Genomic and Single-Cell Landscape Reveals Novel Drivers and Therapeutic Vulnerabilities of Transformed Cutaneous T-cell Lymphoma
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT: Cutaneous T-cell lymphoma (CTCL) is a rare cancer of skin-homing T cells. A subgroup of patients develops large cell transformation with rapid progression to an aggressive lymphoma. Here, we investigated the transformed CTCL (tCTCL) tumor ecosystem using integrative multiomics spanning whole-exome sequencing (WES), single-cell RNA sequencing, and immune profiling in a unique cohort of 56 patients. WES of 70 skin biopsies showed high tumor mutation burden, UV signatures that are prognostic for survival, exome-based driver events, and most recurrently mutated pathways in tCTCL. Single-cell profiling of 16 tCTCL skin biopsies identified a core oncogenic program with metabolic reprogramming toward oxidative phosphorylation (OXPHOS), cellular plasticity, upregulation of MYC and E2F activities, and downregulation of MHC I suggestive of immune escape. Pharmacologic perturbation using OXPHOS and MYC inhibitors demonstrated potent antitumor activities, whereas immune profiling provided in situ evidence of intercellular communications between malignant T cells expressing macrophage migration inhibitory factor and macrophages and B cells expressing CD74. SIGNIFICANCE: Our study contributes a key resource to the community with the largest collection of tCTCL biopsies that are difficult to obtain. The multiomics data herein provide the first comprehensive compendium of genomic alterations in tCTCL and identify potential prognostic signatures and novel therapeutic targets for an incurable T-cell lymphoma. This article is highlighted in the In This Issue feature, p. 1171.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it