Lake, A., Novak, P., Fisher, C., Jackson, J., Hardwick, R., Billheimer, D., Klimecki, W., & Cherrington, N. (2011). Analysis of Global and ADME Gene Expression In the Progressive Stages of Human Non-Alcoholic Fatty Liver Disease. Drug Metab Dispos, 39(10), 1954-1960.
Lafleur, B., Lee, W., Billhiemer, D., Lockhart, C., Liu, J., & Merchant, N. (2011). Statistical methods for assays with limits of detection: Serum bile acid as a differentiator between patients with normal colons, adenomas, and colorectal cancer. Journal of Carcinogenesis, 10.
PMID: 21712958;PMCID: PMC3122101;Abstract:
In analytic chemistry a detection limit (DL) is the lowest measurable amount of an analyte that can be distinguished from a blank; many biomedical measurement technologies exhibit this property. From a statistical perspective, these data present inferential challenges because instead of precise measures, one only has information that the value is somewhere between 0 and the DL (below detection limit, BDL). Substitution of BDL values, with 0 or the DL can lead to biased parameter estimates and a loss of statistical power. Statistical methods that make adjustments when dealing with these types of data, often called left-censored data, are available in many commercial statistical packages. Despite this availability, the use of these methods is still not widespread in biomedical literature. We have reviewed the statistical approaches of dealing with BDL values, and used simulations to examine the performance of the commonly used substitution methods and the most widely available statistical methods. We have illustrated these methods using a study undertaken at the Vanderbilt-Ingram Cancer Center, to examine the serum bile acid levels in patients with colorectal cancer and adenoma. We have found that the modern methods for BDL values identify disease-related differences that are often missed, with statistically naive approaches.
Huang, S., Chengcheng, H., Bell, M., Billheimer, D., Guerra, S., Roe, D., Monica, V., & Bedrick, E. (2018). Regularized Continuous-Time Markov Model via Elastic Net. Biometrics.
BIO5 Collaborators
Dean Billheimer, Stefano Guerra, Chengcheng Hu
Pulko, V., Davies, J. S., Martinez, C., Lanteri, M. C., Busch, M. P., Diamond, M. S., Knox, K., Bush, E. C., Sims, P. A., Sinari, S., Billheimer, D., Haddad, E. K., Murray, K. O., Wertheimer, A. M., & Nikolich-Žugich, J. (2016). Human memory T cells with a naive phenotype accumulate with aging and respond to persistent viruses. Nature immunology, 17(8), 966-75.
The number of naive T cells decreases and susceptibility to new microbial infections increases with age. Here we describe a previously unknown subset of phenotypically naive human CD8(+) T cells that rapidly secreted multiple cytokines in response to persistent viral antigens but differed transcriptionally from memory and effector T cells. The frequency of these CD8(+) T cells, called 'memory T cells with a naive phenotype' (TMNP cells), increased with age and after severe acute infection and inversely correlated with the residual capacity of the immune system to respond to new infections with age. CD8(+) TMNP cells represent a potential new target for the immunotherapy of persistent infections and should be accounted for and subtracted from the naive pool if truly naive T cells are needed to respond to antigens.
Li, J., Xu, B. J., Shakhtour, B., Deane, N., Merchant, N., Heslin, M. J., Washington, K., Coffey, R. J., Beauchamp, R. D., Shyr, Y., & Billheimer, D. (2007). Variability of in situ proteomic profiling and implications for study design in colorectal tumors. International Journal of Oncology, 31(1), 103-111.
PMID: 17549410;Abstract:
Knowledge of intrinsic tumor heterogeneity is vital for understanding of tumor progression mechanisms as well as for providing efficient treatments. In situ proteomic profiling of tumors is a powerful technology with potential to enhance our understanding of tumor biology, but sources of variability due to patient and tumor heterogeneity are poorly understood and are the topic of this investigation. Clarification of variability within case and between cases is also important for designing future studies. Direct protein profiling by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a sensitive and powerful technology for obtaining hundreds of protein expression peaks from a thin tissue section. By combining robotic microspotting and laser capture microdissection with MALDI MS, we acquired multiple spectra per case to evaluate inter- and intra-case variability in human colorectal tumor and murine cecal carcinoma. We detected 256 peaks from 164 samples of 111 patients, which consisted of 55 normal colorectal mucosal samples, 24 adenomas, 71 primary carcinomas, and 14 hepatic metastases. In addition, we detected 291 peptide/protein peaks from 34 orthotopically transplanted murine cecal carcinomas and 14 hepatic metastases. In human colorectal samples, we observed that proteomic profiling in adenomas was more homogeneous across patients than in normal mucosa specimens (p=0.0008), but primary carcinoma exhibited greater heterogeneity than normal mucosa and adenomas (both p0.0001). Murine cecal carcinomas were homogeneous within and between carcinomas, while their hepatic metastases tended toward greater intra-tumor differences (p0.0001). Inter- and intra-case variability was approximately equal for many protein peaks. Acquiring up to 5 subsamples per case could reduce the total number of cases required, but further reduction from additional subsampling was modest unless intra-case variability comprises a greater proportion of total variation (e.g. >70%). In summary, this study characterizes intra- and inter-case variability of high-throughput protein expression in colorectal tumors, and provides guidance for the sample numbers required for in situ proteomic studies.