The online version of this article (https://doi.org/10.1186/s12885-017-3964-3) contains supplementary material, which is available to authorized users.
Metastases play a role in about 90% of cancer deaths. Markers of epithelial-mesenchymal transition (EMT) measured in primary tumor cancer cells might provide diagnostic information about the likelihood that cancer cells have detached from the primary tumor. Used together with established diagnostic tests of detachment—lymph node evaluation and radiologic imaging—EMT marker measurements might improve the ability of clinicians to assess the patient’s risk of metastatic disease. Translation of EMT markers to clinical use has been hampered by a lack of valid analyses of clinically-informative parameters. Here, we demonstrate a rigorous approach to estimating the sensitivity, specificity, and prediction increment of an EMT marker to assess cancer cell detachment from primary tumors.
We illustrate the approach using immunohistochemical measurements of the EMT marker E-cadherin in a set of colorectal primary tumors from a population-based prospective cohort in North Carolina. Bayesian latent class analysis was used to estimate sensitivity and specificity in a setting of multiple imperfect diagnostic tests and no gold standard. Risk reclassification analysis was used to assess the extent to which addition of the marker to the panel of established diagnostic tests would improve mortality prediction. We explored how changing the latent class conditional dependence assumptions and definition of marker positivity would impact the results.
All diagnostic accuracy and prediction increment statistics varied with the choice of cut point to define marker positivity. When comparing different definitions of marker positivity to each other, numerous trade-offs were observed in terms of sensitivity, specificity, predictive discrimination, and prediction model calibration. We then discussed several implementation considerations and the plausibility of analytic assumptions.
The approaches presented here can be extended to any EMT marker, to most forms of cancer, and to different kinds of EMT marker measurements, such as RNA or gene methylation data. These methods provide valid, clinically-informative assessment of whether and how to use a given EMT marker to refine tumor staging and consequent treatment decisions.
Additional file 1: This file has 2 sections providing details about the following: 1) the rationale for the Bayesian priors used for the lymph node evaluation and radiologic imaging diagnostic tests in the latent class analysis of diagnostic accuracy, and 2) sample WinBUGS code for Bayesian latent class estimation of EMT marker sensitivity and specificity. (PDF 779 kb)12885_2017_3964_MOESM1_ESM.pdf
Additional file 2: This file provides 4 risk stratification tables (Tables S1-S4) showing classification of subject risk for all-cause mortality based on a model with predictors of lymph node evaluation and radiologic imaging compared to classification based on a model with predictors of lymph node evaluation, radiologic imaging, and E-cadherin measurements in primary tumor cancer cells. Each of the 4 tables is for a different form of the E-cadherin variable (continuous on a scale of 0–3 or dichotomized at 0.52, 0.60, or 0.85). The file also provides several figures: 1) images of high and low E-cadherin immunohistochemistry staining in tumor tissue specimens (Additional file 2: Figure S1), and 2) graphical comparisons of predicted probabilities based only on established diagnostic tests to predicted probabilities based on E-cadherin added to established diagnostic tests (Additional file 2: Figures S2-S5). (PDF 479 kb)
Weinberg RA. The biology of cancer. New York: garland. Science. 2007;
Busch EL, McGraw KA, Sandler RS. The potential for markers of epithelial-mesenchymal transition to improve colorectal cancer outcomes: a systematic review. Cancer Epidemiol. Biomark. Prev. :Pub. Am. Assoc. Cancer Res. cosponsored Am. Soc. Prev. Oncology. 2014;23(7):1164–75. CrossRef
Busch EL, Keku TO, Richardson DB, Cohen SM, Eberhard DA, Avery CL, Sandler RS. Evaluating markers of epithelial-mesenchymal transition to identify cancer patients at risk for metastatic disease. Clinical & experimental metastasis. 2016;33(1):53–62. CrossRef
Collins LM, Lanza ST. Latent class and latent transition analysis: with applications in the social, behavioral, and health sciences. Hoboken, New Jersey: Wiley; 2010.
Ayanian JZ, Chrischilles EA, Fletcher RH, Fouad MN, Harrington DP, Kahn KL, Kiefe CI, Lipscomb J, Malin JL, Potosky AL, et al. Understanding cancer treatment and outcomes: the cancer care outcomes research and surveillance consortium. J. Clin. Oncol. Off. J. Am. Soc. Clin. Oncol. 2004;22(15):2992–6. CrossRef
Malin JL, Ko C, Ayanian JZ, Harrington D, Nerenz DR, Kahn KL, Ganther-Urmie J, Catalano PJ, Zaslavsky AM, Wallace RB, et al. Understanding cancer patients’ experience and outcomes: development and pilot study of the cancer care outcomes research and surveillance patient survey. Support. Care Cancer. 2006;14(8):837–48. CrossRefPubMed
Kerr KF, Wang Z, Janes H, McClelland RL, Psaty BM, Pepe MS. Net reclassification indices for evaluating risk prediction instruments: a critical review. Epidemiology (Cambridge, Mass). 2014;25(1):114–21. CrossRef
Cook NR. Division of Preventive Medicine Risk Prediction Modeling. http://ncook.bwh.harvard.edu. Accessed 3 Aug 2017.
SEER Stat Fact Sheets. Colon and Rectum Cancer. http://seer.cancer.gov/statfacts/html/colorect.html. Accessed 29 Aug 2016.
Rothman KJ, Greenland S, Lash TL. Modern Epidemiology. Third ed. Philadelphia: Wolters Kluwer, Lippincott Williams & Wilkins; 2008.
Busch EL, Crous-Bou M, Prescott J, Chen MM, Downing MJ, Rosner BA, Mutter GL, De Vivo I. Endometrial cancer risk factors, hormone receptors, and mortality prediction. Cancer Epidemiol. Biomarkers Prev.: Pub. Am Assoc. Cancer Res. cosponsored by the Am. Soc. Prev. Oncol. 2017;26(5):727–35. CrossRef
- Diagnostic accuracy and prediction increment of markers of epithelial-mesenchymal transition to assess cancer cell detachment from primary tumors
Evan L. Busch
Prabhani Kuruppumullage Don
David B. Richardson
Temitope O. Keku
David A. Eberhard
Christy L. Avery
Robert S. Sandler
- BioMed Central
Neu im Fachgebiet Onkologie
Mail Icon II