Abstract 4303: Definitive identification and characterization of ovarian cancer-initiating cells
Bibliographic record
Abstract
Abstract Serous ovarian cancer (SOC) typically presents with advanced disease. Current therapy significantly increases survival, yet nearly all patients recur within five years and die of their disease. The cancer-initiating cell (CIC) hypothesis holds that only a subset of cells have the potential to extensively self-renew and give rise to other tumor cells. As their properties may differ from bulk tumor cells, CIC may be spared by available therapies. Identification and characterization of CIC may lead to more effective therapeutic strategies. Previous reports suggested the presence of ovarian CIC, but these findings require validation in primary human samples. Primary SOC were dissociated and depleted of CD45+ cells. Cell surface (CD133/CD44/CD117/CDCP1/MUC-1/VEGFR2) and functional (ALDH1) markers were examined by flow cytometry (n=105). All markers demonstrated intra-/inter-tumor heterogeneity; however only CD133, VEGFR2 and ALDH marked minority populations in all samples. In contrast to a report that CD44+/CD117+ cells identify ovarian CIC, CD117 was present on only half of SOC samples examined (N=75) and only one quarter had a CD44+/CD117+ population. Limiting dilution analysis of primary SOC injected in the mammary fat pad of NOD/SCID mice (95% take at 106 cells) revealed the CIC frequency in primary tumors (n=13) and metastases (n=6 +5 matched) to be ∼1/40000 (n=13). The CIC frequency was significantly higher (∼1/9000) in primary and recurrent ascites (n=16, p=0.002). Xenografts could be passaged at least 3 times, providing evidence of self-renewal. The CIC frequency remained constant in nearly all xenografts from primary tumors, but increased substantially with passage of recurrences, suggesting greater genetic instability. CD133+ cells from primary tumors (n=2), matched metastases (n=2), ascites (n=6) and passage 1 xenografts (n=6) were enriched for CIC (1/300-1/4000), and all (or the vast majority) of CIC activity resided within the CD133+ fraction. Xenografts from CD133+ cells gave rise to CD133+ and CD133- cells and could be serially passaged at least 1-3x. VEGFR2+ and ALDH1+ cells also were enriched for CIC, to a lower extent than CD133. In contrast, after sorting for CD117/CD44 (n=3), tumors arose from all fractions but CD117+/CD44+ cells. Our data are consistent with a hierarchical model of SOC and indicate that CD133 is a marker for ovarian CIC. Current work is devoted to profiling the CD133+ population and identifying additional markers, using high throughput flow cytometry and a panel of 234 antigens and other methods. Note: This abstract was not presented at the AACR 101st Annual Meeting 2010 because the presenter was unable to attend. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4303.
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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) | 0.005 | 0.002 |
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".