Immunometabolic factors contributing to obesity-linked hepatocellular carcinoma
Bibliographic record
Abstract
Hepatocellular carcinoma (HCC) is a major public health concern that is promoted by obesity and associated liver complications. Onset and progression of HCC in obesity is a multifactorial process involving complex interactions between the metabolic and immune system, in which chronic liver damage resulting from metabolic and inflammatory insults trigger carcinogenesis-promoting gene mutations and tumor metabolism. Moreover, cell growth and proliferation of the cancerous cell, after initiation, requires interactions between various immunological and metabolic pathways that provide stress defense of the cancer cell as well as strategic cell death escape mechanisms. The heterogenic nature of HCC in addition to the various metabolic risk factors underlying HCC development have led researchers to focus on examining metabolic pathways that may contribute to HCC development. In obesity-linked HCC, oncogene-induced modifications and metabolic pathways have been identified to support anabolic demands of the growing HCC cells and combat the concomitant cell stress, coinciding with altered utilization of signaling pathways and metabolic fuels involved in glucose metabolism, macromolecule synthesis, stress defense, and redox homeostasis. In this review, we discuss metabolic insults that can underlie the transition from steatosis to steatohepatitis and from steatohepatitis to HCC as well as aberrantly regulated immunometabolic pathways that enable cancer cells to survive and proliferate in the tumor microenvironment. We also discuss therapeutic modalities targeted at HCC prevention and regression. A full understanding of HCC-associated immunometabolic changes in obesity may contribute to clinical treatments that effectively target cancer metabolism.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".