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Record W2983422204 · doi:10.1101/829671

Independent evolution of cutaneous lymphoma subclones in different microenvironments of the skin

2019· preprint· en· W2983422204 on OpenAlexafffund
Aishwarya Iyer, Dylan Hennessey, Sandra O’Keefe, Jordan Patterson, Weiwei Wang, Gane Ka‐Shu Wong, Robert Gniadecki

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldMedicine
TopicCutaneous lymphoproliferative disorders research
Canadian institutionsUniversity of Alberta
FundersBispebjerg HospitalUniversity of AlbertaCanadian Dermatology Foundation
KeywordsDermisMycosis fungoidesEpidermis (zoology)BiologyCutaneous T-cell lymphomaCutaneous lymphomaLymphomaPathologyInfiltration (HVAC)Cancer researchCell of originCancerMedicineImmunologyGeneticsAnatomy

Abstract

fetched live from OpenAlex

Abstract Mycosis fungoides (MF) is the most common, yet incurable, cutaneous T-cell lymphoma. We have recently shown that the disease is initiated by hematogenous seeding the skin with clonotypically diverse neoplastic T-cells which proliferate accumulating numerous mutations and produce lesions of high intratumoral heterogeneity (ITH). A characteristic but a poorly studied feature of MF is epidermotropism, the tendency to infiltrate skin epithelial layer (epidermis) in addition to the vascularized dermis. By sequencing the exomes of the microdissected clusters of lymphoma cells from the epidermis and the dermis, we found that those microenvironments harbored different malignant clonotypes and exhibited different patterns of driver gene mutation. Phylogenetic relationships between cancer subclones witnessed to the independent mutational evolution in the epidermis and dermis. Thus, the invasion of MF to different skin layers does not occur by gradual infiltration of the expanding tumor mass, but is caused by separate seeding processes with different malignant clones that develop independently of one another via a neutral, branched evolution. In conclusion, tissue microenvironments shape the subclonal architecture in MF leading to “ecological heterogeneity” which contributes to the total ITH. Since ITH adversely affects cancer prognosis, targeting the microenvironment may present therapeutic opportunities in MF and other cancers.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.010
GPT teacher head0.227
Teacher spread0.218 · 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.

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

Citations1
Published2019
Admission routes2
Has abstractyes

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