Human cancers converge at the HIF-2α oncogenic axis
Bibliographic record
Abstract
Cancer development is a multistep process, driven by a series of genetic and environmental alterations, that endows cells with a set of hallmark traits required for tumorigenesis. It is broadly accepted that growth signal autonomy, the first hallmark of malignancies, can be acquired through multiple genetic mutations that activate an array of complex, cancer-specific growth circuits [Hanahan D, Weinberg RA (2000) The hallmarks of cancer. Cell 100:57-70; Vogelstein B, Kinzler KW (2004) Cancer genes and the pathways they control. Nat Med 10:789-799]. The superfluous nature of these pathways is thought to severely limit therapeutic approaches targeting tumor proliferation, and it has been suggested that this strategy be abandoned in favor of inhibiting more systemic hallmarks, including angiogenesis (Ellis LM, Hicklin DJ (2008) VEGF-targeted therapy: Mechanisms of anti-tumor activity. Nat Rev Cancer 8:579-591; Stommel JM, et al. (2007) Coactivation of receptor tyrosine kinases affects the response of tumor cells to targeted therapies. Science 318:287-290; Kerbel R, Folkman J (2002) Clinical translation of angiogenesis inhibitors. Nat Rev Cancer 2:727-739; Kaiser J (2008) Cancer genetics: A detailed genetic portrait of the deadliest human cancers. Science 321:1280-1281]. Here, we report the unexpected observation that genetically diverse cancers converge at a common and obligatory growth axis instigated by HIF-2alpha, an element of the oxygen-sensing machinery. Inhibition of HIF-2alpha prevents the in vivo growth and tumorigenesis of highly aggressive glioblastoma, colorectal, and non-small-cell lung carcinomas and the in vitro autonomous proliferation of several others, regardless of their mutational status and tissue of origin. The concomitant deactivation of select receptor tyrosine kinases, including the EGFR and IGF1R, as well as downstream ERK/Akt signaling, suggests that HIF-2alpha exerts its proliferative effects by endorsing these major pathways. Consistently, silencing these receptors phenocopies the loss of HIF-2alpha oncogenic activity, abrogating the serum-independent growth of human cancer cells in culture. Based on these data, we propose an alternative to the predominant view that cancers exploit independent autonomous growth pathways and reveal HIF-2alpha as a potentially universal culprit in promoting the persistent proliferation of neoplastic cells.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".