High Ki67 Gene Expression Is Associated With Aggressive Phenotype in Hepatocellular Carcinoma
Bibliographic record
Abstract
Background: Hepatocellular carcinoma (HCC) with high Ki67 protein expression, the most commonly used cell proliferation marker, is associated with an aggressive biologic phenotype; however, conventional immunostaining is hampered by variability in institutional protocol, specific antibody probe, and by assessor subjectivity. To this end, we hypothesized that Ki67 gene ( MKi67 ) expression would identify highly proliferative HCC, and clarify its association with oncologic outcome, tumor progression, and immune cell population in the tumor microenvironment (TME). Furthermore, we sought to identify the cell-cycle gene expression profile that confers this aggressive phenotype. Methods: A total of 473 HCC patients with clinicopathological data associated with transcriptome were selected for this study: 358 patients from The Cancer Genome Atlas (TCGA) as the testing cohort, and 115 from GSE76427 as the validation cohort. Each cohort was divided into a highly proliferative group (MKi67-high) and the low MKi67 group (MKi67-low) by the median of Ki67 gene ( MKi67 ) expression levels. Results: MKi67-high HCC patients had worse disease-free survival (DFS), disease-specific survival (DSS), and overall survival (OS) independent of histological grade in the TCGA cohort. MKi67 expression correlated with histological grade and tumor size. MKi67 expression increased throughout the HCC carcinomatous sequence from normal liver, cirrhotic liver, early HCC, and advanced HCC. MKi67-high HCC was associated with higher intratumor heterogeneity, homologous recombination deficiency, and altered fraction as well as intratumoral infiltration of T helper type 1 (Th1) and Th2 cells, but lower interferon-gamma response and M2 macrophage infiltration. Cell proliferation-related gene sets in the Hallmark collection (E2F targets, G2M checkpoint, Myc target v1 and mitotic spindle), MTORC1 signaling, DNA repair, PI3K MTOR signaling, and unfolded protein response were all enriched in the MKi67-high HCC (false discovery rate (FDR) < 0.25). Conclusions: High MKi67 gene expression identified highly proliferative HCC with aggressive biology involving classical pathways in cell cycle regulation and DNA repair, as well as poor overall oncologic outcomes. This suggests potential for personalized treatment strategies, but validation and refinement of these observations require further research to elucidate the underlying mechanisms and validate therapeutic targeting of these pathways in MKi67-high HCC tumors. World J Oncol. 2024;15(2):257-267 doi: https://doi.org/10.14740/wjon1751
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".