High-throughput flow cytometry screening of human hepatocellular carcinoma reveals CD146 to be a novel marker of tumor-initiating cells
Bibliographic record
Abstract
Hepatocellular carcinoma (HCC) remains a common and lethal cancer. Cancer stem cells, or tumor-initiating cells (TICs), are thought to contribute to the pathogenesis of HCC, but remain to be fully characterized. Unbiased screens of primary human HCC cells for the identification of novel HCC TIC markers have not been reported. We conducted high-throughput flow cytometry (HT-FC) profiling to characterize the expression of 375 CD antigens on tumor cells from 10 different human HCC samples. We selected 91 of these for further analysis based on HT-FC data that showed consistent expression in discrete, rare, sortable populations of HCC cells. Nine of these CD antigens demonstrated significantly increased expression in the EpCAM+ stem/progenitor fraction of a human HCC cell line and were further evaluated in primary human HCC tissues from 30 different patients. Of the nine tested, only CD146 demonstrated significantly increased expression in HCC tumor tissue as compared with matched adjacent non-tumor liver tissue. CD146+CD31−CD45− cells purified from HCC tumors and cell lines demonstrated a unique phenotype distinct from mesenchymal stem cells. As compared with other tumor cell fractions, CD146+CD31−CD45− cells showed significantly increased colony-forming capacity in vitro, consistent with TICs. This study demonstrates that HT-FC screening can be successfully applied to primary human HCC and reveals CD146 to be a novel TIC marker in this disease.
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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 | 0.000 | 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".