • Integration with existing multi-omic platforms
Explore partnerships
Research Labs

Academic & Translational Research

Accelerate discovery with access to our validated methylation analysis pipeline. Integrate cfDNA methylomics into immunology, oncology, or computational biology research programmes.

  • API access to the Totiomics analysis pipeline
  • Batch processing for cohort-level studies
  • Co-development of novel methylation biomarkers
  • Annotated cfDNA methylation reference datasets
  • Collaboration on publication-grade analyses
Request research access
Patients

Informed Treatment Decisions

Before starting immunotherapy, understand your likelihood of response. The Totiomics report gives you and your oncologist a personalised, blood-based prediction to support shared decision-making.

  • Non-invasive single blood draw
  • Personalised response probability score
  • Plain-language patient report
  • Oncologist consultation support material
  • Compatible with NHS and private referral pathways
Learn about testing

Epigenomic precision at clinical scale

Totiomics combines long-read sequencing, genome-wide methylation profiling, and validated machine learning to deliver actionable predictions — not just biomarker correlations.

Multi-omic Integration

Combines cfDNA methylation with RNA-seq immune profiling and clinical variables for robust, multi-dimensional predictions.

Rapid Turnaround

From sample receipt to clinical report in under 7 days. Designed for real-world clinical workflows, not just research settings.

Clinically Validated

Models trained and tested on prospective phase II clinical trial data across multiple cancer indications and treatment contexts.

API & EHR Integration

Seamless integration with clinical and research data ecosystems via a secure REST API and HL7/FHIR-compatible reporting.

Circular methylation heatmap visualisation showing CpG methylation patterns across the genome

Methylation as a window into immune evasion

Genomic hypomethylation in late-replicating domains and LINE-1 elements is mechanistically coupled to tumour immune evasion. When tumours silence antigen-presentation genes via promoter hypermethylation, they become invisible to T-cells. Totiomics reads these epigenomic signals from a simple blood draw — earlier and more comprehensively than tissue biopsy.

cfDNA Methylomics LINE-1 Hypomethylation Immune Checkpoint Blockade CpG Island Analysis Tumour Microenvironment PD-1 / CTLA-4 Pathways MHC Regulation Survival Analysis
Cancer Cell
Tumour monocyte content predicts immunochemotherapy outcomes in oesophageal adenocarcinoma — published in Cancer Cell (2023)
AUC 0.83
ROC achieved by integrating methylation, mutation, immune and clinical biomarkers — outperforming any single modality alone
5+ cancers
Ability to assess NSCLC, melanoma, bladder, renal cell, and head & neck indications
cfDNA
Captures intra-tumour heterogeneity missed by single-site tissue biopsy

Ready to unlock the methylome?

Whether you're evaluating Totiomics for a clinical trial, integrating it into your research pipeline, or seeking a test for a patient — our team will guide you through the process.

Our publications

Peer-reviewed research, conference abstracts, and theses underpinning the Totiomics platform — from epigenetic biomarker discovery to multi-omics immunotherapy prediction.

10
Total publications
2022–2025
Active research period
5+
Cancer indications studied
2025 1 publication
Preprint

MIND: Multimodal Integration with Neighbourhood-aware Distributions

Xing, H., & Yau, C.

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2024 3 publications
Thesis University of Oxford

Deep molecular profiling of the anti-tumour immune response in immune checkpoint inhibitor-treated oesophageal cancer

Fuchs, H.

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Conference abstract Cancer Research

Abstract CT208: High tumor monocyte content predicts long-term survival for patients with operable oesophageal cancer treated with neoadjuvant immunochemotherapy in the LUD2015-005 trial

Fuchs, H. S., James, S. A., Carroll, T. M., Xie, P. F., Chadwick, J. A., Parkes, D., Lord, S. R., Griffiths, L., Underwood, T., Karydis, I., Petty, R. T., Schuster-Böckler, B., Owen, R. P., Middleton, M. R., & Lu, X.

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Conference abstract Clinical Cancer Research — Liquid Biopsy

Abstract PR017: A T-cell signature in circulating cell-free DNA at time of diagnosis predicts response to checkpoint inhibition

Xie, P., Etzioni, Z., Song, C.-X., Owen, R. P., Middleton, M. R., Lu, X., & Schuster-Boeckler, B.

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2023 4 publications
Journal article Cancer Cell

Tumor monocyte content predicts immunochemotherapy outcomes in esophageal adenocarcinoma

Carroll, T. M., Chadwick, J. A., Owen, R. P., White, M. J., Kaplinsky, J., Peneva, I., Frangou, A., Xie, P. F., Chang, J., Roth, A., Amess, B., James, S. A., Rei, M., Fuchs, H. S., McCann, K. J., Omiyale, A. O., Jacobs, B. A., Lord, S. R., Norris-Bulpitt, S., … LUD Team.

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Conference abstract Journal of Clinical Oncology

Long-term outcomes from adding durvalumab to neoadjuvant treatment of operable gastroesophageal cancers: Results from a multicenter study LUD2015-005

Middleton, M. R., Karydis, I., Lu, X., Ryan, A., Venhaus, R. R., Ramirez, K. A., Macri, M., Ricciardi, T., Lawrence, M., Scott-Brown, M., Griffiths, G. O., Collins, L., Griffiths, L., Wilding, S., Lord, S., Owen, R., & Petty, R. D.

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Thesis University of Oxford

DNA methylation in late-stage oesophageal cancer

Xie, P.

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Conference abstract Cancer Research

Abstract LB131: Association between epigenetic heterogeneity of esophageal adenocarcinoma and response to first-line immunochemotherapy in LUD2015-005 Trial

Xie, P. F., Chang, J., Siejka-Zielińska, P., Inoue, M., Drożdż, M., Chadwick, J. A., Carroll, T. M., Owen, R. P., White, M. J., Kaplinsky, J., Amess, R., Middleton, M., Kriaucionis, S., Song, C., Schuster-Böckler, B., & Lu, X.

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2022 2 publications
Thesis University of Oxford

Antibodies, B cells, and immune tolerance in immunotherapy treated oesophageal cancer

Chadwick, J.

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Conference abstract Cancer Research

Abstract 1247: Comprehensive molecular profiling to predict first-line immunochemotherapy outcomes in inoperable esophageal adenocarcinoma

Carroll, T. M., Chadwick, J. A., Owen, R. P., White, M. J., Kaplinsky, J., Peneva, I., Frangou, A., Chang, J., Xie, P. F., Roth, A., Amess, B., Lou, H., McCann, K. J., Berridge, G., Fischer, R., Phetsouphanh, C., Omiyale, A. O., Jacobs, B.-A., Ahern, D., … Lu, X.

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