The Genetic Basis of Hepatosplenic 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 Hepatosplenic T-cell lymphoma (HSTL) is a rare and lethal lymphoma; the genetic drivers of this disease are unknown. Through whole-exome sequencing of 68 HSTLs, we define recurrently mutated driver genes and copy-number alterations in the disease. Chromatin-modifying genes, including SETD2, INO80, and ARID1B, were commonly mutated in HSTL, affecting 62% of cases. HSTLs manifest frequent mutations in STAT5B (31%), STAT3 (9%), and PIK3CD (9%), for which there currently exist potential targeted therapies. In addition, we noted less frequent events in EZH2, KRAS, and TP53. SETD2 was the most frequently silenced gene in HSTL. We experimentally demonstrated that SETD2 acts as a tumor suppressor gene. In addition, we found that mutations in STAT5B and PIK3CD activate critical signaling pathways important to cell survival in HSTL. Our work thus defines the genetic landscape of HSTL and implicates gene mutations linked to HSTL pathogenesis and potential treatment targets. Significance: We report the first systematic application of whole-exome sequencing to define the genetic basis of HSTL, a rare but lethal disease. Our work defines SETD2 as a tumor suppressor gene in HSTL and implicates genes including INO80 and PIK3CD in the disease. Cancer Discov; 7(4); 369–79. ©2017 AACR. See related commentary by Yoshida and Weinstock, p. 352. This article is highlighted in the In This Issue feature, p. 339
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.
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 | 0.001 | 0.001 |
| 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