AutoTFCNNY: A multi-instance neural network for enhanced early cancer detection using TCR data.

ABSTRACT: For most cancers, early diagnosis and intervention can significantly improve cure rates and patient survival. Consequently, achieving early and accurate cancer detection has always been a central focus in both medical practice and scientific research. Recently, studies based on peripheral blood T-cell receptors (TCRs) have attracted considerable attention due to their noninvasiveness and potential for high sensitivity. It has been reported that cancer-associated TCRs (caTCRs) exist in the peripheral blood of cancer patients, suggesting that discerning whether a TCR repertoire is associated with cancer provides a viable strategy for early cancer prediction. However, extracting crucial cancer-related information from a large and heterogeneous TCR repertoire remains a major challenge.To addre

SUBMITTER: Yang D 

PROVIDER: S-EPMC12507200 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature