Abstract B32: A specialized post-transcriptional program in chemoresistant, quiescent cancer cells
Bibliographic record
Abstract
Abstract Quiescent (G0) cells are a clinically relevant fraction in cancers, which include dormant cancer stem cells, and resist clinical therapy. G0 cells reveal extensive changes in gene expression at the protein and translation levels. We previously identified that the translation mechanism is altered in G0 cancer cells. MicroRNAs, noncoding RNAs that target distinct mRNAs to alter gene expression, were found to associate with a key RNA-binding protein and enable specialized functions in G0, where they recruit noncanonical translation factors to regulate specific mRNA translation. We find that G0 leukemic cells show similar proteome and translatome to cells isolated post-chemotherapy. These data suggest that specialized post-transcriptional mechanisms in G0 leukemic cells regulate a distinct translatome to mediate chemoresistance. To understand the role of post-transcriptional regulation in chemoresistance, we compared global transcriptome, translatome and proteome profiling in chemoresistant G0 acute monocytic leukemic (AML) cells. We find that chemotherapy or G0 induction leads to DNA damage responsive ATM and stress signaling, which alter post-transcriptional and translational mechanisms. ATM and stress-activated p38 MAPK/MK2 increase AU-rich-element (ARE) bearing proinflammatory cytokine and immune gene mRNAs, by regulating a key ARE RNA binding protein and modifying canonical translation. AREs are present on 3'UTRs of tightly regulated oncogenes and cytokines, to post-transcriptionally control their expression. Both rate-limiting steps—mRNA cap recognition and tRNA recruitment—in canonical translation are altered. These signaling pathways lead to low mTOR activity in G0, which activates the cap complex inhibitor, eIF4EBP to impair canonical translation, leading to noncanonical translation of specific mRNAs with specialized cap binding and ribosome recruitment factors. In addition, stress and STAT1/interferon signaling are activated to reduce the canonical tRNA recruitment mechanism, enabling noncanonical translation of specific mRNAs. These changes permit translation of ARE bearing proinflammatory cytokine TNFa, and immune and cell-migration modulators that promote survival. Co-inhibiting p38 MAPK and TNFa that promote antiapoptosis—prior to or along with chemotherapy—decreases chemoresistance in AML cells, in vivo, and in patient samples without affecting normal cells. Our studies reveal a proinflammatory subpopulation in AML that mediates resistance, enabled by DNA damage- and stress-regulated post-transcriptional and translational mechanisms that are mediated by AU-rich-elements and a critical ARE RNA binding protein. Disrupting ARE regulation reduces TNFα and chemoresistance, revealing AREs, an important ARE RNA binding protein and noncanonical translation as regulators of chemoresistance. These studies reveal the significance of post-transcriptional regulation of proinflammatory and immune gene-mediated chemoresistance. Citation Format: Sooncheol Lee, Syed I.A. Bukhari, Samuel S. Truesdell, Swapna Kollu, Richard D. Mortensen, Myriam Boukhali, Esha Jain, Dongjun Lee, Maria Mazzola, Radhika Raheja, Adam Langenbucher, Nicholas Haradhwala, Akiko Yanagiya, Michael Lawrence, Roopali Gandhi, Ruslan Sadreyev, David Sweetser, Wilhelm Haas, Shobha Vasudevan. A specialized post-transcriptional program in chemoresistant, quiescent cancer cells [abstract]. In: Proceedings of the AACR Special Conference on Targeting PI3K/mTOR Signaling; 2018 Nov 30-Dec 8; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Res 2020;18(10_Suppl):Abstract nr B32.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".