Sox7 Is an Independent Checkpoint for β-Catenin Function in Prostate and Colon Epithelial Cells
Bibliographic record
Abstract
The presence of somatic beta-catenin mutations in some prostate cancers implies that aberrant WNT signaling is involved in the cancer development. Although beta-catenin stability is regulated by a multicomponent destruction complex, mutational alterations of beta-catenin or other components of the destruction complexes are rare in prostate tumors. Therefore, beta-catenin may be regulated by another protein in the prostate. In fact, recent linkage and somatic deletion analyses in prostate cancers reveal a 1.4-Mb candidate tumor suppressor locus on 8p23.1, which includes the Sox7 gene. Here we show that Sox7 protein expression was indeed down-regulated in 47% (15 of 32) of prostate adenocarcinomas. In addition, Sox7 mRNA was down-regulated in 60% of snap-frozen tumors. This down-regulation was found to be due to tumor-specific promoter hypermethylation, which was present in 48% (10 of 21) of primary prostate tumors and 44% (11 of 25) of prostate cancer cell lines/xenografts. We discovered that Sox7 protein physically interacts with beta-catenin and suppresses beta-catenin-mediated transcription by depleting active beta-catenin. Furthermore, in HCT116 colorectal cancer cell lines with Sox7 inactivation, ectopic Sox7 expression suppressed cell proliferation and inhibited transcription that was activated by an endogenous mutant beta-catenin. Although nearly all colorectal cancers contain mutations in beta-catenin or adenomatous polyposis coli/axin, epigenetic silencing of Sox7 was still observed. These data suggest that Sox7 is a tumor suppressor that functions as an independent checkpoint for beta-catenin transcriptional activity. Inactivation of Sox7 could promote the development of a majority of colorectal tumors and approximately half of prostate tumors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".