Abstract 4899: Investigating mutation co-operativity in early tumorigenesis of low-grade serous ovarian carcinoma with organoid model system and single-cell RNA sequencing
Bibliographic record
Abstract
Abstract Background: Ovarian cancers are the most common gynecologic malignancies. Low grade serous ovarian carcinoma (LGSOC) is a rare tumor, accounting for ~2000 cases diagnosed every year in North America. Most of LGSOCs are characterized by high fatality rates over the long term, with only 20% of women surviving 10 years after diagnosis, due suboptimal response to current chemotherapies. Understanding the molecular events is crucial for developing better early detection strategies and more informed therapeutic options. LGSOC harbors a relatively stable genome, with common activating mutations in BRAF, KRAS and NRAS. Recently, NRAS mutations (Q61R) were found to co-exist with EIF1AX mutations (G8E) in LGOSC, and the two mutated proteins functionally cooperate. Increasing histological and gene expression evidence suggest that the cell of origin of LGSOC is in the Fallopian tube. Low incidence of this disease means it is poorly understood, and the resulting lack of available models further limits the study of underlying mechanisms. We therefore propose to use organoid cultures. These consist of 3D multicellular units that resemble in vitro a tissue or organ of body, both structurally and functionally. Objective: to elucidate molecular events underpinning LGSOC, specifically how NRAS(Q61R) and EIF1AX (G8E) mutations co-operate to drive early stages of tumorigenesis, with organoid system and single-cell RNA sequencing (scRNA-seq) technologies. Method: To reflect genetic background and cell of origin of LGSOC, NRAS Q61R and EIF1AX G8E mutant proteins were overexpressed via lentiviral transduction in organoid cultures of normal human Fallopian tubes. After allowing organoids to establish, 2 weeks after transduction gene expression alterations were resolved with scRNA-seq. Histology of organoids were assessed for histomorphological signs of transformation. Patient-derived tumor organoids (PDTOs) were also cultured to assess how well our LGSOC-modelling organoids (LMOs) recapitulate the histological features of patient tumours. Result: LMOs showed cytologic signs of transformation such as increased nuclear/cytoplasmic ratio, prominent nucleoli, and cellular pleomorphism. Papillary structures, a major histologic characteristic of LGSOC tumor were also observed in LMOs. PDTOs showed similar cytological features and organization as LMOs. From scRNA-seq, we identified genes up-regulated in double-mutant compared to single-mutant organoids such as CA125 and TACSTD2. CA125 is one of the earliest identified biomarkers for ovarian cancer and has remained to be the most useful serum marker despite limited sensitivity and specificity; whereas TACSTD2 overexpression has been found to correlate with a chemo-resistant, aggressive malignant phenotype. Conclusion and future directions: Organoid culture and scRNA-seq is a powerful duo in studying early tumorigenesis events. We established a novel model system of LGSOC by introducing common co-occurring mutations into normal Fallopian tube tissues. Our model recapitulates to a large extent of LGSOC histology. Genes upregulated in double mutants included well-characterized biomarker (CA125) and a potential biomarker or therapeutic target (TACSTD2). Our work will be crucial for developing early detection strategies and targeted treatment options. Citation Format: Joyce Yu Han Zhang, Dawn Cochrane, Kieran Campbell, Minh Bui, Germain Ho, Cindy Shen, Winnie Yang, Clara Salamanca, Genny Trigo, David G. Huntsman. Investigating mutation co-operativity in early tumorigenesis of low-grade serous ovarian carcinoma with organoid model system and single-cell RNA sequencing [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4899.
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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".