Bibliographic record
Abstract
Dysregulation of lipid metabolism has recently emerged as a hallmark of cancer (Beloribi-Djefaflia S), as well as alterations of the lipid profile in head and neck cancer. Liang J, et al describe in their review on lipid metabolism reprogramming and its potential therapeutic targets in head and neck cancer (Liang J). Figure 1 demonstrates the most important enzymes involved in lipid metabolism in head and neck cancer showing the elevated level of uptake and synthesis of various fatty acids and sterol lipids in cancer cells. 2 lists the potential lipid metabolism-related therapeutic targets, mostly overexpressed enzymes of different fatty acid synthases. They also highlighted the deteriorating effects of prolonged consumption of tobacco, alcohol, and high-fat diets on healthy cells.Non-small cell lung cancer (NSCLC) accounts for most lung cancer histological types, which mainly include squamous cell carcinoma and adenocarcinoma, and a poor survival rate. Wang Z, et al detail in their review about Aryl hydrocarbon receptor (AhR), which is a ligandactivated nuclear transcription factor. AhR overexpression helps tumor cells evade the immune system by sending inhibitory signals to the immune cells through the tumor microenvironment (Sadik A). Figure 1 highlights the clinical applications of metabolic reprogramming in tumors. In Figure 2, the authors revealed that AhR elevation correlates with increased glycolysis in cancer cells. In conclusion, they suggest that AhR is crucial in the regulation of cellular metabolism, especially in tumor metabolic reprogramming.Challenges in cancer treatment are metastasis, chemoresistance, and disease relapse; cancer stem cells (CSC) are known to be related to these phenomena. Wang and colleagues reviewed the impact of studying the cancer stem cells (CSCs) for cancer treatment (Wang H). CSCs can renew themselves, differentiate, and form new tumors, characteristics related to drug resistance, recurrence, and the spread of cancer cells to other parts of the body. Thus, targeting CSCs presents an opportunity for cancer treatment. They also delved into the changes observed in iron metabolism, lipid peroxidation, and the removal of lipid peroxides in CSCs, exploring their implications on ferroptosis. This research investigates the mechanisms governing iron metabolism and ferroptosis regulation in CSCs, extending the discussion to potential treatment tactics and new compounds that target CSCs by promoting ferroptosis.It is well-documented how tumors satisfy their energy, biosynthesis, and redox requirements by undergoing metabolic reprogramming, resulting in an increased lactate level and other metabolites in the tumor microenvironment. According to Xu and colleagues, lactate and lactylation mediate the reprogramming of immune cells and cellular adaptability to enhanced immunosuppression within the tumor microenvironment in hepatocellular carcinoma (HCC) (Xu Y). The alteration of glucose metabolism and the Warburg effect in HCC leads to significant lactate production and accumulation, suggesting abnormal lactate modification in tumor tissue. In this context, Xu reviewed the immune regulation of atypical lactate metabolism and lactate modification in hepatocellular carcinoma and the therapeutic approach of lactate-immunotherapy targeting, aiming to improve guidance for medication and treatment of patients with hepatocellular carcinoma.One of the main problems of monotherapies is chemoresistance. A strategy to target different hallmarks of the cancer cell simultaneously could be an appropriate approach to stop drug resistance, metastasis, and disease recurrence. In leukemia, despite the efforts in drug development, chemoresistance is still of concern with the current chemotherapies, reducing the success of a complete recuperation, especially in elderly patients. Feng, et al, introduced in their review the term "mitotherapy" and emphasized the importance of disordered mitochondrial metabolism and metabolic reprogramming as a therapeutic strategy in leukemia treatment, particularly in addressing chemoresistance (Feng L).In summary, the reviews within this special issue discussed some metabolic alterations observed in cancer cells, highlighting the significance of understanding cancer metabolism for developing targeted therapies and improving patient outcomes. Studies on lipid, iron, and lactate metabolism, and their roles in chemoresistance, as well as the exploration of mitochondria-dependent metabolic reprogramming in addressing chemoresistance, offer valuable insights into potential treatment strategies. By targeting specific metabolic pathways and identifying metabolic vulnerabilities, there is potential for innovative therapeutic approaches in cancer treatment.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.011 | 0.010 |
| Insufficient payload (model declined to judge) | 0.065 | 0.054 |
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".