Abstract 494: Intravital discovery of miRNA drivers of human cancer cell directional invasion
Bibliographic record
Abstract
Abstract Metastatic cancer cells use directional ECM cues such as blood vessels or collagen fibers when invading through live tissue. Oncogenic miRNAs have been implicated as key regulators of cancer progression, yet the systemic discovery of miRNAs that drive directional cancer cell invasion has not been achieved. Here we describe the first in vivo quantitative whole human miRNAome screen for miRNA drivers of directional cancer cell invasion that is based on high-resolution intravital imaging. We identified several novel miRNAs that promote cancer cell invasion during the key rate-limiting step of cancer metastasis: the initiation of overt metastatic lesions. In vivo 4D cancer cell tracking revealed that these prometastatic miRNAs are required for successful invasion into collagen-rich tissue and for attachment to the outer surface of the vascular wall. Deregulation of these miRNAs led to formation of loose contacts with the vasculature and chaotic, nondirectional cancer cell invasion patterns in living tissue. Intravital SHG microscopy showed that inhibition of the expression of these miRNAs blocked the ability of cancer cells to rearrange the disorganized collagen network into collagen fiber bundles and stably protrude along these bundles. Further imaging analysis revealed that this miRNA expression specifically blocks vesicular transport of key cell invasion machinery proteins such as MT1-MMP to the cancer cell invadopodia. Human cancer gene expression database analysis showed that our top miRNA candidates are specifically deregulated in invasive pancreatic cancer. Indeed, intravital imaging analysis showed that blocking of metastatic miRNA function inhibited MT1-MMP secretion and ECM degradation by human pancreatic cancer cells. In summary, we identified a novel panel of human miRNAs that are functionally involved in the regulation of directional invasion and metastasis. This work establishes these miRNAs as promising therapeutic targets to block the metastatic spread of lethal cancers. Citation Format: Konstantin V. Stoletov, Lian Willetts, Juan Jovel, Emma Woolner, John D. Lewis. Intravital discovery of miRNA drivers of human cancer cell directional invasion [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 494.
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 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".