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Record W2564661908 · doi:10.1182/blood.v126.23.111.111

Genetic Alterations of Gα13 Signaling Pathway with BCL2 over-Expression Confers Lymphoma Dissemination and Inferior Outcome in Germinal Center B Cell Diffuse Large B Cell Lymphoma

2015· article· en· W2564661908 on OpenAlexaff
Daisuke Ennishi, Anja Mottok, Hennady P. Shulha, Pedro Farinha, Fong Chun Chan, Barbara Meissner, Merrill Boyle, Susana Ben‐Neriah, Christoffer Hother, Robert Kridel, Ryan D. Morin, Marco A. Marra, Kerry J. Savage, Laurie H. Sehn, Joseph M. Connors, Christian Steidl, David W. Scott, Randy D. Gascoyne

Bibliographic record

VenueBlood · 2015
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsCanada's Michael Smith Genome Sciences CentreSimon Fraser UniversityBC Cancer Agency
Fundersnot available
KeywordsDiffuse large B-cell lymphomaGerminal centerBiologyBCL6Cancer researchFollicular lymphomaGene expression profilingLymphomaGeneticsB cellGeneImmunologyGene expression

Abstract

fetched live from OpenAlex

Abstract Background: Diffuse large B cell lymphoma (DLBCL) is divided into two distinct molecular subtypes, germinal center B cell (GCB) subtype and activated B cell (ABC) subtype. Genetic landscape studies of DLBCL have revealed several GCB-DLBCL specific mutations, including CREBBP, GNA13, EZH2, TNFRSF14, BCL2 and MEF2B. Functional studies have recently shown that the inactivation of Gα13 signaling pathway genes, including GNA13, together with BCL2 over-expression, allows GC B-cells to escape the germinal center niche and widely disseminate. Although these findings revealed a critical role of genetic alterations of Gα13 signaling pathway in GC-driven mouse models of lymphomagenesis, clinical correlation is lacking. Here we analyzed the clinical impact of genetic alterations of Gα13 signaling pathway in a large population-based DLBCL cohort. Methods: We analyzed 347 newly diagnosed de novo DLBCL cases that were uniformly treated with R-CHOP at the BC Cancer Agency. Comprehensive clinical annotation was available through the BCCA Lymphoid Cancer Database. Deep targeted re-sequencing of the coding exons of GNA13, P2RY8, ARHGEF1, S1PR2 and RHOA was performed using a Truseq Custom Amplicon assay (Illumina) and/or Fluidigm Access Array chips. High-resolution copy number analyses were performed using Affymetrix SNP 6.0 arrays. Immunohistochemical staining and break-apart FISH assays for MYC and BCL2 were performed on tissue microarrays (n=332). Cell-of-origin classification was available in 331 cases, according to gene expression profiling by the Lymph2Cx assay using the NanoString platform (Scott, Blood 2014; 123) in 299 patients and the Hans algorithm (Hans, Blood 2004; 103) in 32 cases with low tumor content (<40%). Results: Using next generation sequencing, 225 SNVs and 5 Indels were detected in GNA13 (16%), P2RY8 (18%), ARHGEF1 (6%), S1PR2 (3%) and RHOA (6%). SNP 6.0 microarrays revealed heterozygous deletions in GNA13 (2%), ARHGEF1 (1%), S1PR2 (4%) and RHOA (8%), but homozygous deletion was not found in any of these five loci. GNA13, P2RY8 and ARHGEF1 mutations were significantly more frequent in the GCB subtype than ABC subtype (26% vs. 6%; p<.0001, 25% vs 7%; p=.0002, and 8% vs. 5%; p=.008, respectively). 185 GCB-DLBCL cases were further analyzed for clinical correlations. In the cases with mutations of any of the five Gα13 signaling pathway genes, BCL2 over-expression (cut off; 50%) and translocation was associated with increasing stage (p=.018 and p=.005, respectively), but not in wt cases (p=.53 and p=.63, respectively). Specifically, in the cases with GNA13 and P2RY8 mutations individually, BCL2 over-expression was associated with advanced stage (stage III/IV, p=.018 and p=.037, respectively), but not in wild type (wt) cases. Importantly, BCL2 over-expression in the cases harboring Gα13 pathway mutations was not significantly associated with other poor risk features, including any other IPI factors or bone marrow involvement, indicating that genetic alterations in Gα13 signaling pathway accompanied by BCL2 over-expression might promote lymphoma dissemination into lymph nodes but not extranodal sites. With a median follow up of 6.5 years for living patients, there was no prognostic impact of harboring any isolated Gα13 pathway mutation in GCB-DLBCL patients. However, in cases with any Gα13 pathway mutations, BCL2 over-expression was significantly associated with an inferior 5y-time to progression (TTP; 90% vs 62%, p=.003) and disease-specific survival (DSS; 90% vs 71%, p=.042), but not in wt cases (Fig 1). In a Cox model of TTP including the IPI, BCL2 over-expression remained prognostic in the cases harboring any Gα13 pathway mutations (HR=4.13 [1.42-12.01], p=.009), but not in wt cases (HR=1.70 [0.62-4.68], p=.31). In cases with any Gα13 pathway alterations including copy number loss, BCL2 over-expression was also significantly associated with an inferior TTP (HR=3.64 [1.39-9.57], p=.009) independent of IPI, but not in the cases without genetic alterations (HR=1.75 [0.57-5.34], p=.33). Conclusions: Genetic alterations in Gα13 signaling pathway genes cooperate with BCL2 over-expression to promotes lymphoma dissemination to nodal sites and is associated with the poor outcome in GCB-DLBCL Figure 1. TTP and DSS according to BCL2 over-expression with/without Gα13 signaling pathway mutations in GCB-DLBCL patients (n=185) treated with R-CHOP Figure 1. TTP and DSS according to BCL2 over-expression with/without Gα13 signaling pathway mutations in GCB-DLBCL patients (n=185) treated with R-CHOP Disclosures Savage: Seattle Genetics: Honoraria, Speakers Bureau; BMS: Honoraria; Infinity: Honoraria; Roche: Other: Institutional research funding. Connors:Roche: Research Funding; Seattle Genetics: Research Funding. Scott:Celgene: Consultancy, Honoraria; NanoString: Patents & Royalties: Inventor on a patent that NanoString has licensed.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.013
GPT teacher head0.255
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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