IL6 Promotes a STAT3-PRL3 Feedforward Loop via SHP2 Repression in Multiple Myeloma
Bibliographic record
Abstract
Overexpression of PRL-3, an oncogenic phosphatase, was identified as a novel cluster in patients with newly diagnosed multiple myeloma. However, the regulation and oncogenic activities of PRL-3 in multiple myeloma warrant further investigation. Here, we report that IL6 activates STAT3, which acts as a direct transcriptional regulator of PRL-3. Upregulation of PRL-3 increased myeloma cell viability and rephosphorylated STAT3 in a biphasic manner through direct interaction and deactivation of SHP2, thus blocking the gp130 (Y759)-mediated repression of STAT3 activity. Abrogation of PRL-3 reduced myeloma cell survival, clonogenicity, and tumorigenesis, and detailed mechanistic studies revealed "deactivation" of effector proteins such as Akt, Erk1/2, Src, STAT1, and STAT3. Furthermore, loss of PRL-3 efficiently abolished nuclear localization of STAT3 and reduced its occupancy on the promoter of target genes c-Myc and Mcl-1, and antiapoptotic genes Bcl2 and Bcl-xL. PRL-3 also played a role in the acquired resistance of myeloma cells to bortezomib, which could be overcome by PRL-3 silencing. Of clinical relevance, STAT3 and PRL-3 expression was positively correlated in five independent cohorts, and the STAT3 activation signature was significantly enriched in patients with high PRL-3 expression. Furthermore, PRL-3 could be used as a biomarker to identify high-risk patients with multiple myeloma that exhibited poor prognosis and inferior outcome even when treated with novel combinational therapeutics (proteasome inhibitors and immunomodulatory imide drugs). Conclusively, our results support a feedforward mechanism between STAT3 and PRL-3 that prolongs prosurvival signaling in multiple myeloma, and suggest targeting PRL-3 as a valid therapeutic opportunity in multiple myeloma. SIGNIFICANCE: IL6 promotes STAT3-dependent transcriptional upregulation of PRL-3, which in turn re-phosphorylates STAT3 and aberrantly activates STAT3 target genes, leading to bortezomib resistance in multiple myeloma.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".