Abstract A108: A Tissue-Specific Hydrogel Promotes the Enrichment of Pancreatic Cancer Stem Cells
Bibliographic record
Abstract
Abstract Pancreatic Ductal Adenocarcinoma (PDAC) is one of the deadliest types of cancer. To identify novel therapeutic targets, it is crucial to develop robust cell culture models that more faithfully recapitulate the microenvironment and PDAC heterogeneity, including the enrichment for cancer stem cells (CSCs). Here, we generated and characterized tumorspheres encapsulated in a tissue-specific hydrogel, recapitulating the desmoplastic extracellular matrix (ECM) of PDAC. We initially demonstrated the potential of CFPAC-1 and HPAF-II cell lines to generate suspended tumorspheres by plating the cell lines in 24-well ultra-low adherent plates and using a cell culture medium composed of DMEM/F-12 supplemented with EGF, FGF, heparin, insulin, and B27. To assess the capacity to generate encapsulated tumorspheres in the pancreatic hydrogel, we encapsulated the cells using the same medium as described above. Over 10 days, PDAC cells generated proliferative and highly viable tumorspheres, as indicated by size measurements and Live/Dead staining. Next, to determine whether suspended tumorspheres and encapsulated tumorspheres were enriched for CSCs, stemness markers were evaluated by qPCR. Compared to 2D monolayers, there was an increase in stemness-related genes in the suspended HPAF-II tumorspheres, including ALDH1, C-Met, IGF2R, EPCAM, CD44, ABCB1, KLF4, and SOX2, while the expression of ABCG2 decreased. Interestingly, encapsulated HPAF-II tumorspheres generated within the hydrogel increased the expression of ALDH1, EPCAM, KLF4, SOX2, ABCB1, and Nestin in comparison with monolayer and suspended tumorspheres models. Suspended CFPAC-1 tumorspheres increased the expression of ALDH1, EPCAM, KLF4, and Nestin in comparison with 2D monolayers, while CXCR4, ABCB1, and CD133 expression levels decreased. The expression of ALDH1, EPCAM, and KLF4 was reduced in encapsulated CFPAC-1 tumorspheres compared to those generated in suspension, while CD44 was the only gene that exhibited an increase. Since both CSCs and desmoplastic tumor environment can contribute to therapy resistance in PDAC, we tested two PROTAC molecules targeting KRAS and BET proteins (1µM), using the suspended and encapsulated tumorspheres. Both KRAS and BET proteins are well-established targets in PDAC, and these PROTACs have shown efficacy in 2D models. The PROTAC-mediated KRAS degradation reduced the area and perimeter of encapsulated HPAF-II tumorspheres, while BET proteins degradation disrupted the tumorspheres, as seen by changes in the morphology and cell death, evidenced by SYTOX Orange Nucleic Acid Staining. In summary, our findings suggested that HPAF-II tumorspheres generated within a pancreas-specific hydrogel can enrich for CSC markers. However, encapsulated CFPAC-1 tumorspheres did not present the same phenotype, demonstrating that different cell lines can behave differently in this model. Finally, encapsulated HPAF-II tumorspheres may better reflect the efficacy of different anticancer compounds. Citation Format: Beatriz Magalhães Gomes, Ana Júlia dos Santos Bianco Duarte, Manoela Brito Lopes, Raphael Lucas More, Sara Evelyn de Castro Silva, Rodrigo Alexandre Panepucci, Heidge Fukumasu, Susanne Müller, Pedro Luiz Porfirio Xavier. A Tissue-Specific Hydrogel Promotes the Enrichment of Pancreatic Cancer Stem Cells [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research—Emerging Science Driving Transformative Solutions; Boston, MA; 2025 Sep 28-Oct 1; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2025;85(18_Suppl_3):Abstract nr A108.
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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) | 0.002 | 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".