GPCRs, at the Crossroad of Distortions in Extracellular Microenvironment and Intracellular Energetics Homeostasis, a New Model for 21st Century Cancer Therapeutics
Bibliographic record
Abstract
G-protein coupled receptors (GPCRs) have evolved in complexity and are most widely used by metazoan for essential physiological functions. They are involved in mechanisms that allow cells to receive signals from their environment and react to them. Nearly 20% of human tumors harbor mutations in GPCRs and aberrant expression and activity of G proteins and G-protein-coupled receptors are frequently associated with tumorigenesis. In this article, we review and discuss the roles of GPCRs in normal and neoplastic transformation. This could be looked upon the crossroad of distortions in extracellular microenvironment and intracellular energetics landscape homeostasis. We hypothesize that GPCRs have taken over the role of sensing cellular energetics status and are involved in regulation of signal transduction and gene expression. We also present evolutionary biology perspectives lending further support to the above mentioned notions. We propose that however complex and intricate these pathways and interactions seem, they are all guided by one elegant and simple law, namely keeping the network entropy of the cell at the minimum possible level which correlates inversely with its free energy. Cancer cells are in abnormal state(s) characterized by dysregulated energetics. Based on this view of malignant transformation, further studies and measurements of cellular energetics landscape in both normal cell and its malignant counterpart and mathematical modeling could open the way for future cancer therapeutics strategies. We propose that our future cancer treatment strategies should target conversion rather than destruction of the malignant cell which is the current dominant theme of cancer therapy that has faced insurmountable barriers as evidenced by the short and limited survivorship of patients diagnosed with advanced malignant disorders.Keywords: G-protein coupled receptors, evolution, cancer, multicellular unit, environment, network entropy, free energy
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".