Nuclear Location Bias of HCAR1 Drives Cancer Malignancy through Numerous Routes
Bibliographic record
Abstract
Abstract The involvement of G-Protein-Coupled Receptors’ (GPCR) location bias in diverse cellular functions and their misregulation in pathology is an underexplored territory. HCAR1, a GPCR for lactate is linked to cancer progression, mainly due to Warburg effect, but its mechanism of action remains elusive. Here, we show HCAR1 has a nuclear localization, capable of signaling intranuclearly to induce nuclear-ERK and AKT phosphorylation concomitant with higher cancer cell proliferation and survival. We determine its nuclear interactome, proving its involvement in protein-translation and DNA-damage repair. Nuclear HCAR1 (N-HCAR1) directly interacts with chromatin/DNA promoting expression of genes involved in cellular migration. Notably, we show N-HCAR1 particularly regulates a broader transcriptomic signature than its PM counterpart, emphasizing on the facts that functional output of N-HCAR1 is larger than PM localized HCAR1. Our study presents several unprecedented processes by which a GPCR through location-biased activity regulate various cellular functions and how cancer cells exploit these.
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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) | 0.000 | 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 | 0.000 |
| 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".