Decreased PCSK9 expression in human hepatocellular carcinoma
Bibliographic record
Abstract
BACKGROUND: The management of hepatocellular carcinoma (HCC) is limited by the lack of adequate screening biomarkers and chemotherapy. In response, there has been much interest in tumor metabolism as a therapeutic target. PCSK9 stimulates internalization of the LDL-receptor, decreases cholesterol uptake into hepatocytes and affects liver regeneration. Thus, we investigated whether PCSK9 expression is altered in HCC, influencing its ability to harness cholesterol metabolism. METHODS: Thirty-nine patients undergoing partial hepatectomy or liver transplantation for HCC were consented for use of HCC tissue to construct a tissue microarray (TMA). The TMA was immunostained for PCSK9. Imagescope software was used to objectively determine staining, and assess for pathological and clinical correlations. PCSK9 and LDL receptor mRNA levels in flash-frozen HCC and adjacent liver tissue were determined by quantitative RT-PCR. Serum PCSK9 levels were determined by ELISA. RESULTS: By immunohistochemistry, there was significantly lower expression of PCSK9 in HCC as compared to adjacent cirrhosis (p-value < 0.0001, wilcoxon signed-rank test). Significantly greater staining of PCSK9 was present in cirrhosis compared to HCC (p value <0.0001), and positivity (percentage of positive cells) was significantly greater in cirrhosis compared to HCC (p-value < 0.0001). Conversely, significantly higher expression of LDL-R was present in HCC as compared to the adjacent cirrhosis (p-value < 0.0001). There was no significant correlation of PCSK9 staining with grade of tumor, but there were significant correlations between PCSK9 staining and stage of fibrosis, according to spearman correlation test. PCSK9 mRNA levels were relatively less abundant within HCC compared to adjacent liver tissue (p-value =0.08) and normal control tissue (p-value =0.02). In contrast, serum PCSK9 levels were significantly increased among patients with HCC compared to those with chronic liver disease without HCC (p-value =0.029). LDL receptor mRNA was consistantly greater in HCC when compared to normal control tissue (p-value = 0.06) and, in general, was significantly greater in HCC when compared to adjacent liver (p-value = 0.04). CONCLUSIONS: The decreased expression of PCSK9 and conversely increased LDL-R expression in HCC suggests that HCC modulates its local microenvironment to enable a constant energy supply. Larger-scale studies should be conducted to determine whether PCSK9 could be a therapeutic target for HCC.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".