No association between antibodies to sexually transmitted infections and colorectal hyperplastic polyps in men: Minnesota Cancer Prevention Research Unit Polyp Study

Validation of Multiplex Serology for human hepatitis viruses B and C, human T-lymphotropic virus 1 and Toxoplasma gondii

Multiplex Serology is a high-throughput technology developed to simultaneously measure specific serum antibodies against multiple pathogens in one reaction vessel. Serological assays for hepatitis B (HBV) and C (HCV) viruses, human T-lymphotropic virus 1 (HTLV-1) and the protozoan parasite Toxoplasma gondii (T. gondii) were developed and validated against established reference assays. For each pathogen, between 3 and 5 specific antigens were recombinantly expressed as GST-tag fusion proteins in Escherichia coli and tested in Monoplex Serology, i.e. assays restricted to the antigens from one particular pathogen. For each of the four pathogen-specific Monoplex assays, overall seropositivity was defined using two pathogen-specific antigens. In the case of HBV Monoplex Serology, the detection of past natural HBV infection was validated based on two independent reference panels resulting in sensitivities of 92.3% and 93.0%, and specificities of 100% in both panels. Validation of HCV and HTLV-1 Monoplex Serology resulted in sensitivities of 98.0% and 95.0%, and specificities of 96.2% and 100.0%, respectively. The Monoplex Serology assay for T. gondii was validated with a sensitivity of 91.2% and specificity of 92.0%. The developed Monoplex Serology assays largely retained their characteristics when they were included in a multiplex panel (i.e. Multiplex Serology), containing additional antigens from a broad range of other pathogens. Thus HBV, HCV, HTLV-1 and T. gondii Monoplex Serology assays can efficiently be incorporated into Multiplex Serology panels tailored for application in seroepidemiological studies.

Absence of an association of human polyomavirus and papillomavirus infection with lung cancer in China: a nested case-control study

Background

Studies of human polyomavirus (HPyV) infection and lung cancer are limited and those regarding the association of human papillomavirus (HPV) infection and lung cancer have produced inconsistent results.

Methods

We conducted a nested case–control study to assess the association between incident lung cancer of various histologies and evidence of prior infection with HPyVs and HPVs. We selected serum from 183 cases and 217 frequency matched controls from the Yunnan Tin Miner’s Cohort study, which was designed to identify biomarkers for early detection of lung cancer. Using multiplex liquid bead microarray (LBMA) antibody assays, we tested for antibodies to the VP1 structural protein and small T antigen (ST-Ag) of Merkel cell, KI, and WU HPyVs. We also tested for antibodies against HPV L1 structural proteins (high-risk types 16, 18, 31, 33, 52, and 58 and low-risk types 6 and 11) and E6 and E7 oncoproteins (high risk types 16 and 18). Measures of antibody reactivity were log transformed and analyzed using logistic regression.

Results

We found no association between KIV, WUV, and MCV antibody levels and incident lung cancer (P-corrected for multiple comparisons >0.10 for all trend tests). We also found no association with HPV-16, 18, 31, 33, 52, and 58 seropositivity (P-corrected for multiple comparisons >0.05 for all).

Conclusions

Future studies of infectious etiologies of lung cancer should look beyond HPyVs and HPVs as candidate infectious agents.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-016-2381-3) contains supplementary material, which is available to authorized users.

Prior human polyomavirus and papillomavirus infection and incident lung cancer: a nested case-control study

PURPOSE

To test whether infection with select human polyomaviruses (HPyV) and human papillomaviruses (HPV) is associated with incident lung cancer.

METHODS

We performed a nested case-control study, testing serum from the carotene and retinol efficacy trial, conducted 1985-2005, for antibodies to Merkel cell (MCV), KI (KIV), and WU (WUV) HPyVs as well as to six high-risk and two low-risk HPV types. Incident lung cancer cases (n = 200) were frequency-matched with controls (n = 200) on age, enrollment and blood draw dates, intervention arm assignment, and the number of serum freeze/thaw cycles. Sera were tested using multiplex liquid bead microarray antibody assays. We used logistic regression to assess the association between HPyV and HPV antibodies and lung cancer.

RESULTS

There was no evidence of a positive association between levels of MCV, KIV, or WUV antibodies and incident lung cancer (p corrected >0.10 for all trend tests; odds ratio (OR) range 0.72-1.09, p corrected >0.10 for all). There was also no evidence for a positive association between HPV 16 or 18 infection and incident lung cancer (p corrected ≥0.10 for all trend tests; OR range 0.25-2.54, p > 0.05 for all OR > 1), but the number of persons with serologic evidence of these infections was small.

CONCLUSIONS

Prior infection with any of several types of HPyV or HPV was not associated with subsequent diagnosis of lung cancer. Infection with these viruses likely does not influence a person's risk of lung cancer in Western smoking populations.

Analysis of liquid bead microarray antibody assay data for epidemiologic studies of pathogen-cancer associations

BACKGROUND

Liquid bead microarray antibody (LBMA) assays are used to assess pathogen-cancer associations. However, studies analyze LBMA data differently, limiting comparability.

METHODS

We generated 10,000 Monte Carlo-type simulations of log-normal antibody distributions (exposure) with 200 cases and 200 controls (outcome). We estimated type I error rates, statistical power, and bias associated with t-tests, logistic regression with a linear exposure and with the exposure dichotomized at 200 units, 400 units, the mean among controls plus two standard deviations, and the value corresponding to the optimal sensitivity and specificity. We also applied these models, and data visualizations (kernel density plots, receiver operating characteristic (ROC) curves, predicted probability plots, and Q-Q plots), to two empirical datasets to assess the consistency of the exposure-outcome relationship.

RESULTS

All strategies had acceptable type I error rates (0.03 ≤ P ≤ 0.048), except for the dichotomization according to optimal sensitivity and specificity, which had a type I error rate of 0.27. Among the remaining methods, logistic regression with a linear predictor (Power=1.00) and t-tests (Power=1.00) had the highest power to detect a mean difference of 1.0 MFI (median fluorescence intensity) on the log scale and were unbiased. Dichotomization methods upwardly biased the risk estimates.

CONCLUSION

These results indicate that logistic regression with linear predictors and unpaired t-tests are superior to logistic regression with dichotomized predictors for assessing disease associations with LBMA data. Logistic regression with continuous linear predictors and t-tests are preferable to commonly used LBMA dichotomization methods.

Carcinogenic viruses and solid cancers without sufficient evidence of causal association

Viral infections are important risk factors for tumor development in humans. Selected types of cancers, either lymphomas or carcinomas, for which there is sufficient evidence in humans of a causal association with specific viruses, have been identified. Experimental and clinical data on the possible association of other tumor types and carcinogenic viruses are presently controversial. In this article, we review the current evidence on the relationship between breast, colorectal and lung cancers and carcinogenic viruses. The majority of the publications reviewed do not provide definitive evidence that the viruses studied are associated with breast, colon and lung cancers. However, since this association may be clinically relevant for some tumor subtypes (i.e., lung cancer and papillomaviruses), there is an urgent need for further investigation on this topic. Using innovative laboratory techniques for viral detection on well-defined tumor types, National and International networks against cancer should encourage and organize concerted research programs on viruses and solid cancer association.