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Record W2549638472 · doi:10.1182/blood.v114.22.624.624

MicroRNA Are Useful Biomarkers for Prediction of Response to Therapy and Survival of Patients with Diffuse Large B-Cell Lymphoma.

2009· article· en· W2549638472 on OpenAlexaff
Alvaro J. Alencar, Raquel Malumbres, Ranjana H. Advani, Neha Talreja, Ragini Shyam, Javier Briones, Yasodha Natkunam, Randy D. Gascoyne, Robert Tibshirani, Izidore S. Lossos

Bibliographic record

VenueBlood · 2009
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsDiffuse large B-cell lymphomamicroRNALymphomaAnthracyclineCancer researchBCL6Gene expression profilingBiologyCarcinogenesisOncologyGene expressionGeneMedicineInternal medicineCancerImmunologyB cellAntibodyBreast cancerGeneticsGerminal center

Abstract

fetched live from OpenAlex

Abstract Abstract 624 Background: Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease with a variable clinical outcome even in the current era of rituximab containing anthracycline-based chemotherapy (RCHOP). We have previously reported a 6 gene model which is predictive for outcome in DLBCL (Lossos et al NEJM 2004, 350:1829 and Malumbres et al Blood 2008, 111:5509). Recently, short non-protein coding microRNAs (miRNA) that regulate gene expression by targeting the 3'UTR region of mRNA have been identified and are postulated to play an important role in oncogenesis. We have previously demonstrated that miRNAs exhibit specific expressions at different lymphocyte differentiation stages as well as distinct expression in gene expression-defined DLBCL subtypes (Malumbres et al Blood 2009; 113:3754). Herein, we evaluated whether specific miRNAs differentially expressed across DLBCL cell lines were prognostic biomarkers for prediction of outcome of DLBCL patients (pts). Patients and Methods: RNA was extracted from paraffin-embedded archived specimens (Chen et al Diagn Mol Pathol 2007, 16:61), from pts with newly diagnosed de novo DLBCL treated with R-CHOP at 4 different institutions. Expression of 11 miRNAs, including miR-146a, miR-146b-5p, miR-222, miR-500, miR-574-3p, miR-363, miR-155, and miR-21 that are differentially expressed between the ABC and GCB DLBCL subtypes, as well as expression of miR-18a, miR-140-3p, and miR-181a which has been reported to be variably expressed across DLBCL tumors were analyzed by ABI real-time PCR assays. Expression of the genes comprising the 6 gene survival prediction model were measured as reported previously. Expression was correlated to progression-free survival (PFS) and overall survival (OS). Predictive value of miRNAs was evaluated both as a continuous variable as well as a in a dichotomous model with pts grouped based on miRNA median expression. Results: The study group consisted of 176 pts with a median age 59 years (y) (range 16-92) of which 84 pts (48%) were > 60 y. 54 pts (30%) had an ECOG PS ≥2 and 86 (49%) presented with stage III or IV. Distribution according to the IPI was: 0-1 factor (n=77); 2 factors (n=50); 3 factors (n=30); and ≥4 factors (n=19). There were 41 deaths during a median follow-up of 2.6 years (range 0.04-8.1y). OS correlated with expression of miR-18a as a continuous variable, with higher expression correlating with inferior OS (p=0.038) but was not independent of the IPI in a multivariate model. PFS correlated with expression of miR-181a as a continuous variable (p=0.026; higher expression associated with longer PFS) and with expression of miR-222 as a categorical variable (miR-222cat; p=0.004, lower expression associated with longer PFS). In a multivariable model including IPI, both miR-222cat and miR-181a were IPI independent (p=0.01 and p=0.003, respectively). The mortality-prediction score calculated from the 6-gene model predicted both the OS (p=0.007) and PFS (p=0.004) and was IPI-independent. A multivariate Cox regression analysis that included IPI scores, mortality predictor scores and expression of miR-18a, miR-181a and miR-222cat revealed that all factors except miR-222cat were independent predictors of OS and all factors except miR-18a were independent predictors of PFS. Conclusions: We confirm that in RCHOP treated pts with DLBCL the 6-gene model predicts both OS and PFS independent of the IPI. Expression of miRNAs miR-18a, miR-181a and miR-222 is associated with response to therapy and outcome of pts with DLBCL, independent of the IPI and the mortality-prediction score calculated from the 6-gene model. While the expression of miR-181a and miR-222 may reflect the cell of origin of DLBCL tumors, the expression of miR-18a does not. Further studies are warranted to evaluate the precise role of these miRNAs in B-cell biology and DLBCL pathogenesis and prognosis. Disclosures: Advani: Seattle Genetics, Inc.: Research Funding.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.001
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.012
GPT teacher head0.225
Teacher spread0.213 · 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".

Quick stats

Citations3
Published2009
Admission routes1
Has abstractyes

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