Targeting of Adhesion Molecules as a Therapeutic Strategy in Multiple Myeloma
Bibliographic record
Abstract
Multiple myeloma (MM) is a clonal disorder of plasma cells that remains, for the most part, incurable despite the advent of several novel therapeutic agents. Tumor cells in this disease are cradled within the bone marrow (BM) microenvironment by an array of adhesive interactions between the BM cellular residents, the surrounding extracellular matrix (ECM) components such as fibronectin (FN), laminin, vascular cell adhesion molecule-1 (VCAM-1), proteoglycans, collagens and hyaluronan, and a variety of adhesion molecules on the surface of MM cells including integrins, hyaluronan receptors (CD44 and RHAMM) and heparan sulfate proteoglycans. Several signaling responses are activated by these interactions, affecting the survival, proliferation and migration of MM cells. An important consequence of these direct adhesive interactions between the BM/ECM and MM cells is the development of drug resistance. This phenomenon is termed ‘‘cell adhesion-mediated drug resistance’’ (CAM-DR) and it is thought to be one of the major mechanisms by which MM cells escape the cytotoxic effects of therapeutic agents. This review will focus on the adhesion molecules involved in the cross-talk between MM cells and components of the BM microenvironment. The complex signaling networks downstream of these adhesive molecules mediated by direct ligand binding or inside-out soluble factors signaling will also be reviewed. Finally, novel therapeutic strategies targeting these molecules will be discussed. Identification of the mediators of MM-BM interaction is essential to understand MM biology and to elucidate novel therapeutic targets for this disease. Keywords: Adhesion, integrins, anti-adhesion agents, CAM-DR, microenvironment, multiple myeloma, Antibody-dependent cellular cytotoxicity, basic fibroblast growth factor, Fas-associated death domain-containing protein, Integrin linked kinase, Lymphocyte function-associated antigen 1, Monocyte chemoattractant protein 1, P-selectin Glycoprotein Ligand-1, Bone marrow microvascular density, Unfolded protein response.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".