Upregulation of <i>BCAM</i> and its sense lncRNA <i>BAN</i> are associated with gastric cancer metastasis and poor prognosis
Bibliographic record
Abstract
Patients with metastatic gastric cancer (GC) have a poor prognosis; however, the molecular mechanism of GC metastasis remains unclear. Here, we employed bioinformatics to systematically screen the metastasis-associated genes and found that the levels of basal cell adhesion molecule (BCAM) were significantly increased in GC tissues from patients with metastasis, as compared to those without metastasis. The upregulation of BCAM was also significantly associated with a shorter survival time. Depletion of BCAM inhibited GC cell migration and invasion. Knockout (KO) of BCAM by the CRISPR/Cas9 system reduced the invasion and metastasis of GC cells. To explore the mechanism of BCAM upregulation, we identified a previously uncharacterized BCAM sense lncRNA that spanned from exon 6 to intron 6 of BCAM, and named it as BCAM-associated long noncoding RNA (BAN). Knockdown of BAN inhibited BCAM expression at both mRNA and protein levels. Knockdown of BAN suppressed GC cell migration and invasion, which was effectively rescued by ectopic expression of BCAM. Further clinical data showed that BAN upregulation was associated with GC metastasis and poor prognosis. Importantly, BAN expression was also significantly associated with that of BCAM in GC tissues. Taken together, these results indicate that increased expression of BCAM and its sense lncRNA BAN promote GC cell invasion and metastasis, and are associated with poor prognosis of GC patients.
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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".