ArticleInternational journal of nanomedicine2012
The scent fingerprint of hepatocarcinoma: in-vitro metastasis prediction with volatile organic compounds (VOCs).
Article in International journal of nanomedicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 27 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
The Diagnostic Power of VOCs Compared With CTCs for Cancer
Diagnosing Cancers From Healthy From Human Exhaled Breath With Na-nose
Who cites it
27 citing papers in PubMed, 81 citations in OpenAlex.
- Volatile organic compounds for the detection of hepatocellular carcinoma-A scoping review.iLIVER · 2024Review
- Diagnosis of Carcinogenic Pathologies through Breath Biomarkers: Present and Future Trends.Biomedicines · 2023Review
- Methanethiol: A Scent Mark of Dysregulated Sulfur Metabolism in Cancer.Antioxidants (Basel, Switzerland) · 2023Review
- Novel breath biomarkers identification for early detection of hepatocellular carcinoma and cirrhosis using ML tools and GCMS.PloS one · 2023Article
- Highly Adsorptive Au-TiOACS applied materials & interfaces · 2022Article
- Artificially Intelligent Nanoarray Detects Various Cancers by Liquid Biopsy of Volatile Markers.Advanced healthcare materials · 2022Article
- Exhaled volatile organic compounds for diagnosis of hepatocellular carcinoma.Scientific reports · 2022Article
- Volatolomics in healthcare and its advanced detection technology.Nano research · 2022Review
- Raman Spectroscopy: A Novel Technology for Gastric Cancer Diagnosis.Frontiers in bioengineering and biotechnology · 2022Review
- Exploratory Study Using Urinary Volatile Organic Compounds for the Detection of Hepatocellular Carcinoma.Molecules (Basel, Switzerland) · 2021Article
- Breath analysis based early gastric cancer classification from deep stacked sparse autoencoder neural network.Scientific reports · 2021Article
- Quantitative Measures of Reliability and Sensitivity of Nanoparticle-Based Sensors in Detecting Volatile Organic Compounds.ACS omega · 2019Article
- Review and Comparison of Cancer Biomarker Trends in Urine as a Basis for New Diagnostic Pathways.Cancers · 2019Review
- Profiling Single Cancer Cells with Volatolomics Approach.iScience · 2019Article
- Carbon Nanotube Chemical Sensors.Chemical reviews · 2019Review
- Pilot Study: Detection of Gastric Cancer From Exhaled Air Analyzed With an Electronic Nose in Chinese Patients.Surgical innovation · 2018Article
- A Prediction Model with a Combination of Variables for Diagnosis of Lung Cancer.Medical science monitor : international medical journal of experimental and clinical research · 2017Article
- Volatile metabolomic signature of human breast cancer cell lines.Scientific reports · 2017Article
- Loss of protocadherin-17 (PCDH-17) promotes metastasis and invasion through hyperactivation of EGFR/MEK/ERK signaling pathway in hepatocellular carcinoma.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2016Article
- Investigation of VOCs associated with different characteristics of breast cancer cells.Scientific reports · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHepatocellular carcinoma (HCC) is a common and aggressive form of cancer. Due to a high rate of postoperative recurrence, the prognosis for HCC is poor. Subclinical metastasis is the major cause of tumor recurrence and patient mortality. Currently, there is no reliable prognostic method of invasion.
aimTo investigate the feasibility of fingerprints of volatile organic compounds (VOCs) for the in-vitro prediction of metastasis.
methodsHeadspace gases were collected from 36 cell cultures (HCC with high and low metastatic potential and normal cells) and analyzed using nanomaterial-based sensors. Predictive models were built by employing discriminant factor analysis pattern recognition, and the classification success was determined using leave-one-out cross-validation. The chemical composition of each headspace sample was studied using gas chromatography coupled with mass spectrometry (GC-MS).
resultsExcellent discrimination was achieved using the nanomaterial-based sensors between (i) all HCC and normal controls; (ii) low metastatic HCC and normal controls; (iii) high metastatic HCC and normal controls; and (iv) high and low HCC. Several HCC-related VOCs that could be associated with biochemical cellular processes were identified through GC-MS analysis.
conclusionThe presented results constitute a proof-of-concept for the in-vitro prediction of the metastatic potential of HCC from VOC fingerprints using nanotechnology. Further studies on a larger number of more diverse cell cultures are needed to evaluate the robustness of the VOC patterns. These findings could benefit the development of a fast and potentially inexpensive laboratory test for subclinical HCC metastasis.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.