Cystatin B Promotes the Proliferation, Migration, and Invasion of Intrahepatic Cholangiocarcinoma
Bibliographic record
Abstract
Background and Aims: Cystatin B (CSTB) has been demonstrated to play a significant role in the pathogenesis of a number of diseases, including the evolution and progression of multiple cancers. Nevertheless, the function of CSTB in intrahepatic cholangiocarcinoma (iCCA) is yet to be fully elucidated. Methods: By analyzing transcriptome sequencing data from the FU-iCCA cohort, the iCCA-27 cohort, and three public databases, we identified genes associated with iCCA prognosis and selected CSTB as the subject of our study. The expression of CSTB was examined between tumor tissues and adjacent normal tissues obtained from iCCA patients via Western blot analysis. The clinical significance of CSTB was analyzed through immunohistochemical staining of a tissue microarray. Subsequently, the biological effects of CSTB overexpression or knockdown on iCCA cells were evaluated in vitro and in vivo. Results: CSTB expression was markedly elevated in the CCA pathological tissues in comparison to the corresponding adjacent normal tissues. A correlation was identified between higher CSTB expression and poorer patient prognosis in the analysis of 176 iCCA patients. It is noteworthy that overexpression or knockdown experiments demonstrated that CSTB plays a role in the proliferation, migration, and invasion of cells. In subcutaneous tumor models in nude mice, the knockdown of CSTB resulted in smaller tumors in terms of size and weight, and a slower growth rate. Conclusions: CSTB plays a significant function in the regulation of iCCA progression and may serve as a promising biomarker for iCCA.
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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 | 0.001 | 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".