Abstract B09: Single-cell RNA sequencing of normal endometrial organoids uncovers novel cell-type markers for prognostication of primary tumor samples
Bibliographic record
Abstract
Abstract Endometrial epithelium gives rise to both endometrial and ovarian cancers (of clear-cell and endometrioid subtypes), the latter arising from ectopic endometrium (endometriosis). Endometrial epithelium comprises mainly secretory cells, with a minor ciliated cell population. Due to their scarcity, little is known about the biology or function of endometrial ciliated cells. To understand the biology of endometrial epithelium, and by extension the cancers that arise from it, organoids derived from normal endometrial tissue were cultured. Notch signaling inhibitors were used to induce ciliated cell differentiation. Through single-cell RNA sequencing, distinct secretory and ciliated cell populations were observed, with the ciliated cell population increasing with Notch signaling inhibition. Many novel markers of ciliated cells were observed, but no highly specific markers of secretory cell differentiation. A marker of secretory cells (MST) and several markers of ciliated cells (FAM92B, WDR16 and DYDC2) were validated by immunohistochemistry on organoids and tissue sections. In endometrial tumors, both MST and FAM92B exhibited diffuse staining and were markers of better prognosis. This suggests that tumors expressing differentiation markers have better prognosis, whether it is a marker of secretory or ciliated cells. Interestingly, a small number of endometrial tumors stained positive for DYDC2; however, these tumors exhibited a variable staining pattern with 25-50% tumor cells staining intensely, and the remaining tumor cells not staining at all. A similar variable staining pattern had been observed previously with CTH, another ciliated cell marker. Endometrial and ovarian tumor tissue microarrays were stained with DYDC2, CTH and two ciliated cell markers, FOXJ1 and p73. For all these markers, a subset of tumors displayed a variable staining pattern and for endometrial cancers, the variable staining was a good prognostic indicator. Single-cell sequencing of endometrial tumors has been able to capture these two populations of tumor cells. In ovarian tumors, only variable CTH staining was a significant prognostic indicator. Normal endometrial secretory cells are able to differentiate into ciliated cells, and the variable staining pattern suggests that a subset of tumors retains this ability, and these are clinically less aggressive. Using single-cell sequencing technology on normal tissues to guide development of prognostic markers and provide insight into the biology of the tumors arising from these tissues may be useful for many other tumor types. Citation Format: Dawn R. Cochrane, Kieran R. Campbell, Kendall Greening, Germain C. Ho, James Hopkins, Minh Bui, Vassilena Sharlandjieva, Daniel Lai, Maya DeGrood, Evan W. Gibbard, Samuel Leung, Angela S. Cheng, Jamie L.P. Lim, Samantha Neilson, David Farnell, Friedrich Kommoss, Jessica N. McAlpine, Sohrab P. Shah, David G. Huntsman. Single-cell RNA sequencing of normal endometrial organoids uncovers novel cell-type markers for prognostication of primary tumor samples [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr B09.
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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 | 0.001 |
| 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 | 0.001 |
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".