The STEAP protein family: Versatile oxidoreductases and targets for cancer immunotherapy with overlapping and distinct cellular functions
Bibliographic record
Abstract
The human six-transmembrane epithelial antigen of the prostate (STEAP) protein family contains at least five homologous members. The necessity of multiple homologous STEAP proteins is still unclear, but their peculiar and tissue-specific expression suggests that they are assigned to distinct functional tasks. This concept is supported by the fact that especially STEAP1, and to a lesser extent STEAP2 and -4, are highly over-expressed in many different cancer entities, while being only minimally expressed in a few normal tissues. Despite their very similar domain organisation, STEAP3 seems to act as a potent metalloreductase essential for physiological iron uptake and turnover, while in particular STEAP4 appears to be rather involved in responses to nutrients and inflammatory stress, fatty acid and glucose metabolism. Moreover, individual STEAP proteins possess overlapping functions important for growth and survival of cancer cells. Due to their membrane-bound localisation and their high expression in many different cancers such as prostate, breast and bladder carcinoma as well as Ewing's sarcoma, STEAP proteins have been recognised and utilised as promising targets for cell- and antibody-based immunotherapy. This review summarises our present knowledge of the individual members of the human STEAP family and highlights the functional differences between them.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".