Targeting of inflammatory pathways with R2CHOP in high-risk DLBCL.
Keenan T HartertKerstin WenzlJordan E KrullMichelle ManskeVivekananda SarangiYan AsmannMelissa C LarsonMatthew John MaurerSusan SlagerWilliam R MaconRebecca L KingAndrew L FeldmanAnita K GandhiBrian K LinkThomas M HabermannZhi-Zhang YangStephen M AnsellJames R CerhanThomas E WitzigGrzegorz S NowakowskiAnne J NovakPublished in: Leukemia (2020)
Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoma, and front line therapies have not improved overall outcomes since the advent of immunochemotherapy. By pairing DNA and gene expression data with clinical response data, we identified a high-risk subset of non-GCB DLBCL patients characterized by genomic alterations and expression signatures capable of sustaining an inflammatory environment. These mutational alterations (PIM1, SPEN, and MYD88 [L265P]) and expression signatures (NF-κB, IRF4, and JAK-STAT engagement) were associated with proliferative signaling, and were found to be enriched in patients treated with RCHOP that experienced unfavorable outcomes. However, patients with these high-risk mutations had more favorable outcomes when the immunomodulatory agent lenalidomide was added to RCHOP (R2CHOP). We are the first to report the genomic validation of a high-risk phenotype with a preferential response towards R2CHOP therapy in non-GCB DLBCL patients. These conclusions could be translated to a clinical setting to identify the ~38% of non-GCB patients that could be considered high-risk, and would benefit from alternative therapies to standard RCHOP based on personalized genomic data.
Keyphrases
- diffuse large b cell lymphoma
- end stage renal disease
- epstein barr virus
- gene expression
- newly diagnosed
- ejection fraction
- chronic kidney disease
- peritoneal dialysis
- electronic health record
- poor prognosis
- stem cells
- copy number
- immune response
- signaling pathway
- dendritic cells
- machine learning
- metabolic syndrome
- skeletal muscle
- high dose
- weight loss
- toll like receptor
- drug delivery
- nuclear factor
- pi k akt