A Human Genome-Wide RNAi Screen Reveals Diverse Modulators that Mediate IRE1α–XBP1 Activation
Bibliographic record
Abstract
Abstract Activation of the unfolded protein response (UPR) signaling pathways is linked to multiple human diseases, including cancer. The inositol-requiring kinase 1α (IRE1α)–X-box binding protein 1 (XBP1) pathway is the most evolutionarily conserved of the three major signaling branches of the UPR. Here, we performed a genome-wide siRNA screen to obtain a systematic assessment of genes integrated in the IRE1α–XBP1 axis. We monitored the expression of an XBP1-luciferase chimeric protein in which luciferase was fused in-frame with the spliced (active) form of XBP1. Using cells expressing this reporter construct, we identified 162 genes for which siRNA inhibition resulted in alteration in XBP1 splicing. These genes express diverse types of proteins modulating a wide range of cellular processes. Pathway analysis identified a set of genes implicated in the pathogenesis of breast cancer. Several genes, including BCL10, GCLM, and IGF1R, correlated with worse relapse-free survival (RFS) in an analysis of patients with triple-negative breast cancer (TNBC). However, in this cohort of 1,908 patients, only high GCLM expression correlated with worse RFS in both TNBC and non-TNBC patients. Altogether, our study revealed unidentified roles of novel pathways regulating the UPR, and these findings may serve as a paradigm for exploring novel therapeutic opportunities based on modulating the UPR. Implications: Genome-wide RNAi screen identifies novel genes/pathways that modulate IRE1α–XBP1 signaling in human tumor cells and leads to the development of improved therapeutic approaches targeting the UPR. Visual Overview: http://mcr.aacrjournals.org/content/molcanres/16/5/745/F1.large.jpg. Mol Cancer Res; 16(5); 745–53. ©2018 AACR.
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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 | 0.000 | 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 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".