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MP16-06 EXPLOITING NOVEL THERAPEUTIC TARGETS TO BLOCK METASTASIS OF CLEAR CELL RENAL CELL CARCINOMA (RCC)

2019· article· en· W2940502605 on OpenAlexaboutno aff
Jan K. Rudzinski, Natasha Govindasamy, Konstantin Stoletov, Adrian Fairey, John Lewis

Bibliographic record

VenueThe Journal of Urology · 2019
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRenal cell carcinomaSmall hairpin RNAMetastasisCancer researchClear cell renal cell carcinomaCellCancerKidney cancerCell culturePathologyInternal medicineBiologyGene knockdownGenetics

Abstract

fetched live from OpenAlex

You have accessJournal of UrologyKidney Cancer: Basic Research & Pathophysiology I (MP16)1 Apr 2019MP16-06 EXPLOITING NOVEL THERAPEUTIC TARGETS TO BLOCK METASTASIS OF CLEAR CELL RENAL CELL CARCINOMA (RCC) Jan Rudzinski*, Natasha Govindasamy, Konstantin Stoletov, Adrian Fairey, and John Lewis Jan Rudzinski*Jan Rudzinski* More articles by this author , Natasha GovindasamyNatasha Govindasamy More articles by this author , Konstantin StoletovKonstantin Stoletov More articles by this author , Adrian FaireyAdrian Fairey More articles by this author , and John LewisJohn Lewis More articles by this author View All Author Informationhttps://doi.org/10.1097/01.JU.0000555342.90934.fcAboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES: Metastatic RCC is incurable, and the current therapeutic paradigm is centered around controlling the disease burden to prolong overall survival. We conducted a whole human genome short hairpin RNA (shRNA) screen on human squamous cell carcinoma (Hep3) cells to identify a panel of novel functional genes that are required for productive cell motility and successful metastatic dissemination. One such novel protein target encodes for chromosome 14 open reading frame 142 (C14orf42), which has been demonstrated to be up regulated in metastatic clear cell RCC. The objective of our study was to characterize the impact of C14orf142 on clear cell RCC in vitro motility, invasion, and in vivo vascular extravasation. METHODS: Benign proximal convoluted tubule cells (PCT) and clear cell RCC cell lines 786-0 (derived from renal tissue) were obtained from American Type Culture Collection (ATCC). Targeted genomic editing to knockout (KO) C14orf142 was achieved with CRISPR-Cas9 system. Successful protein knockdown was validated using western blot analysis. To measure impact of gene KO on in vitro invasion we conducted the FITC-gelatin degradation assay. To measure the combined effect of invasion and productive cell migration in vitro we utilized the modified Boyden chamber assay coated with 0.1% gelatin. To study cancer cell vascular extravasation in vivo, 786-0 cells were injected IV into fertilized avian embryos. For statistical analysis, t-test was used to evaluate differences between groups with p value of ≤0.05 accepted as statistically significant. RESULTS: The baseline expression of C14orf142 was significantly higher in 786-0 (1.078AUD±0.11) compared to PCT(0.12AUD±0.04) (p≤0.05). The CRISPR-Cas9 targeted genomic editing resulted in generation of 786-0 clones with complete KO of C14orf142. The FITC-gelatin degradation assay demonstrated significant difference in gelatin degradation between 786-0 scramble and 786-0 CRISPR KO clones (100% vs 27%±5.56%, respectively, p≤0.05). The modified Boyden chamber assay also showed significant difference in productive cell migration between 786-0 scramble and 786-0 CRISPR KO clones (100% vs 42±3.46%, respectively, p≤0.05). Compared to 786-0 scramble clones, 786-0 CRISPR KO clones demonstrated significant reduction in extravasation on the avian embryo model (100% vs 46.33±8.37%, respectively, p≤0.05). CONCLUSIONS: Up regulation of novel target protein, C14orf142, in 786-0 clear cell RCC cells may play an important role in cancer cell invasion, productive cell migration, and vascular extravasation. Source of Funding: Kidney Cancer Research Network (KCRN); Kidney Cancer Canada (KCC); Canadian Institute of Health Research (CIHR) Edmonton, Canada© 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 201Issue Supplement 4April 2019Page: e207-e208 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information Jan Rudzinski* More articles by this author Natasha Govindasamy More articles by this author Konstantin Stoletov More articles by this author Adrian Fairey More articles by this author John Lewis More articles by this author Expand All Advertisement PDF downloadLoading ...

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 score0.009
Threshold uncertainty score0.030

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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.002

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 head0.027
GPT teacher head0.249
Teacher spread0.222 · 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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