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Platelet RNA–Based Liquid Biopsy

Conventional liquid biopsy technologies rely on detecting tumor-derived DNA,

which typically becomes detectable only after cancer has progressed.


Foretell My Health introduces a platelet RNA–based approach that analyzes

signals from tumor-educated platelets (TEPs)—platelets actively altered by

cancer cells—to enable detection at earlier stages of disease.


How Cancer Cells Transform Platelets

Cancer cells release proteins, RNA, and exosomes, or interact directly with platelets, altering their genetic information. 

These transformed platelets carry distinct RNA signatures that reflect the presence, location, and progression of cancer. 

By decoding these signals, we can not only detect cancer early but also predict treatment response and patient outcomes.

PCR-based Molecular Profiling of Platelets

Foretell My Health analyzes platelet-associated RNA signals using PCR-based molecular profiling. This technology enables sensitive and quantitative detection of cancer-related molecular changes in platelets and serves as a robust foundation for scalable and standardized diagnostic testing.

Imaging-Based Analysis of Platelet Signal Changes

During cancer development, tumor-associated signals actively reshape circulating platelets and alter their phenotypic characteristics.
Foretell My Health captures these changes through imaging-based analysis of platelets, providing an additional layer of signal characterization that complements molecular profiling.

Abnormal Platelets
Abnormal Platelets
Normal Platelets
Normal Platelets

Foretell My Health Early Detection

Estimated 5x increase in early detection (at stage I and II)

Projected 36% improvement in survival rate

Technology

Foretell My Health combines advanced platelet RNA profiling with AI-powered analytics to accurately predict the presence, type, and stage of cancer.

Multiplexed RNA Profiling 

Simultaneous analysis of thousands of platelet RNA transcripts
AI-based Prediction

Deep-learning algorithms identify cancer-specific RNA patterns
Non-invasive Testing 

Early cancer detection and monitoring through a single blood draw
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Reading the signals within blood to foretell the onset of cancer

Research and Validation

Our technology is being clinically validated in collaboration with leading medical institutions in Korea. Results are continuously published in peer-reviewed journals, academic conferences, and patent filings, demonstrating the robustness and innovation of our approach.

Publications

Catalyzing early ovarian cancer detection: Platelet RNA-based precision screening

iScience

Eunyong Ahn, Se Ik Kim, Sungmin Park, Sarah Kim, Hyejin Lee, Yeochan Kim, Sangick Park, Suyeon Lee, Dong Won Hwang, Heeyeon Kim, HyunA Jo, Untack Cho, Juwon Lee, Cheol Lee, TaeJin Ahn, Yong-Sang Song

Innovative qPCR Algorithm Using Platelet-Derived RNA for High-Specificity and Cost-Effective Ovarian Cancer Detection

Cancers (Basel)

Ahn E, Kim SI, Park S, Kim S, Kim H, Lee H, Kim H, Song EJ, Ahn T, Song YS

Presentations

Abstract 7073: Development and validation of a high-specificity PCR algorithm for ovarian cancer diagnosis

2025 AACR Poster Presentation

Eunyong Ahn, Se Ik Kim, Sungmin Park, Sarah Kim, Hyunjung Kim, Hyejin lee, Heeyeon Kim, TaeJin Ahn, Yong-Sang Song

Abstract 2339: Development of a blood cell analysis-based AI model for detecting early ovarian cancer signals

2025 AACR Poster Presentation

Eunyong Ahn, Sungmin Park, Sarah Kim, Se Ik Kim, Hyejin Lee, Heeyeon Kim, Seong Eun Kang, Ji Won Park, TaeJin Ahn, Yong-Sang Song

Abstract 1065: Two-step method for early detection of ovarian cancer with high specificity via platelet RNA

2024 AACR Poster Presentation

Eunyong Ahn, Se Ik Kim, Sungmin Park, Sarah Kim, Yeochan Kim, Eunchong Huang, Suyeon Lee, Dong Won Hwang, Heeyeon Kim, HyunA Jo, Untack Cho, Juwon Lee, TaeJin Ahn, Yong-Sang Song

Abstract 5549: Normalized platelet splicing junction count is a novel biomarker for diagnosis of ovarian tumors

2023 AACR Poster Presentation

Eunyong Ahn, Se Ik Kim, Sungmin Park, Sarah Kim, Seung Jin Yang, Yeochan Kim, Dong Won Hwang, Heeyeon Kim, HyunA Jo, Untack Cho, Juwon Lee, Yong-Sang Song, TaeJin Ahn

Patents

Exon-junction markers and reference markers for cancer diagnosis
2025.05

KR: 1020250058986

PCT/KR2025/006080

Method and system for providing information on tumor diagnosis based on artificial intelligence using blood cell analysis

2025.04

KR: 1020250053812

Method for diagnosing cancer using exon-junction information of RNA in blood
2023.10

KR: 1020230138881

PCT/KR2023/016067