Why Your New Cancer Biomarker May Never Work: Recurrent Patterns and Remarkable Diversity in Biomarker Failures
ABSTRACT Less than 1% of published cancer biomarkers actually enter clinical practice. Although best practices for biomarker development are published, optimistic investigators may not appreciate the statistical near-certainty and diverse modes by which the other 99% (likely including your favorite new marker) do indeed fail. Here, patterns of failure were abstracted for classification from publications and an online database detailing marker failures. Failure patterns formed a hierarchical logical structure, or outline, of an emerging, deeply complex, and arguably fascinating science of biomarker failure. A new cancer biomarker under development is likely to have already encountered one or more of the following fatal features encountered by prior markers: lack of clinical significance, hidden structure in the source data, a technically inadequate assay, inappropriate statistical methods, unmanageable domination of the data by normal variation, implausibility, deficiencies in the studied population or in the investigator system, and its disproof or abandonment for cause by others. A greater recognition of the science of biomarker failure and its near-complete ubiquity is constructive and celebrates a seemingly perpetual richness of biologic, technical, and philosophical complexity, the full appreciation of which could improve the management of scarce research resources. Cancer Res; 72(23); 1-5. ©2012 AACR.
SourceAvailable from: Angela Re[Show abstract] [Hide abstract]
ABSTRACT: Cancer results from dysregulation of multiple steps of gene expression programs. We review how transcriptome profiling has been widely explored for cancer classification and biomarker discovery but resulted in limited clinical impact. Therefore, we discuss alternative and complementary omics approaches. © The Author 2015. Published by Oxford University Press.Briefings in Bioinformatics 03/2015; DOI:10.1093/bib/bbv013 · 5.92 Impact Factor
[Show abstract] [Hide abstract]
ABSTRACT: MicroRNAs regulate gene expression at the post-transcriptional level. Differential expression of miRNAs can potentially be used as biomarkers for early diagnosis and prediction for outcomes. Failure in validation of miRNA profiles is often caused by variations in experimental parameters. In this study, the performance of five extraction kits and three RT-qPCR systems were evaluated using BioMark high-throughput platform and the effects of different experimental parameters on circulating miRNA levels were determined. Differences in the performance of extraction kits as well as varying accuracy, sensitivity and reproducibility in qPCR systems were observed. Normalisation of RT-qPCR data to spike-in controls can reduce extraction bias. However, the extent of correlation for different qPCR systems varies in different assays. At different time points, there was no significant fold change in eight of the plasma miRNAs that we evaluated. Higher level of miRNAs was detected in plasma as compared to serum of the same cohort. In summary, we demonstrated that high-throughput RT-qPCR with pre-amplification step had increased sensitivity and can be achieved with accuracy and high reproducibility through stringent experimental controls. The information provided here is useful for planning biomarker validation studies involving circulating miRNAs.Scientific Reports 03/2015; 5. DOI:10.1038/srep09430 · 5.08 Impact Factor
[Show abstract] [Hide abstract]
ABSTRACT: Earlier detection of cancers can dramatically improve the efficacy of available treatment strategies. However, despite decades of effort on blood-based biomarker cancer detection, many promising endogenous biomarkers have failed clinically because of intractable problems such as highly variable background expression from nonmalignant tissues and tumor heterogeneity. In this work we present a tumor-detection strategy based on systemic administration of tumor-activatable minicircles that use the pan-tumor-specific Survivin promoter to drive expression of a secretable reporter that is detectable in the blood nearly exclusively in tumor-bearing subjects. After systemic administration we demonstrate a robust ability to differentiate mice bearing human melanoma metastases from tumor-free subjects for up to 2 wk simply by measuring blood reporter levels. Cumulative change in reporter levels also identified tumor-bearing subjects, and a receiver operator-characteristic curve analysis highlighted this test's performance with an area of 0.918 ± 0.084. Lung tumor burden additionally correlated (r(2) = 0.714; P < 0.05) with cumulative reporter levels, indicating that determination of disease extent was possible. Continued development of our system could improve tumor detectability dramatically because of the temporally controlled, high reporter expression in tumors and nearly zero background from healthy tissues. Our strategy's highly modular nature also allows it to be iteratively optimized over time to improve the test's sensitivity and specificity. We envision this system could be used first in patients at high risk for tumor recurrence, followed by screening high-risk populations before tumor diagnosis, and, if proven safe and effective, eventually may have potential as a powerful cancer-screening tool for the general population.Proceedings of the National Academy of Sciences 02/2015; 112(10). DOI:10.1073/pnas.1414156112 · 9.81 Impact Factor