Abstract 1439: Increasing potency of anticancer drugs through SORT1+ technology: A new targeted approach for the treatment of ovarian and endometrial cancers
Bibliographic record
Abstract
Abstract Accumulating evidence suggests a relationship between endometrial cancer and ovarian cancer.Whereas little therapy advances have been made in recent years, precise anticancer drug targeting modalities could be achieve by incorporating a peptide ligand that has the ability to specifically recognize cancer cells. High expression of sortilin (SORT1), a scavenging receptor, was observed in ovarian and endometrial cancers. In light of this, we developed a SORT1-targeted technology to increase both selectivity and efficacy of anticancer drug delivery. Docetaxel was conjugated to a sortilin-binding peptide (TH19P01 peptide). In vitro, high and saturable intracellular delivery of the fluorescent Alexa488-TH19P01 was confirmed in different SORT1+ cancer cell models, whereas internalization was reduced by 70-80% when SORT1 was silenced using siRNA, or by 50-70% upon competition with the SORT1 ligands neurotensin and progranulin. Sortilin expression level was assessed in tissue micro-arrays of biopsies from patients with high grade serous ovarian carcinoma (HGSC), from endometrial cancers, and from healthy tissues. A strong sortilin staining was effectively observed in more than 90% of the tumor biopsies and remained high in those from HGSC patients that received neoadjuvant chemotherapy. Immunoblotting also revealed high levels of SORT1 in a wide variety of human cancer cell lines including ovarian and endometrial cancer cells. In vivo, tumor xenografts were generated from two of the sortilin-expressing ovarian cancer cell lines (ES-2 and SKOV-3/Luc). Administration of TH1902, a docetaxel-TH19P01 conjugate, impeded ES-2 ovarian tumor xenograft growth when administered for three cycles at 35 mg/kg/week, versus unconjugated docetaxel at 15 mg/kg/week. A 78% decrease in tumor growth was observed in TH1902-treated animals, though docetaxel-treated tumor volumes were indistinguishable from either of the other groups. In contrast, administration of either docetaxel or TH1902 completely prevented tumor growth in SKOV-3/Luc ovarian tumor xenografts and even led to tumor regression. When TH1902 and docetaxel were administered to mice bearing AN3-CA endometrial tumor xenografts at an equivalent of docetaxel dose (3.75 mg/kg/week), a decrease in the rate of tumor growth by 73% was apparent in TH1902 group whereas docetaxel lacked any observable effect. In addition, higher equivalent dose of both TH1902 and docetaxel (15 mg/kg/week) inhibited tumor growth, however and in contrast to docetaxel group, TH1902-treated mice showed sustained tumor regression. These results strongly support the clinical development of this SORT1+ technology for both endometrial and ovarian cancers. Citation Format: Michel Demeule, Jean-Christophe Currie, Cyndia Charfi, Alain Larocque, Alain Zgheib, Richard Béliveau, Christian Marsolais, Borhane Annabi. Increasing potency of anticancer drugs through SORT1+ technology: A new targeted approach for the treatment of ovarian and endometrial cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1439.
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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 | 0.001 |
| 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".