Abstract IA024: Identification of a “hypoxic secretome” and its role in metastasis
Bibliographic record
Abstract
Abstract Only a small percentage of disseminating tumor cells are capable of forming lethal metastatic foci. Though advances in sequencing and genomics have dramatically enhanced our understanding of primary tumor biology and novel target identification, these techniques alone have not proven sufficient to identify the factors that permit metastasis of this small cellular fraction. For example, we observed that in some tumors the major molecular predictor of metastatic potential is HIF1α protein stabilization in response to low intratumoral O2 tension (hypoxia). These observations clearly show that in-depth understanding of environmental signals and subsequent cellular responses is necessary to fully characterize metastatic potential. Consistent with our earlier observations, we discovered that the collagen-modifying enzyme PLOD2, a direct transcriptional target of HIF1α, dramatically enhances both early (cell migration/invasion) and late (extravasation/lung colonization) steps of the metastatic cascade. We previously reported the role of PLOD2 in modulating the primary tumor microenvironment to facilitate cell migration and intravasation. However, the mechanisms by which PLOD2 and tumor associated collagen impact later metastatic stages (i.e., endothelial adherence, extravasation) are unknown- in part because these processes are particularly difficult to simulate in vitro and to visualize in vivo. Therefore, we have developed new models and tools including a zebrafish embryo xenograft system to image migrating and extravasating tumor cells in vivo. This approach allows us to investigate the late metastatic cascade and define the microenvironmental cues that promote tumor cell dissemination. We also observed that PLOD2-modified collagen is secreted into the extracellular milieu during dissemination and weakens endothelial barrier function. We are investigating the role of tumor collagen and PLOD2 in endothelial adherence and extravasation for the purpose of therapeutically targeting the molecular underpinnings of metastases. Our work focuses on soft tissue sarcomas. However, recent studies by other groups have linked PLOD2 and modified collagen to carcinoma metastasis as well, suggesting a broader applicability for our work. Ultimately, we believe these studies will transform our ability to treat and even prevent metastasis, a unique possibility in sarcoma patients due to the relatively long interval between primary tumor diagnosis and metastatic outgrowth in some patients (5-10 years). The tools we have developed and the mechanisms we are pursuing will open new avenues of research that were once inaccessible and lead to novel therapeutic opportunities for the treatment of metastatic disease in multiple cancer contexts. Citation Format: T.S. Karin Eisinger, Ying Liu, Ileana Murazzi. Identification of a “hypoxic secretome” and its role in metastasis [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 IA024.
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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 | 0.001 |
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".