Abstract 156: Screening and characterization of inhibitors of G-protein coupled receptor kinase GRK6 as potential therapeutics for multiple myeloma
Bibliographic record
Abstract
Abstract Multiple myeloma (MM) is one of the most common hematological malignancies, but current therapy options are limited to high-dose chemotherapy or high-risk stem-cell transplantation. It is clear that the development of more selective and less toxic treatments for MM is greatly needed. In a recent kinome-wide RNAi study by Tiedemann and colleagues (2010), the G-protein coupled receptor kinase-6 (GRK6) was identified as a critical kinase required for survival of MM cells. This study also suggests that MM cells, but not other cell types, are dependent on GRK6; and that gene silencing by shRNA or siRNA of GRK6, but not other GRKs, results in decreased survival. At present, the G-protein coupled receptor (GPCR) signaling mediated by GRK6 in MM cells is not well understood. Our current research aims to identify the important GPCRs phosphorylated by GRK6 and the signaling proteins/pathways implicated in survival of multiple myeloma cells. Through gene silencing techniques and expression of either the wild-type or kinase-dead form of GRK6 protein, we have determined that a functional GRK6 kinase domain is required for survival of MM cells. We have also demonstrated that the signaling pathway downstream of CXCR4 phosphorylation by GRK6 is defective in cells expressing the kinase-dead GRK6-mutant protein. This loss of signaling by the GRK6-mutant protein was observed for other GPCRs found to be important for survival of MM cells. These findings helped to validate that the kinase domain of GRK6 is a potential target for MM, and spurred the identification of small molecule kinase inhibitors of GRK6. Compounds with high potency in preliminary biochemical assays were screened against MM and non-MM cell lines to evaluate their activity and specificity in vivo. Small molecule inhibition of GRK6 kinase activity is a novel approach to the treatment of MM, as it specifically targets a protein found to be critical for survival of these cells through an unbiased RNAi study. Treatment options for patients with MM are limited and based on our preliminary findings small molecule inhibitors of GRK6 offer an alternative therapeutic approach to the treatment of MM. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 156. doi:1538-7445.AM2012-156
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".