Translational Insights From the Molecular Landscape to Precision Therapy in Peripheral T‐Cell Lymphoma: Integrating Multi‐Omics and Artificial Intelligence

Peripheral T-cell lymphoma (PTCL) is a heterogeneous group of aggressive malignancies with poor prognosis and limited response to standard chemotherapy. Although recent advances in molecular and biological characterization have refined PTCL classification, profound molecular heterogeneity continues to result in highly variable treatment outcomes. Emerging targeted and immunotherapeutic agents show activity in specific subtypes, yet responses remain difficult to predict amid their biological complexity. This review synthesizes current molecular insights, evaluates the limitations of existing therapies, and explores the potential of multi-omics profiling integrated with artificial intelligence (AI) to decode complex signatures for improved subtype classification, treatment response prediction, and survival prognostication. By addressing the "black-box" issue through explainable AI, this approach offers a promising framework to advance PTCL management from empirical treatment toward biomarker-driven precision therapy.

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Publication Details

Journal
European Journal Of Haematology
Published
2026-09-08
DOI
https://doi.org/10.1111/ejh.70313
Primary Topic
Lymphoma Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00
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article

Translational Insights From the Molecular Landscape to Precision Therapy in Peripheral T‐Cell Lymphoma: Integrating Multi‐Omics and Artificial Intelligence

Qiuyu Zhang, Yanyan Liu, Wei Fang
European Journal Of Haematology
Lymphoma Diagnosis and Treatment
article

Translational Insights From the Molecular Landscape to Precision Therapy in Peripheral T‐Cell Lymphoma: Integrating Multi‐Omics and Artificial Intelligence

Qiuyu Zhang, Yanyan Liu, Wei Fang
article en

Abstract

Peripheral T-cell lymphoma (PTCL) is a heterogeneous group of aggressive malignancies with poor prognosis and limited response to standard chemotherapy. Although recent advances in molecular and biological characterization have refined PTCL classification, profound molecular heterogeneity continues to result in highly variable treatment outcomes. Emerging targeted and immunotherapeutic agents show activity in specific subtypes, yet responses remain difficult to predict amid their biological complexity. This review synthesizes current molecular insights, evaluates the limitations of existing therapies, and explores the potential of multi-omics profiling integrated with artificial intelligence (AI) to decode complex signatures for improved subtype classification, treatment response prediction, and survival prognostication. By addressing the "black-box" issue through explainable AI, this approach offers a promising framework to advance PTCL management from empirical treatment toward biomarker-driven precision therapy.

European Journal Of Haematology
Zhengzhou University (CN), Henan Cancer Hospital (CN)
No poverty
Openalex Percentile: Top 11%
Lymphoma Diagnosis and Treatment
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