Skip to main content
Top
Published in: BMC Cancer 1/2018

Open Access 01-12-2018 | Technical advance

Diagnostic accuracy and prediction increment of markers of epithelial-mesenchymal transition to assess cancer cell detachment from primary tumors

Authors: Evan L. Busch, Prabhani Kuruppumullage Don, Haitao Chu, David B. Richardson, Temitope O. Keku, David A. Eberhard, Christy L. Avery, Robert S. Sandler

Published in: BMC Cancer | Issue 1/2018

Login to get access

Abstract

Background

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.

Methods

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.

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.

Conclusions

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.
Appendix
Available only for authorised users
Literature
1.
go back to reference Weinberg RA. The biology of cancer. New York: garland. Science. 2007; Weinberg RA. The biology of cancer. New York: garland. Science. 2007;
2.
go back to reference Young PE, Womeldorph CM, Johnson EK, Maykel JA, Brucher B, Stojadinovic A, Avital I, Nissan A, Steele SR. Early detection of colorectal cancer recurrence in patients undergoing surgery with curative intent: current status and challenges. J Cancer. 2014;5(4):262–71.CrossRefPubMedPubMedCentral Young PE, Womeldorph CM, Johnson EK, Maykel JA, Brucher B, Stojadinovic A, Avital I, Nissan A, Steele SR. Early detection of colorectal cancer recurrence in patients undergoing surgery with curative intent: current status and challenges. J Cancer. 2014;5(4):262–71.CrossRefPubMedPubMedCentral
3.
go back to reference 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, 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
5.
go back to reference Bellovin DI, Bates RC, Muzikansky A, Rimm DL, Mercurio AM. Altered localization of p120 catenin during epithelial to mesenchymal transition of colon carcinoma is prognostic for aggressive disease. Cancer Res. 2005;65(23):10938–45.CrossRefPubMed Bellovin DI, Bates RC, Muzikansky A, Rimm DL, Mercurio AM. Altered localization of p120 catenin during epithelial to mesenchymal transition of colon carcinoma is prognostic for aggressive disease. Cancer Res. 2005;65(23):10938–45.CrossRefPubMed
6.
go back to reference 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 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
7.
go back to reference Fujikawa H, Tanaka K, Toiyama Y, Saigusa S, Inoue Y, Uchida K, Kusunoki M. High TrkB expression levels are associated with poor prognosis and EMT induction in colorectal cancer cells. J Gastroenterol. 2012;47(7):775–84.CrossRefPubMed Fujikawa H, Tanaka K, Toiyama Y, Saigusa S, Inoue Y, Uchida K, Kusunoki M. High TrkB expression levels are associated with poor prognosis and EMT induction in colorectal cancer cells. J Gastroenterol. 2012;47(7):775–84.CrossRefPubMed
8.
go back to reference He X, Chen Z, Jia M, Zhao X. Downregulated E-Cadherin expression indicates worse prognosis in Asian patients with colorectal cancer: evidence from meta-analysis. PLoS One. 2013;8(7):e70858.CrossRefPubMedPubMedCentral He X, Chen Z, Jia M, Zhao X. Downregulated E-Cadherin expression indicates worse prognosis in Asian patients with colorectal cancer: evidence from meta-analysis. PLoS One. 2013;8(7):e70858.CrossRefPubMedPubMedCentral
9.
go back to reference Shioiri M, Shida T, Koda K, Oda K, Seike K, Nishimura M, Takano S, Miyazaki M. Slug expression is an independent prognostic parameter for poor survival in colorectal carcinoma patients. Br J Cancer. 2006;94(12):1816–22.CrossRefPubMedPubMedCentral Shioiri M, Shida T, Koda K, Oda K, Seike K, Nishimura M, Takano S, Miyazaki M. Slug expression is an independent prognostic parameter for poor survival in colorectal carcinoma patients. Br J Cancer. 2006;94(12):1816–22.CrossRefPubMedPubMedCentral
10.
go back to reference Yun JA, Kim SH, Hong HK, Yun SH, Kim HC, Chun HK, Cho YB, Lee WY. Loss of E-Cadherin expression is associated with a poor prognosis in stage III colorectal cancer. Oncology. 2014;86(5–6):318–28.CrossRefPubMed Yun JA, Kim SH, Hong HK, Yun SH, Kim HC, Chun HK, Cho YB, Lee WY. Loss of E-Cadherin expression is associated with a poor prognosis in stage III colorectal cancer. Oncology. 2014;86(5–6):318–28.CrossRefPubMed
11.
go back to reference Collins J, Huynh M. Estimation of diagnostic test accuracy without full verification: a review of latent class methods. Stat Med. 2014;33(24):4141–69.CrossRefPubMedPubMedCentral Collins J, Huynh M. Estimation of diagnostic test accuracy without full verification: a review of latent class methods. Stat Med. 2014;33(24):4141–69.CrossRefPubMedPubMedCentral
12.
go back to reference Collins LM, Lanza ST. Latent class and latent transition analysis: with applications in the social, behavioral, and health sciences. Hoboken, New Jersey: Wiley; 2010. Collins LM, Lanza ST. Latent class and latent transition analysis: with applications in the social, behavioral, and health sciences. Hoboken, New Jersey: Wiley; 2010.
