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Record W2987982078 · doi:10.1007/s00403-019-02000-0

Molecular profiling of TOX-deficient neoplastic cells in cutaneous T cell lymphoma

2019· article· en· W2987982078 on OpenAlexfundno aff
Jingkai Xu, He Huang, Shangshang Wang, Yanzhen Chen, Xueli Yin, Xuejun Zhang, Yaohua Zhang

Bibliographic record

VenueArchives of Dermatological Research · 2019
Typearticle
Languageen
FieldMedicine
TopicCutaneous lymphoproliferative disorders research
Canadian institutionsnot available
FundersYoung Scientists FundInstitute of Genetics and Developmental Biology, Chinese Academy of SciencesChinese Academy of SciencesInstitute of GeneticsNational Natural Science Foundation of ChinaNatural Science Foundation of Shanghai
KeywordsGene knockdownBiologyCutaneous T-cell lymphomaCancer researchMycosis fungoidesLymphomaTranscriptomeDownregulation and upregulationGene expression profilingWnt signaling pathwaySmall hairpin RNARNA interferenceGeneGene expressionImmunologyRNAGenetics

Abstract

fetched live from OpenAlex

Cutaneous T cell lymphoma (CTCL) is a rare but potentially devastating primary cutaneous lymphoma. CTCL is characterized by localization of neoplastic T lymphocytes to the skin, with mycosis fungoides (MF) and its leukemic form, Sézary syndrome (SS) being the most common variants. Thymocyte selection-associated high-mobility group box (TOX) gene has been found to be highly expressed in MF and SS. It is reported that higher expression levels of TOX in patients will increase risks of disease progression and poor prognosis. However, the molecular events leading to these abnormalities have not been well understood. To better understand the molecular mechanism underlying TOX-mediated differentially expressed genes (DEGs) in CTCL, and to identify DEGs pathways triggered after knockdown of TOX gene in the CTCL cell line Hut78, we employed two shRNA-mediated lentiviruses to knock down TOX gene in the skin lymphoma cell line HuT78. RNA sequencing (RNAseq) analysis was applied to analyze DEGs, DEGs GO and their corresponding pathways. Knockdown of TOX can induce upregulation of 547 genes and downregulation of 649 genes, respectively. HOXC9 was the most significant downregulated gene. Most DEGs are enriched in malignancies and relate to the Wnt and mTOR signaling pathways, and therefore they can regulate cellular processes and induce different biological regulation. Transcriptome analysis of DEGs after knockdown of TOX in our study provides insights into the mechanism of TOX in CTCL and suggests candidate targets for therapy of CTCL.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score0.707

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.026
GPT teacher head0.329
Teacher spread0.303 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations7
Published2019
Admission routes1
Has abstractyes

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