Michail Ignatiadis: New Neural-Network Approach for ctDNA Profiling in Breast Cancer
Michail Ignatiadis/X

Michail Ignatiadis: New Neural-Network Approach for ctDNA Profiling in Breast Cancer

Michail Ignatiadis, Director, Breast Medical Oncology Clinic and Program at Institut Jules Bordet, shared on LinkedIn:

“I am delighted to share our latest piece on fragmentomics and ctDNA profiling in breast cancer.

We developed ALFAssay, a neural-network approach that estimates ctDNA fraction from cfDNA fragmentation patterns using shallow whole-genome sequencing.

Across 896 plasma samples from patients with early and metastatic breast cancer and healthy controls, ALFAssay showed 87% sensitivity and 94% specificity for ctDNA detection and provides complementary information to copy-number- and mutation-based approaches.

Our goal is to move toward multimodal liquid biopsy, combining different cfDNA signals rather than relying on a single genomic feature.”

Title: ALFAssay: A feed‑forward neural network for quantitative fragmentomics‑based ctDNA profiling in breast cancer

Authors: Alexandra Stanciu, Andrea Gombos, Elisa Agostinetto, Delphine Vincent, Laurence Buisseret, Andreas Papagiannis, Francoise Rothe, Nicola Occelli, Christos Sotiriou, David Venet, Michail Ignatiadis.

Read the full article.

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Michail Ignatiadis: New Neural-Network Approach for ctDNA Profiling in Breast Cancer