ALDH1A3-regulated long non-coding RNA NRAD1 is a potential novel target for triple-negative breast tumors and cancer stem cells
Why this work is in the frame
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Bibliographic record
Abstract
To discover novel therapeutic targets for triple-negative breast cancer (TNBC) and cancer stem cells (CSCs), we screened long non-coding RNAs (lncRNAs) most enriched in TNBCs for high expression in CSCs defined by high Aldefluor activity and associated with worse patient outcomes. This led to the identification of non-coding RNA in the aldehyde dehydrogenase 1 A pathway (NRAD1), also known as LINC00284. Targeting NRAD1 in TNBC tumors using antisense oligonucleotides reduced cell survival, tumor growth, and the number of cells with CSC characteristics. Expression of NRAD1 is regulated by an enzyme that causes Aldefluor activity in CSCs, aldehyde dehydrogenase 1A3 (ALDH1A3) and its product retinoic acid. Cellular fractionation revealed that NRAD1 is primarily nuclear localized, which suggested a potential function in gene regulation. This was confirmed by transcriptome profiling and chromatin isolation by RNA purification, followed by sequencing (ChIRP-seq), which demonstrated that NRAD1 has enriched chromatin interactions among the genes it regulates. Gene Ontology enrichment analysis revealed that NRAD1 regulates expression of genes involved in differentiation and catabolic processes. NRAD1 also contributes to gene expression changes induced by ALDH1A3; thereby, the induction of NRAD1 is a novel mechanism through which ALDH1A3 regulates gene expression. Together, these data identify lncRNA NRAD1 as a downstream effector of ALDH1A3, and a target for TNBCs and CSCs, with functions in cell survival and regulation of gene expression.
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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