Abstract 2003: Targeting the human adrenomenulin 2 hormone inhibits cancer cell intravasation
Bibliographic record
Abstract
Abstract Cancer cell intravasation is the crucial step of cancer metastasis, and no therapeutic agents thattarget this process exist. Our laboratory uses high-resolution multidimensional intravital confocalimaging to visualize intratumoral cancer cell invasion and metastasis. Using this techniquecombined with fluorescent reporters, we discovered that in the live tumours, cancer cells withelevated ATF2 transcription factor (ATF+) are lining up the intratumoral vasculature, activelyinvading the perivascular space and responsible for 100% of cancer cell intravasation events. Incontrast, cancer cells low in ATF2 activity (ATF2-) fail to interact with the intratumoralvasculature and do not intravasate. Most cancer cell intravasation events occur in the large(∼50µm) veins deep within the tumour mass (intravasation ports). Isolation of ATF2+ and ATF2-cells followed by their comparative RNAseq analysis revealed that ADM2 (Adrenomennulin 2)peptide hormone is significantly (∼3x) overexpressed in ATF2+ compared to ATF2- tumour cells.shRNA-mediated knockdown of ADM2 expression in cancer cells decreased ATF2 activity, revealing a possible positive feedback loop. We found that shRNA knockdown of ADM2expression drastically inhibited the intratumoral cancer cell invasion and formation of the sizeableintratumoral vasculature. Notably, cancer cells deficient in ADM2 expression fail to invadeintratumoral perivascular space and intravasate. Our findings reveal Adrennomenulin 2 as a noveland potent anti-cancer metastasis target that can specifically inhibit cancer cell intravasation. Citation Format: Seyedeh Sara Karimian, John Lewis, Konstantin Stoletov. Targeting the human adrenomenulin 2 hormone inhibits cancer cell intravasation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2003.
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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".