Lung cancer biomarkers for the assessment of modified risk tobacco products: an oxidative stress perspective

Figures & data

Table 1. IOM candidate biomarkers for lung cancer.

Category and variables	Dose–response data	Associated with cessation or half-life	Target tissue assay available	Chemical specificity	Specific to tobacco	Related to a disease risk	Limitations	Strengths
Enzymatic induction
Aryl hydrocarbon hydroxylase	No	>30 d	Yes	Yes	No	Yes	Technically difficult to assess in large epidemiological studies.	Indicates acquired changes in susceptibility; related to DNA adduct levels.
CYP1A2	No	NDA	Yes	Yes	No	Yes	Technically difficult to assess in large epidemiological studies.	Indicates acquired changes in susceptibility; related to DNA adduct levels.
DNA repair enzymes	NDA	Yes	Yes	NA	No	NDA	Technically difficult.	Indicates acquired changes in susceptibility; provides analysis of what is likely to be critical part of carcinogenesis.
Microarray assays for mRNA   expression and proteomics	NDA	NDA	Yes	NA	No	NDA	Difficult to perform; relationship to disease risk is technically difficult to prove; requires extensive laboratory validation; RNA and protein microarray assays are expensive; large-scale studies are needed; refined bioinformatic analysis required.	Reflects integrated measure of multiple genotypes, provides complex data potentially usable for rapid identification of important risk factors.
Chromosomal alterations
Chromosomal aberrations	Yes	Yes	Yes	No	No	Yes	Very non-specific; relationship to target organ is not established; lack of specificity and wide overlap between smokers and non-smokers.	Can be done in blood as surrogate tissue. Similar lesions observed in cancer. Can be measured in persons without cancer.
Micronuclei	Yes	Yes	Yes	No	No	NDA	Lack of specificity.	Facile assay.
Sister chromatid exchanges	Yes	Yes	No	No	No	No	Very non-specific; relationship to target organ is not established; predictivity for disease risk not established. Association with cancer in case-control studies may have case bias. Wide overlap between smokers and non-smokers.	Easy to do in blood as surrogate tissue. Can be measured in people without cancer.
Loss of heterozygosity	Yes	Yes	Yes	No	No	NDA	Technically complex; relationship to cancer risk unknown.	Similar lesions observed in cancer.
Mutations in reporter genes   (HPRT1, GYPA)	Yes	Yes	No	No	No	NDA	Relationship to target tissue or blood unknown.	Facile assay in blood.
Mutational load in target genes   (TP53, KRAS)	NA	NDA	Yes	No	No	NDA	Very difficult to do in normal tissues.	Target gene specificity.
Mitochondrial mutations
Deletions, insertions	NDA	NDA	Yes	No	No	NDA	Relationship to disease not established.	Provides corroborative marker.
Epigenetic cancer effects
Whole genome methylation	NDA	NDA	Yes	No	No	No	Relationship to disease unknown.	Facile assay.
Hypermethylation of promoter regions	NDA	NDA	Yes	No	No	No	Technically difficult; relationship to risk unknown.	Similar lesions observed in cancers.

NDA = no data available.

mRNA = messenger RNA.

NA = not applicable.

Table 2. LSRO candidate biomarkers for lung cancer.

Disease/biological process	Primary biomarker^a	Secondary biomarker^b	Tertiary biomarker^c
Cytopathological changes	Squamous cell dysplasia	Hyperplasia and metaplasia for SCC, cytology and pathology (sputum, forceps and brush biopsy) for other histological tumour types, spiral CT	–
Genetic damage	–	Chromosomal aberration, micronuclei, aneuploidy, loss of heterozygosity, acquired genetic effects to specific targets, DNA adducts, urine mutagenicity	Gene array technologies
Epigenetic alterations	–	DNA methylation	–
Inflammation	–	–	Inflammatory markers in respiratory tract fluids or tissues
Oxidative stress	–	Oxidatively generated DNA products	Isoprostanes
Protein changes	–	Abnormal or elevated protein concentrations, inactivated or activated proteins/enzymes/receptors, protein adducts	Proteomic technologies

^aLinked to clinical outcomes with strong evidence.

^bSecondary biomarkers have been linked to clinical outcomes with moderate evidence.

^cTertiary biomarkers have been linked to clinical outcomes with preliminary evidence.

SCC = squamous cell carcinoma.

CT = computer tomography.

Table 3. Cancer-related biomarkers reported by Hatsukami et al. (2006).

