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Record W4393073484 · doi:10.1158/1538-7445.am2024-1274

Abstract 1274: Investigating PLOD2 as a therapeutic target to overcome metastasis in radiorecurrent prostate cancer

2024· article· en· W4393073484 on OpenAlexaff
Gavin Frame, Hon S. Leong, Roni Haas, Xiaoyong Huang, Jessica Wright, Paul C. Boutros, Thomas Kislinger, Stanley K. Liu

Bibliographic record

VenueCancer Research · 2024
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsUniversity Health NetworkSunnybrook Health Science CentreUniversity of Toronto
Fundersnot available
KeywordsCancerProstate cancerMetastasisMedicineProstateOncologyInternal medicine

Abstract

fetched live from OpenAlex

Abstract Prostate cancer (PCa) is the second most common cancer in males, with 1 in 8 men developing the disease in their lifetime. For PCa, a common treatment strategy is external beam radiation therapy to the prostate. However, when cancer recurs (radiorecurrent PCa), it often behaves aggressively by invading into surrounding organs or spreading distantly. Radiorecurrent PCa metastasis is therefore a significant cause of morbidity and mortality that must be overcome to improve survival of advanced PCa patients. Proteomic analysis revealed the procollagen enzyme Lysyl Hydroxylase 2 (PLOD2) to be upregulated in our radiorecurrent, and highly aggressive, conventionally fractionated DU145 (DU145-CF) PCa cell line. Given its established function as a mediator of invasion in various other cancers, we sought to characterize the role of PLOD2 in the aggressive phenotype of our radiorecurrent PCa cells. Bioinformatic analysis of clinical data revealed PLOD2 genomic amplification to be significantly associated with biochemical recurrence in PCa patients. Upon further examination in vitro, it was revealed that PLOD2 knockdown significantly reduces matrigel invasion and migration in our radiorecurrent DU145-CF cell line, in addition to numerous other PCa cell lines, including primary cells we derived directly from PCa patients. Using the in vivo chick Chorioallantoic Membrane (CAM) model, we confirmed that PLOD2 knockdown significantly reduces the ability of DU145-CF cells to extravasate from the CAM vasculature into the surrounding stroma, a critical step of the metastatic cascade. To explore mechanisms of metastatic cellular reprogramming downstream of PLOD2, RNA sequencing of DU145-CF cells was conducted; a total of 681 genes were discovered to be dysregulated by PLOD2 knockdown, with their functional analysis suggesting changes in cellular metabolism and respiration. Finally, since PLOD2 is known to be regulated by hypoxia-induced protein HIF1α, we explored whether PLOD2 expression could be inhibited by the HIF1α inhibitor, PX-478. Treatment with PX-478 reduced both HIF1α and PLOD2 protein expression, and significantly reduced invasion, migration, and in vivo extravasation in DU145-CF cells, thereby indicating its potential as a pharmacological inhibitor of HIF1α-associated PLOD2 in radiorecurrent PCa. Together, our results demonstrate for the first time the role of PLOD2 in radiorecurrent PCa invasiveness, and point towards its potential as a therapeutic target to reduce metastasis and improve survival outcomes in PCa patients. Citation Format: Gavin Frame, Hon Leong, Roni Haas, Xiaoyong Huang, Jessica Wright, Paul C. Boutros, Thomas Kislinger, Stanley K. Liu. Investigating PLOD2 as a therapeutic target to overcome metastasis in radiorecurrent prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1274.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.156
GPT teacher head0.485
Teacher spread0.328 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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