HPB P01 Volatile Organic Compounds for the Detection of Hepatocellular Carcinoma – a Scoping Review
Bibliographic record
Abstract
Abstract Background Hepatocellular carcinoma (HCC) is an increasingly common disease and is classified as one of the most common cancers leading to mortality worldwide. Only a small percentage of patients with this disease are eligible to curative treatment. Quite often the main reason is the late diagnosis of the disease. In the last decade, a Nobel prize awarded discovery of the volatile organic compounds in the breath opened the frontiers for new diagnostic tools and methods for several diseases. Cancer is one of the target diseases that appears to have unique biomarkers in the breath of the affected individuals. This have been found true in colorectal, breast, lung cancers. This systematic review aims to answer the question if markers specific to hepatocellular carcinoma exist in exhaled breath and what is the current knowledge regarding its detection. Methods A systematic search was conducted by two reviewers and the Royal College of Surgeons of Edinburgh librarian using the Embase, Medline, PubMed and Web od Science databases. Search strategy included all studied published until the 24th of March 2021 containing combination of keywords (Hepatocellular carcinoma, hepatocellular neoplasm, hepatocellular cancer, hepatocellular tumor, hepatocellular tumour, HCC, liver cancer, liver carcinoma, liver neoplasm, liver tumor, liver tumour AND volatile organic compound, VOC, volatilome, volatilomics, metabolome, metabolomics, breath analysis). Results The search yielded 6 publications using PRISMA pathway. Two of the studies described in vitro experiments and four were conducted on a small number of groups of patients. Overall, in the in vitro studies 42 headspace gases were analysed. Clinical studies included 164 patients with HCC and as control groups - 110 patients with cirrhosis and 130 healthy individuals. Multiple VOCs were found in the studies. Following their identification in PubChem library, a pathway analysis was performed using the Kyoto Encyclopaedia of Genes and Genomes (KEGG). Only three VOCs were annotated in the KEGG maps and out of those, two could be traced back to their biological pathways. These are acetaldehyde and ethanol which participate in glycolysis and gluconeogenesis (Figure 1). Conclusions At present time there are no specific volatile biomarker in exhaled breath characterising hepatocellular carcinoma. Data on extracted studies emphasised lack of unified methodology. This review, however, highlighted metabolic pathway which might be the source of VOCs produced by cancerous hepatocytes. Large population studies are required to verify this finding.
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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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".