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Record W3194849531 · doi:10.1158/1078-0432.ccr-21-0573

Genome-Wide miRNA Expression Profiling of Molecular Subgroups of Peripheral T-cell Lymphoma

2021· article· en· W3194849531 on OpenAlexaff
Waseem Lone, Alyssa Bouska, Sunandini Sharma, Catalina Amador, Saumyaranjan Mallick, Tyler A. Herek, Tayla B. Heavican, Jiayu Yu, Soon Thye Lim, Choon Kiat Ong, Graham W. Slack, Kerry J. Savage, Andreas Rosenwald, German Ott, James R. Cook, Andrew L. Feldman, Lisa M. Rimsza, Timothy W. McKeithan, Timothy C. Greiner, Dennis D. Weisenburger, Federica Melle, Giovanna Motta, Stefano Pileri, Julie M. Vose, Wing C. Chan, Javeed Iqbal

Bibliographic record

VenueClinical Cancer Research · 2021
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsBC Cancer Agency
FundersNational Cancer InstituteNational Institutes of Health
KeywordsBiologymicroRNAPI3K/AKT/mTOR pathwayWnt signaling pathwayCancer researchBCL6EpigeneticsGATA3Gene expression profilingLymphomaT cellProtein kinase BSignal transductionImmunologyB cellGene expressionTranscription factorGeneticsGene

Abstract

fetched live from OpenAlex

Abstract Purpose: Peripheral T-cell lymphoma (PTCL) is a heterogeneous group of non–Hodgkin lymphomas with aggressive clinical behavior. We performed comprehensive miRNA profiling in PTCLs and corresponding normal CD4+ Th1/2 and TFH-like polarized subsets to elucidate the role of miRNAs in T-cell lymphomagenesis. Experimental Design: We used nCounter (NanoString Inc) for miRNA profiling and validated using Taqman qRT-PCR (Applied Biosystems, Inc). Normal CD4+ T cells were polarized into effector Th subsets using signature cytokines, and miRNA significance was revealed using functional experiments. Results: Effector Th subsets showed distinct miRNA expression with corresponding transcription factor expression (e.g., BCL6/miR-19b, -106, -30d, -26b, in IL21-polarized; GATA3/miR-155, miR-337 in Th2-polarized; and TBX21/miR-181a, -331-3p in Th1-polarized cells). Integration of miRNA signatures suggested activation of TCR and PI3K signaling in IL21-polarized cells, ERK signaling in Th1-polarized cells, and AKT–mTOR signaling in Th2-polarized cells, validated at protein level. In neoplastic counterparts, distinctive miRNAs were identified and confirmed in an independent cohort. Integrative miRNA–mRNA analysis identified a decrease in target transcript abundance leading to deregulation of sphingolipid and Wnt signaling and epigenetic dysregulation in angioimmunoblastic T-cell lymphoma (AITL), while ERK, MAPK, and cell cycle were identified in PTCL subsets, and decreased target transcript abundance was validated in an independent cohort. Elevated expression of miRNAs (miR-126-3p, miR-145-5p) in AITL was associated with poor clinical outcome. In silico and experimental validation suggest two targets (miR-126→ SIPR2 and miR-145 → ROCK1) resulting in reduced RhoA-GTPase activity and T–B-cell interaction. Conclusions: Unique miRNAs and deregulated oncogenic pathways are associated with PTCL subtypes. Upregulated miRNA-126-3p and miR-145-5p expression regulate RhoA-GTPase and inhibit T-cell migration, crucial for AITL pathobiology.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.115
GPT teacher head0.454
Teacher spread0.339 · 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

Citations28
Published2021
Admission routes1
Has abstractyes

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