Abstract B09: Efficient generation of patient-matched malignant and normal primary cell cultures from clear cell renal cell carcinoma patients: clinically relevant models for research and personalized medicine
Bibliographic record
Abstract
Abstract Patients with clear cell renal cell carcinoma (ccRCC) have few therapeutic options, as ccRCC is unresponsive to chemotherapy and is highly resistant to radiation. Recently targeted therapies have extended progression-free survival, but responses are variable and no significant overall survival benefit has been achieved. Commercial ccRCC cell lines are often used as model systems to develop novel therapeutic approaches, but these do not accurately recapitulate primary ccRCC tumors at the genomic and transcriptional levels. Furthermore, ccRCC exhibits significant intertumor genetic heterogeneity, and the limited cell lines available fail to represent this aspect of ccRCC. Our objective was to generate accurate preclinical in vitro models of ccRCC using tumor tissues from ccRCC patients. ccRCC primary single cell suspensions were cultured in fetal bovine serum (FBS)-containing media or defined serum-free media (DFSM). The apparent efficiency of primary cell culture establishment was high in both culture conditions, but genotyping by single nucleotide polymorphism (SNP) arrays revealed that the majority of cultures in FBS (6 of 8), and all of the cultures in DFSM (8 of 8), contained normal, not cancer cells. To distinguish cancer vs. normal cells in subsequent experiments, we sequenced the von Hippel Lindau (VHL) gene, which is mutated in a large percentage of patients, in a cohort of samples for which cryopreserved viable single cell suspensions were available. Once patients with sequence-detectable mutations were identified, the cells were thawed and cultured as before. Established cultures were then sequenced for the patient-specific VHL mutations. Once again, the majority of cultures in FBS (1 of 7), and all of the cultures in DSFM (7 of 7) contained VHL-wild type cells. The loss of VHL leads to accumulation of hypoxia-inducible factor (HIF) and expression of HIF target genes. Therefore, in an attempt to select for VHL-mutant cancer cells, we used fluorescence activated cell sorting (FACS) to isolate cells expressing Carbonic Anhydrase IX (CA9), a cell surface HIF target. Isolated CA9+ cells were cultured in FBS-containing media, and upon genotyping, we found that VHL-mutant ccRCC cell cultures were established with an efficiency of ~85%. Parallel cultures of bulk single cell suspensions in serum-free conditions again selected for growth of normal (VHL-wild type) cells. The normal cells were verified to be renal proximal tubule epithelial cells based on their expression of renal proximal tubule markers Aquaporin-1 and Alkaline Phosphatase. Transcriptional profiling of ccRCC and matched normal cell cultures identified up- and down-regulated networks in ccRCC and comparison to The Cancer Genome Atlas confirmed the clinical validity of our cell cultures. The ability to establish patient-derived cultures of ccRCC cells and matched normal kidney epithelial cells from almost every patient provides a resource for future development of novel therapies and personalized medicine for ccRCC patients. Citation Format: Nazleen Lobo, Craig Gedye, Kevin R. Brown, Joshua Paterson, Natalie Stickle, Jason Moffat, Michael A.S. Jewett, Laurie E. Ailles. Efficient generation of patient-matched malignant and normal primary cell cultures from clear cell renal cell carcinoma patients: clinically relevant models for research and personalized medicine. [abstract]. In: Proceedings of the AACR Special Conference: Patient-Derived Cancer Models: Present and Future Applications from Basic Science to the Clinic; Feb 11-14, 2016; New Orleans, LA. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(16_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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".