Mutations of STAT6 DNA Binding Domain Are Characteristic of PMBL and Belong to the Genetic Signature of This Entity.
Bibliographic record
Abstract
Abstract Abstract 2645 Primary mediastinal B-cell lymphoma (PMBL) is a separate entity of aggressive B-cell lymphoma and accounts for about 5% of aggressive lymphomas according to the World Health Organization (WHO) classification. This lymphoma affects young patients and presents as a anterior mediastinal mass consisting of large B-cells that usually express little if any surface or cytoplasmic immunoglobulin and major histocompatibility complex class I and/or class II molecules. PMBL display constitutive activation of janus kinase-signal transducer and activator of transcription (JAK-STAT) signaling pathway, also observed in Hodgkin lymphoma and is characterized by heterozygous missense mutations of STAT6 DNA binding domain that are not observed in diffuse large B-cell lymphoma. To determine whether these mutations could represent a diagnostic or prognostic marker useful in the clinic, we developed a PCR HRM (High Resolution Melting) assay to screen for mutations in STAT6 exon 12, which had been previously identified as a hotspot mutation. We analyzed a series of 80 patients with a mediastinal biopsy and/or histological review of PMBL, enrolled in clinical trials of the GELA (LNH-03) or the GOELAMS (075). DNAs were extracted from FFPE (formalin-fixed and paraffin-embedded) samples with QIAmp DNA mini kit (QIAGEN®) for GELA samples and fully automated Siemens Healthcare Diagnostics proprietary experimental method based on magnetic beads for GOELAMS samples. Sixteen DNAs were not analyzed due to poor amplification in PCR and four DNAs were not analyzed due to other reasons (refused protocol, inclusion at relapse, not included in the tissue microarray/TMA). All cases with abnormal denaturation curves were analyzed by Sanger sequencing. Of the remaining 60 DNA samples, we detected 20 mutated tumors in exon 12 (30%). These mutations were heterozygous single nucleotide variants, often multiple (10 cases, 8 double hit mutations and 2 triple hit mutations) and targeted mostly amino acids 417 (9 hits) and 419 (7 hits). Immunohistochemical analysis of TMA showed that the mutated tumors expressed CD23 (14/20) and MAL proteins (13/15), more frequently than non-mutated ones (10/33, p= 0.009 and 15/27, p=0.049, respectively). Interestingly, these proteins are encoded by genes belonging to the transcriptional signature of PMBL as defined by gene expression profiling in previous studies, There were no significant difference in the clinical presentation between patients with a STAT6 mutation and non-mutated cases regarding age, sex, performance status, Ann Arbor stage, LDH, IPI, treatment response, progression free survival and overall survival. However we noted an absence of elevated β2-microglobulin (1 case elevated/18) and an absence of albumin < 35 g/dl (0 case/8) in the mutated tumors compared with non-mutated tumors (11/31, p= 0.003 and 9/21, p< 0.05, respectively). Finally, we analyzed the correlations of these mutations with cytogenetic abnormalities including CIITA (Class II Transactivator) rearrangement, PD-L1/2 (Programmed death ligand) rearrangement and PD-L1/2 copy number alterations. Indeed, CIITA rearrangements have been described in 38% of PMBL and PD-L1/2 amplification were reported in 63% of PMBL. In this series of patients, CIITA rearrangements were present in 15/49 (31%) and PD-L1/2 low (3–4 copies) and high (>4 copies) level amplification observed in 33/52 (63%) of cases. It is interesting to note that STAT6-mutated cases frequently harbor CIITA rearrangement compared to STAT6-non-mutated cases (9/18 vs 6/31, p= 0.05) as well as PD-L1/2 low level copy number gains (12/19 vs 10/32, p= 0.02), suggesting that the combination of specific genomic alterations cooperate during PMBL oncogenesis. In conclusion, the frequency of this mutation suggests an in vivo selection during PMBL lymphomagenesis. The correlations with the clinico-biological data suggest that STAT6 mutations may be searched for in routine FFPE samples and may help to establish a molecular definition of PMBL that is characterized by alterations of the JAK-STAT pathway. Further investigations are required to identify the mutational mechanisms involved and the oncogenic function associated with these mutations. Disclosures: No relevant conflicts of interest to declare.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".