13.
go back to reference Gaffikin L, McGrath JA, Arbyn M, Blumenthal PD. Visual inspection with acetic acid as a cervical cancer test: accuracy validated using latent class analysis. BMC Med Res Methodol. 2007;7:36.CrossRefPubMedPubMedCentral Gaffikin L, McGrath JA, Arbyn M, Blumenthal PD. Visual inspection with acetic acid as a cervical cancer test: accuracy validated using latent class analysis. BMC Med Res Methodol. 2007;7:36.CrossRefPubMedPubMedCentral
14.
go back to reference Cook NR, Buring JE, Ridker PM. The effect of including C-reactive protein in cardiovascular risk prediction models for women. Ann Intern Med. 2006;145(1):21–9.CrossRefPubMed Cook NR, Buring JE, Ridker PM. The effect of including C-reactive protein in cardiovascular risk prediction models for women. Ann Intern Med. 2006;145(1):21–9.CrossRefPubMed
15.
go back to reference Cook NR, Ridker PM. Advances in measuring the effect of individual predictors of cardiovascular risk: the role of reclassification measures. Ann Intern Med. 2009;150(11):795–802.CrossRefPubMedPubMedCentral Cook NR, Ridker PM. Advances in measuring the effect of individual predictors of cardiovascular risk: the role of reclassification measures. Ann Intern Med. 2009;150(11):795–802.CrossRefPubMedPubMedCentral
16.
17.
go back to reference 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 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
18.
go back to reference Kang M, Shen XJ, Kim S, Araujo-Perez F, Galanko JA, Martin CF, Sandler RS, Keku TO. Somatic gene mutations in African Americans may predict worse outcomes in colorectal cancer. Cancer biomarkers : section A of Disease markers. 2013;13(5):359–66.CrossRefPubMedCentral Kang M, Shen XJ, Kim S, Araujo-Perez F, Galanko JA, Martin CF, Sandler RS, Keku TO. Somatic gene mutations in African Americans may predict worse outcomes in colorectal cancer. Cancer biomarkers : section A of Disease markers. 2013;13(5):359–66.CrossRefPubMedCentral
19.
go back to reference 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 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
20.
go back to reference Zhang J, Cole SR, Richardson DB, Chu H, Bayesian A. Approach to strengthen inference for case-control studies with multiple error-prone exposure assessments. Stat Med. 2013;32(25):4426–37.CrossRefPubMedPubMedCentral Zhang J, Cole SR, Richardson DB, Chu H, Bayesian A. Approach to strengthen inference for case-control studies with multiple error-prone exposure assessments. Stat Med. 2013;32(25):4426–37.CrossRefPubMedPubMedCentral
21.
go back to reference Pencina MJ, D'Agostino RB Sr, D'Agostino RB Jr, Vasan RS. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med. 2008;27(2):157–72. discussion 207-112CrossRefPubMed Pencina MJ, D'Agostino RB Sr, D'Agostino RB Jr, Vasan RS. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med. 2008;27(2):157–72. discussion 207-112CrossRefPubMed
22.
go back to reference 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 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
25.
go back to reference Rothman KJ, Greenland S, Lash TL. Modern Epidemiology. Third ed. Philadelphia: Wolters Kluwer, Lippincott Williams & Wilkins; 2008. Rothman KJ, Greenland S, Lash TL. Modern Epidemiology. Third ed. Philadelphia: Wolters Kluwer, Lippincott Williams & Wilkins; 2008.
26.
go back to reference Pepe MS, Janes H, Longton G, Leisenring W, Newcomb P. Limitations of the odds ratio in gauging the performance of a diagnostic, prognostic, or screening marker. Am J Epidemiol. 2004;159(9):882–90.CrossRefPubMed Pepe MS, Janes H, Longton G, Leisenring W, Newcomb P. Limitations of the odds ratio in gauging the performance of a diagnostic, prognostic, or screening marker. Am J Epidemiol. 2004;159(9):882–90.CrossRefPubMed
27.
go back to reference Cook NR. Use and misuse of the receiver operating characteristic curve in risk prediction. Circulation. 2007;115(7):928–35.CrossRefPubMed Cook NR. Use and misuse of the receiver operating characteristic curve in risk prediction. Circulation. 2007;115(7):928–35.CrossRefPubMed
28.
go back to reference 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 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
Metadata
Title
Diagnostic accuracy and prediction increment of markers of epithelial-mesenchymal transition to assess cancer cell detachment from primary tumors
Authors
Evan L. Busch
Prabhani Kuruppumullage Don
Haitao Chu
David B. Richardson
Temitope O. Keku
David A. Eberhard
Christy L. Avery
Robert S. Sandler
Publication date
01-12-2018
Publisher
BioMed Central
Published in
BMC Cancer / Issue 1/2018
Electronic ISSN: 1471-2407
DOI
https://doi.org/10.1186/s12885-017-3964-3

Other articles of this Issue 1/2018

BMC Cancer 1/2018 Go to the issue
Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras
Prof. Fabrice Barlesi
Developed by: Springer Medicine