The Circadian Clock Regulates Metabolic Phenotype Rewiring Via HKDC1 and Modulates Tumor Progression and Drug Response in Colorectal Cancer
Bibliographic record
Abstract
An endogenous molecular clockwork drives various cellular pathways including metabolism and the cell cycle. Its dysregulation is able to prompt pathological phenotypes including cancer. Besides dramatic metabolic alterations, cancer cells display severe changes in the clock phenotype with likely consequences in tumor progression and treatment response. In this study, we use a comprehensive systems-driven approach to investigate the effect of clock disruption on metabolic pathways and its impact on drug response in a cellular model of colon cancer progression. We identified distinctive time-related transcriptomic and metabolic features of a primary tumor and its metastatic counterpart. A mapping of the expression data to a comprehensive genome-scale reconstruction of human metabolism allowed for the in-depth functional characterization of 24 h-oscillating transcripts and pointed to a clock-driven metabolic reprogramming in tumorigenesis. In particular, we identified a set of five clock-regulated glycolysis genes, ALDH3A2, ALDOC, HKDC1, PCK2, and PDHB with differential temporal expression patterns. These findings were validated in organoids and in primary fibroblasts isolated from normal colon and colon adenocarcinoma from the same patient. We further identified a reciprocal connection of HKDC1 to the clock in the primary tumor, which is lost in the metastatic cells. Interestingly, a disruption of the core-clock gene BMAL1 impacts on HKDC1 and leads to a time-dependent rewiring of metabolism, namely an increase in glycolytic activity, as well as changes in treatment response. This work provides novel evidence regarding the complex interplay between the circadian clock and metabolic alterations in carcinogenesis and identifies new connections between both systems with pivotal roles in cancer progression and response to therapy.
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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) | 0.000 | 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".