		Relation to tobacco product use
Biomarker	Measurement	Difference: users versus non-users	Change with cessation	Dose response with use	Change with reduced use
Chemical biomarkers
NNAL and NNAL glucuronides	Carcinogen (NNK) uptake	Yes	Yes	Yes	Yes
3-Aminobiphenyl, 4-aminobiphenyl and other  aromatic amine haemoglobin adducts	Carcinogen (aromatic amines) uptake plus metabolic activation	Yes	Yes	–	Yes
1-Hydroxypyrene in urine	Carcinogen (PAH) uptake	Yes	Yes		Yes
Trans, trans-muconic acid in urine	Carcinogen (benzene) uptake	Yes	–	–	–
S-phenylmercapturic acid	Carcinogen (benzene) uptake	Yes	–	–	–
Benzene and other volatile organic carcinogens in exhaled air	Volatile organic carcinogens	Yes	–	Yes	–
Ethylene oxide haemoglobin adducts	Carcinogen (ethylene oxide) uptake	Yes	–	–	–
Other N-terminal valine adducts in haemoglobin	Carcinogen uptake	Yes	–	–	–
Cadmium and other metals in blood and urine	Carcinogen uptake	In part^a	–	–	–
Acetaldehyde-DNA and protein adducts	Carcinogen uptake	–	–	–	–
F2-isoprostanes and oxidised proteins	Oxidatively generated damage, inflammation^c	Yes	–	–	–
8-Oxoguanine or 8-hydroxy-deoxyguanosine in DNA or urine^b	Oxidatively generated damage, inflammation^c	In part	–	–	–
Mercapturic acids of acrolein and related compounds in urine	Toxin uptake and metabolism	In part	–	–	–
Benzo(a)pyrene diol epoxide-DNA and haemoglobin adducts	Carcinogen (benzo[a]pyrene) uptake and metabolic activation	In part	–	–	–
NNK and NNN-DNA and haemoglobin adducts	Carcinogen (NNK/NNN) uptake and metabolic activation	In part	–	–	–
Apurinic sites in DNA	DNA damage	–	–	–	–
^32P-post-labelling of DNA	Carcinogen uptake and metabolic activation	Yes	Yes	–	–
Immunoassays for DNA damage	Carcinogen (mainly PAH) uptake and metabolic activation	Yes	Yes	–	–
Cellular biomarkers
Urine mutagenicity	Mutagen uptake	Yes	Yes	Yes	Yes
Sister chromatid exchange in peripheral lymphocytes	DNA damage	Yes	Yes	Yes	–
Chromosomal aberrations and micronuclei  frequency in lymphocytes	DNA damage	In part	–	–	–
Hypoxanthine-guanine phosphoribosyltransferase mutant frequency in cultured lymphocytes	Gene mutations	In part	–	–	–
Bronchial metaplasia and dysplasia, sputum atypia	Preneoplastic changes	In part	In part	–	–
Comet assay-DNA strand breaks	DNA damage	No consistent effect	–	–	–
Proteome differences	Effects on proteins	–	–	–	–
Promoter methylation	Effects on gene expression	–	–	–	–
Carcinoembryonic antigen	Inflammation^c	In part	–	–	–

^aSome studies support change in biomarkers by smoking status.

^bPublished values may be unreliable owing to unrecognised artefact formation.

^cUncertainty exists over whether the biomarker is a measurement of inflammation.

NNAL = 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol.

NNK = 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone.

NNN = N-nitrosonornicotine.

PAH = polycyclic aromatic hydrocarbons.

Table 4. Concentrations of F₂-isoprostanes in biofluids from groups of smokers and non-smokers.

			F2-isoprostane concentration
Study	Biomatrix	Number of people	Smokers	Non-smokers
Keaney et al. (2003)	Urine	2828	240 ± 145 ng/mmol creatinine	148 ± 100 ng/mmol creatinine
Liang et al. (2003)	Urine	60	530 ± 370 ng/mmol creatinine	250 ± 150 ng/mmol creatinine
Oguogho et al. (2000)	Urine	14	65 ± 16 ng/mmol creatinine	25 ± 5 ng/mmol creatinine
Harman et al. (2003)	Urine	138	124 ± 11 ng/mmol creatinine	58 ± 5 ng/mmol creatinine
Lowe et al. (2009)	Urine	20	1.04 ± 0.36 μg/mmol creatinine	0.61 ± 0.21 μg/mmol creatinine
Zedler et al. (2006)	Urine	115	Median 1.94 (range 0.69–4.61) μg/mmol creatinine	Median 1.03 (range 0.58–2.17) μg/mmol creatinine
Montuschi et al. (2000)	Exhaled breath condensate	10	24.3 ± 2.6 pg/ml	10.8 ± 0.8 pg/ml
Borrill et al. (2008)	Exhaled breath condensate	28	49.9 ± 2.9 pg/ml	8.9 ± 4.0 pg/ml
Reilly et al. (1996)	Urine	10	176.5 ± 31.0 pmol/mmol creatinine^a
Reilly et al. (1996)	Urine	10	92.7 ± 5.0 pmol/mmol creatinine^b
Morrow et al. (1995)	Plasma (free)	10	250 ± 156 pmol/l	156 ± 67 pmol/l^c
Morrow et al. (1995)	Plasma (esterified)	10	469 ± 108 pmol/l	624 ± 214 pmol/l
Frost-Pineda et al. (2011)	Urine	1044 non-smokers 3322 smokers	1890 ± 1053 ng/24 h	1331 ± 754 ng/24 h^d

All data are statistically significant (p < 0.05) and are presented as mean ± SD unless stated otherwise.

^aHeavy smokers.

^bModerate smokers.

^cAfter 2 weeks’ abstinence.

^dp < 0.0001.

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