P178 | ARGININE DEPRIVATION INDUCES CANCER DORMANCY AND GENOMIC INSTABILITY: THE SEED AND SOIL OF MULTIPLE MYELOMA RECURRENCE
Bibliographic record
Abstract
We combined multi-omics approaches to investigate the adaptive response to acute and chronic arginine deprivation, in two human myeloma cell lines (U266 and NCI-H929). We failed to identify a common trigger for the activation of integrated stress response, due to a variable expression of BIP, PERK, IRE-1α and downstream factors ATF4 and HO-1 in all tested lines, in lack of significant autophagy activation. However, the sequential treatment of arginine deprivation for 48 hours followed by 12 hours exposure to the integrated stress response inhibitor ISRIB, an experimental drug that reverses the effects of eIF2α phosphorylation, induced a significant suppression of ATF4, ATF5, CHOP and GADD34 transcripts, suggesting the occurrence of a transcriptional response despite the upstream lack of EIF2α activation. Ribosome profiling unveiled a reduced translation efficiency for tumor suppressors ADCK2, AGGF1, AP5M1, MESDC1, SCRIB, the chromatin modifying enzyme MSL2, and the transcription factors E2F1 among others. We observed a significant increase in the number of cells exhibiting DNA damage markers (ATM+/γH2AX+), along with an increased percentage of micronuclei, coupled with the increased expression of the suppressive histone marks H3K9me3 and H3K27me3, elevated levels of macroH2AX protein, and a higher percentage of heterochromatin. Finally, we explored the clinical relevance of in vitro observations described above in 768 RNA-Seq samples obtained from NDMM patients enrolled in the MMRF CoMMpass study. We identified identify 5 PRGs among 888 DEGs shared by U266 and NCI-H929 in response to arginine deprivation associated to inferior overall survival: TUBB (HR=13.12, p<0.0001), CEP55 (HR=18.72, p<0.0001), CENPF (HR=20.19, p<0.0001), SPAG5 (HR=20.44, p<0.0001) and FAM83D (HR=29.13, p<0.0001). STRING analysis showed that CEP55, CENPF, SPAG5 and FAM83D were part of the kinetochore assembly network. Among 773 patients carrying at least one mutation in the MMRF CoMMpass dataset, increased expression of CEP55 was associated with an increased mutation load in p53 (2.1 vs 18.3%, p<0.001) The reduced metabolic activity, changes in cell cycle, and regulation of genes involved in chromatin organization suggest that arginine deprivation could induce a shift towards a dormant phenotype, potentially contributing to disease recurrence in myeloma patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".