ReviewHistopathology2025
Advances in peripheral T cell lymphomas: pathogenesis, genetic landscapes and emerging therapeutic targets.
Review in Histopathology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- The Role of AP-1 in Cancer: Regulation, Tumor Microenvironment and Therapeutic Targeting.Biomolecules · 2026Review
- Functional genomics and proteomics identify Folate Carrier SLC19A1 as a predictor of pralatrexate sensitivity in diverse T-cell lymphoma models.Molecular cancer therapeutics · 2026Article
- Precision Medicine in Non-Hodgkin Lymphoma: Advances in BTK Inhibition, CD30-Directed Antibody-Drug Conjugates, and HDAC-Mediated Epigenetic Therapy with Pirtobrutinib, Brentuximab Vedotin, and Belinostat.Journal of clinical medicine · 2026Review
- The Diagnostic Evolution of Haematological Neoplasms: A Narrative Review of the Road to Two Genetically Focused Classification Systems Through a Resource-Limited Perspective.Diagnostics (Basel, Switzerland) · 2026Review
- Automated Classification of Lymphoma Subtypes From Histopathological Images Using a U-Net Deep Learning Model: Comparative Evaluation Study.JMIR medical informatics · 2026Article
- Risk and Survival Outcomes of Secondary Primary Malignancies in Chinese Lymphoma Patients in the Era of Modern Targeted Therapies: A Single-Center Retrospective Cohort Study.Blood and lymphatic cancer : targets and therapy · 2026Article
- ALK-negative anaplastic large cell lymphoma in pediatric and adolescent patients: a mini-review.Frontiers in oncology · 2026Review
- Integrating functional genomics and proteomics identifies Folate Carrier SLC19A1 as a predictor of pralatrexate sensitivity in T-cell lymphoma.bioRxiv : the preprint server for biology · 2025Article
- Real-world outcomes of T cell lymphoma in a tertiary cancer center in Saudi Arabia.Annals of Saudi medicineArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Peripheral T cell lymphomas (PTCLs) are a biologically diverse and aggressive group of non-Hodgkin lymphomas that originate from mature T cells, often presenting with complex clinical and morphological features. This review explores the challenges in diagnosing and classifying PTCLs, focusing on the intricate biology of the more common nodal entities. Advances in molecular diagnostics, such as mutational and gene expression profiling, have improved our understanding. However, the rarity and morphological variability of PTCLs continue to complicate the definition of biologically and clinically meaningful entities, as well as the application of current diagnoses in daily practice; these advancements have not yet translated into improved clinical outcomes. Standard therapies fail in most cases and lead to poor prognoses, highlighting the urgent need for improved therapeutic strategies. Precise characterisation of PTCL advances refined classification and supports the development of more targeted and effective treatments. Recent approaches have focused on biology-based risk stratification, either within specific entities or in an entity-agnostic manner. This development aims for improved treatment selection or even personalised treatment based on genetic, epigenetic and functional profiles.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.