Identification of Small Molecules that Sensitize Resistant Tumor Cells to Tumor Necrosis Factor-Family Death Receptors
Bibliographic record
Abstract
Two major pathways for apoptosis have been identified, involving either mitochondria (intrinsic) or tumor necrosis factor (TNF)-family death receptors (extrinsic) as initiators of caspase protease activation and cell death. Because tumor resistance to TNF-family death receptor ligands is a common problem, helping malignant cells evade host immune defenses, we sought to identify compounds that selectively sensitize resistant tumor cells to death receptor ligands. We screened a 50,000-compound library for agents that enhanced anti-FAS antibody-mediated killing of FAS-resistant PPC-1 prostate cancer cell, then did additional analysis of the resulting hits to arrive at eight compounds that selectively sensitized PPC-1 cells to anti-FAS antibody (extrinsic pathway agonist) without altering sensitivity to staurosporine and etoposide (VP-16; intrinsic pathway agonists). These eight compounds did not increase Fas surface levels and also sensitized PPC-1 cells to apoptosis induced by TNF-family member TNF-related apoptosis-inducing ligand, consistent with a post-receptor mechanism. Of these, two reduced expression of c-FLIP, an intracellular antagonist of the extrinsic pathway. Characterization of the effects of the eight compounds on a panel of 10 solid tumor cell lines revealed two structurally distinct compounds that frequently sensitize to extrinsic pathway agonists. Structure-activity relation studies of one of these compounds revealed a pharmacophore from which it should be possible to generate analogues with improved potency. Altogether, these findings show the feasibility of identifying compounds that selectively enhance apoptosis via the extrinsic pathway, thus providing research tools for uncovering resistance mechanisms and a starting point for novel therapeutics aimed at restoring sensitivity of tumor cells to immune effector mechanisms.
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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".