期刊
BLOOD ADVANCES
卷 5, 期 24, 页码 5588-5598出版社
ELSEVIER
DOI: 10.1182/bloodadvances.2021005171
关键词
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类别
资金
- Instituto de Salud Carlos III [CP16/00116, CA18/00017]
- Ministerio de Economia, Industria y Competitividad
- Asociacion Espanola Contra el Cancer (AECC) [PROYE18054PIRI]
- Comunidad Autonoma de Madrid
- Centre for Biomedical Network Research on Cancer (CIBERONC) [SAF2013-47416-R]
- CIBERONC-ISCIII [CB16/12/00291]
- ISCIII-MINECO-AES-FEDER (Plan Estatal I + D + I 2013-2016)
- CAM [B2017/BMD-3778, PIC97/2017_FJD, PIE15/0081, PIE16/01294, PI19/00715]
- PFIS predoctoral fellowship
- Marie Sklodowska-Curie Individual Fellowship [882597]
- CIBERONC [CB16/12/00291]
- Marie Curie Actions (MSCA) [882597] Funding Source: Marie Curie Actions (MSCA)
This study analyzed cases of Peripheral T-cell lymphoma (PTCL) to identify specific gene sets associated with different histological types, supporting the division of PTCL into 3 categories and identifying B-cell gene expression as an independent prognostic factor for AITL. The study also highlighted the importance of mutational profiles, with differences in RHOA mutations among the PTCL classes.
Peripheral T-cell lymphoma (PTCL) is a clinically aggressive disease, with a poor response to therapy and a low overall survival rate of approximately 30% after 5 years. We have analyzed a series of 105 cases with a diagnosis of PTCL using a customized NanoString platform (NanoString Technologies, Seattle, WA) that includes 208 genes associated with T-cell differentiation, oncogenes and tumor suppressor genes, deregulated pathways, and stromal cell subpopulations. A comparative analysis of the various histological types of PTCL (angioimmunoblastic T-cell lymphoma [AITL]; PTCL with T follicular helper [TFH] phenotype; PTCL not otherwise specified [NOS]) showed that specific sets of genes were associated with each of the diagnoses. These included TFH markers, cytotoxic markers, and genes whose expression was a surrogate for specific cellular subpopulations, including follicular dendritic cells, mast cells, and genes belonging to precise survival (NF-kappa B) and other pathways. Furthermore, the mutational profile was analyzed using a custom panel that targeted 62 genes in 76 cases distributed in AITL, PTCL-TFH, and PTCL-NOS. The main differences among the 3 nodal PTCL classes involved the RHOA(G)(17V) mutations (P < .0001), which were approximately twice as frequent in AITL (34.09%) as in PTCLTFH (16.66%) cases but were not detected in PTCL-NOS. A multivariate analysis identified gene sets that allowed the series of cases to be stratified into different risk groups. This study supports and validates the current division of PTCL into these 3 categories, identifies sets of markers that can be used for a more precise diagnosis, and recognizes the expression of B-cell genes as an IPI-independent prognostic factor for AITL.
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