OGX-427 inhibits tumor progression and enhances gemcitabine chemotherapy in pancreatic cancer
Bibliographic record
Abstract
Despite many advances in oncology, almost all patients with pancreatic cancer (PC) die of the disease. Molecularly targeted agents are offering hope for their potential role in helping translate the improved activity of combination chemotherapy into improved survival. Heat shock protein 27 (Hsp27) is a chaperone implicated in several pathological processes such as cancer. Further, Hsp27 expression becomes highly upregulated in cancer cells after chemotherapy. Recently, a modified antisense oligonucleotide that is complementary to Hsp27 (OGX-427) has been developed, which inhibits Hsp27 expression and enhances drug efficacy in cancer xenograft models. Phase II clinical trials using OGX-427 in different cancers like breast, ovarian, bladder, prostate and lung are in progress in the United States and Canada. In this study, we demonstrate using TMA of 181 patients that Hsp27 expression and phosphorylation levels increase in moderately differentiated tumors to become uniformly highly expressed in metastatic samples. Using MiaPaCa-2 cells grown both in vitro and xenografted in mice, we demonstrate that OGX-427 inhibits proliferation, induces apoptosis and also enhances gemcitabine chemosensitivity via a mechanism involving the eukaryotic translation initiation factor 4E. Collectively, these findings suggest that the combination of Hsp27 knockdown with OGX-427 and chemotherapeutic agents such as gemcitabine can be a novel strategy to inhibit the progression of pancreas cancer.
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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 | 0.000 |
| 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".