Abstract B005: Hypoxic sarcoma spheroid on a chip: Insights into treatment response
Bibliographic record
Abstract
Abstract Context: Hypoxia is found in at least 47% of soft-tissue sarcoma (STS) patients and is known to be a major contributor to treatment resistance, metastasis progression and associated with poor prognosis. Indeed, expression of hypoxic proteins (HIF1-α, CAIX) in STS is associated with a shorter overall survival, and a shorter progression-free survival in patients. Specifically, Yang et al. demonstrated in 2017 that patients stratified by a 24-gene hypoxia signature had a poorer distant metastasis free survival. Nevertheless, hypoxia is seldom considered during treatment development due to the lack of a user-friendly way to culture naturally hypoxic 3D tumor models. Therefore, we developed a user-friendly in vitro preclinical tool allowing the study of natural chronic hypoxia and its effect on treatment response. Methods: Microfabrication technologies were used to design a microfluidic chip allowing culture, maintenance, treatment, and analysis of 240 STS naturally hypoxic spheroids (750µm of diameter). SK-LMS-1 Human leiomyosarcoma and STS117 (human primary undifferentiated pleomorphic sarcoma cells) spheroids were formed 48h after seeding. Gold-standard hypoxic protein Hypoxia Inducible Factor 1 alpha (HIF1- α) and Carbonic Anhydrase IX (CAIX) expression was assessed by Western Blot (WB). Spatial distribution of CAIX was assessed by immunofluorescence (IF). Based on the IF, an in silico model of the oxygen consumption of the spheroids was built using COMSOL. As a proof of concept, the spheroids were treated using two oxygen-dependent treatment: RT and hypoxia prodrug Tirapazamine (TPZ). DNA-damages were quantified using yH2AX in IF to assess treatment efficacy. Results: These spheroids on-a-chip are the largest to date (>750µm), and express gold-standard hypoxic protein CAIX in their core only, a feature absent in spheroids of 450µm of diameter of the same cell lines. HIF1-α expression patterns were cell line dependent. CAIX expression in SK-LMS-1 and STS117 large spheroids was respectively 7.8 and 24 times higher than in 450µm spheroids. Quantification of DNA damages (count of yH2AX foci/nuclei area in mm²) demonstrated that TPZ preferentially targets the hypoxic core. However, the response (DNA damages) to RT alone showed no evidence of radioresistance of the hypoxic regions, on samples fixed 24h after irradiation. A possible explanation could be that, in 24h, the oxygen-dependent DNA repair and the accumulation of DNA damages in hypoxic regions hide the oxygen-dependent radioresistance. Therefore, quantification of DNA damages with yH2AX 30min after irradiation is currently being investigated, as maximum DNA damage response has been shown to be observed at this time point. Our 750µm spheroids naturally display a hypoxic core expressing gold-standard hypoxic protein CAIX at 120µm of depth, a feature absent in smaller spheroids. Together, these results cement our microfluidic device and our spheroids as a potent fundamental and pre-clinical tool to explore the biology of hypoxia on 3D tumor model, its effects on treatment response. Citation Format: Elena Refet-Mollof, Ouafa Najyb, Rodin Chermat, Audrey Glory, Julie Lafontaine, Philip Wong, Thomas Gervais. Hypoxic sarcoma spheroid on a chip: Insights into treatment response [abstract]. In: Proceedings of the AACR Special Conference: Sarcomas; 2022 May 9-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(18_Suppl):Abstract nr B005.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".